ECTS Information Package for Academic Year 2016/2017

Transcription

University of Zagreb
Faculty of Electrical Engineering and Computing
Unska 3, HR-10000 Zagreb
ECTS Information Package
for Academic Year
2016/2017
Course Catalogue – Undergraduate Study
Accepted by the Council of the Faculty of Electrical Engineering and Computing
on April 20th 2016
ECT S Information Package
for Academic Year
2016/2017
Accepted by the Council of the Faculty of Electrical Engineering and Computing
on April 20th 2016
PUBLISHED BY
Univ ersity of Zagreb
Faculty of Electrical Engineering and Computing
Unska 3, HR-10000 Zagreb
www.fer.unizg.hr
FOR T HE PUBLISHER
Prof. dr. sc. Mislav Grgić,
Dean
EDIT OR
Izv . prof. dr. sc. Marko Delimar,
Vice Dean
DESIGN AND PREPRESS
Vlatka Paunović, dipl. ing.
mr. sc. Siniša T omić
LECT ORS
Prof. dr. sc. Nina Skorin-Kapov
Doc. dr. sc. Jan Šnajder
PHOT OS
Goran Baotić, univ . bacc. ing. comp.
Izv . prof. dr. sc. Gordan Gledec
dr. sc. Ana Sović
Personal collections
ISSN: 1848-3569
UDK: 378.4
Table of Contents
Study Programs
Electrical Engineering and Information Technology (180 ECTS)
Module Control Engineering and Automation
Module Electrical Power Engineering
Module Electronic and Computer Engineering
Module Electronics
Module Wireless Technologies
Computing (180 ECTS)
Module Information Processing
Module Software Engineering and Information Systems
Module Computer Engineering
Module Computer Science
Module Telecommunication and Informatics
Courses
Advanced LabVIEW
Advanced Use of Linux Operating System
Alarm Systems
Algorithms and Data Structures
Application development using C# programming language
Applied Electromagnetics
App Start Contest
Artificial Intelligence
Audio and Computers
Audiotechnics
Automatic Control
Automation Practicum
Basics of Sound Recording and Processing
Basic Use of Linux Operating System
BSc Thesis
BSc Thesis
BSc Thesis
BSc Thesis
BSc Thesis
BSc Thesis
BSc Thesis
BSc Thesis
BSc Thesis
BSc Thesis
Chess
Commercial Law
Communication Networks
Competitive Programming
Computer Aided Design of Electronic Systems
Computer Architecture 1
Computer-Controlled Systems
Computer-Telephony Integration
University of Zagreb F aculty of Electrical Engineering and Computing
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101
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110
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Computing Methods of Modern Physics
Control System Elements
Databases
Design Patterns in Software Design
Development of Software Applications
Digital Logic
Digital Video
DisCont mathematics 1
Economics and Managerial Decision Making
Electrical Actuators
Electrical Circuits
Electrical Machines Control Practicum
Electric F acilities
Electric F acilities Design
Electroacoustics
Electromagnetic F ields
Electromagnetic Transients and Electromagnetic Compatibility
Electromechanical and Electrical Conversion
Electromechanical Systems
Electromechanics
Electronic Communications
Electronic Equipment Design
Electronics 1
Electronics 2
Embedded Systems
Energy Efficiency Audit and Energy Management Programme
Energy Technology
F undamentals of Electrical Drives
F undamentals of Electrical Engineering
F undamentals of Electronic Measurements and Instrumentation
F undamentals of Intelligent Control Systems
F undamentals of Mechatronics
Human F actors in Computing
Information, Logic and Languages
Information Processing
Information Theory
Interactive Computer Graphics
Introduction Into F ault F inding
Introduction to Java Programming Language
Introduction to Pattern Recognition
Introduction to physics
Introduction to R programming language
Introduction to Theoretical Computer Science
Introduction to the Scala programming language
Introduction to Virtual Environments
Laboratory and Skills – Maths on the Computer
Laboratory and Skills – Matlab
LabVIEW
Local Area Networks
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Low-voltage Power Systems
Management in Engineering
Mathematical Modeling of Computer
Mathematics 1
Mathematics 2
Mathematics 3 – C
Mathematics 3 – EE
Methods of Measurement
Metrology F undamentals
Mobile Communications
Modern Methods of Physics for Electrical Engineering and Information Technology
Modern Physics and Applications in Electrical Engineering
Multimedia Services
Multimedia Technologies
Network Programming
Object-oriented programming
Open Computing
Operating Systems
Optical Communication Technology
PHP Application Development Basics
Physical Education 1
Physics 1
Physics 2
Power Electronics Practicum
Power Plants
Probability and Statistics
Process Measurements and Diagnostic in Power Plants
Programing for the Robot Operating System
Programming and Software Engineering
Programming in Haskell
Programming Language Translation
Programming Paradigms and Languages
Project
Project
Project
Project
Project
Public Mobile Network
Quality Management
Radio Navigation
Robotics Practicum
Scripting Languages
Seminar
Seminar
Service and Application Development for Operating System Android
Signals and Systems
Skills of Communication
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5
Software Design
Software Design Project
Solving Optimization Problems Using Evolutionary Computation Algorithms in Java
Sound and Environment
Statistical Data Analysis
Sustainable Development and Environment
Technical Standardization and Legislative
Technology in Medicine
Telecommunication Systems and Networks
Transmission and Distribution of Electric Power
Transmission of Audio
Xamarin.F orms – cross-platform native mobile apps development
Lecturers
Andrea Aglić-Aljinović
Ana Anušić
Barbara Arbanas
Ana Babić
Dubravko Babić
Jurica Babić
Josip Bačmaga
Petar Bakić
Niko Bako
Vedrana Baličević
Željko Ban
Mato Baotić
Mirta Baranović
Adrijan Barić
Tin Bariša
Danko Basch
Alen Bažant
Maja Bellotti
Sead Berberović
Tomislav Berić
Vedran Bilas
Lahorija Bistričić
Vitomir Blagojević
Bruno Blašković
Raul Blečić
Stjepan Bogdan
Nikola Bogunović
Dario Bojanjac
Marko Bosiljevac
Ivana Bosnić
Ivica Botički
Jelena Božek
Mario Brčić
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Karla Brkić
Ljiljana Brkić
Ilko Brnetić
Ivan Budišćak
Mario Bukal
Tomislav Burić
Tomislav Capuder
Stjepan Car
Željka Car
Mario Cifrek
Igor Cvišić
Nikola Čavlina
Igor Čavrak
Vladimir Čeperić
Marko Čupić
Josip Ćesić
Martin Dadić
Bojana Dalbelo-Bašić
Nenad Debrecin
Goran Delač
Marko Delimar
Šandor Dembitz
Petar Djerasimović
Ognjen Dobrijević
Mirjana Domazet-Lošo
Hrvoje Domitrović
Leon Dragić
Paulina Dučkić
Kosjenka Dumančić
Alen Duspara
Dominik Džaja
Matija Džanko
Hrvoje Džapo
Mladen Đalto
Ante Đerek
Marko Đurasević
Ivan Đurek
Neven Elezović
Igor Erceg
Siniša F ajt
Božidar F erek-Petrić
Kristina F erković
Luka F erković
Krešimir F ertalj
Ivan F ilković
Petar F ranček
Nikolina F rid
Luka F ućek
Ivica Gavranić
Vlado Glavinić
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7
Gordan Gledec
Marin Golub
Goran Grdenić
Marijana Greblički
Davor Grgić
Mislav Grgić
Sonja Grgić
Tomislav Grgić
Karlo Griparić
Stjepan Groš
Danijela Grozdanić
Sanja Grubeša
Marko Gulin
Tamara Hadjina
Zlatko Hanić
Juraj Havelka
Hrvoje Hegeduš
Daniel Hofman
Ninoslav Holjevac
Hana Horak
Marko Horvat
Lana Horvat Dmitrović
Silvio Hrabar
Tomislav Hrkać
Darko Huljenić
Luka Humski
Nikola Hure
Perica Ilak
Šandor Ileš
Damir Ilić
Željko Ilić
Saša Ilijić
Antun Ivanović
Krunoslav Ivešić
Danko Ivošević
Branimir Ivšić
Davor Jadrijević
Tomislav Jagušt
Domagoj Jakobović
Željko Jakopović
Kristian Jambrošić
Žarko Janić
Radomir Ječmenica
Leonardo Jelenković
Tino Jerčić
Branko Jeren
Dragan Jevtić
Gordan Ježić
Alan Jović
Marko Jurčević
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8
Darko Jurić
Dražen Jurišić
Zoran Kalafatić
Damir Kalpić
Mladen Karan
Nenad Katanić
Damjan Katušić
Josip Knezović
Petar Knežević
Tihomir Knežević
Edin Kočo
F etah Kolonić
Marko Koričić
Luka Korkut
Tomislav Kos
Zvonko Kostanjčar
Mario Kovač
Domagoj Kovačević
Marinko Kovačić
Zdenko Kovačić
Slavko Krajcar
Ivan Krešo
Miljenko Krhen
Sabina Krivec
Mario Krnić
Igor Krois
Ivica Kunšt
Mario Kušek
Martina Kutija
Igor Kuzle
Igor Lacković
Kruno Lenac
Ivan Leniček
Vinko Lešić
Sven Lončarić
Snježana Lubura
Željka Lučev Vasić
Marko Magerl
Ratko Magjarević
Krešimir Malarić
Roman Malarić
Zlatko Maljković
F ilip Mandić
Tvrtko Mandić
Marijo Maračić
Ljubo Marangunić
Darijan Marčetić
Ivan Marković
Nenad Markuš
Anita Martinčević
452
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9
Ante Marušić
Maja Matijašević
Mario Matijević
Krešimir Matković
Jadranko Matuško
Ivan Maurović
Igor Mekterović
Željka Mihajlović
Lenka Mihoković
Neven Mijat
Igor Mijić
Damjan Miklić
Miljenko Mikuc
Boris Milašinović
Siniša Miličić
Josipa Pina Milišić
Nikola Mišković
Danijel Mlinarić
Hrvoje Mlinarić
Borivoj Modlic
Vedran Mornar
Petar Mostarac
Ivan Mrčela
Damir Muha
Robert Nađ
Zoran Narančić
Ivana Nižetić Kosović
Andrej Novak
Leonard Novosel
Branimir Novoselnik
Matko Orsag
Predrag Pale
Hrvoje Pandžić
Igor Sunday Pandžić
Mervan Pašić
Mario Osvin Pavčević
Marko Pavelić
Armin Pavić
Ivica Pavić
Zvonimir Pavlić
Tomislav Pavlović
Nedjeljko Perić
Tomislav Petković
Antonio Petošić
Davor Petrinović
Ivan Petrović
Juraj Petrović
Tamara Petrović
Igor Piljić
Damir Pintar
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10
Sanda Pleslić
Ivana Podnar Žarko
Vedran Podobnik
Mirko Poljak
Siniša Popović
Pavle Prentašić
Tomislav Pribanić
Krešimir Pripužić
Ana Prlić
Marina Ptiček
Goran Radunović
Ivan Rajšl
Mirko Randić
Maja Resman
Slobodan Ribarić
Dubravko Sabolić
Denis Salopek
Marija Seder
Damir Seršić
Igor Sirotić
Zoran Skočir
Lea Skorin-Kapov
Ivan Slivar
Martin Soldić
Ana Sović Kržić
Siniša Srbljić
Vlado Sruk
Antonio Starčić
Mario Stipčić
Stjepan Stipetić
Marko Subašić
Mia Suhanek
Tomislav Suligoj
Damir Sumina
Siniša Šadek
Stjepan Šebek
Siniša Šegvić
Goran Šeketa
Mile Šikić
Tomislav Šikić
Marin Šilić
Dina Šimunić
Zvonimir Šipuš
Gordan Šišul
F rano Škopljanac-Mačina
Dejan Škvorc
Jan Šnajder
Željko Štih
Hrvoje Štimac
Darko Štriga
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Matija Šulc
Viktor Šunde
Saša Tepić
Sejid Tešnjak
F rano Tomašević
Tomislav Tomiša
Željko Tomšić
Dijana Tralić
Bojan Trkulja
Krešimir Trontl
Martin Tutek
Ivo Uglešić
Darko Vasić
Goran Vasiljević
Mario Vašak
Igor Velčić
Klemo Vladimir
Domagoj Vlah
Mihaela Vranić
Mario Vražić
Boris Vrdoljak
Mladen Vučić
Zoran Vukić
Josip Vuković
Marin Vuković
Damir Vuljaj
Slaven Zakošek
Davor Zaluški
Marko Zec
Mario Žagar
Damir Žarko
Ana Žgaljić Keko
Josip Žilak
Sanja Žonja
Darko Žubrinić
Sara Žulj
Tomislav Župan
Vesna Županović
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Study Programs
13
Electrical Engineering and Information Technology (180
ECTS)
Qualification awarded: Bachelor of Science in Electrical Engineering and Information Technology
(univ.bacc.ing.el.techn.inf.)
1st semester, 1st year
E/C
6
E/C
7
E/C
1
E/C
7
E/C
0
E/C
6
E/C
ECTS
3
E/C
ECTS
3
Required courses
Digital Logic (19674)
Glavinić, V.; Mikuc, M.; Kalafatić, Z.
F undamentals of Electrical Engineering (86494)
Berberović, S.; Skočir, Z.; Knežević, P.; Pavić, A.; Blašković, B.; Dembitz, Š.;
Randić, M.; Dadić, M.; Trkulja, B.; Pintar, D.
Laboratory and Skills - Maths on the Computer (91611)
Pašić, M.
Mathematics 1 (86475)
Žubrinić, D.; Brnetić, I.; Milišić, J.; Velčić, I.; Horvat Dmitrović, L.; Žgaljić Keko,
A.
Physical Education 1 (21013)
Blagojević, V.
Programming and Software Engineering (19676)
Mornar, V.; Gledec, G.; Zakošek, S.
Skills of Communication (19678)
Pale, P.
Bridge Course
=> Number of ECTS credits to select: at least 0.0
Introduction to physics (137274)
Pleslić, S.
Eng.
Lev.
L1
Study
Sem.
Hours
75
1
(60+0+15)
L0
105
(90+0+15)
1
L0
15
(0+0+15)
1
L0
105
(90+15+0)
1
L3
L0
L1
Eng.
Lev.
L0
30
(0+0+30)
75
(60+0+15)
30
(30+0+0)
Study
Hours
30
(30+0+0)
1
1
1
Sem.
1
2nd semester, 1st year
E/C
6
E/C
6
E/C
2
E/C
3
E/C
7
E/C
0
E/C
ECTS
6
E/C
ECTS
6
Required courses
Algorithms and Data Structures (21008)
Mornar, V.; Botički, I.; Domazet-Lošo, M.
Computer Architecture 1 (21010)
Kovač, M.; Basch, D.
Laboratory and Skills - Matlab (104307)
Ban, Ž.; Baotić, M.; Matuško, J.
Management in Engineering (21012)
Štih, Ž.; Bilas, V.; Car, Ž.; Trkulja, B.; Pandžić, H.
Žubrinić, D.; Pašić, M.; Šikić, T.; Kovačević, D.; Horvat Dmitrović, L.; Žgaljić
Keko, A.
Blagojević, V.
Physics 1 (21006)
Petković, T.; Bistričić, L.; Narančić, Z.; Pleslić, S.; Ilijić, S.
Courses for exceptionally successful students
DisCont mathematics 1 (90094)
Elezović, N.
Eng.
Lev.
L1
L0
L1
L0
L0
L3
L1
Eng.
Lev.
L0
Study
Sem.
Hours
75
2
(60+0+15)
75
2
(60+0+15)
20
2
(8+0+12)
30
2
(30+0+0)
105
(90+15+0)
30
(0+0+30)
90
(75+0+15)
Study
Hours
60
(60+0+0)
2
2
2
Sem.
2, 4
14
3rd semester, 2nd year
EEIT
7
EEIT
5
EEIT
ECTS
0
EEIT
6
EEIT
ECTS
6
EEIT
4
EEIT
2
EEIT
1.5
EEIT
4
EEIT
2
EEIT
4
EEIT
2
EEIT
2
EEIT
4
EEIT
ECTS
4
Required courses
Electrical Circuits (31489)
Mijat, N.; Jurišić, D.; Lacković, I.; Kostanjčar, Z.
Mathematics 3 - EE (86477)
Županović, V.
Blagojević, V.
Elezović, N.
Electromechanics (90096)
Štih, Ž.; Berberović, S.; Ilijić, S.
Eng.
Lev.
L2
L0
L3
Eng.
Lev.
L0
L0
Study
Sem.
Hours
90
3
(75+0+15)
75
3
(60+15+0)
30
3
(0+0+30)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
3
3
Skills
Eng.
Study
Sem.
Lev.
Hours
Application development using C# programming language (132841)
45
L0
3
Botički, I.
(30+15+0)
Basics of Sound Recording and Processing (71794)
60
L0
3, 4
Domitrović, H.
(30+0+30)
Basic Use of Linux Operating System (86495)
15
L0
3
Groš, S.
(15+0+0)
Competitive Programming (65973)
60
L1
3
Đerek, A.
(30+0+30)
Introduction Into F ault F inding (70072) (currently not given)
60
L2
3
Jurčević, M.; Hegeduš, H.
(30+30+0)
Introduction to the Scala programming language (122825)
45
L0
3
Hrkać, T.
(30+0+15)
LabVIEW (69393)
60
L2
3
Malarić, R.; Havelka, J.
(30+0+30)
Programing for the Robot Operating System (127101)
18
L0
3
Miklić, D.
(9+0+9)
Programming in Haskell (127252)
45
L3
3
Šnajder, J.
(30+0+15)
Solving Optimization Problems Using Evolutionary Computation Algorithms
30
in Java (79087)
L0
3
(30+0+0)
Čupić, M.
4th semester, 2nd year
EEIT
4
EEIT
6
EEIT
6
EEIT
0
EEIT
Eng.
Lev.
5
Economics and Managerial Decision Making (41251)
Štih, Ž.; Tomšić, Ž.; Malarić, R.
Electromagnetic F ields (86459)
Berberović, S.; Štih, Ž.; Dadić, M.; Trkulja, B.
Energy Technology (86466)
Grgić, D.; Šadek, S.
Blagojević, V.
Probability and Statistics (86539)
Elezović, N.; Brnetić, I.; Aglić-Aljinović, A.; Krnić, M.; Velčić, I.; Burić, T.
EEIT
Required courses
3
Seminar (31498)
L3
EEIT
ECTS
6
Signals and Systems (31494)
Jeren, B.; Seršić, D.; Kostanjčar, Z.
L2
L1
L3
L1
L3
L0
Study
Sem.
Hours
45
4
(45+0+0)
90
4
(75+0+15)
75
4
(60+15+0)
30
4
(0+0+30)
75
4
(60+15+0)
30
4
(30+0+0)
75
4
(60+0+15)
15
EEIT
6
EEIT
ECTS
6
EEIT
2
EEIT
1.5
EEIT
4
EEIT
2
EEIT
2
EEIT
4
EEIT
3
EEIT
4
EEIT
ECTS
4
Elezović, N.
Modern Physics and Applications in Electrical Engineering (90097)
Bistričić, L.; Šipuš, Z.; Hrabar, S.
Eng.
Lev.
Skills
Advanced LabVIEW (86483)
Advanced Use of Linux Operating System (86484)
Groš, S.
App Start Contest (127248)
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Introduction to Java Programming Language (38047)
Čupić, M.
PHP Application Development Basics (58312)
Čupić, M.
Service and Application Development for Operating System Android (91617)
Kušek, M.; Pripužić, K.
Xamarin.F orms - cross-platform native mobile apps development (155582)
Pribanić, T.
Eng.
Lev.
L0
L0
L2
L0
L1
L0
L2
L0
L0
L0
L0
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
2, 4
4
Study
Sem.
Hours
60
4
(30+0+30)
15
4
(15+0+0)
75
4
(30+0+45)
60
3, 4
(30+0+30)
60
4
(30+0+30)
75
4
(60+0+15)
45
4
(30+0+15)
65
4
(26+0+39)
65
4
(26+0+39)
16
Module Control Engineering and Automation
5th semester, 3rd year
CEA
5
CEA
4
CEA
4
CEA
5
CEA
Eng.
Lev.
4
Automatic Control (34313)
Perić, N.; Vukić, Z.; Baotić, M.; Mišković, N.
Control System Elements (34296)
Kovačić, Z.; Bogdan, S.
Electromechanical Systems (86461)
Jakopović, Ž.; Kolonić, F .; Erceg, I.
Electronic Communications (83117)
Modlic, B.; Grgić, S.; Šišul, G.
Information Theory (34315)
Bažant, A.; Pandžić, I.; Ilić, Ž.; Vuković, M.
CEA
Required courses
6
Project (37832)
L3
CEA
ECTS
2
Sustainable Development and Environment (34275)
Čavlina, N.; Debrecin, N.
L0
CEA
6
CEA
ECTS
6
CEA
4
CEA
2
CEA
4
CEA
2
CEA
4
CEA
2
CEA
2
CEA
ECTS
4
L0
L2
L2
L0
L0
Elezović, N.
Eng.
Lev.
Skills
Botički, I.
Domitrović, H.
Đerek, A.
Hrkać, T.
LabVIEW (69393)
Miklić, D.
Šnajder, J.
Eng.
Lev.
L0
L0
L0
L0
L1
L2
L0
L2
L0
L3
Study
Sem.
Hours
75
5
(60+0+15)
60
5
(45+0+15)
60
5
(45+5+10)
75
5
(60+0+15)
60
5
(45+0+15)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Study
Sem.
Hours
45
5
(30+15+0)
60
5, 6
(30+0+30)
60
5
(30+0+30)
60
5
(30+30+0)
45
5
(30+0+15)
60
5
(30+0+30)
18
5
(9+0+9)
45
5
(30+0+15)
ECTS
Required courses
Eng.
Lev.
CEA
12
BSc Thesis (34317)
L3
CEA
2
CEA
4
Commercial Law (34294)
Horak, H.
Computer-Controlled Systems (34297)
Petrović, I.
L0
L1
Study
Sem.
Hours
0
6
(0+0+0)
30
6
(30+0+0)
60
6
(45+0+15)
17
CEA
4
CEA
4
CEA
4
CEA
4
CEA
4
CEA
4
CEA
4
CEA
4
CEA
4
CEA
ECTS
4
CEA
ECTS
6
CEA
2
CEA
1.5
CEA
4
CEA
2
CEA
2
CEA
4
CEA
3
CEA
4
CEA
ECTS
4
Elective Courses
Alarm Systems (34320)
Ban, Ž.
Automation Practicum (34344)
Vašak, M.
Electrical Actuators (86458) (currently not given)
Vražić, M.
Electrical Machines Control Practicum (86502)
Kolonić, F .; Sumina, D.
F undamentals of Intelligent Control Systems (34341)
Bogdan, S.; Kovačić, Z.
F undamentals of Mechatronics (34343)
Kolonić, F .; Matuško, J.
Metrology F undamentals (86536)
Ilić, D.; Malarić, R.
Power Electronics Practicum (34347)
Jakopović, Ž.; Šunde, V.
Robotics Practicum (34346)
Kovačić, Z.
Technology in Medicine (127185)
Magjarević, R.; Cifrek, M.; Lončarić, S.; Lacković, I.; Bilas, V.
Eng.
Lev.
Study
Hours
Sem.
L1
45
(30+0+15)
6
L1
L1
L1
L0
L1
L1
L1
L2
L1
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Pribanić, T.
Eng.
Lev.
L0
L2
L0
L1
L0
L2
L0
L0
L0
L0
45
(15+0+30)
45
(26+4+15)
47
(13+4+30)
45
(30+0+15)
45
(30+0+15)
45
(27+3+15)
45
(15+0+30)
45
(15+0+30)
45
(30+0+15)
Study
Hours
60
(60+0+0)
6
6
6
6
6
6
6
6
6
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
45
6
(30+0+15)
65
6
(26+0+39)
65
6
(26+0+39)
18
Module Electrical Power Engineering
EPE
5
EPE
4
EPE
4
EPE
5
EPE
Eng.
Lev.
4
Electric F acilities (91833)
Krajcar, S.; Marušić, A.
Electromechanical and Electrical Conversion (127433)
Maljković, Z.; Šunde, V.; Vražić, M.; Žarko, D.
EPE
Required courses
6
Project (37831)
L3
EPE
ECTS
2
L0
EPE
6
EPE
ECTS
6
EPE
4
EPE
2
EPE
4
EPE
2
EPE
4
EPE
2
EPE
2
EPE
ECTS
4
L0
L1
L1
L0
L0
Elezović, N.
Eng.
Lev.
Skills
Botički, I.
Domitrović, H.
Đerek, A.
Hrkać, T.
LabVIEW (69393)
Miklić, D.
Šnajder, J.
Eng.
Lev.
L0
L0
L0
L0
L1
L2
L0
L2
L0
L3
Study
Sem.
Hours
75
5
(60+0+15)
90
5
(45+30+15)
80
5
(45+20+15)
75
5
(60+0+15)
60
5
(45+0+15)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Study
Sem.
Hours
45
5
(30+15+0)
60
5, 6
(30+0+30)
60
5
(30+0+30)
60
5
(30+30+0)
45
5
(30+0+15)
60
5
(30+0+30)
18
5
(9+0+9)
45
5
(30+0+15)
ECTS
Required courses
Eng.
Lev.
EPE
12
BSc Thesis (41423)
L3
EPE
2
EPE
4
Horak, H.
Transmission and Distribution of Electric Power (127563)
Pavić, I.; Delimar, M.
L0
L3
Study
Sem.
Hours
0
6
(0+0+0)
30
6
(30+0+0)
87
6
(45+30+12)
19
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
4
EPE
ECTS
4
EPE
ECTS
6
EPE
2
EPE
1.5
EPE
4
EPE
2
EPE
2
EPE
ECTS
4
Elective Courses
Computing Methods of Modern Physics (34351)
Babić, A.
Electrical Machines Control Practicum (86502)
Kolonić, F .; Sumina, D.
Electric F acilities Design (34350)
Marušić, A.; Havelka, J.
Electromagnetic Transients and Electromagnetic Compatibility (34348)
Uglešić, I.
Energy Efficiency Audit and Energy Management Programme (34333)
Tomšić, Ž.
F undamentals of Electrical Drives (91613)
Žarko, D.; Erceg, I.
F undamentals of Electronic Measurements and Instrumentation (86493)
Bilas, V.
F undamentals of Mechatronics (34343)
Kolonić, F .; Matuško, J.
Low-voltage Power Systems (35245)
Krajcar, S.
Mathematical Modeling of Computer (91612)
Pašić, M.
Methods of Measurement (34334)
Leniček, I.; F erković, L.
Modern Methods of Physics for Electrical Engineering and Information
Technology (34340)
Petković, T.
Power Electronics Practicum (34347)
Jakopović, Ž.; Šunde, V.
Power Plants (127413)
Tešnjak, S.; Grgić, D.; Kuzle, I.
Process Measurements and Diagnostic in Power Plants (35244) (currently not
given)
Tomiša, T.
Technical Standardization and Legislative (34355)
Šimunić, D.; Pavić, I.
Eng.
Lev.
Study
Hours
Sem.
L3
45
(30+0+15)
6
L1
L1
L1
L0
L1
L0
L1
L1
L2
L0
L1
L1
L1
L1
45
(45+0+0)
45
(15+0+30)
49
(30+15+4)
6
6
6
6
6
6
6
6
6
6
6
6
6
6
L1
30
(30+0+0)
6
L0
45
(45+0+0)
6
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Eng.
Lev.
47
(13+4+30)
45
(30+0+15)
45
(30+0+15)
45
(30+0+15)
45
(26+4+15)
75
(45+15+15)
45
(30+0+15)
30
(30+0+0)
45
(30+0+15)
45
(30+0+15)
45
(27+3+15)
L0
L2
L0
L1
L0
L2
L0
Study
Hours
60
(60+0+0)
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
20
EPE
3
4
EPE
EPE
ECTS
4
Skills
Čupić, M.
Pribanić, T.
Eng.
Lev.
Study
Hours
Sem.
L0
45
(30+0+15)
6
L0
L0
65
(26+0+39)
65
(26+0+39)
6
6
21
Module Electronic and Computer Engineering
ECE
5
ECE
5
ECE
4
ECE
4
ECE
Eng.
Lev.
4
Electronics 2 (34299)
Barić, A.; Krois, I.; Koričić, M.
Embedded Systems (86535)
Petrinović, D.; Vučić, M.; Mlinarić, H.
ECE
Required courses
6
Project (37833)
L3
ECE
ECTS
2
L0
ECE
6
ECE
ECTS
6
ECE
4
ECE
2
ECE
4
ECE
2
ECE
4
ECE
2
ECE
2
ECE
ECTS
4
L0
L0
L1
L0
L0
Elezović, N.
Eng.
Lev.
Skills
Botički, I.
Domitrović, H.
Đerek, A.
Hrkać, T.
LabVIEW (69393)
Miklić, D.
Šnajder, J.
Eng.
Lev.
L0
L0
L0
L0
L1
L2
L0
L2
L0
L3
Study
Sem.
Hours
75
5
(60+0+15)
75
5
(60+0+15)
60
5
(45+0+15)
63
5
(45+0+18)
60
5
(45+0+15)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Study
Sem.
Hours
45
5
(30+15+0)
60
5, 6
(30+0+30)
60
5
(30+0+30)
60
5
(30+30+0)
45
5
(30+0+15)
60
5
(30+0+30)
18
5
(9+0+9)
45
5
(30+0+15)
ECTS
Required courses
Eng.
Lev.
ECE
12
BSc Thesis (41424)
L3
ECE
2
ECE
4
Horak, H.
Bilas, V.
L0
L0
Study
Sem.
Hours
0
6
(0+0+0)
30
6
(30+0+0)
75
6
(45+15+15)
22
ECE
4
ECE
4
ECE
4
ECE
4
ECE
4
ECE
4
ECE
4
ECE
4
ECE
4
ECE
ECTS
4
ECE
ECTS
6
ECE
2
ECE
1.5
ECE
4
ECE
2
ECE
2
ECE
4
ECE
3
ECE
4
ECE
ECTS
4
Elective Courses
Computer Aided Design of Electronic Systems (34352)
Cifrek, M.; Džapo, H.
Petrović, I.
Electronic Equipment Design (34308)
Magjarević, R.; Lacković, I.; Džapo, H.
Information Processing (34278)
Lončarić, S.; Seršić, D.; Subašić, M.
Mobile Communications (34312)
Nađ, R.; Šišul, G.
Multimedia Technologies (86482)
Petrinović, D.; Grgić, S.; Knezović, J.
Scripting Languages (86526)
Kalafatić, Z.; Šegvić, S.
Statistical Data Analysis (155246)
Dalbelo-Bašić, B.; Kostanjčar, Z.; Šnajder, J.; Velčić, I.
Eng.
Lev.
Study
Hours
Sem.
L1
45
(30+0+15)
6
L1
L1
L1
L1
L1
L0
L1
L1
L1
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Pribanić, T.
Eng.
Lev.
L0
L2
L0
L1
L0
L2
L0
L0
L0
L0
60
(45+0+15)
60
(45+0+15)
60
(45+0+15)
45
(27+3+15)
60
(45+0+15)
60
(40+5+15)
45
(30+0+15)
60
(45+15+0)
45
(30+0+15)
Study
Hours
60
(60+0+0)
6
6
6
6
6
6
6
6
6
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
45
6
(30+0+15)
65
6
(26+0+39)
65
6
(26+0+39)
23
Module Electronics
EL
5
EL
5
EL
4
EL
Eng.
Lev.
4
EL
Required courses
6
Project (37834)
L3
EL
ECTS
2
L0
EL
4
EL
ECTS
4
EL
6
EL
ECTS
6
EL
4
EL
2
EL
4
EL
2
EL
4
EL
2
EL
2
EL
ECTS
4
L0
L0
L1
L0
Specialization courses
Applied Electromagnetics (86507)
Hrabar, S.
Electroacoustics (34303)
F ajt, S.; Domitrović, H.
Eng.
Lev.
Elezović, N.
Eng.
Lev.
Skills
Botički, I.
Domitrović, H.
Đerek, A.
Hrkać, T.
LabVIEW (69393)
Miklić, D.
Šnajder, J.
Eng.
Lev.
L2
L1
L0
L0
L0
L0
L1
L2
L0
L2
L0
L3
Study
Sem.
Hours
75
5
(60+0+15)
75
5
(60+0+15)
60
5
(45+0+15)
60
5
(45+0+15)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Sem.
Hours
69
5
(45+9+15)
60
5
(45+0+15)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Study
Sem.
Hours
45
5
(30+15+0)
60
5, 6
(30+0+30)
60
5
(30+0+30)
60
5
(30+30+0)
45
5
(30+0+15)
60
5
(30+0+30)
18
5
(9+0+9)
45
5
(30+0+15)
ECTS
Required courses
Eng.
Lev.
EL
12
BSc Thesis (41426)
L3
EL
2
Horak, H.
L0
Study
Hours
0
(0+0+0)
30
(30+0+0)
Sem.
6
6
24
EL
4
EL
ECTS
4
EL
4
EL
4
EL
4
EL
4
EL
4
EL
4
EL
4
EL
4
EL
4
EL
4
EL
ECTS
4
EL
ECTS
6
EL
2
EL
1.5
EL
4
EL
2
EL
2
EL
4
EL
3
EL
4
EL
ECTS
4
Audiotechnics (34309)
Đurek, I.
Electronic Equipment Design (34308)
Magjarević, R.; Lacković, I.; Džapo, H.
Eng.
Lev.
Elective Courses
Audio and Computers (91858)
F ajt, S.
Petrović, I.
Digital Video (34322)
Grgić, M.
Bilas, V.
Optical Communication Technology (91856)
Šipuš, Z.; Babić, D.
Sound and Environment (91857)
Jambrošić, K.
Transmission of Audio (91853)
Domitrović, H.
Eng.
Lev.
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Pribanić, T.
Eng.
Lev.
L1
L1
L1
L1
L1
L1
L0
L1
L1
L1
L1
L1
L1
L0
L2
L0
L1
L0
L2
L0
L0
L0
L0
Study
Sem.
Hours
60
6
(45+0+15)
60
6
(45+0+15)
Study
Sem.
Hours
51
6
(45+0+6)
45
6
(30+0+15)
60
6
(45+0+15)
45
6
(30+0+15)
75
6
(45+15+15)
45
6
(27+3+15)
60
6
(45+0+15)
45
6
(26+9+10)
51
6
(45+0+6)
45
6
(30+0+15)
69
6
(45+8+16)
Study
Hours
60
(60+0+0)
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
45
6
(30+0+15)
65
6
(26+0+39)
65
6
(26+0+39)
25
Module Wireless Technologies
WT
4
WT
5
WT
5
WT
4
WT
Eng.
Lev.
4
Applied Electromagnetics (86507)
Hrabar, S.
WT
Required courses
6
Project (37835)
L3
WT
ECTS
2
L0
WT
6
WT
ECTS
6
WT
4
WT
2
WT
4
WT
2
WT
4
WT
2
WT
2
WT
ECTS
4
L2
L0
L0
L1
L0
Elezović, N.
Eng.
Lev.
Skills
Botički, I.
Domitrović, H.
Đerek, A.
Hrkać, T.
LabVIEW (69393)
Miklić, D.
Šnajder, J.
Eng.
Lev.
L0
L0
L0
L0
L1
L2
L0
L2
L0
L3
Study
Sem.
Hours
69
5
(45+9+15)
75
5
(60+0+15)
75
5
(60+0+15)
60
5
(45+0+15)
60
5
(45+0+15)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Study
Sem.
Hours
45
5
(30+15+0)
60
5, 6
(30+0+30)
60
5
(30+0+30)
60
5
(30+30+0)
45
5
(30+0+15)
60
5
(30+0+30)
18
5
(9+0+9)
45
5
(30+0+15)
ECTS
Required courses
Eng.
Lev.
WT
12
BSc Thesis (41428)
L3
WT
2
WT
4
Horak, H.
L0
L1
Study
Sem.
Hours
0
6
(0+0+0)
30
6
(30+0+0)
60
6
(45+0+15)
26
WT
4
WT
4
WT
4
WT
4
WT
4
WT
4
WT
4
WT
4
WT
4
WT
ECTS
4
WT
ECTS
6
WT
2
WT
1.5
WT
4
WT
2
WT
2
WT
4
WT
3
WT
4
WT
ECTS
4
Elective Courses
Audiotechnics (34309)
Đurek, I.
Grgić, M.
Introduction to Virtual Environments (34345)
Pandžić, I.; Matković, K.
Pašić, M.
Optical Communication Technology (91856)
Šipuš, Z.; Babić, D.
Public Mobile Network (34330)
Ježić, G.; Kos, T.
Radio Navigation (34353)
Kos, T.
Technical Standardization and Legislative (34355)
Šimunić, D.; Pavić, I.
Eng.
Lev.
Study
Hours
Sem.
L1
60
(45+0+15)
6
L1
L0
L2
L1
L0
L1
L1
L1
L0
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Pribanić, T.
Eng.
Lev.
L0
L2
L0
L1
L0
L2
L0
L0
L0
L0
45
(30+0+15)
45
(30+0+15)
45
(30+0+15)
45
(27+3+15)
60
(40+5+15)
45
(26+9+10)
45
(30+0+15)
45
(30+0+15)
45
(45+0+0)
Study
Hours
60
(60+0+0)
6
6
6
6
6
6
6
6
6
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
45
6
(30+0+15)
65
6
(26+0+39)
65
6
(26+0+39)
27
Computing (180 ECTS)
Qualification awarded: Bachelor of Science in Computing
(univ.bacc.ing.comp.)
1st semester, 1st year
E/C
6
E/C
7
E/C
1
E/C
7
E/C
0
E/C
6
E/C
ECTS
3
E/C
ECTS
3
Required courses
Digital Logic (19674)
Glavinić, V.; Mikuc, M.; Kalafatić, Z.
F undamentals of Electrical Engineering (86494)
Berberović, S.; Skočir, Z.; Knežević, P.; Pavić, A.; Blašković, B.; Dembitz, Š.;
Randić, M.; Dadić, M.; Trkulja, B.; Pintar, D.
Laboratory and Skills - Maths on the Computer (91611)
Pašić, M.
Žubrinić, D.; Brnetić, I.; Milišić, J.; Velčić, I.; Horvat Dmitrović, L.; Žgaljić Keko,
A.
Blagojević, V.
Programming and Software Engineering (19676)
Mornar, V.; Gledec, G.; Zakošek, S.
Skills of Communication (19678)
Pale, P.
Bridge Course
Introduction to physics (137274)
Pleslić, S.
Eng.
Lev.
L1
Study
Sem.
Hours
75
1
(60+0+15)
L0
105
(90+0+15)
1
L0
15
(0+0+15)
1
L0
105
(90+15+0)
1
L3
L0
L1
Eng.
Lev.
L0
30
(0+0+30)
75
(60+0+15)
30
(30+0+0)
Study
Hours
30
(30+0+0)
1
1
1
Sem.
1
2nd semester, 1st year
E/C
6
E/C
6
E/C
2
E/C
3
E/C
7
E/C
0
E/C
ECTS
6
E/C
ECTS
6
Required courses
Algorithms and Data Structures (21008)
Mornar, V.; Botički, I.; Domazet-Lošo, M.
Kovač, M.; Basch, D.
Laboratory and Skills - Matlab (104307)
Ban, Ž.; Baotić, M.; Matuško, J.
Management in Engineering (21012)
Štih, Ž.; Bilas, V.; Car, Ž.; Trkulja, B.; Pandžić, H.
Žubrinić, D.; Pašić, M.; Šikić, T.; Kovačević, D.; Horvat Dmitrović, L.; Žgaljić
Keko, A.
Blagojević, V.
Physics 1 (21006)
Elezović, N.
Eng.
Lev.
L1
L0
L1
L0
L0
L3
L1
Eng.
Lev.
L0
Study
Sem.
Hours
75
2
(60+0+15)
75
2
(60+0+15)
20
2
(8+0+12)
30
2
(30+0+0)
105
(90+15+0)
30
(0+0+30)
90
(75+0+15)
Study
Hours
60
(60+0+0)
2
2
2
Sem.
2, 4
28
3rd semester, 2nd year
COM
5
COM COM COM
ECTS
5
7
0
COM
ECTS
7
COM
ECTS
6
COM
ECTS
3
COM COM
ECTS
6
6
COM
COM COM COM COM COM COM COM COM COM
ECTS
4
2
1.5
4
2
4
2
2
4
4
Required courses
Mathematics 3 - C (88206)
Pavčević, M.; Šikić, T.; Kovačević, D.
Object-oriented programming (127225)
Kušek, M.; Pripužić, K.; Botički, I.; Milašinović, B.; Čupić, M.
Operating Systems (31501)
Golub, M.; Jelenković, L.; Jakobović, D.
Blagojević, V.
Eng.
Lev.
Study
Hours
Sem.
L0
75
(60+15+0)
3
L1
L1
L3
Required courses - Electronics 1
Barić, A.; Suligoj, T.; Krois, I.; Koričić, M.; Čeperić, V.
Eng.
Lev.
Required courses - Physics 2
Physics 2 (31487)
Eng.
Lev.
Required courses - Quality Management
Quality Management (31490)
Ilić, D.; Malarić, R.; Leniček, I.; F erković, L.; Jurčević, M.
Eng.
Lev.
Elezović, N.
Eng.
Lev.
L2
L1
L2
L0
L0
75
(60+0+15)
90
(75+0+15)
30
(0+0+30)
3
3
3
Study
Sem.
Hours
105
3
(75+15+15)
Study
Sem.
Hours
90
3
(75+0+15)
Study
Hours
30
(30+0+0)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
3
Sem.
3
3
Skills
Eng.
Study
Sem.
Lev.
Hours
45
L0
3
Botički, I.
(30+15+0)
60
L0
3, 4
Domitrović, H.
(30+0+30)
15
L0
3
Groš, S.
(15+0+0)
60
L1
3
Đerek, A.
(30+0+30)
60
L2
3
(30+30+0)
45
L0
3
Hrkać, T.
(30+0+15)
LabVIEW (69393)
60
L2
3
(30+0+30)
18
L0
3
Miklić, D.
(9+0+9)
45
L3
3
Šnajder, J.
(30+0+15)
30
in Java (79087)
L0
3
(30+0+0)
Čupić, M.
29
4th semester, 2nd year
COM COM COM COM COM COM COM
ECTS
COM COM
Eng.
Lev.
5
Databases (31503)
Baranović, M.; Skočir, Z.; Zakošek, S.
Economics and Managerial Decision Making (41251)
Štih, Ž.; Tomšić, Ž.; Malarić, R.
Introduction to Theoretical Computer Science (86537)
Srbljić, S.; Kalafatić, Z.; Škvorc, D.; Đerek, A.
Blagojević, V.
Probability and Statistics (86539)
Elezović, N.; Brnetić, I.; Aglić-Aljinović, A.; Krnić, M.; Velčić, I.; Burić, T.
3
Seminar (31505)
L3
6
Signals and Systems (31494)
Jeren, B.; Seršić, D.; Kostanjčar, Z.
L2
6
4
6
0
ECTS
6
6
ECTS
COM COM COM COM COM COM COM COM COM
Required courses
2
1.5
4
2
2
4
3
4
4
L3
L1
L1
L3
L0
Elezović, N.
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Pribanić, T.
Eng.
Lev.
L0
L0
L2
L0
L1
L0
L2
L0
L0
L0
L0
Study
Sem.
Hours
75
4
(60+0+15)
45
4
(45+0+0)
75
4
(45+15+15)
30
4
(0+0+30)
75
4
(60+15+0)
30
4
(30+0+0)
75
4
(60+0+15)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
2, 4
4
Study
Sem.
Hours
60
4
(30+0+30)
15
4
(15+0+0)
75
4
(30+0+45)
60
3, 4
(30+0+30)
60
4
(30+0+30)
75
4
(60+0+15)
45
4
(30+0+15)
65
4
(26+0+39)
65
4
(26+0+39)
30
Module Information Processing
IP
4
IP
4
IP
Eng.
Lev.
8
Communication Networks (34272)
Jevtić, D.; Glavinić, V.; Matijašević, M.; Ježić, G.
Software Design (34269)
Sruk, V.
IP
Required courses
8
Software Design Project (36696)
L3
IP
ECTS
2
L0
IP
4
IP
ECTS
4
IP
6
IP
ECTS
6
IP
4
IP
2
IP
1.5
IP
4
IP
2
IP
4
IP
4
IP
2
IP
2
IP
4
IP
ECTS
4
L3
L0
L1
Ribarić, S.; Šegvić, S.; Hrkać, T.
Programming Language Translation (86504)
Srbljić, S.; Škvorc, D.; Đerek, A.
Eng.
Lev.
Elezović, N.
Eng.
Lev.
L1
L1
L0
L0
Study
Sem.
Hours
60
5
(45+0+15)
60
5
(45+0+15)
120
5
(60+0+60)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Sem.
Hours
60
5
(45+0+15)
75
5
(45+15+15)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Skills
Eng.
Study
Sem.
Lev.
Hours
45
L0
5
Botički, I.
(30+15+0)
60
L0
5, 6
Domitrović, H.
(30+0+30)
15
L0
5
Groš, S.
(15+0+0)
60
L1
5
Đerek, A.
(30+0+30)
60
L2
5
(30+30+0)
Introduction to R programming language (147661)
45
L0
5
Pintar, D.
(30+0+15)
45
L0
5
Hrkać, T.
(30+0+15)
LabVIEW (69393)
60
L2
5
(30+0+30)
18
L0
5
Miklić, D.
(9+0+9)
45
L3
5
Šnajder, J.
(30+0+15)
30
in Java (79087)
L0
5
(30+0+0)
Čupić, M.
31
L3
Horak, H.
Information Processing (34278)
Lončarić, S.; Seršić, D.; Subašić, M.
IP
BSc Thesis (41429)
12
IP
Eng.
Lev.
2
IP
Required courses
4
IP
ECTS
4
IP
4
IP
4
IP
4
IP
4
IP
4
IP
4
IP
4
IP
4
IP
4
IP
4
IP
4
IP
ECTS
4
IP
ECTS
6
IP
2
IP
1.5
IP
4
IP
2
IP
2
IP
ECTS
4
L0
L1
L0
Elective Courses
Development of Software Applications (34283)
F ertalj, K.
Grgić, M.
Interactive Computer Graphics (34287)
Mihajlović, Ž.
Introduction to Pattern Recognition (34358)
Ribarić, S.
Local Area Networks (34332)
Ilić, Ž.
Multimedia Services (34289)
Podnar Žarko, I.; Skorin-Kapov, L.; Dobrijević, O.
Transmission of Audio (91853)
Domitrović, H.
Eng.
Lev.
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Eng.
Lev.
L0
L1
L1
L1
L0
L1
L1
L1
L1
L1
L1
L1
L0
L2
L0
L1
L0
L2
L0
Study
Sem.
Hours
0
6
(0+0+0)
30
6
(30+0+0)
60
6
(45+0+15)
60
6
(40+5+15)
Study
Sem.
Hours
60
6
(45+0+15)
45
6
(30+0+15)
60
6
(45+0+15)
45
6
(45+0+0)
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+0+15)
60
6
(45+0+15)
45
6
(30+0+15)
60
6
(45+15+0)
45
6
(30+0+15)
69
6
(45+8+16)
Study
Hours
60
(60+0+0)
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
32
IP
3
IP
4
IP
ECTS
4
Skills
Čupić, M.
Pribanić, T.
Eng.
Lev.
Study
Hours
Sem.
L0
45
(30+0+15)
6
L0
L0
65
(26+0+39)
65
(26+0+39)
6
6
33
Module Software Engineering and Information Systems
S EIS
4
S EIS
4
S EIS
4
S EIS
Eng.
Lev.
8
Sruk, V.
S EIS
Required courses
8
L3
S EIS
ECTS
2
L0
S EIS
6
S EIS
ECTS
6
S EIS
4
S EIS
2
S EIS
1.5
S EIS
4
S EIS
2
S EIS
4
S EIS
4
S EIS
2
S EIS
2
S EIS
4
S EIS
ECTS
4
Elezović, N.
L3
L0
L1
L1
Eng.
Lev.
L0
L0
Study
Sem.
Hours
60
5
(45+0+15)
60
5
(45+0+15)
75
5
(45+15+15)
120
5
(60+0+60)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Skills
Eng.
Study
Sem.
Lev.
Hours
45
L0
5
Botički, I.
(30+15+0)
60
L0
5, 6
Domitrović, H.
(30+0+30)
15
L0
5
Groš, S.
(15+0+0)
60
L1
5
Đerek, A.
(30+0+30)
60
L2
5
(30+30+0)
45
L0
5
Pintar, D.
(30+0+15)
45
L0
5
Hrkać, T.
(30+0+15)
LabVIEW (69393)
60
L2
5
(30+0+30)
18
L0
5
Miklić, D.
(9+0+9)
45
L3
5
Šnajder, J.
(30+0+15)
30
in Java (79087)
L0
5
(30+0+0)
Čupić, M.
ECTS
Required courses
Eng.
Lev.
S EIS
12
BSc Thesis (41430)
L3
S EIS
2
Horak, H.
L0
Study
Hours
0
(0+0+0)
30
(30+0+0)
Sem.
6
6
34
S EIS
4
S EIS
ECTS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
4
S EIS
ECTS
4
S EIS
ECTS
6
S EIS
2
S EIS
1.5
S EIS
4
S EIS
2
S EIS
2
S EIS
ECTS
4
Required courses
F ertalj, K.
Programming Paradigms and Languages (34282)
Mornar, V.; Botički, I.
Eng.
Lev.
L0
L1
Elective Courses
Artificial Intelligence (34285)
Dalbelo-Bašić, B.; Šnajder, J.
Computing Methods of Modern Physics (34351)
Babić, A.
Design Patterns in Software Design (86487)
Šegvić, S.
Human F actors in Computing (34327)
Gledec, G.; Car, Ž.
Mihajlović, Ž.
Ribarić, S.
Modern Methods of Physics for Electrical Engineering and Information
Technology (34340)
Petković, T.
Network Programming (34335)
Mikuc, M.
Open Computing (34286)
Žagar, M.; Čavrak, I.
Eng.
Lev.
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Eng.
Lev.
L3
L3
L1
L1
L1
L1
L0
L1
L1
L0
L1
L1
L1
L0
L2
L0
L1
L0
L2
L0
Study
Hours
60
(45+0+15)
60
(45+0+15)
Sem.
6
6
Study
Sem.
Hours
60
6
(45+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+0+15)
45
6
(45+0+0)
45
6
(30+0+15)
45
(45+0+0)
45
(30+0+15)
60
(45+0+15)
45
(30+0+15)
60
(45+15+0)
45
(30+0+15)
Study
Hours
60
(60+0+0)
6
6
6
6
6
6
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
35
S EIS
3
S EIS
4
S EIS
ECTS
4
Skills
Čupić, M.
Pribanić, T.
Eng.
Lev.
Study
Hours
Sem.
L0
45
(30+0+15)
6
L0
L0
65
(26+0+39)
65
(26+0+39)
6
6
36
Module Computer Engineering
CE
4
CE
4
CE
4
CE
Eng.
Lev.
8
Sruk, V.
CE
Required courses
8
L3
CE
ECTS
2
L0
CE
6
CE
ECTS
6
CE
4
CE
2
CE
1.5
CE
4
CE
2
CE
4
CE
4
CE
2
CE
2
CE
4
CE
ECTS
4
Elezović, N.
L3
L1
L0
L1
Eng.
Lev.
L0
L0
Study
Sem.
Hours
60
5
(45+0+15)
60
5
(45+0+15)
60
5
(45+0+15)
120
5
(60+0+60)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Skills
Eng.
Study
Sem.
Lev.
Hours
45
L0
5
Botički, I.
(30+15+0)
60
L0
5, 6
Domitrović, H.
(30+0+30)
15
L0
5
Groš, S.
(15+0+0)
60
L1
5
Đerek, A.
(30+0+30)
60
L2
5
(30+30+0)
45
L0
5
Pintar, D.
(30+0+15)
45
L0
5
Hrkać, T.
(30+0+15)
LabVIEW (69393)
60
L2
5
(30+0+30)
18
L0
5
Miklić, D.
(9+0+9)
45
L3
5
Šnajder, J.
(30+0+15)
30
in Java (79087)
L0
5
(30+0+0)
Čupić, M.
ECTS
Required courses
Eng.
Lev.
CE
12
BSc Thesis (41431)
L3
CE
2
Horak, H.
L0
Study
Hours
0
(0+0+0)
30
(30+0+0)
Sem.
6
6
37
CE
4
CE
ECTS
4
CE
4
CE
4
CE
4
CE
4
CE
4
CE
4
CE
4
CE
4
CE
4
CE
4
CE
ECTS
4
CE
ECTS
6
CE
2
CE
1.5
CE
4
CE
2
CE
2
CE
4
CE
3
CE
ECTS
4
Required courses
Eng.
Lev.
L0
L0
Elective Courses
Šegvić, S.
F ertalj, K.
Bilas, V.
Ilić, Ž.
Mikuc, M.
Eng.
Lev.
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Eng.
Lev.
L1
L1
L0
L0
L0
L1
L1
L0
L1
L1
L1
L0
L2
L0
L1
L0
L2
L0
L0
L0
Study
Hours
63
(45+0+18)
60
(45+0+15)
Sem.
6
6
Study
Sem.
Hours
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+0+15)
75
6
(45+15+15)
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+0+15)
60
6
(40+5+15)
45
6
(30+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
Study
Hours
60
(60+0+0)
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
45
6
(30+0+15)
65
6
(26+0+39)
38
CE
ECTS
4
Skills
Pribanić, T.
Eng.
Lev.
Study
Hours
Sem.
L0
65
(26+0+39)
6
39
Module Computer Science
CS
4
CS
4
CS
Eng.
Lev.
8
Sruk, V.
CS
Required courses
8
L3
CS
ECTS
2
L0
CS
4
CS
ECTS
4
CS
6
CS
ECTS
6
CS
4
CS
2
CS
1.5
CS
4
CS
2
CS
4
CS
4
CS
2
CS
2
CS
4
CS
ECTS
4
L3
L0
L1
Eng.
Lev.
Elezović, N.
Eng.
Lev.
L1
L1
L0
L0
Study
Sem.
Hours
60
5
(45+0+15)
60
5
(45+0+15)
120
5
(60+0+60)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Sem.
Hours
60
5
(45+0+15)
75
5
(45+15+15)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Skills
Eng.
Study
Sem.
Lev.
Hours
45
L0
5
Botički, I.
(30+15+0)
60
L0
5, 6
Domitrović, H.
(30+0+30)
15
L0
5
Groš, S.
(15+0+0)
60
L1
5
Đerek, A.
(30+0+30)
60
L2
5
(30+30+0)
45
L0
5
Pintar, D.
(30+0+15)
45
L0
5
Hrkać, T.
(30+0+15)
LabVIEW (69393)
60
L2
5
(30+0+30)
18
L0
5
Miklić, D.
(9+0+9)
45
L3
5
Šnajder, J.
(30+0+15)
30
in Java (79087)
L0
5
(30+0+0)
Čupić, M.
40
CS
4
Artificial Intelligence (34285)
Dalbelo-Bašić, B.; Šnajder, J.
L3
CS
Eng.
Lev.
12
BSc Thesis (41432)
L3
CS
Required courses
2
CS
ECTS
4
Horak, H.
Mihajlović, Ž.
CS
4
CS
4
CS
4
CS
4
CS
4
CS
4
CS
4
CS
4
CS
4
CS
ECTS
4
CS
ECTS
6
CS
2
CS
1.5
CS
4
CS
2
CS
2
CS
4
CS
3
CS
ECTS
4
L0
L1
Elective Courses
Šegvić, S.
Information, Logic and Languages (34288)
Blašković, B.; Kušek, M.
Ribarić, S.
Mikuc, M.
Eng.
Lev.
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Eng.
Lev.
L1
L0
L1
L1
L0
L1
L1
L1
L1
L1
L0
L2
L0
L1
L0
L2
L0
L0
L0
Study
Sem.
Hours
60
6
(45+0+15)
0
6
(0+0+0)
30
6
(30+0+0)
60
6
(45+0+15)
Study
Sem.
Hours
45
6
(30+0+15)
63
6
(45+0+18)
60
6
(45+0+15)
45
6
(45+0+0)
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+15+0)
Study
Hours
60
(60+0+0)
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
60
6
(30+0+30)
75
6
(60+0+15)
45
6
(30+0+15)
65
6
(26+0+39)
41
CS
ECTS
4
Skills
Pribanić, T.
Eng.
Lev.
Study
Hours
Sem.
L0
65
(26+0+39)
6
42
Module Telecommunication and Informatics
TI
4
TI
4
TI
Eng.
Lev.
8
Sruk, V.
TI
Required courses
8
L3
TI
ECTS
2
L0
TI
4
TI
ECTS
4
TI
6
TI
ECTS
6
TI
4
TI
2
TI
1.5
TI
4
TI
2
TI
4
TI
4
TI
2
TI
2
TI
4
TI
ECTS
4
L3
L0
L1
Eng.
Lev.
Elezović, N.
Eng.
Lev.
L1
L1
L0
L0
Study
Sem.
Hours
60
5
(45+0+15)
60
5
(45+0+15)
120
5
(60+0+60)
0
5
(0+0+0)
30
5
(30+0+0)
Study
Sem.
Hours
60
5
(45+0+15)
75
5
(45+15+15)
Study
Hours
60
(60+0+0)
60
(60+0+0)
Sem.
5
5
Skills
Eng.
Study
Sem.
Lev.
Hours
45
L0
5
Botički, I.
(30+15+0)
60
L0
5, 6
Domitrović, H.
(30+0+30)
15
L0
5
Groš, S.
(15+0+0)
60
L1
5
Đerek, A.
(30+0+30)
60
L2
5
(30+30+0)
45
L0
5
Pintar, D.
(30+0+15)
45
L0
5
Hrkać, T.
(30+0+15)
LabVIEW (69393)
60
L2
5
(30+0+30)
18
L0
5
Miklić, D.
(9+0+9)
45
L3
5
Šnajder, J.
(30+0+15)
30
in Java (79087)
L0
5
(30+0+0)
Čupić, M.
43
ECTS
Required courses
Eng.
Lev.
TI
12
BSc Thesis (41433)
L3
TI
2
TI
4
Horak, H.
Information, Logic and Languages (34288)
Blašković, B.; Kušek, M.
TI
4
TI
ECTS
4
TI
4
TI
4
TI
4
TI
4
TI
4
TI
4
TI
4
TI
4
TI
4
TI
4
TI
4
TI
ECTS
4
TI
ECTS
6
TI
2
TI
1.5
TI
4
TI
ECTS
2
L0
L1
Multimedia Services (34289)
Podnar Žarko, I.; Skorin-Kapov, L.; Dobrijević, O.
Telecommunication Systems and Networks (34290)
Jevtić, D.
Eng.
Lev.
Elective Courses
Computer-Telephony Integration (34328)
Jevtić, D.
Human F actors in Computing (34327)
Gledec, G.; Car, Ž.
Ilić, Ž.
Pašić, M.
Mikuc, M.
Eng.
Lev.
Eng.
Lev.
Skills
Groš, S.
Podobnik, V.
Domitrović, H.
Eng.
Lev.
L1
L1
L1
L1
L0
L1
L2
L1
L0
L1
L1
L1
L1
L1
L0
L2
L0
L1
L0
Study
Sem.
Hours
0
6
(0+0+0)
30
6
(30+0+0)
60
6
(45+0+15)
Study
Sem.
Hours
60
6
(45+0+15)
60
6
(45+0+15)
Study
Sem.
Hours
45
6
(30+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+0+15)
60
6
(45+0+15)
45
6
(30+0+15)
45
6
(30+0+15)
60
6
(45+15+0)
45
6
(30+0+15)
Study
Hours
60
(60+0+0)
Sem.
6
Study
Sem.
Hours
60
6
(30+0+30)
15
6
(15+0+0)
75
6
(30+0+45)
60
5, 6
(30+0+30)
44
TI
2
TI
4
TI
3
TI
4
TI
ECTS
4
Skills
Chess (69392)
Malarić, K.
Čupić, M.
Čupić, M.
Pribanić, T.
Eng.
Lev.
Study
Hours
Sem.
L2
60
(30+0+30)
6
L0
L0
L0
L0
75
(60+0+15)
45
(30+0+15)
65
(26+0+39)
65
(26+0+39)
6
6
6
6
45
Courses
46
Course Description
LabVIEW isa graphical programming environment for measurment,
automatization and visualisation. It is used as a development tool for applications
in measuremewnt and instrumentation, data acquisition (DAQ), analysis and
process management. This course will cover advanced techniques of programming,
design of stand alone applications, application optimization, data handling, and
input/output functions.
L2
E-learning Level
L1
Study Hours
Lecturers
Laboratory exercises
30
30
T eaching Assistants
Doc. dr. sc. Hrvoje Hegeduš
Doc. dr. sc. Marko Jurčević
Dr. sc. Hrvoje Hegeduš
Dr. sc. Petar Mostarac
EEIT
English Level
C OM
Doc. dr. sc.
Juraj Havelka
2
C EA
Prof. dr. sc.
Roman Malarić
ECT S Credits
Grading
This is a pass/fail course.
Minimal number of points
required for pass is: 50%
EL
Learning Outcomes
EP E
Lecturers in Charge
E/C
86483
Advanced LabVIEW
EC E
IP
Apply skills for LabVIEW DSC module programming
Apply skills for LabVIEW RT module rogramming
Produce SCADA systems
Create software for Real-Time controllers
Explain and use OPC servers
Design Modbus protocol server
Design control loops
SEIS
1.
2.
3.
4.
5.
6.
7.
WT
On successful completion of the course, students will be able to:
CE
General Competencies
CS
The basic knowledge of Labview programming, data acquisition from connected
instruments to computers. SCADA programmming. Communication with
programmible logic controllers using various protocols.
TI
F orms of Teaching
» Lectures
» Lectures
» Laboratory Work
» Examples
» Experiments
» Work with LabVIEw
» Experimental Exercises
» During lectures
47
Grading System
Continuous Assessment
T ype
T hreshold
Percent of
Grade
0%
0%
0%
30 %
30 %
40 %
Laboratory Exercises
Mid Term Exam: Written
F inal Exam: Written
Exam: Written
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
100 %
Week by Week Schedule
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
DSC module basics
I/O serves 1.
I/O serveri 2.
Shared variables
User interface
Evente and alarm servers
Citadel database (SQL) basics
Citadel database (SQL) advanced
SCADA system security
RT module basics
Hardware configuration
Real-Time architecture
Comunication
Deploying application
Scada system demo
Literature
M. L. Chungani,A. R.
Samant,M. Cerna (1998).
LabVIEW Signal Processing,
PTR PH
R. Bitter, T. Mohiuddin, M.
Nawrocki (2006). LabVIEW
Digital Signal Processing: and
Digital Communications;C.
Clark;McGraw Hill;2005,
CRC Press
C. Clark (2005). LabVIEW
Digital Communications,
McGraw Hill
J. Essick (1989). Advanced
LabVIEW Labs, PTR PH
L. Sokoloff (2004).
Applications in LabVIEW,
Pearson PH
Similar Courses
» LabVIEW course, Chalmers University
» Engineering Tool IV: Programming with LabView, ETH Zurich
» ME220 Lab #1 Introduction to LabView Environment and Signals in the,
Stanford
48
L0
E-learning Level
L1
Study Hours
Lecturers
15
Grading
Doc. dr. sc.
Stjepan Groš
Course Description
The goal of this skill is to teach students with advanced features of Linux
operating system that will allow them to install and maintain/administer their
own systems.
Learning Outcomes
Skill doesn't have grades, it
only counts if student passed
or not.
Prerequisites
Basic Use of Linux Operating
System
EEIT
English Level
C OM
1.5
C EA
ECT S Credits
EP E
Lecturer in Charge
E/C
86484
Advanced Use of Linux Operating System
EC E
WT
Distinguish basic parts of a hardware and their relationsip
Apply knowledge to create and maintain partitions and file systems
Apply knowledge to manage RAID and LVM systems
Apply knowledge to install custom linux kernel
Apply knowledge to manage system services
Apply knowledge to manage packages
IP
1.
2.
3.
4.
5.
6.
EL
SEIS
CE
The goal of this skill is to teach students with advanced features of Linux
operating system that will allow them to install and maintain/administer their
own systems.
CS
F orms of Teaching
» Lectures
» Lectures with live examples.
TI
» Exams
» Quizzes during lectures.
Grading System
T ype
Homeworks
Quizzes
Class participation
Seminar/Project
Attendance
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
30 %
30 %
5%
30 %
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
49
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Introduction
Hardware and hardware architecture.
Hardware and hardware architecture.
RAID, LVM and qutoas.
RAID, LVM and qutoas.
Compiling Linux kernel, modules and patches.
Compiling Linux kernel, modules and patches.
Managing services and jobs scheduling.
Managing services and jobs scheduling.
Packages.
Packages.
Maintaining system.
Maintaining system.
Installing Linux system.
Installing Linux system.
Literature
Garrels, Machtelt (2004).
Bash guide for begginers,
F ultus
Hubert, Bert Linux advanced
routing and traffic control
Žagar, Mario (2006). UNIX i
kako ga koristiti, 7. digitalno
(XML) izdanje, F ER, Zagreb
Barret, Daniel (2001). Secure
shell: The definitive guide,
O'Reilly
50
Survey of the sources and classes of the risks. Risk degree estimation. Protection
classification and management. Anti burglar alarm systems. Access control. Alarm
installations design principles. Role of the intern television and protective
illumination. F ire alarm systems and other risk state detection. S-equipment.
Norms and regulations.
Study Programmes
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
T eaching Assistant
Dr. sc. Tomislav Pavlović
EEIT
English Level
50
62.5
75
87.5
Prerequisites
Laboratory and Skills Matlab
C EA
Course Description
4
EP E
Prof. dr. sc.
Željko Ban
ECT S Credits
EC E
Lecturer in Charge
E/C
34320
Alarm Systems
EL
WT
» Control Engineering and Automation -> Electrical Engineering and
Information Technology (Module) (elective courses, 6th semester, 3rd year)
Learning Outcomes
CE
SEIS
Describe the procedure of the alarm system design
Identify the elements of anti burglar and fire alarm system
Explain the principles of alarm system functioning
Use the elements of the anti burglar system
Analyze the protection system
Model the protection system by the diagram
Design the ant burglary system
Estimate the numerical vulnerability assessment of the facility
CS
1.
2.
3.
4.
5.
6.
7.
8.
IP
TI
Good understanding of the sources and classes of the risks. Basic knowledge of the
norms and regulations in the security area. Good understanding of the alarm
design and installation principles for the anti burglar alarm systems, fire alarm
systems and the access control systems. Practical skills to implement alarm
system.
F orms of Teaching
» Lectures
» Two hours lecture per week
» Exams
» Laboratory exercises test
Midterm exam
F inal exam in written form
51
Oral final exam
» Laboratory Work
» Laboratory exercises consist of 5 exercises. Each exercise is worth 3
points for the laboratory work and writen report from laboratory
exercise.
» Consultations
» After each lecture
» Internship visits
» Excursion to company for design and instalation of the alarm
systems
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
50 %
50 %
50 %
50 %
Percent of
Grade
15 %
15 %
25 %
25 %
20 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
5%
5%
50 %
40 %
50 %
Comment:
It is necessary to complete all laboratory exercises and homework for taking the
final exam
1. Topics overview, literature, undertaking of teaching and exams.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Sources and classification of the risks
Qualitative assesment of vulnerability to intrusion
Numerical estimate of adversary sequence interruption
Classification and management of the protection
Anti burglar alarm systems
External sensors of the anti burglar alarm systems
Internal sensors of the anti burglar alarm systems
Video supervision.
Midterm exam.
Access control systems
F ire alarm systems. Smoke and fire detectors.
Vulnerability analysis of the protection system using methods based on
ASD diagrams
Alarm and surveillance centers.
Explosion protection systems and Ex equipment
Norms and regulations
F inal exam
52
Literature
L. F ennelly (2004).
Handbook of Loss Prevention
and crime Prevention L. J.
Fennelly Butterworth, Boston
198 9, Elsevier Inc
J. Cieszynski (2007). The
principles and Practice of
Closed Circuit Television H.
Constant, P. Turnbull
Paramount Publ. Ltd.
Hertfordshire 1994, Elsevier
M. L. Garcia (2008). The
Design and Evaluation of
Physical Protection systems,
Butterworth-Heinemann
Jane I. Lataille (2003). Fire
Protection Engineering in
Building Design (Plant
Engineering), Elsevier
Science
Thomas Norman (2007).
Integrated security system
design, ButterworthHeinemann
53
Study Programmes
» Electrical Engineering and Information Technology and Computing (Study)
(required course, 2nd semester, 1st year)
Learning Outcomes
1. Describe the usage of various data structures
2. Recognize the complexity of operations and algorithms
3. Apply appropriate data structures and algorithms in solving real-life
problems
4. Develop computer programs to implement appropriate data structures
and algorithms
5. Assess the complexity of algorithms and computer programs
6. Identify appropriate data structures and algorithms in solving real-life
problems
Students will be able to design and program algorithms over advanced data
structures, using the basics of the object-oriented program paradigm in C.
Study Hours
Lecturers
60
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
66
80
90
Prerequisites
Programming and Software
Engineering
Prerequisites for
Interactive Computer
Graphics
Object-oriented
programming
Operating Systems
Scripting Languages
F orms of Teaching
» Lectures
» Semester is organized in two cycles in totally 15 weeks, which
accounts for two weeks for intermediate exams. There are four
hours of lectures per week, divided in two terms of two hours (2+2).
» Exams
EC E
Dr. sc. Mario Brčić
Ivan Budišćak, dipl. ing.
Petar Djerasimović, dipl. ing.
Antun Ivanović, mag. ing.
Marina Ptiček, mag. ing.
EP E
C EA
C OM
Lecturers
Prof. dr. sc. Damir Kalpić
Izv. prof. dr. sc. Tomislav
Pribanić
Izv. prof. dr. sc. Mile Šikić
Doc. dr. sc. Hrvoje Džapo
EEIT
L1
EL
Building on the knowledge obtained in Programming and software engineering,
basic data structures and algorithms are introduced. After the topic of dynamic
memory allocation, function calling mechanism is presented. Computational
complexity of algorithms is introduced. Search methods are presented, followed
by recursion. Algorithms for sorting are explained and illustrated. Dynamic data
structures are introduced: singly and multiply linked lists. Basic data structures,
stack and queue, are presented followed by hashing, binary trees, and heap. Heap
sort illustrates priority queue application.
E-learning Level
WT
Course Description
L1
IP
Doc. dr. sc.
Mirjana DomazetLošo
English Level
SEIS
Doc. dr. sc.
Ivica Botički
6
CE
Prof. dr. sc.
Vedran Mornar
ECT S Credits
CS
Lecturers in Charge
E/C
21008
Algorithms and Data Structures
TI
54
» There are two exams: midterm exam and final exam.
» Laboratory Work
» Two to three cycles of laboratory exercises.
Grading System
T ype
Exam: Written
T hreshold
Percent of
Grade
0%
40 %
50 %
30 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
30 %
50 %
70 %
Comment:
On midterm and final exams students are required to gather the sum of at least 35
points.
1. Introduction. Review of basic programming and data structures. Memory
allocation.
2. F unction call mechanisms. Definition of algorithm. Complexity of
algorithms.
3. Searching: sequential, jump-search, binary search.
4. Recursion.
5. Recursion examples, exercises.
6. Sorting algorithms: selection sort, bubble sort, insertion sort, Shell sort,
mergesort, quicksort.
7. Linear list. Multiple linear lists.
8. Mid-term exam.
9. Mid-term exam.
10. Stack. Queue.
11. Hashing.
12. Hashing examples.
13. Introduction to graphs. Trees.
14. Heap.
15. Heap sort.
55
Literature
R. Sedgewick (2001).
Algorithms in C:
Fundamentals, Data
Structures, Sorting,
Searching and Graph
Algorithms in C, Addison
Wesley
Thomas H. Cormen, Charles
E. Leiserson, Ronald L.
Rivest, Clifford Stein (2009).
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not for sale in the US or
Canada. Look Inside Index
Preface Sample Chapter
Essential Info Table of
Contents Supplemental
Content Author Errata Page
Khan Academy Course
Instructor Resources Digital
Exam/Desk Copy Print
Exam/Desk Copy Ancillary
Material Introduction to
Algorithms, Third Edition,
MIT Press
Additional Literature
Adam Drozdek (2000). Data
Structures and Algorithms in
C++, Course Technology
M. A. Weiss (1996). Data
Structures and Algorithm
Analysis in C (2nd Edition),
Addison Wesley
Similar Courses
» Introduction to Algorithms, MIT
» Data Structures and Algorithms, Cambridge
» Data Structures and Algorithms, IEEE & ACM Computing Curricula
» Algoritmi e strutture dei dati, Aalto University
56
ECT S Credits
4
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
Exercises
30
15
EEIT
Lecturer in Charge
132841
C EA
Doc. dr. sc.
Ivica Botički
EP E
Course Description
WT
EL
EC E
The goal of this course is to introduce students to the world of modern software
development using C# programming language. Students will be familiarized with
the world of applications starting form application types and core programming
fundamentals. The first part will focus on storage and fetching of data with the
emphasis on the specifics of Microsoft technologies. The second part is devoted for
development of backend part of the application through web services and
complementing technologies (AJAX, SignalR, Web API etc.). The third part of the
course will be focused on implementation of client part of the application
(frontend) working with various client technologies (HTML, JavaScript and
XAML). The last part is reserved for hosting of server part of the application and
new cloud computing paradigm.
IP
Study Programmes
TI
CS
CE
SEIS
» Electrical Engineering and Information Technology -> Electrical Engineering
and Information Technology and Computing (Study) (skills, 3rd semester, 2nd
year)
» Computing -> Electrical Engineering and Information Technology and
Computing (Study) (skills, 3rd semester, 2nd year)
» Control Engineering and Automation -> Electrical Engineering and Information
Technology (Module) (skills, 5th semester, 3rd year)
» Electrical Power Engineering -> Electrical Engineering and Information
» Electronic and Computer Engineering -> Electrical Engineering and
Information Technology (Module) (skills, 5th semester, 3rd year)
» Electronics -> Electrical Engineering and Information Technology (Module)
(skills, 5th semester, 3rd year)
» Wireless Technologies -> Electrical Engineering and Information Technology
(Module) (skills, 5th semester, 3rd year)
» Information Processing -> Computing (Module) (skills, 5th semester, 3rd year)
» Software Engineering and Information Systems -> Computing (Module) (skills,
5th semester, 3rd year)
» Computer Engineering -> Computing (Module) (skills, 5th semester, 3rd year)
» Computer Science -> Computing (Module) (skills, 5th semester, 3rd year)
» Telecommunication and Informatics -> Computing (Module) (skills, 5th semester,
3rd year)
E/C
Application development using C# programming
language
C OM
57
Learning Outcomes
1. Apply C# programming language and related technologies in designing
simple programs
server-side applications
client applications
web services
cloud applications
6. Prepare applications for deployment
F orms of Teaching
» Lectures
» Lectures
» Programming Exercises
» Project implementation
Grading System
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
1. Applications types and programming fundamentals
2. Supporting software development lifecycle and program development
models in Microsoft tools (e.g. TF S and SCRUM)
3. The specifics of object-oriented programming in C#. Generics. Delegates.
Events. Lambda expressions. Other advanced elements of C#.
4. The application of database fundamentals and SQL language to using SQL
Server. The overview of inovations in new SQL Server versions. Stored
procedured and functions in SQL Server.
5. ORM - object-relations mapping in Microsoft tehnologies. LINQ.
6. WCF services and REST services. Client and service communication (Ajax,
SignalR, Web API)
7. Midterm
8. Midterm
9. User experience design. The basics of HTML and CSS. Introduction to
JavaScript and JQuery.
