Untitled - International Journal of Soft Computing and Engineering

Editor In Chief
Dr. Shiv K Sahu
Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT)
Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal (M.P.), India
Dr. Shachi Sahu
Ph.D. (Chemistry), M.Sc. (Organic Chemistry)
Additional Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal (M.P.), India
Vice Editor In Chief
Dr. Vahid Nourani
Professor, Faculty of Civil Engineering, University of Tabriz, Iran
Prof.(Dr.) Anuranjan Misra
Professor & Head, Computer Science & Engineering and Information Technology & Engineering, Noida International University,
Noida (U.P.), India
Chief Advisory Board
Prof. (Dr.) Hamid Saremi
Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran
Dr. Uma Shanker
Professor & Head, Department of Mathematics, CEC, Bilaspur(C.G.), India
Dr. Rama Shanker
Professor & Head, Department of Statistics, Eritrea Institute of Technology, Asmara, Eritrea
Dr. Vinita Kumari
Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., India
Dr. Kapil Kumar Bansal
Head (Research and Publication), SRM University, Gaziabad (U.P.), India
Dr. Deepak Garg
Professor, Department of Computer Science and Engineering, Thapar University, Patiala (Punjab), India, Senior Member of IEEE,
Secretary of IEEE Computer Society (Delhi Section), Life Member of Computer Society of India (CSI), Indian Society of Technical
Education (ISTE), Indian Science Congress Association Kolkata.
Dr. Vijay Anant Athavale
Director of SVS Group of Institutions, Mawana, Meerut (U.P.) India/ U.P. Technical University, India
Dr. T.C. Manjunath
Principal & Professor, HKBK College of Engg, Nagawara, Arabic College Road, Bengaluru-560045, Karnataka, India
Dr. Kosta Yogeshwar Prasad
Director, Technical Campus, Marwadi Education Foundation’s Group of Institutions, Rajkot-Morbi Highway, Gauridad, Rajkot,
Gujarat, India
Dr. Dinesh Varshney
Director of College Development Counceling, Devi Ahilya University, Indore (M.P.), Professor, School of Physics, Devi Ahilya
University, Indore (M.P.), and Regional Director, Madhya Pradesh Bhoj (Open) University, Indore (M.P.), India
Dr. P