10. Web development with ASP.NET fundamentals
11. XAML fundamentals (WCF and Windows Phone)
12. Security and user authentication in applications.
13. Application hosting and Cloud Computing
14. F inals
15. F inals
58
John Sharp (2014). Microsoft
Visual C# 2013 Step by Step,
Microsoft Press
Andrew Troelsen (2012). Pro
C# 5.0 and the .NET 4.5
Framework, APress
Similar Courses
» E-Commerce Technologies, Carnegie Mellon University
59
The curse deals with the basic phenomena associated with time-varying
electromagnetic fields. The radiation and propagation of the electromagnetic
waves in unbounded media and along the guiding structures are analyzed
mathematically together with clear physical interpretation. The experimental
demonstration of all analyzed phenomena with examples of practical applications
in various engineering systems such as communications, electronics and computers
are given.
E-learning Level
L1
Study Hours
Lecturers
Exercises
45
9
15
Dr. sc. Damir Muha
Dr. sc. Davor Zaluški
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
L2
C OM
English Level
C EA
Course Description
4
50
60
80
90
Prerequisites
EP E
Prof. dr. sc.
Silvio Hrabar
ECT S Credits
EC E
Lecturer in Charge
E/C
86507
EL
Study Programmes
IP
WT
(specialization courses, 5th semester, 3rd year)
(Module) (required course, 5th semester, 3rd year)
SEIS
Learning Outcomes
TI
CS
CE
1. Explain physical background of propagation of EM waves in free space, in
unbounded loss-free and lossy dielectric as well as the propagation along
guiding structures
2. Explain physical background of Maxwell equations in integral and
differential forms, vector wave equation and associated solutions for
travelling wave, standing wave and evanescent wave
3. Explain physical background of radiation of EM wave, elemental electric
dipole and a simple antenna array with two radiators
4. Calculate basic parameters (a characteristic impedance and propagation
constant) of simple guiding structures: TEM transmission line, dielectric
slab and rectangular waveguide
5. Calculate all the parameters needed for matching of an arbitrary load to the
generator using one-stub matching circuit
6. Calculate the EM field distribution in the case of propagation of EM wave
that impinge onto dielectric half-space or multi-layer dielectric from the
free space, at normal and oblique incidence
7. Identify components for radiation and propagation of EM waves in
practical engineering systems in communications in electronics and explain
associated background physics
60
Clear and deep understanding the basic physical phenomena associated with
radiation and propagation of the electromagnetic waves together with
appropriate mathematical analysis. After completed course the students are
expected to be able to understand basic principles of various engineering systems
that make use of time-varying electromagnetic fields (wireless communication
systems, optical communication systems, radio frequency and microwave
electronic systems, high-speed digital systems). It is also expected that students
will develop the competence to solve a broad range of practical problems in these
systems.
F orms of Teaching
» Lectures
» Theoretical background of each unit is given in the lectures. This is
complemented by in-front-of-class experiments and computer
situations that explain physics of particular phenomenon.
» Exams
» Short conceptual problems and numerical problems.
» Exercises
» Numerical examples of realistic engineering electromagentic
problems are solved in details.
» Laboratory Work
» Three blocks of laboratory exercises. Each exercise is run as a group
work of four students.
» Experiments
» There are 10 in-front-of-class experiments that cover whole
syllabus. Each experiment is recorded by camera and projected on
the screen. Therefore, each student is able to follow the experiment.
Each experiment is also complemented by computer simulation,
which enables further discussion and analysis.
» Consultations
» There are weekly scheduled consultations with a professor and a
teaching
assistant. F or some special problems, the group
consultations are also organized occasionally
Grading System
T ype
Homeworks
Quizzes
Class participation
Attendance
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
0%
0%
0%
Percent of
Grade
10 %
5%
3%
3%
1%
10 %
18 %
50 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
10 %
5%
3%
3%
1%
0%
28 %
50 %
61
1. Introduction – The importance of electromagnetics in engineering. Brief
review of applications of time-varying electromagnetic fields in different
engineering systems such as communications, electronics and computers.
Distributed parameters, general transmission line equation and its
solutions.
2. Distributed parameters, general transmission line equation and its
solutions. Physical interpretation of transmission line equations: reflection,
a standing wave, matching. Analogy between propagation of the
electromagnetic wave along a transmission line and propagation in
homogenous dielectric.
3. Smith chart. Practical problem of matching of an antenna to transmitter or
a receiver. Laboratory exercises - Part I - Propagation of EM waves along
TEM transmission line and matching
4. Maxwell equations, wave equation. The basic solutions of vector wave
equation. Physical interpretation of the solutions: traveling plane wave, an
evanescent wave, a standing wave.
5. Group velocity, flux of electromagnetic energy, Poynting vector. Plane
wave propagation in infinite homogenous media. Lossless and lossy case.
6. Normal incidence of a plane wave on a homogenous dielectric half space
including multilayer problem. Lossless and lossy case.
7. Oblique incidence of a plane wave on a homogenous dielectric half space
including multilayer problem. Lossless and lossy case. Laboratory exercises
- Part II - Basic properties of EM wave in free-space
8. Midterm exam
9. Propagation of electromagnetic wave along a general uniform guiding
structure. Parallel-plate waveguide
10. Rectangular waveguide, TE and TM modes of propagation.
11. Circular waveguide, electromagnetic resonators.
12. Propagation in dielectric slab, dielectric waveguide.
13. Introduction to radiation, magnetic vector potential, elemental Hertz
dipole
14. Basic antenna parameters, radiation pattern, radiation resistance,
directivity and gain. A simple linear (wire) antenna. The concept of antenna
array. A simple antenna array comprising two radiators. Laboratory
exercises Part III- Waveguides and radiation of EM waves
15. F inal exam
Literature
Z. Smrkić (1986).
Mikrovalna elektronika,
Školska Knjiga
Staelin, Morgenthaler,
Kong (1994). Electromagnetic
Waves, Prentice Hall
C.Balanis (1989). Advanced
Engineering Electromagnetics,
John Willey
F . Ulaby Fundamentals of
Applied Electromagentics
Similar Courses
» Electromagnetics and Applications, MIT
» Electromagnetics, MIT
» Electromagnetic Waves, UCLA
62
Doc. dr. sc.
Vedran Podobnik
ECT S Credits
4
English Level
L1
E-learning Level
L2
Study Hours
Lecturers
30
45
T eaching Assistant
Darko Štriga, mag. ing.
EEIT
Lecturer in Charge
E/C
127248
App Start Contest
C OM
IP
WT
The educational component of the course consists of workshops on technical issues
and lectures on economic themes related to launching business projects based on
mobile and web technologies. The practical component of the course is organized
as a competition between teams, where teams of students develop their original
business ideas, implement them as mobile and/or web applications and compare
in a competitive manner with the solutions of their fellow students.
Learning Outcomes
SEIS
TI
CS
CE
1. Apply a techno-economic knowledge needed to develop applications for
popular mobile and web platforms
2. Plan a life cycle of mobile and web applications
3. Distinguish mobile and web technologies
4. Develop creative and innovative mobile and web applications
5. Demonstrate sense of entrepreneurship in the mobile and web technology
sector
6. Develop knowledge and skills needed to work in a team
Students through the course gain the following techno-economic competencies
needed to develop mobile and applications:
i) ability to manage the project life-cycle by using agile methodologies;
ii) basic knowledge of mobile and web technologies;
iii) ability to develop mobile applications for popular mobile platforms (iOS,
Android, WP8) with an advanced knowledge of the platform selected for the
project;
iv) ability to turn one’s idea from concept into a innovative mobile and/or web
application;
v) ability to develop a business model for a project;
vi) ability to work in a small to mid-sized team.
EP E
Student success in skills is not
rated on insufficient (1) excellent (5) scale. Students
can pass or fail the skill.
EC E
The course is designed to offer students an opportunity to acquire a technoeconomic knowledge needed to develop applications for popular mobile
platforms and web. Through presenting students the entire life cycle of an
application development, the goal of the course is to develop student creativity,
sense for innovations and entrepreneurship, as well as ability to work in a team.
required for pass is: -%
EL
Course Description
C EA
Grading
63
F orms of Teaching
» Lectures
» Lectures on economic topics related to developing business projects
based on mobile and web platforms are held once a week in a twohour block. The lectures are filmed and presented in a digital format
on the web pages of the course. The lecturers are respected experts
from the business and academic communities possessing know-how
in the area of developing mobile and/or web projects: i) university
professors and assistants (University of Zagreb F aculty of Electrical
Engineering and Computing and University of Zagreb F aculty of
Economics and Business); ii) entrepreneurs and managers with
experience in starting and managing companies whose business
models are based on mobile and/or web platforms; iii) members and
alumnae of the student association eSTUDENT.
» Workshops on relevant technical skills related to developing
business projects based on mobile and web platforms are held once a
week in a three-hour block. The workshops are filmed and
presented in a digital format on the web pages of the course.
The workshop presenters are respected experts from the business
and academic communities possessing know-how in the area of
developing mobile and/or web projects:
i) university professors and assistants (University of Zagreb F aculty
of Electrical Engineering and Computing and University of Zagreb
F aculty of Economics and Business);
ii) experts from the industry with experience of developing
applications for targeted platforms (partner firms and leading firms
for mobile application development).
» Consultations
» Judges who mentor and grade projects comment the results of
projects at defined milestone points.
» Seminars
» Students present their project ideas as well as their business plan
through seminar papers. The required materials are used by mentors
to correct the course of development of student projects at defined
milestones. Students also create the technical documentation for
their application as well as presentations for their project.
» The project must fulfill, among others, technical completion criteria,
meaning: i) the application must be functionally complete, with
functionalities defined in the project idea document fully
implemented; ii) the application’s user interface must have a
complete design.
» E-learning
» Lectures and workshops are filmed and presented in a digital format
on the web pages of the course. A dedicated forum is activated to
enable students ask questions about the course/competition
organization or content of lectures/workshops, as well as problems
they encounter during their applications development process.
These questions are answered by course/competition organizers,
lecturers and experts for popular web/mobile platform.
Additionally, the course interactively communicates with all
stakeholders (i.e., students-competitors, organizers, lecturers,
sponsors) via social networks (i.e., F acebook, Twitter).
64
Grading System
T ype
Seminar/Project
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
100 %
Comment:
To successfully complete the course students must fulfill the following criteria: i)
regular attendance at lectures and workshops; ii) regular fulfillment of required
tasks, meaning timely submissions of the project idea document, the business plan
document, the required materials for mentors to evaluate the project at
milestones, as well as the final submission of the finished project, which must
fulfill completion criteria, which are defined as: a) the application must be
functionally complete, with functionalities defined in the project idea document
fully implemented; b) the application’s user interface must have a complete
design; c) the associated technical documentation must contain the main elements
presented in the relevant template document; d) a presentation must be enclosed
to describe the project.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Introduction into the mobile application market
Mobile application development
Android application development, part 1
Android application development, part 2
Web - an introduction
Web - HTML5, CSS3
iOS application development, part 1
iOS application development, part 2
WP7 application development
Application development life-cycle, part 1
Application development life-cycle, part 2
Mobile payment
The impact of mobile devices on the information and communication
market
14. Starting a business
15. Exporting applications based on Information and Communication
Technology (ICT)
65
Literature
E. Brunette (2009). Hello,
Android: Introducing
Google's Mobile Development
Platform, Pragmatic
Bookshelf
R. Meier (2010). Professional
Android 2 Application
Development, Wrox
S.G. Kochan (2011).
Programming in Objective-C
(4th Edition) (Developer's
Library), Addison-Wesley
Professional
J. Conway (2010). iPhone
Programming: The Big Nerd
Ranch Guide, AddisonWesley Professional
A. Nathan (2011). 101
Windows Phone 7 Apps,
Volume I: Developing Apps 150, Sams
Similar Courses
» iPhone Application Development, Stanford
» Developing Mobile Application by Web Technologies, Stanford
66
There are many cognitive tasks that are simple for the human, but very difficult
for the computer. Artificial intelligence (AI) tries to solve these kind of problems.
Traditional approach to AI is based on symbolic knowledge representation and
reasoning as symbol manipulation. Biologically inspired connectivistic approach
simulates cognitive abilities of the brain. The aim of the course is to introduce
different AI approaches and to give an overview AI methods, including methods
for knowledge representation, automatic reasoning, problem solving, learning,
and optimization.
Study Programmes
» Software Engineering and Information Systems -> Computing (Module)
(elective courses, 6th semester, 3rd year)
» Computer Science -> Computing (Module) (required course, 6th semester, 3rd
year)
E-learning Level
L1
Study Hours
Lecturers
45
15
C OM
Lecturer
Doc. dr. sc. Marko Čupić
C EA
Mladen Karan, mag. ing.
comp.
Martin Tutek, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
76
89
Prerequisites
Algorithms and Data
Structures
SEIS
Learning Outcomes
TI
CS
CE
1. Define the basic concepts of artificial intelligence
2. Distinguish between symbolic and connectivistic approaches to AI
3. Apply state search algorithms and biologically inspired optimization
algorithms on basic problems
4. Solve basic problems using logic programming
5. Apply inference algorithms on basic logical problems
6. Compare among various approaches to representing uncertainty
7. Assess the applicability of different AI methods on a given AI problem
8. Review the philosophical aspects of artificial intelligence
Students will have an overview of the different approaches to AI and different AI
methods. They will understand the drawbacks and the advantages of different
approaches and will be able to recognize the types of problems that can be tackled
successfully using AI methods. Students will gain practical programming
experience in solving diverse AI problems, including state space search, game
playing, automatic inference, logic programming, neural networks, and
biologically inspired optimization.
EEIT
L3
EP E
Course Description
English Level
EC E
Doc. dr. sc.
Jan Šnajder
4
EL
Prof. dr. sc.
Bojana DalbeloBašić
ECT S Credits
WT
Lecturers in Charge
E/C
34285
IP
67
F orms of Teaching
» Lectures
» Lectures are given for 13 weeks (3 hours each). Lectures are divided
in two study periods. There will be a midterm exam after the first
period and a final exam after the second period.
» Exams
» Midterm exam and final exam; short quizzes during the semester.
» Laboratory Work
» There will be 4-5 lab take-home lab assignments, demonstrated to
the instructor or the lab assistent.
» Consultations
» Weekly office hours.
Grading System
T ype
Quizzes
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
25 %
0%
0%
0%
25 %
5%
35 %
35 %
Exam
T hreshold
Percent of
Grade
25 %
0%
0%
25 %
0%
50 %
37.5 %
37.5 %
Comment:
Exams after the final exam are written and oral, together contributing 75% to the
final grade. Students are required to score above 50% on written exam to be
admitted to the oral exam.
1. Overview of the artificial intelligence. History of AI. AI research areas and
newest trends. Relation to other disciplines. Intelligence and the Turing
test.
2. Solving problems by searching state space search. Blind search strategies.
3. Informed search strategies. A* algorithm. Constraint satisfaction problems.
Game playing. Min-max algorithm.
4. Knowledge and reasoning. F irst order logic. Theorem proving. Unification.
Resolution rule.
5. Logic programming. Prolog.
6. Semantic networks, frames and rules. Ontologies. Expert systems.
7. Natural language processing.
8. Midterm exam.
9. Uncertain knowledge and reasoning. Probability-based knowledge
representation. Bayes rule. F uzzy logic and fuzzy inference.
10. Introduction to machine learning. Naive Bayes classifer.
11. Connectivistic approaches to AI. Artificial neural networks. Perceptron
algorithm. Backpropagation algorithm.
12. Computational intelligence. Genetic algorithm. Ant colony optimization.
13. Embodied AI. Behavior-oriented AI.
14. Philosophical foundations of AI. Wrap up.
15. F inal exam.
68
Literature
Stuart Russell and Peter
Norvig (2009). Artificial
Intelligence: A Modern
Approach, Prentice Hall,
London
Rolf Pfeifer and Christian
Scheier (2001).
Understanding Intelligence,
The MIT Press
Similar Courses
» Artificial Intelligence, MIT
» Introduction to Artificial Intelligence, Stanford
» Artificial Intelligence I, Cambridge
» Introduction to Artificial Intelligence: The ShanghAI lectures, ETH Zurich
» Artificial Intelligence 1, Chalmers University
» Grundzüge der Artificial Intelligence, TU Wien
» Problem Solving and Search in Artificial Intelligence, TU Wien
» Introduction to Artificial Intelligence, University of California Berkeley
» Intelligent Systems, Oxford
» Künstliche Intelligenz: Grundlagen und Anwendungen, TU Berlin
69
The application of computers has become inevitable when sound recording and
processing is concerned. The following thematic units are elaborated in detail: A/D
conversion. D/A conversion. Ways of exchanging audio content and the formats
used in the process. Media and formats used for storage of audio content.
Characteristics of sound cards. Recording, editing and processing of audio using a
computer. Computer control of musical instruments. Computer-aided sound
analysis. Computer-aided sound synthesis. Computer-controlled sound
reinforcement and PA systems. Computer-controlled radio-diffusion systems.
Multimedia home systems. Audio content archives. Computer-aided and
controlled electroacoustical measurements.
L1
E-learning Level
L1
Study Hours
Lecturers
45
6
51
61
76
91
Prerequisites
Engineering
Study Programmes
IP
SEIS
Learning Outcomes
CS
CE
Explain the principle of A/D and D/A conversion
Differentiate media and formats for sharing audio content
Explain the features of sound cards
Apply recording, editing and sound processing with computer
Analyze the sound with a computer
Describe the computer control of musical instruments
Choose a good way of audio content archiving
Use a computer for electroacoustic measurements
TI
1.
2.
3.
4.
5.
6.
7.
8.
Good understanding of the problems and solutions of sound recordings and
procesing, with applications to computers. Theoretical and practical knowledge
about methods and techniques in measuring of sound, with applications to
computers. Basic knowledge about methods and techniques in sound processing.
C EA
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
T eaching Assistant
Dr. sc. Miljenko Krhen
EEIT
English Level
EP E
Course Description
4
EC E
Izv. prof. dr. sc.
Siniša F ajt
ECT S Credits
EL
Lecturer in Charge
E/C
91858
Audio and Computers
WT
70
F orms of Teaching
» Lectures
» Lectures are held in two cycles, 3 hours per week. After each cycle
assessment is carried out.
» Exams
» Continuous assessment is carried out through mid-term exams and
final exams. Assessment on the examinations are carried out
according to schedule.
» Laboratory Work
» Three laboratory exercises are provided, they are graded, and take
place under the supervision of an assistant.
» Experiments
» Demonstration of some phenomena that are topics at a lecture
» More complex demonstration of some phenomena that are topics at
a lecture
» Consultations
» Consultations take place according to agreement with the teacher
» Seminars
» Individual work for selected topic from the area of the whole course
Grading System
T ype
Seminar/Project
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
15 %
15 %
20 %
20 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
15 %
15 %
0%
40 %
30 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Introduction lecture about sound
A/D i D/A conversion
Methods and formats for audio content sharing
Computer and digital audio workstation
A/D and D/A conversion - Matlab - presentation and demonstration
Audio coding techniques
Sound analysis and sound synthesis
Mid-term exam
Sound card and measuring on sound cards
Audio streaming
VoIP - Internet Phone
Home multimedia systems
Audio content archive
Computer-controlled electroacoustic measurements
F inal exam
71
Literature
Ross Kirk, Andy Hunt
(1999). Digital Sound
Processing for Music and
Multimedia, F ocal Press,
Linacer House, Jordan Hill,
Oxford OX2 8DP
Dieter Thomsen (1987).
Digitalna audiotehnika,
Tehnička knjiga, Zagreb
I.Glover, P.Grant (2000).
Prentice Hall
Y.Huang, J.Benesty (2004).
Audio Signal Processing for
Next-Generation Multimedia
Communication Systems,
Kluwer Academic Press
M.R.Schroeder (2004).
Computer Speech:
Recognition, Compression,
Synthesis, Springer-Verlag
Similar Courses
» F oundations of Computer-Generated Sound, Stanford
» Medientechnik, TU Munchen
» Digital Audio, EPF L Lausanne
» Advanced Topics in Digital Speech Processing, UCLA
72
English Level
L1
E-learning Level
L1
Study Hours
Lecturers
45
15
T eaching Assistant
Dr. sc. Marko Horvat
This subject covers the principles of audiotechnics and the concepts of audio
systems. Measuring units. Audio preamplifiers, power amplifiers, correction
preamplifiers. Devices used for amplitude, dynamic, time and frequency
processing of audio signals. Interconnection of audio devicesand systems. Audio
devices distortion basics. Basics on measurements on audio frequency circuitry,
components, devices and systems. Applications of basic audio devices in sound
reinforcement. Basics of digital audio devices. Basic of electroacoustic transducers
and their connection with other audio devices.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C EA
Course Description
C OM
Lecturers
Doc. dr. sc. Antonio Petošić
50
65
80
90
WT
Study Programmes
IP
(Module) (elective courses, 6th semester, 3rd year)
SEIS
Learning Outcomes
TI
CS
CE
1. Describe basic technical characteristics given in a device's specifications
2. Name electroacoustical chain components
3. Reproduce basic concepts behind amplitude, dynamic, time and frequency
processing of audio signal
4. Name audio power amplifier classes
5. Design basic circuits of audio preamplifiers and filters
6. Compare various audio devices quality
7. Outline basic concepts of an sound reinforcement system
8. Name basic features of electroacoustic transducers
The subject gives the necessary qualifications for understanding of audiotechnics
and audio devices. Based on the knowledge they have gained, the students will be
able to identify the most important features of audio devices, audio system's parts
and electroacoustic transducers and compare them to similar audio devices,
systems and transducers.
EEIT
4
EP E
Izv. prof. dr. sc.
Ivan Đurek
ECT S Credits
EC E
Lecturer in Charge
E/C
34309
Audiotechnics
EL
73
F orms of Teaching
» Lectures
» Lectures are organized through two lecturing cycles. The first cycle
consists of 7 weeks of lectures and the midterm exam. The second
cycle consists of 6 weeks of lectures and the final exam. The lectures
are given in total 15 weeks with weekly load of 3 hours.
» Exams
» Exams consist of one midterm exam and a final exam. The final exam
includes materials from all lectures
» Laboratory Work
» During the 15 weeks of lectures, students must attend 5 laboratory
excersises. The exercises are practical and include measurements and
construction of basic preamplifier, filter and signal processing
devices circuits.
» Consultations
» Consultations are given after each lecture or specially according to
agreement with the lecturer.
Grading System
T ype
Attendance
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
20 %
5%
25 %
40 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
20 %
5%
0%
65 %
10 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Measuring units, signals and distortions
Analog preamplifier circuits
Operational amplifier circuits
Audio signal processing in time domain
Audio signal processing in frequency domain
Dynamic processing of audio signals
Basic on mixers and mixing consoles
Exams
Output power amplifiers - basic circuits
Output power amplifiers - stability, protection, thermal dynamics
Basics on digital audio dvices, A/D and D/A conversion
Basics on electroacoustic transducers
Basics on sound reinforcement systems, signal levels in sound reinforcement
systems
14. Screeing of an documentary about sound reinforcement systems
15. Exams
74
Literature
F rancis Rumsey, Tim
McCormick (2008). Sound
and Recording, F ocal Press
Bob Cordell (2011).
Designing Audio Power
Amplifiers, McGraw Hill
razni, urednik Glen M.
Ballou (2005). Handbook for
Sound Engineers, F ocal Press
Scott Hunter Stark (2005).
Live Sound Reinforcement,
Thomson Course
Technology
Similar Courses
» Audio and Speaker Electronics, MIT
» Verstärkunbgschaltungen, TU Munchen
» F oundations of Sound Recording Technology, Stanford
75
Study Programmes
Information Technology (Module) (required course, 5th semester, 3rd year)
Technology (Module) (required course, 5th semester, 3rd year)
(required course, 5th semester, 3rd year)
60
15
EC E
EP E
C EA
C OM
Dr. sc. Tamara Hadjina
Dr. sc. Vinko Lešić
Josip Ćesić, mag. ing.
Mladen Đalto, mag. ing.
Nikola Hure, mag. ing.
Kruno Lenac, mag. ing.
F ilip Mandić, mag. ing.
Anita Martinčević, mag. ing.
Ivan Maurović, mag. ing. el.
Branimir Novoselnik, mag.
ing.
Antonio Starčić, mag. ing.
Grading
Acceptable (2)
50
Good (3)
62.5
Very Good (4)
75
Excellent (5)
87.5
Grades are not subject to
Gaussian distribution.
Prerequisites
Signals and Systems
Prerequisites for
Computer-Controlled
Systems
Learning Outcomes
1. Explain the pricinple of feedback in control systems
2. Apply laws of conservation of energy and matter in mathematical
modelling of dynamical systems; linearize nonlinear model
3. Employ block agebra and Laplace transform in transfer function calculation
4. Compute frequency characteristics of linear systems
5. Apply methods of analysis of stability of linear continuous-time control
systems in frequency domain
6. Apply discretization on a linear continuous-time system
7. Apply methods of analysis of stability of dicrete time systems
EEIT
Study Hours
Lecturers
EL
Introducing course, terminology, historical overview. Classification of control
systems. Principle of feedback. F ormal representation of control systems.
Mathematical modelling. Static and dynamic working regime. Linearization.
Responses of linear time invariant (LTI) systems. Use of Laplace transform. Basic
dynamic components of control systems. Transfer function and frequency
characteristics. Stability analysis: Lyapunov, algebraic and frequency methods.
Internal model principle. Sensitivity. Digital control systems. Choice of the
sampling period. Mathematical description of A/D and D/A converters,
quantization. Discretization methods. Mathematical models of discrete-time
systems. Controllability and observability. Performance indices of control
systems. Introduction to design. PID regulator and parametrization of PID
regulators. F eedforward and cascade control. Digital PID regulator. Windup and
antiwindup. Design of digital control system by emulating continuous system.
L1
WT
Course Description
E-learning Level
IP
Doc. dr. sc.
Nikola Mišković
L0
SEIS
Izv. prof. dr. sc.
Mato Baotić
English Level
CE
Prof. dr. sc.
Zoran Vukić
5
CS
Prof. dr. sc.
Nedjeljko Perić
ECT S Credits
TI
Lecturers in Charge
E/C
34313
Automatic Control
76
8. Apply tuning rules for PID regulator based on experiments (ZieglerNichols).
Understanding the role of control related to flow of matter, energy and
information. Understanding the basic control systems analysis and design
techniques. Ability to design and tune classical controllers.
F orms of Teaching
» Lectures
» Two times per week two hours of lectures.
» Exams
» One midterm and one final exam in written form, or an exam in a
written and oral form.
» Laboratory Work
» Laboratory exercises consist of 6 exercises. Each exercise is worth 3
points: 1 point for homework which is evaluated during the exercise,
0.5 for the laboratory work and 1.5 for a quiz written at the end of
the exercise.
» Consultations
» After each lecture.
Grading System
T ype
Homeworks
Quizzes
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
3%
6%
9%
35 %
47 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
1.5 %
3%
4.5 %
0%
41 %
50 %
Comment:
On midterm exam and final exam at least 40 out of total 82 points is required. At
least 50 out of total 100 points is required to pass the course.
1. Overview of thematic subjects, references, organization of the course and
exams.
Historical background of automatic control development. Examples and
research trends.
2. Systems and control systems. Examples of various systems. System
classification.
F ormal representation of control systems. Block algebra.
3. Modeling of dynamical systems.
4. Linearization of nonlinear systems.
Systems representations: impulse system response, step system response,
state-space representation.
77
5. Use of Laplace transform. Transfer function.
6. System frequency characteristics. Various representations (Nyquist, Bode,
Nichols). Examples.
7. Poles, zeros and time responses of linear dynamical systems.
Control systems structures.
8. Midterm exam.
9. Stability of linear continuous-time control systems.
Stability analysis by frequency method (Nyquist, Bode).
10. Time performance indices for control system steady-state response.
Introduction to digital control systems.
11. Mapping of poles and zeros from s-domain to z-domain.
12. Discretization of continuous-time systems.
Models of digital control systems.
13. Stability of discrete-time control systems.
PID controller.
14. Parametrization of PID controllers.
PID - additional functions.
15. F inal exam.
Literature
Zoran Vukić, Ljubomir
Kuljača (2005). Automatsko
upravljanje
N. Mišković, S. Jurić-Kavelj,
M. Đakulović, V. Petrović i
ostali (2012). Automatsko
upravljanje - zbirka zadataka,
F ER
J. Matuško, M. Vašak, M.
Seder. (2006). Automatsko
upravljanje - zbirka
zadataka., F ER
N. Perić (1998). Automatsko
upravljanje - auditorne vježbe,
F ER
N. Perić (2005). Automatsko
upravljanje-predavanja, F ER
Feedback Control of
Dynamical Systems. G.F.
Franklin, J.D. Powell, A.
Emami.Naeini. 4th edition,
Prentice Hall, 2002.
Digital Control of Dynamic
Systems. G. F. Franklin, J.D.
Powell, M.L. Workman. 3rd
edition, Prentice Hall, 1997.
Linear Control System
Analysis and Design Conventional and Modern. J.J.
DÁzzo, C.H. Houpis. 4th
edition, McGraw-Hill, 1995.
Control System Design. G.C.
Goodwin, S.F. Graebe, M.E.
Salgado. Prentice Hall, 2001.
Similar Courses
» Control Systems, ETH Zurich
» Automatic Control, Lund University
» Regelungs- und Steuerungstechnik 1, TU Munchen
» , MIT
78
Multilevel organization of distributed control systems for automation of plants
and processes. F unctions and databases of automation levels. Programmable logic
controllers (PLCs) - architectures, programming and application examples.
Individual work with PLCs - logical functions, PID controller. Communications in
automation systems. Examples of industrial communication networks and
protocols. Individual work with industrial communication networks. Introduction
to real-time databases. Human - control system communication interface and
SCADA programs. Individual work with a SCADA program.
L1
E-learning Level
L1
Study Hours
Lecturers
15
30
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
Igor Cvišić, dipl. ing.
Antonio Starčić, mag. ing.
EEIT
English Level
C EA
Course Description
4
50
62.5
75
87.5
Prerequisites
EP E
Izv. prof. dr. sc.
Mario Vašak
ECT S Credits
EC E
Lecturer in Charge
E/C
34344
EL
WT
Study Programmes
IP
Learning Outcomes
SEIS
TI
CS
CE
1. Identify basic functions and elements of a digital computer in an
automation system computer (process computer)
2. Explain the basic structure of the automation system
3. Explain the basic structure of the programmable logic controllers
4. Solve tasks of sequential control in an automation system by writing
corresponding programmable logic controllers programs
5. Solve tasks of proportional-integral-derivative (PID) control of continuous
processes in an automation system by writing corresponding
programmable logic controllers programs
6. Integrate individual elements of an automation system into a system
connected with standard fieldbus communication networks
7. Apply configuration tools for SCADA system design for an automation
system
8. Develop a hierarchical automation system based on programmable logic
controllers, fieldbus communication systems and SCADA systems for real
applications
The course trains students for stand-alone programming of automation systems
and design of industry processes and plants control systems.
79
F orms of Teaching
» Lectures
» 15 hours, ununiformly divided over weeks
» Exams
» Tasks for analysis and synthesis of programming solutions and
hardware configuration in an automation system
» Laboratory Work
» Work with a software package for configuring and programming
devices in an automation system
» Work with a software package for configuring and programming
devices in an automation system
» Consultations
» After lectures or arranged via e-mail
» Seminars
» More complex tasks which are demonstrated on programmable logic
controllers
Grading System
T ype
Quizzes
Seminar/Project
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
47 %
47 %
47 %
12 %
3%
45 %
20 %
20 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
10 %
0%
40 %
0%
30 %
20 %
Comment:
F or a cummulative exam there are no thresholds on laboratory exercises and
seminars, but they should be all done.
1. Lecture 00 -- Course rules; Lecture 01 -- Architecture of automation
systems; Lecture 02 -- Architecture of programmable logic controllers (2
hours)
2. Lecture 02 (continuation) -- Architecture of programmable logic controllers
(2 hours)
3. Lecture 03 -- Configuration and programming of programmable logic
controllers (2 hours)
4. Lecture 04 -- Data blocks, functions and function blocks. Indirect
addressing. (2 hours)
Laboratory block 1 -- Interactive laboratory excercise: Introduction to a
software package for configuring and programming of programmable logic
controllers (2x2 solar hours)
5. Lecture 04 (continuation) -- Data blocks, functions and function blocks.
Indirect addressing. (2 hours)
Laboratory block 2 - Laboratory excercise: PLC programming - binary and
digital operations. (2x2 solar hours)
80
6. Lecture 05 - Analog values processing using PLC. Control in closed loop
using PLC. (2 hours)
Laboratory block 3 (Seminar 1) -- Individual work od students in
laboratory on more complex tasks in binary and digital operations.
7. Laboratory block 3 (Seminar 1) -- Individual work od students in
laboratory on more complex tasks in binary and digital operations.
8. Midterm exam
9. Laboratory block 4 -- Laboratory exercise: Analog values processing using
PLC. (2x2 solar hours)
10. Laboratory block 5 -- Laboratory exercise: PID control using PLC. (2x2
solar hours)
11. Lecture 06 -- Communication networks in automation systems. (2 hours)
Laboratory block 6 (Seminar 2) -- Individual work of students in laboratory
on implementation of PID control using PLC.
12. Lecture 07 -- SCADA systems (1 hour)
Laboratory block 7 -- Interactive exercises: (7.1) Configuration of fieldbus
communication networks in an automation system (1 solar hour); (7.2)
Configuration of a human-machine interface in an automation system (2
solar hours)
13. Laboratory block 8 -- Laboratory exercises: (8.1) Configuration of fieldbus
communication networks in an automation system (1 solar hour); (8.2)
Configuration of a human-machine interface in an automation system (2
solar hours)
14. Laboratory block 9 -- Seminar 3: Integration of fieldbus communication
and human-machine interface within complex automation systems
15. F inal exam
Literature
William Bolton (2003).
Programmable Logic
Controllers, third edition,
Elsevier
Bogdan Wilamowski, David
Irwin (2010). The Industrial
Electronics Handbook -Industrial Communication
Systems, Taylor and F rancis
Group
Stuart A. Boyer (2004).
SCADA: Supervisory Control
and Data Acquisition, third
edition, ISA-The
Instrumentation, Systems,
and Automation Society
Similar Courses
» Industrial Automation, EPF L Lausanne
» Praktikum Automatisierungstechnik und Robotik, TU Munchen
81
Course Description
The course objective is to introduce students to sound recording in different
recording conditions as well as to frequency, amplitude and time analysis and
processing of sound, with the purpose to obtain optimal sound quality. Every
chapter is presented through a theoretical overview and practical or
demonstrational exercises.
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
30
30
C OM
Lecturer
EEIT
2
T eaching Assistant
C EA
Prof. dr. sc.
Hrvoje
Domitrović
ECT S Credits
Grading
EP E
Lecturer in Charge
E/C
71794
Basics of Sound Recording and Processing
EC E
EL
Learning Outcomes
IP
WT
Select optimal equipment for sound recording
Define optimal place and way for recording
Judge necessary procedures of sound processing
Generate effescts for improvement of recorded sound
Estimate the quality of stereophonic reproduction
Evaluate recorded sound samples
SEIS
1.
2.
3.
4.
5.
6.
CS
CE
By successfully passing the course, students will aquire skills for selecting
appropriate recording techniques in different situations, as well as skills related to
basic processing of simple audio recordings.
F orms of Teaching
TI
» Lectures
» Class is held for two school hours per week.
» Laboratory Work
» Lab. is organized after the lessons.
» Recording will take place at th School of Music
» Acquisition of Skills
» Exercises are carried out individually on a personal computer
(recommended software packages: Steinberg Cubase or Nuendo),
except for exercises requiring additional equipment (e.g.
microphones) which will be held in larger groups or set up as
demonstrational exercises.
82
Grading System
T ype
T hreshold
F inal Exam: Oral
Exam: Written
Exam: Oral
0%
Percent of
Grade
Exam
T hreshold
Percent of
Grade
50 %
50 %
0%
50 %
50 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Analog and digital sound recording
Room acoustics
Microphones and loudspeakers
Sound cards, A/D and D/A converters
Digital and analog audio formats and their quality
Personal computer based sound recording
Sound synthesis, virtual instruments and MIDI. Connecting audio
components in a studio.
Editing of sound samples
Recording speech and vocals.
Acoustical and electrical instruments recording
Types of sound processing.
Principles of mixing.
Automation in sound recording.
Audio mastering.
Exam
Literature
F . Alton Everest, Ken
Pohlmann (2009). Master
Handbook of Acoustics,
McGraw-Hill/TAB
Electronics
F . Alton Everest (2006).
Critical Listening Skills for
Audio Professionals Book,
Artistpro
Bob Katz (2007). Mastering
Audio, Second Edition: The art
and the science, F ocal Press
Similar Courses
» The Sciencs of Sound Recording, Stanford
83
1.5
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
15
Grading
Doc. dr. sc.
Stjepan Groš
The course has no grades but
only pass or not pass.
This skill is oriented towards students with no knowledge of Linux and it's
command line. To accomplish this goal basic concepts will be introduced, as well
as tools necessary for efficient use of command line. At the end, graphical user
interface will be presented, as well as remote work using ssh shell.
Prerequisites for
Advanced Use of Linux
Operating System
EC E
EP E
Course Description
Learning Outcomes
EL
WT
Apply knowledge to manipulate files and directories
Describe Linux file system hierarchy
Apply knowledge to view and manipulate file content
Apply knowledge to manage users and groups
Apply knowledge to manage ownership and permissions
Create regular expressions and patterns
IP
1.
2.
3.
4.
5.
6.
SEIS
CS
CE
Students will gain basic knowledge necessary for a work in a command line of
Unix operating system, and in particular Linux operating system. In order to
achieve that some basic terminology and knowledge will be thought like files,
directories, users and groups, ownerships and permissions. Also, students will gain
knowledge of some mechanisms that will allow them use of some advanced
possibilities of command line.
TI
F orms of Teaching
» Lectures
» Lectures with slides.
» During lectures students are shown examples.
EEIT
ECT S Credits
C OM
Lecturer in Charge
E/C
86495
Basic Use of Linux Operating System
C EA
84
Grading System
T ype
Homeworks
Quizzes
Class participation
Seminar/Project
Attendance
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
30 %
30 %
5%
30 %
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Description of the skills. Introduction.
Working with files and directories.
Working with files and directories.
F ile system hierarchy.
View inside files.
View inside files.
Users and groups.
Ownerships and persmissions.
Searching, filters and pipes.
Searching, filters and pipes.
Patterns and regular expressions.
Patterns and regular expressions.
Processes.
Shells.
Shells.
Literature
Grupa autora (2006). Osnove
operacijskog sustava Linux,
F ER, Zagreb
Žagar, Mario (2006). UNIX i
kako ga koristiti, 7. digitalno
(XML) izdanje, F ER, Zagreb
85
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
The final thesis is a comprehensive and highly independent task where the student
has to demonstrate the ability to analyse the given problem from theoretical and
practical aspects, devise a solution using the knowledge acquired in multiple
courses and literature, implement the solution, write the documentation and
instructions for use and/or for further work, to present his or her work in written
and oral form. The accent is given on demonstration of ability in all these aspects
rather than to force students to pursue some work intensive repetitive activities
in order to fully complete a product.
ECT S Credits
Prerequisites
Project
C OM
Course Description
E/C
34317
BSc Thesis
Study Programmes
C EA
EP E
WT
EL
EC E
Students are to achieve self confidence in their acquired knowledge, ability to
additionally consult the mandatory or supplementary textbooks, consult the
advisor with well structured and prepared questions and, in most cases, devise a
practical solution of moderate but representative functionality. Last, but not least,
they have to present it in a written form, formally, linguistically and ethically
correct, prepared on computer, according to instructions, of the average overall
size of 30 single spaced A4 pages, what raises their awareness of importance of
this ability. Computer prepared transparencies and a 10 minutes oral presentation
both serve to train the students how to present their work to specific audience
within a given time frame.
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
F inal work assignment
Work on final thesis
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
86
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
Project
C OM
Course Description
E/C
41423
BSc Thesis
Study Programmes
C EA
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
87
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
Project
C OM
Course Description
E/C
41424
BSc Thesis
Study Programmes
C EA
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
88
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
Project
C OM
Course Description
E/C
41426
BSc Thesis
Study Programmes
C EA
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
89
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
Project
C OM
Course Description
E/C
41428
BSc Thesis
Study Programmes
C EA
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
90
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
C OM
Course Description
E/C
41429
BSc Thesis
Study Programmes
C EA
» Information Processing -> Computing (Module) (required course, 6th semester,
3rd year)
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
91
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
C OM
Course Description
E/C
41430
BSc Thesis
Study Programmes
C EA
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
92
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
C OM
Course Description
E/C
41431
BSc Thesis
Study Programmes
C EA
» Computer Engineering -> Computing (Module) (required course, 6th semester,
3rd year)
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
93
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
C OM
Course Description
E/C
41432
BSc Thesis
Study Programmes
C EA
year)
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
94
12
English Level
L3
E-learning Level
L1
Study Hours
EEIT
ECT S Credits
Prerequisites
C OM
Course Description
E/C
41433
BSc Thesis
Study Programmes
C EA
» Telecommunication and Informatics -> Computing (Module) (required course,
EP E
WT
EL
EC E
Grading System
T ype
T hreshold
Percent of
Grade
T hreshold
IP
Exam
Percent of
Grade
SEIS
CS
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
CE
95
Prof. dr. sc.
Krešimir Malarić
ECT S Credits
2
English Level
L2
E-learning Level
L1
Study Hours
Lecturers
30
30
T eaching Assistant
Dr. sc. Branimir Ivšić
EEIT
Lecturer in Charge
E/C
69392
Chess
C OM
50 points to pass
EL
Learning Outcomes
IP
WT
Identify chess openings
Explain chess rules
Apply tournament rules
Analyze chess problems
Arrange chess tournaments
Evaluate the position on a board in a chess game
SEIS
1.
2.
3.
4.
5.
6.
CS
CE
F amiliarizing with the game of chess. Learning chess game rules and strategies in
opening, middle game and endgame. Solving chess problems. Acquiring
knowledge necessary to play in tournaments and clubs.
F orms of Teaching
TI
» Lectures
» Lectures are given with the use of powerpoint presentations
published on the web pages. The lectures are organized through 2
cycles. The first cycle consists of 7 weeks of lectures and midterm,
while other cycle has six weeks of lectures and final exam. The
lectures are given in total of 15 weeks, two hours per week.
» Laboratory Work
» Laboratory works consists of playing chess games and tournament.
» Practicing openings and chess problems covered at lectures.
EP E
Historical survey of chess. Game rules and piece movement. Most used openings.
Middle game and endgame. Most important chess games. World championship
and Croatian grandmasters. Playing chess in clubs and on turnaments. Proper
game writing. Chess categories. Internet Chess. Playing against computers. Chess
strategy. Chess problems.
EC E
Course Description
C EA
Grading
96
Grading System
T ype
T hreshold
Percent of
Grade
0%
0%
0%
30 %
35 %
35 %
Exam: Written
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
100 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Historical survey of chess
Game rules and figure movement.
Chess notation
Common openings
Open games
Semi-open games. Closed games.
Semi-closed games. Side openings.
Midterm.
Middle game. Endgame
Computer chess
Tournament chess
World champions
Croatian masters
Ilustrative games. Problem chess.
F inal exam.
Literature
Josip Varga (2001). Prvi
šahovski koraci, AGM
Krešimir Malarić (2011).
Skripta s predavanja, F ER
Vladimir Cvetnić (2005).
Šah i kako ga lako naučiti
igrati, ALF A
Vladimir Cvetnić (2002).
Šah u 100 lekcija, ALF A
Jeremy Silman (1998).
Complete Book of Chess
Strategy: Grandmaster
Techniques from A to Z, Siles
Press
Similar Courses
» Chess and Critical Thinking, University of Southern California
97
The concept and subject of a company. Legal and physical persons. Legal capacity.
Merchant. The company. Partnerships. Capital company. Boundary determination
between commercial and other branches of law. The history of commercial law.
Trade agreement law. The concept of a trade agreement. Agreement making,
amendment and cancellation. Trade agreement interpretation. Trade agreement
law - special chapter. Types of trade agreement law. Securities law. Types of
securities. Securities circulation. Basics of corporate property law.
L0
E-learning Level
L1
Study Hours
Lecturers
30
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
Lecturer
Doc. dr. sc. Kosjenka
Dumančić
60
71
81
91
Study Programmes
TI
CS
CE
SEIS
IP
WT
» Information Processing -> Computing (Module) (required course, 6th semester, 3rd
year)
» Computer Engineering -> Computing (Module) (required course, 6th semester, 3rd
year)
» Computer Science -> Computing (Module) (required course, 6th semester, 3rd year)
Learning Outcomes
1. Define a matter of commercial law and the basic application in business
practice.
2. Define the work and activities of the court registry and address practical
issues related to the operations of the company.
3. Define the theoretical aspects of many types of companies, the possibility
of establishing them, and all terms related companies
EEIT
English Level
C EA
Course Description
2
EP E
Prof. dr. sc.
Hana Horak
ECT S Credits
EC E
Lecturer in Charge
E/C
34294
Commercial Law
EL
98
4. Define the key concepts of commercial law
5. Define and develop some case law
6. Define the relationship between the contracts
To enable the student to develop an understanding of the legal framework of
business, to develop an understanding of the purpose and logic of the law, to
develop a vocabulary which will be helpful in the future and to develop a general
knowledge of how the law affects the business world. This general understanding
will be demonstrated by the completion of all required assignments and
examination scores.
F orms of Teaching
» Lectures
» Lectures, talks and presentations
» Other
» Seminars
Grading System
T ype
Seminar/Project
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
10 %
40 %
50 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
60 %
100 %
1. Introduction.Basics of Law. Law and State. Law System. Sources of Law.
Subjects and Objects of Law.
2. Postulation of current Commercial Law. Commercial law in status terms.
Trader, companies and sole trader.
3. Pre-corporarions.Branches of the corporation. Company. Target of business
activity. Head-office. Representation. Trade registry.
4. Companies. Legal entity. Public company. Limited partnership. Economy
interest company.
5. Silent partnership. Capital companies. Stock companies. Limited liability
companies.
6. Merge and acquisition. Transfer of property. Company transformation and
termination. Liquidation. Bankruptcy.
7. Trade agreement law in general. Obligations. Contract. Contract validity
and invalidity.Making a contract. Types of contracts. Amendments.
Contract termination. Obligations out of contract. Expiration.
8. F irst Small Exam
9. Trade agreements in general. Sale. Exchange. Loan.
10. Rent agreement. Leasing. Construction. Storage. Representation.
11. Agency. Commission. Concession. Licence. Transport. Bank agreements.
12. Securities. Promissory notes, drafts, cheques, shares, etc.
13. Court and arbitration procedures in cases of disputes.
14. Corporation property rights. Invention. Patent. Patent right procedure.
Patent effects.
15. F inal exam
99
Literature
Horak, H. i dr. (2011). Trgovačko pravo, e-knjiga dostupna na
FER web
Similar Courses
» Business Law, TU Munchen
» Business law, University of Toronto
100
Study Programmes
3rd year)
year)
Learning Outcomes
1.
2.
3.
4.
5.
6.
7.
8.
Define concept, architecture and organisation of communication networks
Explain how communication networks operate and their functionality
Apply knowledge about communication networks and protocols
Analyze protocol functions and services, as well as protocol stacks in order
to select appropriate ones
Analyze organization of public and private networks based on IP protocol
Define secutity threats and available solutions in the Internet
Design network models including local area networks, Internet
subnetworks and Internet access
Evaluate communication solutions based on TCP/IP protocol stack
Doc. dr. sc. Ognjen Dobrijević
Dr. sc. Tomislav Grgić
Dr. sc. Krunoslav Ivešić
Ivan Slivar, mag. ing.
EEIT
C OM
C EA
Lecturers
Doc. dr. sc. Stjepan Groš
Doc. dr. sc. Vedran Podobnik
Doc. dr. sc. Lea Skorin-Kapov
EP E
45
15
EC E
Study Hours
Lecturers
EL
Introduction to communication networks. Network architectures, classification
and topology. Communication channel and information packet. Communication
protocols, layered models: Open System Interconnection Reference Model (OSI
RM), Internet model. IP protocol and other network layer protocols in Internet.
Organisation of IP-based networks. Transport layer protocols, TCP and UDP.
Host naming, Internet domains. Information and multimedia services and Internet
applications. Local area network, wide area network, internetworking. User
services and business applications, billing and cost accounting. Public network,
academic and research network.
L1
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
70
85
WT
Course Description
E-learning Level
IP
Prof. dr. sc.
Gordan Ježić
L3
Prerequisites
Operating Systems
Prerequisites for
Computer-Telephony
Integration
Local Area Networks
Multimedia Services
Network Programming
Open Computing
Telecommunication Systems
and Networks
101
SEIS
Prof. dr. sc.
Maja Matijašević
English Level
CE
Prof. dr. sc.
Vlado Glavinić
4
CS
Prof. dr. sc.
Dragan Jevtić
ECT S Credits
TI
Lecturers in Charge
E/C
34272
Students will gain fundamental knowledge of communication networks, network
architecture and protocols, with special emphasis on local area networks, Internet
and public networks. Students will gain knowledge and skills enabling them
understanding of communication network design problems and professional
approach to them. They will develop learning skills necessary to continue to
undertake further study of communication networks.
F orms of Teaching
» Lectures
» Lectures, with lecture notes and presentations available in advance
on the web.
» Exams
» Midterm exam and final exam.
» Laboratory Work
» Complex laboratory assignments that include building network
models, defining communication and system parameters, simulation
and emulation of different usage scenarios, and measurement and
evaluation of network traffic.
» Selected network models implemented using software tool
IMUNES are demosntrated during lectures.
» Consultations
» Regular consultation hours with all lectureres, four tems every
week.
» Literature search on communication networks. Building software
environment for communication network design and analysis.
» Personal software package IMUNES. Network modelling,
simulation and emulation using software tool IMUNES.
» Other F orms of Group and Self Study
» Homeworks related to IP networks and Internet services.
Grading System
T ype
Homeworks
Class participation
Attendance
Exam: Written
T hreshold
Percent of
Grade
20 %
0%
0%
0%
0%
0%
15 %
10 %
5%
5%
30 %
35 %
Exam
T hreshold
Percent of
Grade
20 %
0%
0%
0%
0%
15 %
10 %
5%
5%
0%
65 %
Comment:
All laboratory assignements should be completed succefully.
102
1. Introduction to communication networks and basic network architectures.
2. Physical layer, transmission media and data link layer in communication
networks. Layer functions and design issues.
3. Communication protocols in data link layer: basic models and
communication efficiency. Local area network, media access and logical link.
Case study: local area network implementation based on Ethernet/IEEE
802.3.
4. Network layer: services, packet switching and routing, principles of
congestion control. Internet architecture and internetworking. Case study:
simulation and emulation of IP networks by using software tool IMUNES
(Integrated MUltiprotocol Network Emulator/Simulator).
5. Network layer in Internet. Organisation of Internet. Internet Protocol and
other network layer protocols. IP datagram format, IP addressing. Routing
in Internet, routing protocols.
6. Internetworking: basic principles and network equipment. Interconnecting
local area networks. Internetworking in network layer, connecting IP
networks and subnetworks. Case study: interconnection models, emulation
and simulation using IMUNES.
7. Transport layer: services and functionality. Transport layer in Internet.
Transmission Control Protocol. User Datagram Protocol. Case study:
modelling transport services using IMUNES.
8. Session, presentation and application layers. Services and application
protocols in Internet. Selected Internet services and related protocols:
Domain Name System, World Wide Web, electronic mail. Case study:
modelling Internet services using IMUNES.
9. World Wide Web and electronic mail: communication protocols in TCP/IP
stack. Introduction to network security and security mechanisms. Basic
cryptography, symmetric cryptography, public key cryptography. digital
signature.
10. Network security. Security architecture of Internet. Security protocols.
Secure extension of Internet Protocol, IPsec. Secure socket layer, SSL.
Selected solutions: virtual private network, firewall.
11. Service implementation and internetworking of private and public
networks in Internet, Internet telephony, voice over IP. F ixed and mobile
public networks. Case studies: academic and research network, voice and
data networks.
12. Wireless local area networks. High-speed local and access networks,
evolution of Ethernet.
13. Internet access, Internet users and Internet service providers. Access models
and solutions: protocol PPP, network address translation. F ixed Internet
access through public switched telephone network and integrated services
digital network. Broadband access. Mobile Internet access: GPRS, EDGE,
UMTS, HSPA, LTE/SAE. Internet challenges and future development.
14. 15. -
103
Literature
A. Bažant, G. Gledec, Ž. Ilić,
G. Ježić, M. Kos, M. Kunštić,
I. Lovrek, M. Matijašević, B.
Mikac, V. Sinković (2004).
Osnovne arhitekture mreža,
Element, Zagreb
Andrew S. Tanenbaum,
David J. Wetherall (2010).
Computer Networks, 5/e,
Prentice Hall
F red Halsall (2005).
Computer Networking and
the Internet (5th Edition),
Addison Wesley
James F . Kurose, Keith W.
Ross (2012). Computer
Networking: A Top-Down
Approach Featuring the
Internet, 6/e, Pearson
Larry L. Peterson, Bruce S.
Davie (2011). Computer
Networks: A Systems
Approach, 5/e, Morgan
Kaufmann Publishers
Similar Courses
» Computer Networks, IEEE & ACM Computing Curricula
» Computer Networks, EPF L Lausanne
» Telematics Networks, University of Twente
» Introduction to Computer Networks, Stanford
104
English Level
L1
E-learning Level
L1
Study Hours
Lecturers
30
30
Grading
Doc. dr. sc.
Ante Đerek
EC E
Competitive programming is the course in which students will learn how to
apply algorithms in order to solve complex problems. The goal of this course is to
teach students how to apply familiar algorithms to non-intuitive problems.
No grades, students either
pass or fail.
EP E
Course Description
EEIT
4
C OM
ECT S Credits
C EA
Lecturer in Charge
E/C
65973
Competitive Programming
Learning Outcomes
WT
Describe how algorithmic problems are solved
Recognize the time and memory complexity of an algorithm or a structure
Explain the concrete algorithms and data structures
Analyze the given problem and recognize subproblems
Apply the knowledge on a wider set of problems
Assemble the solutions of subproblems to solve the whole problem
Assess advantages and shortcomings of different algorithms
IP
1.
2.
3.
4.
5.
6.
7.
EL
SEIS
CE
Competitive programming is the course in which students will learn how to
apply algorithms in order to solve complex problems. The goal of this course is to
teach students how to apply familiar algorithms to non-intuitive problems.
CS
F orms of Teaching
TI
» Lectures
» Exams
Grading System
T ype
Homeworks
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
20 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
100 %
105
Comment:
No grades, students either pass or fail.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Introduction lecture.
Graph theory.
Searching algorithms.
Searching algorithms.
Advanced data structures.
Advanced data structures.
Number theory and linear algebra.
Number theory and linear algebra.
Dynamic programming.
Dynamic programming.
Hashing.
Hashing.
Sweep line.
Heuristics.
Heuristics.
Literature
Thomas H. Cormen, Charles
E. Leiserson (2001).
Introduction to Algorithms,
2/e, The MIT Press; 2nd
edition
Robert Sedgewick (2002).
Algorithms in C++, AddisonWesley Professional; 3
edition
Similar Courses
» Competition Programming and Problem Solving, Carnegie Mellon University
106
Course Description
This course introduces students into the overall process of computer aided design
of electronic equipment and systems. Course description: Electronic equipment
development and life cycle. Printed circuit board (PCB) fabrication and surface
mount technologies. Technical documentation. Introduction to Altium Designer.
Schematic entry, schematic library component management, electrical rule check
and netlist generation. Circuit analysis and simulation. Board level design: PCB
design rules, computer aided board design, mechanical design, preparation of
manufacturing documentation. Design recommendations for circuits and
equipment with special requirements.
E-learning Level
L1
Study Hours
Lecturers
30
15
Lecturer
Dr. sc. Željka Lučev Vasić
Saša Tepić, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
E/C
L1
EEIT
English Level
C OM
Doc. dr. sc.
Hrvoje Džapo
4
C EA
Prof. dr. sc.
Mario Cifrek
ECT S Credits
50
70
80
90
EP E
Lecturers in Charge
34352
EC E
Computer Aided Design of Electronic Systems
EL
Prerequisites
Electronics 1
WT
Study Programmes
SEIS
IP
» Computer Engineering -> Computing (Module) (elective courses, 6th semester, 3rd
year)
CE
Learning Outcomes
Describe process of electronic device development and its life cycle.
Describe printed circuit board fabrication and surface mount technologies.
Produce technical documentation of an electronic device.
Analyze electronic device schematic.
Design printed circuit board.
Analyze schematic using SPICE simulation.
Define specific aspects of analog circuit design and high speed digital
design.
8. Use Altium Designer for schematic entry, princted circuit board design, and
SPICE simulation.
TI
CS
1.
2.
3.
4.
5.
6.
7.
107
Students learn about the process of computer aided design of electronic equipment
and systems. The course covers theoretical and practical aspects of the overall
process, from the conceptual design, schematic entry, circuit analysis and
simulation, board level design, and manufacturing documentation preparation.
Students learn about the principles and good practice in preparation of technical
documentation for each design and manufacturing step.
F orms of Teaching
» Lectures
» Lectures are focused on theoretical and practical aspects of key
course topics (two hours per week).
» Exams
» Continuous evaluation encompasses two written exams (midterm
and final exam). Students who do not satisfy at continuous
evaluation must undertake both the written and oral exam. Students
are questioned at the laboratory exercises and they also obtain the
points for a practical project.
» Laboratory Work
» Students are obliged to take laboratory exercises (15 hours). During
the laboratory exercises, students learn printed circuit board design
by using Altium Designer software package.
» Consultations
» Consultations for students are held once per week.
» Seminars
» Students make complete technical documentation of electronic
device based on a project specification, different for each student.
The documentation encompasses block diagrams, electrical
schematics, printed circuit board production masks, bills of material,
technical characteristics and other necessary parts of the overall
technical documentation.
» Students visit companies that produce electronic devices where they
can see how to apply their knowledge and skills in practice.
Grading System
T ype
Seminar/Project
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
35 %
20 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
15 %
35 %
0%
20 %
30 %
Comment:
Work on project is divided into three parts: the first part must be submitted after
the 7th week (up to 5 points), the second part after the 13th week (up to 5 points),
and a complete technical documentation must be finished in the last week of the
semester (up to 25 points).
108
1. Overview of development process and life cycle of electronic device.
2. Printed circuit board fabrication and surface mount technology.
3. Technical documentation. Structure of an electronic device documentation.
Guidelines for technical documentation preparation.
4. Presentation of Altium Designer board level design tool. Demonstration of
module for schematic entry and schematic library management.
5. Schematic analysis and entry. Guidelines for schematic design. Electrical
rule checking.
6. Printed circuit board (PCB) design. Electrical parameters of PCB traces.
Component placement. Guidelines for PCB design.
7. Demonstration of Altium Designer module for PCB design. Design rule
checking.
8. Midterm exam.
9. Particular requirements for electronic device design: grounding, shielding
and power supply.
10. Particular requirements for electronic device design: sensitive analog
circuits, high speed digital logic. Signal integrity analysis.
11. Particular requirements for electronic device design: electromagnetic
compatibility (EMC).
12. Analysis and simulation of electrical circuits. Realistic electronic
components. SPICE simulation of electrical circuits.
13. Preparation of manufacturing documentation. Low and high volume
production, testing. Mechanical design and enclosures. Economical aspects.
Complex examples.
14. Visit to electronic device design and manufacturing company.
15. F inal exam.
Literature
Kim R. F owler (1996).
Electronic Instrument Design:
Architecting for the Life Cycle,
Oxford University Press
R. Magjarević, Z. Stare, M.
Cifrek, H. Džapo, M.
Ivančić, I. Lacković (2009).
Projektiranje tiskanih veza,
Sveučilište u Zagrebu
F akultet elektrotehnike i
računarstva
Tim Williams (2005). The
Circuit Designer's
Companion, Newnes
Henry Ott (1988). Noise
Reduction Techniques in
Electronic Systems, WileyInterscience
H. Džapo, Ž. Lučev Vasić
(2015). Računalom podržano
projektiranje elektroničkih
uređaja, upute za
laboratorijske vježbe,
računarstva
Similar Courses
» Projet de Construction de Dispositifs Electronique, EPF L Lausanne
» 6.070J Electronics Project Laboratory, MIT
109
Learning Outcomes
1.
2.
3.
4.
5.
List the main parts of processors and computers
Explain how processors execute instructions
Explain the function of the main parts of a processor
Solve simple programming problems in assembly language
Explain the interfacing and communication between processor, memoy,
and IO units
6. Solve simple problems of communication between processor and IO units
Grading
Acceptable (2)
50
Good (3)
65
Very Good (4)
80
Excellent (5)
90
This grading system is applied
to both, continuous
assessment and exams.
Prerequisites
Digital Logic
Engineering
Prerequisites for
Embedded Systems
Operating Systems
Project
Students will be able to understand fundamentals of computer architecture, and be
able to solve basic programming problems using assembly language.
F orms of Teaching
» Lectures
» Lectures are held every week (4 hours per week).
» Exams
» All exams are in written form
» Laboratory Work
» Laboratoy excercises are held three times per semester (2 hours per
excercise)
EEIT
C OM
Dr. sc. Ivana Bosnić
Dr. sc. Daniel Hofman
Barbara Arbanas, mag. ing.
Leon Dragić, mag. ing. comp.
Alen Duspara, mag. ing.
Petar F ranček, dipl. ing.
Igor Piljić, mag. ing. comp.
C EA
60
15
EP E
Study Hours
Lecturers
EC E
L1
EL
Study Programmes
E-learning Level
WT
This course gives basic understanding of processor architecture and computer
system organization. Principles are explained using simple RISC processor and
commercial ARM CPU architecture. Internal architecture of a processor is
explained together with the details of the instruction execution. Assembly
language programming is explained. Interfacing with memory and IO units is
explained.
L0
IP
Course Description
English Level
SEIS
Prof. dr. sc.
Danko Basch
6
CE
Prof. dr. sc.
Mario Kovač
ECT S Credits
CS
Lecturers in Charge
E/C
21010
TI
110
Grading System
T ype
Quizzes
Exam: Written
T hreshold
Percent of
Grade
16 %
16 %
0%
0%
12 %
18 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
16 %
16 %
0%
5%
10 %
0%
85 %
Comment:
All 3 Laboratory excercises must be succesfully completed (you dont get points for
that) in order to get the passing grade.
1. Computer organization. Introduction to processor architectures.
2. CISC and RISC processors. Basic model of a RISC processor. Instruction set
of a processor.
3. Datapath and instruction execution. Assembly language programming.
4. Basic algorithms and techniques in assembly programming. Subroutines.
5. Buses. Interfacing processor and memory. Bus communication protocols.
Pipeline and instruction execution.
6. IO data transfer. IO units. IO programming.
7. Interrupts. Direct Memory Access (DMA).
8. Midterm exam
9. ARM processor architecture.
10. ARM instruction set. Addressing modes of ARM processor.
11. Programming ARM processor in assembly language. Subroutines.
12. Exceptions, busses and IO data transfer for ARM processor.
13. Pipeline and instruction execution for ARM processor.
14. Memory organization. Cache memory. Basics of virtual memory.
15. F inal exam
Literature
Mario Kovač, Danko Basch
(2011). Rukopisi s predavanja
Mario Kovač (2015).
Arhitektura računala
D. A. Patterson, J. L.
Hennessy (2005). Computer
Organization & Design, 3rd
ed., Morgan Kaufmann
Danko Basch, Martin Žagar,
Branko Mihaljević, Marin
Orlić, Josip Knezović, Ivana
Bosnić, Daniel Hofman,
Mario Kovač (2012). Zbirka
programskih zadataka za
procesor FRISC, F ER
Martin Žagar, Josip
Knezović, Ivana Bosnić,
Mario Kovač (2013). Zbirka
programskih zadataka za
procesor ARM 7, F ER
111
Similar Courses
» Computer System Architecture, University of California Berkeley
» Computer Architecture, IEEE & ACM Computing Curricula
» Computer System Architecture, MIT
112
Course Description
This course studies architectural components of computer systems: processor,
memory, buses, and IO devices. The course considers design approaches which
allow us to achieve the desired computer system properties: performance, price,
power consumption, reliability. The main fields of interest are i) specificities of
general purpose computer architecture, ii) organizational details of the
architectural components which affect the software performance, and iii)
exploiting the parallelism at the levels of instructions, vector instructions and
threads.
E-learning Level
L1
Study Hours
Lecturers
45
15
Ivan Krešo, mag. ing. comp.
Marijo Maračić, dipl. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
76
89
Prerequisites
WT
Study Programmes
CE
SEIS
IP
» Information Processing -> Computing (Module) (specialization courses, 5th
semester, 3rd year)
3rd year)
» Computer Science -> Computing (Module) (specialization courses, 5th semester,
3rd year)
» Telecommunication and Informatics -> Computing (Module) (specialization
courses, 5th semester, 3rd year)
Learning Outcomes
CS
TI
1. Distinguish the roles of major components of a computer including CPU,
memory, buses and I/O devices.
2. Predict activity on the memory bus of a simple procesor, as a consequence
of execution of short machine code snippets
3. Demonstrate the implementation of simple instructions at the logic level
4. Summarize design principles of instruction set architectures RISC and x86
5. Solve small-scale problems by complementing C with assembly
6. Summarize the organization of superscalar processors with dynamic
pipeline scheduling
7. Illustrate stages of physical address generation in presence of caches and
virtual memory
8. Explain the implementation of coarse-grained parallelism on multi-core
and multi-processor computers
EEIT
L1
C OM
Doc. dr. sc.
Tomislav Hrkać
English Level
C EA
Izv. prof. dr. sc.
Siniša Šegvić
4
EP E
Prof. dr. sc.
Slobodan Ribarić
ECT S Credits
EC E
Lecturers in Charge
E/C
34277
EL
113
The students are trained for solving problems related to design, configuration and
utilization of general purpose computers. Lectures and laboratory exercises
stimulate associating architectural and organizational concepts with recent case
studies. In particular, the students are acquainted with detailed organization of a
simplified processor, performance metrics, instruction set architectures, dynamic
pipeline scheduling, memory hierarchy, multi-processor and multi-core systems,
and consequences which affect software design.
F orms of Teaching
» Lectures
» The course includes three hours of lectures per week.
» Exams
» The knowledge tests include the midterm exam (35%), the final
exam (45%), two short tests in class (5%) and three tests in the
laboratory (15%).
» Laboratory Work
» The course includes two laboratory exercises.
http://www.zemris.fer.hr/~ssegvic/ar2/index_en.html
» Consultations
» Consultations are held once a week within a time slot of two hours.
Grading System
T ype
Quizzes
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
5%
35 %
45 %
Exam
T hreshold
Percent of
Grade
40 %
0%
0%
0%
0%
0%
80 %
20 %
1. Introduction. Trends in VLSI technology, computer architecture, and
processor performance. Roles of major components in the Von Neumann's
computer model including CPU, memory, buses and I/O devices.
Implementing a shared bus with three-state buffers. Problem solving
exercises.
2. Simplified model of the processor organization. Tracking the memory
activity during the execution of short machine code snippets. Problem
solving exercises.
3. Hardwired control in a 8-instruction processor model. Implementation of
simple instructions at the gate level. Components of control unit: sequence
counter, decoder, logic array, clock generator. Problem solving exercises.
4. Implementation of control in the model of the microprogrammable
processor: microprogrammable processor model, organization and
structure of the microprogrammable control unit, microinstruction formats.
Problem solving exercises.
5. Hardware/software interface: stacks, exceptions, creation of executable
files, memory layout of a typical process. Problem solving exercises.
114
6. Computer architecture classifications with respect to parallelism (F lynn),
control flow (instruction, data), and instruction sets (CISC, RISC, VLIW).
Computer performance: introduction of the parameter CPI, SPEC
benchmark collections. Problem solving exercises.
7. Instruction set architectures RISC and x86. Data path of a modern RISC
processor. Problem solving exercises.
8. Midterm exam.
9. The concept of pipelined data processing. Pipeline hazards: structural, data,
and control. Organization of a pipelined RISC processor.
10. Aggresive exploitation of instruction-level parallelism. Superscalar
organization. Dynamic scheduling. Register renaming. Branch prediction.
Case studies.
11. Memory hierarchy. Approaches for improving the bandwidth of the main
storage. Cache organization: direct-mapped, fully associative and setassociative. Replacement algorithms. Cache coherency. Case studies.
Problem solving exercises.
12. Virtual memory system. Physical and logical address spaces. Address
mapping by paging and segmentation. TLB-s and multi level page tables.
Replacement policies. Case studies. Problem solving exercises.
13. F orms and levels of parallelism. Parallel architectures. Multiprocessor
SIMD computers. Vector processors.
14. Multiprocessor MIMD computers. Multiprocessor cache coherency.
Synchronization of processes and threads. Multicore processors. Graphic
processors.
15. F inal exam
Literature
S. Ribarić (2011). Građa
računala, Arhitektura i
organizacija računarskih
sustava, Algebra
S. Ribarić (1996).
Arhitektura računala RISC i
CISC, Školska knjiga
D. A. Patterson J. L.
Hennessy (2008). Computer
Organization & Design,
Morgan Kaufmann
J. L. Hennessy, D. A.
Patterson (2006). Computer
Architecture, A Quantitative
Approach, Morgan
Kaufmann
Similar Courses
» Computer System Architecture, MIT
» Architecture des ordinateurs II, EPF L Lausanne
» Introduction to Computer Architecture, Carnegie Mellon University
» Architecture and Organization: F unctional Organization, IEEE & ACM
Computing Curricula
115
Control of systems with considerable delay. Smith predictor. Process periphery.
Signal pre-processing in the digital automatic control system. Implementation
aspects of the control algorithms. Distributed control systems. Computer
networks for real-time applications. Event-triggered protocols. Time-triggered
protocols. Sampling time selection of the control loops in distributed control
systems. Basics of synthesis of controlled systems over the communication
network. Examples of computer controlled systems.
E-learning Level
L1
Study Hours
Lecturers
45
15
Grading
Acceptable (2)
50
Good (3)
62.5
Very Good (4)
75
Excellent (5)
87.5
Students who have passed the
written exam with marks
excellent (5) and very good (4)
do not have to attend the oral
exam.
Prerequisites
Automatic Control
EP E
C EA
C OM
Doc. dr. sc. Marija Seder
Dr. sc. Ivan Marković
Luka F ućek, mag. ing.
EEIT
L1
EC E
Computer supported automatic control. Requirements, structures and
implementations of computer controlled systems. Mathematical description of
discrete-time systems - a short overview. Graphoanalytical identification
methods of process mathematical models. Approaches to digital controllers
design. Control systems design in time domain - relay method of PID controller
design, general linear parametric controller and its design by optimization.
Control systems design in frequency domain: Design by Bode diagrams. Lead-lag
compensator. Analytical methods of control systems design: Truxal-Guillemin
method.
English Level
EL
Course Description
4
WT
Prof. dr. sc.
Ivan Petrović
ECT S Credits
IP
Lecturer in Charge
E/C
34297
Computer-Controlled Systems
SEIS
Study Programmes
TI
CS
CE
Learning Outcomes
1.
2.
3.
4.
5.
6.
Define the basic concepts and principles of computer control systems
Select appropriate method for system identification
Estimate which method is appropriate for control of a specific system
Compute paremeters of digital controllers for typical industrail processes
Demonstrare functionality of computer-controlled system by simulation
Apply the chosen control method to control a real process by a computer
116
This course qualifies students for design and implementation of computer
controlled systems for processes that are common in industry.
F orms of Teaching
» Lectures
» Lectures are organized in two cycles. F irst cycle 7 weeks, 3 hours per
week. Second cycle 6 weeks, 3 hours per week.
» Laboratory Work
» 6 laboratory exercises, 2,5 hours each
» Consultations
» Upon request. Through the forum on the course webpage.
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
50 %
50 %
40 %
50 %
Percent of
Grade
12 %
12 %
26 %
30 %
20 %
Exam
T hreshold
Percent of
Grade
50 %
50 %
0%
12 %
12 %
50 %
50 %
26 %
1. Topics overview, literature, undertaking of teaching and exams. Computer
supported automatic control. Requirements, structures and realizations of
computer controlled systems.
2. Mathematical description of discrete-time systems - a short overview.
Graphoanalytical identification methods of process mathematical models.
3. Introduction to digital controllers design. Design problem definition,
Approaches to controllers design. Architecture of digital controllers.
4. Control systems design in time domain - first part: Relay method of PID
controller design.
5. Control systems design in time domain - second part: General linear
parametric controller and its design by optimization.
6. Control systems design in frequency domain: Design by Bode diagrams.
Lead-lag compensator.
7. Analytical methods of control systems design: Truxal-Guillemin method.
Controller design with respect to disturbance and reference values.
8. Midterm exam.
9. Control of processes with time-delay: Controllers with Smith predictors.
10. Realization aspects of computer-controlled systems: Hardware design.
Measuring signals conditioning and processing. Interfaces to actuating
devices and operators.
11. Implementation aspects of digital controllers: Impelmentation forms.
Limited world length. Coefficient errors. Quantization. Controllers
implementation
in F PGA circuits.
117
12. Communication networks in distributed computer-controlled systems:
Communication model for real-time operation. The most important realtime networks.
13. Sampling time selection in distributed computer-controlled systems:
Problem identification. Algorithms for sampling time selection in systems
with Time-Triggered network and in systems with CAN network.
14. Closed loop control over communication networks.
15. F inal exam.
Literature
Ivan Petrović (2011).
Računalno upravljanje
sustavima - bilješke za
predavanja, F ER - ZARI
Nedjeljko Perić, Ivan
Petrović (2005).
Automatizacija postrojenja i
procesa - predavanja, F ER ZARI
Karl J. Astrom, Bjorn
Wittenmark (1996).
Computer-Controlled
Systems, Theory and Design,
Prentice Hall
Gene F . F ranklin, J. David
Powell, Michael L.
Workman (1997). Digital
Control of Dynamic Systems Third Edition, Prentice Hall
Dimitrios HristuVarsakelis and William S.
Levine (Editors) (2005).
Handbook of Networked and
Embedded Control Systems
(Control Engineering),
Birkhauser
Similar Courses
» Computer-Controlled Systems, Lund University
» Regelsysteme II (Control Systems II), ETH Zurich
» Distributed Real-Time Systems Engineering, TU Wien
118
Course Description
Introduction in Computer Telephony Integration technologies (CTI), interfaces,
international standards and organizations. CTI domain and components, signaling
and CTI topology.
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
70
85
Prerequisites
EEIT
English Level
C OM
4
C EA
Prof. dr. sc.
Dragan Jevtić
ECT S Credits
EP E
Lecturer in Charge
E/C
34328
Computer-Telephony Integration
EC E
EL
CTI in converged architectures. Call and contact centers and application controlled
routing for incoming and outgoing calls. Interactive voice response (IVR) systems.
Traffic modeling and resource allocation in call centers. CSTA protocol and CSTA
call procedures. CTI and intelligent network architectures and services. CTI service
market analysis.
WT
Study Programmes
IP
» Telecommunication and Informatics -> Computing (Module) (elective courses,
SEIS
Learning Outcomes
5.
6.
7.
8.
CS
CE
To define concept, architecture and organisation of CTI services
To explain how CTI services operate and their functionality
To apply knowledge about CTI services and related protocols
To analyze functions of CTI services, as well as their interactions in order to
select appropriate ones
To analyze organization of CTI services for public and private networks
To define basic components for CTI service realisation and solutions for
special instances
To create network CTI services including available private and public
resources
To evaluate and assess solutions of CTI services based on different
technologies
TI
1.
2.
3.
4.
After finishing this course students will have basic knowledge on computertelephony integration technologies, system architecture and basic concepts about
service creation in an environment that includes public telephone network,
integrated services digital network and Internet. Students will have basic
knowledge about difference between technological solutions for CTI and for
intelligent network - both are based on application of computers for service
deployment.
119
F orms of Teaching
» Lectures
on the web.
» Exams
» Laboratory Work
» Complex laboratory assignments that
include building CTI services, defining
communication and system parameters,
running different usage scenarios.
» Consultations
» Regular consultations hours with lecturer, four tems every week.
» Literature search on CTI services. Building software environment for
CTI service design and anslysis.
» Service modelling using software tool ENVOX.
» Homeworks related to CTI services and architectures.
Grading System
T ype
Homeworks
Class participation
Attendance
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
50 %
50 %
0%
0%
50 %
50 %
Percent of
Grade
20 %
10 %
5%
5%
20 %
20 %
20 %
Exam
T hreshold
Percent of
Grade
10 %
5%
0%
0%
0%
20 %
10 %
0%
0%
50 %
40 %
30 %
Comment:
1. Introduction, historical overview, standardization and environment, basic
definitions of CTI (Computer Telephony Integration) terminology, CTI
services.
2. CTI environment: commutation, LAN, ISDN, internet and mobile
networks, converging systems. Standard interfaces and tools, specificity and
criteria for call processing in diverse networks, CTI domain.
3. Integration technologies and interfaces. CTI domain and conditions of the
resource accessibility. Basic call and additional services, service management
in CTI domain.
4. CTI in converged architectures. LAN-PBX, IP-PBX, Softswitch, hybrid and
multifunction architecture. Transparent service management for channel
and packet switched networks.
120
5. CTI service implementation in H.323 network. Components, protocols and
services. 1-st and 3-rd party call control in H.323 network.
6. CTI service implementation in SIP network. Components, protocols and
services. 1-st and 3-rd party call control in SIP network.
7. Electronic mail service in CTI domain - call and email integration. Unified
messaging service. Methods for format and message translation.
8. Midterm exam.
9. Call center and remote dialling systems. Agents, agent state model. Model
of contact center. Performances of remote dialing systems.
10. Automatic call distribution - architectures and call routing criterias.
Contact centers and customer relationship managamenet (CRM) systems.
11. Interactive voice response (IVR) systems. Voice information, analysis and
synthesis of speech signal. Types and features of spoken dialogue for CTI
services.
12. Traffic Modeling and Resource Allocation in Call Centers. Methods and
functions for speaker recognition, information retrieval or recognition of
forms for special purposes in CTI services.
13. CSTA protocol in packet and channel switched networks. Call state model
of CSTA. CSTA call procedures.
14. CTI market, qualitative and quantitative properties of CTI services.
Comparison of CTI and intelligent network architectures and
corresponding services.
F uture trends.
15. F inal exam.
Literature
Computer Telephony
Integration Rob Walters
Artech House Publishers
Boston London 1998
Internet Telephony David D.
Clark, at all MIT Press 2001
Computer Telephony
Integration William A., Jr.
Yarberry Auerbach
Publications 2003
Similar Courses
» Computer Telephony Integration Program / 3 CTI cou, Cambridge
» Telematics Systems and Applications (TSA / TST), University of Twente
» Computer-Based Communications Systems and Networks, University of
California Berkeley
» Enterprise Networks, TU Delft
121
Course Description
Ray tracing in curved spacetime: Spacetime. Curved spacetime. Metric. Path
length. Riemannov tensor. Einstein’s equation and spherically symmetric
solutions. Light propagation in curved spacetime. Numerical solutions of
differential equation. Ray-tracing. Gravitational lens.
L3
E-learning Level
L1
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
60
70
80
90
Prerequisites
Mathematics 2
Physics 2
EEIT
English Level
C OM
4
C EA
Doc. dr. sc.
Ana Babić
ECT S Credits
EP E
Lecturer in Charge
E/C
34351
Computing Methods of Modern Physics
EC E
WT
EL
Application of machine learning to event classification in high energy physics:
Introduction to ground-based gamma-astronomy: observed objects and
instruments. Data acquisition and analysis chain. Event reconstruction. Problem of
signal separation in the presence of high levels of noise. Application of random
forest algorithm to the gamma-hadron separation problem in high energy
physics.
IP
Material surface adsorption: Chemisorption and physisorption. Van der Waals
force. Crystal lattice. Van der Waals material layers (graphen as an example).
Simulating Van der Waals material adsorption onto a surface. F inding optimal
orientation of adsorbed material with respect to the substrate layer.
CE
SEIS
Percolation, application to material properties: Percolation concepts. Abrupt
transitions in material behavior. Long range connectivity. Electrical conductivity
in composite materials. Tunneling effects. Monte Carlo simulations of materials,
comparison with measured properties.
CS
Study Programmes
TI
Technology (Module) (elective courses, 6th semester, 3rd year)
Learning Outcomes
1. Explain the gravitational lens effect.
2. Apply appropriate numerical methods for solving differential equations to
the problem of finding light trajectories in curved spacetime.
3. Explain the process of atmospheric particle shower creation initiated by
high energy photons.
4. Apply machine learning methods to event classification.
5. Describe the origin and properties of van der Waals forces.
122
6. Apply computer modelling to the problem of finding energy minimum of a
given system configuration.
7. Apply computer modelling to the percolation phenomena.
Students will learn how to apply computational methods (numerical and analytic)
by studying modern physics problems i.e. 20th and 21st century physics topics:
quantum mechanics, quantum solid state physics and classical and quantum
solitons. Special attention will be given to situations where standard analytic
methods are not applicable. Students will simulate motion of quantum particle in
different quantum potentials. They will acquire and develop computational skills
by solving problems in gravitational theory and cosmology as well.
F orms of Teaching
» Lectures
» Lectures with the AV support and a computer package "IQ" for QM
simulations.
» Exams
» Midterm exam, homework assignments with problems, final exam.
» Exercises
» Within lectures problems will be solved. Also examples will be
discussed by using a progam package for QM simulation.
» Laboratory Work
» Simulation of quantum mechanical processes on a computer. Simple
problems solved on a computer.
» Consultations
» Consultations will be organized in a direct contact with students.
» Seminars
» Each of the students will be assigned a special topic which will be
shortly presented during lectures.
Grading System
T ype
Homeworks
Seminar/Project
2. Mid Term Exam: Written
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
10 %
10 %
10 %
20 %
50 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
10 %
10 %
10 %
0%
30 %
40 %
1. Spacetime. Curved spacetime. Metric. Path length.
2. Riemannov tensor. (možda sljedeći tjedan) Einstein’s equation and
spherically symmetric solutions.
3. Light propagation in curved spacetime. Numerical solutions of differential
equation.
4. Ray-tracing. Gravitational lens.
5. Introduction to ground-based gamma-astronomy: observed objects and
instruments. Data acquisition and analysis chain.
123
6. Event reconstruction. Problem of signal separation in the presence of high
levels of noise.
7. Application of random forest algorithm to the gamma-hadron separation
problem in high enery physics.
8. Midterm exam
9. Chemisorption and physisorption. Van der Waals force.
10. Crystal lattice. Van der Waals material layers (example graphen).
11. Simulating Van der Waals material adsorption onto a surface. F inding
optimal orientation of adsorbed material with respect to the substrate
layer.
12. Percolation concepts. Abrupt transitions in material behavior. Long range
connectivity.
13. Electrical conductivity in composite materials. Tunneling effects.
14. Monte Carlo simulations of materials, comparison with measured
properties.
15. F inal exam
Literature
Valeri P. F rolov, Andrei
Zelnikov (2011).
Introduction to Black Hole
Physics, Oxford University
Press
H. Kasai, P. Lazić (2016).
Physics Of Surface, Interface
And Cluster Catalysis, Ch.2,
IOP Publishing Ltd
Myra Spiliopoulou, Lars
Schmidt-Thieme, Ruth
Janning (2013). Data
Analysis, Machine Learning
and Knowledge Discovery,
Springer Science &
Business Media
Zheng et al. (2011).
Characteristics of the Electrical
Percolation in Carbon
Nanotubes/Polymer
Nanocomposites, American
Chemical Society
Similar Courses
» Computational Physics, ETH Zurich
» Computational Physics I,II, TU Munchen
» Special Problems in Computational Physics, Carnegie Mellon University
» Introduction to Computational Physics, Carnegie Mellon University
» Computational Physics, University of Toronto
124
Course Description
Control systems structure. Static and dynamic characteristics of control system
elements. Principles and clasification of detectors, transmitters and transducers.
Sensors in robotics. Processing and transmission of measurement signals to control
devices, measurement noise reduction. Specific requirements on measurement
devices in control systems. Intelligent sensors. Actuators and motors (pneumatic,
hydraulic), control valves. Types of control devices. Introduction to programmable
logic controllers (PLCs). Elements for protection, supervision and display of states
of automated process. Introduction to supervisory control and data acquisition
systems (SCADA).
E-learning Level
L1
Study Hours
Lecturers
45
15
Dr. sc. Damjan Miklić
Karlo Griparić, mag. ing. el.
Edin Kočo, mag. ing.
Grading
Acceptable (2)
51
Good (3)
60
Very Good (4)
78
Excellent (5)
89
exam.
WT
Study Programmes
EEIT
L2
C OM
English Level
C EA
Prof. dr. sc.
Stjepan Bogdan
4
EP E
Prof. dr. sc.
Zdenko Kovačić
ECT S Credits
EC E
Lecturers in Charge
E/C
34296
Control System Elements
EL
IP
SEIS
Learning Outcomes
CS
CE
Describe functioning of detectors of phisycal quantities
Describe functioning of hydraulic and pneumatic actuators
Explain the role of of transducers and transmitters
Explain role and types of control devices
Apply ladder diagram-based PLC programming
List detectors of phisycal quantities
Explain role of sensors in robotics
Describe functioning of SCADA systems
TI
1.
2.
3.
4.
5.
6.
7.
8.
Knowledge about principles and types of control systems elements.
Understanding control systems and connections between elements. Ability to
determine parameters of static and dynamic characteristics of control systems
elements. Work with real elements.
F orms of Teaching
» Lectures
» Lectures are organized in thematic parts according to the basic types
of control system elements.
125
» Laboratory Work
» Detectors of caloric variables; digital speed measurement; PLC
programming
» Consultations
» Upon request
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
18 %
30 %
30 %
22 %
Exam
T hreshold
Percent of
Grade
0%
0%
18 %
0%
60 %
22 %
Comment:
The oral exam share is ±30%.
1. Control system structure and principles and classification of detectors,
transmitters and transducers; Detectors of mechanic variables
2. Detectors of mechanic variables; Detectors of caloric variables
3. Detectors of pressure, level, flow and pH
4. The role of transducers and transmitters; Requirements on measurement
devices
5. Processing and transmision of measured signals to control center; Noise
reduction in measured signal
6. Intelligent sensors; Sensors in robotics - digital compass, sonar, touch
sensor, camera, laser finder
7. Characteristics of actuators; Pneumatic actuators
8. Midterm exam
9. Hydraulic actuators; Control valves
10. Types of control devices - analog and digital (uP, uC)
11. Operating principles and components of programmable logic controllers
(PLC); Ways of PLC programming
12. Ladder diagram-based PLC programming
13. PLC programming tools and examples
14. Elements for alarms, protection, supervision and display of states in
automated processes; Introduction to supervisory control and data
acquisition systems (SCADA)
15. F inal exam
Literature
Z. Kovačić, S. Bogdan
(2014). Elementi sustava
automatizacije - Bilješke za
predavanja / Control System
Elements – Lecture notes,
Zavod za APR, F ER Zagreb.
Clarence W. de Silva (2007).
Sensors and Actuators –
Control System
Instrumentation, CRC Press
126
Bill Drury (2009). Control
Techniques Drives and
Controls Handbook, The
Institution of Engineering
and Technology, London,
UK
Bela G. Liptak (2003).
Instrument Engineers'
Handbook, Fourth Edition,
Volume One, CRC Press
John G. Webster, Halit Eren
(2014). Measurement,
Instrumentation, and Sensors
Handbook, Second Edition,
CRC Press
Similar Courses
» E407 Control Engineering Design, NU Singapore
127
Study Programmes
Computing (Study) (required course, 4th semester, 2nd year)
Learning Outcomes
1.
2.
3.
4.
5.
6.
7.
Define basic concepts of databases
Describe main parts of database management systems
Explain principles of data modelling
Explain and understand syntax and semantics of the SQL
Explain and understand basic principles of database protection
Apply the knowledge about data modelling to simple practical examples
Use relational algebra and SQL in problem solving
Lecturers
Izv. prof. dr. sc. Boris Vrdoljak
Doc. dr. sc. Ljiljana Brkić
Doc. dr. sc. Igor Mekterović
Doc. dr. sc. Damir Pintar
EC E
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EP E
Danijel Mlinarić, dipl. ing.
EEIT
60
15
C OM
Study Hours
Lecturers
C EA
L1
50
62.5
75
87.5
Prerequisites
Operating Systems
Prerequisites for
Development of Software
Applications
Open Computing
Programming Paradigms and
Languages
EL
The goal of the course is to familiarize students with key concepts and issues
related to database management systems, relational data model and relational
databases. Course focuses on the skills needed to design relational databases and
database design using the entity-relationship data model; on the relational
algebra, relational query language SQL and the fundamentals of the data
protection.
E-learning Level
WT
Course Description
L3
IP
Doc. dr. sc.
Slaven Zakošek
English Level
SEIS
Prof. dr. sc.
Zoran Skočir
6
CE
Prof. dr. sc.
Mirta Baranović
ECT S Credits
CS
Lecturers in Charge
E/C
31503
Databases
TI
Students will be able to design and implement moderate sized databases, program
queries in SQL and understand the basics of data protection.
F orms of Teaching
» Lectures
» Theoretical fundations and paradigms exposed during the lectures
are illustrated with practical examples and demonstrated using a
database management system.
» Laboratory Work
» Applying the knowledge acquired on lectures on previously
unknown practical examples.
128
Grading System
T ype
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
21 %
4%
5%
30 %
40 %
Homeworks
Quizzes
Exam: Written
Exam: Oral
Exam
T hreshold
Percent of
Grade
30 %
50 %
0%
0%
0%
0%
0%
50 %
50 %
50 %
1. Introduction to the course.
Introduction to databases;
Relational data model.
2. Relational data model (continued), relational operations, relational algebra.
Missing information, NULL values.
3. Relational query language - SQL.
4. Structured Query Language - SQL (continued).
5. Introduction to relational database design, functional dependencies;
Normal forms, normalization
6. Normal forms, normalization - Continued
Introduction to physical organization, indexes, B-trees;
7. Database integrity, integrity constraints, integrity rules.
8. Midterm exam
9. Temporary and virtual tables.
Triggers and stored procedures.
10. F undamentals of query optimization.
Introduction to ER model.
11. Entity-relatioship data model; Entity-relatioship model design.
12. Database management systems, transactions. Database recovery.
13. Database security.
Concurrency control.
14. NoSQL databases. Big data.
15. F inal exam
Literature
J. D. Ullman, J. Widom
(2008). A First Course in
Database Systems, PrenticeHall
Abraham Silberschatz,
Henry F . Korth, S.
Sudarshan (2011). Database
System Concepts, McGrawHill Education
C.J. Date (2003). An
Introduction to Database
Systems, 8 th Edition,
Addison Wesley
Thomas Connolly, Thomas
M. Connolly, Carolyn E.
Beg (2014). Database
Systems, Addison-Wesley
Robert Manger (2012). Baze
podataka, Element
Mladen Varga (2012).
Upravljanje podacima,
Element
129
Similar Courses
» CS-145 Introduction to Databases, Stanford
» CS270T Databases, IEEE & ACM Computing Curricula
» Models and Databases, Royal Instutute of Technology Stockholm
130
The course addresses general principles and specific methods for designing flexible
and modular software subsystems. A notion of a design pattern is introduced as a
well known and tested solution to a recurring problem in a particular problem
domain. The classifications of design patterns are considered, according to
purpose, scope, and the level of abstraction, together with the corresponding
representatives. It is assumed that the basic pieces of knowledge from the domain
of object oriented programming have been acquired on the introductory courses.
Study Programmes
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
C OM
Lecturer
T eaching Assistant
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
76
89
Prerequisites
Software Design
IP
WT
» Computer Engineering -> Computing (Module) (elective courses, 6th semester,
3rd year)
» Computer Science -> Computing (Module) (elective courses, 6th semester, 3rd year)
SEIS
Learning Outcomes
TI
CS
CE
1. Recognize symptoms of inadequate software design
2. Discuss advantages of dynamic polymorphism, templates, and duck typing
3. Explain the major principles of software design and recognize cases of their
violation
4. Evaluate the quality of multiple software designs based key design
principles
5. Recognize different design patterns in uncommented code
6. Select and apply appropriate design patterns in the construction of a
software product
7. Compare the adequateness of different design patterns in the context of a
given design problem
8. Apply design principles for conceiving high-quality software components
EEIT
English Level
C EA
Course Description
4
EP E
Izv. prof. dr. sc.
Siniša Šegvić
ECT S Credits
EC E
Lecturer in Charge
E/C
86487
Design Patterns in Software Design
EL
131
Students are trained to apply key design principles in planned construction of
high quality software subsystems. These information enable critical assessment of
different solutions to the problem at hand in software design. The presented
patterns offer an in-depth view onto common organizational challenges in
software design, as well as a pragmatic insight into advantages of novel features of
modern programming languages. By employing the acquired knowledge and
practical experience, the students will be able to improve the organization of their
software systems, as well as to clarify documentation through usage of established
pattern terminology.
F orms of Teaching
» Lectures
» The course includes two hours of lectures per week.
» Exams
» The knowledge tests include the midterm exam (35%), the final
exam (40%), two short tests in class (5%) and tests in the laboratory
(20%).
» Exercises
» The course includes four auditory exercises.
» Laboratory Work
» The course includes four laboratory exercises.
» Consultations
» Regular consultations will be held after each lecture. Ad-hoc
consultations should be arranged by e-mail.
» Seminars
» Students can be awarded additional points by presenting a seminar.
Grading System
T ype
Quizzes
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
5%
35 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
80 %
20 %
1. Introduction: importance of software organization, goals of software
design, review of development process models. Symptoms of inadequate
software organization.
2. Example: the loss of integrity due to changed requirements and the
adaptation of the design to new conditions. Review of diagrams and
programming concepts. Techniques for achieving flexible code in C, C++
and Python: dynamic and static polymorphism, duck typing.
3. Principles of logical design: the Open-closed principle, and the Liskov
substitution principle.
4. Principles of logical design: the Dependency inversion principle, the Single
responsibility principle, and the Interface segregation principle.
132
5. Principles of physical design: the desired form of the component
dependency graph, adequate stability and abstractness of packages.
6. The design pattern concept illustrated on the Strategy pattern example.
The Observer pattern.
7. The Decorator pattern. Parameterized factory. F actories which do not
depend on concrete types.
8. Midterm exam.
9. The F actory Method pattern. The Abstract factory pattern. The Singleton
pattern.
10. The Command pattern. The Adapter pattern. The Template method
pattern.
11. The Iterator pattern. The Composite pattern. The State pattern.
12. The Proxy pattern. The Bridge pattern. The Visitor pattern.
13. The Prototype pattern, the Model-View-Controller pattern.
14. Rješavanje problema za vježbu.
15. F inal exam
Literature
Erich Gamma, Richard
Helm, Ralph Johnson, John
Vlissides (1995). Design
Patterns, Addison-Wesley
Professional
Robert C. Martin (2002).
Agile Software Development:
Principles, Patterns, and
Practices, Prentice Hall
John Lakos (1996). LargeScale C++ Software Design,
Addison-Wesley
Professional
Andrei Alexandrescu (2001).
Modern C++ Design: Generic
Programming and Design
Patterns Applied, AddisonWesley Professional
Similar Courses
» Design Patterns, Oxford
» SE/SoftwareDesign, SE/ComponentBasedComputing, IEEE & ACM
Computing Curricula
» Software Architecture, ETH Zurich
» Patterns in Software Engineering, TU Munchen
133
Study Programmes
» Information Processing -> Computing (Module) (elective courses, 6th semester,
3rd year)
year)
Study Hours
Lecturers
45
15
Lecturers
Doc. dr. sc. Boris Milašinović
Dr. sc. Ivana Nižetić Kosović
Nenad Katanić, mag. ing.
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
70
Excellent (5)
85
The final grades are assigned
according to fixed thresholds.
EEIT
L1
C OM
E-learning Level
C EA
L0
EP E
This course elaborates software engineering concepts, principles and techniques.
The course studies approaches to the development of end user applications,
including requirements analysis and specification, design and construction of
software components, programming techniques, documentation, implementation
and maintenance of applications.
English Level
EC E
Course Description
4
EL
Prof. dr. sc.
Krešimir F ertalj
ECT S Credits
WT
Lecturer in Charge
E/C
34283
Development of Software Applications
Prerequisites
Databases
IP
SEIS
Learning Outcomes
CS
CE
Differentiate and define project lifecycle
Reproduce adequate programming techniques
Apply development tools and groupware
Identify software requirements
Design and create software components
Produce user and program documentation
Analyze user requirements
Distinguish key software architecture concepts
TI
1.
2.
3.
4.
5.
6.
7.
8.
The course will prepare students for development of complex interactive
applications, particularly database applications. The course will provide a
knowledge for successful design, construction and implementation of application
software. Students will be able to formulate the software requirements and to
develop, implement and maintain quality software built upon different software
architectures.
134
F orms of Teaching
» Lectures
» Lectures are conducted in two cycles. The first cycle contains 7 weeks
of lectures followed by the second cycle of 6 weeks, with teaching
load of 3 hours per week.
» Exams
» Assessments include interim exam, final exam and short computerbased tests.
» Laboratory Work
» Laboratory exercises are carried out in the weeks of lectures, one
hour per week.
» Consultations
» Consultations have been organized in all weeks except weeks of
exam.
» Other
» Homework.
Grading System
T ype
Homeworks
Quizzes
Class participation
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
15 %
30 %
5%
20 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
30 %
5%
0%
50 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Software engineering fundamentals. Software development life cycle.
Project definition. Project plan.
Requirements specification. Unified modeling language basics.
Coding standards. Programming techniques.
Graphical user interface.
Data access logic.
Object-relational mapping.
Mid-term exam.
Software archituectures.
Multi-layer applications.
Universal and self-adaptable program modules. Report design.
Web applications.
Service oriented architecture.
Interactive help and software documentation. Software release.
F inal exam.
135
Literature
Roger S. Pressman (2009).
Software engineering: A
Practitioner`s Approach;,
McGraw-Hill Science
Ian Sommerville (2010).
Software engineering,
Addison Wesley
Steve McConnell (2004).
Code Complete: A Practical
Handbook of Software
Construction, Microsoft
Press
Stephen R Schach (2010).
Object-Oriented and Classical
Software Engineering,
McGraw-Hill Science
Andrew Troelsen (2010). Pro
C# 2010 and the .NET 4
Platform, Apress
Similar Courses
» Software Engineering and Design, Cambridge
» Software Development, IEEE & ACM Computing Curricula
136
Study Programmes
(required course, 1st semester, 1st year)
Learning Outcomes
1. Choose the appropriate level of standard combinational and sequential
components to design simple digital circuits
2. Design simple combinational and sequential digital circuits
3. Analyze simple combinational and sequential digital circuits
4. Apply Boolean algebra as a formalism for describing of combinational and
sequential digital circuits
5. Apply the VHDL hardware description language in modeling and
simulation of simple combinational and sequential digital circuits
6. Identify and classify standard and programmable combinational and
sequential digital circuits
7. Recognize the limitations represented by dynamic and electrical properties
of digital circuits and their interconnections
Students will gain fundamental knowledge on the structure of digital systems,
based on levels of characteristic logic circuits and subsystems, as well as on
applying basic methods of digital systems analysis and design, both combinational
and sequential. Students will be qualified to carry out basic design procedures
using standard and programmable modules, under physical constraints imposed
by both dynamic and electrical characteristics of circuits and their interconnections.
Davor Jadrijević
Dr. sc. Darijan Marčetić
Dr. sc. Mario Matijević
Dr. sc. Mia Suhanek
Ivan F ilković, mag. ing. comp.
Nikolina F rid, mag. ing.
comp.
Marko Pavelić, mag. ing.
Denis Salopek, mag. ing.
Martin Soldić, mag. ing.
Marko Zec, dipl. ing.
Grading
Acceptable (2)
50
Good (3)
62
Very Good (4)
75
Excellent (5)
88
The scoring awarded under
Class participation is intended
as a corrective factor of the
final objective scoring through
other types of assessment and
represents the subjective
instructor's evaluation of the
student.
Prerequisites for
137
EEIT
C OM
C EA
Lecturers
Izv. prof. dr. sc. Ivan Đurek
Izv. prof. dr. sc. Mario Kušek
Izv. prof. dr. sc. Tomislav
Pribanić
Doc. dr. sc. Tomislav Hrkać
Dr. sc. Danko Ivošević
EP E
60
15
EC E
Study Hours
Lecturers
EL
L1
WT
Digital systems process in discrete steps real-world values previously converted
into numbers. As within digital systems data are given a binary representation,
what is based on both theoretical and technological grounds, digital systems are
based upon logic circuits. The objective of the course is to introduce students to
fundamental principles of digital systems design, starting with the elementary
procedures of analysis and design. Elementary combinational and sequential
components and modules are elaborated too, as well as the inclusion of digital
systems in the real world.
E-learning Level
IP
Course Description
L1
SEIS
Izv. prof. dr. sc.
Zoran Kalafatić
English Level
CE
Izv. prof. dr. sc.
Miljenko Mikuc
6
CS
Prof. dr. sc.
Vlado Glavinić
ECT S Credits
TI
Lecturers in Charge
E/C
19674
Digital Logic
F orms of Teaching
» Lectures
»» Exams
»» Laboratory Work
»» Consultations
»-
Grading System
T ype
Homeworks
Quizzes
Class participation
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
15 %
10 %
5%
10 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
15 %
0%
0%
0%
0%
85 %
Comment:
Short evaluations will be in principle performed by assigning short tests during
the lectures.
1. Introduction and course overview. Analog values and their digital
representation. Binary system, binary arithmetic, basic operations:
addition, subtraction, multiplication.
2. Binary codes and coding. Error detecting and error correcting codes.
3. Propositional logic, Boolean algebra, Boolean functions, canonical forms for
Boolean functions. Minimization of Boolean functions: algebraic, Karnaugh
maps.
4. Quine-McCluskey method for minimization of Boolean terms.
Incompletely specified functions. Delay and hazard.
5. Basic logic circuits: AND, OR, NOT, NAND, NOR, EX-OR. Transistor
(CMOS) level implementation of Boolean functions.
Integrated digital circuits. Electrical characteristics.
6. Standard combinational modules: decoders, demultiplexors, multiplexors,
ROMs, priority encoders, comparators. VHDL models of combinational
modules. Standard combinational module implementation of Boolean
functions.
7. Arithmetic circuits: adders, carry look-ahead generators, subtractors,
multipliers, shifters.
8. Midterm examination.
9. Programmable modules: PLDs and F PGAs. Programmable module
implementation of Boolean functions.
10. F lip-flops: basic latch, flip-flop, flip-flop types, triggering, dynamic
parameters.
138
11. Sequential circuits, finite state machines, Moore and Mealy automata, state
diagram and table. Design of synchronous sequential circuits, state
minimization, state coding. Analysis of synchronous sequential circuits.
12. Standard sequential modules: registers, shift registers, counters - ripple and
synchronous.
13. Memories: characteristic parameters; static and dynamic memories;
memory modules organization.
14. Interfacing digital systems with the analog environment, D/A and A/D
conversion.
15. F inal examination.
Literature
U. Peruško, V. Glavinić
(2005). Digitalni sustavi,
Školska knjiga
S. D. Brown, Z. G. Vranešić
(2001). Fundamentals of
Digital Logic with VHDL
Design, McGraw-Hill
Similar Courses
» Digital Logic, IEEE & ACM Computing Curricula
» Digital Systems, University of Toronto
» Digitaltechnik, ETH Zurich
» Systèmes logiques (Logic Systems), EPF L Lausanne
» Digital System Design, Montreal
» Digitale Verarbeitungssysteme, Hamburg
139
Video signal production and presentation. Image analysing parameters. Image
formats. Color spaces, system nonlinearity, gamma correction and constant
luminance principle. Component video and interfaces (S-Video, SCART, SDT V,
HDT V, D-konektor, VGA). Analog-to-digital video signal conversion. Digital
video formats. Digital video interfaces (SDI, SDTI, DVI-D, DVI-I, USB 2.0, IEEE
1394). Digital video processing. Brightness, contrast, saturation and hue
manipulation. Simple and advanced special effects. Video compression
parametres, overview of compression techniques and standards, applications.
F ormats for uncompressed digital video storage and recording. Linear and nonlinear editing. Content-based digital video description.
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
C OM
Lecturer
Dr. sc. Jelena Božek
C EA
T eaching Assistant
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
---
EEIT
English Level
50
60.5
75.5
89.5
EP E
Course Description
4
EC E
Prof. dr. sc.
Mislav Grgić
ECT S Credits
EL
Lecturer in Charge
E/C
34322
Digital Video
Prerequisites
WT
Study Programmes
SEIS
IP
» Information Processing -> Computing (Module) (elective courses, 6th semester, 3rd
year)
CE
Learning Outcomes
Interpret basic terms in video production and digital video processing
Describe methods for digital video processing
Distinguish image and video compression systems and algorithms
Explain image and video compression standards
Analyze image and video quality
Operate with nonlinear video editing
TI
1.
2.
3.
4.
5.
6.
CS
Upon completion of the course students will understand differences between
analog and digital video. They will have extensive theoretical knowledge about
digital video formats, interfaces and standards. Students will have the ability to
make their own digital video editing.
140
F orms of Teaching
» Lectures
» --» Exams
» --» Laboratory Work
» --» Consultations
» --» Internship visits
» ---
Grading System
T ype
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
15 %
40 %
45 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
85 %
15 %
1. Video production and scanning parameters, image formats, amplitude and
frequency range of video signal, temporal relationships
2. Color spaces (RGB, YUV, YIQ, YCrCb), Constant Luminance Principle,
system nonlinearity and gamma correction
3. Component video formats and interfaces (S-Video, SCART, SDTV, HDTV,
D-Connector, VGA)
4. Analog-to-digital video conversion, quantization error, signal-to-noise
ratio
5. Digital video formats and interfaces (parallel interace, SDI, SDTI, HDSDTI, DVI, USB 2.0, IEEE 1394)
6. Color system conversions, 4:4:4 YCrCb to 4:2:2 YCrCb conversion, 4:2:2
YCrCb to 4:2:0/4:1:1 YCrCb conversion
7. Brightness, contrast, saturation and hue manipulation, display
enhancement
8. Mid-term exam
9. Resolution scaling, frame rate conversions, scanning conversions
10. Simple and advanced special effects: chroma keying, video mixing, spatial
effects, rotations, different angle views, adding titles
11. Video compression parametres, compression techniques overview, video
compression standards (M-JPEG, DV, MPEG-1, MPEG-2, MPEG-4, H26x)
12. Application of video compression standards, content-based digital video
description (MPEG-7)
13. F ormats for uncompressed digital video recording (D-1, D-2, D-3, D-5, D6), error detection and correction, interleaving, synchronization
14. F ormats for compressed digital video recording (Digital Betacam, Betacam
SX, IMX, DV, DVCPRO, Digital S, DVD)
15. Editing types, linear and non-linear editing; non-linear editing system
architecture; time coding, editing points; special effects
141
Literature
J. Watkinson (2001). An
Introduction to Digital Video,
F ocal Press, Oxford
A. C. Luther (1997).
Principles of Digital Audio and
Video, Artech House,
Norwood
C. Poynton (2003). Digital
Video and HDTV - Algorithms
and Interfaces, Morgan
Kaufmann Publishers, San
F rancisco
Similar Courses
» Digitales Video, TU Munchen
» Digital Video Production, Royal Instutute of Technology Stockholm
142
Course Description
Selected topics of discrete mathematics and mathematical analysis, with emphasis
on solving complex examples and tasks, based on algorithmic approach.
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
60
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
70
80
Prerequisites
Mathematics 1
EC E
Study Programmes
WT
EL
(courses for exceptionally successful students, 2nd semester, 1st year)
and Information Technology and Computing (Study) (courses for exceptionally
successful students, 4th semester, 2nd year)
Computing (Study) (courses for exceptionally successful students, 4th semester, 2nd
year)
IP
Learning Outcomes
SEIS
CS
CE
Understand the principles and analysis of complex algorithms.
Apply the technique of recursive relations, in various situations.
Apply complex terchniques of calculations of finite sums.
Analyse the complexity of an algortihm.
Undersand the connection between various mathematical structures.
Use the technique of generating functions in various situations.
Understand the principles of cyphers and coding.
Analyze the principles of sorting and searching algorithms.
TI
1.
2.
3.
4.
5.
6.
7.
8.
The course enables students to a deeper understanding of the basic modern
mathematical structures, mainlz in the field of discrete mathematics,
combinatorics, number theory and analysis of algorithms.
F orms of Teaching
» Lectures
» Lectures are organized through two cycles. The first cycle consists of
7 weeks of classes and mid-term exam, a second cycle of 6 weeks of
classes and final exam. Classes are conducted through a total of 15
weeks with a weekly load of 4 hours.
EEIT
6
C OM
Prof. dr. sc.
Neven Elezović
ECT S Credits
C EA
Lecturer in Charge
E/C
90094
EP E
143
» Exams
» Mid-term exam in the 8th week of classes and final exam in the 15th
week of classes.
» Consultations
» Consultations are held one hour weekly according to arrangement
with students.
Grading System
T ype
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
20 %
2%
20 %
40 %
40 %
Homeworks
Class participation
Seminar/Project
Exam: Written
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
10 %
20 %
0%
80 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Introductory example - The Tower of Hanoi
F inite sums
Binomial coefficients. Combinatorial identities
Walks on integer latices. Generating functions.
Binomial series. Polynomial formulae. Increasing and decreasing factoriels.
F inite differences.
Recursions. Sequences given by recursive formulas. Examples.
F ibonacci numbers.
Exams
Euler and Stirling numbers. Sum of powers. Bernoulli numbers.
Elementary inequalities.
Means. Inequality between means. Symmetric functions.
Euclid's algorithm, divisibility. Relatively prime numbers. Congruences.
Prime numbers. F ermat's and Wilson's Theorem. Applications.
Basic search and sorting algorithms and their complexity.
Exam.
Literature
M. Aigner (2007). A Course
in Enumeration, Springer
R. Graham, D.E. Knuth, O.
Patashnik (2004). Concrete
Mathematics, 2ed, AddisonWesley
M.W. Baldoni, C. Ciliberto,
G.M.P. Cattane (2009).
Elementary Number Theory,
Cryptography and Codes,
Springer
J. Herman, R. Kučera, J.
Šimša (2000). Equations and
Inequalities, Springer
N. Ya. Vilenkin (1971).
Combinatorics, Academic
Press
144
Similar Courses
» MATH 108: Introduction to Combinatorics and Its Applications, Stanford
145
Course Description
Selected topics of discrete mathematics and mathematical analysis, with emphasis
on solving complex examples and tasks, based on algorithmic approach.
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
60
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
70
80
Prerequisites
Mathematics 2
EC E
Study Programmes
TI
CS
CE
SEIS
IP
WT
EL
successful students, 3rd semester, 2nd year)
Computing (Study) (courses for exceptionally successful students, 3rd semester, 2nd
year)
Technology (Module) (courses for exceptionally successful students, 5th semester, 3rd
year)
year)
Information Technology (Module) (courses for exceptionally successful students, 5th
semester, 3rd year)
(courses for exceptionally successful students, 5th semester, 3rd year)
(Module) (courses for exceptionally successful students, 5th semester, 3rd year)
» Information Processing -> Computing (Module) (courses for exceptionally
successful students, 5th semester, 3rd year)
» Computer Engineering -> Computing (Module) (courses for exceptionally
» Computer Science -> Computing (Module) (courses for exceptionally successful
students, 5th semester, 3rd year)
» Telecommunication and Informatics -> Computing (Module) (courses for
exceptionally successful students, 5th semester, 3rd year)
EEIT
6
C OM
Prof. dr. sc.
Neven Elezović
ECT S Credits
C EA
Lecturer in Charge
E/C
90095
EP E
146
Learning Outcomes
1. Understand the principles of numerical calculation of some elementary
functions.
2. Understand the principles of varyous types of approximations.
3. Use the technique of approximatrion of a function by orthogonal
polynomials.
4. Use the technique of fast summing algorithms.
5. Use the technique of acceleration of the convergence of some numerical
series.
6. Understzand the asymptotical convergence and its application in
calculations of values of some special functions.
7. Learn how to use modern mathematical literature
8. Lear how to use mathematical software in solving of complex problems.
Learning advanced and modern techniques of evaluation of the values of some
functions and various forms of its approximations.
F orms of Teaching
» Lectures
» Exams
week of classes.
» Consultations
with students.
» Other
» Student's seminars.
Grading System
T ype
Homeworks
Seminar/Project
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
10 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
20 %
10 %
0%
60 %
1. Evaluation of values of functions. Horner's algorithm. F ast summation
algorithm. identities.
2. Solving algebraic equations
3. Acceleration of convergence. Manipulation with series.
147
4. The connection between integrals and sums. Complex techniques of
summing.
5. Continued fractions. Basic properties and formulas.
6. Representation of numbers and functions by continued fractions. Rational
approximations.
7. Orthogonal polynomials. Polynomials given by reccursive relations.
Applications of fast summing algorithms
8. Exam
9. Čebyšev's polynomials and problem of approximations. F ast calculations
of F ourier series.
10. Series of functions. Generating functions of functional series. Ztransformation
11. F actorial and gamma functions. Stirling formula. Approximations of
binomial coefficients.
12. Asympthotic behaviour. Asymptotic series.
13. Harmonic series and related problems. Euler constant.
14. Student seminar. Solution of advanced problems
15. Exam
Literature
F . S. Acton (1990). Numerical
Methods That Usually Work,
Mathematical Association
of America
J. Borwein J, D. Bailey, R.
Girgensohn (2004).
Experimentation in
Mathematics, Computational
Paths to Discovery, A. K.
Peters
Z. A. Melzak (1973).
Companion to Concrete
Mathematics, Mathematical
Techniques and Various
Applications, John Wiley &
Sons
A. Cuyt et al (2008).
Handbook of Continued
Fractions for Special
Functions, Springer
G. Boros, V. Moll (2004).
Irresistible Integrals Symbolics, Analysis and
Experiments in the Evaluation
of Integrals, Cambridge
University Press
Similar Courses
» Numerical analysis, EPF L Lausanne
148
F undamentals of economics. Microeconomics and macroeconomics. Key concepts
in economics - opportunity cost, the cost and benefits, market. Circular flow of
economy. Production possibilities frontier. Law of supply. The law of demand.
Market equilibrium and social welfare. The elasticity of supply and demand.
Consumer behavior. Production costs. Market structures - perfect competition,
monopoly, monopolistic competition, oligopoly. Antitrust and regulation.
Assessment of investment projects. Risk analysis. Introduction to financial
markets.
Study Programmes
and Information Technology and Computing (Study) (required course, 4th
semester, 2nd year)
Study Hours
Lecturers
45
C OM
Lecturers
Izv. prof. dr. sc. Dubravko
Sabolić
Dr. sc. Mihaela Vranić
E/C
L1
EEIT
E-learning Level
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
Participation in teaching
brings 10% points, homework
20% points, mid-term exam
30% points, final exam 44%
points.
Prerequisites
C EA
Course Description
L1
EP E
Prof. dr. sc.
Roman Malarić
English Level
EC E
Izv. prof. dr. sc.
Željko Tomšić
4
EL
Prof. dr. sc.
Željko Štih
ECT S Credits
IP
Lecturers in Charge
41251
WT
Economics and Managerial Decision Making
SEIS
Learning Outcomes
CE
TI
CS
1. Explain functioning of competitive markets based on the laws of supply
and demand
2. Idenify key factors influencing decision making in the firm
3. Distinguish between different market structures influencing market
position of a firm
4. Recognise the role of the state in the competitve market
5. Calculate cost-effectivness of different investment options by using simple
profitability estimationmethods
6. Idetify risks related to the investments and participation in the market
7. Recognise different instruments offerd at finacial markets
The main objective of the course is to teach students basic economic concepts. By
the end of the course students should: comprehend the concepts and other tools
that economists use to address economic issues; be able to practically apply these
concepts and tools in engineering practice.
149
F orms of Teaching
» Lectures
» Lectures are performed every week except in weeks when exams
take place. Weekly lecture load is 2hours. Every lecture ends with
brief examination of students' understanding of the subject by
answering few short questions.
» Exams
» There are two examinations during the lectures and three on-line
examinations using Moodle system.
» Consultations
» Lecturers are available for consultations any time upon agreement,
via e-mail or in person.
» E-learning
» Through Moodle system students get additional literature for
reading, examples of calculations and possibility for self-testing.
Grading System
T ype
Homeworks
Attendance
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
10 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
20 %
10 %
0%
30 %
40 %
Comment:
The exam is successfully passed if minimally 50 points out of 100 is collected.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Introduction to economics
Supply and demand: theory
Microeconomics fundamentals
Consumer behavior
Production and costs
Market structures 1
Market structures 2
Exam
Exam
Antitrust and regulation
Assessment of investment projects 1.
Assessment of investment projects 2.
Risk analysis 1.
Risk analysis 2.
Introduction to financial markets
150
Literature
Dominick Salvatore (1994).
Ekonomija za menadžere u
svjetskoj privredi, Mate d.o.o.
Paul A. Samuelson, William
D. Nordhaus (2011).
Ekonomija, McGraw-Hill /
Mate d.o.o.
A. Koutsoyiannis (1997).
Moderna mikroekonomika,
Mate d.o.o.
Silvije Orsag (2002).
Budžetiranje kapitala:
Procjena investicijskih
projekata, Masmedia
Roger A. Arnold (2010).
Microeconomics, SouthWestern/Cengage Learning
Similar Courses
» Principles of Microeconomics, ETH Zurich
151
Basic actuator classification. The importance and the application areas of
electromechanical, hydraulic and pneumatic actuators. Electromagnet and
electrical motor as an actuator. Electrical starter. Parameters, characteristics and
mathematical models of electromechanical actuators. Characteristics of DC,
synchronous, reluctance, inductor and hysteresis motors. Induction motors for
automation. Brushless DC motor. Tachogenerators. Permanent magnet motors.
Stepping motor. Nano actuators.
E-learning Level
L1
Study Hours
Lecturers
Exercises
26
4
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
61
71
86
EEIT
L1
C OM
English Level
C EA
Course Description
4
EP E
Izv. prof. dr. sc.
Mario Vražić
ECT S Credits
Prerequisites
F undamentals of Electrical
Engineering
EC E
Lecturer in Charge
E/C
86458
Electrical Actuators
EL
Study Programmes
WT
(currently not given)
IP
Learning Outcomes
CE
Classify basic actuators groups
Describe importance and the application areas of actuators
Explain operation principles of actuators
Identify actuators characteristics
Compare actuators eficency
Select actuators for industrial purpose
CS
1.
2.
3.
4.
5.
6.
SEIS
TI
The knowledge of properties and characteristics of actuators relevant for their
application is acquired.
F orms of Teaching
» Lectures
» in two cycle; 6+5 lecture
» Exams
» labs, exams
» Exercises
» an exercise at the end of each lecture ciklus
» Laboratory Work
» Three labs in groups in department laboratory
152
Grading System
T ype
T hreshold
F inal Exam: Oral
Exam: Written
Exam: Oral
60 %
20 %
20 %
Percent of
Grade
20 %
20 %
20 %
40 %
Exam
T hreshold
Percent of
Grade
60 %
0%
20 %
30 %
20 %
60 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Basic actuator classification (electromechanical, hydraulic and pneumatic)
The importance and the application areas of actuators.
Electromagnet as an actuator.
Electrical motor as an actuator.
Electrical starter.
Parameters and characteristics of electromechanical actuators
Exercise
Midterm exam
Characteristics of DC, synchronous, reluctance, inductor and hysteresis
motors.
Induction motors for automation.
Brushless DC motor. Permanent magnet motors.
Stepping motors.
Nano actuators.
Exercise
F inal exam
Literature
Radenko Wolf (1991).
Osnove električnih strojeva,
Školska knjiga, Zagreb
T. Kenjo (1991). Stepping
Motors and their
Microprocessor Controls,
Clarendon Press
J.R. Hendershot Jr., TJE
Miller (1994). Design of
Brushless Permanent-Magnet
Motors, Clarendon Press
T.A. Lipo (2004).
Introduction to AC Machine
Design, WisPERC,
University of Wisconsin Madison, USA
M. Jufer (1979).
Electromécanique, Dunod
153
Similar Courses
» Einführung in Aktorik, Cambridge
» Grundlagen electromechanischer Aktoren, TU Munchen
» Elektrische Aktoren, TU Munchen
» Elektrische Kleinmaschinen, TU Munchen
» Praktikum Geregelte elektrische Aktoren, TU Munchen
» Small electrical machines, TU Wien
154
Study Programmes
and Information Technology and Computing (Study) (required course, 3rd
semester, 2nd year)
Learning Outcomes
1. Define real electrical component and circuit models.
2. Apply physical laws and mathematical tools for solving el. circuit
problems.
3. Use Laplace transform in electrical circuita.
4. Solve electrical circuit using loop, node and state equations.
5. Calculate imitances, transfer functions and characteristic frequencies.
6. Analyze electrical circuit in time and frequency domains.
7. Analyze and create simple one-, two-ports and electrical filters.
8. Analyze transmission lines and signal transfer.
Study Hours
Lecturers
75
15
Prerequisites
Engineering
Mathematics 2
EP E
EC E
EL
Grading
Acceptable (2)
50
Good (3)
62
Very Good (4)
75
Excellent (5)
90
To pass the exam, a student
must have a minimum of 50%
of the points from the middle
and final exams, and 50% of
the total points, and must
complete all 6 laboratory
exercises.
C EA
C OM
Doc. dr. sc. Darko Vasić
Dr. sc. Ana Sović Kržić
Marko Gulin, mag. ing. el.
EEIT
L1
WT
Basic definitions, terms, clasification, and properties of electrical circuits, elements,
modelling, network transformations. Network theorems, electrical signals
definition and signal properties, Laplace transform, application to basic signals,
application to simple circuits, circuit equations, graphs and networks, definition
of branch, node, tree fundamental loop, and cutsets, application ofr graph theory
to circuit equations, solution of circuit equations in time and frequency domain,
network functions, transfer functions, frequency response, immitance functions, LC
and RC immitances, twoports, twoport parameters: z, y, a, h, and g, twoport
interconections, basic filter circuits, gain and phase response, electrical
transmission lines, definition, time and space signal distribution, reflections.
E-learning Level
IP
Course Description
L2
Prerequisites for
SEIS
Izv. prof. dr. sc.
Doc. dr. sc.
Igor Lacković Zvonko Kostanjčar
English Level
CE
Izv. prof. dr. sc.
Dražen Jurišić
7
CS
Prof. dr. sc.
Neven Mijat
ECT S Credits
TI
Lecturers in Charge
E/C
31489
Electrical Circuits
155
Acquiring the basic knowledge on electrical circuit concepts, their properties, and
methods for solving the electrical circuit problems. Understanding the basic
principles of electrical circuits and their properties. Understanding nodal and
mesh analyses of simple circuits. Understanding the basic time and frequency
properties of signals and circuits. Understanding 1st and 2nd order transients in
RC and RLC circuits. Ability to perform the analyses of electrical circuits in time
and frequency domain. Ability to design simple circuits according to given
specifications. Understanding the basic elements for computer aided circuit
analysis and design. Understanding the basic principles of signal prosessing and
transmission.
F orms of Teaching
» Lectures
» Material is tought using Power point presentation and blackboard.
Lectures are organized together with laboratory exercises. Lectures
also include auditory excercises. Using Moodle system students also
solve domestic exercises.
» Exams
» Examinations are organized after each of six lecture cycles. The
points are cummulatively added. There exist midterm and final
exams, as well as, repeated exam.
» Laboratory Work
» The goal is to introduce electrical components and present
measurement equipment and measurement procedures. Individual
practical experience in laboratory in applying the concepts that are
taught in lectures.
» Consultations
» Organized upon request.
Grading System
T ype
Homeworks
Attendance
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
15 %
8%
2%
35 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
8%
2%
0%
75 %
Comment:
To pass the exam, a student must: -have a minimum of 50% of the points from the
middle and final exams, -have a minimum of 50% of the total points, -must
complete all 6 laboratory exercises. Possible changes in scoring and grading will
be announced on the first lecture.
1. Definitions and basic laws. Electric circuit elements. Modelling of real
passive and active circuit components.
2. Kirchhoff laws. Circuit theorems. Network transformations.
3. Electric signals and Laplace transform.
156
4. Loop, node and, state equations. Circuit equations in time domain.
Application of Laplace transform to circuit equations.
5. Linear graphs and networks. Circuit analysis using graph theory.
6. RC, RL and RLC circuit responses. Solution of circuit equations. Sinusoidal
steady state analysis.
7. Midterm
8. Network functions. Natural frequencies. F requency response.
9. Bode diagrams. Immitance functions.
10. One-port circuits.Two-port circuits. Interconnection of two-ports.
Reactance circuits.
11. Transfer functions of RLC circuits. Passive electrical filters.
12. Active circuits. Active electrical filters.
13. Transmission lines. Time and space signal distribution.
14. Special cases of transmission line.
15. F inal exam
Literature
V. Naglic (1992). Osnovi
teorije mreža, Sveučilišna
naklada
J. Vlach (1992). Basic
Network Theory with
Computer Applications, Van
Nostrand
A. M. Davis (1998). Linear
Circuit Analysis,
Brooks/Cole, Pacific Grove,
CA, USA
A. B. Carlson (2000).
Circuits, Brooks/Cole,
Pacific Grove, CA, USA
Similar Courses
» 227-0001-00L Netzwerke und Schaltungen II, ETH Zurich
» 74102 Schaltungstechnik 2, TU Munchen
» TU Delft Nizozemska ET1150 Lineaire Elektrische Ci, TU Delft
» EE 101B, Circuits II, Stanford
» EE100: Electronic Techniques for Engineering, University of California
Berkeley
157
Study Programmes
Study Hours
Lecturers
Exercises
13
4
30
Lecturer
Dr. sc. Martina Kutija
C EA
Doc. dr. sc. Igor Erceg
Tin Bariša, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
L1
C OM
E-learning Level
EP E
DC machines, the principle of operation, and control. DC machine control using an
industrial converter, industrial converter parameter settings, example of the
industrial project. Induction machine: physical model, the principle of operation,
the mathematical model, the principle of control. Torque characteristic of
induction machine, control methods: V/f and vector control, open and closed loop
control. Control of induction machines using a frequency converter, the converter
structure, the principle of work. The fundamentals of vector control, energy flows
in converter. Laboratory setup for the control of induction machines and BLDC
machines. Control of BLDC machines. Control of synchronous machines.
L1
50
60
75
90
Prerequisites
Engineering
EC E
Course Description
English Level
EL
Doc. dr. sc.
Damir Sumina
4
WT
Prof. dr. sc.
F etah Kolonić
ECT S Credits
IP
Lecturers in Charge
E/C
86502
Electrical Machines Control Practicum
SEIS
Learning Outcomes
CS
Distinguish the types of electrical machines and their basic characteristics
Apply control structure for DC machine
Apply control structure for AC induction machine
Apply control structure for brushless machine (BLDC)
Apply control structure for synchronous machine
Practice with frequency converter for induction machine control
Practice with frequency converter for brushless (BLDC) machine control
Apply industrial software tools to adjust the parameters of frequency
converter
TI
1.
2.
3.
4.
5.
6.
7.
8.
CE
F undamentals of electrical machines control. Experience in the application of
frequency converter for AC induction machine and BLDC machine control.
Experience in application of industrial software tools for parameter tuning of
frequency converters, commissioning of frequency converter for AC induction
motor and BLDC motor control, recording and analysis of measured values.
158
F orms of Teaching
» Lectures
» One hour lecture per week.
» Exercises
» Before the exams are held exercises in two hours
» Laboratory Work
» The six laboratory exercises will be held in two weeks for 2 hours in
the laboratory.
» Experiments
» The lectures will take place thru experimentally commissioning of
industrial converter for DC machine control.
» Consultations
» Consultations are conducted with prior notification by email.
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
18 %
12 %
30 %
30 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
18 %
12 %
0%
40 %
30 %
1. Direct current (DC) machines: physical model, the principle of operation
2. Direct current (DC) machines: the mathematical model, the principle of
control
3. Direct current (DC) machines: control characteristics, converters for DC
machines
4. Control of DC machine using an industrial converter, the identification of
components of industrial converter
5. Setting the parameters of industrial converter for DC machine control,
example of the industrial project
6. Induction machines: physical model, the principle of work, the
mathematical model, the principle of control
7. Torque vs speed characteristic of induction machine, control methods: V/f
control and vector control, open and closed loop control
8. Mid-term exam
9. Induction motor control using frequency converter, structure of the
converter, the principle of operation
10. Basis of vector control, energy flows in the converter, generally about
industrial frequency converters (Siemens Sinamics S120)
11. Laboratory setup for the control of induction machines and BLDC machines
12. Control of BLDC machines
13. Synchronous machines: physical model, the principle of operation,
mathematical model, the principle of control
14. Control of synchronous machine connected to electrical power system,
description of industrial solution for control of synchronous machines
159
15. F inal exam
Literature
Gorislav Erceg (2002).
Inžinjerski priručnik IP3" ,
(20. Elektromotorni pogoni
str. 1017-1074), Školska
knjiga Zagreb
Werner Leonhard (2001).
" Control of Electrical drives" ,
Springer
Peter Vas (1994). " Vector
Control of AC Machines" ,
D. W. Novotny, T. A. Lipo
(1996). Vector Control and
Dynamics of AC Drives,
Similar Courses
» Projektpraktikum Antriebssysteme, TU Munchen
» Labor elektrische Antriebe, TU Wien
» Electric Drives and Controls, RWTH Aachen
» Electrical Power Drives, TU Delft
160
Introduction to electric power systems.Voltage and current stresses in switchgear
and industrial
systems.Symmetrical
and unsymmetrical
three-phase
systems.Symmetrical components. Sequence impedances. Short circuit currents in
three-phase AC systems.International Standards and specifications for calculation
of short circuit currents.Short circuit current components (peak short circuit
current, breaking current, thermal and dynamic short circuit strength).Substations
and switchgear systems design.Selection criteria and planning guidelines for
switchgear and distribution systems.Electric power transformers.Measuring
(current and voltage) transformers.Main circuit assemblies.Electric facilities and
distribution networks protection.Measuring. Overvoltage protection.Reactive
power compensation.Grounding systems.Protection against electric shock (direct
and indirect contact).
Study Programmes
L1
Study Hours
Lecturers
Exercises
45
30
15
C EA
Dr. sc. Ivan Rajšl
Perica Ilak, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
90
Prerequisites
Energy Technology
Engineering
Prerequisites for
Electric F acilities Design
SEIS
Learning Outcomes
CE
Define basic parts of electric facilities and their purposes
Identify basic parts of electric facilities on field
Describe current-voltage conditions in balanced and unbalaced systems
Solve short circuit problem on simple power system example
Employ softvare solutions for power system modeling and short circuit
calculations
6. Distinguish between different arc interrupting techniques
7. Choose adeqate electric products for specific location in the system
8. Argue about utilization of given electric product in specific location in the
system
TI
CS
1.
2.
3.
4.
5.
Having successfully completed the module, students will be able to demonstrate
knowledge and understanding of fault analysis, fundamental concepts of
substations and switchgear systems design, reactive power compensation, concept
of protection against overvoltages and electric shock, brief introduction to how
computer methods and relevant standards are applied.
EEIT
E-learning Level
C OM
L1
EP E
Course Description
English Level
EC E
Prof. dr. sc.
Ante Marušić
4
EL
Prof. dr. sc.
Slavko Krajcar
ECT S Credits
WT
Lecturers in Charge
E/C
91833
Electric Facilities
IP
161
F orms of Teaching
» Lectures
» Lectures are performed every week except in weeks when exams
take place. Weekly lecture load is 3 hours. Use of electronic student
response system.
» Exams
» There are two examinations during the lectures.
» Exercises
» Calculations are integral part of the lecture
» Laboratory Work
» NEPLAN is using for modeling and calculation of short circuits
» Consultations
» Lecturers are available for consultations any time upon agreement,
via e-mail or in person.
» Structural Exercises
» NEPLAN is using for modeling and calculation of short circuits
Grading System
T ype
Quizzes
Seminar/Project
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
33 %
33 %
33 %
33 %
Percent of
Grade
10 %
15 %
25 %
35 %
15 %
Exam
T hreshold
Percent of
Grade
33 %
33 %
0%
10 %
15 %
50 %
50 %
25 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Introduction. New directions in power systems.
Power system basics.
Three phase systems (phasors, current, voltage, symmetrical components)
Modeling of power system components 1
Modeling of power system components 1
Short circuit calculation
Main parts of facilities (buses, insulators, disconectors, circuit-breakers)
Exams
Exams
Low voltage switch devices
Power and measurement transformers, secondary systems
Connection diagrams for main circuits
Power system protection
F inal chapters (measurements, reactive power compensation, earthing,
insulation)
15. Preparations for exams
162
Literature
S. Krajcar; M. Delimar
(2011). Transparencije s
predavanja
(www.fer.hr/zvne), F ER
H. Požar (1990).
Visokonaponska rasklopna
postrojenja, Tehnička knjiga,
Zagreb
J.D. McDonald (2003).
Electric Power
Substations Engineering,
CRC Press
(http://ocw.mit.edu/index.html)
MIT OpenCourseWare (2005).
Introduction to Electric Power
Systems, MIT
J. Lewis Blackburn
(1993). Symmetrical
Components for Power
Systems Engineering,
Marcel Dekker
Power System Analysis John
Grainger, Jr., William Stevenson
McGraw-Hill 1994
Similar Courses
» Elektrische Energiesysteme, ETH Zurich
» Elektrické prístroje a stanice, Cambridge
» Power System Analysis and Protection, NU Singapore
» Power System, Basic Course, Royal Instutute of Technology Stockholm
» Power System Disign, Chalmers University
» Power Transmission, TU Munchen
» Technology of electrical devices in systems of ele, TU Munchen
163
Structure of the electric power system, Classifications, Standards. IEC standards.
Equipment definitions and terminology. Design principles. Substation project
chronology. Workflow and project sequence. Planning. Engineering design,
drawings and documentation (CAD). Construction, testing and commissioning.
Costs and F inancial Analysis. Schedules and Impacts. Substation Grade Types.
Design techniques. Bus configurations, Reliability criteria. Insulation and
insulation protection. General specification and ratings of power equipment.
Transformers. Circuit breakers. Switches. Disconnectors. Ancillary equipment.
Potential and current transformers. Substation auxiliary systems. Grounding.
Grounding design considerations.
L1
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
90
Prerequisites
Study Programmes
IP
SEIS
Learning Outcomes
Describe electrical blueprints,
Analyze current transformers,
Analyze voltage transformers,
Analyze substation technical requirements,
Choose substation elements (busbar, switching devices, transformers,
cables, grounding),
6. Apply knowledge about substation system design.
TI
CS
CE
1.
2.
3.
4.
5.
The course addresses a complete variety of substation design subjects at a level
appropriate to those relatively new to the area of substation design. It introduces
technical requirements, configuration philosophies, design practices, information
sources and work processes.
F orms of Teaching
» Lectures
» Lectures will be held two hours a week with the use of PowerPoint
presentations and overhead projectors.
» Seminars
EEIT
E-learning Level
C OM
L1
C EA
Course Description
English Level
EP E
Doc. dr. sc.
Juraj Havelka
4
EC E
Prof. dr. sc.
Ante Marušić
ECT S Credits
EL
Lecturers in Charge
E/C
34350
Electric Facilities Design
WT
164
» During semester, students will create one seminar.
Grading System
T ype
Quizzes
Class participation
Seminar/Project
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
0%
4%
12 %
4%
20 %
15 %
15 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
0%
0%
0%
20 %
0%
40 %
40 %
1. Introduction to electric power substation design. The course addresses a
complete variety of substation design subjects at a level appropriate to
those relatively new to the area of substation design.
2. Equipment definitions and terminology. Design principles. Planning.
Engineering design, drawings and documentation (CAD).
3. Relevant International Standards. IEC and HRN norms. Construction Law.
ISO 9001.
4. Designation of equipment, conductors and general functions. Graphics
symbols. IEC 750.
5. Electrical schemes. Circuit diagrams: survey diagram, circuit diagram,
equivalent circuit diagram. Main and auxiliary circuits.
6. Substation project chronology. Workflow and project sequence. Costs and
F inancial Analysis. Schedules and Impacts
7. Skills (E-plan). Quiz/Assignment. Project task (homework)
8. Design, construction and operation of electric power substations for
community acceptance and environmental. Testing and commissioning.
9. Calculation of electrical parameters for primary and secondary equipment
design. Voltage drop and loss of electric power.
10. Substation Grade Types. Design techniques. Bus configurations, Reliability
criteria. General specification and ratings of power equipment.
11. Busbar design. Insulation and insulation protection.
12. Design of power transformers, circuit breakers, switches and disconnectors.
13. Cable design. Overload and overcurrent protection.
14. Potential and current transformers for measuring and protection
15. Grounding. Grounding design considerations. Grounding testing.
Protection against overvoltage. Grounding in low-voltage networks.
165
Literature
S. Badanjak (1996). Osnove
inženjeringa u izgradnji,
Energetika marketing,
Zagreb
Yi-Nung Chung (1986).
Computer-aided design for
electrical power substations,
Lamar University
J.D. McDonald (2001).
Electric Power Substations
Engineering, CRC Press
Hrvatski Sabor (2007).
Zakon o prostornom uređenju
i gradnji, Narodne Novine
RH 76/07
Similar Courses
» Power System Design, Chalmers University
» Power Engineering, Design Project, Chalmers University
» Hochspannungsgeräte- und Anlagentechnik, TU Munchen
166
The course presents the broad field of acoustics and electro-acoustics. Basical
acoustics. Sound. Acoustic signals. The theory and characteristics of sound field.
Sound waves in closed spaces. Music and speech. Phenomena related to sound
propagation. Electroacoustical-mechanical analogies. Sound sources (spherical,
di p o l e ). Resonators, absorbers, filters. Hearing acoustics. Psychoacoustics.
Architectural and building acoustics. Absorption materials and constructions.
Noise and vibrations. Electroacoustic transducers: microphones, loudspeakers,
headphones, hydrophones and pick ups, loudspeaker box. Sound reinforcement.
Ultrasound and its applications in medicine and technology. Hydroacoustics.
Acoustical and electroacoustical measurements.
Study Programmes
E-learning Level
L1
Study Hours
Lecturers
45
15
C OM
Lecturer
C EA
Dr. sc. Mia Suhanek
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
76
89
Prerequisites
Engineering
Mathematics 1
SEIS
Learning Outcomes
CS
CE
Define the sound propagation in room or space
Analize the acoustical properties of room
Apply the electro-acoustic-mechanical analogies
Classify the impact of noise to human
Appraise the quality of electroacoustic devices
Assemble electro-acoustic systems
Astimate the application of specific acoustic materials
Analyze the effects and properties of sound in advanced technologies
TI
1.
2.
3.
4.
5.
6.
7.
8.
The subject gives the necessary qualifications for understanding of basic
electroacoustic and acoustic principles. Based on the knowledge they have gained,
the students will be able to individually solve problems from fields of acoustics,
electroacoustics and audiotechnics. Understanding the properties of human
hearing. Introduce the electro-acoustic transducers and their properties. The
students will acquire knowledge about the widespread use of ultrasound.
EEIT
L1
EP E
Course Description
English Level
EC E
Prof. dr. sc.
Hrvoje
Domitrović
4
EL
Izv. prof. dr. sc.
Siniša F ajt
ECT S Credits
WT
Lecturers in Charge
E/C
34303
Electroacoustics
IP
167
F orms of Teaching
» Lectures
» Concentrated lecture, with all the options and present. Practical
examples. Communication with students during and after school
hours.
» Exams
» Mid-term exams after half of the teaching material. F inal exam:
written and oral.
» Laboratory Work
» 6 independent laboratory exercises. The student must demonstrate
an understanding of the practice areas of practice. Each exercise
carries 2.5 points
» Experiments
» Demonstration of specific acoustic parameters. A detailed insight
into specific structures and electro-acoustical constructions.
» 2 complex exercises. Each exercise carries 2.5 points
» Consultations
» Lecturer is available to students in office hours for oral consultations,
and by email any time.
» Seminars
» Student should select a topic from relevant to the course. The theme
is mostly an introduction to the area of student interest. 20 points
Grading System
T ype
Seminar/Project
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
15 %
15 %
20 %
20 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
15 %
15 %
0%
40 %
30 %
1. Introduction. F undamentals of acoustics. The phenomena of the sound
propagation.
2. The theory and characteristics of sound field. Sound waves in closed spaces.
Acoustic signals. Music and speech.
3. Electroacoustical-mechanical analogies.
4. Sound sources (spherical, dipole) and phenomena related to sound
propagation.
5. Hearing acoustics. Psychoacoustics.
6. Communication acoustics. Architectural and building acoustics.
7. Architectural and building acoustics. Absorbers, resonators and diffusers.
8. Middle term exam
9. Environmental noise. Noise influence on human. Noise and vibrations in
architectural acoustics. Laws and regulations.
10. Measurement and evaluation of airborne and structural noise.
168
11. Ultrasound. Kind of expansion in different media. Snell's law. The main
effects. The application in technique and medicine. Hydroacoustics.
12. Electroacoustic transducers: microphones. Classification, basic properties,
applications.
13. Electroacoustic transducers: loudspeakers. Classification, basic properties,
applications.
14. Electroacoustic transducers: headphones, hydrophones, pickups.. Sound
reinforcement. Loudspeaker systems.
15. F inal exam.
Literature
B. Ivančević (2007).
Elektroakustika, Sveučilište
u Zagrebu Ur. br.: 380-2/607-4, 2007.
T. Jelaković Zagreb, (1978).
Zvuk, sluh i arhitektonska
akustika Zagreb, 1978 ,
Školska knjiga,
Marshall Long (2006).
Architectural Acoustics,
Elsevier, San Diego
H. Kuttruff (2000). Room
Acoustics, Elsevier applied
science, London
D.T. Blackstock (2000).
Fundamentals of physical
acoustics, Wiley Interscience
publication
Signals, Sound and Sensation
(Modern Acoustics and Signal
Processing), W. M. Hartmann
Amazon 1997
Elektroakustika, B. Ivančević,
Sveučilište u Zagrebu, FER,
Zagreb 2007
Similar Courses
» Akustik I, ETH Zurich
» Engineering Acoustics, University of Twente
» Engineering Acoustics, UCLA
» Elektroakustik, RWTH Aachen
» Tehnische akustik, RWTH Aachen
» technische Akustik, TU Munchen
» Akustik I, Akustik II, TU Berlin
169
The circuit concept, which was presented in subjects "F undamentals of Electrical
Engineering" and "Electric circuits", is expanded to a multi-dimensional field
concept based on Maxwell equations. The themes are: Lorentz force, electric field
strength, magnetic flux density. Sources: charge and current. Charge at rest:
Coulomb's law, Gauss's law, energy and potential in electric field. Dielectrics,
conductors, capacitance. Charge in uniform motion: Ohm's law, resistance. BiotSavart's law, Ampere's circuital law, magnetic materials, energy in magnetic field,
inductances, magnetic circuits. Time-dependent fields, F araday's law, sinusoidal
fields. Displacement currents, Maxwell equations, electromagnetic waves.
Study Programmes
semester, 2nd year)
Learning Outcomes
Study Hours
Lecturers
75
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C EA
C OM
Ivica Kunšt, dipl. ing.
F rano Škopljanac-Mačina,
dipl. ing.
Tomislav Župan, dipl. ing.
50
62
74
86
Prerequisites
Electrical Circuits
Mathematics 3 - C
Mathematics 3 - EE
Prerequisites for
TI
CS
CE
1. Explain fundamental laws of electromagnetism (Coulomb's, Biot-Savart,
F araday's and Gauss's law).
2. Apply the fundamental laws of electromagnetism to solution of
electromagnetic field problems.
3. Classify problems of electromagnetic fields into static electric, static
magnetic, static current and dynamic fields.
4. Recognize advantages of application of numerical approach to solution of
electromagnetic problems.
5. Apply calculation of electromagnetic fields, inductances and capacitances to
solution of practical problems.
6. Describe fundamental operating principles of transformers, motors and
generators.
7. Explain the relationship between electromagnetic fields and circuit
elements.
8. Analyze how energy is stored and transported in an electromagnetic field.
Understanding multi-dimensional approach to analysis of electromagnetic
phenomena. Knowledge of fundamental laws of electromagnetism formulated by
Maxwell equations, and their application to practical problems.
EEIT
L1
EP E
Course Description
E-learning Level
EC E
Doc. dr. sc.
Bojan Trkulja
L3
EL
Izv. prof. dr. sc.
Martin Dadić
English Level
WT
Prof. dr. sc.
Željko Štih
6
IP
Prof. dr. sc.
Sead Berberović
ECT S Credits
SEIS
Lecturers in Charge
E/C
86459
Electromagnetic Fields
170
F orms of Teaching
» Lectures
» Exams
» Laboratory Work
» Consultations
Grading System
T ype
Quizzes
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
10 %
6%
30 %
30 %
24 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
10 %
6%
24 %
60 %
24 %
1. F undamental postulates: conservation of charge. Lorentz force: electric field
strength, magnetic induction. Charge in motion in electric and magnetic
field. Macroscopic and microscopic approach. F ield sources: charge and
current. Volume, surface, line and point sources. Continuity equation.
Static electric field in vacuum. Coulomb's law.
2. Electric field strength. Electric field of point charge and of continuous
charge distributions. Electric flux. Gauss's law. Potential in electric field,
voltage. Integral equations of potential of point charge and of continuous
charge distributions. Visual presentation of electric field: field lines and
equipotentials.
3. Relationship between field strength and potential. Curl of electric field.
Materials in electric field. F ield and charge in a conductor.
4. Polarization of dielectric, vector of electric flux density and permittivity.
Boundary conditions. Laplace’s and Poisson’s differential equation of
potential. Method of images in static electric field. Energy in electric field:
system of point charges, volume charge density, energy expressed by field
vectors.
5. Condensers and capacity. Energy in condenser. F orces in electric field.
Laboratory 1: Coulomb's law, permittivity. Energy in electric fields
(experiments).
6. Charge in uniform motion - first Kirchhoff's law. Equations of static current
field - analogies and imaging. Conductor-insulator boundary conditions.
Ohm’s law, resistance. Joule's law. Electromotive force - second Kirchhoff's
law. Static magnetic field in vacuum. Biot-Savart's law. Magnetic force on
the current carrying conductor. Magnetic flux, Gauss's law. Laboratory 2:
Application of numerical finite element software software in calculation of
static electric fields
7. Mid-term exam
8. Mid-term exam
9. Ampere’s circuital law. Magnetic vector potential: differential and integral
equation of potential. Visual presemtation of magnetic filed. Magnetic
materials, magnetization.
171
10. Magnetic field strength and permeability, types of magnetic materials,
permanent magnets. Boundary conditions. Energy in magnetic field: current
loop in magnetic field, system of current loops, energy expressed by field
vectors, energy in linear and non-linear materials. Inductance and mutual
inductance.
11. F orces in magnetic field. Magnetic circuits.Laboratory 3: Magnetic field on
the axis of a multilayer air-core solenoid. Energy of a linear solenoid.
Hysteresis (experiments).
12. Quasistatic fields. F araday’s law of electromagnetic induction: voltage
induced in a conductor which is moving in static magnetic field, voltage
induced in static loop which is in quasistatic field. Lenz's rule. Applications:
generator, transformer. Voltages induced due to self-induction and mutual
induction. Eddy currents. Laboratory 4: Application of numerical finite
element software in calaculation of magnetic circuits.
13. Extension of Ampere's circuital law, displacement current. Maxwell’s
equations in differential and integral form. Energy and power flow.
Poynting’s theorem.
14. Sinusoidal time varying fileds. Energy and power flow, Poynting's
theorem. Electromagnetic waves in free space. Plane wave. Constants of
wave propagation: impedance, wave length, phase velocity, phase
constant. Laboratory 5: Transformer. Helmholtz coils. Levitating ring.
Velocity of electromagnetic waves in dielectric (experiments).
15. Electromagnetic waves in real dielectrics and conductors. Attenuation
constant and depth of penetration. Energy flow. Classification of materials
to dielectrics and conductors. Skin effect. Polarization. Laboratory 6:
Application of finite element software in calculation of a levitating ring.
Literature
Z. Haznadar, Ž. Štih (1997).
Elektromagnetizam I, Školska
knjiga
Elektromagnetizam II,
Školska knjiga
S. Berberović (1998).
Teorijska elektrotehnika odabrani primjeri, Graphis
Electromagnetic Fields, Waves
and Numerical Methods, IOS
Press
S.V. Marshall, G.G. Skitek
(1990). Electromagnetic
Concepts and Applications,
Prentice-Hall
Engineering Electromagnetics
W.H. Hayt McGraw Hill 198 8
Similar Courses
» 6.630 Electromagnetic Theory, MIT
» Elektromagnetische F eldtheorie, TU Munchen
172
Theoretical and practical introduction with electromagnetic transients and the
associated problems of ElectroMagnetic Compatibility (EMC). Analytical and
numerical problems solving of transients in electrical networks. Oscillatory
circuit. Transients in circuits with linear and nonlinear elements. Switching-in of
un unloaded and short-circuited transmission line. Inrush currents of an unloaded
transformer. Overvoltage- and overcurrent- protection of the high voltage (HV)
and low voltage (LV) systems. Protection equipment of the HV and LV systems,
operating principles and design. Laboratory measurements of the transient
voltages and currents. Transients as a source of the electromagnetic disturbances.
EMC of the HV and LV systems. Basic concepts. Influence of the electromagnetic
appearances on the current circuits, equipment, systems and living organisms.
Recommendations and mitigation techniques for transients in the secondary
circuits of the HV switchgears.
E-learning Level
L2
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
85
Prerequisites
Engineering
C OM
C EA
SEIS
Study Programmes
CE
Learning Outcomes
CS
TI
1. Define and classify the types of transients in electric power system
2. Describe various methods for solving transients
3. Apply acquired theoretical knowledge in concrete examples, and calculate
the transients in power system by using a software package for calculation
of electromagnetic transients, EMTP-ATP
4. Define electromagnetic compatibility and specify the ways of transmission
interference
5. Analyze problems related to electromagnetic compatibility
6. Explain the problems of electromagnetic compatibility in SF 6 substations
7. Calculate the electric and magnetic field and explain the procedure for their
measurement
8. Describe and explain the overvoltage protection in HV and LV systems
E/C
L1
EEIT
English Level
EC E
Course Description
4
EL
Prof. dr. sc.
Ivo Uglešić
ECT S Credits
WT
Lecturer in Charge
34348
EP E
Electromagnetic Transients and Electromagnetic
Compatibility
IP
173
Qualifying for analysis of the transients in basic configurations, measurements and
recording of the electrical appearances, introduction with the EM influences and
protection measures of the EMC.
F orms of Teaching
» Lectures
» A total of 30 hours (2 hours per week).
» Exams
» - 1 mid-term exam + final exam
- homework
» Laboratory Work
» Laboratory exercises consist of two parts:
- use of software package for calculation of electromagnetic
transients EMTP-ATP (10 hours),
- measurements in high voltage laboratory (5 hours).
» Consultations
» Consultations are held every day from 12 am - 13 pm at the
department of high voltage and power systems.
» Independent work in a software package for calculation of
electromagnetic transients, EMTP-ATP.
Grading System
T ype
Homeworks
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
10 %
45 %
45 %
Exam
T hreshold
Percent of
Grade
0%
0%
10 %
50 %
90 %
1. - Sources of transients
- Analytical solving of transients in electrical networks.
- Laplace transform
2. - Oscillatory circuit
- Parallel and series resonance
- Numerical solving of transients in electrical networks
- Theory of traveling waves
3. - Reflection and refraction of traveling waves
- Bewley lattice diagram
4. - Petersen rule
- The passage of travelling wave through the inductor
- The passage of travelling wave nearby capacitor
5. - Analysis of travelling waves entering substation
- Travelling waves with steep front entering oscillatory circuit.
174
6. - Overvoltage and overcurrent protection of the high voltage (HV) and low
voltage (LV) systems
- Protection equipment of the HV and LV systems, operating principles
and design
- Laboratory measurements on surge arrester
7. - A method for calculation of transient phenomena in the Electromagnetic
Transients Program EMTP-ATP.
8. Mid-term exams week.
9. Mid-term exams week.
10. - Transients as a source of the electromagnetic disturbances. EMC in the HV
and LV systems. Basic concepts.
- Mechanisms of the disturbance transmission between source and the
object. Capacitive and inductive influences on the LV equipment in the HV
substation.
- Tesla transformer as a source of electromagnetic disturbances - laboratory
measurements.
11. - Lightning protection and impulse earthing systems in the substations.
- Recommendations for the reduction of transient overvoltages in
secondary circuits of HV switchgears.
- Acting of electromagnetic interferences on electric circuits, systems,
equipment, and living organisms.
12. - Survey of EMC standards and regulations.
- Substation project with regard of EMC protective concept. Practical
examples.
13. - Theory and calculation of magnetic field - practical examples.
- Measurement of magnetic induction in HV laboratory.
14. - Theory and calculation of electric field - practical examples.
- Measurement of electric field in HV laboratory.
15. - Preparation for final exam.
Literature
N. WATSON, J. ARRILAGA
(2002). Power Systems
Electromagnetic Transients
Simulation, Institution of
Engineering and
Technology
L. van der SLUS (2001).
Transients in Power Systems,
John Wiley & Sons, Ltd,
New York
P. CHOWDHURI (1996).
Electromagnetic Transients in
Power Systems, Research
Studies Press
A. L. Shenkman (2005).
Transient Analysis of Electric
Power Circuits - Handbook,
Springer
Similar Courses
» Electromagnetic Compatibility in Power Systems, TU Munchen
» Electromagnetic Compatibility, ETH Zurich
175
Study Programmes
Learning Outcomes
1. Describe the principle of rotating machinery and the basic topology of the
electronic converters učinskih
2. List the basic types of electric machines and electronic power conversion
3. Explain the basic models of transformers, rotating machines and power
semiconductor devices
4. Distinguish different control methods and modulation techniques of
electronic power converters and synchronous generator excitation
powering types
5. Use the vector-phasor diagram in the analysis of synchronous machine
6. Combine electronic power converter to the other system components for
the electromechanical conversion, connect different tools (P-Q and vectorphasor diagrams) in synchronous generator operation principle clarification
50
60
70
85
Prerequisites
Energy Technology
Engineering
The possibilities and means of application of various types of electrical machines,
transformers and power electronic converters are introduced. The students will
acquire knowledge on overall electromechanical and electrical energy conversion
system in the process of production, transfer, distribution and consumption.
E/C
C EA
Dr. sc. Ivan Mrčela
Dr. sc. Stjepan Stipetić
Zlatko Hanić, dipl. ing.
Tino Jerčić, mag. ing.
Marinko Kovačić, dipl. ing.
Igor Sirotić, mag. ing.
Damir Vuljaj, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
45
20
15
C OM
Study Hours
Lecturers
Exercises
EP E
The structure of a system of electromechanical energy conversion and the basic
laws. Power transformers. Types and properties. No-load operation, short-circuit
operation, loading, parallel operation. Special transformers. Synchronous
machines. Drive characteristics, vector diagrams, power charts. Generators for
small hydro power plants and wind power plants. Excitation systems. Induction
machines. Properties and drive characteristics. Electrical drive system. Power
converters, topologies, functions, characteristics.
L1
EC E
Course Description
E-learning Level
EL
Izv. prof. dr. sc.
Damir Žarko
L1
IP
Izv. prof. dr. sc.
Mario Vražić
English Level
SEIS
Prof. dr. sc.
Viktor Šunde
4
CE
Prof. dr. sc.
Zlatko Maljković
ECT S Credits
CS
Lecturers in Charge
127433
WT
Electromechanical and Electrical Conversion
TI
176
F orms of Teaching
» Lectures
» Lectures take place in two cycles: the first 7 weeks at 3 hours and
another 6 weeks, 3 hours per week.
» Exams
» Exam
» Exercises
» Exercises are held in the first cycle 3 times for 2 hours and in the
second cycle, 2 times for 2 hours.
» Laboratory Work
» Laboratory exercises consist of three exercises, each lasting for 5
hours.
» Experiments
»» Experimental Exercises
»» Consultations
» Possible after each lecture and exercises.
» Seminars
»» Acquisition of Skills
» Laboratory exercises
»» E-learning
»» Other
» Consultation
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
15 %
25 %
35 %
25 %
Exam
T hreshold
Percent of
Grade
0%
0%
15 %
0%
50 %
35 %
Comment:
Laboratory exercises are compulsory and a condition that can take the final exam
and repeated examination
1.
2.
3.
4.
Basic laws and structure of electromechanical transformation system
Power transformers. Basic designs. F orms of winding connections.
Power transformer characteristics. Parallel operation. Autotransformer.
Equivalent scheme and parameters of the transformer. Standards.
177
5. Synchronous machines. Generator. Basic characteristics.
6. Network operation. Power chart of turbine-generator and hydrogenerator
7. Synchronous motor. Synchronous compensator. Synchronous machines
excitation systems.
8. Mid-term exam
9. Induction machines, three phase and single phase motors.
10. Asynchronous machines. Generators for small and wind power plants.
11. Drives with induction, synchronous and DC machines.
12. Examples of the application of power electronics. Electronic energy
conversion. Basic topology and functions of electronic power converters.
13. Models of power semiconductor components, transformers and passive
components. Line commuted converters.
14. DC-DC converters. Inverters.
15. F inal exam
Literature
Radenko Wolf (1995).
Osnove električnih strojeva,
Stephan J. Chapman (2004).
Electric Machinery
Fundamentals, McGraw-Hill
International Edition
Zlatko Maljković (2002).
Inžinjerski priručnik IP3 Električni strojevi, Školska
knjiga, Zagreb
Luigi De Paoli i Alfredo
Višković; Kigen (2007).
Ekonomija i politika
proizvodnje električne
energije, Kigen, Zagreb
Sergey E. Lyshevski (2000).
Electromechanical Systems,
Electric Machines, and Applied
Mechatronics, CRC Press
J. G. Kassakian, M. F .
Schlecht, G. C. Verghese
(2000). Osnove učinske
elektronike, Graphis, Zagreb
Similar Courses
» Seminars in Electrical Machines and Power Electron, Royal Instutute of
Technology Stockholm
» Leistungselektronik, TU Munchen
» Energiewandlungstechnik, TU Munchen
» Laboratory exercises on machines and plants, TU Wien
178
System structure. Components of electromechanical systems. Operating principles
of DC and AC motors. DC motors (series, shunt and compound, permanent
magnet). AC motors (synchronous, asynchronous, reluctance, hysteresis, step,
electronic commutated). Static and dynamic models of electric machines. Power
semiconductor valves and switches. Overview of basic semicinductor valves
properties. Electronic power converters for DC and AC motor control; adjustable
speed and servo drives. Control and power characteristics of converters.
Interaction between power supply, converter and motor. Current and voltage
mode control of power converters. Examples of electromechanical systems.
Study Programmes
Study Hours
Lecturers
Exercises
45
5
10
Lecturer
Dr. sc. Šandor Ileš
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
62.5
75
87.5
Prerequisites
Engineering
SEIS
Learning Outcomes
Explain operation principles of DC and AC motors
Explain operation principles of basic power electronic converters
Explain basic mechanical laws for electric drives
Analyze dependance of converter control variables on converter behavior
Analyze dependance of motor control variables motor behavior
Assemble power converter, electric motor and mechanical load into
operating system
7. Create simulation model of power converter, electric motor and drive
8. Define and understand fundamental industrial applications of electric
drives
TI
CS
CE
1.
2.
3.
4.
5.
6.
Good understanding of electromechanical systems and components structure,
characteristics and application. Ability to model, simulate and analyze basic types
of motors and power converters, as well as their interaction.
EEIT
L1
C OM
E-learning Level
C EA
Course Description
L2
EP E
Doc. dr. sc.
Igor Erceg
English Level
EC E
Prof. dr. sc.
F etah Kolonić
4
EL
Prof. dr. sc.
Željko Jakopović
ECT S Credits
WT
Lecturers in Charge
E/C
86461
Electromechanical Systems
IP
179
F orms of Teaching
» Lectures
» Lectures are organized through 2 teaching cycles. The first cycle
consists of 7 weeks of classes and mid-term exam, a second cycle of 6
weeks of classes and final exam. Classes are conducted through a
total of 15 weeks with a weekly load of 3 hours.
» Exams
» Examination consists of mid-term exam and final exam in which
numerical problems are solved, and the writing of reports on
laboratory exercises.
» Exercises
» On the oral exercises the process of solving complex medium and
complex problems is shown to students.
» Laboratory Work
» Laboratory exercises are organized in 3 cycles of thematically linked
to the 3 main areas of the lectures (electrical machinery, electronic
power converters, motor drives).
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
30 %
20 %
40 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
30 %
0%
50 %
20 %
1. Structure of electromechanical systems. Components of electromechanical
systems.
2. Principles of electromagnetism and electromechanical energy conversion.
3. F undamental mechanical components.
4. DC motors (series, shunt and compound, permanent magnet). Operating
principles, characteristics, structure, models.
5. AC motors (synchronous, asynchronous). Operating principles,
characteristics, structure, models.
6. AC motors (reluctance, hysteresis, step, electronic commutated). Operating
principles, characteristics, structure, models.
7. Basic power semiconductor valves and switches. Overview of basic
semiconductor valves properties.
8. Mid-term exam
9. Power converters for adjustable speed and servo DC drives.
10. Power converters for AC drives.
11. Power converters for reluctance, hysteresis, step and electronic commutated
motors.
12. Energy and control characteristics of converters. Interaction of sources,
converters and drives.
13. Electromechanical system example, traction drive.
14. Electromechanical system example, automotive drive.
15. F inal exam
180
Literature
M.E. El-Hawary (2002).
Principles of Electric Machines
with Power Electronic
Applications, WileyInterscience
N. Mohan, T. Undeland, W.
Robins (2004). Power
Electronics: Converters,
Applications and Design,
Wiley
J.H. Harter (1995).
Electromechanics, Prentice
Hall
D. W. Hart (1997).
Introduction to Power
Electronics, Prentice Hall
Similar Courses
» Electric Machines, MIT
» Elektrische Aktoren, TU Munchen
181
Course Description
The course explains interactions between mechanical structures and
electromagnetic fields. Electrical and mechanical parts in such systems are modeled
by concentrated parameters (circuit approach). Circuit theory, which was
introduced in the course on F undamentals of electrical engineering, is extended to
generalized inductances, capacitances and mechanical elements. Electromechanical
coupling is introduced and energy conversion is explained. F undamental
principles are introduced via analysis of practical devices (motors, generators,
levitation systems, electromechanical relays, capacitive microphones …). F inally,
nano- and micro-electromechanical systems are introduced.
L1
Study Hours
Lecturers
60
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
62
74
86
Prerequisites
Engineering
Physics 1
WT
Study Programmes
TI
CS
CE
SEIS
IP
successful students, 3rd semester, 2nd year)
Computing (Study) (courses for exceptionally successful students, 3rd semester, 2nd
year)
year)
year)
semester, 3rd year)
EEIT
E-learning Level
C OM
L0
C EA
Doc. dr. sc.
Saša Ilijić
English Level
EP E
Prof. dr. sc.
Sead Berberović
6
EC E
Prof. dr. sc.
Željko Štih
ECT S Credits
EL
Lecturers in Charge
E/C
90096
Electromechanics
182
Learning Outcomes
1.
2.
3.
4.
5.
6.
Explain complexity of devices for electromechanical energy conversion
Apply fundamental principles of Newtonian mechanics to simple systems
Analyze simple systems by Lagrangean and Hamilton equations of motion
Explain fundamental laws of electromagnetism
Model systems by lumped electromechanical parameters and circuits
Explain operation of complex apparatus for energy conversion (rotational
machines, actuators, levitation)
7. Describe micro and nano electromechanical systems
Undrstanding of complexity of devices for electromegnetic energy conversion,
which requires knowledge of various disciplines of physics and engineering in
research, development and design of such devices.
F orms of Teaching
» Lectures
» Lectures in 2 cycles of 7 and 6 weeks
» Exams
» Exams
» Experiments
» Experiments
» Consultations
» Consulting
» Seminars
» Seminars
Grading System
T ype
Homeworks
Quizzes
Seminar/Project
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
10 %
5%
30 %
20 %
35 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
10 %
5%
30 %
0%
20 %
35 %
1.
2.
3.
4.
5.
Intrduction: Electromechanical systems
Newtonian mechanics
Lagrange's equations of motion
Hamilton's equations of motion
F undamentals of electromagnetism
183
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Lumped parameters and circuits
Electromechanical circuits
Midterm exam
Electromechanical dynamics
Rotating machines
Actuators
Electromagnetic levitation
Microelectromechanical systems
Nanoelectromechanical systems
F inal exam
Literature
H.H. Woodson, J.R. Melcher
(1968). Electromechanical
Dynamics, John Wiley &
Sons
L.J. Kamm (1996).
Understanding ElectroMechanical Engineering,
IEEE Press
S.E. Lyshevski (2001). Nanoand Microelectromechanical
systems, CRC Press
Similar Courses
» Continuum Electromechanics, MIT
» Electrical Energy Conversion Systems, Manchester University and UMIST
184
Study Programmes
Study Hours
Lecturers
60
15
C OM
Lecturers
Dr. sc. Marko Bosiljevac
C EA
Dr. sc. Dijana Tralić
Leonard Novosel, mag. ing.
Josip Vuković, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
L1
EP E
General model of communication system, transmission media: types,
characteristics and applications. Modulation concept, basic forms of analog and
digital modulation techniques. Multiplexing, switching and multiple access
techniques. Open systems interconnect reference model, interconnectivity and
internetworking. Overview of telecommunication network architectures and
characteristics. Overview of commercial wireless systems and technologies.
Service classification and implementation.
E-learning Level
EC E
Course Description
L0
50
62
76
90
Prerequisites
Signals and Systems
EL
Izv. prof. dr. sc.
Gordan Šišul
English Level
WT
Prof. dr. sc.
Sonja Grgić
5
IP
Prof. dr. sc.
Borivoj Modlic
ECT S Credits
SEIS
Lecturers in Charge
E/C
83117
CE
CS
Learning Outcomes
TI
1. Explain elements of electronic communication system
2. Define parameters that describe information transmission in different
types of communication systems
3. Estimate digital signal characteristic in baseband transmission
4. Identify and recognize main characteristic of analog and digital modulation
methods
5. Explain principle of OF DM signal generation
6. Select modulation method parameters for meeting given application
demands
7. Distinguish multiplexing techniques, compare switching techniques,
understand multiple access techniques
8. Analyze possibilities and limitations of different communication systems
185
Overall concept and fundamental knowledge on characteristics and architectures of
electronic communication systems. Explanation of modulation techniques and
their applications in different types of communication systems. Complete
overview of modern communication technologies and their possibilities in service
implementation.
F orms of Teaching
» Lectures
» -» Exams
» -» Laboratory Work
» --
Grading System
T ype
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
10 %
39 %
51 %
Exam
T hreshold
Percent of
Grade
0%
0%
10 %
0%
90 %
1. Information sources and types: sound, image and data. Various information
signals characteristics. Information transmission through space
(communication) and time (storage).
2. Communication system model, analog and digital transmission,
transmission media types, physical parameters and applications,
narrowband and broadband services.
3. Communication channel: transmission characteristics, channel noise.
Modulation concept, modulation methods classification.
4. Continuous and discrete sine carrier modulation. Amplitude modulation
and the derived methods. Modulated signal distortion and noise
performance.
5. Phase modulation, frequency modulation. Modulated signal distortion and
noise performance.
6. Digital data electric representation, signal formats. Inter-symbol
interference (ISI), Nyquist criteria. Signals with ISI. Channel noise impact
on transmission error performance, bit error rate (BER), symbol error rate
(SER).
7. Discrete (digital) modulations. Amplitude-shift keying. F requency-shift
keying. Coherent and non-coherent demodulation. Phase-shift keying.
Differential encoding of PSK-signal, differentially-coherent and differential
demodulation. Carrier recovery.
8. Mid-term exam.
9. Minimum-shift keying, Gaussian minimum-shift keying. Hybrid
modulation methods, QAM. Channel equalization. Optimum receiver
concept, matched filter.
10. Orthogonal frequency division multiplex (OF DM). Pulse train modulation,
PAM, PDM, PPM.
186
11. Open systems interconnect (OSI) reference model, interfaces between
layers, interconnectivity and internetworking, protocols and protocol
stacks.
12. Javna komutirana telefonska mreža. Sinkroni i asinkroni prijenos, postupci
multipleksiranja i komutacije, pleziokrona (PDH) i sinkrona digitalna
hijerarhija (SDH). Dvosmjerna komunikacija: F DD, TDD, simpleks,
poludupleks, dupleks, tehnike višestrukog pristupa: F DMA, TDMA,
CDMA, SDMA, CSMA.
13. Modem connections. Digital Subscriber Lines Technologies. Local area
network.
14. Electromagnetic spectrum, radio frequency bands and allocations, licensed
and license-free bands. Wireless local area networks.
15. Mobile communication systems overview.
Literature
R. Horak (2002).
Communications Systems and
Networks, Wiley
R: E. Ziemer, W. H. Tranter
(2008). Principles of
Communications, Wiley
A. Leon-Garcia, I. Widjaja
(2003). Communication
Networks, McGraw Hill
J. G. Proakis, M. Salehi
Communication Systems,
Prentice Hall
Similar Courses
» Communication Systems, ETH Zurich
187
Course Description
This course provides a survey of principles of electronic equipment and system
design and manufacturing. Contents: Electronic equipment and systems design
principles. Electronic systems manufacturing in industrial environment. Life-cycle
and reliability. Characteristics of electronic components, their equivalent circuits,
standard components' notation and packaging. Characteristics of power supplies
for electronic equipment and systems. Printed circuit boards layout and
manufacturing. Electronic components interconnection. Heat transfer: natural and
forced convection, heatsink design. Overcurrent and overvoltage protection.
Electromagnetic compatibility. Regulations and standards. Technical
documentation. Quality management. Examples.
E-learning Level
L1
Study Hours
Lecturers
45
15
C OM
Lecturer
Dr. sc. Božidar F erek-Petrić
Dominik Džaja, mag. ing.
Goran Šeketa, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
90
Prerequisites
Electrical Circuits
Study Programmes
SEIS
IP
Learning Outcomes
CE
TI
CS
1. Explain electronic equipment and systems design principles and give
examples electronic systems manufacturing in industrial environment
2. Analyze and compare characteristics of electronic components, their
equivalent circuits, life cycle and realibility
3. Calculate characteristics of power supplies for electronic equipment and
systems
4. Design printed circuit boards layout and manufacturing. Electronic
components interconnection.
5. Calculate heat transfer: natural and forced convection, heatsink design.
6. Design overcurrent and overvoltage protection. Electromagnetic
compatibility.
7. Explain regulations and standards. Technical documentation. Quality
management. Examples.
EEIT
L1
C EA
Doc. dr. sc.
Hrvoje Džapo
English Level
EP E
Izv. prof. dr. sc.
Igor Lacković
4
EC E
Prof. dr. sc.
Ratko Magjarević
ECT S Credits
EL
Lecturers in Charge
E/C
34308
WT
188
Good understanding of electronic equipment and systems design principles with
particular emphasis to manufacturing in industrial environment. Good knowledge
of the process of transforming schematic diagrams into final equipment design and
generation of proper technical documentation related to production. Practical
skills in using standard simulation and design software. Ability to understand
datasheets used to characterize real electronic and electromechanical components.
Extensive knowledge about design rules for PCB engineering. Good
understanding of electromagnetic interference sources and methods of their
suppression. Deep understanding of heat transfer principles and design of
heatsinks. Ability to design and implement overvoltage and overcurrent
protection circuits in compliance with related standards. Basic understanding of
regulations and standards for manufacturing and testing of the equipment.
F orms of Teaching
» Lectures
» Exams
» Laboratory Work
» Consultations
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
15 %
25 %
25 %
35 %
Exam
T hreshold
Percent of
Grade
0%
0%
15 %
0%
50 %
35 %
1. Introduction.
Electronic equipment and systems design principles.
2. Electronic systems manufacturing in industrial environment.
3. Life-cycle and reliability.
4. Characteristics of electronic components, their equivalent circuits, standard
components' notation and packaging.
5. Characteristics of power supplies for electronic equipment and systems.
Printed circuit boards layout and manufacturing.
6. Printed circuit boards layout and manufacturing. Electronic components
interconnection.
7. Examples and exercises
8. Testing - written midterm exam
9. Heat transfer: natural and forced convection, heatsink design.
10. Overcurrent and overvoltage protection.
11. Electromagnetic compatibility.
12. Regulations and standards
13. Technical documentation. Quality management.
189
14. Examples and exercises
15. Testing - final exam, written and oral
Literature
Kim R. F owler (1996).
Electronic instrument design,
R. Magjarević, M. Cifrek, Z.
Stare, H. Džapo, M. Ivančić,
I. Lacković (2004).
Konstrukcija i proizvodnja
elektroničkih uređaja, F ERZESOI
Henry W. Ott John Wiley &
Sons (1988). Noise reduction
techniques in Electronic
Systems, Inc.
Paul Horowitz, Winfield
Hill (2001). The art of
electronics, Cambridge
University Press
R. Magjarević, Z. Stare, M.
Cifrek, H. Džapo, M.
Ivančić, I. Lacković (2009).
Projektiranje tiskanih veza,
Sveučilište u Zagrebu, F ER
Similar Courses
» Design of Electronics Devices, EPF L Lausanne
» EE2001 Project, NU Singapore
190
Course Description
Introduction. Basic characteristics of analog and digital circuits. Electrical
characteristics of semiconductors, charge carriers, current conduction in
semiconductors. pn and Schottky diode. Basic diode circuits in analog electronics
(rectifiers, regulators, limiting circuits). MOS structure and MOSF ET. Various F ET
types. Basic F ET amplifier circuits. Basic CMOS logic circuits (inverter, NAND
and NOR circuits, bistable multivibrator). Bipolar junction transistor (BJT). Basic
BJT amplifier circuits. Differential amplifier. BJT switch. ECL logic circuits.
Characteristics of ideal and real operational amplifier. Basic operational amplifier
circuits in analog and digital electronics (amplifiers, multivibrators, triangular
waveform generator). Analysis of electronic circuits by CAD tools.
Study Programmes
Computing (Study) (required courses - electronics 1, 3rd semester, 2nd year)
Learning Outcomes
1.
2.
3.
4.
5.
6.
7.
Explain the operation of basic semiconductor devices
Analyze basic electronic amplifiers
Compare the amplifiers with different electronic devices
Analyze CMOS logic circuits
Apply operational amplifier in analog and digital circuits
Analyze of electronic circuits using electronic computers
Apply basic measurements in electronic laboratory
75
15
15
EEIT
Study Hours
Lecturers
Exercises
C OM
L1
C EA
Lecturers
Dr. sc. Tvrtko Mandić
Dr. sc. Mirko Poljak
Dr. sc. Sanja Žonja
EL
EC E
EP E
Dr. sc. Niko Bako
Dr. sc. Mirko Poljak
Josip Bačmaga, mag. ing.
Raul Blečić, dipl. ing.
Tihomir Knežević, dipl. ing.
Sabina Krivec, mag. ing.
Marko Magerl, mag. ing.
Hrvoje Štimac, mag. ing.
Josip Žilak, dipl. ing.
WT
Doc. dr. sc.
Vladimir Čeperić
E-learning Level
IP
Doc. dr. sc.
Marko Koričić
L2
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
62
75
87
Prerequisites
Engineering
Mathematics 2
SEIS
Izv. prof. dr. sc.
Igor Krois
English Level
CE
Izv. prof. dr. sc.
Tomislav Suligoj
7
CS
Prof. dr. sc.
Adrijan Barić
ECT S Credits
TI
Lecturers in Charge
E/C
91841
Electronics 1
Prerequisites for
Computer Aided Design of
Electronic Systems
Electronics 2
F undamentals of Electronic
Measurements and
Instrumentation
Optical Communication
Technology
Project
Project
191
Understanding of characteristics of electronic devices and basic circuits in analog
and digital electronics. Understanding and usage of electronic circuits analysis
techniques.
F orms of Teaching
» Lectures
» lectures
» Exercises
» problem solving exercises
» Laboratory Work
» laboratory exercises
» Consultations
» consultations
Grading System
T ype
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
12 %
44 %
44 %
Exam
T hreshold
Percent of
Grade
0%
0%
12 %
0%
50 %
38 %
Comment:
Before final exam students must have completed all laboratory exercises.
1. Role of electronics. Types of signals in analog and digital electronics.
Amplifiers: gains, power supply nonlinear characteristics of real amplifiers.
Types of amplifiers. F requency response of amplifiers. F requency response
of CR i RC network.
2. Impulse response of CR i RC networks. Inverter: transfer characteristic,
time response. Electrical properties of semiconductors. Silicon structure.
Intrinsic and doped silicon. Other semiconductors. Bandgap. Intrinsic
concentration.
3. Carrier concentrations. Temperature dependence. Carrier energy
distribution. Drift current. Semiconductor conductivity. Carrier diffusion.
4. pn-junction in equilibrium. Built-in voltage. Depletion layer. F orward and
reverse biased pn-junction. Current-voltage characteristics. pn-junction
breakdown. Temperature dependence.
5. Small-signal diode resistance. Junction capacitance. Diffusion capacitance.
Small-signal equivalent model. Diode as a switch. Metal-semiconductor
junction. Schottky diode. Diodes in optoelectronics: light emitting diodes,
photodiodes, solar cells. Analysis of circuits with nonlinear devices. Smallsignal and large-signal circuit operation.
6. Diode rectifiers. Limiters. MOS structure. MOS transistor. Operation.
Current-voltage characteristics. CMOS structure. Junction F ET. MESF ET.
7. F ET temperature dependence and breakdowns. Small-signal F ET
parameters and small-signal equivalent model. F ET amplifiers. Biasing.
192
8. Midterm exam.
9. Common-source, common gate and common drain amplifier. Comparison
of basic F ET amplifiers. CMOS inverter: voltage transfer characteristic,
time-domain operation, power dissipation.
10. CMOS logic gates. CMOS latches. Bipolar junction transistor (BJT).
Operation in the active mode. Current gains. BJT connections and modes of
operation.
11. BJT current-voltage characteristics. Temperature dependence. BJT dynamic
parameters and small-signal equivalent model. BJT amplifiers. Biasing.
12. Common-emitter, common base and common collector amplifier.
Comparison of basic BJT amplifiers. Differential amplifier.
13. BJT as a switch. ECL logic circuit. Voltage regulators. Zener diode
regulator. Transistor voltage regulator.
14. Ideal operational amplifier (Op-Amp). Properties of real operational
amplifiers. Op-Amp amplifiers. Op-Amps in analog computations. OpAmp comparator. Op-Amp astable and mostable multivibrator. Op-Amp
triangular waveform generator.
15. F inal exam
Literature
Ž. Butković, J. DivkovićPukšec, A. Barić (2013).
Elektronika 1, F akutet
elektrotehnike i
računarstva, Zagreb interna skripta
A.S. Sedra, K.C. Smith
(2011). Microelectronic
Circuits, 6th ed., Oxford
University Press
R.C. Jaeger, T.N. Blalock
Circuit Design, 4th ed.,
McGraw-Hill
Similar Courses
» EE101A Circuits I, Stanford
» EE115A Analog Electronic Circuits I, UCLA
» Circuits and Electronics, MIT
193
Study Programmes
Study Hours
Lecturers
45
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C EA
C OM
Josip Bačmaga, mag. ing.
Tihomir Knežević, dipl. ing.
Marko Magerl, mag. ing.
Josip Žilak, dipl. ing.
50
62
75
87
Prerequisites
Electronics 1
CE
Learning Outcomes
CS
Describe the properties of differential amplifiers
Combine the basic amplifier stages of multistage amplifiers
Describe the specificity of power amplifiers
Distinguish the impact of capacity at low and at high frequencies
Calculate the amplifier time constants
Analyze complex feedback amplifiers
Identify the stability of the feedback amplifier
Describe the sinusoidal oscillators operation
TI
1.
2.
3.
4.
5.
6.
7.
8.
Understanding advanced analog circuits characteristics. Understanding and usage
of electronic circuits analysis and design techniques.
F orms of Teaching
» Lectures
» lectures
EEIT
L1
EP E
Differential amplifiers, differential and common voltage gain, common-mode
rejection ratio, transfer characteristics. Class A, B and AB power amplifiers.
Amplifier frequency characteristics, low frequency and high frequency analysis.
Properties of feedback amplifiers, feedback topologies, analysis of feedback
amplifiers. Stability of feedback amplifiers, stability analysis, frequency
compensation. Sinusoidal oscillators, positive feedback, typical sinusoidal
oscillator circuits. Analog integrated circuits, operational amplifiers, integrated
regulators
E-learning Level
EC E
Course Description
L1
EL
Doc. dr. sc.
Marko Koričić
English Level
WT
Izv. prof. dr. sc.
Igor Krois
4
IP
Prof. dr. sc.
Adrijan Barić
ECT S Credits
SEIS
Lecturers in Charge
E/C
34299
Electronics 2
194
» Laboratory Work
» laboratory exercises
» Consultations
» consultations
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
12 %
30 %
30 %
28 %
Exam
T hreshold
Percent of
Grade
0%
0%
12 %
0%
50 %
38 %
Comment:
Before final exam students must have completed all laboratory exercises.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
BJT differential amplifier.
F ET differential amplifier.
Multistage amplifiers.
Darlington configuration. Power amplifiers. Power amplifier classification.
Class A power amplifier. Class B power amplifier.
Crossover distortion. Class AB power amplifier. Power transistors.
Amplifier frequency response. Bode plot.
Common-emitter and amplifier at low frequencies.
Common-source amplifier at low frequencies.
Midterm exam.
Common-emitter and common-source amplifiers at high frequencies.
Common-base amplifier and cascode amplifier at high frequencies.
Common-collector amplifier at high frequencies. F eedback amplifiers.
F eedback structure. Effect of negative feedback on amplifier properties.
F eedback topologies. Effect of negative feedback on input and output
resistance.
F eedback amplifier analysis.
Stability of feedback amplifiers. Effect of feedback on amplifier poles.
Nyquist plot and Nyquist criterion of stability. Stability study using Bode
plots.
F requency compensation. Sinusoidal oscilators. Barkhausen criterion of
oscillations. RC oscilators. LC and crystal oscilators.
Analog integrated circuits. Current sources in integrated circuits. Basic
integrated amplifiers. Differential integrated-circuit amplifiers.
Operational integrated-circuit amplifiers.
F inal exam.
195
Literature
Ž. Butković (2013).
Elektronika 2, F akultet
elektrotehnike i
računarstva, Zagreb interna skripta
A.S. Sedra, K.C. Smith
Circuits, 6th ed., Oxford
University Press
R.C. Jaeger, T.N. Blalock
Circuit Design, 4th ed.,
McGraw-Hill
Similar Courses
» EE101B - Circuits II, Stanford
» EE115B Analog Electronic Circuits II, UCLA
196
Embedded systems and their applications. Component specification. Standard
operating voltages, and compatibility. F amilies of processors and controllers.
Internal busses. Memories. Input-output units. Circuits for initialization and
monitoring. Serial synchronous and asynchronous busses. Low power operating
modes. Implementation technologies. Tools and environment for development.
Logic synthesis. Hardware description languages. Timing specification and
simulation. Software for embedded systems. Soft microcontroller cores. Examples
of embedded systems.
Study Programmes
L1
Study Hours
Lecturers
45
18
C OM
Maja Bellotti, mag. ing.
Igor Mijić, mag. ing.
EEIT
E-learning Level
Grading
Acceptable (2)
50
Good (3)
62
Very Good (4)
75
Excellent (5)
88
Possible changes in scoring
and grading will be announced
on the first lecture.
Prerequisites
C EA
Course Description
L0
EP E
Izv. prof. dr. sc.
Hrvoje Mlinarić
English Level
EC E
Prof. dr. sc.
Mladen Vučić
4
EL
Prof. dr. sc.
Davor Petrinović
ECT S Credits
WT
Lecturers in Charge
E/C
86535
Embedded Systems
SEIS
IP
3rd year)
Learning Outcomes
CE
TI
CS
1. Define embedded system, its elements and architecture
2. Classify embedded system components based on signal type, integration
level, realization and functionality
3. Analyze and build a simple embedded computer system from scratch
4. Develop hardware and software for embedded computer system with 8-bit
microcontroller
5. Apply peripherals which are built in 8-bit microcontrollers
6. Design embedded computer system using F PGA
7. Apply programmable logic, programmable array logic (PAL), field
programmable gate arrays (F PGA)
Knowledge of embedded system design, the corresponding implementation
technology, and their application.
197
F orms of Teaching
» Lectures
» 3 hours once every week
» Exams
» midterm exam and final exam
» Laboratory Work
» 6 times in semester
» Consultations
»-
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
24 %
33 %
33 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
24 %
0%
66 %
10 %
Comment:
The student is allowed to approach the oral exam if minimum 50% is gained on
the midterm and written part of the final exam. The student is allowed to
approach the oral exam if minimum 50% is gained on the written part of the
exam. Oral exam is not mandatory.
1. Embedded computer systems - historical perspective from Apollo guidance
computer to IPhone. Elements and architecture of typical embedded
computer.
2. Classification of embedded system components based on signal type,
integration level, inner and outer realization and application domain.
Packaging of electronic components.
3. Design of embedded systems: chip level design and board level design.
Technical specification and standards. Interconnection standards, logic level
standards and power supply standards.
4. F amilies of digital components. Unipolar and bipolar signaling standards.
Noise sources and immunity; digital signal integrity.
5. Example of a rudimentary digital system. F rom specification to
implementation and evaluation. Bus-timing analysis.
6. Microcontrollers in embeded systems. Basic microcontroller architecture.
Example of 8-bit microcontroller. Hardware design of microcontroler
based embedded systems. Design examples.
7. Built-in periferial circuitry. Analog to digital convertor, pulse width
modulator, capture and compae circuitry, watch dog. Software
development in assembler. Examples of assembler programs working with
built-in peripherals.
8. Midterm exam.
198
9. Reset circuitry, clock sources, power supplies. Example of embedded
system based on 8-bit microcontroller. EPROM emulator. Emulacija
ugrađenih komponentara. Microcontroller emulator. Software
development in C.
10. Dedicated user interfaces. Connection od LEDs, 7- segment indicators and
liquid crystal displays (LCDs). I2C bus. In-circuit emulation. EPROM
emulator. Microcontroller emulator. Protection of hardware and software
design.
11. Programmable logic, programmable array logic (PAL), field programmable
gate arrays (F PGA).
12. Design tools for programmable logic devices.
13. Soft microcontroller cores, PicoBlaze
14. Single chip implementation in F PGA technology.
15. F inal exam.
Literature
Computers as Components:
Principles of Embedded
Computer Systems Design
Wayne Wolf Morgan
Kaufmann 2000
Mladen Vučić (2007).
Upotreba mikrokontrolera u
ugrađenim računalnim
sustavima, F ER
Davor Petrinović, Mladen
Vučić (2007). Osnove
projektiranja računalnih
sustava, F ER
Pong P. Chu (2008). FPGA
Prototyping by VHDL
Examples: Xilinx Spartan-3
Version, John Wiley & Sons,
Inc.
Surhone, Tennoe,
Henssonow MICROBLAZE,
Betascript publishing
Similar Courses
» CSCA302: Embedded Systems I, IEEE & ACM Computing Curricula
» CSCA401: Embedded Systems II, IEEE & ACM Computing Curricula
» ET3 301 Embedded Systems, TU Delft
» ET3 301 Embedded Systems (description), TU Delft
» 72313 Mikroprozessoren, TU Munchen
» 72313 Eingebettete Systeme (vormals: Mikroprozesso, TU Munchen
199
Course Description
The main goal is to educate students for an overall understanding of the
mechanisms between energy production, energy transportation, energy use,
energy policy and the influence it brings to the environment. The activities are
based on a theoretical and a practical scheme in order to make the subject as
realistic as possible to enable students to work with in industry, business,
government, or as a consultant performing energy audits and implementing
energy efficiency measures. Programme cover: Energy Efficiency within Energy
Supply and F uel Systems, Electric Energy Management, Process Systems, Building
Systems, Energy Efficiency Audit, Technical and Economic Calculations and Case
Study.
L0
E-learning Level
L1
Study Hours
Lecturers
30
15
Prerequisites
Energy Technology
C OM
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
Participation in teaching
brings 6% points, homework
8% points, with at least 5%
points, mid-term exam 31%
points, with minimum of 15%,
final writen exam 40% points,
with a minimum 20% points.
IP
Study Programmes
SEIS
Learning Outcomes
CE
TI
CS
1. Explain and identify energy production and consumption in the World and
Croatia and role of energy efficiency
2. Apply principles of energy management in industry and organization of
energy management programme
3. Assess role and methodology of energy audits
4. Analyze electricity consumption and costs of electricity
5. Recognize most important energy systems in industry (compressed air,
boilers, pumps, fans)
6. Analyze energy consumption and energy efficiency in buildings
7. Apply and use measuring instruments for measuring electrical values,
temperatures, illumination values, pressure, combustion
8. Apply method of Infrared thermography in energy (infrared thermometers
and cameras)
E/C
English Level
EEIT
4
EP E
Izv. prof. dr. sc.
Željko Tomšić
ECT S Credits
EC E
Lecturer in Charge
34333
EL
Energy Efficiency Audit and Energy Management
Programme
WT
200
The program is designed to provide students with the necessary theoretical and
practical knowledge in energy management and auditing. Understanding of the
basic science of energy, its conversion from one form to another and transfer from
one place to another. To be able to predict and monitor the financial effect of
changes in practice, or of investment in energy efficient technology, practical
calculations involving both energy and money. Students will carry out a number
of exercises to enhance comprehension of the theoretical background. This will
enable them to carry out energy audits and identify ways of improving efficiency
in energy consumption.
F orms of Teaching
» Lectures
» Course lectures are organized through 2 study cycles. F irst cycle
consists of 7 weeks of lectures and mid-term exam. Second cycle
consists of 6 weeks of lectures and final exam. Lectures are held
through total of 15 weeks with weekly load of 2 hours.
» Exams
» Examination is performed in two parts: in eighth week mid-term
exam and in fifteenth week the final exam. Exams are written and
consist of multiple choice questions, essay questions and exercises.
» Laboratory Work
» Laboratory exercises are kept in 7 time slots. In first study cycle 4
and in second cycle 3 laboratory exercises are held. F irst laboratory
exercise is 3 hours long, while all the rest are 2 hours long. F irst
laboratory exercise consists of measuring and instruments
introduction. Other exercises consist of one hour of theoretical
preparation and calculation exercises and of one hour of performing
measurements.
» Demonstrate use of measuring instruments.
» Consultations
» Consultation acording to the needs of students.
» Seminars
» Seminar on the results of measurements in laboratory.
» Preparation for laboratory exercise
» Other
» Homework tasks.
» Visit to energy plant in fyctory or large building
Grading System
T ype
Homeworks
Attendance
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
66 %
60 %
50 %
50 %
50 %
15 %
8%
13 %
34 %
30 %
Exam
T hreshold
Percent of
Grade
66 %
0%
0%
0%
15 %
0%
0%
50 %
55 %
30 %
201
1. Energy Efficiency within Energy Supply. Sources of Energy and Pollution;
Strategic Approach to Energy and Environmental Management; Basic
Principles of Energy Efficiency.
2. Role of energy efficiency in energy policy, essential factors for energy
efficiency policy enforcement. National action plan for energy efficiency
2008. – 2010. and Croatian energy efficiency program 2008. – 2016.
F irst laboratory exercise (3 academic hours): Measuring in general: energy
consumption measurements, exercise and definition of measuring,
measuring units, measuring traceability, measurement uncertainty,
measurement of temperature, pressure, flow and electrical values.
3. Energy efficiency and energy management program introduction. Energy
management in industry in general and energy efficiency program
organization.
Second laboratory exercise (2 academic hours): Electrical energy
consumption (measuring electrical values).
4. Energy Management in Industry - Electric Energy Management I Electrical Power and Motor Systems – Part 1 Tariff systems, Load diagram,
Electric Energy Management.
Third laboratory exercise (2 academic hours): Measuring O2 and CO
substance in gas emission.
5. Energy Management in Industry - Electric Energy Management II Electrical Power and Motor Systems – Part 2 Electric Motors and Drives;
Transformers and Capacitors, Lighting; Electrical Demand and Power
F actor; Control Systems; Power Quality.
F ourth laboratory exercise (2 academic hours): Physical values measuring
(illumination values, noise, humidity, vibrations, etc.).
6. Industrial energy systems - Process Systems – Part 1 Boiler Systems;
Efficient Operation of Boiler House; Steam Delivery System.
7. Industrial energy systems - Process Systems – Part 2 Heat Recovery;
Compressed Air, Pumps, F ans and Liquid/Steam Distribution.
F ifth laboratory exercise (2 academic hours): Measuring compressor
parameters (pressure etc.).
8. Midterm Exam
9. Building Energy Systems –Energy Managements in Buildings; Air
Conditioning; Ventilation; HVAC Systems.
Sixth laboratory exercise (2 academic hours): Infrared thermograph
application in constructions.
10. Building Energy Systems – Part 2 Thermal Insulation; Heating and Heat
Recover.
Seventh laboratory exercise (2 academic hours): Temperature measurements
– with and without contact.
11. Project Management, Energy Management; Utility Information; Energy
Conservation Project Planning and Company Policy.
12. “Energy efficiency project in Croatia” and systematic energy management
in cities.
13. Technical and Economic Calculations – Part 1 Role and Methodology of
Energy Audit; Instrumentation and Measurement; Monitoring and
Metering Equipment.
14. Technical and Economic Calculations - part 2: Performing Energy Audit;
Reporting the Energy Audit Results; The F ollow-up Program; Measures
for energy efficiency increase and examples of their application.
15. Exam.
202
Literature
Zoran K. Morvay; Dusan D.
Gvozdenac (2008). Applied
Industrial Energy and
Environmental Management,
John Wiley & Sons Ltd,
United Kingdom
Wayne C. Turner and Steve
Doty (2009). Energy
Management Handbook, 7th
edition, F airmont Press
Barney L. Capehart; Wayne
C. Turner; William J.
Kennedy (2008). Guide to
Energy Management, Sixth
Edition, F airmont Press
Albert Thumann; William J.
Younger, Terry Niehus
(2009). Handbook of Energy
Audits, Eighth Edition, CRC
Press
Kenneth C. Weston (2000).
Energy Conversion, PWS
Pub. Co.
Similar Courses
» KVM012 - Industrial energy systems, Chalmers University
» BS5213 Building Energy Analysis and Management, NU Singapore
» Applied Energy Technology, Royal Instutute of Technology Stockholm
» Efficient Energy Use and Thermal Building Optimization, TU Wien
» Measurement and Instrumentation, TU Wien
» Selected Topics Energy Systems, TU Wien
203
Study Programmes
semester, 2nd year)
Learning Outcomes
1. Develop an intuitive understanding of energy processes in power systems
with emphasis on physical explanations using (by means of) methods of
thermodynamics, fluid mechanics and electrical engineering
2. Analyze and calculate the basic parameters of energy processes in thermal
power plants, nuclear power plants, hydro power plants and wind power
plants
3. Calculate entropy changes for reversible and irreversible energy processes:
calculate the loss of exergy (maximum mechanical work)
4. Calculate exergy, ideal, reversible and real work of energy processes
5. Describe direct energy conversions to electrical energy (thermoelectric,
thermionic and photoelectric transformation, fuel cells and
magnetohydrodynamics generators) and electrical energy conversions to
other (useful) energy forms
6. Develop energy balance and predict the growth of electricity consumption
7. Describe environmental impact of energy utilization, conversion and
consumption (environmental pollution and climatic change)
8. Combine independent learning, analytical and problem solving skills that
can be applied in the diverse career paths
T eaching Assistant
Doc. dr. sc. Tomislav Capuder
50
60
75
90
EC E
Prerequisites
Physics 1
Prerequisites for
Electromechanical and
Electrical Conversion
Energy Efficiency Audit and
Energy Management
Programme
Power Plants
Process Measurements and
Diagnostic in Power Plants
Project
Transmission and
Distribution of Electric
Power
EL
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
60
15
C OM
Study Hours
Lecturers
Exercises
C EA
L1
EP E
E-learning Level
WT
Importance of energy, energy supply, energy constraints. Energy forms and
sources, classification of energy forms. Renewable and non-renewable energy
sources. Transformations of primary energy forms into more usable forms and
transformation of electrical energy into other forms of energy. Energy
transportation and delivery. Electrical energy: generation, transmission,
distribution and usage. Electrical energy consumption. Energy systems. Energy
balance. Environmental impact during generation, transformation and
consumption of energy (environmental pollution and climate change). Sustainable
development and energy. Energy storage. Energy alternatives. Energy efficiency.
L1
IP
Course Description
English Level
SEIS
dr. sc.
Siniša Šadek
6
CE
Izv. prof. dr. sc.
Davor Grgić
ECT S Credits
CS
Lecturers in Charge
E/C
86466
Energy Technology
TI
204
Acquiring of knowledge related to various energy technologies and energy
relations in modern world. Achieving level of knowledge for use in any other
electrotechnical study and for further education in the field of electrical
engineering.
F orms of Teaching
» Lectures
» Teaching the course is organized in two teaching cycles. The first
cycle contains seven weeks, mid-term exam, and the second cycle
contains six weeks of classes and a final exam. Classes are conducted
through a total of 15 weeks with weekly load of 4 hours.
» Exams
» homework assignments
» Exercises
» Exercises are held in place so far in the present schedule of
laboratory exercises in the same number of hours.
Grading System
T ype
Class participation
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
6%
40 %
54 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
100 %
1. Introduction: importance of energy, energy supply. Energy issues and
constraints in modern world. F orce, mechanical work, energy and power.
2. Energy classification and supply: primary (conventional and nonconventional), useful, stored and transitional energy; energy, exergy and
anergy. Energy sources. Non-renewable energy sources (fossil fuels, nuclear
and geothermal energy). Renewable energy (hydropower, biomass, wind,
solar radiation and others).
3. Basic energy conversions. Chemical and nuclear energy conversion to
internal (thermal) energy.
4. Internal (thermal) energy conversion to mechanical energy, gravitational
potential water energy conversion to mechanical energy, mechanical energy
conversion to electrical energy.
5. Direct energy conversions to electrical energy (thermoelectric, thermionic,
photoelectric transformation, fuel cells, magneto-hydrodynamics
generators). Electrical energy conversions to other energy forms.
6. Power generation facilities. Power plants for electrical energy production.
7. Electrical energy: production, transmission, distribution, and electrical
energy usage.
8. Exams
9. Exams
10. Energy for transportation. Other than electrical energy transportation and
delivery.
11. Energy consumption: trends and predictions.
12. Efficiency of energy conversions.
205
13. Energy balance.
14. Environmental impact of energy utilization, conversion and consumption
(environmental pollution and climatic change).
15. Sustainable development and energy.
F uture energy alternatives. Energy efficiency and savings.
Literature
POŽAR, H. (1992). Osnove
energetike, 1, 2. i 3. dio,
AUBRECHT, G.J. (2006).
Energy, PEARSON PrenticeHall
MIKULIČIĆ, V.; ŠIMIĆ, Z.
(2011). Energijske tehnologije
(Tekst, h ttp : //www.fer.h r/p re
dmet/eneteh )
Similar Courses
» Energy Technology, Royal Instutute of Technology Stockholm
» Energy and Society, University of California Berkeley
» Sustainable Energy, MIT
» F undamentals of Energy Processes, Cambridge
» F undamentals of Energy Processes, Stanford
206
General structure of an electrical drive system. Concepts, definitions, motion
equations. Drive components, motors, power converters, transmissions, working
mechanisms, power supplies, transformers. Classifications and characteristics of
drives. Characteristics of DC, AC and universal motors. Characteristics of working
mechanisms. Definitions of drives according to IEC standards. Electrical drives
with DC, induction and synchronous motors. Drives in steady state. Basics of
dynamics. Starting, braking and reversing. Rotational speed control and power
saving with the application of controlled drives. Basics of drive protection. Drives
in classical and nuclear power plants. Anti-explosive construction of drives.
Standards.
L1
Study Hours
Lecturers
Exercises
26
4
15
Tino Jerčić, mag. ing.
Igor Sirotić, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
61
71
86
Prerequisites
Engineering
Study Programmes
IP
SEIS
Learning Outcomes
CS
CE
Describe general structure of an electrical drive system
Define basic electromechanical terms
Discuss basic motor characteristic for electrical drive
Predict drive behaviour in typical applications
Prepare drives parameters acording demands
Select motor for electrical drive
TI
1.
2.
3.
4.
5.
6.
The knowledge of properties and characteristics of electrical drives relevant for
their application is acquired.
F orms of Teaching
» Lectures
» Two cycles; 6+5 lectures
» Exams
» Labs, exams
» Exercises
» Two exercises.
EEIT
E-learning Level
C OM
L1
C EA
Course Description
English Level
EP E
Doc. dr. sc.
Igor Erceg
4
EC E
Izv. prof. dr. sc.
Damir Žarko
ECT S Credits
EL
Lecturers in Charge
E/C
91613
Fundamentals of Electrical Drives
WT
207
» Laboratory Work
» Threee cycles in groups in department laboratory.
One of them can be changed with praxis visit.
» Electrical drives in industrial plant.
Grading System
T ype
T hreshold
F inal Exam: Oral
Exam: Written
Exam: Oral
60 %
20 %
20 %
Percent of
Grade
20 %
25 %
25 %
30 %
Exam
T hreshold
Percent of
Grade
60 %
0%
20 %
40 %
30 %
50 %
1. General structure of an electrical drive system. Concepts, definitions,
motion equations. Classifications and characteristics of drives.
2. Drives in steady state, characteristics of working mechanisms, electrical
motor characteristics.
3. Electrical drives with DC motors, basic characteristics.
4. Electrical drives with DC motors, starting, breaking, rotational speed
control. Traction applications.
5. Electrical drives with induction motors, basic characteristics.
6. Electrical drives with induction motors. Starting, breaking, reversing. Slip
ring motor. Speed control. Industry application.
7. Exercise
8. Interexam
9. Electrical drives with synchronous motors. Synchronous motors with
classical excitation system and permanent magnet starting. Speed control.
10. Electrical drive dynamic basics. Mechanical transients and power losses.
Cutting losses.
11. Electrical drive with DC, induction and synchronous motors dynamics.
12. Electrical motor selection for defined electrical drive. Types of typical loads
according to IEC 60034-1, basics of motor heating and cooling.
13. Electrical drives protection, overload and grid disturbances influence,
environmental influence. Drives in explosive environment. ATEX
standards. Typical application of electrical drives.
14. Exercise
15. F inal exam
Literature
Jurković Berislav (1986).
Elektromotorni pogoni,
Školska knjiga Zagreb
Gopal K.Dubey (2001).
Fundamental of Electrical
Drives, Alpha Science Ltd,
Pangabourne, UK
Ned Mohan (2001). Electric
Drives, an integrative
Aproach, MNPERE,
Minneapolis, USA
Muhamed H.Rashid (2011).
Power Electronics Handbook,
Editor-In-Chief, Academic
Press,New York
208
Similar Courses
» Electrical Machines and Drives, Royal Instutute of Technology Stockholm
» Seminars in Electrical Machines and Power Electron, Royal Instutute of
» Elektrische Antriebssysteme, TU Munchen
» Machine development for electrical drive systems, TU Wien
209
Izv. prof. dr. sc.
Bruno Blašković
Izv. prof. dr. sc.
Šandor Dembitz
Doc. dr. sc.
Mirko Randić
Izv. prof. dr. sc.
Martin Dadić
L1
Study Hours
Lecturers
90
15
Luka Humski,
mag.ing.inf.et.comm.techn.
dipl. ing.
Tomislav Župan, dipl. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
E-learning Level
C OM
Prof. dr. sc.
Armin Pavić
L0
C EA
Prof. dr. sc.
Petar Knežević
English Level
EP E
Prof. dr. sc.
Zoran Skočir
7
EC E
Prof. dr. sc.
Sead Berberović
ECT S Credits
50
62
74
86
IP
Prerequisites for
Course is prerequisite for
more than 15 courses
EL
Lecturers in Charge
E/C
86494
Fundamentals of Electrical Engineering
WT
SEIS
Doc. dr. sc.
Damir Pintar
CE
Doc. dr. sc.
Bojan Trkulja
Course Description
TI
CS
The overview of development and current trends in electrical engineering and
computer science. F undamentals of electricity, capacitance. Electric current and
electrical phenomena. F undamentals of magnetism, inductance and mutual
inductance. Concepts, elements and topology of electric circuits. Kirchhoff's laws.
Elementary DC circuits. Circuits with capacitors. Complex DC circuits (bridge
circuit, star-delta transformation, circuits with multiple sources). Superposition,
Thevenin's, Norton's and Millman's theorem. Current and voltage waveforms.
Complex calculus in analysis of AC circuits. RLC circuits. Topographic and locus
diagrams. F requency characteristics. Instantaneous, real, reactive and apparent
power. AC circuits with multiple sources. Polyphase system. Harmonic analysis,
applications in circuit analysis. Transients.
Study Programmes
210
Learning Outcomes
1. Define and understand the fundamental concepts related to electricity,
magnetism and electric circuit theory.
2. Understand and apply Kirchhoff's Laws to DC and AC circuit analysis.
3. Understand and apply phasors for sinusoidal steady-state AC circuit
analysis.
4. Analyze DC and AC circuits by following circuit analysis methods and
theorems: nodal analysis, star-delta transformation, transformation
between real source models, Millman's, Thévenin's and Norton's theorems.
5. Understand and apply the principle of linearity and superposition to AC
and DC circuits.
6. Analyze circuits with non-sinusoidal sources by harmonic analysis.
7. Analyze transient response of first order circuits (series RC and RL).
8. Use basic laboratory measurement equipment including the power
supplies, ammeters, voltmeters, ohmmeters, digital multimeters, function
generators, and oscilloscopes as well as to conduct experiments, to measure
basic quantities in electric circuits, and to interpret data.
The course gives understanding of concepts, laws and principles regarding
electrical circuits. After finishing this course students will be able to analyze DC
and AC electrical circuits and understand underlying physical phenomena.
F orms of Teaching
» Lectures
» Involvement in lectures
» Exams
» Computer aided, written, amd oral exams
» Laboratory Work
» Laboratory work
» Consultations
» Lecturers consultations
» Other
» Individual work and learning
» E-learning
» Homework
Grading System
T ype
Homeworks
Class participation
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
0%
Percent of
Grade
15 %
3%
4%
27 %
27 %
24 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
3%
4%
0%
54 %
24 %
211
1. Course description with the overview of development and current trends
in electrical engineering and computer science. F undamentals of electricity,
(atoms and their structure, electric charge, electric force, electric field,
electric potential, capacitance and capacitor, capacitor energy.
2. Electric current and electrical phenomena (resistance, Ohm's and Joule's
Law, electrical energy and power). Concepts, elements and topology of
electric circuits. Kirchhoff's laws.
3. Elementary DC circuits. Circuits with capacitors.
4. More complex DC circuits (bridge circuit, star-delta transformation,
circuits with multiple sources). Superposition principle.
5. F undamentals of magnetism (magnetic force, magnetic field, F araday's Law,
inductance and mutual inductance, inductor energy).
6. Current and voltage waveforms. Complex calculus in analysis of AC
circuits. Phasors.
7. RLC circuits. F requency characteristics.
8. Midterm exam.
9. Power and energy in AC circuits.
10. Topographic and locus diagrams.
Complex AC circuits.
11. Circuit analysis methods.
12. Poliphase systems.
13. Transients.
Characteristics of nonsinusoidal periodical waveforms.
14. Waveform harmonic analysis.
15. F inal exam.
Literature
V. Pinter (1989). Osnove
elektrotehnike, I i II dio,
Tehnička knjiga, Zagreb
E. Šehović, M. Tkalić, I F elja
(1992). Osnove elektrotehnike
- zbirka primjera, I dio,
A. Pavić, I. F elja (1996).
Osnove elektrotehnike 1,
auditorne vježbe, Korijandol
Similar Courses
» Linear Circuits and Devices, Cambridge
» Elektrizitätslehre, TU Munchen
» Electrical Engineering 1, TU Wien
» Electrical Engineering 2, TU Wien
212
Study Programmes
year)
L1
Study Hours
Lecturers
Exercises
45
15
15
EP E
T eaching Assistant
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
Only students who pass oral
exam can pass the course.
Prerequisites
Electronics 1
CS
TI
Apply electronic measurement equipment
Describe electronic measurement channel and define it’s key parameters
Select mode of connecting signal source to measurement channel
Explain influence of interference and noise and estimate their impact
Employ various sensors
Estimate parameters of a voltage reference
Select an analog to digital converter and estimate the device error
Basic understanding of electronic measurement channel concept, knowledge of
selection of its components as well as of impact of interferences and noise.
Practical experience on a real implementation.
C OM
C EA
Lecturer
Learning Outcomes
1.
2.
3.
4.
5.
6.
7.
E/C
E-learning Level
EEIT
L0
EC E
The course gives an overview of fundamentals of electronic measurement systems
and elements of electronic instrumentation. Contents: Digital multimeter and
oscilloscope. Eelectronic measurements, electronic measurement channel, static
and dynamic characteristics, electromagnetic interferences, signal sources and
acquisition. Sensors. Amplifiers. Noise. Voltage references. Analog-to-digital
conversion. Measurement data communication. Examples and exercises.
English Level
EL
Course Description
4
IP
Prof. dr. sc.
Vedran Bilas
ECT S Credits
SEIS
Lecturer in Charge
86493
WT
Fundamentals of Electronic Measurements and
Instrumentation
CE
213
F orms of Teaching
» Lectures
» Three hours lectures per week for 15 weeks.
» Exams
» There are short written tests on each laboratory exercise. Mid exam
is written and final exam has written and oral part. Students who do
not pass through continuous tests can take a written and oral exam
at the end of semester.
» Exercises
» Tutorials cover numerical examples from the various course topics,
as well as preparation for laboratory exercises. The tutorials are held
for one additional academic hour per week.
» Laboratory Work
» Laboratory exercises provide hands-on experience on practical
implementation of the basic concepts. There are 6 laboratory
exercises. The first two deal with laboratory instruments and
electromagnetic interferences. The rest cover details of electronic
measurement channel on s digital balance.
» Consultations
» Students have weekly scheduled consultations with both professor
and assistant.
» Other
» Two home works are given as preparation for written exams.
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
20 %
25 %
25 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
20 %
0%
40 %
40 %
Comment:
Student must complete all laboratory exercises.
1. Electronic measurements and electronic measurement systems. Basic
concepts: accuracy, precision, sensitivity, measurement uncertainty.
2. Electronic measurement channel. F unctional elements. Sensor. Signal
conditioning and analog processing. Analog-to-digital conversion. Voltage
references. Static and dynamic characteristics.
3. Grounding. Types of signal sources (asymmetric, differential, floating) and
their connection to a measurement circuit. Common and serial interference.
Common mode rejection ratio.
4. Electromagnetic interference. Sources, kinds of coupling and reduction of
the influence on sensor signals.
5. Measurement of voltage and current. Measurement of time and frequency.
Digital multimeter. Analog and digital oscilloscope.
214
6. Sensors, part 1: resistive temperature detectors, thermistors, strain gauges.
Capacitive and inductive sensors. Principle of operation and connection to
measurement circuit.
7. Sensors part 2: piezoelectric sensors, thermocouple, photodiode, Hall
sensor. Principle of operation and connection to measurement circuit.
8. Mid term exam - written
9. Amplifiers, part 1: operational amplifier, basic parameters. Offset. Slewrate. Basic asymmetric amplifier circuits.
10. Amplifiers, part 2: analysis of differential amplifier, common mode
rejection ratio. Instrumentation amplifier, topologies and parameters.
11. Physical origin and kinds of noise. Noise parameters. Thermal noise. Shot
noise. 1/f noise. Amplifier equivalent circuit and total output noise. Signal
to noise ratio.
12. Voltage references in electronic measurement channel. Specification of a
voltage reference. Basic topologies of the Zenner and bandgap based
voltage references.
13. Analog-to-digital conversion, part 1: signal sampling and quantization.
Sampling frequnecy selection, aliasing. Sample and hold circuit analysis.
Quantization error and quantization noise. Oversampling and quantization
noise filtering, increase in ADC’s resolution.
14. Analog-to-digital conversion, part 2: quantizator static characteristic, INL,
DNL. ENOB. Selection of an ADC. ADC basic topologies: flash converter,
successive approximation converter, voltage to frequency converter, two
slope converter, delta-sigma converter. Interconnecting ADC to a
microcontroller. Measurement data transmission and vizualization.
15. F inal exam - written and oral
Literature
C. F . Coombs (1994).
Electronic instrument
handbook, Mc-Graw-Hill
A. F P Van Putten (1996).
Electronic measurement
systems, Taylor&F rancis
A. Šantić (1993).
Elektronička instrumentacija,
Školska knjiga
Vedran Bilas, Goran Horak,
Tihomir Marjanović, Zoran
Stare, Darko Vasić (2013).
Osnove elektroničkih mjerenja
i instrumentacije,
laboratorijske vježbe,
računarstva
Similar Courses
» Electronic Instrumentation, TU Delft
» Measurement science, University of Twente
» Electronic instrumentation, Katholieke Universiteit Leuven
» Sensors nad instrumentation, Manchester University and UMIST
215
Prof. dr. sc.
Zdenko Kovačić
Course Description
Basic properties of the Intelligent control systems. Basics of the fuzzy sets theory.
F uzzy sets in the control. Standard fuzzy controller. Hybrid fuzzy controller.
F uzzy numbers. Lyapunov stability in fuzzy systems. F uzzy phase plane. Adaptive
and selflearning fuzzy controllers. Industrial applications of the intelligent control
systems. Student work on the practical design and implementation of the
intelligent control algorithms.
L0
E-learning Level
L1
Study Hours
Lecturers
30
15
T eaching Assistant
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
E/C
English Level
EEIT
4
C OM
Prof. dr. sc.
Stjepan Bogdan
ECT S Credits
50
60
75
90
Prerequisites
Mathematics 2
C EA
Lecturers in Charge
34341
EP E
Fundamentals of Intelligent Control Systems
EC E
EL
Study Programmes
WT
Learning Outcomes
CE
SEIS
Explain notion of fuzzy sets
Explain functioning principles of fuzzy controller
Explain methods for fuzzy controller preset
Explain notion of fuzzy controller stability
Compute fuzzy controller parameters
Apply fuzzy controller and self-learning fuzzy controller
CS
1.
2.
3.
4.
5.
6.
IP
TI
Students will be able to design and implement intelligent control algorithms
based on the fuzzy sets theory.
F orms of Teaching
» Lectures
» problem solving exercises are part of lectures, with active
participation of students
» Laboratory Work
» Design and simulation of fuzzy controller (Matlab); design of fuzzy
controller on PLC; design of fuzzy controller on PIC and PC
216
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
12 %
21 %
30 %
27 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
12 %
21 %
50 %
47 %
20 %
1. Basics of the fuzzy sets; F uzzy operators and fuzzy norms
2. Linquistic variables; F uzzy propositions and fuzzy relations; F uzzy rules;
F uzzy implication; F uzzy inference engines
3. F uzzy controller structure; F uzzy rule table; Distribution of the fuzzy
membership functions; F uzzyfication and defuzzyfication
4. Initial setting of the fuzzy controller - emulation of the standard control
algorithms
5. Design, simulation and practical implementation of the basic fuzzy
controller
6. Lyapunov stability of fuzzy control systems
7. F uzzy controller design based on phase plane isoclines
8. midterm exam
9. F uzzy numbers; fuzzy controller design based on fuzzy numbers
10. Design, simulation and practical implementation of fuzzy controller based
on fuzzy numbers
11. Basic principles of adaptive control systems
12. Reference model based fuzzy adaptive control
13. Basics of the control system sensitivity theory; self-learning fuzzy
controller based on sensitivity functions
14. Design and implementation of self-learning fuzzy controller
15. final exam
Literature
Zdenko Kovačić, Stjepan
Bogdan (2005). Fuzzy
controller design: theory and
applications, CRC Press
D. Driankov, H.
Hellendoorn, M. Reinfrank
(1993). An Introduction to
Fuzzy Control, SpringerVerlag
Similar Courses
» Knowledge-Based Control Systems, TU Delft
217
Synergistic integration of technical mechanics, electronics, computer engineering
and information technology. Demands on mechatronics components. Modeling of
mechanical components for mechatronic applications, kinematics and dynamics
equations of motion. Block structure of the microcomputer control unit with
process I/O interface. Data acquisition, conversion and exchange between process
and control unit. Translational and rotational electromechanical systems
integration as an example of mechatronic system design. CAD tools application
for modeling, control algorithms synthesis, simulation and real time control.
Study Programmes
E-learning Level
L1
Study Hours
Lecturers
30
15
C OM
Lecturer
T eaching Assistant
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
62.5
75
87.5
Prerequisites
Engineering
IP
SEIS
Learning Outcomes
CS
CE
Define mechatronic system.
Explain holonomic and non-holonomic constraints in mechanical systems
Apply Lagrange formalism to mechanical system modeling.
Apply the bond graph method for modeling of mechatronic systems.
Explain the criteria for selection of the components in mechatronic systems
Apply PID control algorithm to the electromechanical system.
TI
1.
2.
3.
4.
5.
6.
Development of systems thinking in mechatronic product design. Ability of a
mechatronic system integration based on components knowledge.
F orms of Teaching
» Lectures
» Lectures are organized in two cycles. The first cycle consists of 7
two-hours lectures while the second cycle consists of 6 two-hours
lectures.
» Exams
» Examination process consists of midterm exams and final exam.
EEIT
L1
C EA
Course Description
English Level
EP E
Izv. prof. dr. sc.
Jadranko Matuško
4
EC E
Prof. dr. sc.
F etah Kolonić
ECT S Credits
EL
Lecturers in Charge
E/C
34343
Fundamentals of Mechatronics
WT
218
» Laboratory Work
» Laboratory work consists of 6 individual exams (3 simulation exams
and 3 experimental exams).
Grading System
T ype
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
50 %
30 %
30 %
30 %
35 %
35 %
Exam
T hreshold
Percent of
Grade
50 %
0%
30 %
50 %
40 %
30 %
1. Definition of mechatronics. Principles of synergistic integration of
technical mechanics, electronics, computer engineering and information
technology. Examples of mechatronic systems.
2. Osnovni pojmovi mehanike krutih tijela. Modeliranje mehaničkih sustava
primjenom Newtonovih zakona.
3. Conservation laws (momentum, angular momentum and energy) and their
application in modeling of mechanical systems.
4. Analytical mechanics. Holonomic and nonholonomic constraints in
mechanical systems. Lagrange equation.
5. Bond graphs and their applications in modeling of mechatronic systems.
6. Actuators in mechatronic systems. Selection criteria for actuators in
mechatronic systems.
7. Modern actuators in mechatronic systems. Brushless DC motors with
rectangular and sine-wave currents.
8. Mid-term exam
9. The role of the gears in mechatronic systems. The main characteristics of the
gears and the criteria for their selectio
10. The role of sensors in mechatronic systems. Basic characteristics of the
sensor (static and dynamic).
11. Sensors of mechanical quantities. Position sensors. Speed sensor.
Acceleration sensors. F orce and torque sensors.
12. I / O interface and signal conditioning (protection,
changes in types of signals, changes in signal level, eliminating or reducing
the impact of noise).
13. Control in mechatronic systems.
14. An example of mechatronic systems with elastic transmission. Modeling
the mechanical part of the system. Synthesis of control algorithms.
15. F inal exam
219
Literature
L.J.Kamm (1996).
Understanding electromechanical engineering, an
introduction to mechatronics,
IEEE Press
S.E.Lishevski (1999).
Electromechanical systems,
electric machines and applied
mechatronics, CRC Press
Osnove Mehatronike
(predavanja) F.Kolonić ZESAFER 2001
Einfuerung in die Mechatronik
W. Roddeck Teubner, Stutgart 1
Similar Courses
» Mechatronics, ETH Zurich
» Mechatronics, Lund University
» Introduction to Mechatronics (ME210), Stanford
220
Course Description
The term human factors (or ergonomics) in computing is defined and relevant
norms are elaborated. Possible health hazards introduced by using computing
equipment are explained and preventive measures are suggested. Ergonomics of
computerised working environment is elaborated analysing the impact of visual
displays, input and output devices, interior arrangements, microclimate, noise and
illumination on workplace design. Appropriate practical solutions are presented.
Regarding the software ergonomics, fundamental principles of human-computer
interaction are explained, with emphasis on user interface design for desktop, web
and mobile applications.
E-learning Level
L1
Study Hours
Lecturers
30
15
T eaching Assistant
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
90
Prerequisites
Engineering
EEIT
L1
C OM
English Level
C EA
Izv. prof. dr. sc.
Željka Car
4
EP E
Izv. prof. dr. sc.
Gordan Gledec
ECT S Credits
EC E
Lecturers in Charge
E/C
34327
Human Factors in Computing
EL
WT
Study Programmes
SEIS
IP
Learning Outcomes
CE
TI
CS
1. Identify the importance of standards and relevant legal provisions related
to ergonomics
2. Explain the basic principles of user interface development
3. Distinguish ergonomics-related factors related to computer workstations
4. Modify user interfaces in order to increase usability of software products
5. Analyze possible health risks with computer workstations
6. Plan and organize preventive measures to protect the health of people who
work with computers
7. Evaluate ergonomic quality of workplace in computer environment
8. Assess and justify processes of user interface development for desktop, web
or mobile applications
221
The course informs students about possible health hazards of a modern workplace
and explains how to reduce these hazards. By getting acquainted with
fundamental principles of human factors (ergonomics) in computing systems,
students are encouraged to design and improve their own workplace or give
advice to others to design workplace according to ergonomic principles. The
course gives fundamental knowledge about the development of usable user
interfaces for desktop, web and mobile applications.
F orms of Teaching
» Lectures
» Direct lectures of 2 hours in length are held once a week.
» Exams
» Continuous examination is performed in the form of 10-minute
exams on selected lectures.
» Laboratory Work
» Laboratory exercises are performed at home as part of homework.
» Consultations
» According to arrangement with the lecturer, with announcement via
e-mail.
Grading System
T ype
Homeworks
Quizzes
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
30 %
20 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
20 %
30 %
0%
50 %
1. Ergonomics and human factors as a scientific discipline. Introduction to
human factors. Human factors in computing.
2. F undamentals of ergonomics: antropometry, work physiology and
sociology, organisation. Aesthetics and ergonomics. System HumanMachine.
3. Standardization and standards in ergonomics. Legislation in the world and
in Croatia.
4. Hardware ergonomics: monitor, computer, peripherals: keyboard, mouse.
5. Health hazards on a computerised workplace. Practical exercises for
relaxation, stretching and rest for eyes.
6. Ergonomics of computerised workplace: room microclimate, noise.
7. Ergonomics of computerised workplace: interior arrangements, furniture,
workplace illumination. Examples of properly arranged computerised
workplaces.
8. Mid-term exam.
9. Software ergonomics. F undamentals of user interface design. Window
management.
10. F undamentals of human-computer interaction. Basics of user interface
programming. Tools for user interface programming.
222
11. Haptic interfaces. Video games, PCs, touch sensitive screens. Virtual reality.
History, application, design and research.
12. Adaptation of hardware to handicapped persons. Accessibility standards.
13. Software product quality models. Measurements and metrics. Usability
models. Quality standards.
14. Usability on World Wide Web. Usability evaluation methods.
15. F inal exam.
Literature
Mikšić, Dragutin (1997).
Uvod u ergonomiju,
Sveučilište u Zagrebu,
F akultet strojarstva i
brodogradnje
Kroemer, Karl H. E;
Grandjean, Etienne (2000).
Prilagođavanje rada čovjeku:
ergonomski priručnik,
Naklada Slap, Jastrebarsko
Shneiderman, Ben; Plaisant,
Catherine; Cohen, Maxine;
Jacobs, Steven (2009).
Designing the User Interface:
Strategies for Effective
Human-Computer
Interaction, Addison-Wesley
Similar Courses
» Computer Workstation Ergonomics, Stanford
» Ergonomics, Carnegie Mellon University
» UCLA ergonomics, UCLA
» Human-Computer Interaction, Chalmers University
» User Interface Design and Implementation, University of Toronto
223
Introduction to relationships between concepts: information, logic and artificial
languages in telecommunication domain. Observartion, communication, learning,
thinking and domain knowledge. Information as a difference between domain
knowledge states. Information theory and semantic contents of information,
symbols as elements of semantic representations (semantic web). Lexical and
syntax structure, context and semantics. Logic and logical rules, structure of formal
languages. Language space as a function of system development and problems
solving. F unctional specification, modelling. Verification and validation testing.
Methods based on some languages: UML, DSL, Java, XML and TTCN. Industrial
approach for development and application of formal models and methods in
telecommunication systems design.
E-learning Level
L1
Study Hours
Lecturers
45
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
-
C OM
dipl. ing.
EEIT
L1
C EA
Course Description
English Level
50
60
70
85
Prerequisites
Information Theory
EP E
Izv. prof. dr. sc.
Mario Kušek
4
EC E
Izv. prof. dr. sc.
Bruno Blašković
ECT S Credits
EL
Lecturers in Charge
E/C
34288
Information, Logic and Languages
WT
Study Programmes
SEIS
IP
» Computer Science -> Computing (Module) (elective courses, 6th semester, 3rd
year)
CE
Learning Outcomes
CS
Explain term information content and possible use
Explain process for telecommunication software development
Develop software in object-orijented programming language Java
Apply of language XML in telcommunications software
Generate and execute software testing based on unit tests
Conduct functional testing and compare correctness of UML specification
with developed program
TI
1.
2.
3.
4.
5.
6.
Basic knowledge about relationships between information, logic and language,
from the point of view of telecommunication systems analysis and synthesis.
Theoretical and practical knowledge about modelling, specification and testing of
information and communication software including skills related to the usage of
Unified Modelling Language, programming language Java and test tools.
224
F orms of Teaching
» Lectures
» Materials and presentations are on course web page before each
lecture.
» Exams
» Midterm exam and final exam
» Laboratory Work
» complex laboratory assignments which includes: programming in
Java, using XML, and program testing
» Inside the lectures are demonstrations of program solutions and
tools.
» Consultations
» Consultations are conducted by all professors and teaching assistants
every week in 3 different times.
» Searching Web and finding work in the field of the course.
» Personal tools for programming in Java (Eclipse), independent
specification generation, programming and testing programs
» homework
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
20 %
15 %
30 %
25 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
20 %
15 %
0%
55 %
10 %
Comment:
All laboratory work must be successfully accomplished. On oral exam students
must have at least 50% of possible points in order to pass this course.
1. About information, logic and language. Information, logic and languages in
network and service development processes
2. Exception handling and data logging in programming language Java
3. Domain specific languages and network programming in Java
4. Testing in programming language Java, test driven programming (JUnit)
5. Object oriented design for Internet, communication and protocols
6. Object oriented design for Internet, client and server
7. Information: languages for markup.
XML technologies: Introduction to XML
8. Midterm exam.
225
9.
10.
11.
12.
13.
14.
15.
XML technologies: DTD, XML Schema, XPath
XML technologies: XQuery, XSLT
Model based testing
Software logic
Logic in programming languages
Semantics, semantic web
F inal exam.
Literature
Marko Topolnik, Mario
Kušek (2008). Objektno
orijentirano programiranje u
programskom jeziku Java,
F ER - skripta
Marina Bagić Babac, Mario
Kušek (2010). Jezici za
označavanje sadrž aja, F ER skripta
Marina Bagić Babac, Mario
Kušek (2010). Testiranjem
upravljano programiranje,
F ER - skripta
Bruce Eckel (2002). Thinking
in Java, Prentice Hall
Elliotte Rusty Harold
(2004). XML 1.1 Bible, Wiley
Similar Courses
» F ormal Methods for Software Engineering, University of Twente
» Introduction to Information Systems (IIS), EPF L Lausanne
» XML and Related Technologies, University of California Berkeley
» Software Engineering, University of California Berkeley
» Software Engineering, Stanford
» Java and J2EE Programming, Carnegie Mellon University
226
Course Description
Types of multimedia information (audio signals, images and video signals).
F ormats and standards. Digital signal processing. Signal representation. Linear
transforms. F IR and IIR filters. 1-D filtering. Image and video processing. Image
filtering. Enhancement and reconstruction of images and video. Analysis of 1-D
signals, images and video signals. Image segmentation. Information visualization.
Compression basics. Protection of the information integrity and authenticity.
Software tools for information processing and analysis. Applications.
Study Programmes
L1
Study Hours
Lecturers
45
15
C OM
T eaching Assistant
Pavle Prentašić, mag. ing.
comp.
EEIT
E-learning Level
Grading
Acceptable (2)
56
Good (3)
65
Very Good (4)
75
Excellent (5)
87
Grading is based on the points
collected through the course
activities. The same scale is
used for continuous activity
grading and for the final exam.
Prerequisites
Signals and Systems
IP
3rd year)
L1
C EA
Doc. dr. sc.
Marko Subašić
English Level
EP E
Prof. dr. sc.
Damir Seršić
4
EC E
Prof. dr. sc.
Sven Lončarić
ECT S Credits
EL
Lecturers in Charge
E/C
34278
WT
SEIS
Learning Outcomes
Describe various types of multimedia information
Define and describe basic concepts of digital signal processing
List examples of digital signal processing applications
Apply knowledge for solution of simple signal processing problems
Define and describe basic concepts of image and video processing and
analysis theory
6. List examples of digital image and video processing applications
7. Apply knowledge for solution of simple image processing and analysis
problems
TI
CS
CE
1.
2.
3.
4.
5.
F undamental knowledge in digital signal processing, image and video processing
in the multimedia systems. Student understands concepts of signal and image
representation and decomposition in spectral domain. Student gains knowledge
about F IR and IIR filters, basic methods of F IR filter design, and fundamentals of
filter banks and their application to signal compression. Student understands
methods for image enhancement, image restoration, image feature extraction, and
image segmentation.
227
F orms of Teaching
» Lectures
» 12 lectures and 1 problem solving session
» Exams
» The midterm exam and the final exam.
» Laboratory Work
»» Consultations
» After lectures
Grading System
T ype
Homeworks
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
25 %
10 %
30 %
35 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
50 %
50 %
1. Introduction. Types of multimedia information (audio signals, images and
video signals).
2. Signal and system representation.
3. System realizations. Transfer functions.
4. Signal spectrum. Digital filter banks.
5. System design. Examples and problems.
6. Real spectra. Signal interpolation. Non-linear filters.
7. Problem solving sessions.
8. Midterm exam.
9. Introduction to image and video processing.
10. Two dimensional signals and systems. Sampling and quantisation.
11. Image transforms.
12. Image enhancement.
13. Image restoration.
14. Image feature extraction. Image segmentation. Problem solving sessions.
15. F inal exam.
Literature
J. H. McClellan, R. W.
Schafer, M. A. Yoder (1999).
DSP First: A Multimedia
Approach, Prentice Hall
R. C. Gonzalez, R. E. Woods
(2007). Digital Image
Processing, Prentice Hall
Z.-N. Li, M. S. Drew (2003).
Fundamentals of Multimedia,
Prentice Hall
228
Similar Courses
» Computing Curricula for CE 2005 (CE – DSP), IEEE & ACM Computing
Curricula
» EECS 20N Structure and Interpretation of Systems a, University of California
Berkeley
» 74103 Grundlagen der Signalverarbeitung, TU Munchen
» 227-0447-00 Bilddatenanalyse und Computer Vision, ETH Zurich
229
Study Programmes
year)
year)
45
15
Prerequisites
Prerequisites for
Information, Logic and
Languages
Introduction to Virtual
Environments
Learning Outcomes
1.
2.
3.
4.
Identify information, coding and communication problems
Explain coding and compression methods and information limits
Apply accepted knowledge to real systems analysis
Analyze complex information and communication systems
C EA
EP E
40
55
70
85
EC E
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
Nenad Markuš, mag. ing.
Matija Šulc, mag. ing.
EEIT
Study Hours
Lecturers
EL
Introduction to the quantitative Shannon?s theory of information and its
applications, especially to information coding. Mathematical definition and
properties of information. Source coding theorem, lossless data compression and
optimal lossless coding. Structural properties of natural languages. Information
characteristics of images. Cryptography, data encryption. Noisy communication
channels, channel coding theorem, multiple access channels. Error detection and
error correction. Cyclic, binary block and convolutional codes, capacityapproaching codes. Gaussian noise, time-varying channels. Unified theory of
information with applications to other sciences.
L1
WT
Course Description
E-learning Level
IP
Doc. dr. sc.
Marin Vuković
L0
SEIS
Doc. dr. sc.
Željko Ilić
English Level
CE
Prof. dr. sc.
Igor Sunday
Pandžić
4
CS
Prof. dr. sc.
Alen Bažant
ECT S Credits
TI
Lecturers in Charge
E/C
34315
Information Theory
230
5. Explain phenomens in different area of science
6. Estimate performances of different information and communication
systems
After finishing this course students will be able to understand and apply
fundamentals of information theory. They will know principles of information
coding as well as properties of communication channels. They will gain skills
required for modelling and analysis of optimal, error-detecting and errorcorrecting codes. They will develop learning skills necessary to continue to
undertake further study in the field of information theory and coding theory.
F orms of Teaching
» Lectures
» F irst cycle (seven weeks): lectures then Midterm exam, and Second
cycle (six veeks): lectures and F inal exam. Lecture duration: 3 hours
per week.
» Exams
» Midterm exam: 8th week; F inal exam: 15th week.
» Laboratory Work
» Programming and testing basic coding algorithms.
» Consultations
» Consultation every week in terms defined by lecturer.
» Programming skills: students write programs for different coding
algorithms.
Grading System
T ype
Exam: Written
T hreshold
Percent of
Grade
0%
0%
50 %
50 %
Exam
T hreshold
Percent of
Grade
0%
0%
100 %
Comment:
Although laboratory exercises and homeworks have 0% of a total share on this
course, students are obliged to successfully complete both of these activities. In
other words, they are precondition, i.e. it is impossible to pass the final exam or
any further exam without having successfully completed laboratory exercises and
homeworks.
1. Introduction. Information, communication and processing. Model of
communication system.
2. Discrete communication system, probability distributions and measures of
information, entropy and mutual information. Communication channels,
discrete memoryless noisy communication channels, channel capacity.
3. Information sources, information content of discret information source,
information redundancy, data compression and optimal coding.
4. Sources with memory. Shannon-F ano, Huff,man, aritmetic coding and
dictionary methods (Lempel-Ziv algorithms).
231
5. Source coding: quantization, undersampling, transform methods, prediction
method.
6. Introduction to block codes: Hamming distance, perfect codes, parity check
coding.
7. Linear binary block codes: parity check matrix, syndrome decoding.
9. Hamming and cyclic codes. Linear BCH block codes. R-S codes.
10. Convolutional codes. Viterbi algorithm. Turbo codes.
11. Signals: deterministic, random, noise, spectar. Continous channel.
12. Sampling and quantization.
13. Capacity of band-limited channel.
14. Introduction to media coding.
Literature
I.S. Pandžić, A. Bažant, Ž.
Ilić, Z. Vrdoljak, M. Kos, V.
Sinković (2009). Uvod u
teoriju informacije i kodiranje,
2. izd., Element, Zagreb
V. Sinković (1997).
Informacija, simbolika i
semantika, Školska knjiga
R.E. Hamming (1986).
Coding and Information
Theory. 2nd ed., PrenticeHall. Englewood Cliffs,
New Jersey
R. Togneri, C.J.S. deSilva
Information Theory and
Coding Design, Cjapman &
Hall/CRC
F .M. Reza (1994). An
Introduction to Information
Theory, Dover, New York
Pandžić, I. S. Bažant, A. Ilić, Ž.
Vrdoljak, Z. Kos, M. Sinković,
V. Uvod u teoriju informacije i
kodiranje. Element, 2007.
Similar Courses
» Theorie de l information/Information Theory, EPF L Lausanne
» Infromation Theory, Stanford
» Informationstheorie und Quellencodierung, TU Munchen
» Information and Entropy, MIT
232
Study Programmes
3rd year)
Learning Outcomes
45
15
Doc. dr. sc. Siniša Popović
Dr. sc. Karla Brkić
Marko Đurasević, mag. ing.
Ivan Krešo, mag. ing. comp.
Grading
Acceptable (2)
50
Good (3)
Very Good (4)
Excellent (5)
The distribution of points for
each grade greater than 2 will
be made depending on the
severity of exams, in
accordance with Gausssovom
distribution.
Prerequisites
Algorithms and Data
Structures
Mathematics 2
CE
TI
CS
1. Define concepts of contemporary graphics hardware
2. Apply mathematics, physics and computer programming to computer
graphics applications and problem solutions
3. Develop interactive graphics applications using graphics application
programming interface
4. Develop applications that implement graphics primitives and demonstrate
geometrical transformations
5. Explain principles of the 3D graphics rendering and modelling
6. Solve problems in 3D graphics and develop graphical applications
This course introduces students to the theory and practice of interactive computer
graphics. Its principal aim is to teach the fundamental principles of two- and
three-dimensional interactive computer graphics. OpenGL is used as the API
platform for practical programming exercises, and as an example of a system
which incorporates many of the fundamental ideas and algorithms of computer
graphics.
EEIT
Study Hours
Lecturers
C OM
L2
C EA
E-learning Level
EP E
L1
EC E
Interactive computer graphics is the art and science of creation, manipulation and
viewing of the objects representations using computer technologies. This requires
the design and construction of models that represent objects in ways that support
the creation and viewing of them first, than the design of devices and techniques
through which the person may interact with the model or the view and the
creation of techniques for rendering and preserving the model. The goal of this
course is to provide an introduction to the theory and practice of computer
graphics.
English Level
EL
Course Description
4
WT
Prof. dr. sc.
Željka Mihajlović
ECT S Credits
IP
Lecturer in Charge
E/C
34287
Interactive Computer Graphics
SEIS
233
F orms of Teaching
» Lectures
» 7 weeks x 3 hours Mid-term exam 6 weeks x 3 hours F inal exam
» Exams
» Mid-term and final exam or
classic exam
» Laboratory Work
» http://www.zemris.fer.hr/predmeti/irg/laboratorijske_vjezbe.html
» Consultations
» Office D331, once a week.
» E-learning
» http://ferko.fer.hr/ferko/Login.action
wiki
Grading System
T ype
Homeworks
Quizzes
Attendance
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
15 %
5%
8%
2%
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
50 %
50 %
1. Introduction. Computer graphic pipeline. Raster Graphics.
2. Object rasterization. Discretization aliasing artifacts. Bresenham algorithm.
3. Two-dimensional and three-dimensional computer graphics. Mathematical
tools in geometric modeling. Homogeneous coordinates.
4. Graphics primitives. Two-dimensional primitives and transformations.
Three-dimensional primitives and transformations. Affine transformation.
Linear interpolation, bilinear interpolation. Barycentric coordinates.
5. Graphics software and hardware. Data structures. Graphic Standards, a
graphical programming interface (API). The basics of OpenGL.
6. Modeling of objects and scenes. Polygonal, parametric, implicit, volumetric
and procedural objects. Geometrical and topological data.
7. Midterm
8. Bezier curve.
9. Hidden surface removal algorithms, clipping. BSP tree and octree.
10. Global and local illuminations models. Shading.
Ray casting. Ray tracing.
11. Radiosity. Shadows. Shadow maps, shadow volumes and soft shadows.
12. Color and perception. Color models. Gamma correction. HDR.
13. Texture mapping
14. F ractal objects.
15. F inal exam
234
Literature
Edward Angel (2009).
Graphics: A Top-Down
Approach with OpenGL,,
Pearson
Marko Čupić i Željka
Mihajlović (2011).
Interaktivna računalna
grafika kroz primjere u
OpenGL-u, zavodska skripta
Dave Shreiner, Mason Woo,
Jackie Neider, Tom Davis
(2009). OpenGL
Programming Guide: The
Official Guide to Learning
OpenGL, Addison-Wesley
Donald Hearn and M.
Pauline Baker (2003).
Computer Graphics with
OpenGL, third edition,
Prentice Hall
Similar Courses
» CS 248: Interactive Computer Graphics, Stanford
» 6.837 Computer Graphics, MIT
» Informatique Graphique, EPF L Lausanne
» F OUNDATIONS OF COMPUTER GRAPHICS, University of California
Berkeley
» Surface Representations and Geometric Modeling - SS11 - Home, ETH Zurich
» IN2770 Computer graphics, TU Delft
» CS 5237 Computational Geometry and Applications, NU Singapore
» Introduction to Computer Graphics, University of California Berkeley
» Computer Graphics, EPF L Lausanne
» GDV1, ETH Zurich
235
English Level
L2
E-learning Level
L3
Study Hours
Lecturers
Exercises
30
30
Grading
dr. sc.
Hrvoje Hegeduš
Course Description
IP
WT
EL
EC E
EP E
The aim of this course is to give practical understanding of fault finding in
electronic circuits. Electrical faults in any electrical system often origin from
instance, from bad construction, bad installation, ageing, overvoltages or
overheating. This faulty systems of electronic circuit are comprised of a number of
smaller circuits/units connected together to perform a final function. To
understand the overall circuit and find a fault, it is necessary to break it down into
smaller, more easily understood units and then apply fault finding strategy. This is
most important when something should be tested to find electrical fault. The
students will learn to select fault finding measuring instruments, how to use them
and be able to apply the techniques used for the diagnosis of faults. One of skills is
basic understanding of safe working practices when carrying out fault finding
activities in electrical and electronic circuits under voltage. Examples are given for
fault diagnostics in electrical installations, information and communication
systems faults and on-board diagnostic systems.
EEIT
2
C OM
Doc. dr. sc.
Marko Jurčević
ECT S Credits
C EA
Lecturers in Charge
E/C
70072
Introduction Into Fault Finding
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
CE
SEIS
Grading System
CS
TI
1. Introduction to analogue and digital circuit diagrams, types of circuit
diagrams, electronic components
2. Health and safety requirements for working with electronic systems
3. Normal equipment operating conditions and the different component and
circuit fault conditions
4. Normal equipment operating conditions and the different component and
circuit fault conditions
5. Use of a variety of different test and measurement instruments
6. Use of a variety of different test and measurement instruments
7. Use of different fault location and signal tracing techniques and faultfinding aids
8. Software analysis, simulation and measurement tools
9. Preparing written fault location strategies for given electronic systems
10. Practical examples - installation faults
11. Practical examples - installation faults
236
12.
13.
14.
15.
Practical examples - information and communication systems faults
Practical examples - on-board diagnostic systems
Literature
Brian Scaddan (2008).
Wiring Systems and Fault
Finding for Installation
Electricians, Newnes
Ian Sinclair, John Dunton
(2007). Electronic and
electrical servicing, Newnes
Tom Denton (2006).
Advanced Automotive Fault
Diagnosis, Elsevier
Earl D. Gates (2007).
Introduction to electronics,
Delmar
237
Java as a programming language. Java as a processor independent platform.
Classes and objects - inheritance, polymorphism, encapsulation, hiding. Java
collection framework - sets, lists, trees, stacks, queues, maps. Java Generics.
Multithreading and multithreaded applications. Synchronization problems and
synchronization techniques (mutexes, semaphores, barriers). Design and
development of applications with graphical user interface: AW T and Swing; usage
of existing and development of custom components. MVC paradigm. Test Driven
Development (TDD). Working with files and file systems. Data streams.
Distributed applications (java.net packet). Usage of UDP and TCP protocol. HTTP
protocol. Design of Web applications. Java Servlets and Java Server Pages (JSP).
Web forms. Apache Tomcat. Security in Web applications. Advanced technologies:
ANT, Hibernate, MySQL. Working with relational databases. Mapping and
storage of objects into relational databases (O/R mapping).
E-learning Level
L1
Study Hours
Lecturers
60
15
C OM
Grading
E/C
L0
EEIT
English Level
Course has no grades. To pass
the course, students must be
present at lectures, pass all
homework and individual
student project. There will be
no additional exams.
C EA
Course Description
4
EC E
Doc. dr. sc.
Marko Čupić
ECT S Credits
EL
Lecturer in Charge
38047
EP E
Introduction to Java Programming Language
WT
IP
Learning Outcomes
SEIS
Create programs using Java programming language
Use Java collection framework for data organization and work with files
Develop graphical user interface using Swing
Apply multithreading
Combine Java application and relational database and use O/R mappers
Construct web-servers and use Servlet and JSP technologies for
construction of web applications
7. Develop distributed applications which communicate by computer
network
TI
CS
CE
1.
2.
3.
4.
5.
6.
Students will be able to develop desktop and web applications using Java
programming language. They will be able to use built-in data collections, work
with files, develop graphical user interface and employ multithreading. They will
be able to write distributed applications which communicate by computer
network. They will be able to combine application with relational database and
use O/R mappers. They will understand internal working of web application and
will be able to create them.
238
F orms of Teaching
» Lectures
» Will be held in computer laboratories so that students can work out
presented examples and solve given course tasks.
» Exams
» Students will be given a series of problems to solve as part of
regular homeworks. At the end, an individual student project will be
given which is mandatory for positive grade.
Grading System
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
Comment:
Course does not have grades.
1. Introduction. Java as programming language, Java as platform. F irst
program
2. Classes and objects. References
3. Test-driven development
4. Java collection framework (1)
5. Working with files
6. Java collection framework (2)
7. Multithreaded applications
8. Swing (1)
9. Swing (2)
10. Distributed applications. java.net package
11. Web applications
12. Web forms. Tomcat servlet container. Web security.
13. Additional technologies (ANT, Hibernate, MySQL)
14.
15.
Literature
Marko Čupić (2007).
Materijali za Java tečaj
Kent Beck (2006). TestDriven Development, By
Example, Addison-Wesley,
Boston
Tutorijali s
http://java.sun.com/
Bruce Eckel (2002).
Thinking in Java, 3rd Edition
(Free electronic book),
Prentice-Hall
239
Pattern recognition. Basic motivation. Pattern recognition model. Examples of
pattern recognition systems. Relation: artificial intelligence ? pattern recognition.
F eature extraction and selection. Linear and non-linear transformations. F eature
coding. Linear decision functions. Non-linear decision functions. Learning
procedures for decision functions. Statistical classification. Bayes classifier.
Estimation of parameters.Non-numerical pattern recognition. Structural
classification. Syntactic recognition. Stochactic Grammars and Languages.Cluster
analysis. Examples of pattern recognition system design.
E-learning Level
L1
Study Hours
Lecturers
45
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
61
74
89
Prerequisites
Mathematics 3 - C
Mathematics 3 - EE
WT
Study Programmes
SEIS
IP
3rd year)
Learning Outcomes
CE
TI
CS
1. Define concepts of pattern recognition
2. Explain and distinguish porocedures, methods and algorithms related to
pattern recognition
3. Apply methods from the pattern recognition for new applications
4. Analyze and breakdown problem related to the pattern recognition system
5. Design and develop a simple pattern recognition system for the specific
application
6. Evaluate quality of solution of the pattern recognition system
The course “Introduction to Pattern Recognition” enables the students to
understand basic concepts of pattern analysis that are used in machine
interpretation of a world and environment in which machine works. Pattern
recognition is basic building block of understanding human-machine interaction.
EEIT
L1
C OM
English Level
C EA
Course Description
4
EP E
Prof. dr. sc.
Slobodan Ribarić
ECT S Credits
EC E
Lecturer in Charge
E/C
34358
Introduction to Pattern Recognition
EL
240
F orms of Teaching
» Lectures
» Classes are held in two phases - each 7 weeks. Classes are conducted
over 15 weeks with a weekly load of three hours. After each phase,
ie, in the 8th week of lectures and 15th week of lectures exames are
held.Week immediately prior to the exams is scheduled for problem
solving and illustrations of procedures.
» Exams
» Knowledge checking is done by written examination twice in a
semester. Short ununounced exams are held periodically.
» Consultations
» Consultations are planned for 2 hours per week.
Grading System
T ype
Quizzes
Class participation
Attendance
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
6%
2%
2%
40 %
50 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
0%
0%
100 %
1. Pattern recognition. Task of pattern recognition. Basic motivation.
Example of pattern recognition system.
2. Model of pattern recognition system.
3. Linear decision function.
4. Determining linear decision function. Perceptron algorithm.
5. Illustration of procedures. Numerical problem solving.
6. Nonlinear decision functions. Generalized decision functions.
8. Midterm exam.
9. Nonlinear decision functions – potential functions.
10. Statistical classification. Bayes classifier. Estimation of parameters.
11. Syntactic (non-numerical) pattern recognition.
12. Syntactic (non-numerical) pattern recognition. Stochastic grammar.
Grammar inference.
13. Introduction to clustering – unsupervised learning.
15. F inal exam.
241
Literature
S. Theodoridis, K.
Koutroumbas (2009). Pattern
Recogniton, Elsevier
R.O. Duda, P. E. Hart, D.G.
Stork (2001). Pattern
Classification, J. Wiley, New
York
L. Gyrgyek, N. Pavešić, S.
Ribarić (1988). Uvod u
raspoznavanje uzoraka,
Tehnička knjiga Zagreb
J.T. Tou, R.C. Gonzalez
(1977). Pattern Recognition
Principles, Addison-Wesley
Similar Courses
» Pattern Recognition, Cambridge
» Pattern Recognition, TU Delft
» PATTERN RECOGNITION AND ANALYSIS, Cambridge
» Pattern Recognition and Analysis, MIT
242
ECT S Credits
3
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
30
Grading
Only positive or negative
mark. 50% for positive mark.
C EA
Doc. dr. sc.
Sanda Pleslić
Course Description
EC E
EP E
Physical quantities; units; vectors; scalars; coordinate systems. Kinematics.
Dynamics. Mechanics of fluids. Heat and thermodynamics. Oscillations and waves.
Electricity and magnetism. Optics; modern physics.
Study Programmes
EL
(bridge course, 1st semester, 1st year)
WT
Learning Outcomes
SEIS
IP
Apply knowledge about physical quantities, units and coordinate systems
Analyze and compute simple problems from kinematics and dynamics
Explain basic phenomena in fluid mechanics
Analyze simple thermodynamical systems
Explain oscillating systems and wave phenomena
Explain basic laws of electromagnetism
Analyze and compute simple optical systems
Explain phenomena in modern physics
CE
1.
2.
3.
4.
5.
6.
7.
8.
EEIT
Lecturer in Charge
E/C
137274
Introduction to physics
C OM
CS
F orms of Teaching
» Lectures
TI
» Lectures with examples and problems.
» Exams
» Written exam
» Consultations
» Consalting
» Demonstrations
243
Grading System
T ype
Attendance
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
10 %
45 %
45 %
Exam
T hreshold
Percent of
Grade
0%
0%
10 %
0%
90 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Physical quantities; units; vectors; scalars; coordinate systems. Kinematics.
Dynamics. Mechanics of fluids.
Heat and thermodynamics. Oscillations and waves.
Electricity and magnetism.
Optics; modern physics.
Exam
REMARK: The course is performed continuously for the first 5 weeks of
classes.
-
Literature
Matko F izić (2008). Klasifikacijski ispiti na tehničkim
fakultetima, Element
Nada Brković, Planinka Pećina (2013). Fizika u 24 lekcije,
Element
Similar Courses
» Programme Specification: Part IA Physics, Cambridge
244
The primary goal of the course is to enable students to use the programming
language R with the emphasis on problem solving and practical application. The
R programming language is tailored specifically for exploratory, statistical and
data mining analysis of data sets. By its nature, it has a lot in common with
classical programming languages such as Python, Java or C ++ but also with
statistical tools such as SAS or SPSS. With its interactive approach, but also the
ability to write complex programming scripts, R has established itself as one of
the leading statistical programming languages which together with the
accompanying packages offers a very efficient way to perform complex analysis of
data sets and create reports accompanied by complex visualizations and
calculations. Learning R requires a specific combination of programming skills,
knowledge of elementary statistics, but also a certain level of creativity and
readiness for challenges.
L0
E-learning Level
L1
Study Hours
Lecturers
30
15
50
62.5
75
85
C EA
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
Lecturer
EEIT
English Level
EP E
Course Description
4
EC E
Doc. dr. sc.
Damir Pintar
ECT S Credits
EL
Lecturer in Charge
E/C
147661
Introduction to R programming language
WT
IP
Study Programmes
CS
CE
SEIS
3rd year)
TI
Learning Outcomes
1.
2.
3.
4.
5.
Analyze small and large data sets in a meaningful and organized manner
Identify the nature of the data and the nature of its processing
Use the interactive programming approach to data analysis
Modify the raw data into a form suitable for analysis
Prepare complex scripts and software packages in the programming
language R
6. Apply machine learning methods in the programming environment
7. Apply the methodology of preparing reports
245
F orms of Teaching
» Lectures
» PPT presentations and interactive demonstration of examples in R
language with the option of executing examples on personal
computers
» Laboratory Work
» Writing scripts in R language , programmatic data analysis,
applying machine learning methods through the R language,
writing reports.
» Consultations
» Consultations in a predefined weekday time slot or via e-mail
correspondence.
» Dataset analysis and reporting
» E-learning
» Solving interactive scripts in the programming language R with the
help of the Swirl package
Grading System
T ype
Homeworks
Class participation
Seminar/Project
Attendance
T hreshold
Percent of
Grade
10 %
5%
0%
5%
0%
5%
10 %
20 %
10 %
5%
20 %
5%
15 %
25 %
Exam
T hreshold
0%
0%
0%
0%
0%
0%
Percent of
Grade
0%
0%
0%
0%
0%
1. Introduction to statistical programming, exploratory analysis and data
mining; comparison between R and other programming languages
2. Basic R concepts: data types, functions, data structures, index vectors
3. Basic R concepts: functions, libraries, more advanced programming
examples
4. Advanced programming concepts in R - OOP, optimization, debugging
5. Dataset management - data retrieval, cleaning and transformation
6. Dataset management - data retrieval, cleaning and transformation (2)
7. Exploratory analysis and data visualization: basic plotting
8. 1. midexam
9. 1. midexam
10. Exploratory analysis and data visualization: advanced visualization
methods, outlier detection and management, ggplot2 package
11. Working with distributions in R: inferential satistics, sampling,
simulations
12. Organization of a data analysis process and report creation - R Markdown
13. Chosen data mining methods: predictive analysis - regression, classification
14. Chosen data mining methods: decision trees, clustering, association rules
15. A look ahead: overview of paths for expanding the knowledge of R through
illustrative examples
246
Literature
Richard Cotton (2013).
Learning R, "O'Reilly Media,
Inc."
David Diez, Christopher
Barr, Mine ÇetinkayaRundel (2015). OpenIntro
Statistics
Jared Lander (2013). R for
Everyone, Addison-Wesley
Professional
Jiawei Han, Jian Pei,
Micheline Kamber (2011).
Data Mining: Concepts and
Techniques, Elsevier
Similar Courses
» Programming with R, University of California Berkeley
» Statistical Learning, Stanford
» An Introduction to R: Software F or Statistical Analysis, Cambridge
247
Study Programmes
Learning Outcomes
1. Model the behavior of a computer system and communication protocol
using formal language
2. Design a computing process using a formal model
3. Apply formal models to verify the corectness of a computer system
4. Categorize a problem with respect to Chomsky hierarchy of formal
languages
5. Select the optimal formal model for description, design, and
implementation of a computer system
6. Estimate time and space complexity of a computing process
7. Evaluate the efficiency of a computer system and communication protocol
E/C
C EA
Lecturers
Dr. sc. Goran Delač
Dr. sc. Marin Šilić
Dr. sc. Klemo Vladimir
Zvonimir Pavlić, mag. ing.
comp.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
75
88
Prerequisites
Engineering
Prerequisites for
Programming Language
Translation
Software Design
The course prepares the students for application of formal models in engineering
for the design of computer and communication processes, protocols, and systems.
Based on the problem definition, students will be able to construct the formal
model of the proposed solution, validate its correctness, estimate its efficiency and
complexity, implement it in software or hardware, as well as document and test
it. F urthermore, students acquire solid fundamental knowledge that is the basis
for further study of theory of complex computing processes and systems.
EEIT
45
15
15
C OM
Study Hours
Lecturers
Exercises
EP E
The course introduces formal models of automata and grammars used for
description, definition, software and hardware implementation, as well as
verification of correctness of execution of computer and communication processes,
protocols, and systems. Basic properties of computing processes and systems, such
as determinism, decidability, computability, complexity, and tractability, are
explained. Basics of automata theory, formal grammars, and languages are given.
Chomsky hierarchy of languages is presented: regular languages, context-free
languages, context-sensitive languages, recursive languages, and recursivelyenumerable languages. Complexity classes and hierarchy of complexity classes are
defined: complete and hard problems, polynomial classes P and NP, and reduction
method.
L1
EC E
Course Description
E-learning Level
EL
Doc. dr. sc.
Ante Đerek
L1
WT
Doc. dr. sc.
Dejan Škvorc
English Level
IP
Izv. prof. dr. sc.
Zoran Kalafatić
6
CE
Prof. dr. sc.
Siniša Srbljić
ECT S Credits
CS
Lecturers in Charge
86537
SEIS
Introduction to Theoretical Computer Science
TI
248
F orms of Teaching
» Lectures
» Lecturer-driven classroom presentations, examples of practical
application of formal languages, automata, and grammars
» Exams
» Two written exams
» Exercises
» Lecturer-driven classroom problem solving, preparation for written
exams
» Laboratory Work
» Implementation of algorithms on formal languages, automata, and
grammars. Application of automata and grammars in practical
software development. Online submission and evaluation of student
work.
» Consultations
» Individual office hours with lecturers and assistants are organized on
student's request.
Grading System
T ype
Class participation
Exam: Written
T hreshold
Percent of
Grade
50 %
0%
0%
0%
30 %
5%
35 %
35 %
Exam
T hreshold
Percent of
Grade
50 %
0%
0%
0%
0%
50 %
100 %
Comment:
Continuous Assessment: Min (Mid Term Exam: Written + F inal Exam: Written +
Lecture attendance and oral examination in classroom) = 50 %
1. Symbol, alphabet, string, and formal language; Example of formal
language, automata, and grammar; ([1], pp. 1-14) Deterministic finite
automata: example and definition; Deterministic finite automata:
implementation and minimization; ([1], pp. 15-29)
2. Determinism and nondeterminism; Nondeterministic finite automata;
Nondeterministic finite automata with e-moves; ([1], pp. 29-39) F inite
automata with output; Regular expressions; F inite automata generator;
([1], pp. 39-51)
3. Properties of regular sets; F ormal grammar: example and definition;
Regular grammar; ([1], pp. 51-63) Regular grammar (continuation);
Context-free languages; Context-free grammar; Grammar and language
ambiguity; Simplification of context-free grammars; ([1], pp. 63-78)
4. Simplification of context-free grammars (continuation); ([1], pp. 78-88)
String derivation and parsing; Implementation of top-down parsing;
Recursive-descent parsing; Bottom-up parsing; LR parsing; ([1], pp. 89102)
5. Pushdown automata: example and definition; ([1], pp. 103-114) Pushdown
automata (continuation); Properties of context-free languages; ([1], pp. 114125)
249
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Exercises: regular languages;
Exercises: context-free languages;
F irst mid term exam: regular languages, context-free languages;
Recursively-enumerable languages; Turing machine; Techniques for
constructing Turing machine; ([1], pp. 126-138) Generalization of basic
Turing machine model; ([1], pp. 139-146)
Restriction of basic Turing machine model; Turing machine based language
generation; ([1], pp. 146-151) Unrestricted grammar; Properties of recursive
and recursively-enumerable languages; Computability; Decidability; ([1],
pp. 152-164)
Context-sensitive languages; Context-sensitive grammar; Linear bounded
automata; Properties of context-sensitive languages; ([1], pp. 165-172)
Properties of context-sensitive languages (continuation); Chomsky
hierarchy of formal languages, grammars, and automata; Definitions of
space and time complexity; Complexity of automata and languages;
Properties of space and time complexity functions; ([1], pp. 173-187)
Complexity classes; ([1], pp. 187-190) Complexity properties of hierarchy
of languages; ([1], pp. 190-194)
Polynomial complexity classes; Tractability; Reduction method; Definition
of complete and hard problems; P-complete (hard) and NP-complete (hard)
problems; ([1], pp. 194-199)
Exercises: recursively-enumerable languages, context-sensitive languages,
complexity theory;
F inal exam: whole course matter;
Literature
S. Srbljić (2007). Uvod u
teoriju računarstva, Element
Zagreb
J. Hromkovic (2003).
Theoretical Computer Science:
Introduction to Automata,
Computability, Complexity,
Algorithmics, Randomization,
Communication, and
Cryptography, Springer
J. E. Hopcroft, R. Motwani,
J. D. Ullman (2000).
Introduction to Automata
Theory, Languages, and
Computation, AddisonWesley
P. Linz (2000). An
Introduction to Formal
Languages and Automata,
Jones & Bartlett Publishers
D. C. Kozen (1997).
Automata and Computability,
Springer
Similar Courses
» CS: AL5-AL7; CE: ALG5-ALG6, IEEE & ACM Computing Curricula
» Introduction to Automata and Complexity Theory, Stanford
» Automata, Computability, and Complexity, MIT
» Automata Theory and F ormal Languages, NU Singapore
» Automaten, F ormale Sprachen und Berechenbarkeit, TU Munchen
» Theoretische Informatik, ETH Zurich
» Models of Computation, Oxford
» Basic models in computer science, University of Twente
» Computability and Complexity, University of California Berkeley
» Complexity Theory, Cambridge
250
Lecturer in Charge
122825
ECT S Credits
4
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
30
15
C OM
Grading
Doc. dr. sc.
Tomislav Hrkać
C EA
Course Description
EC E
EP E
An introduction to the Scala programming language. Short history, a comparison
with Java and other similar languages. Scala in context of object oriented and
functional programming. Overview of commonly used provided functions.
Language features. Support for concurrent programming. Overview of data
st ruct ures. Testing libraries. Overview o commonly used libraries and
frameworks. Short introduction to using Scala on the Android platform.
EL
Study Programmes
TI
CS
CE
SEIS
IP
WT
year)
3rd year)
Grading System
T ype
E/C
Introduction to the Scala programming language
EEIT
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
251
Virtual environments are objects and spaces created as models on a computer and
brought to life using 3D computer graphics. The applications reach into a wide
variety of fields such as computer games, television, design, virtual prototyping,
training, various types of simulation, information visualization, communications,
marketing etc. The fundamental techniques of virtual environments are presented,
including virtual scene modeling, rendering, intersection testing, collision
detection and interaction. More advanced technologies are introduced and
explained: virtual and augmented reality networked virtual environments, virtual
environments on mobile platforms. Applications of these technologies are
discussed, aiming to stimulate students to think of the opportunities opened by
them.
E-learning Level
L1
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
No additional comments.
C OM
Nenad Markuš, mag. ing.
EEIT
L0
55
65
75
90
C EA
Course Description
English Level
EP E
Izv. prof. dr. sc.
Krešimir Matković
4
EC E
Prof. dr. sc.
Igor Sunday
Pandžić
ECT S Credits
Prerequisites
Information Theory
EL
Lecturers in Charge
E/C
34345
Introduction to Virtual Environments
WT
Study Programmes
TI
CS
CE
SEIS
IP
3rd year)
year)
Learning Outcomes
1.
2.
3.
4.
5.
6.
Define the concept of virtual environment
Define the concept of virtual scene and all its elements
Use 3D graphics tools and APIs
Model 3D objects
Apply knowledge in projects applying 3D virtual environments
Develop applications of virtual environments
252
Students will gain knowledge and skills enabling them for practical
implementation of models and applications of virtual environments, and for
participation in projects involving virtual environment technologies.
F orms of Teaching
» Laboratory Work
» F our lab assignments:
V1 Modelling - Maya
V2 Scene graph - VRML
V3 Principles of rendeirng - ray tracing
V4 Basic API - OpenGL
» Experiments
» Interactive 3D software is used to demonstrate key concept during
certain lectures.
Grading System
T ype
Class participation
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
25 %
6%
29 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
25 %
6%
0%
69 %
1. Virtual environment: concept, definition, overview, classification of terms
related to virtual environments.
2. Overview of virtual environment applications: games, TV, design, virtual
prototyping, training, simulation, information visualization,
communications, marketing etc.
3. Virtual environment modeling: virtual scene and its components, modeling
of geometry.
4. Virtual environment modeling: camera, lighting and material models.
5. Organization of the virtual environment in a scene graph, basic geometry
transformations in the scene, scene graph traversal.
6. Rendering: ray tracing as example of a rendering method, typical rendering
pipeline.
7. Graphics hardware: architecture, use, memory needs.
8. Languages and formats for virtual environments.
9. Application Programming Interfaces (APIs) for virtual environments.
10. Intersection tests and collision detection.
11. Interaction in the virtual scene: selection and manipulation of objects,
navigation, introducing navigation constraints.
12. Networked virtual environments: concept, applications, fundamental
techniques.
13. Virtual environments on the WWW: displaying virtual environments on
the WWW, data types and formats, networking requirements.
14. Introduction to virtual reality, fundamental techniques and applications.
253
15. Introduction to augmented reality, fundamental techniques and
applications.
Literature
Igor S. Pandžić, Tomislav
Pejša, Krešimir Matković,
Hrvoje Benko, Aleksandra
Čereković, Maja Matijašević;
(2011). Virtualna okruženja:
Interaktivna 3D grafika i njene
primjene, Element Manualia Universitatis
Studiorum Zagrabiensis
Tomas Akenine-Möller,
Eric Haines, Naty Hoffman
(2008). Real-Time Rendering,
A. K. Peters Ltd.
Mel Slater, Anthony Steed,
Yiorgos Chrysanthou (2001).
Computer Graphics and
Virtual Environments: From
Realism to Real-Time,
Addison-Wesley Pub Co
Similar Courses
» Virtual Reality (CS 294), University of California Berkeley
» Building Virtual Worlds [53-831], Carnegie Mellon University
» Computer Graphics and Applications (CSC204), NU Singapore
» 3D Computer graphics en virtual reality (IN4006), TU Delft
254
Prof. dr. sc.
Mervan Pašić
Course Description
1
English Level
L0
E-learning Level
L1
Study Hours
15
T eaching Assistant
Dr. sc. Siniša Miličić
E/C
ECT S Credits
C OM
Lecturer in Charge
91611
EEIT
Laboratory and Skills – Maths on the Computer
Grading
C EA
EC E
EP E
The student should learn some commonly used mathematical software as to be
able to check the solution of problems that he has been or not solving without
using the computer. As far as connected with Mathematics 1, this includes
differential and integral calculus of one real variable as well as solving linear
systems of equations.
EL
Study Programmes
WT
Learning Outcomes
SEIS
Show on computer how calculate determinants of higher order
Show on computer matrix algebra
Show on computer the solving of linear systems of higher order
Write a program for solving a problem from linear algebra
Show on computer a basis of differential calculus
Show on computer a basis of integral calculus
CE
1.
2.
3.
4.
5.
6.
IP
CS
TI
Getting acquainted with elementary orders and programming principles from
software for sympbolic mathematical calculus and learning how to use them
properly when checking solutions of mathematical problems.
F orms of Teaching
» Exams
» On computer and written.
» Laboratory Work
» Laboratory exercises are made in weeks reserved for laboratory
exercises and skills.
255
Grading System
T ype
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
100 %
1. Introduction to the basic commands of Mathematica
2. Matrix algebra on computer by using Mathematica
3. Computation determinants of higher order on computer by using
Mathematica
4. Solving linear systems of algebraic equations on computer by using
Mathematica
5. Solving linear systems of algebraic equations on computer by using
Mathematica
6. Vector calculus on computer by using Mathematica
7. Vector calculus on computer by using Mathematica
8. Drawing and visual anlaysis of the graph of the one variable functions
9. Drawing and visual anlaysis of the graph of the one variable functions
10. Differential calculus on computer by using Mathematica
11. Differential calculus on computer by using Mathematica
12. Differential calculus of higher order on computer by using Mathematica
13. Differential calculus of higher order on computer by using Mathematica
14. Calculus of extreme points for one dimensional functions on computer by
using Mathematica
15. Calculus of extreme points for one dimensional functions on computer by
using Mathematica
Literature
M. Pašić (2004).
Matematičko modeliranje
pomoću Wolframove
matematike, Skriptarnica
F ER
F . E. Szabo (2002). Linear
Algebra. An Introduction
Using Mathematica,
Academic Press
K. R. Coombes, R. L.
Lipsman, J. M. Rosenberg
(1998). Multivariable
Calculus and Mathematica.
With Applications to
Geometry and Physics,
Springer
Similar Courses
» Matematičko modeliranje pomoću Wolframove Mathematice, Cambridge
256
Learning Outcomes
1.
2.
3.
4.
5.
6.
7.
List basic Matlab comands
Describe the method of the problem solvin using Matlab
Explain the description of dynamic systems in Matlab
Use Matlab for simulation of the dinamic systems
Analyze the obtained results
Illustrate the results using MATLAB graphics tools
Combine different Matalab and Simulink tools for determining the
behavior of dynamic systems
8. Assess the validity of the results
Grading
This course has no midterm
exam.
The students will get acquainted with MATLAB 7.X user interface, be able to work
with MATLAB variables, interactively process data, plot and visualizes results,
create and debug M-files and build graphical user interface.
Prerequisites
Mathematics 1
F orms of Teaching
Prerequisites for
Alarm Systems
» Lectures
» Lectures 8 hours
» Exams
» Laboratory exercises - test
F inal exam
» Laboratory Work
» Two hours opf exercises per week.
EEIT
C OM
Dr. sc. Tamara Hadjina
Dr. sc. Ivan Marković
Dr. sc. Matko Orsag
Dr. sc. Tamara Petrović
Igor Cvišić, dipl. ing.
Josip Ćesić, mag. ing.
Mladen Đalto, mag. ing.
Luka F ućek, mag. ing.
Nikola Hure, mag. ing.
Edin Kočo, mag. ing.
F ilip Mandić, mag. ing.
Anita Martinčević, mag. ing.
Branimir Novoselnik, mag.
ing.
Goran Vasiljević, dipl. ing.
C EA
8
12
EP E
Study Hours
Lecturers
EC E
L1
EL
Study Programmes
E-learning Level
WT
The purpose of this course is to provide the students with a working introduction
to the MATLAB technical computing environment and give the practical
knowledge about programming techniques in MATLAB. Themes of vector and
matrix data analysis, graphical visualization, data modeling, and MATLAB
programming are explored in the context of realistic examples.
L1
IP
Course Description
English Level
SEIS
Izv. prof. dr. sc.
Izv. prof. dr. sc.
Mato Baotić
Jadranko Matuško
2
CE
Prof. dr. sc.
Željko Ban
ECT S Credits
257
CS
Lecturers in Charge
E/C
104307
Laboratory and Skills – Matlab
TI
Grading System
T ype
Exam: Written
T hreshold
Percent of
Grade
0%
0%
33.33 %
66.67 %
Exam
T hreshold
Percent of
Grade
0%
33.33 %
0%
66.67 %
Comment:
This course has no midterm exam.
1. 1st Lecture
Overview of Matlab software. Basic operations in MATLAB. Application of
M functions. Graphic presentation of results in 2D and 3D space.
Application of the Symbolic Toolbox.
2. 2nd Lecture
Applying Simulink for simulation of the dynamical technical systems.
3. Preparing for the first Laboratory exercise (LV1)
Basic operation of the program Matlab.
4. Work on the first Laboratory exercise (LV1)
Basic operation of the program Matlab.
5. F inalizations of the first Laboratory exercise (LV1) and analyze of the
results.
6. Preparing for the second Laboratory exercise (LV2)
Design of the M scripts and M functions.
7. Work on the second Laboratory exercise (LV2).
Using M scripts and M functions.
8. F inalizations of the second Laboratory exercise (LV2) and analyze of the
results.
9. Preparing for the third Laboratory exercise (LV3).
Preparation for solving problems using symbolic expressions.
10. Work on the third Laboratory exercise (LV3).
Solving problems using Symbolic Toolbox.
11. F inalizations of the third Laboratory exercise (LV3) and analyze of the
results.
12. Preparing for the fourth Laboratory exercise (LV4).
Modelling of RLC circuit using Matlab / Simulink.
13. Work on the foruth Laboratory exercise (LV4).
Simulation of RLC circuit using Matlab / Simulink.
14. F inalizations of the fourthLaboratory exercise (LV4) and analyze of the
results.
15. F inal exam.
Literature
Ž. Ban, J. Matuško, I.
Petrović (2010). Primjena
programskog sustava Matlab
za rješavanje tehničkih
problema, Graphis, Zagreb
MATLAB 7.x Documentation
The Mathworks The
Mathworks 2005
258
Similar Courses
» Engineering Tools II: Intro to Matlab, ETH Zurich
259
30
30
LabVIEW is graphical programming for measurement, automation and
visualization. It is a development tool available for applications in test and
measurement, data acquisition (DAQ), analysis, instrument and process control.
This course will teach students advanced technics of Labview programming.
Learning Outcomes
Grading
Prerequisites
Engineering
Engineering
IP
To use software enviroment LabVIEW
To appraise the program code to smaller units
To produce smaller functional programs
To modify current examples to his demands
To merge smaller program parts to usefull programs
To choose needed functions for the realization of task
EEIT
Study Hours
Lecturers
C OM
L1
C EA
E-learning Level
EP E
L2
EC E
English Level
Doc. dr. sc.
Juraj Havelka
Course Description
1.
2.
3.
4.
5.
6.
2
EL
Prof. dr. sc.
Roman Malarić
ECT S Credits
WT
Lecturers in Charge
E/C
69393
LabVIEW
SEIS
CE
The basic knowledge of Labview programming, data acquisition from connected
instruments to computers. SCADA programmming. Communication with
programmible logic controllers using various protocols.
CS
F orms of Teaching
» Lectures
TI
» Lectures with presentations
» Experiments
» During presentations
Grading System
T ype
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
30 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
100 %
260
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Virtual instrumentation and LV
The LabVIEW Environment
LabVIEW F oundations
Structures
Arrays and Clusters
Charts and Graphs
Strings and F ile I/O
Signal Measurement and Generation
Data Acquisition
Advanced LabVIEW F eatures
Examples
Examples
Examples
Examples
Test
Literature
R. Bitter, T. Mohiuddin, M.
Nawrocki (2006). LabView:
Advanced Programming
Techniques, CRC Press
C. Clark (2005). LabVIEW
McGraw Hill
M. L. Chungani,A. R.
Samant,M. Cerna (1998).
LabVIEW Signal Processing,
PTR PH
J. Essick (1989). Advanced
LabVIEW Labs, PTR PH
L. Sokoloff (2004).
Applications in LabVIEW,
Pearson PH
Similar Courses
» LabVIEW course, Chalmers University
» Engineering Tool IV: Programming with LabView, ETH Zurich
» ME220 Lab #1 Introduction to LabView Environment and Signals in the,
Stanford
261
Course Description
Definition of a local area network. Protocol architecture and LAN topologies.
Multiple medium access in local area networks. Multiple access control. Standards
of physical layer in local area networks. Networking devices in LAN. LAN
internetworking. Virtual LANs. Security in local area networks. Local area
network management. LAN performance. Internetworking between LANs and
public networks.
English Level
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
T eaching Assistant
Matija Šulc, mag. ing.
40
65
75
85
Prerequisites
EL
Study Programmes
IP
WT
3rd year)
3rd year)
SEIS
Learning Outcomes
CS
CE
Define the basic concepts of LANs
Estimate the important parameters of local area networks (LANs)
Solve the problem in LANs
Analyze the problem
Categorize existing ideas and give a new solution
Compare of quality of solutions
TI
1.
2.
3.
4.
5.
6.
Theoretical knowledge about protocol architecture of local area networks (LANs),
especially Ethernet LANs. Practical knowledge about LAN standardization and
about LAN switches. Practical skills for designing and administering of local area
networks, and for data traffic measurements in LANs.
EEIT
4
C EA
Doc. dr. sc.
Željko Ilić
ECT S Credits
EP E
Lecturer in Charge
E/C
34332
Local Area Networks
EC E
262
F orms of Teaching
» Lectures
» Teaching is organized through two teaching cycles. The first cycle
includes seven weeks of classes and ends with a mid-term exams,
while the second cycle includes six weeks of classes and ends with a
final examination.
» Laboratory Work
» Laboratory work is carried out through three cycles, which include
three parts (Linux, Packet Tracer software and network monitoring
(SNMP)). Laboratory ends with laboratory exam.
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
25 %
25 %
25 %
25 %
Exam
T hreshold
Percent of
Grade
0%
0%
25 %
50 %
50 %
25 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Course information; Introduction to LANs
Introduction to LANs (cont.); Ethernet basics
Ethernet basics (cont.)
Ethernet networks: 100-BASE, G-BASE, 10GbE
LANs: networking
Switched LANs
Switched LANs (cont.); Virtual LANs: Applications and Concepts
Exam
Wireless LANs
Wireless LANs (cont.)
Network management (SNMP)
Network performance: LANs
Transmission media
Structural cabling
Exam
Literature
Rich Seifert; Jim Edwards
(2008). The All-New Switch
Book, Wiley
Gilbert Held (2003). Ethernet
Networks, John Wiley &
Sons
Charles E. Spurgeon (2000).
Ethernet: The Definitive
Guide, O Reilly
263
Similar Courses
» Projects in Computer Networks, Stanford
» Local and Wide Area Networks [core], IEEE & ACM Computing Curricula
» Breitbandnetze, TU Munchen
264
General rules of electrical installation design. Connection to the MV utility
distribution network. Connection to the LV utility distribution network. MV &
LV architecture selection guide. LV Distribution. Protection against electric
shocks. Sizing and protection of conductors. LV switchgear: functions & selection.
Protection against voltage surges in LV. Energy Efficiency in electrical
distribution. Power factor correction and harmonic filtering. Harmonic
management. Characteristics of particular sources and loads. Residential and other
special locations. Using tools for designing LV networks.
English Level
L1
E-learning Level
L1
Study Hours
Lecturers
30
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
90
Prerequisites
EP E
Course Description
4
EC E
Prof. dr. sc.
Slavko Krajcar
ECT S Credits
EL
Lecturer in Charge
E/C
35245
EEIT
C OM
C EA
WT
Study Programmes
IP
Learning Outcomes
SEIS
TI
CS
CE
1. Identify basic components of medium and low voltage installations
2. Employ software solutions for modelling LV networks and calculation of
protective device selectivity
3. Choose adequate equipment for specific implementations in LV network
4. Explain the role of individual components in LV distribution systems
5. Estimate usefulness of individual protective devices in LV networks
6. Synthesize theoretical knowledge of designing LV networks with software
tools
The objectives of the course are to give the students the knowledge about low
voltage power systems. Upon the completition of the course, students will be
qualified to do following: 1.planning and design of low voltage power systems; 2.
project management for low voltage power systems
F orms of Teaching
» Lectures
» Guest lecturers at the beginning of each learning cycles (3 in one
semester)
» Exams
265
» Performed on-line, using the Moodle system, in a controlled
computer lab.
» Consultations
» Via on-line forums, e-mail and other electronic media, and also in
person with lecturers.
» Structural Exercises
» Work in DOC2 software, independent creation of LV installation.
» E-learning
» Use of e-learning and e-transfer of knowledge throughout the
course, Moodle platform.
Grading System
T ype
Quizzes
Class participation
Seminar/Project
Exam: Written
T hreshold
Percent of
Grade
50 %
0%
50 %
40 %
60 %
20 %
5%
15 %
40 %
20 %
Exam
T hreshold
Percent of
Grade
50 %
0%
50 %
0%
20 %
5%
15 %
50 %
60 %
1. General rules of electrical installation design.
2. Connection to the MV utility distribution network. Connection to the LV
utility distribution network.
3. MV & LV architecture selection guide.
4. LV Distribution.
5. Protection against electric shocks.
6. Knowledge exam 1
7. Sizing and protection of conductors.
LV switchgear: functions & selection.
8. Protection against voltage surges in LV.
9. Power factor correction and harmonic filtering.
10. Using tools for designing LV networks.
11. Characteristics of particular sources and loads.
12. Residential and other special locations.
13. Harmonic management.
14. F inishing the project task
15. F inal knowledge exam
Literature
Vjekoslav Srb (1989).
Električne instalacije i
niskonaponske mreže,
Tehnička knjiga
Merlin Gerin, Schneider
Electric (2007). Electrical
installation guide According
to IEC International
Standards, (on-line)
266
Similar Courses
» Application of electrical components and installations, Royal Instutute of
» Designs of electrical equipment and installations, ETH Zurich
267
Doc. dr. sc.
Hrvoje Pandžić
Course Description
Within the scope of this subject students have to gain knowledge on business,
legal, and project engineering environment. Main topics: engineering profession,
engineering ethics, intellectual property, engineering approach to problem
solving, teamwork, projects and project management, project planning, risks in
projects, management and managers, organizing, and leadership.
Study Programmes
L1
Study Hours
Lecturers
30
C EA
Prerequisites for
Economics and Managerial
Decision Making
Project
Project
Project
Project
Project
EP E
50
62
74
86
EC E
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
Lecturers
Prof. dr. sc. Stjepan Car
Prof. dr. sc. Darko Huljenić
Izv. prof. dr. sc. Dubravko
Sabolić
Dr. sc. Žarko Janić
EEIT
E-learning Level
EL
Doc. dr. sc.
Bojan Trkulja
L0
WT
Izv. prof. dr. sc.
Željka Car
English Level
IP
Prof. dr. sc.
Vedran Bilas
3
SEIS
Prof. dr. sc.
Željko Štih
ECT S Credits
CE
Lecturers in Charge
E/C
21012
CS
Learning Outcomes
Identify complex environment of engineering
Explain ethic aspects of engineering
Explain fundamental characteristics of intellectual property
Apply fundamental principles of teamwork
Prepare project plan
Explain managerial functions
Identify organizational forms
Explain importance of leadership
TI
1.
2.
3.
4.
5.
6.
7.
8.
Understanding of ethical, business, legal, and project framework of engineering.
268
F orms of Teaching
» Lectures
» Teaching is organized in two cycles. The first cycle includes of 7
weeks of teaching and mid-term exam, and the second cycle includes
of 6 weeks of teaching and final exam. Teaching is executed in 15
weeks with two hours of teaching per week.
» Exams
» Knowledge is tested by written exam.
» Consultations
» Consultations are held individually.
» Seminars
» Seminar work is a plan for a small project.
Grading System
T ype
Class participation
Seminar/Project
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
10 %
30 %
30 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
10 %
30 %
0%
60 %
1. Engineering as a profession, history of engineering, greatest engineering
achievements in twentieth century, modern engineering, engineering skills,
engineering jobs.
2. Engineering ethics, profession, etiquette, law and moral, ethics and ethic
codes, moral dilemmas, individual responsibility, case studies.
3. Intellectual property, types of intellectual property, authors' and similar
rights, industrial property, patents, trade marks, industrial design,
geographical indications, topography of semiconductor chips, intellectual
property in digital era.
4. Engineering problem solving, good and bad approaches to problem
solving, understanding of a problem, categories of problems, problem
solving cycle.
5. Teamwork, definition of a team, roles and responsibilities, importance of a
team, problems in teamwork, team building, resolving of conflicts.
6. Projects and project management, definition of a project, project
management functions, phases and processes in a project.
7. Project planning - methodology, determination of a scope, identification of
activities, scheduling, Gantt chart, resources and budget.
8. mid-term exams
9. mid-term exams
10. Project planning - tools, MS Project, examples.
11. Project risk management, risk identification, qualitative risk analysis,
quantitative risk analysis, plan of risk avoidance, tracking and control of
risks.
12. Management and managers, organization, managers, management,
managerial functions, managerial roles, managerial skills, engineering and
management.
269
13. History of management, scientific management, general administrative
management, psychological movement in management, quantitative
approach to management, system theory and management, situational
approach to management, quality management, modern trends.
14. Organization, job specialization, organizational structures, relationships in
organizations, centralization and decentralization, business functions of a
company, organization of engineering departments.
15. Leadership, short survey of research on leadership, transformationaltransactional leadership, charismatic leadership, team leading.
Literature
B.S. Dhillon (2002).
Engineering and Technology
Management Tools and
Applications, Artech House
S.P. Robbins, M. Coulter
(2007). Management – ninth
edition, Prentice Hall
Project Management
Institute (2004). A Guide to
the Project Management Body
of Knowledge (PMBOK®
Guide), Project Management
Institute
Similar Courses
» Management in Engineering, MIT
» Grundlagen des Managements für Ingenieure, TU Munchen
270
E-learning Level
L1
Study Hours
Lecturers
30
15
45
60
75
85
Prerequisites
Mathematics 2
SEIS
Study Programmes
CS
CE
TI
Learning Outcomes
1.
2.
3.
4.
Recognize problems which can be modeled on computer
Define a problem and write a computer algorithm for its solving
Describe possible input and output parameters and possible solutions
Write a solution of a problem appearing in classic mathematics or
profession
5. Analyze written algorithms in the sense of real problem and computer
view
6. Create mathematical model for given problem and write a computer
progrem for solving it
C EA
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
T eaching Assistant
EEIT
L2
EP E
Basic and advanced programming in Mathematica. Experiment, analysis and
visualization on computer of mathematical notions and topics, like: matrix
operations, linear systems and transformations, differential and integral calculus,
multivariable calculus, vector analysis, differential equations, Laplace and F ouirer
transformations, z - transformation, introduction in complex analysis, fractals,
mathematical statistics, elements of numerical analysis, discrete mathematics.
Mathematical modeling on the computer of some problems appearing in
applications, like: signal processing and image compression, neural network, data
base, cryptography, simulation of games, optimization and physics, electrical
circuit and some problems from electrotechnique. Basic ctructure of mathematical
modeling must contain: definition and physical version of the experiment (if it is
possible to do), measurement of experimental results, definition of suitable chosen
mathematical model, calculation on computer the results obtained from the
mathematical model - the so-called theoretical results, comparison between
experimental and theoretical results, and based on the preceding, deducing a
conclusion on the suitability of chosen mathematical model.
English Level
EC E
Course Description
4
EL
Prof. dr. sc.
Mervan Pašić
ECT S Credits
WT
Lecturer in Charge
E/C
91612
Mathematical Modeling of Computer
IP
271
Basic and advanced programing in Mathematica. The mathematical modeling on
computer by using Mathematica of the seceral topics: from the classical
mathematics (linear algebra, mathematical analysis, differential equations,
probability and statistics etc.), from the vocational courses during the study of
electrotechics, tele and radio communication, computer engineering, etc.
Definition of experiment and choosing of suitable mathematical model, getting
the experimental results, calculation of theoretical results on computer obtained
from the mathematical model, comparison between experimental and theoretical
results, conclusion about the suitability o chosen mathematical model.
F orms of Teaching
» Lectures
» Themas of lectures are focused to mathematical modeling on
computer of notions and problems, which are classified into the
next four different groups: the classic mathematics appearing on the
first year of the study (lnear algebra, mathematical analysis 1 and 2,
satistics etc.), profession (physics, electrotehnique, computer
engineering, radio and telecomunitation etc), education (practical
life problems) and computer games.
» Laboratory Work
» Laboratory exercises are concentrated on manipulation with basci
commands of Mathematica on computer, which are applied to basic
problems from: matrix and vector algebra, one dimensional calculus
(differentiation and integration), more variable calculus, functions of
complex variable, combinatorics, statistics, etc.
» Experiments
» Definition of some experiments: electrical circuit, image
compression, static and fluid dynamics, etc.
» Seminars
» Seminar is an independent work in which a student defines a
problem in collaboration with professor, and then he try to give the
solution of that problem: write algorithm, check it on computer,
analyze obtained results, etc. At the end, student presents his
seminar on computer in a public presentation.
» Defining, realization and measurement in experiment; defining and
computer calculation of mathematical model; comparison and
analysis of experimental and theoretical results.
Grading System
T ype
Class participation
Seminar/Project
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
10 %
30 %
30 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
30 %
0%
70 %
1. Basic commands which are available in Mathematica or other software for
simbolic calculus on computer.
272
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Analysis and examples for good and poor program made on computer.
Basic examples from the topics appearing in the classical mathematics.
Basic examples from the topics appearing in the computer engineering.
Basic examples from the topics appearing in the electrical engineering.
Detailed examples for mathematical modeling of topics from matric and
vectors calculus, one variable differential and integral calculus, more
variable calculus, statistics etc.
Detailed examples for mathematical modeling of several topics from
physics, electrotechnique, computing, tele and radio communications and
other topics appearing during the study.
Detailed examples for mathematical modeling of several topics with the
educational purposes.
Detailed examples for mathematical modeling of several topics appearing
in the computer games.
Presentation, analysis and estimate of student seminars on the
mathematical modeling on computer, with some of basic researching
elements.
elements.
elements.
elements.
elements.
elements.
Literature
M. Pašić (2000).
Matematičko modeliranje
pomoću Wolframove
Mathematice, Skriptarnica
F ER
F . E. Szabo (2002). Linear
Algebra. An Introduction
Using Mathematica,
Academic Press
K. R. Coombes, R. L.
Lipsman, J. M. Rosenberg
(1998). Multivariable
Calculus and Mathematica.
With Applications to
Geometry and Physics,
Springer
M. L. Abell, J. P. Braselton
(1993). Differential Equations
with Mathematica, Academic
Press
Similar Courses
» Computer Laboratory II, Cambridge
273
Real numbers and functions of one real variable. Limits of sequences. Limit of a
real function of real variable. Derivative of a function and applications. Integrals
and applications. Matrices, determinants and solving linear systems.
Study Programmes
Learning Outcomes
1. Describe and apply basic concepts of course
2. Describe, connect and interpret basic notions, results and methods from
course
3. Demonstrate fundamental skills from course such as differentiation,
integration, calculation of limits, solving systems and others
4. Apply basic methods and skills into practice
5. Analyze problems and making conclusions by using mathematical reasoning
6. Demonstrate skills of mathematical modelling and problem solving
7. Demonstrate an ability for mathematical expression
Lecturers
Prof. dr. sc. Ljubo Marangunić
Prof. dr. sc. Mervan Pašić
Dr. sc. Mario Bukal
Dr. sc. Marijana Greblički
Dr. sc. Maja Resman
Dr. sc. Domagoj Vlah
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
Attendance of lectures is
mandatory.
45
55
70
85
Prerequisites for
Electroacoustics
Mathematics 2
Physics 1
Acceptance of elementary concepts and methods in linear algebra. Mastering the
basic knowledge and techniques of the differential and integral calculus of
functions of one variable and applications.
EEIT
EL
EC E
Dr. sc. Tomislav Berić
Dr. sc. Dario Bojanjac
Dr. sc. Snježana Lubura
Dr. sc. Ana Prlić
Petar Bakić, mag. math.
Stjepan Šebek, mag. math.
C OM
90
15
C EA
Study Hours
Lecturers
Exercises
EP E
L2
WT
Course Description
E-learning Level
IP
Doc. dr. sc.
Ana Žgaljić Keko
L0
SEIS
Doc. dr. sc.
Igor Velčić
English Level
CE
Doc. dr. sc.
Lana Horvat
Dmitrović
Izv. prof. dr. sc.
Izv. prof. dr. sc.
Ilko Brnetić
Josipa Pina Milišić
7
CS
Prof. dr. sc.
Darko Žubrinić
ECT S Credits
TI
Lecturers in Charge
E/C
86475
Mathematics 1
274
F orms of Teaching
» Lectures
» Lectures are held in two cycles, 6 hours per week
» Exams
» Midterm and final exam
» Exercises
» Excercises are held one hour per week
» Consultations
» each lecturer one hour per week
Grading System
T ype
Quizzes
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
20 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
20 %
0%
80 %
Comment:
The scores achieved on short tests will be transferred to the score of the exam only
in the case when it is in the interest of the student.
1. Mathematical logic. Sets. F unctions. The set of natural numbers, integers,
and rational numbers. Mathematical induction. Real numbers. Complex
numbers.
2. Real functions of one real variable. Review of elementary functions.
3. Sequences. Accumulation points. Limit of a sequence.
4. Limit of a real function of one real variable. Continuity of functions. Basic
theorems about continuous functions.
5. Derivative of a function. Differentiation rules. Differentiation of implicit
and parametric functions.
6. Differential of a function. Basic theorems of Differential Calculus. Lagrange
mean value theorem. Taylor's theorem. L'Hospital's rule.
7. F inding extrema of a function. Convexity and concavity of a function.
Sketching curves and qualitative graph of a function.
8. Midterm exam.
9. The indefinite and the definite integral. Methods of the integration (the
substitution method and the integration by parts).
10. Integration of rational functions. Integration of some irrational and
trigonometric functions.
11. The improper integral. F inding the area of planar sets. Computation of the
length of curves. F inding the volume of the revolution. F inding surface of
the revolution.
12. Matrices. Summation and the scalar multiplication. Multiplication of
matrices. Properties of matrix multiplication. Determinants and their
properties.
13. Inverse of a matrix. Rank of a matrix.
14. Solving linear systems of equations using the Gauss method. F inding
eigenvalues and eigenvectors of quadratic matrices.
275
15. F inal exam.
Literature
N. Elezović (1999). Linearna
algebra, Element
P. Javor (1999). Matematička
analiza 1, Element
M. Pašić (2004).
Matematička analiza 1,
Merkur ABD
M. Pašić (2004).
Matematička analiza 2,
Merkur ABD
Similar Courses
» Mathematik 1 für ET, TU Wien
» Höhere Mathematik 1, TU Munchen
» Calculus in one variable, Royal Instutute of Technology Stockholm
276
Course Description
Vectors. Analytic geometry in space. Differential calculus of several variables.
Series. Power series. Taylor series. Ordinary differential equations.
Study Programmes
Learning Outcomes
1. Understand the notion of convergence of series of numbers and apply the
basic criteria for convergence of series of numbers.
2. Determine the area of convergence of power series.
3. Develop the function in a Taylor power series.
4. Apply tecniques and procedures on problems related to lines and planes in
the space.
5. Understand basic techniques in calculus of several variables.
6. Apply calculus of several variables on finding local and global extremas of
differentiable functions of several variables.
7. Relate techiques of Mathematics 2 and Mathematics 1 and use them to solve
basic types of ordinary differential equations
8. Create a mathematical model, based on the differential equation, related to
electircal engineering
Lecturers
Prof. dr. sc. Ljubo Marangunić
Dr. sc. Goran Radunović
EC E
EP E
Dr. sc. Tomislav Berić
Dr. sc. Dario Bojanjac
Dr. sc. Ana Prlić
Mario Stipčić, mag. math.
EEIT
90
15
C OM
Study Hours
Lecturers
Exercises
C EA
L2
EL
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
mandatory.
45
55
70
85
WT
Doc. dr. sc.
Ana Žgaljić Keko
E-learning Level
IP
Doc. dr. sc.
Domagoj
Kovačević
L0
Prerequisites
Mathematics 1
SEIS
Izv. prof. dr. sc.
Tomislav Šikić
English Level
Prerequisites for
Computing Methods of
Modern Physics
Electrical Circuits
Electronics 1
F undamentals of Intelligent
Control Systems
Graphics
Mathematical Modeling of
Computer
Mathematics 3 - C
Mathematics 3 - EE
Robotics Practicum
277
CE
Doc. dr. sc.
Lana Horvat
Dmitrović
Prof. dr. sc.
Mervan Pašić
7
CS
Prof. dr. sc.
Darko Žubrinić
ECT S Credits
TI
Lecturers in Charge
E/C
86476
Mathematics 2
Student is supposed to achieve a good level of understanding of theoretic concepts
and principles in the topics of series, power series, Taylor series, analytic
geometry in space and differential calculus of several real variables. Student will
be able to select and apply corresponding methods and techniques o f calculations
from topics mentioned above. Student will synthesize all above competences and
use it in the solving of ordinary differential equations(ODE's). Student will be able
to design the differential equation, as a mathematical model, related to simple
examples of the engineering practice.
F orms of Teaching
» Lectures
» Lectures which contain a large number of examples and problems
» Exams
» Mid-term and final exam during the lecture-free weeks.
» Exercises
» More examples for students which need more practice.
» Individually, implement by best students from higher years of study.
» Consultations
» At least once a week.
Grading System
T ype
Quizzes
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
20 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
20 %
0%
80 %
Comment:
1. VECTORS.
Operations with vectors and linear combination of vectors.
Coordinate system and canonical basis.
Scalar product of two vectors and the angle between them.
Vector product, scalar triple product and vector triple product of vectors.
Liner independence of vectors and basis decomposition of vectors.
2. LINE AND THE PLANE.
Plane in space and equation of the plane.
Line in space and equation of the line.
Mutual relationship between the line and the plane.
3. F UNCTION OF SEVERAL VARIABLES (AN INTRODUCTION)
Euclidean space R^n.
The notion of the graph of the function in several variables.
An overview of some surfaces in Euclidean space.
The equation of the curve in space.
Level curves and level surfaces.
278
4. CALCULUS OF SEVERAL VARIABLES. (1st PART)
Limit and continuity of functions in several variables.
Partial derivatives.
The notion of the gradient and differentiable function in several variables.
Higher order derivatives and Schwartz theorem.
Approximations of functions using the first differential.
5. CALCULUS OF SEVERAL VARIABLES (2nd PART)
Derivatives of composite functions and chain rule.
Derivatives of vector functions and tangent line on the space curve.
Tangent plane.
Integrals depending on the parameter.
6. APPLIED CALCULUS OF SEVERAL VARIABLES (1st PART)
Directional derivative
Mean value theorem
Derivation of implicit function
High-order differentials. 2nd Differential and quadratic forms
Taylor's formula for functions of two variables
7. APPLIED CALCULUS OF SEVERAL VARIABLES (2nd PART)
Extreme values of linear functions
Local extreme of function of several variables
Extreme of function subject to constraints. Lagrange multiplier
8. MIDTERM EXAM
9. SERIES
Definition of series and convergence of series.
Criteria for convergence of series.
Absolute and conditional convergence.
Product of series.
10. POWER SERIES AND TAYLOR SERIES
Power series, area of convergence and radius of convergence.
Taylor series of elementary functions.
Derivatives and integrals of power series.
Convergence of sequence of functions.
Series of functions.
11. F IRST-ORDER DIF F ERENTIAL EQUATION (1st PART)
The notion of differential equation.
The field of directions.
Equations with separated variables.
Homogeneous equations.
Ortogonal trajectories
Linear differential equations of the first order and applications.
12. F IRST-ORDER DIF F ERENTIAL EQUATION (2nd PART)
Exact differential equations.
Solving using parameters.
Existence and uniquness of the solution.
Singular solutions of differential equations of the first
order.
13. HIGH-ORDER DIF F ERENTIAL EQUATION
Solving the differential equation by decreasing the order.
Existence and uniquness of the solution.
Linear differential equation of the second order.
Linear differential equation of the second order with constant coefficients.
Applications of the linear differential equation.
14. LINEAR HIGH-ORDER DIF F ERENTIAL EQUATION
Vector subspaces and linear operators. Differential operators.
Higher order homogeneous differential equations.
F inding the particular solution.
Linear differential equation of higher order with constant coefficients.
Euler equation.
15. F INAL EXAMS
279
Literature
N. Elezović (1999). Linearna
algebra, Element
P. Javor (1999). Matematička
analiza 2, Element,
B. P. Demidovič (1998).
Zbirka zadataka iz
matematičke analize za
tehničke fakultete, Tehnička
knjiga
Serge Lang (1987). Calculus
of Several Variables, Third
Edition, Springer
M. Pašić (2004). Matematička analiza 2, Merkur ABD
Similar Courses
» Mathematics 2 for electrical engineering (101.135 ), TU Wien
» Calculus II, MIT
280
Computing (Study) (required course, 3rd semester, 2nd year)
Learning Outcomes
1. Solve the differential equation using the Laplace transform
2. Analyze problems in electrical engineering using differential equations and
the Laplace transform
3. Describe the nature of periodic functions
4. Illustrate the role of infinite sets and relations
5. Compare problems in combinatorics
6. Recognize problems related to recurrrence relations
7. Design the notion of the graph
8. Solve some typical problems in graph theory
60
15
C EA
45
55
70
85
EP E
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
mandatory.
C OM
Dr. sc. Mario Bukal
Dr. sc. Maja Resman
Ana Anušić, mag. math.
Mario Stipčić, mag. math.
EEIT
Study Hours
Lecturers
Exercises
EC E
Study Programmes
L1
EL
F ourier series and F ourier and Laplace transform are studied, as well as their
applications. We introduce notions and methods of combinatorics including an
introductory approach to difference equations. Descriptions of modelling of
problems of discrete mathematics using graphs are given.
E-learning Level
Prerequisites
Mathematics 2
WT
Course Description
L0
Prerequisites for
Introduction to Pattern
Recognition
Project
Signals and Systems
IP
Doc. dr. sc.
Domagoj
Kovačević
English Level
SEIS
Izv. prof. dr. sc.
Tomislav Šikić
5
CE
Prof. dr. sc.
Mario Osvin
Pavčević
ECT S Credits
CS
Lecturers in Charge
E/C
88206
Mathematics 3 – C
TI
Each student will learn the necessery techniques of integral transorms for solving
problems in electrical engineering. One gets capabale of modelling as well as the
theoretical and the computational solving of combinatorial problems.
F orms of Teaching
» Lectures
» Lectures contain a large number of examples and problems
» Exams
» Mid-term and final exam during the lecture-free weeks.
» Exercises
» F or students which need more practice.
» Individually.
281
» Individually.
» Consultations
» At least once a week.
Grading System
T ype
T hreshold
Percent of
Grade
0%
0%
0%
20 %
40 %
40 %
Quizzes
Exam: Written
Exam
T hreshold
Percent of
Grade
0%
0%
20 %
0%
80 %
Comment:
1. Periodic functions. Trigonometric F ourier series.
2. Properties of F ourier series.
3. Laplace transform. Examples of Laplace transforms.
Properties of Laplace transform.
4. Inverse transform. Convolution.
Solving of integral and differntial equations.
5. Applications. Dirac function.
Power series and step functions.
6. Sets.
7. Binary relations.
8. Midterm exams
9. Product rule.
Variations, permutations and combinations without repetition.
Variations, permutations and combinations with repetition.
10. Inclusion - exclusion principle.
Generating functions. Pigeonhole principle.
11. Recurrrence relations.
12. The notion of the graph.
13. Connectivity.
14. Optimization algorithms.
15. F inal exams.
Literature
Neven Elezović (2010).
Fourierov red i integral
Laplaceova transformacija,
Element
Darko Žubrinić (2007). Uvod
u diskretnu matematiku,
Element
Mario-Osvin Pavčević
(2007). Uvod u teoriju
grafova, Element
282
Similar Courses
» Differential Equations, Carnegie Mellon University
» Combinatorics, Carnegie Mellon University
» Graph theory, Carnegie Mellon University
283
Learning Outcomes
1. Define and explain the orthogonality of trigonometric system of functions
and calculate F ourier series of a periodic function.
2. Apply F ourier analisys in thoery of signal analisys.
3. Apply Laplace transformation to solution of integral and differential
equations and use Laplace tansformation in research of electrical circles.
4. Calculate double and triple integrals over different domains and solve
many problems in applications of double and triple integrals.
5. Recognize i describe different scalar and vector fields and use formal
calculus with nabla operator.
6. Calculate different line and surface integrals.
7. Apply divergence theorem and Stokes theorem in evalation of surfsace and
line integrals.
Study Hours
Lecturers
Exercises
60
15
Prerequisites
Mathematics 2
Prerequisites for
Introduction to Pattern
Recognition
Project
Signals and Systems
Learn as much of the concept of linear integral transformations to be able to apply
them for solving differential equations and electric circuits. Getting good
fundamental knowledge and techniques of vector analysis, including line and
surface integrals, enables one to solve problems from electromagnetism and
electrostatics.
C EA
EP E
45
55
70
85
EC E
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
mandatory.
C OM
Andrej Novak, mag. math.
EEIT
L1
EL
semester, 2nd year)
E-learning Level
WT
Study Programmes
L0
IP
F ourier analysis, Laplace and Z-transform are introduced together with their
applications. Basic concepts of vector analysis, line and surface integrals, together
with divergence theorem and Stokes formula are studied.
English Level
SEIS
Course Description
5
CE
Prof. dr. sc.
Vesna Županović
ECT S Credits
CS
Lecturer in Charge
E/C
86477
Mathematics 3 – EE
TI
284
F orms of Teaching
» Lectures
» Exams
week of classes.
» Exercises
» The brief assessments will be held during the auditory exercises (up
to 1 hour per week).
» Consultations
» Consultations are held one hour weekly.
Grading System
T ype
Quizzes
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
20 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
20 %
0%
80 %
Comment:
1. Periodic functions. Trigonometric F ourier series. Computing of series and
its applications.
F ourier integral. F ourier transform.
2. Definition of the original and the Laplace transform. Laplace transform of
elementar functions.
3. Properties of the Laplace transform. Basic theorems about the Laplace
transform. Convolution and transform of periodic functions.
4. Applications to linear differential equations and systems. Applications to
integral equations of convolution type. Applications to electric circuts.
Z-transform. Difference and summation of originals. Applications of Ztransform.
5. Double and triple integrals. Change of variables in double and triple
integrals.
Applications of double and triple integrals.
6. Scalar and vector fields. Hamiltonian operator and properties. Gradient,
divergence and curl.
Directional derivative of scalar and vector fields. Laplace operator.
7. Vector potential. Line integral of the first type.
8. Midterm exam.
9. Line integral of the second type. Greens formula.
10. Potential vector field. Basic theorem about line integrals. Potential
computing .
285
11. Implicit and parametric definition of surfaces Tangent plane. Normal
sections of surfaces. Surface integral of the first type.
12. Surface integral of the second type. Applications of surface integrals.
13. Divergence, gradient and curl theorem. F low of vector fields.
14. Circulation of vector fields. Stokes formula.
15. F inal exam.
Literature
Matematička analiza 2 P.
Javor Element 1999
Funkcije kompleksne
varijable. Laplaceova
transformacija I. Ivanšić Liber
1978
Neven Elezović (2010).
Fourierov red i integral.
Laplaceova transformacija,
Element
Ilko Brnetić, Vesna
Županović (2010). Višestruki
integrali, Element
Tomislav Burić, Luka
Korkut, Mario Krnić, Josipa
Pina Milišić, Mervan Pašić
(2010). Vektorska analiza,
Element
Similar Courses
» Mathematik 3 fur Elektrotechnik, TU Munchen
» Analysis III, Analysis IV, EPF L Lausanne
286
Accuracy of measurement, errors and the expression of uncertainties. Passive
elements of measurement circuits. Analog and digital measuring instruments. The
main properties, limitations, accuracy and applications. Measurements of voltage
and current. Voltmeters and ammeters. Compensators and calibrators, high
voltage dividers. Conventional and unconventional measuring transformers.
Thermal current comparator. Resistance measurement. I-U method, measurement
of insulation resistance and ground resistance. Measurement of capacity and
inductance. Measuring bridges, digital impedance and admittance instruments.
Oscilloscopes. Sampling of signals. Application of an oscilloscope. Measuring
probe. Power measurement. DC, AC single phase and three phase measurements.
Digital wattmeter. Semi-direct and indirect power measurement. Measurement of
reactive and apparent power. Measurement of energy. Watthour meters; tariff
setting, remote reading. Quality of electric energy. Measuring converters.
Characteristics, the normalized output values, application. Temperature
measurements. Resistive sensors, thermocouples. Measurement of pressure, flow,
strain and relative extension. Application of unbalanced bridges.
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
55
67
79
90
Prerequisites
Engineering
EEIT
L1
C OM
E-learning Level
C EA
L0
EP E
Course Description
English Level
EC E
Doc. dr. sc.
Luka F erković
4
EL
Izv. prof. dr. sc.
Ivan Leniček
ECT S Credits
WT
Lecturers in Charge
E/C
34334
Methods of Measurement
IP
SEIS
Protection from interference.
CE
Study Programmes
CS
Learning Outcomes
TI
1. Choose measuring instruments with respect to the measurement
requirements
2. Apply appropriate measurement procedure for a given measurand
3. Identify influential factors and make the correction of the results
4. Practice correctly measuring instruments
5. Classify systematic and random errors in the measurement procedure
6. Show measurement result and the corresponding measurement uncertainty
287
The course gives the basic knowledge about the principles of operation of
measuring instruments and various methods for measuring different electrical and
non-electrical quantities. The students will have theoretical basis and practical
skills to implement modern measuring instruments in many different methods,
and ability to analyse the obtained results of measurements.
F orms of Teaching
» Lectures
» Lectures are designed as 10 thematic units that are logically continue
each other. F ollowing the lectures, students are introduced to the
problem of measuring the spectrum of different quantities, in a
wide range of their values. The lectures dealt with the
computational examples.
» Exams
» Examination is conducted through mid-term exam and final exam.
» Laboratory Work
» Laboratory work provides 5 laboratory exercises that build on
material from lectures. During the exercise, students have the
opportunity to perform real measurements and apply the
knowledge acquired in lectures.
Grading System
T ype
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
30 %
20 %
50 %
Exam
T hreshold
Percent of
Grade
0%
0%
30 %
0%
50 %
20 %
1. Accuracy of measurement and theory of errors. Standard deviation and
statistical analysis of results. Measurement uncertainty, type A and type B.
The complex expression of uncertainty and uncertainty. Computational
examples.
2. Passive elements of measurement circuits. Real parameters and the
equivalent diagrams. Parasitic parameters and frequency dependent
parameters. Waveforms of AC quantities, definition and calculation of mean
and effective values. Computational examples.
3. Analog and digital measuring instruments. The principle of operation,
characteristics, limitations and accuracy. Application of analog and digital
multimeter. Computational examples.
4. Measurement of direct currents. Ammeters. Current clamp with a Hall
probe. DC current transformer.
5. Measurement of DC voltage. The compensation method and method of
frequency transposition. Measuring amplifiers. High voltage divider and
measuring probes. Electrostatic voltmeter.
6. Measurement of alternating current. Instruments with rectifiers.
Measurement via thermoconverters. Conventional and unconventional
current transformers.
288
7. Measurement of AC voltages. Voltmeters responsive to the effective value.
Conventional and capacitive voltage transformer. Inductive divider. Ball
spark gap and Chubb procedure.
8. Mid-term exam
9. Mid-term exam
10. Resistance measurement. UI method and comparison method. Ohmmeter
method. Constant current method. Method of charge loss. Measuring the
resistance of insulating materials. Measurement of ground resistance.
11. Measurement of inductance and capacitance. UI methods. Resonance
method. Measuring bridges: Maxwell and Wien bridge. Schering and Glynn
bridge. Digital RLC bridges.
12. Power measurement. DC, AC single phase and three phase metering.
Digital wattmeter. Semi-direct and indirect measurement of power.
Reactive and apparent power.
13. Measurement of energy. Watthour meters. Additional control functions:
charging, remote sensing. The quality of electrical energy.
14. Measuring transducers. Characteristics, the normalized output values,
application. Temperature measurements. Resistive sensors, thermocouples.
Measurement of pressure, flow, stress and relative displacement. The
application of unbalanced bridges.
15. Magnetic measurements
Literature
V. Bego (2003). Mjerenja u
elektrotehnici, Graphis
A. Morris (2001).
Measurement and
Instrumentation Principles,
Butterworth-Heinemann
V. Haasz, M. Sedláček
(1998). Electrical
Measurements. Instruments
and Methods, VČVUT, Praha
D. Vujević, B. F erković
(2001). Osnove
elektrotehničkih mjerenja, I. i
II. dio, Školska knjiga
Similar Courses
» Messtechnik, TU Wien
» Messtechniklabor, TU Wien
» Grundlagen der elektronischen Messtechnik, TU Berlin
» Messtechnik und Sensorik, TU Munchen
289
Study Programmes
Study Hours
Lecturers
Exercises
27
3
15
50
61
73
85
Prerequisites
Engineering
Learning Outcomes
TI
1.
2.
3.
4.
5.
6.
Identify different contributions to the uncertainty of measurement
Classify diferent types of measuring instruments
Apply measuring instruments on correct manner
Analyse methods of measurement of electric quantities
Develop computer-bysed measuring systems
Assess possible accuracy improvements
EC E
EP E
C EA
Kristina F erković, dipl. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
L1
C OM
E-learning Level
EL
F undamental terms of metrology. Measurand, influencing quantities and result of
measurement. Least squares theory. Assessment of the uncertainty of measurement
and expression of the results. International System of Units (SI). Metrology
infrastructure and traceability. Basic analog and digital measuring instruments.
Principles of work, characteristics and applications. Measurement of voltage,
current, resistance, power and energy. Measuring bridges. Grounding, shielding
and interference protection. Computer based measurements. Virtual and
distributed measuring systems. Communication protocols connecting computer
and instruments. Software for acquisition and analysis of results of measurement.
L1
WT
Course Description
English Level
IP
Prof. dr. sc.
Roman Malarić
4
SEIS
Prof. dr. sc.
Damir Ilić
ECT S Credits
CE
Lecturers in Charge
E/C
86536
Metrology Fundamentals
CS
290
The students will have a good understanding of the importance and application of
metrology and measurement in the electrical engineering. They will have a good
basic knowledge of metrology terminology, units, and the analysis of the
measurement results, as well as a of different types of measuring instruments and
measurement systems controlled by the computer, used in the methods of
measurement of electrical quantities.
F orms of Teaching
» Lectures
» Lectures with presentations
» Exercises
» Will be a part of the lectures.
» Laboratory Work
» Instead of lectures
» Experiments
» Whenever it is possible.
Grading System
T ype
Homeworks
Quizzes
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
15 %
10 %
10 %
25 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
0%
0%
0%
35 %
50 %
1. F undamental terms of metrology. Measurand, influencing quantities and
result of measurement.
2. International System of Units (SI). Metrology infrastructure and
traceability. Calibration of instruments.
3. Least squares theory. Assessment of the uncertainty of measurement and
expression of the results.
4. Elements of measuring circuits. Laboratory measuring and regulation
equipment.
5. Basic analog measuring instruments. Principles of work, characteristics and
applications.
6. Basic digital measuring instruments. Principles of work, characteristics and
applications.
7. Measurement of dc and ac voltage and current. Measurement of resistance.
8. Mid-term exam.
9. Measurement of power and energy.
10. Balanced and unbalanced measuring bridges.
11. Grounding, shielding and interference protection.
12. Computer based measurements. Virtual and distributed measuring systems.
13. Communication protocols connecting computer and instruments.
14. Software for acquisition and analysis of results of measurement.
291
15. F inal exam.
Literature
J. Bucher (2004). The
Metrology Handbook, ASQ
V. Bego (2003). Mjerenja u
elektrotehnici, Graphis,
Zagreb
*** (2008). International
vocabulary of metrology
(VIM), JCGM
*** (2008). Guide to the
expression of uncertainty in
measurement (GUM), JCGM
V. Haasz, M. Sedlaček
(2006). Electrical
Measurements, ČVUT, Praha
Measurement Systems and
Sensors W. Nawrocki Artech
House 2005
Similar Courses
» Measurement Science, University of Twente
» Grundlagen der elektronischen Messtechnik, TU Berlin
292
Course Description
The observation of radiocommunication phenomena, especially in mobile systems,
analysis of events in radio channel during propagation in ideal and real conditions.
Understanding of more representative mobile systems with survey through
mobile generations.
Study Programmes
L1
E-learning Level
L1
Study Hours
Lecturers
45
15
T eaching Assistant
Leonard Novosel, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
English Level
C OM
Izv. prof. dr. sc.
Gordan Šišul
4
50
65
80
90
Prerequisites
C EA
Prof. dr. sc.
Robert Nađ
ECT S Credits
EP E
Lecturers in Charge
E/C
34312
EC E
SEIS
IP
WT
EL
year)
year)
CE
Learning Outcomes
TI
CS
1. 1. Introduction with the basic terms of mobile communications along with
the special emphasis on wireless interface. Student is gaining knowledge of
all phenomenons that are affecting on the quality of the transmission of
information with the radio channel.
2. 2. Student can apply the knowledge from the theory of electromagnetic
waves on understanding of the phenomenons inside of the radio channel
and connect them with the technical solutions of certain mobile systems
towards quality assurance for all levels of services.
3. 3. Knowledge of mobile communications basics prior has application in
further process of learning and solving particular examples.
4. 4. Students can, based on the knowledge of channel response in time or
frequency domain, analyse behaviour of the system for certain type of
information which is transferred through the channel. It means that based
on impulse response you can conclude whether it is about narrowband or
broadband channel.
5. 5. Because it is a elementary course, which gives an overview of the
phenomenons, it isn't estimated that the students can be able to suggest
some plan for solving the particular problems.
293
6. 6.With the acquirement from the course student can reach cognition about
solvability or unsolvability of particular problems in mobile
communications.
Good understanding of communication systems with deeper insight of particular
phenomena from the electromagnetic waves propagation theory, processing of
stochastic signals, evaluation of modulation methods and signal detection.
Theoretical basic comprehension of physical system phenomena, not reducing the
system knowledge only on general block view.
F orms of Teaching
» Lectures
» Lectures are held with the help of a power-point presentation with
explanations on the blackboard. Lectures are available in electronic
format on the course website.
» Exams
» The assessment is carried out through two written exams (one midterm and final exam) and final oral examination.
» Exercises
» Numerical examples are an integral part of the course.
» During the course are provided three demonstration exercises. At the
end of each exercise, test activities carried out, checking
understanding of the material presented.
» Consultations
» Permanent consultation entire whole semester.
» Other
» During the semester, one homewor is provided with concrete
numerical problems from the course.
» During the semester several projects are planned from the course
topics. Intention is to solve complex tasks, often with the use of
computers and software simulations. Each project would be dealt
with smaller groups of students.
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
6%
8%
26 %
40 %
20 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
60 %
40 %
Comment:
Oral exam has 4 main parts (one question from every part). It is necessary to
collect 40% from every part for passing exam.
294
1. Signals in radiocommunications, deterministic and random. Signals in time
and frequency domain, signal spectrum, noise. Survey of characterististics
mobile systems first, second and third generation.
2. Radio channel, channel characteristics. Antennas for base and mobile
stations.
3. Signal propagation loss, radio wave reflection, two ray model. Wave
difraction, F resnel zone. Propagation loss models survey.
4. F ading, small and large scale fading statistics. Multipath in mobile systems,
mobile station movement, Doppler shift. Radio-channel multipath effects,
inter-symbol interference.
5. Multiple access in mobile systems, F DD and TDD communication mode.
Cell structure, cell clusters and frequency reuse principle. Handover,
handover types, umbrella cell.
6. Cochannel interference, adjacent channel interference, cell sectorization.
System capacity, cell splitting, channel allocation methods. Reducing signal
fading influence, diversity.
7. Reducing signal fading influence, diversity. TDMA access characteristics,
digital signal equalization. Specific modulations in mobile systems.
8. Specific modulations in mobile systems. Mobile systems second generation,
beginnings and common characteristics of GSM system.
9. Architecture of GSM system, characteristics of physical layer, burst groups
in GSM.
10. Speech coding, source information coding, interleaving, logical channels.
Down- and uplink simulation in GSM system.
11. Migration toward third generation of mobile systems, GPRS and EDGE.
Picocellular systems, WLL and DECT.
12. Private trunked systems, TETRA. Indoor nomadic communications survey.
13. Megacells, mobile satellite systems, characteristics, significant mobile
satellite systems.
14. Spread spectrum systems fundamentals, CDMA access. 1
Third generation mobile system main characteristics, capacity, soft
handover.
15. Efficiency of second and third generation comparison, beginning of fourth
mobile generation. Introduction to mobile system planing, planing tools,
examples.
Literature
Zentner E. (2001). Antene i
radiosustavi, Graphis
P. Mohana Shankar (2002).
Introduction to Wireless
Systems, John Wiley & Sons
Theodore S. Rappaport
(2001). Wireless
Communicatios, Principles
and Practice, Prentice Hall
Andreas F . Molisch (2011).
Wireless Communications,
Sec.ed., John Wiley & Sons
Ltd.
Similar Courses
» S-72.231 Mobile Communications Systems, Cambridge
» EE359 - Wireless Communications, Stanford
» EE290I Wireless Communications, University of California Berkeley
» 389.063 VU Mobile Communications, TU Wien
295
E-learning Level
L1
Study Hours
Lecturers
45
C OM
C EA
50
60
75
85
EP E
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
F inal mark related to the
Point-regime system.
EEIT
L1
Prerequisites
Physics 2
EC E
Conceptual bridges from classical physics to quantum physics, particle-wave
dualism, basic notions and experiments. Derive of Schroedinger equation. Tunnel
effect, electron in a potential well, WBK method. Uncertainty principle and its
application in methods. Spectroscopic methods of analysis of materials based on
the characteristic X-rays and gamma-photons. Detectors of radiation, applications
and resolutions. Computed tomography and PET technique. Basic quantummechanical description of the properties of conductors and semiconductors.
Effective masses of electrons and holes. Hall effect and quantum Hall effect,
plateaus and Klitzing constant. Modern quantum technology methods: ESR,
NMR, spin waves. Low temperature superconductivity, basic pictures of the BCS
theory, quantization of magnetic flux, Josephson junction and magnetometer.
Methods of synchrotron light beams and nanotechnologies. Elements and circuits
on micro and nanoscale in the electrical engineering and IT. Elementary particles
and their roles in modern cosmology and epistemology.
English Level
EL
Course Description
4
WT
Prof. dr. sc.
Tomislav Petković
ECT S Credits
IP
Lecturer in Charge
E/C
34340
Modern Methods of Physics for Electrical
Engineering and Information Technology
SEIS
Study Programmes
CS
CE
Learning Outcomes
TI
1.
2.
3.
4.
5.
Explain events and concepts of quantum systems.
Apply quantum mechanics to elementary processes and radiation detectors.
Analyze quantum conductivity of metals, semiconductors, and apparatus.
Combine classical and quantum Hall efect in the contemporary metrology.
Derive formulae of apparatus operating based on magnetic electron and
nuclear resonances.
6. Reconstruct basic pictures of the BCS-superconductivity and HTSmaterials.
7. Analyze synchrotron light for application in nanotechnology.
8. Illustrate role and consequences of particle physics for modern cosmology
and epistemology.
296
Students will be educated for appliactions of science in electrcal engineering and
information technology, based on a good understanding of basic results, quantum
methods and techniques of modern physics. Based on the knowledge obtained by
the Physics 1 and Physics 2, students will be thought for practical skills important
for implementation, maintenance, and/or simple design of technological
components, modules, and devices.
F orms of Teaching
» Lectures
» Lectures with AV support originated by the laboratories. Simple
experiments and demonstrations.
» Exercises
» Examples and problem solutions.
» Experiments
» Simple experiments by using detectors with digital oscilloscope and
pulse height analyser.
» Consultations
» Regular - weekly consultations.
» Seminars
» Individual and/or group presentations of special topics.
» Work on computer (simulation, data handling, searching on articles
and solutions in quantum physics).
Grading System
T ype
Homeworks
Class participation
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
10 %
10 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
10 %
10 %
0%
40 %
40 %
Comment:
Two (equally valid) exams during the course: midexam and final.
1. Basic concepts and pictures of quantum physics. Derive of Schroedinger
equation.
2. Tunnel effect. Electron in a potential well. WBK method.
3. Uncertainty principle. Applications in methods.
4. Spectroscopic methods of analysis of materilas. Detectrors for X and
gamma photons. CT and PET technique.
5. Quantum-mechanical description of metals and semiconductors. Effective
mass of electron and hole.
6. Hall effect and quantum Hall effect. Plateaus and Klitzing constant.
7. Quantum technology method: ESR.
297
8.
9.
10.
11.
12.
13.
EXAM
Quantum technology method: NMR.
Low temperature superconductivity. BCS theory - basic pictures.
Quantization of magnetic flux. Josephson junction and magnetometer.
High temperature superconductivity.
Synchrotron light beam. Nanotechnology. Applications on the micro and
nanoscale in the electrical engineering and IT.
14. Elementary particles. The roles in modern cosmology and epistemology.
15. EXAM
Literature
R. J. Scherrer (2006).
Quantum mechanics: an
accessible introduction,
Pearson Addison Wesley,
San F rancisco
Tomislav Petković (2011).
Eksperimentalna fizika i
spoznajna teorija,
Postskriptum, 3.prom.izd.,
L. I. Schiff (1968). Quantum
Mechanics, 3rd ed., McGrawHill Book Company
C. Hamaguchi (2001). Basic
semiconductor physics,
Springer-Verlag, Berlin
Heildeberg New York
S. Blundell (2009).
SUPERCONDUCTIVITY: A
Very Short Introduction,
Oxford University Press,
Oxford
Radiation Detection and
Measurement G. F. Knoll J.
Wiley & Sons, New York
2000
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» Physics of Electrotechnology (EE&IT), TU Munchen
» Modern Physics (Year 2 Curriculum, Engineering Science), University of
Toronto
298
Prof. dr. sc.
Silvio Hrabar
Course Description
Objective of the course is to provide a review of modern physics (physics of the
20th century) and to provide a link between classical and quantum views of
reality. Modern concepts in physics, especially quantum physics, had a major
impact on electronics and today there is a multitude of applications (and devices)
that are based on these concepts. Therefore, the objective of this course to
elaborate basic concepts in modern physics - from macroscopic to microscopic
approaches, and to treat some of the applications in microwave and optical
frequency regime (lasers, structures for guiding and directing elektromagnetic
waves, optical fibers, periodic structures, new artificial materials based on
metamaterial concept, plasmonic and nano-electromagnetic systems).
E-learning Level
L1
Study Hours
Lecturers
60
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
76
89
C OM
Prerequisites
Engineering
Physics 2
IP
Study Programmes
TI
CS
CE
SEIS
successful students, 4th semester, 2nd year)
Computing (Study) (courses for exceptionally successful students, 4th semester, 2nd
year)
year)
year)
semester, 3rd year)
E/C
L0
EEIT
English Level
EP E
Prof. dr. sc.
Zvonimir Šipuš
6
EC E
Izv. prof. dr. sc.
Lahorija Bistričić
ECT S Credits
EL
Lecturers in Charge
90097
C EA
Modern Physics and Applications in Electrical
Engineering
WT
299
Learning Outcomes
1.
2.
3.
4.
5.
6.
Relate different areas of morden physics
Explain the principles of quantum physics
Apply the principles of quantum physics in simple examples
Relate principles of modern physics and innovative technology
Explain basic principles of EM metamterials in RF and THz regimee
Explain basic principles of nanoelectromagentics, plasmonic and graphene
structures
Knowledge of various topics in physics and engineering in research, development
and design of electronic devices.
F orms of Teaching
» Lectures
» Lectures in2 cycles of 7 and 6 weeks
» Seminars
» Seminars
» Discussions
Grading System
T ype
Seminar/Project
F inal Exam: Oral
T hreshold
0%
Percent of
Grade
70 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
1. Introduction
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
An overview of macroscopic physics
Transition to the microscopic physics
Simple applications of quantum mechanics
Electromagnetic field and Schrödinger equation
Magnetism and quantum mechanics
Quantum mechanics and optics
Mid-term exam
Antennas - structures for directing electromagnetic waves
Structures for guiding electromagnetic waves
Quantum mechanics and optical communications
Electromagnetic metamaterials - artificial crystal structures
300
13. Terahertz electromagnetic systems - a combination of classical
electromagnetism and quantum physics
14. Plasmonic and nano-electromagnetic systems 15. Presentation of seminar project
Literature
B. Schumacher and M.
Westmoreland (2010).
Quantum Processes Systems
and Information, Cambridge
Univ. Press
J . W. Rohlf (1994). Modern
Physics from Alpha to Z,
Wiley
N. Engheta, R. Ziolkowski
(editors) (2006).
Metamaterials, Physics and
Engineering Exploarations,
Wiley
J. D. Joannopoulos, S.G.
Johnson, J.N. Winn, R.D.
Meade (2008). Photonic
Crystals, Molding the flow of
light, Princeton University
Press
Y. B. Band (2006). Light and
Matter, Electromagnetism,
Optics, Spectroscopy and
Lasers, Wiley
Similar Courses
» Contemporary physics, University of California Berkeley
301
Study Programmes
3rd year)
E-learning Level
L1
Study Hours
Lecturers
45
15
Grading
Acceptable (2)
50
Good (3)
65
Very Good (4)
75
Excellent (5)
85
The requirements for passing
the course include the
following: (1) passing grades
on all laboratory exercises, and
(2) the obtained minimum
grade on the oral exam.
Prerequisites
SEIS
Learning Outcomes
Describe fundamental characteristics and methods of multimedia coding.
Explain fundamental concepts and architecture of the World Wide Web.
Create simple static and dynamic web content.
Analyze web traffic between client and server.
Describe the fundamentals of web search.
Explain Voice over IP (VoIP) architecture and identify fundamental
protocols.
7. Explain video over IP and IPTV fundamentals.
8. Explain fundamentals of P2P networks and applications.
TI
CS
CE
1.
2.
3.
4.
5.
6.
Knowledge and skills in the area of multimedia services, service architecture and
communication protocols. Understanding of multimedia streaming services, with
emphasis on Internet telephony and multimedia conferencing. Skills required for
practical implementation of services based on World Wide Web and related
technologies.
C EA
C OM
T eaching Assistant
Ivan Slivar, mag. ing.
EEIT
L1
EP E
Introduction to multimedia services, concepts and terminology. F undamental
service architectures and communication requirements. Media spatial and
temporal relations, synchronization. Multimedia content formats and standards.
Auditory and visual multimedia content. Syntetic content. Metadata and
searching. World Wide Web, architecture, communication protocols, applications
and technologies. Multimedia streaming. Internet telephony. Multimedia
conferencing. Multimedia services in mobile networks. Multiuser games and
virtual environments.
English Level
EC E
Course Description
4
EL
Izv. prof. dr. sc.
Doc. dr. sc.
Doc. dr. sc.
Ivana Podnar Lea Skorin-Kapov Ognjen Dobrijević
Žarko
ECT S Credits
WT
Lecturers in Charge
E/C
34289
Multimedia Services
IP
302
F orms of Teaching
» Lectures
» Lectures in student groups.
» Exams
» Written and oral exam.
» Laboratory Work
» Three laboratory assignments.
» Experiments
» Demonstration of analyzed technologies using case study examples.
» Consultations
» Instructors are available for students during the weekly time slot
announced on the web, as well as during regular office hours.
» F our homework assignments.
» Visit to SRCE (University Computing Centre)
Grading System
T ype
Homeworks
Class participation
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
0%
Percent of
Grade
15 %
10 %
10 %
30 %
25 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
10 %
10 %
0%
55 %
10 %
1. Introduction to multimedia services, concepts and terminology. The
concept of media; discrete media, continuous media. Digital form, coding
and compression. Quality of Service and Quality of Experience.
2. Models and architectures of multimedia communication systems.
Distributed systems and distributed processing models.
3. World Wide Web, architecture and communication protocols. Concept of
hypertext and hypermedia, selected standards. Client and server
technologies, dynamic content.
4. Auditory multimedia components, audio and speech coding, selected
standards. Visual multimedia components: image coding.
5. Visual multimedia components: video coding, selected standards. Media
spatial and temporal relationships. Synchronization of auditory and visual
components.
6. Multimedia streaming models.
7. Communication protocols in multimedia systems: RTP, SIP/SDP, RTSP.
8. Voice over IP and Internet telephony. Network configurations, protocols,
standards. Internet telephony quality.
9. Week in which midterms are being held.
10. Week in which midterms are being held.
11. Cloud-based multimedia services.
303
12. Video over IP. IPTV.
13. Peer-to-peer networks and service examples.
14. Content distribution networks, examples and communication
requirements.
15. Conversational services. Multiuser environments. Virtual environments
and networked games.
Literature
OA. Bažant, G. Gledec, Ž.
Ilić, G. Ježić, M. Kos, M.
Kunštić, I. Lovrek, M.
Matijašević, B. Mikac, V.
Sinković (2004). Osnovne
arhitekture mreža, Element,
Zagreb
J. Crowcroft, M. Handley, I.
Wakeman (1999).
Internetworking Multimedia,
Morgan Kaufmann
Publishers
B. Krishnamurthy, J.
Rexford (2001). Web
Protocols and Practice: HTTP
1.1, networking protocols,
caching, and traffic
measurement, AddisonWesley Pearson Education
J.F . Kurose, K.W. Ross
(2009). Computer
Networking: A Top-Down
Approach Featuring the
Internet (5th Edition),
Addison Wesley
Similar Courses
» Telematics Services (263000), University of Twente
» Communication and Multimedia (6A2916), Royal Instutute of Technology
Stockholm
» Topics in Multimedia Computing and Networking (CS2, University of
California Berkeley
304
Study Programmes
year)
year)
40
5
15
Lecturer
C EA
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
Study Hours
Lecturers
Exercises
C OM
L1
EP E
Multimedia technologies and systems; architecture and applications. Multimedia
signal sources. F undamentals of compression and coding. Speech signal, modeling
and analysis. Parametric models; speech coding standards. Speech synthesis and
recognition. Audio signal. Psychoacoustic model, audio coding principles and
standards. Human visual perception model. Image formats, coding, and standards.
Video signal and its properties. Spatial, time and subjective redundancy. Video
compression standards. Storage, processing and transmission of multimedia
content. Hardware and software implementations. Integration of multimedia
content; synchronization. Multimedia systems and tools.
E-learning Level
50
62
78
90
Prerequisites
Algorithms and Data
Structures
EC E
Course Description
L0
EL
Doc. dr. sc.
Josip Knezović
English Level
WT
Prof. dr. sc.
Sonja Grgić
4
IP
Prof. dr. sc.
Davor Petrinović
ECT S Credits
SEIS
Lecturers in Charge
E/C
86482
CE
CS
Learning Outcomes
TI
1. Define media signals, their representation, processing and applications
2. Distinguish source coding and entropy coding and various algorithms for
media compression
3. Apply and analyze methods for predictive and transform coding of media
signals
4. Describe human visual perception model and explain properties of video
signal
5. Explain differences between analog and digital video signal representation
6. Employ methods for image and video signal compression
305
The purpose of the course is to give students fundamental knowledge on
multimedia signals and technologies for their representation, processing,
transmission and presentation. Students will learn to use computer-based tools
for multimedia signal processing and composition and will be able to choose and
implement suitable algorithms for voice, image, audio and video processing to
meet given demands in different multimedia applications.
F orms of Teaching
» Lectures
» -» Exercises
» -» Laboratory Work
» -» Experimental Exercises
» -» Internship visits
» --
Grading System
T ype
Homeworks
Attendance
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
0%
Percent of
Grade
12 %
3%
5%
30 %
40 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
12 %
3%
5%
0%
60 %
20 %
Comment:
Necessary requirements to pass the course exam through continuing education are
the following: student must attain at least 50% of total points from categories:
laboratory exercises, homework and class attendance and at least 50% of total
points from midterm exam and written part of the final exam. Student who
doesn't fulfill these requirements can not approach the oral part of the final exam.
The requirement to pass the course through end of semester course exam is also
50% of total points from categories: laboratory exercises, homework and class
attendance
1. Introduction to multimedia technologies. Architecture of multimedia
system. Business aspects of multimedia systems and their applications.
Multimedia signals and sources, requirements for their processing and
transmission in multimedia systems.
2. Principles of coding and compression. Classification of methods. Lossless
and lossy compression.
306
3. Entropy coding. Huffman coder, Arithmetic coder. Entropy constrained
scalar quantization. High rate analysis of entropy constrained scalar
quantization.
4. Predictive, transform and sub-band coding. Speech signal. Modeling and
analysis. Parametric model and speech coding.
5. Coding standards and their properties. Demonstration of basic properties
of different audio coding algorithms. Principles of speech synthesis and
recognition.
6. Human visual perception model. Eye-brain mechanism, human perception
of color. Light sources, equal-energy white, subjective effects of color
sensation. Standard observer and luminosity curve. Additive color mixing,
CIE and EBU primary colors.
7. Color matching, unity equation, chromaticity coordinates, color matching
functions. Vector representation of color, primary-color triangle,
chromaticity diagram, color temperature, hue and saturation in
chromaticity diagram.
8. Mid-term exam.
9. Video signal, formats and properties. Progressive and interlaced scanning.
Number of lines and number of frame per second. Video bandwidth.
Horizontal and vertical resolution. SDTV and HDTV formats. Analog to
digital conversion. Chroma subsampling. Bit rate.
10. Principles of image and compression. Spatial, time and subjective
redundancy in video signal. Transform coding. Common image formats and
compression standards, their fundamental properties and applications.
Video coding standards and their applications.
11. Storage, processing, transmission and presentation of multimedia sources.
12. Hardware and software implementations of multimedia processing
algorithms.
13. Integration of multimedia content. Synchronization.
14. Survey of multimedia systems and their applications. Multimedia software
tools. Examples.
15. Visit to Croatian Radiotelevsion.
Literature
Z. N. Li, M. S. Drew (2004).
Fundamentals of Multimedia,
Prentice Hall
R. Steinmetz, K. Nahrstedt
(2002). Multimedia
Fundamentals, Volume I:
Media Coding and Content
Processing, Prentice Hall
Y. Q. Shi, H. Sun (2008).
Image and Video Compression
for Multimedia Engineering:
Fundamentals, Algorithms,
and Standards, CRC Press
Similar Courses
» CE-HCI10 Multimedia systems, IEEE & ACM Computing Curricula
» 72814 Medientechnik, TU Munchen
» 18-796 Multimedia Communications, Carnegie Mellon University
307
Basic concepts of network and distributed programming. TCP and UDP socket
interface. Client and server design. Network applications based on UDP and TCP.
Design and implementation using threading and concurrency. Broadcast and
multicast applications. SCTP socket interface. Security issues. Practical examples
of network applications in Unix environment using C. Practical examples of
network programming in Java and script languages.
Study Programmes
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
C OM
T eaching Assistant
Denis Salopek, mag. ing.
Grading
Acceptable (2)
50
Good (3)
65
Very Good (4)
78
Excellent (5)
90
Prerequisites
SEIS
IP
WT
3rd year)
Learning Outcomes
CE
Define types socket interfaces and specify their properties.
Distinguish between connection and connectionless oriented applications.
Distinguish the design process of iterative and concurrent servers.
Write simple UDP network applications using C in Unix environments.
Analyze simple network applications and debug errors in own
applications.
6. Use the basic tools for design and testing of network programs in Unix
environment.
TI
CS
1.
2.
3.
4.
5.
Students will learn about network programming which will enable them to fully
understand the abilities and uses of network applications. Students will gain
practical skills in creation of network applications in Unix environment using C
with some examples in Java and scripting languages.
EEIT
English Level
C EA
Course Description
4
EP E
Izv. prof. dr. sc.
Miljenko Mikuc
ECT S Credits
EC E
Lecturer in Charge
E/C
34335
Network Programming
EL
308
F orms of Teaching
» Lectures
on the web. Lectures will be held in two cycles (7 + 6 weeks), 2 hours
a week.
» Exams
» Midterm exam will be held after the first lecture cycle, the final
exam after the second lecture cycle. The students can also take
regular exams.
» Laboratory Work
» Design of UDP and TCP clients and servers (using C-programming
language) and verification in IMUNES network simulator
environment.
Laboratory exercises will be held in 3 cycles, each in extent of 5
hours.
» Consultations
» Regular weekly consultations.
» Literature search on communication networks.
Building software in C-programming language, debugging.
» in homework and laboratory
» Students independently solve program problems as a preparation
for laboratory exercises.
Grading System
T ype
Homeworks
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
15 %
30 %
45 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
15 %
0%
0%
85 %
1. Introduction. OSI and TCP/IP reference model. Client-server and peer-topeer models.
2. Port and socket. Socket API. Name and address.
3. UDP server and client. Command line arguments parsing. Program testing.
4. TCP server and client. Concurrency.
5. Socket options.
6. Raw socket.
7. Daemons and super-server "inetd".
9. I/O multiplexing. Threading.
10. Broadcast and multicast addressing and applications.
11. Application protocols based on UDP. TF TP.
12. Application protocols based on TCP. HTTP and F TP. Simple HTTP server.
13. Security issues and programming guidelines.
309
14. Java network programming.
Literature
W. Richard Stevens, Bill F enner, Andrew M. Rudoff Addison
(2003). Unix Network Programming, Vol. 1: The Sockets
Networking API, Addison-Wesley Professional
Gary R. Wright, W. Richard Stevens (1995). TCP/IP Illustrated:
The Implementation, Vol. 2, Addison-Wesley Professional
Similar Courses
» Internet Programmming, EPF L Lausanne
» Concurrent Programming 2: Concurrent Object-Orient, ETH Zurich
310
Doc. dr. sc.
Marko Čupić
Course Description
Introduction. Basic principles of object-oriented programming and design.
Modelling. Reusability. F rameworks for program development. Java
programming language. Java as a machine independent platform. Programming
tools. Command line tools. Coding conventions. Refactoring. Abstraction.
Encapsulation. Classes and objects. Static members. Access modifiers. Constructors.
Class relationships. Memory management and garbage collectors. Inheritance.
Polymorphism. Abstract classes. Interfaces. Introduction to design patterns.
Exceptions. F iles and streams. Collections. General collection algorithms. Simple
and complex comparators. Generics. Multithreading and multithreaded
applications. Events. Development of applications with graphical user interface.
Simple and complex graphical components. Development of custom graphical
components. Program testing. Program performance analysis. Program
optimization.
Doc. dr. sc. Mirko Randić
Dr. sc. Karla Brkić
Jurica Babić, mag. ing.
Tomislav Jagušt, dipl. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
-
50
65
80
90
Prerequisites
Algorithms and Data
Structures
EEIT
TI
Study Programmes
Learning Outcomes
1. Describe the principles of the object oriented programming paradigm
2. Apply the concepts of abstraction, data encapsulation, inheritance and
polymorphism to software design
3. Use an object oriented programming language, and associated class
libraries, to develop programs
4. Design, develop, test, and debug programs using object oriented principles
in conjuncture with an integrated development environment
C OM
60
15
C EA
Study Hours
Lecturers
EP E
L1
EC E
E-learning Level
EL
Doc. dr. sc.
Boris Milašinović
L1
WT
Doc. dr. sc.
Ivica Botički
English Level
IP
Doc. dr. sc.
5
SEIS
Izv. prof. dr. sc.
Mario Kušek
ECT S Credits
CE
Lecturers in Charge
E/C
127225
Object-oriented programming
CS
311
5. Design and develop programs with Graphical User Interfaces capabilities
6. Apply multi-threading for creation of responsive user interfaces
7. Describe and explain the factors that contribute to a good object oriented
solution
After passing the exam, students will be able to understand the basic concepts of
object oriented programming. They will be able to develop the applications of
small and medium complexity in Java on their own. They will be able to apply the
learnt concepts of object oriented paradigm when working in other programming
languages.
F orms of Teaching
» Lectures
» Materials and presentations are on course web page.
» Exams
» Midterm exam and final exam
» Laboratory Work
» complex laboratory assignments which includes object oriented
programming in Java
» Experiments
» inside the lectures are demonstrations of program solutions and
tools
» Consultations
» consultations are conducted by all professors and teaching assistants
every week
» Searching Web and finding work in the field of the course
» Personal tools for programming in Java, independent specification
and programming programs in Java
» E-learning
» independent finding video tutorials and experimenting with them
» Other
» homework
Grading System
T ype
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
50 %
25 %
25 %
Exam
T hreshold
Percent of
Grade
0%
0%
50 %
0%
50 %
1. Java programming language. Java as a machine independent platform.
Programming tools. Command line tools. Coding conventions.
Refactoring.
2. Abstraction. Encapsulation. Classes and objects. Static members. Access
modifiers.
3. Constructors. Class relationships.
312
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Inheritance. Polymorphism.
Abstract classes. Interfaces.
Nested and anonymous classes. Exceptions.
F iles and streams.
Midterm exam.
Collections. Basics of collections, sets and implementations, lists and
implementations. Maps. Other collections.
General collection algorithms. Generics. Simple and complex comparators.
Development of applications with graphical user interface. Basics,
windows, visual component layout and supporting managers. Simple
graphical components.
Introduction to multithreading and multithreaded applications: basics,
working with thread pools.
Components for complex data display: models and views. Menus.
Development and use of custom graphical components. User interfaces and
multithreading.
Program testing. Program performance analysis. Program optimization.
F inal exam.
Literature
Grady Booch, Robert A.
Maksimchuk, Michael W.
Engle, Bobbi J. Young, Jim
Conallen, Kelli A. Houston
(2007). Object-Oriented
Analysis and Design with
Applications (3rd Edition),
Addison-Wesley
Bruce Eckel (2006). Thinking
in Java (4th Edition),
Prentice-Hall
Materijali za Java tečaj, F ER
Kent Beck (2006). TestDriven Development, By
Example, Addison-Wesley
Walter Savitch, Kenrick
Mock (2012). Absolute Java,
Student Value Edition (5th
Edition), Addison-Wesley
Similar Courses
» Introduction to objects oriented programming, EPF L Lausanne
» Object-Oriented Programming, Cambridge
» Object Oriented Programming, Katholieke Universiteit Leuven
» Object-Oriented Programming with Java, Manchester University and UMIST
» Introduction to Programming in Java, MIT
» Object Oriented System Design, Stanford
» Object oriented programming, Politecnico di Torino
» Programmierung für Alle (Java), RWTH Aachen
» Object Oriented Programming with Java, Royal Instutute of Technology
Stockholm
» Introductory Programming and Object Oriented Concepts Using Java, NU
Singapore
313
Definition of term Open Computing, with emphasis on portability, flexibility,
accessibility and interoperability. Comparison of the relationships among the
open hardware, software and users. Analysis of standards, their roles and
standardization process, with emphasis on Internet-related standards and
openness. Explanation of the tagging and example of the presentation of content
using HTML language. Presentation of structured data using XML language.
Representation of rules in the XML language, visualization, transformation and
filtering data, as well as real-world examples of XML language usage. Analysis of
distributed computing concepts (ubiquitous, wireless, mobile, pervasive) based on
open standards and products. Design principles in open, distributed, dynamic,
interactive information services and systems, mostly based on the Web and
associated concepts, technologies, and protocols (REST, Web 2.0, RIA, SOA, HTTP,
URI, MIME, sessions), client (DHTML , F lash) and server technologies (servlets,
ASP, JSP), concepts (MVC, DHTML, AJAX) and languages (PHP, JavaScript, Java).
Basics of security of open systems and the Internet, as well as terms of "free of
costs", freedom of usage and licensing in computer science.
E-learning Level
L2
Study Hours
Lecturers
45
15
Grading
Acceptable (2)
50
Good (3)
62.5
Very Good (4)
75
Excellent (5)
87.5
Depending on the number of
enrolled students and overall
student success, grades are
assigned either by fixed setpoints or on a curve.
Prerequisites
Databases
Software Design
SEIS
Study Programmes
CS
CE
3rd year)
TI
Learning Outcomes
1.
2.
3.
4.
5.
6.
7.
8.
Define term open computing and openness
Describe basic Internet and Web standards
Use structured data in XML form
Apply HTML and CSS languages in Web site pages
Explain communication between browser and Web server
Explain basic server and client Web technologies
Apply different Web technologies
Apply open technology based on its features
C EA
C OM
T eaching Assistant
Dr. sc. Ivana Bosnić
EEIT
L0
EP E
Course Description
English Level
EC E
Doc. dr. sc.
Igor Čavrak
4
EL
Prof. dr. sc.
Mario Žagar
ECT S Credits
WT
Lecturers in Charge
E/C
34286
Open Computing
IP
314
This course capacitates for comprehension of open network computing concepts
and development of dynamical interactive network services. Based on given
parameters, students will be capable to choose appropriate architecture for
network information application or system. Using tools and learned languages,
they will be able to build a system for generation, management and utilization of
dynamic content based on open technologies.
F orms of Teaching
» Lectures
» Lectures will be held 3 hours per week
» Exams
» Exams in written and oral form
» Laboratory Work
» Laboratory exercises will be held every other week for 2 hours
» E-learning
» Usage of additional content in e-learning management system
Grading System
T ype
Quizzes
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
25 %
15 %
20 %
25 %
15 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
25 %
15 %
0%
45 %
15 %
Comment:
To access the written part of exam / final exam it is necessary to submit all
laboratory work and collect a minimum of 50% points, and collect a minimum of
50% points from the mid-term exam. To access the oral exam / final exam it is
necessary to collect a minimum of 45 points from all previous forms of
verification. Oral exam is mandatory and it is necessary to acquire at least 5 of 15
points to pass the course.
1. Introduction to Open Computing; Course organization; Definitions of
Open computing (portability, adaptability, accessibility, interoperability);
Open systems examples; History of open computing; Legends and myths of
Open computing
2. Introduction to tag programming (SCCS, nroff, SGML - Standard
Generalized Markup Language); Visualization of content on Web (HTML HyperText Markup Language); Design of content on Web (CSS - Cascading
Style Sheets); Data forms on Web
3. Structured data; Introduction to XML (Extensible Markup Language); Rules
of XML; Applications of XML; Namespaces; XML rules using DTD
(Document Type Definition); XSD - XML Schema Definition
315
4. Data vizualization, transformations and filtering; DOM - Document Object
Model; XML and DOM; Sequential parsing (SAX - Simple API for XML);
XSL - Extensible Stylesheet Language (XPath, XSLT, XSL-F O)
5. XML usage examples (SMIL - Synchronized Multimedia Integration
Language; RSS - Really Simple Syndication; SVG - Scalable Vector
Graphics; GML - Geography Markup Language; ODF - Open Document
F ormat; OOXML - Office Open XML); Standards (in general, examples,
W3C standards, text data encodings)
6. Distributed systems and Web technologies; Browser, server and
communication (URI - Uniform Resource Identifier , MIME - Multipurpose
Internet Mail Extensions, preglednici, HTTP - HyperText Transfer
Protocol, CGI); PHP language
7. Other server side Web technologies (ASP, Servlets, JSP ...); Programming
languages and openness (portability and scalability, reduction of
complexity, standardization and licensing); Object oriented programming
and Java
8. Mid-term exam
9. Distributed systems; Layered architecture; Distributed applications
architecture;
10. Clients and servers; Inter-process communication; Application protocols;
Protocol mechanisms and services states
11. Web technologies and application server (Servlets, MVC design pattern Model-View-Controller, JSP - JavaServer Pages, JavaBeans)
12. Client Web technologies (DHTML - Dynamic HTML, JavaScript, F lash);
Web 2.0; RIA - Rich Internet Applications; Sessions and statefullness; REST
and Web applications
13. SOA - Service Oriented Architecture; Coupling; Examples (Eclipse, XMLRPC, SOAP); Security and openness (general terms, algorithms, Internet
and security)
14. Wireless and mobile computing (Applets, Midlets, WAP, Java Card);
Various examples of open (and closed) systems; F ree as free of costs and free
for usage, and openness in computing; Creative Commons licence; Other
(ORscar award)
15. F inal exam
Literature
P.A.Dargan (2005). Open
Systems And Standards For
Software Product
Development, Artech House
M.Žagar (2007). UNIX i kako
ga iskorisiti (1. internetsko
izadnje), Sveučilište u
Zagrebu, F akultet
elektrotehnike i računarstva
M.Muffatto (2006). Open
Source: A Multidisciplinary
Approach, Imperial College
Press
B. Eckel (2002). Thinking in
Java (3. elektroničko izdanje),
Prentice Hall
L. Rosen (2004). Open Source
Licensing: Software Freedom
and Intellectual Property Law,
Prentice Hall 2004
Similar Courses
» Software Engineering for Web Applications, MIT
» Client-Side Internet Technologies, Stanford
» Internet Technologies, Stanford
» Introduction to net-centric computing, IEEE & ACM Computing Curricula
316
Learning Outcomes
1. Write an multithreaded program and program which creates multiple
processes
2. Demonstrate how interrupt service routine works
3. Apply synchronization mechanisms
4. List components of operating system kernel
5. Analyze deterministic and non-deterministic task system behaviour
6. List and explain CPU scheduling algorithms
7. Employ memory allocation mechanisms
8. Develop file-system functions
75
15
C OM
Lecturer
EP E
C EA
Darko Jurić, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
-
EEIT
Study Hours
Lecturers
50
63
75
88
EC E
Study Programmes
L1
EL
An operating system is a set of programs that act as an intermediary between a
user of a computer, the computer hardware and the applications programs. The
purpose of an operating system is to provide an environment in which a user can
execute programs in a convenient and efficient manner.
E-learning Level
WT
Course Description
L1
Prerequisites
Algorithms and Data
Structures
IP
Izv. prof. dr. sc.
Domagoj
Jakobović
English Level
Prerequisites for
Databases
Software Design
SEIS
Doc. dr. sc.
Leonardo
Jelenković
7
CE
Izv. prof. dr. sc.
Marin Golub
ECT S Credits
CS
Lecturers in Charge
E/C
31501
Operating Systems
TI
Students will be acquainted with functioning of modern operating systems.
Students will be able to use the standard programming tools to develop program
modules which include interrupts handling, multithreading, synchronization
mechanisms and inter-process communication.
F orms of Teaching
» Lectures
» Teaching is organized into two teaching cycles (15-week classes, 5
hours per week). F irst cycle consists of 7-week classes and midterm
exam. Second cycle consists of 6-week classes and final exam.
» Exams
» Short tests. Midterm exam. F inal exam.
» Laboratory Work
317
» 5 laboratory exercises
» Consultations
» konzultacije
» Programming tasks.
Grading System
T ype
Homeworks
Quizzes
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
16 %
4%
10 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
0%
0%
50 %
50 %
1. Introduction. Operating system roles. Interfaces. Computer and operating
system components. Operating system services. Model of simple
computer. The role of processor and memory in a simple computer.
Računalni proces. Zamjena konteksta. Threads. Processes. Context
switching.
2. I/O structure. Interrupts. Interrupt service routine. Interrupts handling.
Transferring block of data. Direct Memory Access (DMA) devices.
3. Basic terms: programs, tasks, processes and threads. Multithreading.
Independent and cooperating threads. Critical regions. Mutual-exclusion
algorithms. Dekker's algorithm. Peterson's algorithm.
4. Mutual-exclusion for any number of concurrent threads. Lamport's
protocol. Hardware support for mutual-exclusion. Simple kernel model.
Kernel data structures.
5. Thread descriptor. Thread states. Entering and leaving kernel. Mutualexclusion and synchronization: semaphores.
6. Basic I/O kernel functions. Kernel implementation in multiprocessor
system. Producer and consumer problem. Interprocess communication.
Bounded and unbounded buffer problem. Message queue.
7. Thread synchronization. Deadlock and starvation. Avoiding deadlock.
Necessary conditions for deadlock. Dining-philosophers problem.
Monitors. Synchronization examples with monitors.
8. Midterm exam
9. Introduction to computer systems behaviour analysis. Periodic and
aperiodic tasks. Deterministic task system behaviour. Stochastic task
system models.
10. Poisson distribution of task arrivals. Exponential distribution for
processing time. CPU scheduling. F irst-come, first-served scheduling.
Priority scheduling. Round-robin scheduling.
11. Logical and physical address space. Secondary-storage structure. Memory
allocation. Internal and external fragmentation.
12. Segmentation. Paging. Virtual memory.
13. Demand paging. Page-replacement algorithms.
14. F ile-system. F ile-system organization. Disk free space management. F ile
descriptor. Typical file-system functions.
15. F inal exam
318
Literature
Budin, L.; Golub, M;
Jakobovic, D., Jelenkovic, L
(2010). Operacijski sustavi,
Element, Zagreb
Silberschatz, A., P.B. Galvin,
G. Gagne (2003). Operating
Systems Concepts, John
Wiley&Sons, New York
Tannenbaum, A. S. (2001).
Modern Operating Systems,
Prentice Hall
Silberschatz, A., P.B. Galvin,
G. Gagne (2000). Applied
Operating Systems Concepts,
John Wiley&Sons, New
York
Similar Courses
» Operating System F oundations, Cambridge
» Operating Systems and Systems Programming, Stanford
» Operating System Engineering, MIT
319
Course Description
The course deals with the basic phenomena associated with the technology that
enables optical transmission of information. The components needed for building
communication systems are described (lasers, modulators, fibers, photodetectors).
The examples of optical communication systems are given.
Study Programmes
L1
E-learning Level
L1
Study Hours
Lecturers
Exercises
26
9
10
T eaching Assistant
Dr. sc. Marko Bosiljevac
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
EEIT
English Level
C OM
Doc. dr. sc.
Dubravko Babić
4
50
63
76
89
C EA
Prof. dr. sc.
Zvonimir Šipuš
ECT S Credits
EP E
Lecturers in Charge
E/C
91856
Optical Communication Technology
EC E
Prerequisites
Electronics 1
WT
EL
Learning Outcomes
IP
TI
CS
CE
SEIS
1. Describe the physical method of wave propagation inside the fiber,
describe the limitations of fiber data transmission
2. Describe the laser working principle, describe the main laser types
3. Describe the mechanisms that enable realization of high-quality
semiconductor lasers
4. Describe the methods of modulation and working principle of modulators
used in optical communication systems
5. Describe the working method and limitations of semiconductor detectors
6. Describe the multiplexing methods used in optical communication systems
7. Design simple fiber links
The course gives explanation of background physics connected with phenomena of
generation, propagation and detection of optical waves. After completing the
course the students are expected to be able to understand principles of working of
all photonic components that build optical communication systems. F urthermore,
they will be able to design simple optical systems.
F orms of Teaching
» Lectures
» Lectrures are given with the use of powerpoint presentations
published on the web pages.
320
» Exercises
» Solving problems takes place when necessary (according to the
treated subject). Exercises are held by teaching assistant.
» Laboratory Work
» F our laboratory exercises take place as a part of the course.
Grading System
T ype
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
Percent of
Grade
10 %
25 %
25 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
10 %
0%
45 %
45 %
1. Overview of optical communication and non-communication systems;
Waves, plane waves, mathematical description of plane waves,
polarization, intensity.
2. Wave coherence, interferometers, holography
3. Guided optical waves, fibers, fiber types
4. Restrictions on information transmission in fibers (attenuation, dispersion)
5. Absorption, spontaneous emission, stimulated emission, Einstein's
coefficients, lineshape function
6. Laser principle, basic laser gain equation, mode selection, laser types,
examples: HeNe laser, CO2 laser.
7. Mid-term examination
8. Semiconductor properties, quantum mechanics concepts, direct- and
indirect-bandgap semiconductors, semiconductor materials, p-n junction,
heterojunctions
9. Optical semiconductor sources, Light-emitting diodes (LEDs)
10. Laser diodes, characteristics of laser diodes, laser diode types (F abry-Perot,
DF B, DBR, tunable singlemode lasers, VCSEL)
11. Modulation principles in optical systems, direct modulation on LEDs and
laser diodes, electro-optic modulators, electroabsorption modulators,
magneto-optic modulators
12. Semiconductor photodetectors, PIN and avalanche photodiodes
13. Optical amplifiers
14. Design of optical communication systems, power budget, rise-time budget
15. Multiplexing in optical communication systems, WDM systems, properties
of DWDM and CWDM systems
321
Literature
B.E.A. Saleh, M.C. Teich
Photonics 1991, John Wiley
G.P. Agrawal (2010). FiberOptic Communication
Systems, John Wiley
P. Bhattacharya (1997).
Semiconductor
Optoelectronic Devices,
Prentice Hall
Similar Courses
» Optoelectronics, Chalmers University
» Photonics, Royal Instutute of Technology Stockholm
» Photonics and Optical Communication, Lund University
» Optical Communications, TU Wien
» Photonics, Royal Instutute of Technology Stockholm
322
Course Description
Concept of web application. Structure of HTML document. Usage of tables and
forms in HTML. PHP basics. Dynamic HTML generation using PHP. Usage of
relational databases from PHP (illustrated on MySql). Usage of phpMyAdmin web
frontend. Dynamic HTML generation using data from database. Modularization of
PHP applications. Usage of templates for GUI generation. Additional
technologies. Ajax.
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
30
15
C OM
Grading
EEIT
3
Course has no grades. To pass
the course, students must be
present at lectures, pass all
homework and individual
student project. There will be
no additional exams.
C EA
Doc. dr. sc.
Marko Čupić
ECT S Credits
EP E
Lecturer in Charge
E/C
58312
PHP Application Development Basics
EC E
EL
Learning Outcomes
IP
Explain the concept of dynamic web application
Create simple and medium complex web applications
Employ relational database for web application
Employ forms in web application
Describe the structure of HTML document
Define the role of frameworks for the development of web applications
SEIS
1.
2.
3.
4.
5.
6.
WT
CE
TI
CS
Student will be able to differentiate between static and dynamic web applications.
He will be able to apply PHP for development of dynamic web applications. He
will know how employ web forms for communication with users, how to connect
PHP application and relational database and how to use templates for GUI
creation. He will be able to employ Ajax for communication with server.
F orms of Teaching
» Lectures
» Will be held in computer laboratories so that students can work out
presented examples and solve given course tasks.
» Exams
» Students will be given a series of problems to solve as part of
regular homeworks. At the end, an individual student project will be
given which is mandatory for positive grade.
323
Grading System
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
Comment:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Introduction to PHP, web applications and forms
Introduction to object-oriented programming with PHP
Accessing and using relational databases from PHP
Sessions and file uploads
Internet services and RSS technology
Creation and editing of images using PHP
Templating engine Smarty
Control of forms, working with e-mail
Introduction to JavaScript
JavaScript library jQuery
Controlling forms using jQuery, WYSIWYG editors: TinyMCE
Basics of Yii framework
F ramework Yii
Literature
Žuri Goran, Davor Cihlar
(2009). Materijali za
predavanja
Rasmus Lerdorf, Kevin
Tatroe, Peter MacIntyre
(2006). Programming PHP,
O'Reilly
Wiki stranice Practical PHP
Programming
324
Study Hours
30
Grading
Vitomir
Blagojević,
prof.
T ype
Class participation
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Prerequisites for
IP
SEIS
Grading System
CE
CS
Study Programmes
1 point is equal to one hour
spent in training. Walking to
Sljeme is worth 3 hours, or 3
points. It is possible to receive
maximum of 12 point of
activity in the gym. Walking
to Sljeme gives minumum of 9
points and it cannot be
exchanged with exercise in
gym. Student is relieved of the
obligations if he/she
participates at the university
championship or is the
member of a club that
compete in official
competition.
TI
Course Description
EEIT
L1
C OM
E-learning Level
C EA
L3
EP E
English Level
EC E
0
EL
ECT S Credits
WT
Teaching Assistant
E/C
21013
325
Study Hours
30
Grading
Vitomir
Blagojević,
prof.
Course Description
Study Programmes
Grading System
T ype
Class participation
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
compete in official
competition.
CS
CE
SEIS
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
IP
EEIT
L1
C OM
E-learning Level
C EA
L3
EP E
English Level
EC E
0
EL
ECT S Credits
WT
Teaching Assistant
E/C
21015
326
Study Hours
30
Grading
Vitomir
Blagojević,
prof.
semester, 2nd year)
Grading System
T ype
Class participation
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
Prerequisites
IP
Study Programmes
compete in official
competition.
SEIS
Course Description
CS
CE
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
EEIT
L1
C OM
E-learning Level
C EA
L3
EP E
English Level
EC E
0
EL
ECT S Credits
WT
Teaching Assistant
E/C
31492
327
Study Hours
30
Grading
Vitomir
Blagojević,
prof.
semester, 2nd year)
Grading System
T ype
Class participation
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
IP
Study Programmes
compete in official
competition.
SEIS
Course Description
CS
CE
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
Continuous work
TI
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
EEIT
L1
C OM
E-learning Level
C EA
L3
EP E
English Level
EC E
0
EL
ECT S Credits
WT
Teaching Assistant
E/C
31499
328
Course Description
Physical methods, dimensions and units. Kinematics of particle, linear, rotational
and curvilinear motion. Newtons laws. System of particles, center of mass,
conservation of momentum. Work, energy, power. Conservative and
nonconservative forces. Statics. Mechanics of rigid body. Gravitation. Inertial and
noninertial frames. Relativistic mechanics. Statics of fluids, flow of ideal and real
fluids. Heat and thermometry. Kinetic theory of heat. Thermodynamics, cyclic
processes, entropy.
Study Programmes
L1
Study Hours
Lecturers
75
15
Prerequisites
Mathematics 1
EL
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
85
All laboratory exercises must
be completed and get
minimum of 5 points.
EC E
EP E
C EA
C OM
Doc. dr. sc. Ana Babić
Doc. dr. sc. Krešimir Trontl
Dr. sc. Danijela Grozdanić
Mr. sc. Radomir Ječmenica
Paulina Dučkić, mag. ing.
EEIT
E-learning Level
WT
Doc. dr. sc.
Saša Ilijić
L1
IP
Doc. dr. sc.
Sanda Pleslić
English Level
Prerequisites for
Electromechanics
Energy Technology
Physics 2
SEIS
Doc. dr. sc.
Zoran Narančić
6
CE
Prof. dr. sc.
Izv. prof. dr. sc.
Tomislav Petković Lahorija Bistričić
ECT S Credits
CS
Lecturers in Charge
E/C
21006
Physics 1
Learning Outcomes
TI
1. Analyze simple mechanical systems and solve equations of motion.
2. Apply principles of conservation of energy and momentum to particle
collisions.
3. Apply the derivative (Mathematics 1) to find minima or maxima of
physical quantities in excercises in mechanics.
4. Apply integrals (Mathematics I) in finding the centre of mass and moments
of inertia of symmetric bodies.
5. Explain the conditions of statics of rigid bodies and the equation of motion
for rotation of the rigid body around fixed axis.
6. Explain the principles of the Special theory of relativity.
7. Apply the equation of continuity and Bernoulli's equation in simple
problems in fluid mechanics.
329
8. Explain the first law of thermodynamics and analyze thermodynamic
cycles.
Students completing this course will: - understand, appreciate and utilize the
modern scientific methodologies associated with fundamental physical laws. understand the importance of applications of the physical priniples in the
techonological advances in various fields of science and engineering. - understand
the fundamental principles of physics which will prepare them to continue
education in modern science and technology at F aculty of Electrical Engineering
and Computing or another university, as well as forming a foundation for lifelong learning.
F orms of Teaching
» Lectures
» Lectures are delivered to groups of approximately 120 students
using electronic presentations, detailed derivations on the
blackboard and demonstration experiments.
» Exams
» Written mid-term exam and the final exam consist of four excercises
and a number of multiple choice questions.
» Laboratory Work
» Students perform six laboratory experiments, carry out the analisys
of the measured data and write the final report for each experiment.
» Experiments
» Lectures are supported by demonstration experiments that illustrate
the concepts of physics. Approximately 30 mins / week.
» Consultations
» At least once a week each professor is available to the students for
consultations.
» E-learning
» During the semester homework assignments are delivered to the
students through the e-learning system Merlin (Moodle).
» In approximately 5-7 terms per semester additional exercisesolving skills are demonstrated by assistants.
Grading System
T ype
Homeworks
Exam: Written
T hreshold
Percent of
Grade
5%
0%
0%
0%
10 %
10 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
5%
0%
0%
10 %
10 %
0%
80 %
Comment:
In the mid-term exam and in the final exam one (of four) excercises must be
correctly completed. In the written exam two (of six) excercises must be correctly
completed.
330
1. Material point in mechanics. Physical methods,units and measurement, SI
system of units, Kinematic of material point. Coordinate systems. Velocity
and acceleration. I. i II. Newtons law. Lecture demonstrations experiments,
computer simulations, infomation on physics experiments by means of
web.
2. Motion of material point. F orce in mechanics. Equations of motions. F ree
fall. Phenomenological experiments. Meauserment of free fall. Vertcal
shot.F orce of friction.Resisting force linery depending on velocity. Lecture
demonstrations experiments, computer simulations, infomation on physics
experiments by means of web.
3. Curvilinear motion. Uniform circular motion. Projectile motion. Ballistic
curves. Horizontal projectile motion. Uniform circular motion: angular and
tangential velocity.
4. Non-uniform circular motion. III. Newton axiom. Work,energy,power.
Tangential and angular acceleration. Centripetal force. Axial vectors.
Impulse and momentum. Kinetic and potential energy. Conservative forces.
Potential energy and conservative forces. Nonconservative forces.
5. Conservation of momentum and energy. Elastic and non-elastic collisions.
6. Mechanics of rigid body. Static. Static of particles. Rigid body properties.
Rigid body motions. Equilibrium of rigid bodies. Torque. Center of mass.
Center of gravity. Systems of particles.
7. Rotation of rigid body. Rotation of rigid body about a fixed axes. Moment
of inertia. Steiner theorem. Angular momentum. Conservation of angular
momentum. Work and power for rotation of rigid body. Precession and
nutation of top. Princip of virtual work.
8. E X A M
9. Gravitation. Inertial frames. Keplers laws. Newton law of gravitation.
Gravitation field,potential and potential energy. Inertial and gravitational
mass. Noninertial frames. Inertial forces. Centrifugal force. Coriolis force.
10. Special theory of relativity. Michelson-Morleyev experiment. Postulates of
special theory of relativity. Lorentz transformation. Length contraction.
Dilatation of time. Addition of velocities. Relativistic dynamic. Relativistic
energy.
11. F luid mechanics:static. Pressure. Hydrostatic pressure. Pascal principle.
Torricellis experiment. Atmospheric pressure. Buoyant force. Archimedes
principle. Surface tension. Capillarity.
12. F luid dynamics. Ideal fluids. Equation of continuity. Bernoullis equation.
Viscosity. Poiseuille law. Magnus effect. Real fluids.
13. Heat. Temperature. Thermometers. Termic expansion of solids and fluids.
Gas laws. Equation of state for ideal gas. Calorimetry. Heat capacity. Phase
diagrams. Agregate states. Heat conduction. Kinetic theory of gases. Real
gases. Brown motion. Ideal gas law. Internal energy. Termodinamical
temperature. Specific heats of gases. Specific heats of solids. Maxwell
velocity distribution. Maxwell-Boltzmann distribution.
14. Thermodynamics. The first law of thermodynamics. F unction of states and
processes. Mayer relation. Equation of adiabate. Ideal gas work. The second
law of thermodynamics. The Carnot cycle. Heat engines. Entropy. The third
law of thermodynamics.
15. E X A M
331
Literature
Dubravko Horvat (2005).
Fizika 1- Mehanika i toplina,
Hinus
T. Petković (1997). Uvod u
znanost o toplini i
termodinamici, Element
P. Kulišić, L. Bistričić, D.
Horvat, Z. Narančić, T.
Petković, D. Pevec (2002).
Riješeni zadaci iz mehanike i
topline, Školska knjiga,
Zagreb
D. Halliday, R. Resnick, J.
Walker (2003). Fundamentals
of Physics, 6th ed, J. Wiley,
New York
Petar Kulišić (2005).
Mehanika i toplina, Školska
knjiga, Zagreb
Similar Courses
» Physics I, MIT
» Physics for Engineering Students I, Carnegie Mellon University
332
Course Description
Solid state materials elasticity. Mechanical oscillation and mechanical waves.
Sound waves. Doppler?s effect. Electromagnetic waves. Maxwell?s equations.
Wave equation, wave propagation. Geometrical optics, mirrors, lenses and prisms.
Physical optics. Interference, diffraction and polarization. Photometry. Quantum
nature of light. Blackbody radiation, quantization. Photo effect and Compton?s
effect. Atom structure. Atomic specters. X-rays. Atomic nucleus. Radioactivity.
F ission and fusion. Basic nature forces and elementary particles.
Study Programmes
Computing (Study) (required courses - physics 2, 3rd semester, 2nd year)
Learning Outcomes
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
85
All laboratory exercises must
be completed and get
minimum of 5 points.
Prerequisites
Physics 1
Prerequisites for
Computing Methods of
Modern Physics
Modern Methods of Physics
for Electrical Engineering
and Information Technology
Modern Physics and
Applications in Electrical
Engineering
Radio Navigation
EEIT
TI
1. Analyze oscillatory systems in mechanics.
2. Apply the linearization technique to equations of motion of oscillatory
systems.
3. Explain the wave equation in nondispersive medium.
4. Derive the electromagnetic wave equation from the Maxwell equations.
5. Analyze optical systems using the methods of geometrical optics.
6. Explain the phenomena of interference, diffraction and polarization of
light.
7. Explain Planck's law of black body radiation.
8. Relate the atomic spectrum to quantization of energy levels.
C OM
Doc. dr. sc. Ana Babić
Dr. sc. Danijela Grozdanić
Mr. sc. Radomir Ječmenica
Paulina Dučkić, mag. ing.
C EA
75
15
EP E
Study Hours
Lecturers
EC E
L1
EL
E-learning Level
WT
Doc. dr. sc.
Saša Ilijić
L1
IP
Doc. dr. sc.
Sanda Pleslić
English Level
SEIS
Doc. dr. sc.
Zoran Narančić
6
CE
Prof. dr. sc.
Izv. prof. dr. sc.
Tomislav Petković Lahorija Bistričić
ECT S Credits
CS
Lecturers in Charge
E/C
31487
Physics 2
333
Students completing this course will: understand, appreciate and utilize basics of
optics, wave theory and atomic physics in modern technologies and its devices;
understand the fundamental principles of physics to prepare students to continue
education in modern science and technology, as well as forming a foundation for
life-long learning.
F orms of Teaching
» Lectures
» Lectures are delivered to groups of approximately 120 students
using electronic presentations, detailed derivations on the
blackboard and demonstration experiments.
» Exams
» Written mid-term exam and the final exam consist of four excercises
and a number of multiple choice questions.
» Laboratory Work
» Students perform six laboratory experiments, carry out the analisys
of the measured data and write the final report for each experiment.
» Experiments
» Lectures are supported by demonstration experiments that illustrate
the concepts of physics. Approximately 30 mins / week.
» Consultations
» At least once a week each professor is available to the students for
consultations.
» E-learning
» During the semester homework assignments are delivered to the
students through the e-learning system Merlin (Moodle).
» In approximately 4 terms per semester additional exercise-solving
skills are demonstrated by assistants.
Grading System
T ype
Homeworks
Exam: Written
T hreshold
Percent of
Grade
5%
0%
0%
0%
10 %
10 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
5%
0%
0%
10 %
10 %
0%
80 %
Comment:
In the mid-term exam and in the final exam one (of four) excercises must be
correctly completed. In the written exam two (of six) excercises must be correctly
completed.
334
1. The theory of elasticity-introduction. Oscillations. Tension and
compression. Modulus of elasticity. Poisson ratio. Examples and sample
problems. Simple harmonic motion: the force law, equation of motion,
initial conditions. Experiments with the spring. Phasors. Harmonic
motion: energy considerations.
2. Pendula. The simple pendulum. The physical pendulum. Torsion
pendulum. Equations of motion. Torsion modules. Experiments and
examples. Damped simple harmonic motion. Equation of motion, solution
for weak damping, analogy with electrical oscillatory circuit. Examples and
sample problems.
3. Damped harmonic motion II. F orced oscillations and resonance.
Logarithmic damping decrement and Q-factor. Damped harmonic motion:
energy consideration. F orced oscillations and resonance. Experiments.
Analogy with electrical oscillatory circuits. Oberbeck’s pendulums.
Experiments. Modulated oscillations. Lissajouss’s curves. Experiments.
Computer exercises.
4. Waves. Progressive waves. Reflection and superposition. Wave speed.
Reflection and refraction. The principle of superposition. Waves in a
stretched string. Standing waves. F requency specter. Experiments. F ourier
analysis of waves in a stretched string. Wave equation. Energy and power
in a traveling wave.
5. Longitudinal waves. Sound waves. Intensity and sound level. Longitudinal
wave equation. Experiments with the spring. Longitudinal standing waves.
Experiments – Kundt’s tube. Standing waves in solid state materials.
Ultrasound – generation and the application. The Doppler’s sound effect.
6. Basics of electromagnetism. Electromagnetic waves. Gauss law and the
F irst Maxwell’s Equation (both in differential and integral form). AmpereMaxwell theorem and Second Maxwell’s Equation. Third Maxwell’s
Equation. F araday’s law of induction. F araday’s experiments. F ourth
Maxwell’s equation. Wave equation. Experiments with polarization of EM
waves. Poynting’s theorem and Poynting’s vector. Energy transport.
F resnel equations. Computer exercises.
7. Photometry. Geometrical optics I. Basic photometric units and quantities.
Experiments. Basic laws of geometrical optics. Experiments. F ermat’s
principle – reflection and refraction. F resnel equation and geometrical optic
laws. Experimental and demonstrational set. Computer exercises. mirrors.
Spherical refracting surfaces. Thin lenses formulas. Aberration. Prisms.
Dispersion. Experiments.
8. E X A M
9. Physical optics I. Interference. Light as a wave. Young’s experiment.
Coherent light. Intensity in Double-slit interference. Minimums and
maximums. Light interference devices. F resnel biprism experiment.
Michelson’s interferometer. Newton circle. Polarization of light.
Holography. Brewster law. Selective absorption.
10. Physical Optics II. Diffraction of light. Multiple source interference.
Gratings: dispersion and resolving power specter. Experiments. Single-slit
diffraction. Diffraction and optical grating. Polarization of light.
Holography. Brewster law. Selective absorption. Polarization and
absorption device. F araday’s and Tyndal’s effect.
11. Introduction to modern physics I. Blackbody radiation. Rayleigh-Jeans law
of blackbody radiation, Stefan-Boltzman law. Wien laws. Planck law.
Quantum hypothesis.
12. Introduction to modern physics II. The photoelectric effect. Compton effect.
The Bohr model of the hydrogen atom. Clarical explanation of photo effect.
Experiments. Compton scattering. Thomson and Rutherford model of the
atom. Computer exercises.
335
13. The Bohr’s model of atom. Quantization. Balmer’s formula. Energy and
orbit quantization conditions. Absorption and emission of light. Atomic
specters. F ranck-Hertz experiment. X-rays. Experiments. BohrSommerfeld model of the atom. The Schrödinger equation. The Heisenberg
uncertainty principles.
14. Quantum numbers. Nucleus and nuclei-composition of nuclei.
Radioactivity and nuclear reactions. Elementary particles. The Pauli
exclusion principle and the structure of many-electron atoms. Experiments:
detector types, beta-particle detection and gamma-radiation, radiation
protection.
15. E X A M
Literature
V.Henč-Bartolić, P.Kulišić
(2004). Valovi i optika,
Školska kniga, Zagreb
D. Horvat (2011). Fizika II Titranje, valovi,
elektromagnetizam, optika i
uvod u modernu fiziku,
Neodidakta, Zagreb
V. Henč-Bartolić, M. Baće.
P. Kulišić, L. Bistričić, D.
Horvat, Z. Narančić, T.
Petković, D. Pevec (2002).
Riješeni zadaci iz valova i
optike, Školska knjiga,
Zagreb
D. Halliday, R. Resnick, J.
Walker (2003). Fundamentals
of Physics D. Halliday, R.
Resnick, J. Walker J. Wiley, New
York 1993, J. Wiley, New
York
Similar Courses
» Optics and Waves, ETH Zurich
» F ields, Oscillations and Waves, Cambridge
» Waves and Optics; Electromagnetism and Optics, Oxford
336
L1
E-learning Level
L1
Study Hours
Lecturers
15
30
Course Description
Getting acquainted with real solutions of power converters and their operating
characteristics. Power electronic converters, interface between power source and
load. Topologies and functions; basic power conversions. Power converter
components; semiconductor and magnetic, power switches, drivers, DC and AC
filters. Power converter modeling and simulation; control and power
characteristics measurement. Protection and cooling. Power converter application
examples on laboratory devices; line converters, DC/DC and AC/AC converters,
inverters.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
Study Programmes
C EA
C OM
Lecturer
50
62.5
75
87.5
Prerequisites
Engineering
IP
SEIS
Learning Outcomes
TI
CS
CE
1. Explain operation principles of basic power electronic converters
2. Apply the acquired knowledge for modeling and simulation of basic power
converters.
3. Apply the acquired knowledge to measure the characteristic waveforms of
the basic power converters
4. Modify the simulation model to obtain model behavior closer to the real
circuit.
5. Analyze the operation of basic power converters using simulation results
and measurements.
6. Analyze the complex system of a power converters on the basic
components.
Knowing fundamental topologies and functions of power electronic converters.
Ability to select appropriate converter according to required application. Ability
of converter commissioning.
EEIT
English Level
EP E
Prof. dr. sc.
Viktor Šunde
4
EC E
Prof. dr. sc.
Željko Jakopović
ECT S Credits
EL
Lecturers in Charge
E/C
34347
Power Electronics Practicum
WT
337
F orms of Teaching
» Lectures
» Lectures are organized through 2 teaching cycles. The first cycle
consists of 7 weeks of classes and mid-term exam, a second cycle of 6
weeks of classes and final exam. Classes are conducted through a
total of 15 weeks with a weekly load of 1 hour.
» Exams
» Examination consists of mid-term exam and final exam in which
numerical problems are solved, and the writing of reports and
seminars about laboratory exercises.
» Laboratory Work
» Laboratory exercises are organized through 2 cycles. The first cycle
consists of 4 exercises, a second cycle of 2 exercises. Exercises are
conducted through a total of 15 weeks with a weekly load of 2 hours.
» Seminars
» At the end of the second cycle of lectures, students are writting
seminars which demonstrate the ability to connect theoretical
knowledge, modeling and simulation and analysis of measurement
results.
Grading System
T ype
Seminar/Project
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
30 %
30 %
10 %
20 %
10 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
30 %
30 %
0%
20 %
20 %
1. F undamentals of power electronics circuits simulation.
2. F undamentals of power electronics circuits measurements.
3. Basic power electronics switches. Idealised characteristics of power
switches.
4. Power converters topologies and circuits. Rectification and DC/DC
conversion.
5. Power converters topologies and circuits. Inversion and AC/AC conversion.
6. Converter control and power characteristics, efficiency, power factor,
displacement factor.
7. Midterm exam
8. Interaction of power converter, power supply and the load.
9. Power converter system for renewable energy sources as complex power
electronic system. Analysis of basic components.
10. Power converter system for renewable energy sources as complex power
electronic system. Digital control system analysis. Properties and abilities.
Practical work with system.
11. Driver circuits for thyristors and transistors (bipolar, MOSF ET and IGBT).
12. Power semiconductor's dissipated power calculation. Thermal
management. Case study.
338
13. Power semiconductors protection, snubbers, fuses. Catalogue data
interpretation and application.
14. Presentation of seminars. Analysis of complex power electronic systems.
15. F inal exam
Literature
D. W. Hart (1997).
Introduction to Power
Electronics, Prentice Hall
B. W. Williams (2006).
Principles and Elements of
Power Electronics, B. W.
Williams
I. F legar (2010). Elektronički
energetski pretvarači, Kigen
N. Mohan, T. Undeland, W.
Robins (2004). Power
Electronics: Converters,
Applications and Design,
Wiley
Similar Courses
» Leistungselektronik F achpraktikum, ETH Zurich
» Power Electronics, MIT
339
Basic characteristics of the power plants: types, power capabilities, energy
production. Power plants (hydro, thermal, nuclear). Main power plant systems
and equipment. Water, steam and gas turbine types. Nuclear reactor as heat
source. Heat balance diagrams and power generation cycles for different plants.
Characteristics and choice of main power plant electric equipment. Startup and
shutdown of the plant and power change capabilities. One-line station connection
diagram. Choice of synchronous generator parameters. Generator static and
dynamic limits, Q-P diagram. Active and reactive power generation. Generator
synchronization. Analysis of generator operation and loading. Onsite power
systems. Emergency power sources. Grounding system of the plant. Process
measurements. Power plants construction cost, O&M cost, and total production
cost. Electricity price. Power plant operation in liberalized market.
Study Hours
Lecturers
Exercises
30
15
4
Doc. dr. sc. Hrvoje Pandžić
Ninoslav Holjevac, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
90
Prerequisites
Energy Technology
EEIT
L1
C OM
E-learning Level
C EA
Course Description
L1
EP E
Prof. dr. sc.
Igor Kuzle
English Level
EC E
Izv. prof. dr. sc.
Davor Grgić
4
EL
Prof. dr. sc.
Sejid Tešnjak
ECT S Credits
WT
Lecturers in Charge
E/C
127413
Power Plants
IP
Study Programmes
SEIS
Learning Outcomes
CS
Describe main power plants
Explain operation of main equipment in hydro power plant
Explain operation of main equipment in thermal power plant
Identify specific operational requirements in case of nucelar power plants
Analyze s
Describe characteristics of wind power plant operation
Compute main parameters for different power plant types
Analyze connection of different power plants to the grid
TI
1.
2.
3.
4.
5.
6.
7.
8.
CE
Understanding of basic principles and characteristics of different power plant
types. Knowledge of main components characteristics. Power plant operation in
electric power system. Understanding of synchronous generator operation,
operating limits calculation and choice of design characteristics for different power
plant types. Power plants auxiliary electric systems knowledge.
340
F orms of Teaching
» Lectures
» Two hours per week.
» Exams
» Continuously: one writing exam, final exam (writing and oral
examination) and four short tests.
Classical Exam: writing and oral examination at the end of semester.
Results of three short tests are included.
» Exercises
» One hour weekly.
» Laboratory Work
» Two exercises, two hours duration of each:
1. Operation of power plant - island operation, power plant
synchronization on electric power system, generation of active and
reactive power
2. Generator unit operation - types of excitation (DC, brushless,
thyristor), generator response, transfer functions of exciter and
generator, time contants
» Three homeworks.
Grading System
T ype
Homeworks
Quizzes
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
50 %
50 %
50 %
50 %
Percent of
Grade
Exam
T hreshold
8%
12 %
30 %
40 %
10 %
Percent of
Grade
50 %
50 %
0%
8%
12 %
50 %
60 %
20 %
Comment:
Homeworks and short test results are admit in classical exam.
1. Power plants, classification and characteristics.
2. Tzpes of hydro power plants and main equipment.
3. Hydro turbines, types, operation, limits, selection. Hydro generator
selection.
4. Steam thermal power plants and main equipment.
5. Gas thermal power plants and main equipment.
6. Nuclear power plants tpes and main equipemnt.
7. Nuclear power plant operation and power changes.
8. exams
9. exams
10. Combined haet and power plants.
11. Wind power systems and grid connection.
12. Electrical one line diagram. Main operational characteristics and limits of
plant generator.
341
13. Generator connected to the grid and synchronization. Island mode of
operation.
14. Onsite power systems and plants auxiliary. Emergency power supply.
15. Grid code
Literature
H. Požar (1992). Osnove
energetike I, Školska knjiga
energetike II, Školska knjiga
energetike III, Školska knjiga
D. F eretić, N. Čavlina, N.
Debrecin (1995). Nuklearne
elektrane, Školska knjiga
M.M. El-Wakil (1984).
Powerplant Technology,
McGraw Hill
J.S. Gulliver, R.E.A. Arndt
(2001). Hydropower
Engineering Handbook,
McGraw Hill
A.J. Wood, B.F Wollenberg
(1996). Power Generation,
Operation, and Control, John
Wiley
Similar Courses
» Energy Power Plants, EPF L Lausanne
» Elektrische Energieversorgungssysteme, TU Munchen
» Energieübertragung und Kraftwerke, TU Wien
» Kraftverksteknik, Lund University
342
Course Description
The concept of the probability space and the random variables is introduced. The
basic discrete and continuous random variables are analized, as well as random
vectors. The foundations of the sample theory, the estimation theory and the
statistical tests are given. Stochastic processes are discussed, in particular Poisson
and similar processes.
Study Programmes
semester, 2nd year)
Learning Outcomes
Study Hours
Lecturers
Exercises
60
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
mandatory.
45
55
70
85
Prerequisites
Mathematics 2
Prerequisites for
Digital Video
Information Theory
1. Compute the probability of given event and the characteristic related to
concrete example.
2. Recognize a characteristic distribution.
3. Manipulate with discrete and continuous random variables.
4. Manipulate with discrete and continuous random vectors.
5. Estimate the parameters of various distributions.
6. Apply testing hypotheses using the learned statistical tests.
EP E
EC E
EL
Doc. dr. sc. Domagoj
Kovačević
Dr. sc. Snježana Lubura
Petar Bakić, mag. math.
Lenka Mihoković, mag. math.
Stjepan Šebek, mag. math.
C EA
C OM
Lecturers
Prof. dr. sc. Luka Korkut
Dr. sc. Mario Bukal
EEIT
L1
WT
Doc. dr. sc.
Tomislav Burić
E-learning Level
IP
Izv. prof. dr. sc.
Mario Krnić
L0
SEIS
Izv. prof. dr. sc.
Andrea AglićAljinović
English Level
CE
Doc. dr. sc.
Igor Velčić
Izv. prof. dr. sc.
Ilko Brnetić
5
CS
Prof. dr. sc.
Neven Elezović
ECT S Credits
TI
Lecturers in Charge
E/C
86539
343
Students are trained to calculate the probabilities of events, characteristics of
events related to concrete examples and defined random variables. F or given
samples of empiric data student are capable to estimate the different parameters
of various distributions and test different kind of hypotheses. Students are
introduced to basics of stochastic processes.
F orms of Teaching
» Lectures
» Exams
week of classes.
» Exercises
» The brief assessments will be held during the auditory exercises (up
to 1 hour per week).
» Consultations
with students.
Grading System
T ype
Quizzes
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
20 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
20 %
0%
80 %
Comment:
1. Sample space and events. Probability. F inite probability spaces. F inite
equiprobable spaces.
2. Infinite sample spaces. Uncountable uniform spaces.
3. Conditional probability and independance. Bayes formula.
4. Discrete random variables. F unctions of discrete random variables.
Expectation, moments and generating function.
Discrete random vectors. Marginal distributions.
5. Correlation coeficient. Covariance. Geometric distribution. Binomial
distribution.
6. Poisson distribution. Continuous random variables. Density and
distribution functions.
7. F unctions of continuous random variable. Exponential distribution.
8. Mid-term exam.
9. Normal distribution.
344
10. Continuous random vectors. Marginal distributions. F unctions of random
vectors. Conditional density and expectation.
11. Law of large numbers. Central limit theorem. Gamma and beta functions.
Gamma distribution. T-distribution. F -distribution.
12. Basics of sample theory. Mean and median. Random sample of normal
random variable. Point estimations. Maximum likelihood criterion.
Interval estimations. Estimation of parametars of binomial distribution.
13. Interval estimation of expectation. Interval estimation of variance.
Confidance interval of binomial random variable. Kind of errors and test
power. U-test. T-test. Theoretical and empirical distribution. Hi2 test.
14. Stochastic processes. F inite-dimensional distributions. Classification of
processes. Stationarity. Independence. Correlation functions. Poisson
process. Construction of Poisson process. Sum and decomposition of
Poissonovih processes. Birth and death process.
15. F inal exam.
Literature
N. Elezović (2007).
VJEROJATNOST I
STATISTIKA, Diskretna
vjerojatnost, Element,
Zagreb
VJEROJATNOST I
STATISTIKA, Slučajne
varijable, Element, Zagreb
VJEROJATNOST I
STATISTIKA, Matematička
statistika, Stohastički procesi,
Element, Zagreb
Ž. Pauše (1993). Uvod u
matematičku statistiku, Šk.
knjiga, Zagreb
Ž. Pauše (1990). Riješeni
primjeri i zadaci iz teorije
vjerojatnosti i statistike, Šk.
knjiga, Zagreb
Similar Courses
» Wahrscheinlichskeitrechung und Statistik, ETH Zurich
345
Electrical measurement of nonelectric physical values. Gauges, registering meters
and transducers. Standard voltage and current outputs. Measuring loop.
Transducers for displacement, angle, pressure, vibration, force, torque, velocity,
rotating speed, acceleration, level, flow, analytical parameters, temperature and
radiation. Infra-red measuring techniques. Transducers for Ex zone. NAMUR
output. Non-conventional measurements of electrical values (Rogowsky coil,
optical measuring transformers). Intelligent measuring transducers. HART
protocol. Local sensor networks and field busses. Computerized measuring
systems.
E-learning Level
L1
Study Hours
Lecturers
30
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
60
70
80
90
E/C
L1
C OM
EEIT
English Level
Prerequisites
Energy Technology
EP E
Course Description
4
EC E
Prof. dr. sc.
Tomislav Tomiša
ECT S Credits
EL
Lecturer in Charge
35244
C EA
Process Measurements and Diagnostic in Power
Plants
WT
Study Programmes
SEIS
IP
Technology (Module) (elective courses, 6th semester, 3rd year) (currently not given)
Learning Outcomes
CS
Explain elements of measuring chaine
Distinguish measuring transducers of non-electric values
Describe non-conventional transducers of electric values
Describe infrared measuring technology
Identify inteiligent measuring transducers
Explain computerized measuring systems
TI
1.
2.
3.
4.
5.
6.
CE
Understanding the principles of measuring non-electrical quantities.
Understanding technical documentation of measuring circuits in process
measurement systems. Identifying the elements of measurement chains - sensors,
transducers, indicators and recorders. Differentiation of instruments for measuring
and diagnosing in power plants. Understanding computer supported
measurement systems.
F orms of Teaching
» Lectures
» Lectures supported by Power Point presentations.
346
» Experiments
» Demonstration of how to use specific measuring equipment.
Grading System
T ype
Homeworks
Attendance
Exam: Written
T hreshold
Percent of
Grade
50 %
50 %
50 %
50 %
20 %
10 %
30 %
40 %
Exam
T hreshold
Percent of
Grade
50 %
50 %
0%
20 %
10 %
50 %
70 %
1. Gauges, registering meters and measuring transducers of non-electric
values. Standard output voltage and current. Measuring loop 4-20 mA.
2. Temperature measurement: RTD - Resistant Temperature Detectors (Pt
100, Pt 1000), thermocouple sensors, semiconductor sensors, pyrometers.
Measurements of motor winding temperature, bearing temperature and
cooling medium temperature.
3. Infra-red measurements: IR thermometers, thermovision. Remote
temperature measurement, defectoscoping of contact resistance, thermoinsulation damages.
4. Pressure transducers. Measurement of hydrostatic pressure, hydraulic oil
pressure, compressed air pressure, cooling hydrogen pressure, SF 6 pressure.
5. F low measurement of air, steam and technical mediums. Turbine flowmeters, differential pressure flow-meters, Corioliss mass flow meters,
inductive flow-meters, ultrasonic flow meters, Vortex flow meters.
Measurements of water level, fuel level, technical mediums. F loats
transmitters, hydrostatic transmitters, capacitive transmitters, ultrasonic
and radar transmitters
6. Measurements of water level, fuel level, technical mediums. F loats
transmitters, hydrostatic transmitters, capacitive transmitters, ultrasonic
and radar transmitters.
7. Linear displacement measurement: LVDT (Linear Variable Differential
Transformer), magnetostrictive transducers, non-contact transducers
(capacitive, ultrasonic and laser), draw wire transducers. Measurement of
turbine primary mover. Angle measurement: potentiometric and capacitive
transducers. Achieving position of turbine butterfly–valve.
8. Rotating speed measurement: tahogegeratos, optical tahometers.
Asynchronous motor start-up testing.
9. Measurement of acceleration, shock and vibration: accelerometers, vibration
sensors. Bearing vibration diagnostic. Measuring transducers of torque and
shaft strain. F orce transducers. Measurements of strain force in overhead
line rope.
10. Measurements of water quality parameters: pH, redox potential,
conductivity, dissolved oxygen, turbidity, nitrate, chloride, chlorophyll.
Steam-generator water treatment. Waste water analyses
11. Meteorological measurements: wind speed and direction, barometric
pressure, relative humidity, solar radiation, rainfall.
12. Radiation measurements: ionizating radiation detectors. Monitoring of
nuclear plants.
13. Measuring transducers for special purposes: Ex-i (intrinsically safe),
transducers for explosion zones. Transducers with NAMUR output.
347
14. Non-conventional measurements of electrical values: Rogowsky coil,
optical measuring transformers.
15. Inteligent sensors. HART protocol. Local sensor networks and field busses
(Profibus DP, CAN-bus, M-bus, MOD-bus, LON-bus). Computerized
measuring systems.
Literature
James W. Dally, William F .
Riley, Kenneth G. Mcconnell
(1993). Instrumentation for
engineering measuraments,
JOHN WILEY & SONS,
INC.
Grady C. Carroll (1962).
Industrial process measuring
instruments, MCGRAWHILL PUBLISHING
COMPANY
P. H. Mansfield (1973).
Electrical transducers for
industrial measurement,
BUTTERWORTH & CO.
William David Cooper,
Albert D. Helfrick (1970).
Electronic instrumentation
and measurement techniques,
PRENTICE-HALL, INC.
Ivan Piljac (2010). Senzori
fizikalnih veličina i
elektroanalitičke metode,
MEDIAPRINT TISKARA
HRASTIĆ D.O.O.
Similar Courses
» Sensors and Instrumentation, Manchester University and UMIST
» Instrumentation and Sensors, NU Singapore
» Messsystem- und Sensortechnik (EI7723), TU Munchen
» Physical Sensors, Transducers and Instrumentation, Carnegie Mellon
University
» Elektronische Messtechnik, RWTH Aachen
» Messen nichtelektrischer Größen - MT II, TU Berlin
» Industrial Measurement Systems for Control (MIE 041), Lund University
348
ECT S Credits
2
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
9
9
E/C
Lecturer in Charge
127101
EEIT
Programing for the Robot Operating System
C OM
C EA
dr. sc.
Damjan Miklić
Course Description
WT
EL
EC E
EP E
High complexity of tasks that the modern mobile robots are facing calls for using a
programming infrastructure which enables efficient integration of independently
developed subsystems into a single system enabling autonomous robot operation.
The Robot Operating System (ROS) offers an environment for developing
modular control software, a communication infrastructure to connect the software
components and an open source library of implemented algorithms. In the last five
years ROS has become the standard for robot control in the academic community
and its influence is spreading also in the industry. In the scope of this course we
shall cover the practical development of software modules in the ROS
environment and their integration into a completely functional system for
autonomous robot control.
Study Programmes
TI
CS
CE
SEIS
IP
year)
3rd year)
349
Learning Outcomes
1.
2.
3.
4.
Use basic Linux commands.
Use Linux tools to install additional software.
Solve simple problems using the Python programming language.
Explain the role of the Robot Operating System in autonomous robot
control.
5. Produce a ROS node: an application capable of exchanging data over the
ROS middleware.
6. Apply the ROS navigation stack to enable autonomous mobile robot
navigation.
Basic knowledge on using the Linux operating system and programming in the
Python programming language. Basic understanding o the architecture and
implementation of the Robot Operating System (ROS). Capability to implement
ROS nodes: applications that communicat through the ROS middleware. Basic
knowledge about solving the mobile robot autonomous navigation problem and
configuring the ROS navigation stack.
F orms of Teaching
» Lectures
» Interactive lectures with examples and practical assignments.
» Laboratory Work
» Assignments integrated into lectures.
» Project assignment on the robot.
Grading System
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
1. Linux operating system basics.
2. Python programming language basics.
3. Introduction to the Robot Operating System (ROS). Programming ROS
nodes (part 1).
4. Programming ROS nodes (part 2).
5. The ROS navigation stack: parts 1 and 2.
6. Advanced ROS programming topics. F inal project: controllling an
autonomous robot in ROS.
7. No activity.
8. No activity.
9. No activity.
10. No activity.
11. No activity.
12. No activity.
13. No activity.
14. No activity.
350
15. No activity.
Literature
J. M. O'Kane (2013). A Gentle Introduction to ROS, CreateSpace
Similar Courses
» Robot programming laboratory (CS225B), Stanford
» Advanced robot control systems, Katholieke Universiteit Leuven
» CoTeSys-ROS F all School on Cognition-enabled Mobile Manipulation, TU
Munchen
351
Learning Outcomes
1.
2.
3.
4.
5.
6.
Explain how computer stores data
Apply basic principles of software design
Design andimplement, test, and debug simple programs
Use arrays, selections, loops and functions
Describe the mechanics of fucntion calls and parameter passing.
Compose computer programs with sequential and direct access binary and
text files
7. Use pointers and memory allocation
Students are enabled to develop simpler procedural programs in C. Students will
be capable to design a simpler algorithm after a given problem definition, to
describe it in a procedural programming language, to test it and document. They
should be able to locate and correct logical errors.
Ivan Budišćak, dipl. ing.
Nenad Katanić, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
62.5
75
87.5
Prerequisites for
Algorithms and Data
Structures
Audio and Computers
Human F actors in Computing
Introduction to Theoretical
Computer Science
LabVIEW
F orms of Teaching
» Lectures
» 15 weeks, which accounts for two weeks for intermediate exams.
There are four hours of lectures per week, divided in two terms of
two hours (2+2).
» Exams
» There are two exams: intermediate exam and final exam.
» Laboratory Work
» Two to three cycles of laboratory exercises are organised and
EEIT
C OM
Lecturers
Izv. prof. dr. sc. Boris Vrdoljak
Doc. dr. sc. Ljiljana Brkić
Doc. dr. sc. Mirjana DomazetLošo
Doc. dr. sc. Igor Mekterović
Doc. dr. sc. Boris Milašinović
Doc. dr. sc. Damir Pintar
Doc. dr. sc. Marko Subašić
C EA
60
15
EP E
Study Hours
Lecturers
EC E
Study Programmes
L1
EL
Basic concepts of procedural programming are introduced. Data structures, control
structures, functions, arrays and files are explained. Basic concepts of software
engineering are explained, such as problem algorithmization, subtasking,
documenting and software development cycle.
E-learning Level
WT
Course Description
L0
IP
Doc. dr. sc.
Slaven Zakošek
English Level
352
SEIS
Izv. prof. dr. sc.
Gordan Gledec
6
CE
Prof. dr. sc.
Vedran Mornar
ECT S Credits
CS
Lecturers in Charge
E/C
19676
Programming and Software Engineering
TI
performed under control of an assistant.
Grading System
T ype
Quizzes
Exam: Written
T hreshold
Percent of
Grade
5%
0%
0%
15 %
20 %
15 %
25 %
40 %
Exam
T hreshold
Percent of
Grade
5%
0%
0%
20 %
0%
0%
80 %
1. Definition of algorithm. Definition of variable. Variable types. Associative
and arithmetic operators. Elementary input and output.
2. Compilation of source code. Debugging. Preprocessor statements. Logical
operators and expressions.
3. Simple selection. Double selection. Multiple selection and case.
4. While loop. Until loop.
5. F or loop. One dimensional array.
6. Two dimensional array. Multidimensional arrays.
7. Recapitulation of program structures and their presentation in pseudocode.
8. F unction. Call by value. Pointer.
9. Call by reference. Program modules and global variables.
10. One dimensional array as function argument.
Twodimensional array as function argument.
11. Macro statements. Character string. Built-in arithmetic functions. Random
numbers.
12. Other built-in funcions. Built-in functions on character strings. Proprietary
functions on character strings. Bit operators and expressions. Standard
input.
13. Standard output. Data files and classification. Redirection of input and
output. Reading from formatted files.
14. Writing into formatted files. Complex data types. Writing into
unformatted files. Reading from unformatted files. Direct access files.
15. Parameters from command line. Pointer arrays. Dynamic memory
allocation. Program documentation. Advanced examples with testing on
correctness.
Literature
Brian W. Kernighan, Dennis
Ritchie, Dennis M. Ritchie C
Programming Language,
Prentice Hall
Stephen Kochan (2004).
Programming in C 2004,
Sams
N. King, K.N. King (1996). C
Programming: A Modern
Approach, W. W. Norton &
Company
353
Similar Courses
» Introduction to Programming in C, University of California Berkeley
» Introduction to Computer Science I, UCLA
» Programming F undamentals, IEEE & ACM Computing Curricula
354
This is an introductory course to Haskell, an advanced purely-functional
programming language. F unctional programming languages allow for the
development of robust, concise programs in a short amount of time. The key
advantages are higher-order functions as an abstraction mechanism and an
advanced type system for safety and reusability. The course teaches basic
functional programming in Haskell and the basic functional programming
concepts. The course starts with language constructs and data types, moves to
higher-order functions and algebraic data types, and concludes with IO data
streams and monads. Students gain practical experience by solving numerous
programming tasks given during the lectures and as take-home assignments. The
goal of the course is not only to teach a new programming language, but also to
teach a new programming paradigm and a radically different and mathematically
sophisticated approach to programming.
L3
E-learning Level
L1
Study Hours
Lecturers
30
15
This course is not graded. To
pass the course students must
attend all lectures and
practical sessions and hand in
all assignments on time.
C EA
C OM
Grading
EEIT
English Level
EP E
Course Description
4
EC E
Doc. dr. sc.
Jan Šnajder
ECT S Credits
EL
Lecturer in Charge
E/C
127252
Programming in Haskell
WT
IP
Learning Outcomes
SEIS
Define the basic concepts of functional programming in Haskell
Explain the syntax and semantics of a Haskell program
Use Haskell to solve simple practical problems
Apply functional idioms and functional design patterns
Use available programming libraries to solve complex problems
Compare alternative Haskell programs to determine which are better
according to selected criteria
7. Design Haskell programs
TI
CS
CE
1.
2.
3.
4.
5.
6.
Students will learn the basic concepts of functional programming in Haskell,
know and understand the basics of syntax and semantics of Haskell, they will be
able to recognize and apply functional idioms and functional design patterns, use
Haskell to solve simple practical problems, find and use available programming
libraries to solve complex problems, compare alternative Haskell programs to
determine which are better according to selected criteria, and they will learn the
basics of software development in Haskell.
F orms of Teaching
» Lectures
» Three hours lecture per week for 15 weeks.
355
» Laboratory Work
» Each two-hour lecture is intertwined with one-hour practical
session.
» Students will receive homework programming assignments, which
they must demonstrate to the instructor or lab assistent.
Grading System
T ype
Exam
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
50 %
100 %
0%
0%
1. Introduction to functional programming. GHC compiler and other on-line
resources.
2. Basic language constructs. Tuples and lists.
3. Types and type classes.
4. Syntax of functions.
5. Recursive functions. Corecursive functions.
6. Higher-order functions 1.
7. Higher-order functions 2.
8. Custom data types 1.
9. Custom data types 2. Modules.
10. Custom data types 3. Standard library.
11. Input-output operations 1.
12. Input-output operations 2. Random number generator.
13. Monads and monadic programming 1.
14. Monads and monadic programming 2.
15. Strictness. Code documentation. Packages.
Literature
Miran Lipovača (2011).
Learn You a Haskell for Great
Good!: A Beginner's Guide,
No Starch Press
Graham Hutton (2007).
Progamming in Haskell,
Cambridge University Press
Bryan O'Sullivan, Don
Stewart, John Goerzen
(2008). Real World Haskell,
O'Reilly Media
Simon Thompson (1999).
Haskell: The Craft of
Functional Programming,
Addison Wesley
Paul Hudak (2000). The
Haskell School of Expression:
Learning Functional
Programming through
Multimedia, Cambridge
University Press
356
Similar Courses
» F unctional Programming, Chalmers University
» F unctional Programming, Stanford
» F unctional Programming, Oxford
» F unctional Programming, Lund University
357
Study Programmes
» Information Processing -> Computing (Module) (specialization courses, 5th
semester, 3rd year)
» Computer Science -> Computing (Module) (specialization courses, 5th semester,
3rd year)
45
15
15
EEIT
Study Hours
Lecturers
Exercises
C OM
L1
C EA
Lecturers
EP E
Zvonimir Pavlić, mag. ing.
comp.
EC E
The processes of incremental hierarchical translation of end-user languages, highlevel languages, and languages of virtual machines into target language of given
computer system are studied. The techniques and principles of language
translation processes in modern pervasive, ubiquitous, and invisible distributed
systems are described. Brief survey and history of programming languages and
language translators are given. Language translation is explained through basic
processes of source program analysis and target program synthesis. Major phases
of analysis (lexical, syntax, and semantic analysis) and synthesis (intermediate code
generation, optimization, and target code generation) are included. Run-time and
load-time support for program execution is presented. Language translator
generators are studied.
E-learning Level
EL
Course Description
L1
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
75
88
Prerequisites
Computer Science
WT
Doc. dr. sc.
Ante Đerek
English Level
IP
Doc. dr. sc.
Dejan Škvorc
4
SEIS
Prof. dr. sc.
Siniša Srbljić
ECT S Credits
CE
Lecturers in Charge
E/C
86504
Programming Language Translation
CS
Learning Outcomes
TI
1. Breakdown the design of a computer system into problem analysis phase
and solution synthesis phase
2. Describe lexical, syntax, and semantic properties of a programming
language using formal grammar
3. Select optimal formal grammar for formal description of a programming
language
4. Select optimal parsing technique for programming language translation
5. Design and implement a compiler from formal specification of a
programming language
6. Design of an efficient language translation process with respect to
processor resources and memory hierarchy
358
The course prepares students for application of the analysis-synthesis design
model, which is widely used in software engineering. Acquired knowledge of
algorithms, data structures, and translation methods are applicable in a wide
range of computer applications. Students will be able to build efficient software
products by optimally exploiting language translators and other software tools.
F urthermore, students will be able to design and build their own language
translators for end-user languages.
F orms of Teaching
» Lectures
» Lecturer-driven classroom presentations, examples of practical
application of formal languages, automata, and grammars during
the compiler construction
» Exams
» Two written exams
» Exercises
» Lecturer-driven classroom problem solving, preparation for written
exams
» Laboratory Work
» Compiler construction for a simplified C-like programming
language. Individual work or work in a small team comprised of
fellow students. Online submission and evaluation of student work.
» Consultations
» Individual office hours with lecturers and assistants are organized on
student's request.
Grading System
T ype
Class participation
Exam: Written
T hreshold
Percent of
Grade
50 %
0%
0%
0%
40 %
5%
30 %
30 %
Exam
T hreshold
Percent of
Grade
50 %
0%
0%
0%
0%
50 %
100 %
Comment:
Continuous Assessment: Min (Mid Term Exam: Written + F inal Exam: Written +
Lecture attendance and oral examination in classroom) = 50 %
1. Basic phases of translation process: analysis and synthesis; Source program
analysis: lexical, syntax, and semantic analysis; ([1], pp. 1-12) Target
program synthesis: intermediate code generation, optimization, and target
code generation; ([1], pp. 13-19)
2. Error handling during translation; Performance evaluation of translation
process; Classification of language translators; ([1], pp. 19-31) Lexical
analysis; Role and data structure of lexical analyzer; Interaction with syntax
analyzer; Ambiguity in lexical analysis; Transliteration, tokens, lexical
errors, and error-recovery methods; ([1], pp. 44-55)
359
3. Lexical analyzer generators; Program Lex; ([1], pp. 56-70) Syntax analysis;
Role and data structure of syntax analyzer; Languages for syntax rules
definition; Simple parsing techniques: CO-NO table-based parsing; ([1],
pp. 71-84) Exercises: lexical analysis;
4. Top-down parsing; S, Q, and LL(1) grammar; SELECTION sets finding; ([1],
pp. 84-103) SELECTION sets finding (continuation); Adjustment of
productions to LL(1)-grammar; Error handling; Bottom-up parsing; ([1], pp.
103-121)
5. Bottom-up parsing techniques: Shift-Identify parsing, Shift-Reduce
parsing, and operator-precedence parsing; ([1], pp. 121-137) LR parsing; ([1],
pp. 138-147)
6. LR parsing (continuation); Parser generators; Program Yacc; Semantic
analysis; Role and formal models of semantic analyzer; Operations of
semantic analyzer; ([1], pp. 147-166) Exercises: syntax analysis;
7. Operations of semantic analyzer (continuation); Syntax-directed semantic
analysis: attribute translation grammar; ([1], pp. 167-180) L-attribute
translation grammar; Pushdown automata for L-attribute translation
grammar; ([1], pp. 180-190)
8. F irst mid term exam: lexical, syntax, and semantic analysis;
9. Pushdown automata for L-attribute translation grammar (continuation);
Recursive descent method for L-attribute translation grammar; Type
system; ([1], pp. 190-200) Type checking; Type equivalence; Run-time
support for target program execution; ([1], pp. 200-223)
10. Abstract data structures of source program and internal storage structures
of target program; Program flow execution based on procedures; Memory
management; ([1], pp. 223-233) Non-local names access; ([1], pp. 233-242)
11. Input/output parameter passing; Intermediate code generation; Levels and
forms of intermediate code; ([1], pp. 243-256) Levels and forms of
intermediate code (continuation); Syntax-directed intermediate code
generation; Target program generation; Target program generator
structure; ([1], pp. 256-265)
12. Target program generator structure (continuation); ([1], pp. 265-276)
Target program generator algorithms; Target program generator
generators; ([1], pp. 276-285) Second mid term exam: lexical analysis,
syntax analysis;
13. Preparation of target program for execution; Load-and-go language
translators; Absolute and relocatable code generators; Generators of
separate files of relocatable machine code; Linkers and loaders;
Optimization; Program-execution analysis; ([1], pp. 286-297) Programexecution analysis (continuation); ([1], pp. 297-305)
14. Machine-dependent and machine-independent optimization; Peephole
optimization; Brief survey of other optimization methods; ([1], pp. 305317) Exercises: semantic analysis, target program generation, optimization;
15. F inal exam: whole course matter;
360
Literature
S. Srbljić (2007). Prevođenje
programskih jezika, Element
Zagreb
D. Grune, H. E. Bal, C. J. H.
Jacobs, K. G. Langendoen
(2000). Modern Compiler
Design, Wiley
A. V. Aho, R. Sethi, J. D.
Ullman (1986). Compilers:
Principles, Techniques, and
Tools, Addison-Wesley
K. Cooper, L. Torczon
(2003). Engineering a
Compiler, Morgan
Kaufmann
S. S. Muchnick (1997).
Advanced Compiler Design
and Implementation, Morgan
Kaufmann
Algorithms for Compiler
Design O. G. Kakde Charles
River Media 2002
Similar Courses
» CS: PL1-PL5, PL8-PL11; CE: ESY, PRF , IEEE & ACM Computing Curricula
» Programming Languages and Compilers, University of California Berkeley
» Uebersetzerbau (Compiler Design), TU Munchen
» Compiler Design I, ETH Zurich
» Computer Language Engineering, MIT
» Compilerbau, TU Munchen
» Compilers, Oxford
» Compilers, Stanford
» Compiler construction, TU Delft
» Compiler design, NU Singapore
361
The course gives an overview of programming paradigms. It deals with the
concepts common in various imperative programming languages. F urthermore,
object-oriented programming is thaught. The fundamentals of declarative
programming paradigm and its use in modern programming languages are
illustrated as well. The final course topic covers the use of parallelism.
Study Programmes
» Computer Science -> Computing (Module) (elective courses, 6th semester, 3rd
year)
E-learning Level
L2
Study Hours
Lecturers
45
15
Grading
Acceptable (2)
50
Good (3)
65
Very Good (4)
80
Excellent (5)
90
According to the gathered
points on the project,
homework, exams and the oral
exam, grade is formed.
Prerequisites
Databases
C EA
C OM
Tomislav Jagušt, dipl. ing.
EEIT
L1
EP E
Course Description
English Level
EC E
Doc. dr. sc.
Ivica Botički
4
EL
Prof. dr. sc.
Vedran Mornar
ECT S Credits
WT
Lecturers in Charge
E/C
34282
Programming Paradigms and Languages
IP
SEIS
Learning Outcomes
TI
CS
CE
1. Distinguish between different programming paradigms
2. Choose an adequate programming paradigm in solving specific software
engineering problems
3. Apply at least one language from imperative, object-oriented and
declarative paradigm
4. Classify programming languages according to the paradigms they belong
to
5. Recognize the concepts of same kind from different programming
languages and paradigms
6. Employ adequate naming and code organization conventions
Students will get to know programming concepts commom to different
programming languages, which will facilitate further learning of new languages.
They will consolidate their knowledge of object-oriented programming paradigm
and be introduced to functional programming. They will also gain practical
knowledge of programming in a variety of programming languages.
362
F orms of Teaching
» Lectures
» Course lectures through 13 weeks.
» Exams
» The knowledge will be tested with a mid-term exam and a final
exam. During the semester, homeworks will be assigned.
» Laboratory Work
» In the laboratory excercises students will work on their own
programming solutions and demonstrate their correctness.
» Experiments
» During the lectures, the work in various programming languages
will be demonstrated to students in an interactive manner.
» Demonstration exercises will demonstrate the use of technology to
complete the laboratory exercises and to illustrate real practical use.
» Consultations
» During the consultation hours the students will be able to
supplement their knowledge on all course topics.
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
50 %
5%
15 %
15 %
15 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
50 %
5%
0%
30 %
15 %
Comment:
In order to get the pass grade, students have to get at least 7.5 points on the oral
exam.
1. Abstract machines. Interpreters. Compilers. Expressiveness of
programming languages.
2. Names and environments. Blocks. Static and dynamic scope. Static and
dynamic memory management. Scope rules implementation.
3. Control structures. Structured programming. Tail recursion.
4. Procedures. Higher-order functions. Exceptions.
5. Data types. Static and dynamic type checking. Complex types. Type
equivalence. Polymorphism. Type inference. Dangling references. Garbage
collectors. Abstract data types. Information hiding. Modules.
6. Demonstration lecture: writing program code.
7. Exam preparation hours.
8. Exams.
9. Exams.
363
10. The object-oriented programming paradigm. Dynamic method lookup.
Single and multiple inheritance. Dynamic method dispatch. Polymorphism
in object-oriented programming paradigm. Generics. Covariant and
contravariant overloading.
11. Demonstration lecture: application development in an object-oriented
programming language.
12. The functional paradigm. Computations without state. Evaluation
strategies. Pattern matching. The basics of lambda calculus.
13. Demonstration lecture: programming in a functional programming
language.
14. Logic paradigm. Deduction as computation. Theory of unification. Logic
programming with constraints.
15. Paralellism. Historical overview of programming languages and
paradigms.
Literature
M. Gabrielli, S. Martini
(2010). Programming
Languages: Principles and
Paradigms, Springer
S. McConnell (2004). Code
Complete: A Practical
Handbook of Software
Construction, 2/e, MS Press
D. P. F riedman, M. Wand,
C. T. Haynes (2001).
Essentials of Programming
Languages, 2/e, MIT Press
Tomas Petricek, Jon Skeet
(2010). Real World Functional
Programming: With Examples
in F# and C#, Manning
Publications
B. Tucker, R. E. Noonan
(2001). Programming
Languages: Principles and
Paradigms, McGraw-Hill
Similar Courses
» Programming Languages and Paradigms, McGill University
» Concepts in Programming Languages, Cambridge
» Programming Languages, IEEE & ACM Computing Curricula
» Programming Languages & Software Engineering, NU Singapore
364
Learning Outcomes
1.
2.
3.
4.
5.
6.
Define project goals
Construct project team
Develop project task
Demonstrate results of project task
Analyze finished project task
Identify problems during development of the project task
L3
E-learning Level
L1
Prerequisites
Energy Technology
Seminar
Seminar
CE
SEIS
IP
Students participate in team work on research and development project. While
participating they should develop and improve their skills of collecting and
evaluating the literature, participate in the planning, execution and monitoring of
the project, learn more about teamwork, and apply appropriate technology for
given task, implement their own solution and integrate it with solutions from
other students in the final result. They also learn how to present the final product.
Grading System
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
Seminar/Project
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
Prerequisites for
BSc Thesis
T ype
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
Team leader, student,
distributes points that
mentor, teacher, assigns to the
whole group. Points can be
awarded only to students who
actively participated in
project.
EEIT
Study Hours
EP E
English Level
EC E
Study Programmes
6
EL
Promoting cooperation between students and teachers in a team environment
while creating practical solutions to specific problem. Students work in groups of
6 to 8 students, under the guidance of teaching staff who suggests the topic.
Project requires finding the necessary literature, analysis of similar problems and
solutions, identification of project requirements, definition of technical objectives,
planning and time management, creation of alternative solutions, decision
making, solution implementation, writing technical documentation and
presentation.
ECT S Credits
WT
Course Description
E/C
37831
Project
Mentor assignment
Project team forming
Work on project
Work on project
Work on project
Project plan submission. Work on project.
Work on project
Work on project
Work on project
365
10.
11.
12.
13.
14.
15.
Work on project
F inalization of the project
Submission of final work
Project presentation
Project evaluation
Project evaluation
366
Learning Outcomes
1.
2.
3.
4.
5.
6.
L3
E-learning Level
L1
Prerequisites
Seminar
Seminar
Signals and Systems
CE
SEIS
IP
Grading System
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
Seminar/Project
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
Prerequisites for
BSc Thesis
T ype
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
EP E
English Level
EC E
Study Programmes
6
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37832
Project
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
367
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
368
Learning Outcomes
E-learning Level
L1
Prerequisites
Electronics 1
Seminar
Seminar
Prerequisites for
BSc Thesis
Grading System
Seminar/Project
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
T ype
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
CE
IP
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
SEIS
1.
2.
3.
4.
5.
6.
L3
EP E
English Level
EC E
Study Programmes
6
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37833
Project
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
369
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
370
Learning Outcomes
1.
2.
3.
4.
5.
6.
L3
E-learning Level
L1
Prerequisites
Electronics 1
Seminar
Seminar
CE
SEIS
IP
Grading System
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
Seminar/Project
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
Prerequisites for
BSc Thesis
T ype
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
EP E
English Level
EC E
Study Programmes
6
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37834
Project
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
371
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
372
Learning Outcomes
E-learning Level
L1
Prerequisites
Mathematics 3 - C
Mathematics 3 - EE
Seminar
Seminar
Prerequisites for
BSc Thesis
Grading System
Seminar/Project
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
T ype
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
CE
IP
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
SEIS
1.
2.
3.
4.
5.
6.
L3
EP E
English Level
EC E
Study Programmes
6
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37835
Project
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
373
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
374
Technologies for public mobile networks. Global System for Mobile
communications (GSM) architecture. Components of Base Station System (BSS)
and Core Network (CN), interfaces between functional entities. Technical
parameters of GSM network. Call control and mobility management,
identification of mobile subscriber and equipment, security. Basic and teleservices
in GSM network. High Speed Circuit Switched Data (HSCSD). General Packet
Radio Services (GPRS). Characteristics of Enhanced Data rates for Global
Evolution (EDGE) architecture (2,5G), providing third generation 3G services.
Universal Mobile Telecommunication System (UMTS) network architecture,
UMTS features, domains, network nodes, and interfaces. Infrastructure for
interconnection two or more network operators, roaming exchange.
E-learning Level
L1
Study Hours
Lecturers
30
15
C OM
T eaching Assistant
Damjan Katušić, mag. ing.
EEIT
L1
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
70
Excellent (5)
85
All laboratory assignements
should be completed
succefully.
Prerequisites
Information Theory
C EA
Course Description
English Level
EP E
Prof. dr. sc.
Tomislav Kos
4
EC E
Prof. dr. sc.
Gordan Ježić
ECT S Credits
EL
Lecturers in Charge
E/C
34330
WT
Study Programmes
CS
CE
SEIS
IP
3rd year)
year)
TI
Learning Outcomes
1.
2.
3.
4.
5.
6.
7.
8.
Identify processes in the public mobile network
Analyze call establishment procedure
Describe public mobile network architecure 2G, 3G and 4G
Relate knowledge of mobile and communication networks
Explain service provision procedures in mobile networks
Recognize technologies of mobile networks
Define concept, architecture and organisation of mobile networks
Apply knowledge about mobile networks and protocols
375
Students will gain basic knowledge about 2G, 2.5G and 3G mobile systems. They
will be able to understand the concepts, architectures and technologies used in the
public mobile networks. Students will have practical skills to model and analyze
mobile networks by using software tools.
F orms of Teaching
» Lectures
on the web.
» Exams
» Laboratory Work
» Laboratory assignments that include building mobile network
models, defining communication and system parameters, simulation
and emulation of different usage scenarios, and measurement of
network traffic.
» Selected network models implemented using SEA (System
Environment Architecture) emulator are demosntrated during
lectures.
» Consultations
» Regular consultations hours
» Literature search on mobile networks. Building software
environment for mobile network design and anslysis.
» Network modelling, simulation and emulation using mobile
network emulator SEA.
Grading System
T ype
Homeworks
Class participation
Attendance
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
15 %
10 %
5%
5%
30 %
35 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
15 %
10 %
5%
5%
0%
65 %
Comment:
1. Place of public mobile network in the global network for providing
telecommunication services. Classification of technologies for public
mobile network – current state. Mobile network evolution, Global System
for Mobile Communications (GSM) development, GSM norms.
376
2. Architecture of GSM network: mobile terminal, radio access network, core
network (CN), media gateway. Components of Base Station System (BSS),
interfaces between functional entities. GSM protocols.
3. Technical parameters of GSM network, physical and logical channels,
frequency bands for uplink and downlink, radio channels, time division
multiple access (TDMA), frame structure.
4. Control and data logical channel, mapping logical channel onto physical
channels. F orward error correction for data and control channels. Signalling.
F rame organisation hierarchy.okvira.
5. GSM emission spectral requirements. Base and mobile station power
control. Discontinuous transmission concept.
6. Communication procedures and mobility management, identification of
mobile subscriber and terminal, security procedures. GSM terminals,
subscriber identity module (SIM). Procedures of attachment, deattachment
and registration of mobile station (MS) in GSM network. Call control,
locating, pagging, handover.
7. Traffic control and system capacity, congestion in core network. Models of
charging and billing. Addressing and roaming.
8. Services in GSM network. Quality of Service (QoS) parameters. GSMPro
and GSM-R versions.
9. High Speed Circuit Switched Data (HSCSD). General Packet Radio Services
(GPRS). Architecture of GPRS, protocols, and interfaces. Mobility
management states, routing area update, tunneling. Session management,
quality of service (QoS). EGPRS protocol stack. Characteristics of Enhanced
Data rates for Global Evolution (EDGE) architecture, service providing.
10. Development of 3G mobile systems. Universal Mobile Telecommunication
System (UMTS) network architecture. UMTS principles and features.
Network components: radio access network (RAN) radio subsystem, core
network, external network and units, interfaces. Protocol stack.
11. UMTS physical layer, frequency bands. Spreading spectrum and
modulation. WCDMA technology. Logical and physical channels.
12. Data link layer protocols. Mobility and session management. Radio
resource management. UMTS terminals, USIM module. Mobile terminal
registration on the network, call establishment procedure. UMTS services,
Quality of Service (QoS) levels. Security procedures. Infrastructure for
interconnection two or more network operators, roaming exchange.
13. F ourth generation of mobile networks (4G), LTE/SAE. Mobile virtual
network operator MVNO. Market of mobile network.
14. 15. -
Literature
UMTS Origins, Architecture
and the Standard Pierre
Lescuyer Springer Verlag
London Limited 2004
Mobile Radio
Communications Raymond
Steele, Lajos Hanzo John Wiley
& Sons Ltd 1999
Osnovne arhitekture mreža A.
Bažant, G. Gledec, Ž. Ilić, G.
Ježić, M. Kos, M. Kunštić, I.
Lovrek, Element, Zagreb
2004
Similar Courses
» Mobile Communications, TU Munchen
» Wireless and Mobile Network Architectures, Royal Instutute of Technology
Stockholm
377
Izv. prof. dr. sc.
Ivan Leniček
Doc. dr. sc.
Luka F erković
L2
E-learning Level
L1
Study Hours
Lecturers
30
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
63
76
89
EEIT
English Level
C OM
Prof. dr. sc.
Roman Malarić
3
EC E
EP E
Prof. dr. sc.
Damir Ilić
ECT S Credits
C EA
Lecturers in Charge
E/C
31490
Quality Management
EL
Doc. dr. sc.
Marko Jurčević
WT
Course Description
CE
SEIS
IP
Technology development and demonstration of quality. Principles of modern
business determined by globalisation and regional alliances. Standards and
necessity of standardisation. Recommendations, regulations, and laws. European
directives.Quality management. Control, planning and maintenance of the quality
system. User oriented processes. Research, development and marketing of the
products. Realisation the product and its conformity with technical
requirements.Quality system assessment; internal and external audits.
Improvements, corrective and preventive actions.Quality approval through
experiments. Population and sampling. Documentation and records. Technical
competence.Accreditation, certification, and validation procedures. Assessment and
formal recognition of results. CE mark.
CS
Study Programmes
TI
Computing (Study) (required courses - quality management, 3rd semester, 2nd year)
Learning Outcomes
1.
2.
3.
4.
5.
6.
Understand the term quality
Understand the standardization and the need for standardization
To apply the quality management in projects
To discriminate external from internal audit
To discrimiate accreditation from certification
To understand the need for CE sign
378
The course gives a good understanding about the standards in everyday life,
technical systems and quality management systems. The students will have basic
knowledge about the harmonization of the laws and technical regulations. By
analyzing the principles of quality management and the methods of testing of the
established systems, the students will be able and will have practical skills to
establish such systems to ensure the quality of products, whether they are goods
or services.
F orms of Teaching
» Lectures
» Lectures using powerpoint presentations
» Exams
» Mid-term exam and final exam.
» Consultations
» Additional explanations to students.
» Seminars
» Independent work on the default theme.
» Other
» Video presentations
Grading System
T ype
Quizzes
Seminar/Project
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
10 %
10 %
30 %
50 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
50 %
50 %
1. Introduction. Technology development and demonstration of quality.
2. Principles of modern business determined by globalisation and regional
alliances. Quality management.
3. Technical quality infrastructure.
4. Standards and necessity of standardisation. International standardisation
organizations.
5. Recommendations, regulations, and laws. European directives. Croatian
standards. CE mark.
6. Standards ISO 9000 and 14000.
7. Quality management. Control, planning and maintenance of the quality
system. Quality manual – basic document.
8. Mid-term exam.
9. Accreditation of laboratory and certification of products.
10. Total quality management (TQM).
11. EF QM, MB and other models for quality management.
12. Statistical methods in quality management.
13. Quality assurance for software.
379
14. Quality assurance in high education.
15. F inal exam.
Literature
ISO 9001:2000 Quality
management systems ?
Requirements ISO 2000
više autora (1996).
Inženjerski priručnik,
Školska knjiga
D.L. Goetsch, S. Davis
(2002). Quality Management,
Prentice Hall
Similar Courses
» Global Production Engineering / Quality Management II, TU Berlin
» 2503 Quality Management Essentials in Engineering, University of Toronto
380
Positioning methods using radio waves. Determination of lines of position by
measuring direction to the transmitter, distance to the transmitter, or distance
difference to the pair of transmitters. Direction finders - single and two channel
goniometers. Errors in radio goniometry. Determination of position in
multistation systems. Radionavigation. Hyperbolic systems Loran, Decca, Dectra,
Omega. Avionics navigation and landing systems NDB, VAR, VOR/DME, TACAN,
ILS, MLS. Satellite radio navigation. Global satellite navigation systems (GNSS)
Transit, GPS, GLONASS, Galileo. Safety demands and performance of navigation
systems. Applications of GNSS systems.
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C OM
T eaching Assistant
EEIT
English Level
50
61
75
90
Prerequisites
Physics 2
C EA
Course Description
4
EP E
Prof. dr. sc.
Tomislav Kos
ECT S Credits
EC E
Lecturer in Charge
E/C
34353
Radio Navigation
EL
WT
Study Programmes
IP
SEIS
Learning Outcomes
CS
CE
Define positioning methods
Identify measuring procedure of radio signal parameters
Analyze performance of navigation systems
Describe safety criteria in navigation
Relate knowledge about positioning systems errors
Recognize imperfections of satellite navigation systems
Recognize and understand the need for combining more navigation systems
TI
1.
2.
3.
4.
5.
6.
7.
The subject gives an overview of direction-finding and radionavigation systems,
and the knowledge of positioning methods. It analyses safety critical aspects in
us i ng navigation systems and the applications of user position-fix data in
navigation and communication systems.
F orms of Teaching
» Lectures
» lectures
» Exams
» mid-term exam
381
» Laboratory Work
» laboratory excersizes
» Consultations
» consultations
» visit to Crocontrol company
Grading System
T ype
Class participation
Attendance
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
50 %
0%
0%
0%
0%
15 %
5%
5%
30 %
45 %
Exam
T hreshold
Percent of
Grade
50 %
0%
0%
0%
15 %
5%
5%
0%
50 %
25 %
1. Direction-finding and positioning principles - goniometry
2. Direction-finding methods: amlitude, phasometrical and phase
3. Antennas for goniometry: loop, omnidirectional rod, and the combination
of loop and rod antenna
4. Antenna switching method, radiocompass, automatic locator
5. Positioning principles in in multistation systems
6. Safety aspects for navigation systems
7. Hyperbolic navigation systems: LORAN – A, LORAN – C, DECCA,
DECTRA, OMEGA
8. Avionics navigation systems: NDB, radio beacon, VAR
9. Avionics navigation systems: VOR, DME, TACAN
10. Landing systems: ILS, MLS
11. Satellite navigation systems: TRANSIT, GNSS
12. Satellite navigation systems: GPS
13. GLONASS, Galileo
14. Applications of user position-fix data in navigation and communication
systems
15. Augmentation of satellite navigation systems, differential GNSS, WAAS,
EGNOS, EUROF IX
Literature
B. Hofmann-Wellenhof, K.
Legat, M. Wieser (2003).
Navigation, Principles of
Positioning and Guidance,
Springer-Verlag
M.S Grewal, L.R. Weill, A.P.
Andrews (2001). Global
Positioning Systems, Inertial
Navigation and Integration,
John Willey&Sons, Inc.
M. Kayton, W.R. F ried
(1997). Avionics Navigation
Systems, John Wiley&Sons,
Inc.
382
Similar Courses
» Satellite Navigation, TU Munchen
» Navigation, ETH Zurich
» Integrated Navigation, Royal Instutute of Technology Stockholm
383
Robots and robot systems, review. Industrial robots and applications. Structure
and control of laboratory SCARA robot. Basic challenges in robot control (direct
and inverse kinematics). Introduction to virtual modeling of robot system
elements. Control by using Matlab and virtual models. Introduction to robot
vision. Intelligent object manipulation.
Study Programmes
Learning Outcomes
L2
E-learning Level
L1
Study Hours
Lecturers
15
30
Grading
Acceptable (2)
51
Good (3)
60
Very Good (4)
78
Excellent (5)
89
exam.
Prerequisites
Mathematics 2
C EA
C OM
Dr. sc. Matko Orsag
EEIT
English Level
EP E
Course Description
4
EC E
Prof. dr. sc.
Zdenko Kovačić
ECT S Credits
EL
Lecturer in Charge
E/C
34346
Robotics Practicum
WT
IP
CS
CE
SEIS
1. Differentiate the principles and versions of elements of industrial and
mobile robots
2. Explain basic types of robot control
3. Explain basic principles of robot programming
4. Explain basic image processing algorithms for robot vision
5. Explain algorithms for object recognition, localization and manipulation
6. Create a virtual robot model by using VRML
7. Synthesize with VRML robot model by using Matlab
8. Explain algorithms for solving direct and inverse kinematics
TI
Knowledge about principles and implementations of elements of industrial and
mobile robot systems. Understanding of robot control and programming.
Understanding of robot vision as a part of applied artificial intelligence. Work
with real robot systems and applications.
F orms of Teaching
» Lectures
» Organized in three thematic cycles (5+4+4 hours)
» Exercises
» Can be organized if students ask for it
» Laboratory Work
» Two project tasks:
384
• F or a given robot task one should design a robot using the LEGO
Mindstorm NXT system, build a virtual model and execute the
given task in virtual environment using Matlab
• F or a given robot task one should build a robot using the LEGO
Mindstorm NXT system, and write a program and prepare
demonstration of robot operation. The robot task assumes the use of
robot vision.
» Experiments
» In-class demonstration of examples of VRML programming.
» Consultations
» One hour weekly upom request
» Seminars
» Creation of virtual robot model and control of robot model from
Matlab
» Programming of real educational and industrial robots
Mastering of basic VRML programming
» Other
» A multimedia textbook in Croatian is available for students
Grading System
T ype
Seminar/Project
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
60 %
20 %
20 %
Exam
T hreshold
Percent of
Grade
0%
0%
60 %
0%
40 %
30 %
Comment:
The oral exam share is ±30%.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
Robots and robot systems - overview.
Industrial robots and applications.
Structure analysis of a robotic system with a SCARA robot.
Kinematics fundamentals - homogeneous coordinates. Robot tool position
and orientation.
Denavit-Hartenberg method of determining robot kinematic parameters.
Direct kinematics. Examples.
Inverse kinematics. Examples.
Midterm exam
Introduction to VRML. Virtual modeling of robotic systems using VRML.
Control of virtual robotic systems by using Matlab.
Computer tools for modeling, simulation and control of robot systems
Introduction to robot vision. Basic algorithms for image processing (noise
filtering, edge detection, Hough transformation).
Object recognition algorithms (chain code, pattern matching, calculation of
moments). Determination of position and orientation of object in the robot
workspace.
Introduction to intelligent object manipulation using robot vision.
385
15. F inal exam
Literature
Z. Kovačić, S. Bogdan, V.
Krajči (2002). Fundamentals
of robotics (in Croatian),
Graphis, Zagreb
R.J. Schilling (1990).
Fundamentals of robotics,
Prentice Hall
T. Šurina, M. Crnekovic (1990). Industrial robots (in Croatian),
Similar Courses
» E468 ROBOTICS & AUTOMATION, NU Singapore
» CS224 Robot Programming Laboratory, Stanford
» LEGO Robotics, MIT
» 16761: Introduction to Mobile Robotics, Carnegie Mellon University
386
Study Programmes
L1
Study Hours
Lecturers
30
15
Doc. dr. sc. Tomislav Hrkać
Ivan F ilković, mag. ing. comp.
Martin Soldić, mag. ing.
Grading
Acceptable (2)
50
Good (3)
62
Very Good (4)
75
Excellent (5)
88
Prerequisites
Algorithms and Data
Structures
C EA
C OM
Lecturer
EEIT
E-learning Level
EP E
Scripting languages represent a very different style of programming compared to
traditional programming languages. They are designed for "gluing" applications composing new programs by combining existing applications - components. That
approach leads to higher level of programming and more rapid application
development. In this course students explore the nature of scripting and their
application areas. The topics include shell programming, regular expressions,
Unix tools, and basics of Perl and Python programming.
L1
EC E
Course Description
English Level
EL
Izv. prof. dr. sc.
Siniša Šegvić
4
WT
Izv. prof. dr. sc.
Zoran Kalafatić
ECT S Credits
IP
Lecturers in Charge
E/C
86526
Scripting Languages
SEIS
CE
Learning Outcomes
CS
Define scripting languages and list their properties
Select programming language and tools suitable for given problem
Write and apply simple bash scripts
Write and apply simple Perl scripts
Write and apply simple Python programs
Analyze and adapt simple bash, Perl and Python scripts
TI
1.
2.
3.
4.
5.
6.
Students learn basic concepts of scripting language programming. They are
introduced to the basics of programming in several popular scripting languages
(UNIX shell, Perl, Phyton) and their typical application areas.
F orms of Teaching
» Lectures
» Lectures will be held in two cycles (7 + 6 weeks), 2 hours a week.
» Exams
387
» Midterm exam will be held after the first lecture cycle, the final
exam after the second lecture cycle. The students can also take
regular exams.
» Laboratory Work
» Laboratory exercises will be held in 3 cycles, each in extent of 5
hours.
» Writing scripts in bash shell, programming in Perl and Python,
debugging.
» Students independently solve program problems as a preparation
for laboratory exercises.
Grading System
T ype
T hreshold
Percent of
Grade
0%
0%
0%
30 %
30 %
40 %
Exam: Written
Exam
T hreshold
Percent of
Grade
0%
0%
30 %
0%
70 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Introduction – features of scripting languages, typical application areas.
Operating system interface.
Operating system shell programming.
Unix tools. Regular expressions.
Introduction to Perl programming language. Scalar data types.
Lists and arrays in Perl. Associative arrays.
Subroutines. F iles.
Midterm exam.
Regular expressions in Perl. Text processing. Command line programs.
Introduction to Python programming language. Basic data types.
String operations. String methods. Lists.
Dictionaries. F iles. Statements and programming constructs in Python.
F unctions, modules, namespaces.
Object-oriented programming in Python.
F inal exam.
Literature
Stephen Kochan, Patrick
Wood (2003). Unix Shell
Programming, 3rd edition,
Sams
Randal L. Schwartz, Tom
Phoenix, brian d foy (2008).
Learning Perl, 5th Edition,
O'Reilly
Mark Lutz (2009). Learning
Python, 4th Edition, O'Reilly
388
Similar Courses
» Unix Tools, Cambridge
» System oriented programming, EPF L Lausanne
» Programming Tools, Chalmers University
389
Students independently explore current topics from the profession and science. In
doing so, they should develop and improve the skills required for collecting and
evaluating the necessary literature, preparation of technical text based on the
publishing standards in professional and scientific publications and present their
work and knowledge gained to the larger group of people consisting of students
and teacher. Students, as part of this course, develop critical assessment of others'
work.
EEIT
C OM
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
Mentor will grade the
students' work with up to 40
points. Maximum of 40
remaining points will be
given by students from the
presentation group.
C EA
30
EP E
Study Hours
Lecturers
EC E
1. Describe in a concise written report actual topics from the profession and
science
2. Match facts from recommended literature with knowledge gained during
studies
3. Describe and summarize given topic in front of group of students
4. Estimate and critically evaluate quality of presentations of other students
5. Prepare report in accordance with publishing standards in professional and
scientific publications
6. Apply gained knowledge of communication skills for public presentation of
a given topic
L1
Prerequisites
EL
E-learning Level
Prerequisites for
Project
Project
Project
Project
Project
WT
Learning Outcomes
L3
IP
semester, 2nd year)
English Level
SEIS
Study Programmes
3
CE
The aim of this course is improvement of presentation, communication and
writing skills of students by providing an opportunity to discuss their ongoing
work and interests with others. Students work in smaller groups on recent
developments in the field of electrical engineering and information technology or
computing. Each student will be required to select one topic to research and
present, from the list provided on the first day of class.
ECT S Credits
CS
Course Description
E/C
31498
Seminar
Grading System
T ype
Class participation
F inal Exam: Oral
T hreshold
0%
Percent of
Grade
20 %
80 %
Exam
TI
T hreshold
Percent of
Grade
0%
0%
1.
2.
3.
4.
5.
Teacher assignment and seminar assignment
Submission of seminar draft
Work on seminar assignment
390
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Preparing for seminar presentation
Seminar presentation
391
Prerequisites
Prerequisites for
Project
Project
Project
Project
Project
Grading System
Class participation
F inal Exam: Oral
T hreshold
0%
Percent of
Grade
20 %
80 %
T hreshold
Percent of
Grade
0%
0%
1.
2.
3.
4.
5.
EEIT
Exam
TI
T ype
C OM
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
Mentor will grade the
students' work with up to 40
points. Maximum of 40
remaining points will be
given by students from the
presentation group.
C EA
30
CS
Students independently explore current topics from the profession and science. In
doing so, they should develop and improve the skills required for collecting and
evaluating the necessary literature, preparation of technical text based on the
publishing standards in professional and scientific publications and present their
work and knowledge gained to the larger group of people consisting of students
and teacher. Students, as part of this course, develop critical assessment of others'
work.
Study Hours
Lecturers
EP E
1. Describe in a concise written report actual topics from the profession and
science
2. Match facts from recommended literature with knowledge gained during
studies
3. Describe and summarize given topic in front of group of students
4. Estimate and critically evaluate quality of presentations of other students
5. Prepare report in accordance with publishing standards in professional and
scientific publications
6. Apply gained knowledge of communication skills for public presentation of
a given topic
L1
EC E
E-learning Level
EL
Learning Outcomes
L3
WT
English Level
IP
Study Programmes
3
SEIS
The aim of this course is improvement of presentation, communication and
writing skills of students by providing an opportunity to discuss their ongoing
work and interests with others. Students work in smaller groups on recent
developments in the field of electrical engineering and information technology or
computing. Each student will be required to select one topic to research and
present, from the list provided on the first day of class.
ECT S Credits
CE
Course Description
E/C
31505
Seminar
Submission of seminar draft
392
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Preparing for seminar presentation
393
Izv. prof. dr. sc.
Mario Kušek
Doc. dr. sc.
4
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
26
39
EEIT
ECT S Credits
Grading
EP E
Course Description
EC E
The course is designed to offer students an opportunity to acquire knowledge
needed to develop Android applications, and also server side services which will
be used by these applications.
WT
EL
web projects.
IP
Topics and themes covered include: foundations of the Java programming
language, object-oriented design in Java, Android platform architecture, graphical
user interface, using specific hardware, data access for Android, accessing different
services on Internet, developing RESTful web services and accessing them from
Android.
SEIS
Learning Outcomes
TI
CS
CE
1. Develop application in object-orijented programming language Java
independently and in team
2. Develop application for device with operating system Android
3. Design and develop service on server
4. Apply network programming in development of Android applications
5. Relate service with database on Android and on server
Upon completion of the course the student should be able to:
employ object-oriented programming principles,
use common Java classes and interfaces,
apply data structures and streams,
use Java logging and exception handling facilities,
access databases from Java,
use Eclipse integrated development environment,
independently develop Android applications,
utilize Android GUI components,
access specific Android hardware,
independently develop distributed Android applications and
effectively work in small teams.
C OM
Lecturers in Charge
E/C
91617
Service and Application Development for
Operating System Android
C EA
394
F orms of Teaching
» Lectures
» Lectures are held two hours per week, and are accompanied by a
presentation and other materials which are previously uploaded on
the course web site.
» Laboratory Work
» Laboratory excercises involve collaborative projects in small teams
and weekly consultations with lecturer.
» Consultations
» Teams have weekly consultations with lecturer.
» homework
» application development in team
Grading System
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Object-oriented programming in Java
Object-oriented design using Java
Object-oriented environment in Java
Data structures and streams in Java
Introduction to Android development
Android GUI elements
Accessing specific Android hardware
Using Android local data storage
Communication and service-oriented architecture in Android
Networking with Android
Introduction to developing web applications in Java
Database access with Java
Developing RESTfull web services
Literature
Bruce Eckel (2006).
Thinking in Java, Prentice
Hall
Shane Conder, Lauren
Darcey (2010). Android
Wireless Application
Development, AddisonWesley Professional
Zigurd Mednieks, Laird
Dornin, G. Blake Meike,
Masumi Nakamura (2011).
Programming Android,
O'Reilly Media
Marko Gargenta (2011).
Learning Android, O'Reilly
Media
395
Similar Courses
» CS193a Android Programming, Stanford
» 17-623 Software Engineering in Mobile Computing, Carnegie Mellon
University
396
Study Programmes
semester, 2nd year)
Learning Outcomes
Study Hours
Lecturers
60
15
C OM
Lecturers
Doc. dr. sc. Marko Subašić
EEIT
L1
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
C EA
Vedrana Baličević,
Juraj Petrović,
EP E
In this course a computational view of signals and systems is implemented and
students will acquire basic knowledge necessary in computer engineering,
communication, control and electronics. Topics are as follows. Signals as functions.
Discrete and continuous time signals. Elementary signal operations. Elementary
signals. The four F ourier transforms: CTF S, CTF T, DTF S, DTF T. F ourier
transform properties. Sampling and discrete-time signal processing. Discrete time
F ourier transform. Systems as functions. Systems with the memory. Linear and
time invariant (LTI) systems. Convolution sum and convolution integral.
Response of linear time invariant systems. Transfer functions and frequency
response. Laplace and z-transform in LTI system analysis. State-space model. Basic
structures for the implementation of LTI systems.
E-learning Level
EC E
Course Description
L2
50
60
75
90
Prerequisites
Mathematics 3 - C
Mathematics 3 - EE
EL
Doc. dr. sc.
Zvonko Kostanjčar
English Level
WT
Prof. dr. sc.
Damir Seršić
6
IP
Prof. dr. sc.
Branko Jeren
ECT S Credits
Prerequisites for
Automatic Control
Project
SEIS
Lecturers in Charge
E/C
31494
Signals and Systems
CE
CS
TI
1. Classify signals;
2. Explain and apply tests to unknown systems in order to classify the
systems into known categories;
3. Explain and compare the properties of the F ourier Transform, the Laplace
Transform and the Z-Transform;
4. Apply methods to find response of LTI time discrete and time continuous
systems in time domain;
5. Apply Laplace and z- transform to find response of LTI time discrete and
time continuous systems;
6. Analyze transfer functions and frequency responses and present the
properties of the systems;
7. Analyze MIMO systems described with state equations;
8. Analyze and implement linear systems using block diagrams.
397
Students will learn and understand basis of description and analysis of discrete and
continuous-time signals and systems. They will also obtain practical skills in
system analysis in MATLAB.
F orms of Teaching
» Lectures
» Course is divided in two cycles of lecturing. There are six weeks in
the first cycle, and seven weeks lecturing in second cycle. Two weeks
are reserved for midterm and final exam.
» Exams
» Midterm and final exam are organized as written exams.
» Exercises
» Optional recitation sessions are offered weekly with the duration of
two hours.
» Homework.
Grading System
T ype
Homeworks
Exam: Written
T hreshold
Percent of
Grade
100 %
0%
51 %
51 %
0%
10 %
45 %
45 %
Exam
T hreshold
Percent of
Grade
100 %
0%
0%
0%
0%
51 %
100 %
1. Signals as functions. Introduction, motivation, organization of the course.
Introduction to signals and systems. Signals as functions. Classification of
signals. Elementary signal operations. Signal energy and signal power.
2. Elementary signals: unit step, unit ramp, Kronecker delta function, Dirac
delta function. Generalized derivative of signals with jump discontinuities.
Continuous and discrete time sinusoid and complex exponential signal.
3. F ourier transforms: CTF S and CTF T. Generalized F ourier transform.
F ourier transform of Dirac delta function.
4. F ourier transforms: DTF S and DTF T.
CTF T and DTF T of periodic signals.
5. F ourier transform properties: linearity, symmetry, convolution, time and
frequency shift, duality. Continuous time signal sampling. Sampling
theorem. Aliasing. Reconstruction of a signal from its samples.
6. Continuous spectrum sampling. Continuous spectrum reconstruction from
its samples. Discrete F ourier transform – DF T.
7. midterm
8. Systems as functions. Instantaneous and dynamic systems. Causal and
noncausal systems. Time-invariant and time-varying systems. Linear and
incrementally linear systems. BIBO stability. Impulse response.
Convolution sum and convolution integral.
9. Input/output model of discrete time systems. Difference equations.
Homogenous and particular solution. Zero-input response and zero-state
response.
398
10. Input/output model of continuous time systems. Difference equations.
Homogenous and particular solution. Zero-input response and zero-state
response.
11. LTI system response to the complex exponential input. transfer function
and frequency response. Poles and zeros of the transfer function. Poles and
zeros contribution to frequency response.
12. Laplace and z-transform. Inverse Laplace and z-transform. Laplace and ztransform properties. Laplace and z-transform in LTI analysis.
13. State-variable descriptions of LTI systems. State equations for MIMO
systems. Solution of state equations of MIMO time continuous and time
discrete systems.
14. Block diagrams for LTI systems. Basic Structures. Direct form I and II.
Cascade and parallel form structures.
15. final exam
Literature
B. P. Lathi (2004). Linear
Systems and Signals, Oxford
University Press
A.V. Oppenheim and A.S.
Willsky, with S.H. Nawab
(1997). Signals and Systems,
Prentice-Hall
E.A.Lee, P.Varaiya (2011).
Structure and Interpretation of
Signals and Systems, Second
Edition, LeeVaraiya.org,2011
Hrvoje Babić (2001). Signali
i sustavi, elektroničko
izdanje
T. Petković, B. Jeren i ostali
(2004). Signali i sustavi
zbirka zadataka, elektroničko
izdanje
Similar Courses
» Structure and Interpretation of Signals and System, University of California
Berkeley
» Signals and Systems, University of California Berkeley
» Signal - und Systemtheorie I & II, ETH Zurich
» ECEB204: Signals & Systems, IEEE & ACM Computing Curricula
» ENGC304: Signals and Linear Systems, IEEE & ACM Computing Curricula
» ELE301: Signals and Systems, IEEE & ACM Computing Curricula
» Signals and Systems, MIT
» Signaler och System (Signals and Systems), Chalmers University
» Signale und Systeme 1 & 2, TU Wien
» Signaldarstellung, TU Munchen
399
Definition of communication, types of verbal and non-verbal communication.
Principles of successful communication, communication skills. Active listening.
Development of the strategy of effective learning. Development of questionasking skills. Developing of the ability of critical thinking, decision making.
Written and oral communication. Communication using ICT - e-mail, web,
forums. Presentations: preparing and presenting. Individual and group
communication, communication in teams. Interaction management, persuasion
and argumentation, negotiation skills. Assertive communication. Conflict solving.
Public speaking and rhetoric.
E-learning Level
L1
Study Hours
Lecturers
30
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
64
79
90
Prerequisites for
Seminar
Seminar
EEIT
L1
C OM
English Level
C EA
Course Description
3
EP E
dr. sc.
Predrag Pale
ECT S Credits
EC E
Lecturer in Charge
E/C
19678
EL
WT
Study Programmes
IP
SEIS
Learning Outcomes
CS
CE
Describe theories and types of communication
Apply the skill of listening
Practice teh skill of asking questions
Classify learning styles
Demonstrate the skill of asertive communication
Explain group communication
TI
1.
2.
3.
4.
5.
6.
Acquiring communication skills and active listening skills, development of
effective learning strategies and question-asking skills, development of critical
thinking. The students will get acquainted with specific features of
communication using ICT. Presentations skills and team communication are
developed.
F orms of Teaching
» Lectures
» Informing students about knowledge related to human professional
and private communication.
» Exams
400
» mid-term exam, final-exam, multiple choice
seminars
presentations
homework
» Demonstration of communication skills
» Consultations
» when needed
» Other
» observing, detecting and commenting on critical points in
communication on films (e.g.youtube)
» Seminars
» 3 seminars
1. non-verbal communication
2. skill of asking questions
3. team work
» role-play, exercising communication skills in different situations
» Other
» qustionnaries and tests
Grading System
T ype
Homeworks
Class participation
Attendance
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
15 %
10 %
5%
30 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
15 %
10 %
5%
0%
70 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Deffinition of communication, review of communication theories
Verbal, non-verbal and para-verbal communication
Skill of asking questions
Active listening
Other forms of listening
Written communication, writting a report
Presenting
Mid-term-exam
Critical thinking and decision making
Asertive communication
Styles of learning and teaching
ICT communication characteristics
Communication in groups and teams
Cross-cultural communication
F inal exam
401
Literature
John W Davies F (2001).
Communication skills: a guide
for engineering and applied
science students, Upper
Saddle River, NJ : Prentice
Hall
Thomas E. Harris, John C.
Sherblom (2010). Small
Group and Team
Communication, Pearson
Education/Allyn & Bacon
Similar Courses
» 15.289 Communication Skills for Academics, MIT
» CTL 219: Oral Communication for Graduate Students, Stanford
402
Study Programmes
3rd year)
year)
Learning Outcomes
L1
Study Hours
Lecturers
60
60
Lecturers
Prof. dr. sc. Nikola Bogunović
Dr. sc. Alan Jović
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
72
86
Prerequisites
Computer Science
Operating Systems
Prerequisites for
Design Patterns in Software
Design
Open Computing
TI
1. Define effective procedure for software design.
2. Distinguish between structured and unstructured procedures in siftware
design.
3. Apply software engineering process models.
4. Employ methods to specify program requirements.
5. Analyze requirements and derive the most suitable software architecture.
6. Assemble software model using standard graphical and mathematical
notations (UML).
7. Create final software product using selected language and programming
environment.
8. Assess the quality of finalized software product.
EL
EC E
EP E
C EA
Dr. sc. Alan Jović
Nikolina F rid, mag. ing.
comp.
EEIT
E-learning Level
C OM
L1
WT
Software design course addresses basic knowledge and skills for acquiring the
competences in software engineering, namely understanding, evaluating and
designing of software systems. Generic models of software engineering processes.
Requirements engineering. Software architecture concepts and specification
paradigms. Modeling of input/output and reactive software systems. Objectoriented system modeling (UML). F ormal specification and verification of
software system properties. Software testing. Automated assistance and tools in
software design process.
English Level
IP
Course Description
8
SEIS
Izv. prof. dr. sc.
Vlado Sruk
ECT S Credits
CE
Lecturer in Charge
E/C
34269
Software Design
CS
403
Knowledge and skills of software construction. Deriving accurate description of
software architecture from requirement analysis. Generating and selecting
software architectural alternatives based on domain restricted knowledge and
precise specification. Properties verification of particular software architectural
formal models. Utilizing common software development tools.
F orms of Teaching
» Lectures
» The course is organized in two cycles. The first cycle consists of 7
weeks of lectures and midterm exam. The second cycle consists of 6
weeks of lectures and final exam.
» Exams
» Quick quizzes.
Midterm exam.
Successful project completion.
F inal exam.
» Students are arranged in groups of 6 to 8 individuals, and are
working on a project comprising specificatio, design, realization and
testing of software product.
Grading System
T ype
Quizzes
Seminar/Project
Exam: Written
T hreshold
Percent of
Grade
10 %
50 %
0%
30 %
9%
30 %
25 %
36 %
Exam
T hreshold
Percent of
Grade
10 %
50 %
0%
9%
30 %
50 %
61 %
1. Course administration. Introduction to software engineering. Introduction
to software requirements engineering.
2. Processes and models in software requirements specification. Prezentation
of software requirements document. Instructions on students project group
coordination.
3. Processes and models in software engineering (waterfall, evolutionary,
component based, RUP). Prezentation of a tool for UML modeling.
4. Introduction to software architecture and architectural stiles
5. Introduction toobject-oriented software design (classes, objects, variables,
methods, operations, responsibilities, polymorphism, inheritance, dynamic
binding, etc.).
6. Software modeling with basic UML diagrams. Specific presentation on
UML class diagrams.
7. Presentation of all relevant UML diagrams (statical and dynamical) and
ways how to use them.
8. Midterm exam
9. Distributed object-oriented architecture (client-server architecture, broker
based architecture, service oriented architecture, component based
architecture).
404
10. Methods for software testing with presentation of an environment for
software design and testing.
11. F ormal software verification -1: introduction to propositional and
predicate logic.
12. F ormal software verification - 2: temporal logic for spesifying software
behavior.
13. Other software architectures - 1: data flow architecture, event based
architecture.
14. Other software architectures - 2: data repository architecture, layered
architecture, virtual machines, software architecture for process control.
15. F inal exam
Literature
Timothy C. Lethbridge,
Robert Laganiere (2005).
Object-Oriented Software
Engineering, McGraw-Hill
Ian Sommerville (2007).
Software engineering,
Addison-Wesley
Paul Clements, David
Garlan, Paulo Merson
(2010). Documenting
Software Architectures,
Addison-Wesley
Similar Courses
» Software architecture, Cambridge
» Software modeling, analysis, design, verification, IEEE & ACM Computing
Curricula
» Software architecture, ETH Zurich
» Software engineering, Stanford
» Design of Software Architectures, University of Twente
405
Learning Outcomes
E-learning Level
L1
Prerequisites for
BSc Thesis
Grading System
Seminar/Project
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
T ype
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
CE
IP
Prerequisites
Algorithms and Data
Structures
Seminar
Seminar
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
SEIS
1.
2.
3.
4.
5.
6.
L3
EP E
3rd year)
English Level
EC E
Study Programmes
8
EL
presentation.
ECT S Credits
WT
Course Description
E/C
36696
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
406
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
407
Learning Outcomes
1.
2.
3.
4.
5.
6.
L3
E-learning Level
L1
Prerequisites
Databases
Seminar
Seminar
CE
SEIS
IP
Grading System
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
Seminar/Project
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
Prerequisites for
BSc Thesis
T ype
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
EP E
English Level
EC E
Study Programmes
8
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37541
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
408
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
409
Learning Outcomes
1.
2.
3.
4.
5.
6.
L3
E-learning Level
L1
Prerequisites
Operating Systems
Seminar
Seminar
CE
SEIS
IP
Grading System
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
Seminar/Project
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
Prerequisites for
BSc Thesis
T ype
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
EP E
3rd year)
English Level
EC E
Study Programmes
8
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37544
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
410
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
411
Learning Outcomes
E-learning Level
L1
Prerequisites for
BSc Thesis
Grading System
Seminar/Project
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
T ype
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
CE
IP
Prerequisites
Computer Science
Mathematics 3 - C
Mathematics 3 - EE
Seminar
Seminar
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
SEIS
1.
2.
3.
4.
5.
6.
L3
EP E
year)
English Level
EC E
Study Programmes
8
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37547
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
412
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
413
Learning Outcomes
1.
2.
3.
4.
5.
6.
L3
E-learning Level
L1
Prerequisites
Operating Systems
Seminar
Seminar
CE
SEIS
IP
Grading System
T hreshold
Percent of
Grade
T hreshold
Percent of
Grade
0%
100 %
0%
0%
CS
Exam
TI
Seminar/Project
1.
2.
3.
4.
5.
6.
7.
8.
9.
C OM
Prerequisites for
BSc Thesis
T ype
C EA
Grading
Acceptable (2)
50
Good (3)
60
Very Good (4)
75
Excellent (5)
90
project.
EEIT
Study Hours
EP E
English Level
EC E
Study Programmes
8
EL
presentation.
ECT S Credits
WT
Course Description
E/C
37548
Mentor assignment
Work on project
Work on project
Work on project
Work on project
Work on project
Work on project
414
10.
11.
12.
13.
14.
15.
Work on project
Project evaluation
Project evaluation
415
4
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
30
C OM
EEIT
ECT S Credits
Grading
C EA
IP
In everyday life we encounter different types of NP-hard optimization problems,
whose approximate resolution enables efficient and cost-effective management of
various processes. Within this skill, students will learn concepts of single- and
multi-objective optimization, continuous and combinatorial optimization
problems and with a subset of evolutionary computation algorithms that will be
used to obtain satisfactory solutions. As part of this skill, students will learn about
the genetic algorithms, ant colony optimization algorithm, particle swarm
optimization algorithm, artificial immune algorithms and the algorithm of
differential evolution, with examples of single- and multi-objective optimization
of continuous and combinatorial problems. Parallelization of selected algorithms
will be discussed and implemented, and examples will be given in the Java
programming language.
EL
Course Description
In order to pass, students are
required to be present on
lectures, to solve and present
all of laboratory exercises and
to demonstrate minimally
required level of knowledge
and understanding.
WT
Doc. dr. sc.
Marko Čupić
EP E
Lecturer in Charge
79087
E/C
Solving Optimization Problems Using
Evolutionary Computation Algorithms in Java
EC E
SEIS
Learning Outcomes
TI
CS
CE
1. Define the concept of optimization problem
2. Identify evolutionary computation algorithms
3. Apply evolutionary computation algorithms on single-criterion
optimization problems
4. Apply evolutionary computation algorithms on multi-criterion
optimization problems
5. Construct parallel evolutionary computation algorithms
6. Assess the applicability of different evolutionary computation algorithms
on some optimization problems
As part of laboratory exercises students will implement each of before-mentioned
algorithms. Based on these implementations they will gain deeper understanding
about how algorithms work and how they behave (execution speed, the influence
of basic parameters, etc.). Student will learn some of appropriate way for solution
encoding for these algorithms, which will allow them to apply these and similar
encoding to similar problems. Students will understand the difference between
single- and multi-objective optimization. They will write a parallel version of the
selected algorithm, which will enable them to gain additional experience.
416
F orms of Teaching
» Lectures
» Teaching will be conducted in lecture room. A PowerPoint
presentation will be used, as well as the board for detailed
explanations of algorithms and for solving examples. Additionally,
a series of prepared educational computer programs will be used for
the illustration of algorithms applied on several problems.
» Laboratory Work
» In the laboratory, students implementation of algorithms will be
reviewed and advices for improvement will be provided. Laboratory
problems are solved at home; in lab term solutions are presented to
lecturer.
Grading System
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
Comment:
1. Introduction
2. Types of optimization problems.
3. Genetic algorithm applied to the optimization problem of continuous
functions.
4. Genetic algorithm applied to the problem of combinatorial optimization.
5. More advanced genetic algorithms
6. Ant colony optimization algorithm
7. Particle swarm optimization algorithm
8. Immune optimization algorithms
9. Multiobjective optimization
10. Genetic algorithms for multiobjective optimization
11. Immune Algorithms for multiobjective optimization
12. Parallelization of evolutionary algorithms (1)
13. Parallelization of evolutionary algorithms (2)
14.
15.
417
Literature
Prirodom inspirirani
optimizacijski algoritmi.
Metaheuristike.
Michael Affenzeller, Stefan
Wagner, Stephan Winkler,
Andreas Beham (2009).
Genetic Algorithms and
Genetic Programming.
Modern Concepts and
Practical Applications, CRC
Press
Kenneth V.Price, Rainer M.
Storn, Jouni A. Lampinen
(2005). Differential
Evolution. A Practical
Approach to Global
Optimization, Springer
Kalyanmoy Deb (2009).
Multi-Objective Optimization
using Evolutionary
Algorithms, Wiley
Marco Dorigo, Thomas
Stützle (2004). Ant Colony
Optimization, MIT Press
418
English Level
L1
E-learning Level
L1
Study Hours
Lecturers
45
6
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
Study Programmes
C EA
The goal of the subject is to familiarize the students with the influence the sound
has on the environment and on people who live and work in the vicinity of sound
sources. Acoustic emission. Influence of noise and vibrations to man. Time and
spectral characteristics of noise. Parameters used for evaluation of effects the noise
has on people. Noise measurement procedures and methods. Sound level meter.
Spectrum analyzer. Noise evaluation methods. Measures and means of protection
from noise, vibrations and impacts. Noise maps. Soundscapes. Sound quality.
Standards, regulations and recommendations.
50
60
75
90
EP E
Course Description
Dr. sc. Mia Suhanek
C OM
Lecturer
Dr. sc. Mia Suhanek
EEIT
4
EC E
Izv. prof. dr. sc.
Kristian Jambrošić
ECT S Credits
EL
Lecturer in Charge
E/C
91857
Prerequisites
Mathematics 2
Physics 1
WT
IP
Learning Outcomes
SEIS
TI
CS
CE
1. Evaluate the indicators of the interaction between sound sources and the
surrounding, i.e. sound pressure, intensity and power
2. Explain the origin of mechanical vibrations and basic principles of
vibration insulation
3. Operate a sound level meter and an accelerometer for measuring sound and
vibration levels
4. Predict the influence of excess noise and vibration levels on human
5. Compare needed measures for indoor and outdoor noise protection based
on requirements
6. Differentiate elements of interior acoustical design and sound insulation
elements
7. Interpret noise maps for evaluation of imission levels based on noise
indicators
8. Apply noise protection laws and regulations when evaluating the imssion
levels
Good understanding of the problems and solutions of sound insulation and noise
protection, with applications to human environment. Good understanding of
principles and methods in noise and vibration control used for residental
buildings. Theoretical and practical knowledge about methods and techniques in
noise measurements.
419
F orms of Teaching
» Lectures
» Lectures are held in 2 terms, 3 hours per week. Short exams and
solving of numerical examples will be integrated into the lectures.
» Exams
» During the lectures, short tests on comprehension of the adopted
knowledge will be held. Also a mid-term and final exam will be
held.
» Laboratory Work
» 6 laboratory exercises will be organized that follow the contents of
the lectures.
Grading System
T ype
Quizzes
Exam: Written
Exam: Oral
T hreshold
Percent of
Grade
0%
0%
0%
0%
20 %
10 %
35 %
35 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
50 %
50 %
1. Introduction. Sound and vibration basics. Noise.
2. Wave equation of sound. Acoustic quantities. Levels. Sound fields and
sources.
3. Sound analysis - time and frequency domain. F ilters.
4. Sound measurement. Measurement microphone. Sound level meter.
5. Mechanical vibrations. Single/multi degree of freedom systems. Vibration
insulation.
6. Vibration measurement and analysis. Accelerometer.
7. Noise and vibration influence on human.
8. Mid-term exam
9. Sound intensity. Sound power.
10. Noise protection measures 1 - indoors.
11. Noise protection measures 2 - outdoors.
12. Noise maps. Soundscape. Sound quality.
13. Norms and laws in the field of sound and vibration in Croatia.
14. Solving integral problems in the field of sound and vibration.
15. F inal exam
420
Literature
David A. Bies, Colin H.
Hansen (2009). Engineering
Noise Control, Theory and
Practice, Spon Press
Michael Möser (2009).
Engineering Acoustics, An
Introduction to Noise
Control, Springer
F rank F ahy, John Walker
(2004). Advanced
Applications in Acoustics,
Noise & Vibration, Spon
Press
Similar Courses
» Technische Akustik und Lärmbekämfung, TU Munchen
» Mechanical Vibrations, Cambridge
» Schallschutz und Akustik, TU Wien
» Lärmbekämpfung, ETH Zurich
» Sound and vibration measurement, Chalmers University
» Advanced Noise and Vibration Control, TU Berlin
» Aircraft Propulsion, Noise and Pollutant Emissions, TU Delft
421
Doc. dr. sc.
Jan Šnajder
English Level
L1
E-learning Level
L1
Study Hours
Lecturers
Exercises
45
15
Doc. dr. sc.
Igor Velčić
Course Description
EC E
EP E
Statistics plays a vital role in every human activity, while the ability to use
statistical inferential methods and interpret the results are essential in engineering
and science. This
course gives a comprehensive introduction to the methods and practices of
computer-based
EL
statistical data analysis. The course covers and intertwines four integral aspects of
statistical
WT
analysis: data, statistical methods, mathematical foundations, and interpretation
of
IP
results. The first part of the course gives an overview of statistical methods,
approaches to
CS
CE
SEIS
data description, and data visualization and exploration methods. The second part
is devoted to the foundations of statistical inference and covers the selection,
application, and adequacy of parametric statistical tests for numeric and
categorical data. The third part considers more advanced topics, such as nonparametric statistics, analysis of variance, and correlation analysis. All concepts are
illustrated with examples and problem sets on real data in programming
languages R and Python.
Study Programmes
TI
3rd year)
EEIT
4
C EA
Prof. dr. sc.
Doc. dr. sc.
Bojana Dalbelo- Zvonko Kostanjčar
Bašić
ECT S Credits
C OM
Lecturers in Charge
E/C
155246
Statistical Data Analysis
422
Learning Outcomes
1.
2.
3.
4.
5.
Define main notions in the statistical data analysis
Explain mathematical backgrounds of main statistical procedures
Apply procedure of data preparation and visualization
Apply statistical test on real data
Analyze the relation between statistical variables by applying regression
analysis and correltion analyis
6. Justify the adequacy of statistical inference for given data
7. Interpret the results of statistical data analysis and explain their practical
meaning
F orms of Teaching
» Lectures
» 3 hours per week
» Exams
» 2 exams
» Laboratory Work
» 1 hour per week
» Experiments
» Consultations
Grading System
T ype
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
1. Introduction and motivation (the role of statistics in science and practice;
taxonomy of statistical methods; overview of the literature and tools)
2. Data (measurement scales; describing numerical and categorical data;
outliers; data transformation)
3. Data visualization and exploration (scatter plot, histograms, q-q plot)
4. Introduction to statistical inference (population, sample, and sampling;
observational and experimental study designs)
5. Principles of statistical inference (hypoteses; tests; pvalue; significance)
6. Statistical inference for numerical data (comparing the means; paired data;
tests for the variance)
7. Statistical inference for categorical data (testing proportions; contingency
tables; chi-square test)
8. Choosing the right test (sample size; test conditions and limitations)
9. Introduction to nonparametric statistics (methods overview; sign test;
Mann-WhitneyWilcoxon test; Wilcoxon signed-rank test; pros and cons)
10. Resampling methods (permutation test; principles of boostrapping)
11. Introduction to analysis of variance (single factor ANOVA, ANOVA table,
F -test, DurbinWatson test; Barlett's test; Bonferroni correction)
12. Regression and correlation analysis (statistical inference using regression;
residual analysis; confidence intervals)
13. Regression and correlation analysis (multiple regression; nonlinear
regression; logistic regression)
423
14. Alternative approaches to data analysis (bayesian vs. frequentist statistics;
examples of bayesian modeling and inference)
15. Wrap-up and recommendations for further studies
Literature
Željko Pauše (1992). Uvod u
matematičku statistiku,
Školska knjiga
David M. Diez, Crhisopher
D. Barr, Mine
CerinkayaRundel (2015).
OpenIntro Statistics,
OpenIntro
Mirta Benšić, Nenad Šuvak
(2013). Primijenjena
statistika, Sveučilište J. J.
Strossma yera
L. F ahrmeir, T. Kneib, S.
Lang, B. Marx (2013).
Regression: Models, Methods
and Applications, Springer
G. James, Daniela
Witten,Tre vor Hastie,
Robert Tibshirani (2013).
An Introduction to Statistical
Learning with Applications
in R, Springer
Allen B. Downey (2014).
Think Stats, "O'Reilly Media,
Inc."
Similar Courses
» Statistical Data Analysis, ETH Zurich, ETH Zurich
» Applied Statistics, EPF L Lausanne
» Statistical Data Analysis I, TU Munchen
» Statistical Thinking and Data Analysis, MIT
» Statistics for Applications, MIT
424
Prof. dr. sc.
Nikola Čavlina
Prof. dr. sc.
Nenad Debrecin
2
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
30
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
75
90
Course Description
WT
EL
EC E
EP E
Ecology, environment, environment protection, link to economy. Pressure on
environment, problems and trends: atmosphere, climate, Kyoto protocol, water,
soil, forests, fishing, food, famine, energy, transport, biodiversity, waste, Basel
convention. Predication of (im)possible future. Sustainable development,
environmentalist myth or reality. Sustainable enterprise. Dow Jones
Sustainability Group Index. Enterprise concept for 21st century. New business
topics: corporative social responsibility, sustainable consumption, changes in
consumer?s needs, trading and environment, product responsibility. Tools for
management of sustainable development: EMS, ISO 14000, environmental
reports. Sustainable development and Croatian companies.
Study Programmes
TI
CS
CE
SEIS
IP
year)
year)
E/C
ECT S Credits
EEIT
Lecturers in Charge
34275
C OM
Sustainable Development and Environment
C EA
425
Learning Outcomes
1. Explain relationship among economic development, environmental
limitations and scarce resources
2. Explain relationship among pattern of production and consumption, and
large-scale ecosystem disturbances
3. Describe institutional and legal framework in environmental protection in
Croatia
4. Explain greenhouse gases emissions, the global warming, and international
agreement on climate changes
5. Analyze status and trends in exploitation of main resourses: energy, water
and arable land in the world
6. Assess importance of sustainable development, and sustainable
development indicators
Students will acquire basic knowledge in sustainable development and
environment protection. They will become aware of the necessity of environment
protection and active participation in civil society actions. They will find out how
to increase competitiveness by utilizing eco efficiency and how to promote
equality of environmental and social dimensions compared to economical
dimensions.
F orms of Teaching
» Lectures
» Teaching the course is organized in two teaching cycles. The first
cycle contains seven weeks, mid-term exam, and the second cycle
contains six weeks of classes and a final exam. Classes are conducted
through a total of 15 weeks with weekly load of 2 hours. Each
lecture includes written material and slides.
» Seminars
» Student is expected to write an essay on one of the offered subjects.
Essays are written in groups of three students and are expected to be
between 15 000 and 20 000 characters in length. Stdent is expected
to add pictures as needed.
Grading System
T ype
Class participation
Seminar/Project
Exam: Written
T hreshold
Percent of
Grade
0%
10 %
0%
8%
10 %
25 %
30 %
35 %
Exam
T hreshold
Percent of
Grade
0%
10 %
0%
10 %
25 %
0%
65 %
1. Introduction and discussion on course work. Elements of sustainable
development: economy, environment and society. Education in
environmental protection (Harward's Pladge, Tallories Declaration)
2. Easter Islands paradigm, lifestyle choice and importance of world view.
426
3. Systematic approach to sustainable development. Interconnectivity
between economies and ecosystems.
4. Paradigm of economic growth and development. Modern patterns of
production and consummation and their impact on the environment,
economic development and growth and its implications on environment
and polarisation of world economy.
5. Implementation of environmental protection. Documents of environmental
protection.
6. Definitions: ecology, environment, environmental protection. Problems of
environmental protection. History of environmental protection.
7. Physical planning and environmental protection. Locations. Environmental
impact assessment. Environment impact studies. Environmental protection
system in Croatia.
8. Exams
9. Exams
10. Waste management.
11. Cleaner production. Ecological efficiency. Social responsibility of
enterprises. Tools for development management: EMS, ISO 14000.
Reporting on the environment.
12. Ozone layer and ozone holes. Glass house effect. Global warming. Global
warming consequences. Sustainable development and environmental
protection – similarities and differences. How to achieve sustainable
development?
13. Invited lecturer.
14. Growth limits: world population, water, soil, minerals, energy. World
resources and population in geopolitical context. Global development
scenarios. Dimensions of sustainable development.
15. In the search for the solution.
Literature
F eretić, Danilo; Tomšić,
Željko; Škanata, Dejan;
Čavlina, Nikola; Subašić,
(2000). Elektrane i okoliš,
Element, Zagreb
edt--Đikić, Domagoj (2001).
Ekološki leksikon, Barbat,
Zagreb
James Lovelock (2006).
Osveta Geje, Izvori
Similar Courses
» Planning for Sustainable Development, MIT
427
Prof. dr. sc.
Dina Šimunić
Prof. dr. sc.
Ivica Pavić
4
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
45
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
65
75
88
Course Description
EC E
EP E
Structure and action of international and regional organizations for
standardization. Technical standard application in several fields of electrical
engineering. Procedure for Croatian standard approval in field of electrical
engineering.
EEIT
ECT S Credits
C OM
Lecturers in Charge
E/C
34355
Technical Standardization and Legislative
C EA
Study Programmes
WT
EL
Learning Outcomes
CE
SEIS
Select the main principles of standardization and legislation
Evaluate technical standardis in the engineering business
Select world standardization organizations and related standards
Select European standardization organizations and related standards
Select Croatian standardization organizations and related standards
Argue on use of defined technical standard
CS
1.
2.
3.
4.
5.
6.
IP
TI
Student will gain basic knowledge in technical standards and organisations that
develop standars at global, regional and national levels. They will learn how to
use the technical standards in everyday engineering practice.
F orms of Teaching
» Lectures
cycles. The first cycle consists of 4 weeks of lectures and 1st midter.
econd cycle has 4 weeks of lectures and 2nd midterm, while 3rd cycle
has 4 weeks of lectures and final exam. The lectures are given in
total of 15 weeks, three hours per week.
» Exams
» two midterm exams and final exam
428
» Consultations
» Consultation term is determined on the first lecture in agreement
with the
students.
» Seminars
» Students write and present the seminars with the topic of their
interest.
» Other
» homework
» Other
» Students are learning via seminar, which they write and present. In
this way, they learn about the necessity of thorough and deep
knowledge.
Grading System
T ype
Homeworks
Seminar/Project
Attendance
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
0%
5%
5%
10 %
25 %
25 %
30 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
0%
0%
5%
5%
10 %
0%
80 %
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Definitions in technical standards
History of standardisation
Existing technical standards at global, European and national level
Existing standards in electrical engeneering at global, European and
Croatian level
Organization of global standardization
Regional standardization organizations (example Europe)
National Standards (example Croatia)
Ogranisation of global, regional and national standardization organisations,
(CEN, CENELEC, etc.)
NATO standardization organization
Scientific standards
Industrial standards
Harmonisation of technical standards
Croatian standards in electrical engineering
Examples of standards in electrical engineering
Examples of standards in telecommunications
429
Literature
R. Prasad, S. Ohmori, D.
Simunic (2010). Towards
Green ICT, River Publishers
Workshop Committee,
Commission on Engineering
and Technical Systems,
National Research Council
(1990). Crossroads of
Information Technology
Standards, National
Academy Press,
Washington, D.C. 1990
S. Prakash Sethi (2003).
Setting Global Standards,
John Wiley & Sons, Inc.,
Hoboken, New Jersey
Similar Courses
» Engineering Professional Practice, McGill University
430
Prof. dr. sc.
Sven Lončarić
Izv. prof. dr. sc.
Igor Lacković
L1
E-learning Level
L1
Study Hours
Lecturers
30
15
Lecturer
Course Description
EP E
50
65
75
90
Prerequisites
Physics 1
WT
Prof. dr. sc.
Vedran Bilas
C EA
Dominik Džaja, mag. ing.
Goran Šeketa, mag. ing.
Sara Žulj, mag. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
CE
SEIS
IP
Biomedical engineering is one of the fastest-growing fields of engineering. This
field is aimed to produce important innovations that improve health and quality
of life - from developing artificial organs, refinement of imaging technology that
allow doctors to examine patients better than ever before or technologies for
patient distance monitoring. Technologies used to bring together engineering
knowledge with applied knowledge in the fields of biology, chemistry and
physics. The course covers basic concepts of technology in medicine and it serves as
an introduction to the fundamentals on which biomedical engineering is based.
Study Programmes
TI
CS
year)
year)
EEIT
English Level
C OM
Prof. dr. sc.
Mario Cifrek
4
EC E
Prof. dr. sc.
Ratko Magjarević
ECT S Credits
EL
Lecturers in Charge
E/C
127185
431
Learning Outcomes
1.
2.
3.
4.
5.
6.
Recognize different technologies in medical application
Explain physical principles of operation of medical devices and equipment
Analyze interaction of medical instrumentation and tissue
Differentiate invasive and non-invasive technologies in medicine
Combine knowledge from engineering with living world
Identify ethical problems in application of technologies in medicine
- providing students with the fundamental knowledge of technologies in
medicine, and understanding several applications of biomedical engineering
- giving students possibility to participate in discussion on the selected topics
from technologies in medicine
- introducing students with the experience of experts in the field, as well as with
several accessible devices
- introducing students to understand contemporary problems related to health
and quality of life
- preparing students for competence in the multidisciplinary field
F orms of Teaching
» Lectures
» Ex catedra, guest-lecturers from biomedical engineering field
» Exams
» Writtenand oral exams
» Laboratory Work
» Biomedical electronics laboratory
» Consultations
» Standard consultaions
» Other
» Visits to health care institutions
» Other
» Round table discussions
Grading System
T ype
Exam: Written
T hreshold
Percent of
Grade
0%
0%
0%
20 %
40 %
40 %
Exam
T hreshold
Percent of
Grade
0%
0%
20 %
0%
80 %
1. Introduction to technology in medicine
2. Electrophysiology (sources of bioelectric signals)
3. Biomedical instrumentation (principles of measurment and processing of
bioelectric signals)
4. Organs and systems in the human body 2 (including bioengineering and
cellular engineering principles)
432
5. Organs and systems in the human body 2 (Artificial organs - artificial heart,
visual prosthesis (bionic eye), cochlear implant (bionic ear)
6. Implantable devices 1 (Cardiac pacemakers, medical robots)
7. Implantable devices 2 (Intrabody communication)
8. Midterm exam
9. Modelling of biological systems 1 (Modelling of nervous system and brain)
10. Modeliranje bioloških sustava 2 (Modelling and visualization of human
body)
11. Medical imaging 1 (2D, 3D, 4D)
12. Medical imaging 2 (F unctional imaging)
13. Telemetry systems for medical and sports monitoring, m-health
14. Biomedical engineering ethics
15. F inal exam
Literature
Joseph D. Bronzino, ur.
(2006). Biomedical
Engineering Fundamentals
(izabrana poglavlja), CRC
A. Šantić (1997).
Biomedicinska elektronika,
Školska knjiga
Kramme, Hoffmann, Pozos,
ur. (2011). Handbook of
Medical Technology (izabrana
poglavlja), sPRINGER
Similar Courses
» Biomedical Engineering A & B, ETH Zurich
» Biomedical Engineering, Hamburg
» Basics of statistics and biomedical signals, Politecnico di Milano
» Introduction to clinical engineering, Politecnico di Torino
433
Telecommunication network organization.
Telecommunication system
architecture and functionality. Core and access networks, circuit switching and
packet switching. Transmission media, digital modulation techniques and line
codes. Network synchronization, synchronous digital hierarchy (SDH). Optical
transmission systems and networks. Optical link dimensioning. Wavelength
division multiplexing, network protection and restoration. Access and
metropolitan area networks, broadband access. Routing and switching. Reference
model and switching system software structure. Call and services. User and
network signalization. Network management.
L1
E-learning Level
L1
Study Hours
Lecturers
45
15
C OM
T eaching Assistant
Dr. sc. Matija Džanko
EEIT
English Level
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
50
60
70
85
Prerequisites
C EA
Course Description
4
EP E
Prof. dr. sc.
Dragan Jevtić
ECT S Credits
EC E
Lecturer in Charge
E/C
34290
Telecommunication Systems and Networks
EL
WT
Study Programmes
IP
SEIS
Learning Outcomes
TI
CS
CE
1. To define architecture and organization of communication network
2. To explain how telecommunication network operates and functions of
network nodes
3. To apply knowledge about communication networks and services
4. To analyze services, as well as service interactions, in odrer to select
appropriate ones
5. To analyze organization of public and private networks and services
6. To define basic configuration for transport and necesary components
7. To create network model including access functions, transport functions and
services
Basic knowledge about telecommunication systems and networks. Good
understanding of their basic principles, structure, architectures and functions.
Ability to carry out operation and maintenance of contemporary
telecommunication networks.
434
F orms of Teaching
» Lectures
on the web.
» Exams
» Laboratory Work
» laboratory assignments include measurements on optical
components and tracing and analysing of signaling messages.
» Consultations
» Regular consultations hours in four tems every week.
» Literature search on telecommunication systems and information
transport throught core network.
» Homeworks related to case studies.
Grading System
T ype
Homeworks
Class participation
Attendance
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
100 %
50 %
0%
0%
50 %
50 %
Percent of
Grade
15 %
10 %
5%
5%
25 %
30 %
10 %
Exam
T hreshold
Percent of
Grade
100 %
50 %
0%
0%
0%
15 %
10 %
5%
5%
50 %
50 %
15 %
Comment:
1. Transport technologies; Standards; Network topologies;
Telecommunicaton network organization: core and access network;
Transport network of Republic of Croatia; Multiplex systems; Network
layers; Transmission rate; Channel switching.
2. Packet switching; Transmission media: optical, copper and wireless; Basic
parameters. Digital modulation techniques. Line codes.
3. Speech and hearing propertie: power distribution, spectrum, intelligibility;
Telephony channel; Signalization network and CCSS No.7; Dependent
mutual syncronization; Sliding in PDH; F rame synchronization.
4. Network synchronization, plesiochronous and synchronous network.
Multiplexing systems with time, wavelength and code
division.Plesiochronous and synchronous digital hierarchy (SDH).
5. Optical transmission systems and networks; Basic system components and
limits; Optical link dimensioning; Wave division multiplex (WDM);
Protection and regeneration; Line coding.
435
6. Access networks: wire, wireless and optical; features, technologies and
application.
7. Metropolitan area networks (MAN). Technologies Ethernet and resilient
packet ring (RPR)
8. Mid-term exam.
9. Analog subscriber signalization. Dialing, analyzing of address, tones and
codes for display information.
Case studies.
10. Digital subscriber signaling system no.1 - Layers, reference points, ISDN
channels and protocols; PRA and BRA interfaces. Coding, spectrum and
transport rate.
11. Network signalling. Signalling system number 7 (SS7). SS7 network:
components, architectures, hierarchy and protocol. Service centralization.
SS7 - IP interconnections.
Case study.
12. Call and service interactions. Basic call and additional service. Call states.
Service interaction. Dialling in real time and numbering plane. ISDN
addressing.
13. Intelligent network (IN) components and architecure. IN basic call state
model, detection points. Intelligent network service processing. IN service
creation and standard IN services.
14. Switch and switching fabrics. Blocking and nonblocking switching
architectures. Space and time switching. Switching with memory. Self
routing, Banyan networks: Banynan, Delta, Omega.
15. F inal exam.
Literature
A. Bažant, G. Gledec, Ž. Ilić,
G. Ježić, M. Kos, M. Kunštić,
I. Lovrek, M. Matijašević, B.
Mikac, V. Sinković (2004).
Osnovne arhitekture mreža,
Element
R. Ramaswami, K. N.
Sivarajan (2002). Optical
Networks: A Practical
Perspective, Morgan
Kaufmann Publishers
J. Župan (1978). Uvod u
komutacijske sustave,
Školska knjiga
N. Kularatna, D. Dias (2004).
Essentials of Modern
Telecommunications Systems,
Artech House
Similar Courses
» F undamentals of Data Communications and Networking, University of
California Berkeley
» Breitbandnetze (72421), TU Munchen
» Data Communications (CE-NWK8), IEEE & ACM Computing Curricula
» Telecommunications II, EPF L Lausanne
» Transmission systems, University of Twente
436
Course Description
History of electrification. Mechanical calculations on overhead lines. Symmetrical
components. Inductance and Capacitance. Carson formulea. Transmission Theory.
Transmission equations. Ideal lines. Unloaded lines. Short circuit. Optimal
transmission. Mathematical models of lines. Pi model, T model, gamma model.
Power line transients. Distribution networks. Cable Networks. Cable
dimensioning and selection.
Study Programmes
E-learning Level
L1
Study Hours
Lecturers
Exercises
45
30
12
Goran Grdenić, mag. ing.
F rano Tomašević, dipl. ing.
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
E/C
L3
EEIT
English Level
C OM
Izv. prof. dr. sc.
Marko Delimar
4
C EA
Prof. dr. sc.
Ivica Pavić
ECT S Credits
60
70
80
90
Prerequisites
Energy Technology
EP E
Lecturers in Charge
127563
EC E
Transmission and Distribution of Electric Power
EL
WT
Learning Outcomes
IP
CS
CE
SEIS
1. Define the main principles of electric power transmission
2. Explain the function of electric transmission system elements
3. Analyze and calculate electric parameters of the elements of electric
transmission system
4. Analyze the electric circumstances of electric transmission system
5. Plan the development of electric transmission system
6. Choose new elements of electric transmission system
TI
Mechanical calculations on overhead lines. Calculation of electric parameters from
the electric tower geometry. Calculation of a steady state in power line operation.
Determination of voltage drops and active and reactive power losses. Cable
selection and dimensioning. Applications of commercial software in the
calculation of power line mechanical dimensioning, electric parameters and cable
selection and dimensioning.
F orms of Teaching
» Lectures
cycles. The first cycle consists of 7 weeks of lectures and 1st midter.
Second cycle has 6 weeks of lectures and final exam. The lectures are
given in total of 13 weeks, four hours per week.
437
» Exams
» midterm exam, final exam and oral exam
» Exercises
» 2 hours per week. The exercises follow the lectures with practical
and numerical examples. The focus is on the implementation of the
solution methods.
» Laboratory Work
» 6 laboratory exercises
» demonstration of equipment for the power transmission and
distribution (conductors, insulators and other equipment)
» Consultations
» Consultation term is determined on the first lecture in agreement
with the students.
» Other
» homeworks
Grading System
T ype
Homeworks
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
34 %
34 %
Percent of
Grade
10 %
10 %
25 %
35 %
20 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
10 %
10 %
50 %
50 %
30 %
1. Short history of electrification. Electric power networks (by voltage levels,
function, shape, etc.) Overhead-lines (conductors, poles and towers,
insulation, protective and other equipment).
2. Parameters for the mechanical calculation of overhead lines. Line length and
sag determination. Line state equations. montage tables.
3. Symmetrical components. Line resistance (temperature dependability, skin
effect). Like conductance. Corona and critical voltage.
4. Line inductance. Inductance determination in single-phase and three-phase
lines. Median geometric distances method.
5. Inductance determination with ground influence (Carson formulae). Matrix
methods in inductance determinations (direct and null system).
6. Line capacitance. Capacitance in single-phase and three-phase lines.
Ground influence. Matrix methods.
7. Transmission theory. General solution of transmission equations.
8. F orms of transmission equations.
9. Ideal line (unloaded, in short circuit, optimal power transmission). Real
line.
10. Mathematical models of lines (Pi-model, T-model, Gamma-model, etc.)
Determination of voltages and currents in static operation.
11. Transient phenomena on power lines. Transient resistance and travelling
waves. Examples with unloaded lines and grounded lines.
12. Distribution networks (by voltage levels, shape, load, grounding, etc.)
Voltage drops and power losses. Line dimensioning and selection.
438
13. Electric conditions in mashed distribution networks. Electric conditions in
distribution networks with two sided supply.
14. Cable networks. Electric power cables ( by insulation voltage level, etc.).
15. Electric cable dimensioning and selection. Distribution network grounding.
Literature
Marija Ožegović, Karlo
Ožegović (1996). Električne
energetske mreže, F ESB :
Opal computing
Atif Soubhi Debs (1988).
Modern Power System
Control and Operation,
Kluwer Academic
Publishers
J. Grainger, W. Stevenson
(1994). Power System
Analysis, McGraw-Hill
Similar Courses
» Elektrische Anlagen I, RWTH Aachen
» Elektrische Energiesysteme, ETH Zurich
439
Study Programmes
3rd year)
L1
Study Hours
Lecturers
Exercises
45
8
16
Lecturer
EP E
C EA
Dr. sc. Sanja Grubeša
Grading
Acceptable (2)
Good (3)
Very Good (4)
Excellent (5)
Due to small numbers of
students,we have specific
tresholds for marks.
50
61
76
90
Prerequisites
Physics 1
CE
Learning Outcomes
TI
CS
1. Define basic parameters of radiobroadcasting systems
2. Distinguish analog radiobroadcasting systems based on amplitude and
frequency modulation
3. Analyze digitalization steps of audiosignal depending on chosen sampling
frequency and quantization interval
4. Compare basic principles of audiocoding
5. Indicate basic differences between present systems for digital
radiobroadcasting
6. Identify problems of transition from analog to digital radiobroadcasting
systems
7. Explain organization of radio station
8. Define basics parameters which determine acoustic quality of sutios and
management rooms
EEIT
E-learning Level
C OM
L1
EC E
The goal of the subject is to qualify the students for use of modern radiobroadcasting systems and for working in radio stations. The following thematic
units are elaborated in detail: Analog radio-diffusion by using amplitude and
frequency modulations. Compander systems. Organization of operation for a radio
station. Technological spaces for storage, recording, editing and running the
program. Digitalization of audio signal. Audio compression and reduction based
on psychoacoustic models. Digital radio-diffusion. Transmission of additional
information. Audio transmission through public fixed and mobile communication
networks. Multichannel audio systems in multimedia transmission. Model of
audio transmission system for estimation of quality for the received signal.
Measurements and evaluation of the quality of audio transmission. Internet radio.
English Level
EL
Course Description
4
WT
Prof. dr. sc.
Hrvoje
Domitrović
ECT S Credits
IP
Lecturer in Charge
E/C
91853
SEIS
440
The subject offers a review of basics of audio transmission. The students study
classical systems for analog and digital radio-diffusion of audio, as well as modern
interactive systems used for radio-diffusion of multichannel audio. The students
also gain knowledge on the use of public communications for the purpose of
transmitting broadband signals.
F orms of Teaching
» Lectures
» Two lecturing cycles. duration of 1 st is 7 weeks and the second lasts
6 weeeks.
» Exams
» Midterm exam, F inal exam
» Exercises
» Auditory excercises
» Laboratory Work
» Laboratory will be organized through 6 excercises, each of 90
minutes duration.
» Demonstration
» Visiting professional radio-broadcating station with understanding
basics acoustics parameters of control rooms and studio design.
Grading System
T ype
Attendance
F inal Exam: Oral
Exam: Written
Exam: Oral
T hreshold
0%
0%
0%
0%
Percent of
Grade
20 %
5%
30 %
30 %
15 %
Exam
T hreshold
Percent of
Grade
0%
0%
0%
20 %
5%
0%
60 %
15 %
1. Introduction. Basics of sound and hearing process. Basic elements of
radicommunication system. Baseband and passband transmission.
2. Analog radiobroadcasting systems based on amplitude modulation.
Bandwidth of amplitude modulated signal. History of radiobroadcasting.
3. Analog radiobroadcasting systems based on frequency modulation.
Bandwidth of F M modulated signal. Carsons' rule. Steremultiplex. Radio
Data Signal.
4. Propagation of electromagnetic waves. Direct and reflected signals.
Doppler effect. Radiocommunication channel characteristics in time and
frequency.
5. Audio signal digitalization. Sampling frequency. Signal to noise ratio by
using multibit quantization with Nyquist sampling frequency.
6. Oversampling. Signal to noise ratio by using oversampling. Sigma delta
converters. Noise shaping.
441
7. Audio signal coding. F requency and temporal masking. MPEG coding.
8. Exam
9. Digital modulation systems. Digital modulation of amplitude and phase.
Quadrature amplitude modulation. Bits to symbols transformation.
Channel capacity.
10. Digital radiobroadcasting systems. Basics of Digital Audio Broadcasting
System (DAB) and DAB+ system. Channel coding. Time and frequency
interleaving.
11. Digital Radio Mondiale (DRM) and DRM+ system. Audio and channel
coding.
12. Basic characteristics of other digital radio broadcasting systems (DSR, ADR,
HD Radio, DVB-T, DVB-T2, DMB).Internet radio. RadioDNS.
13. Problems with transitions from analog to digital radio bradcasting systems.
Comparison between systems. Digital radio-broadcasting in Croatia.
14. Radio-station organization. Acoustic parameters of rooms.
15. F inal exam
Literature
John Watkinson (2001). The
MPEG Handbook, MPEG
1,2,4, F ocal Press
B. Modlic, I. Modlic (1995).
Modulacije i modulatori,
Školska knjiga
W. Hoegg, T. LauterBach
(2003). Digital Audio
Broadcasting, Wiley
E.A. Lee, D.G,
messerschmidt (1994).
Kluwer Academic Publishers
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442
ECT S Credits
4
English Level
L0
E-learning Level
L1
Study Hours
Lecturers
26
39
EEIT
Lecturer in Charge
155582
C EA
Izv. prof. dr. sc.
Tomislav Pribanić
EP E
Course Description
EC E
Study Programmes
TI
CS
CE
SEIS
IP
WT
EL
and Information Technology and Computing (Study) (skills, 4th semester, 2nd
year)
Computing (Study) (skills, 4th semester, 2nd year)
3rd year)
Grading System
T ype
E/C
Xamarin.Forms – cross-platform native mobile
apps development
C OM
T hreshold
Percent of
Grade
Exam
T hreshold
Percent of
Grade
443
Lecturers
444
Izv. prof. dr. sc. Andr e a Ag l i ćAl ji novi ć
Ana Anuš i ć , mag . math.
- Mathematics 3 - C (E, E)
- Pro bability and S tatis tics (L, L)
Ba r b a r a Ar b a na s , mag . ing .
- Co mputer Architecture 1 (LE, LE)
Doc. dr. sc. D ub r a vk o Ba b i ć
- Optical Co mmunicatio n T echno lo g y (L, L)
J os i p Ba čma g a , mag . ing .
- Electro nics 1 (E, E, LE, LE)
- Electro nics 2 (LE, LE)
Dr. sc. N i k o Ba k o
Doc. dr. sc. Ana Ba b i ć
- Co mputing Metho ds o f Mo dern Phy s ics (L, L)
- Phy s ics 1 (LE, LE)
J ur i ca Ba b i ć , mag . ing .
- Object- o riented pro g ramming (LE, LE)
P e ta r Ba k i ć , mag . math.
- Mathematics 1 (E, E)
- Pro bability and S tatis tics (E, E)
V e dr a na Ba l i če vi ć ,
mag .ing .inf.et.comm.techn.
- S ig nals and S y s tems (LE, LE)
Prof. dr. sc. Že l jk o Ba n
- Alarm S y s tems (L, L, LE, LE)
- Labo rato ry and S kills - Matlab (L, L)
Prof. dr. sc. Mi r ta Ba r a novi ć
- Databas es (L, L)
T i n Ba r i š a , mag . ing .
- Electrical Machines Co ntro l Practicum (LE, LE)
Izv. prof. dr. sc. Ma to Ba oti ć
- Auto matic Co ntro l (L, L)
Prof. dr. sc. Adr i ja n Ba r i ć
- Electro nics 1 (L, L)
Prof. dr. sc. D a nk o Ba s ch
- Co mputer Architecture 1 (L, L)
445
Prof. dr. sc. Al e n Ba ža nt
- Info rmatio n T heo ry (L, L)
Prof. dr. sc. Se a d Be r b e r ovi ć
- Electro mag netic Fields (L, L)
- Electro mechanics (L, L)
- Fundamentals o f Electrical Eng ineering (L, L)
Prof. dr. sc. V e dr a n Bi l a s
- Fundamentals o f Electro nic Meas urements and
Ins trumentatio n (L, L)
- Manag ement in Eng ineering (L, L)
- T echno lo g y in Medicine (L, L)
V i tomi r Bl a g oje vi ć , prof.
- Phy s ical Educatio n 1 (LE, LE)
Ra ul Bl e či ć , dipl. ing .
Prof. dr. sc. N i k ol a Bog unovi ć
- S o ftw are Des ig n (L, L)
Dr. sc. Ma r k o Bos i l je va c
- Electro nic Co mmunicatio ns (L, L)
- Optical Co mmunicatio n T echno lo g y (E, E, LE, LE)
Doc. dr. sc. Ivi ca Boti čk i
- Alg o rithms and Data S tructures (L, L)
- Applicatio n dev elo pment us ing C# pro g ramming
lang uag e (L, L)
- Object- o riented pro g ramming (L, L)
- Pro g ramming Paradig ms and Lang uag es (L, L)
Dr. sc. Ma r i o Br či ć
- Alg o rithms and Data S tructures (LE, LE)
Ma ja Be l l otti , mag . ing .
- Embedded S y s tems (LE, LE)
Dr. sc. T omi s l a v Be r i ć
Izv. prof. dr. sc. L a hor i ja Bi s tr i či ć
- Mo dern Phy s ics and Applicatio ns in Electrical
Eng ineering (L, L)
- Phy s ics 1 (L, L)
Izv. prof. dr. sc. Br uno Bl a š k ovi ć
- Info rmatio n, Lo g ic and Lang uag es (L, L)
Prof. dr. sc. Stje pa n Bog da n
- Co ntro l S y s tem Elements (L, L, LE, LE)
- Fundamentals o f Intellig ent Co ntro l S y s tems (L, L)
Dr. sc. D a r i o Boja nja c
Dr. sc. Iva na Bos ni ć
- Open Co mputing (LE, LE)
Dr. sc. J e l e na Bože k
- Dig ital Video (L, L, LE, LE)
- Electro nic Co mmunicatio ns (L, L, LE, LE)
Dr. sc. Ka r l a Br k i ć
- Interactiv e Co mputer Graphics (LE, LE)
446
Doc. dr. sc. L ji l ja na Br k i ć
- Databas es (L, L)
- Pro g ramming and S o ftw are Eng ineering (L, L)
Iva n Budi š ća k , dipl. ing .
- Pro g ramming and S o ftw are Eng ineering (LE, LE)
Doc. dr. sc. T omi s l a v Bur i ć
Prof. dr. sc. Stje pa n Ca r
Prof. dr. sc. Ma r i o Ci fr e k
- Co mputer Aided Des ig n o f Electro nic S y s tems (L, L)
Prof. dr. sc. N i k ol a Ča vl i na
- S us tainable Dev elo pment and Env iro nment (L, L)
Doc. dr. sc. V l a di mi r Če pe r i ć
J os i p Će s i ć , mag . ing .
- Auto matic Co ntro l (LE, LE)
- Labo rato ry and S kills - Matlab (LE, LE)
Izv. prof. dr. sc. Il k o Br ne ti ć
- Mathematics 1 (L, L)
Dr. sc. Ma r i o Buk a l
Doc. dr. sc. T omi s l a v Ca pude r
- Energ y T echno lo g y (E, E)
Izv. prof. dr. sc. Že l jk a Ca r
- Human Facto rs in Co mputing (L, L)
Ig or Cvi š i ć , dipl. ing .
- Auto matio n Practicum (LE, LE)
Doc. dr. sc. Ig or Ča vr a k
- Open Co mputing (L, L, LE, LE)
Doc. dr. sc. Ma r k o Čupi ć
- Artificial Intellig ence (L, L)
- Des ig n Patterns in S o ftw are Des ig n (L, L, LE, LE)
- Dig ital Lo g ic (L, L, LE, LE)
- Intro ductio n to Jav a Pro g ramming Lang uag e (L, L)
- PHP Applicatio n Dev elo pment B as ics (L, L)
- S o lv ing Optimizatio n Pro blems Us ing Ev o lutio nary
Co mputatio n Alg o rithms in Jav a (L, L)
Izv. prof. dr. sc. Ma r ti n D a di ć
- Electro mag netic Fields (L, L, LE, LE)
447
Prof. dr. sc. Boja na D a l b e l o-Ba š i ć
- S tatis tical Data Analy s is (L, L)
Dr. sc. G or a n D e l a č
- Intro ductio n to T heo retical Co mputer S cience (L, L,
E, E, LE, LE)
- Operating S y s tems (LE, LE)
- Pro g ramming Lang uag e T rans latio n (L, L, LE, LE)
Izv. prof. dr. sc. Ša ndor D e mb i tz
Doc. dr. sc. O g nje n D ob r i je vi ć
- Co mmunicatio n Netw o rks (L, L, LE, LE)
- Dig ital Lo g ic (L, L)
- Multimedia S erv ices (L, L, LE, LE)
Prof. dr. sc. Hr voje D omi tr ovi ć
- B as ics o f S o und Reco rding and Pro ces s ing (L, L)
- Electro aco us tics (L, L)
- T rans mis s io n o f Audio (L, L)
P a ul i na D učk i ć , mag . ing .
Al e n D us pa r a , mag . ing .
Dr. sc. Ma ti ja D ža nk o
- T eleco mmunicatio n S y s tems and Netw o rks (LE, LE)
Ml a de n Đ a l to , mag . ing .
Prof. dr. sc. N e na d D e b r e ci n
- S us tainable Dev elo pment and Env iro nment (L, L)
Izv. prof. dr. sc. Ma r k o D e l i ma r
- T rans mis s io n and Dis tributio n o f Electric Po w er (L,
L)
P e ta r D je r a s i movi ć , dipl. ing .
- Human Facto rs in Co mputing (LE, LE)
Doc. dr. sc. Mi r ja na D oma ze t-L oš o
L e on D r a g i ć , mag . ing . comp.
Doc. dr. sc. Kos je nk a D uma nči ć
- Co mmercial Law (L, L)
D omi ni k D ža ja , mag . ing .
- Electro nic Equipment Des ig n (LE, LE)
- T echno lo g y in Medicine (LE, LE)
Doc. dr. sc. Hr voje D ža po
- Co mputer Aided Des ig n o f Electro nic S y s tems (L, L)
- Electro nic Equipment Des ig n (L, L)
Doc. dr. sc. Ante Đ e r e k
- Co mpetitiv e Pro g ramming (L, L)
- Intro ductio n to T heo retical Co mputer S cience (L, L)
448
Ma r k o Đ ur a s e vi ć , mag . ing .
Prof. dr. sc. N e ve n E l e zovi ć
- Dis Co nt mathematics 1 (L, L)
- Dis Co nt mathematics 2 (L, L)
Izv. prof. dr. sc. Si ni š a Fa jt
- Audio and Co mputers (L, L)
Kr i s ti na Fe r k ovi ć , dipl. ing .
- Metro lo g y Fundamentals (E, E, LE, LE)
Prof. dr. sc. Kr e š i mi r Fe r ta l j
- Dev elo pment o f S o ftw are Applicatio ns (L, L)
P e ta r Fr a nče k , dipl. ing .
L uk a Fuće k , mag . ing .
- Co mputer- Co ntro lled S y s tems (LE, LE)
Prof. dr. sc. V l a do G l a vi ni ć
- Co mmunicatio n Netw o rks (L, L)
Izv. prof. dr. sc. Ma r i n G ol ub
- Operating S y s tems (L, L)
Izv. prof. dr. sc. Iva n Đ ur e k
- Audio technics (L, L)
Doc. dr. sc. Ig or E r ce g
- Electrical Machines Co ntro l Practicum (LE, LE)
- Electro mechanical S y s tems (L, L)
- Fundamentals o f Electrical Driv es (L, L)
Dr. sc. Boži da r Fe r e k -P e tr i ć
Doc. dr. sc. L uk a Fe r k ovi ć
- Metho ds o f Meas urement (L, L, LE, LE)
- Quality Manag ement (L, L)
Iva n Fi l k ovi ć , mag . ing . comp.
- Dig ital Lo g ic (LE, LE)
- S cripting Lang uag es (LE, LE)
N i k ol i na Fr i d , mag . ing . comp.
- S o ftw are Des ig n (LE, LE)
Ivi ca G a vr a ni ć
- Fundamentals o f Electrical Driv es (L)
Izv. prof. dr. sc. G or da n G l e de c
- Human Facto rs in Co mputing (L, L)
G or a n G r de ni ć , mag . ing .
- T rans mis s io n and Dis tributio n o f Electric Po w er (E,
E, LE, LE)
449
Dr. sc. Ma r i ja na G r e b l i čk i
Prof. dr. sc. Mi s l a v G r g i ć
- Dig ital Video (L, L)
Dr. sc. T omi s l a v G r g i ć
- Co mmunicatio n Netw o rks (LE, LE)
Doc. dr. sc. Stje pa n G r oš
- Adv anced Us e o f Linux Operating S y s tem (L, L)
- B as ic Us e o f Linux Operating S y s tem (L, L)
- S cripting Lang uag es (L, L)
Dr. sc. Sa nja G r ub e š a
- T rans mis s io n o f Audio (E, E)
Dr. sc. T a ma r a Ha dji na
Doc. dr. sc. J ur a j Ha ve l k a
- Adv anced LabVIEW (L, L)
- Electric Facilities Des ig n (L, L, LE, LE)
- LabVIEW (L, L)
Dr. sc. D a ni e l Hofma n
- Multimedia T echno lo g ies (E, E, LE, LE)
Izv. prof. dr. sc. D a vor G r g i ć
- Energ y T echno lo g y (L, L)
- Po w er Plants (L, L)
Prof. dr. sc. Sonja G r g i ć
- Multimedia T echno lo g ies (L, L)
Ka r l o G r i pa r i ć , mag . ing . el.
- Co ntro l S y s tem Elements (LE, LE)
Dr. sc. D a ni je l a G r ozda ni ć
Ma r k o G ul i n , mag . ing . el.
- Electrical Circuits (LE, LE)
Zl a tk o Ha ni ć , dipl. ing .
- Electro mechanical and Electrical Co nv ers io n (E, E, LE,
LE)
Doc. dr. sc. Hr voje He g e duš
- Adv anced LabVIEW (LE)
- Adv anced LabVIEW (LE)
- Electro mag netic Fields (LE)
- Electro mag netic Fields (LE)
- Fundamentals o f Electrical Eng ineering (LE)
- Fundamentals o f Electrical Eng ineering (LE)
- Intro ductio n Into Fault Finding (L)
- Intro ductio n Into Fault Finding (L)
- LabVIEW (LE)
- LabVIEW (LE)
- Metro lo g y Fundamentals (LE)
- Metro lo g y Fundamentals (LE)
N i nos l a v Hol je va c , mag . ing .
- Po w er Plants (E, E)
450
Prof. dr. sc. Ha na Hor a k
- Co mmercial Law (L, L)
Doc. dr. sc. L a na Hor va t D mi tr ovi ć
Doc. dr. sc. T omi s l a v Hr k a ć
- Intro ductio n to the S cala pro g ramming lang uag e (L,
L)
L uk a Hums k i ,
- Fundamentals o f Electrical Eng ineering (LE, LE)
P e r i ca Il a k , mag . ing .
- Electric Facilities (LE, LE)
Prof. dr. sc. D a mi r Il i ć
- Metro lo g y Fundamentals (L, L)
Doc. dr. sc. Sa š a Il i ji ć
Dr. sc. Kr unos l a v Ive š i ć
Dr. sc. Br a ni mi r Ivš i ć
- Ches s (LE, LE)
Dr. sc. Ma r k o Hor va t
- Audio technics (L, L, LE, LE)
- B as ics o f S o und Reco rding and Pro ces s ing (L, L, LE,
LE)
- Electro aco us tics (LE, LE)
Prof. dr. sc. Si l vi o Hr a b a r
- Applied Electro mag netics (L, L, E, E)
Eng ineering (L, L)
Prof. dr. sc. D a r k o Hul je ni ć
N i k ol a Hur e , mag . ing .
Dr. sc. Ša ndor Il e š
- Electro mechanical S y s tems (E, E, LE, LE)
- Fundamentals o f Mechatro nics (L, L, LE, LE)
Doc. dr. sc. Že l jk o Il i ć
- Lo cal Area Netw o rks (L, L, LE, LE)
Antun Iva novi ć , mag . ing .
Dr. sc. D a nk o Ivoš e vi ć
D a vor J a dr i je vi ć
451
T omi s l a v J a g uš t , dipl. ing .
- Pro g ramming Paradig ms and Lang uag es (LE, LE)
Prof. dr. sc. Že l jk o J a k opovi ć
- Po w er Electro nics Practicum (L, L)
Dr. sc. Ža r k o J a ni ć
Doc. dr. sc. L e ona r do J e l e nk ovi ć
Prof. dr. sc. Br a nk o J e r e n
- S ig nals and S y s tems (L, L)
Prof. dr. sc. G or da n J e ži ć
- Public Mo bile Netw o rk (L, L)
Doc. dr. sc. Ma r k o J ur če vi ć
- Adv anced LabVIEW (LE, LE)
- Intro ductio n Into Fault Finding (L, L)
- LabVIEW (LE, LE)
- Metro lo g y Fundamentals (LE, LE)
Izv. prof. dr. sc. D r a že n J ur i š i ć
- Electrical Circuits (L, L, LE, LE)
Prof. dr. sc. D a mi r Ka l pi ć
Izv. prof. dr. sc. D oma g oj J a k ob ovi ć
Izv. prof. dr. sc. Kr i s ti a n J a mb r oš i ć
- S o und and Env iro nment (L, L)
Mr. sc. Ra domi r J e čme ni ca
T i no J e r či ć , mag . ing .
- Electro mechanical and Electrical Co nv ers io n (LE, LE)
- Fundamentals o f Electrical Driv es (E, E, LE, LE)
Prof. dr. sc. D r a g a n J e vti ć
- Co mputer- T elepho ny Integ ratio n (L, L)
- T eleco mmunicatio n S y s tems and Netw o rks (L, L)
Dr. sc. Al a n J ovi ć
- S o ftw are Des ig n (L, L, LE, LE)
D a r k o J ur i ć , mag . ing .
Izv. prof. dr. sc. Zor a n Ka l a fa ti ć
Ml a de n Ka r a n , mag . ing . comp.
- Artificial Intellig ence (LE, LE)
452
N e na d Ka ta ni ć , mag . ing .
- Dev elo pment o f S o ftw are Applicatio ns (LE, LE)
Doc. dr. sc. J os i p Kne zovi ć
T i homi r Kne že vi ć , dipl. ing .
Prof. dr. sc. Fe ta h Kol oni ć
- Electrical Machines Co ntro l Practicum (L, L)
- Fundamentals o f Mechatro nics (L, L)
Prof. dr. sc. L uk a Kor k ut
Doc. dr. sc. Zvonk o Kos ta njča r
- Electrical Circuits (L, L, LE, LE)
- S ig nals and S y s tems (L, L, LE, LE)
Doc. dr. sc. D oma g oj Kova če vi ć
- Mathematics 3 - C (L, L)
Prof. dr. sc. Zde nk o Kova či ć
- Co ntro l S y s tem Elements (L, L)
- Fundamentals o f Intellig ent Co ntro l S y s tems (L, L)
- Ro bo tics Practicum (L, L)
Iva n Kr e š o , mag . ing . comp.
D a mja n Ka tuš i ć , mag . ing .
- Public Mo bile Netw o rk (LE, LE)
Prof. dr. sc. P e ta r Kne že vi ć
E di n Kočo , mag . ing .
Doc. dr. sc. Ma r k o Kor i či ć
Prof. dr. sc. T omi s l a v Kos
- Public Mo bile Netw o rk (L, L)
- Radio Nav ig atio n (L, L)
Prof. dr. sc. Ma r i o Kova č
Ma r i nk o Kova či ć , dipl. ing .
- Po w er Electro nics Practicum (LE, LE)
Prof. dr. sc. Sl a vk o Kr a jca r
- Electric Facilities (L, L)
- Lo w - v o ltag e Po w er S y s tems (L, L)
Dr. sc. Mi l je nk o Kr he n
- Audio and Co mputers (LE, LE)
- S o und and Env iro nment (LE, LE)
- T rans mis s io n o f Audio (LE, LE)
453
Sa b i na Kr i ve c , mag . ing .
Izv. prof. dr. sc. Ig or Kr oi s
Izv. prof. dr. sc. Ma r i o Kuš e k
- Info rmatio n, Lo g ic and Lang uag es (L, L)
- S erv ice and Applicatio n Dev elo pment fo r Operating
S y s tem Andro id (L, L)
Prof. dr. sc. Ig or Kuzl e
Kr uno L e na c , mag . ing .
Dr. sc. V i nk o L e š i ć
Dr. sc. Snje ža na L ub ur a
Ma r k o Ma g e r l , mag . ing .
Prof. dr. sc. Kr e š i mi r Ma l a r i ć
- Ches s (L, L, LE, LE)
Izv. prof. dr. sc. Ma r i o Kr ni ć
Ivi ca Kunš t , dipl. ing .
- Electro mag netic Fields (LE, LE)
Dr. sc. Ma r ti na Kuti ja
- Electrical Machines Co ntro l Practicum (L, L, E, E, LE,
LE)
Izv. prof. dr. sc. Ig or L a ck ovi ć
- Electrical Circuits (L, L)
Izv. prof. dr. sc. Iva n L e ni če k
- Metho ds o f Meas urement (L, L, LE, LE)
Prof. dr. sc. Sve n L onča r i ć
- Info rmatio n Pro ces s ing (L, L)
Dr. sc. Že l jk a L uče v V a s i ć
- Co mputer Aided Des ig n o f Electro nic S y s tems (L, L,
LE, LE)
Prof. dr. sc. Ra tk o Ma g ja r e vi ć
Prof. dr. sc. Roma n Ma l a r i ć
- Adv anced LabVIEW (L, L)
- Eco no mics and Manag erial Decis io n Making (L, L)
- LabVIEW (L, L)
- Metro lo g y Fundamentals (L, L)
454
Prof. dr. sc. Zl a tk o Ma l jk ovi ć
- Electro mechanical and Electrical Co nv ers io n (L, L)
Dr. sc. T vr tk o Ma ndi ć
- Electro nics 1 (L, L, E, E, LE, LE)
Prof. dr. sc. L jub o Ma r a ng uni ć
Dr. sc. Iva n Ma r k ovi ć
Ani ta Ma r ti nče vi ć , mag . ing .
Prof. dr. sc. Ma ja Ma ti ja š e vi ć
Izv. prof. dr. sc. Kr e š i mi r Ma tk ovi ć
- Intro ductio n to Virtual Env iro nments (L, L)
Iva n Ma ur ovi ć , mag . ing . el.
Prof. dr. sc. Že l jk a Mi ha jl ovi ć
- Interactiv e Co mputer Graphics (L, L, LE, LE)
Fi l i p Ma ndi ć , mag . ing .
Ma r i jo Ma r a či ć , dipl. ing .
Dr. sc. D a r i ja n Ma r če ti ć
N e na d Ma r k uš , mag . ing .
- Info rmatio n T heo ry (LE, LE)
- Intro ductio n to Virtual Env iro nments (LE, LE)
Prof. dr. sc. Ante Ma r uš i ć
- Electric Facilities (L, L)
- Electric Facilities Des ig n (L, L)
Dr. sc. Ma r i o Ma ti je vi ć
Izv. prof. dr. sc. J a dr a nk o Ma tuš k o
- Fundamentals o f Mechatro nics (L, L)
Doc. dr. sc. Ig or Me k te r ovi ć
- Databas es (L, L)
L e nk a Mi hok ovi ć , mag . math.
455
Prof. dr. sc. N e ve n Mi ja t
- Electrical Circuits (L, L)
Dr. sc. D a mja n Mi k l i ć
- Fundamentals o f Intellig ent Co ntro l S y s tems (LE,
LE)
- Pro g raming fo r the Ro bo t Operating S y s tem (L, L)
- Ro bo tics Practicum (LE, LE)
Doc. dr. sc. Bor i s Mi l a š i novi ć
- Dev elo pment o f S o ftw are Applicatio ns (L, L)
Izv. prof. dr. sc. J os i pa P i na Mi l i š i ć
D a ni je l Ml i na r i ć , dipl. ing .
- Databas es (LE, LE)
- Pro g ramming Paradig ms and Lang uag es (LE, LE)
Prof. dr. sc. Bor i voj Modl i c
Dr. sc. P e ta r Mos ta r a c
- Adv anced LabVIEW (LE, LE)
- LabVIEW (LE, LE)
- Metro lo g y Fundamentals (LE, LE)
Dr. sc. D a mi r Muha
- Applied Electro mag netics (LE, LE)
Doc. dr. sc. Zor a n N a r a nči ć
Ig or Mi ji ć , mag . ing .
Izv. prof. dr. sc. Mi l je nk o Mi k uc
- Netw o rk Pro g ramming (L, L)
Dr. sc. Si ni š a Mi l i či ć
- Labo rato ry and S kills - Maths o n the Co mputer (LE,
LE)
- Mathematical Mo deling o f Co mputer (LE, LE)
Doc. dr. sc. N i k ol a Mi š k ovi ć
Izv. prof. dr. sc. Hr voje Ml i na r i ć
- Embedded S y s tems (L, L)
Prof. dr. sc. V e dr a n Mor na r
- Pro g ramming Paradig ms and Lang uag es (L, L)
Dr. sc. Iva n Mr če l a
LE)
- Po w er Electro nics Practicum (L, L, LE, LE)
Prof. dr. sc. Rob e r t N a đ
- Mo bile Co mmunicatio ns (L, L)
Dr. sc. Iva na N i že ti ć Kos ovi ć
- Dev elo pment o f S o ftw are Applicatio ns (L, L, LE, LE)
456
Andr e j N ova k , mag . math.
- Mathematics 3 - EE (E, E)
Br a ni mi r N ovos e l ni k , mag . ing .
Dr. sc. P r e dr a g P a l e
- S kills o f Co mmunicatio n (L, L)
Prof. dr. sc. Ig or Sunda y P a ndži ć
- Intro ductio n to Virtual Env iro nments (L, L)
Prof. dr. sc. Ma r i o O s vi n P a vče vi ć
Prof. dr. sc. Ar mi n P a vi ć
Zvoni mi r P a vl i ć , mag . ing . comp.
- Intro ductio n to T heo retical Co mputer S cience (E, E,
LE, LE)
- Pro g ramming Lang uag e T rans latio n (E, E, LE, LE)
Prof. dr. sc. N e dje l jk o P e r i ć
Doc. dr. sc. Antoni o P e toš i ć
- Audio technics (L, L)
- T rans mis s io n o f Audio (L, L, LE, LE)
L e ona r d N ovos e l , mag . ing .
- Electro nic Co mmunicatio ns (LE, LE)
- Mo bile Co mmunicatio ns (LE, LE)
Dr. sc. Ma tk o O r s a g
- Ro bo tics Practicum (LE, LE)
Doc. dr. sc. Hr voje P a ndži ć
- Po w er Plants (E, E)
Prof. dr. sc. Me r va n P a š i ć
- Labo rato ry and S kills - Maths o n the Co mputer (L, L)
- Mathematical Mo deling o f Co mputer (L, L)
Ma r k o P a ve l i ć , mag . ing .
- Info rmatio n, Lo g ic and Lang uag es (LE, LE)
- Intro ductio n to Virtual Env iro nments (LE, LE)
Prof. dr. sc. Ivi ca P a vi ć
- T echnical S tandardizatio n and Leg is lativ e (L, L)
- T rans mis s io n and Dis tributio n o f Electric Po w er (L,
L)
Dr. sc. T omi s l a v P a vl ovi ć
- Alarm S y s tems (LE, LE)
Prof. dr. sc. T omi s l a v P e tk ovi ć
- Mo dern Metho ds o f Phy s ics fo r Electrical
Eng ineering and Info rmatio n T echno lo g y (L, L)
Prof. dr. sc. D a vor P e tr i novi ć
457
Prof. dr. sc. Iva n P e tr ovi ć
- Co mputer- Co ntro lled S y s tems (L, L)
J ur a j P e tr ovi ć ,
- S ig nals and S y s tems (LE, LE)
Dr. sc. T a ma r a P e tr ovi ć
Doc. dr. sc. D a mi r P i nta r
- Databas es (L, L)
- Fundamentals o f Electrical Eng ineering (L, L, LE, LE)
- Intro ductio n to R pro g ramming lang uag e (L, L)
Izv. prof. dr. sc. Iva na P odna r Ža r k o
- Multimedia S erv ices (L, L)
Dr. sc. Mi r k o P ol ja k
P a vl e P r e nta š i ć , mag . ing . comp.
- Info rmatio n Pro ces s ing (LE, LE)
Doc. dr. sc. Kr e š i mi r P r i puži ć
- S erv ice and Applicatio n Dev elo pment fo r Operating
S y s tem Andro id (L, L)
Ma r i na P ti če k , mag . ing .
- Databas es (LE, LE)
Dr. sc. Iva n Ra jš l
- Electric Facilities (E, E, LE, LE)
Ig or P i l ji ć , mag . ing . comp.
Doc. dr. sc. Sa nda P l e s l i ć
- Intro ductio n to phy s ics (L, L)
Doc. dr. sc. V e dr a n P odob ni k
- App S tart Co ntes t (L, L)
Doc. dr. sc. Si ni š a P opovi ć
Izv. prof. dr. sc. T omi s l a v P r i b a ni ć
- Xamarin.Fo rms - cro s s - platfo rm nativ e mo bile apps
dev elo pment (L, L)
Dr. sc. Ana P r l i ć
Dr. sc. G or a n Ra dunovi ć
- Mathematics 2 (L, L, E, E)
- Mathematics 3 - EE (E, E)
Doc. dr. sc. Mi r k o Ra ndi ć
458
Dr. sc. Ma ja Re s ma n
Izv. prof. dr. sc. D ub r a vk o Sa b ol i ć
Doc. dr. sc. Ma r i ja Se de r
Ig or Si r oti ć , mag . ing .
- Fundamentals o f Electrical Driv es (E, E, LE, LE)
Doc. dr. sc. L e a Sk or i n-Ka pov
- Multimedia S erv ices (L, L, LE, LE)
Ma r ti n Sol di ć , mag . ing .
Prof. dr. sc. Si ni š a Sr b l ji ć
- Pro g ramming Lang uag e T rans latio n (L, L)
Antoni o Sta r či ć , mag . ing .
Dr. sc. Stje pa n Sti pe ti ć
LE)
Prof. dr. sc. Sl ob oda n Ri b a r i ć
- Intro ductio n to Pattern Reco g nitio n (L, L)
D e ni s Sa l ope k , mag . ing .
- Netw o rk Pro g ramming (LE, LE)
Prof. dr. sc. D a mi r Se r š i ć
Prof. dr. sc. Zor a n Sk oči r
- Databas es (L, L)
Iva n Sl i va r , mag . ing .
- Multimedia S erv ices (LE, LE)
Dr. sc. Ana Sovi ć Kr ži ć
- S ig nals and S y s tems (L, L, LE, LE)
Izv. prof. dr. sc. V l a do Sr uk
- S o ftw are Des ig n (L, L)
Ma r i o Sti pči ć , mag . math.
Doc. dr. sc. Ma r k o Sub a š i ć
459
Dr. sc. Mi a Suha ne k
- S o und and Env iro nment (L, L, LE, LE)
Doc. dr. sc. D a mi r Sumi na
- Electrical Machines Co ntro l Practicum (L, L)
Stje pa n Še b e k , mag . math.
G or a n Še k e ta , mag . ing .
- Electro nic Equipment Des ig n (LE, LE)
Izv. prof. dr. sc. T omi s l a v Ši k i ć
Prof. dr. sc. D i na Ši muni ć
- T echnical S tandardizatio n and Leg is lativ e (L, L)
Izv. prof. dr. sc. G or da n Ši š ul
- Mo bile Co mmunicatio ns (L, L)
Doc. dr. sc. D e ja n Šk vor c
LE, LE)
Prof. dr. sc. Že l jk o Šti h
Prof. dr. sc. T omi s l a v Sul i g oj
Doc. dr. sc. Si ni š a Ša de k
- Energ y T echno lo g y (L, L, E, E)
Izv. prof. dr. sc. Si ni š a Še g vi ć
- Des ig n Patterns in S o ftw are Des ig n (L, L, LE, LE)
Izv. prof. dr. sc. Mi l e Ši k i ć
Dr. sc. Ma r i n Ši l i ć
E, E, LE, LE)
Prof. dr. sc. Zvoni mi r Ši puš
Eng ineering (L, L)
- Optical Co mmunicatio n T echno lo g y (L, L)
Fr a no Šk opl ja na c-Ma či na , dipl. ing .
- Info rmatio n, Lo g ic and Lang uag es (LE, LE)
Doc. dr. sc. J a n Šna jde r
- Pro g ramming in Has kell (L, L, LE, LE)
Hr voje Šti ma c , mag . ing .
460
D a r k o Štr i g a , mag . ing .
- App S tart Co ntes t (LE, LE)
Prof. dr. sc. V i k tor Šunde
- Po w er Electro nics Practicum (L, L)
Prof. dr. sc. Se ji d T e š nja k
Prof. dr. sc. T omi s l a v T omi š a
- Pro ces s Meas urements and Diag no s tic in Po w er
Plants (L, L)
Dr. sc. D i ja na T r a l i ć
- Multimedia T echno lo g ies (L, L, E, E, LE, LE)
Doc. dr. sc. Kr e š i mi r T r ontl
Prof. dr. sc. Ivo U g l e š i ć
- Electro mag netic T rans ients and Electro mag netic
Co mpatibility (L, L)
G or a n V a s i l je vi ć , dipl. ing .
Doc. dr. sc. Ig or V e l či ć
Ma ti ja Šul c , mag . ing .
- Info rmatio n T heo ry (LE, LE)
- Lo cal Area Netw o rks (LE, LE)
Sa š a T e pi ć , mag . ing .
- Co mputer Aided Des ig n o f Electro nic S y s tems (LE,
LE)
Fr a no T oma š e vi ć , dipl. ing .
- T rans mis s io n and Dis tributio n o f Electric Po w er (E,
E)
Izv. prof. dr. sc. Že l jk o T omš i ć
- Energ y Efficiency Audit and Energ y Manag ement
Pro g ramme (L, L)
Doc. dr. sc. Boja n T r k ul ja
Ma r ti n T ute k , mag . ing .
- Artificial Intellig ence (LE, LE)
Doc. dr. sc. D a r k o V a s i ć
- Fundamentals o f Electro nic Meas urements and
Ins trumentatio n (L, L, E, E, LE, LE)
Izv. prof. dr. sc. Ma r i o V a š a k
- Auto matio n Practicum (L, L, LE, LE)
Dr. sc. Kl e mo V l a di mi r
E, E, LE, LE)
461
Dr. sc. D oma g oj V l a h
Izv. prof. dr. sc. Ma r i o V r a ži ć
- Electrical Actuato rs (L, L)
Prof. dr. sc. Ml a de n V uči ć
J os i p V uk ovi ć , mag . ing .
- Multimedia T echno lo g ies (LE, LE)
- Radio Nav ig atio n (LE, LE)
D a mi r V ul ja j , mag . ing .
Dr. sc. D a vor Za l uš k i
- Applied Electro mag netics (E, E, LE, LE)
Prof. dr. sc. Ma r i o Ža g a r
- Open Co mputing (L, L)
Doc. dr. sc. Ana Žg a l ji ć Ke k o
Dr. sc. Sa nja Žonja
Dr. sc. Mi ha e l a V r a ni ć
- Intro ductio n to R pro g ramming lang uag e (L, L)
Izv. prof. dr. sc. Bor i s V r dol ja k
- Databas es (L, L)
Prof. dr. sc. Zor a n V uk i ć
Doc. dr. sc. Ma r i n V uk ovi ć
Doc. dr. sc. Sl a ve n Za k oš e k
- Databas es (L, L)
Ma r k o Ze c , dipl. ing .
Izv. prof. dr. sc. D a mi r Ža r k o
- Fundamentals o f Electrical Driv es (L, L)
J os i p Ži l a k , dipl. ing .
Prof. dr. sc. D a r k o Žub r i ni ć
462
Sa r a Žul j , mag . ing .
T omi s l a v Župa n , dipl. ing .
Prof. dr. sc. V e s na Župa novi ć
- Mathematics 3 - EE (L, L)
463

ECTS Information Package for Academic Year 2016/2017

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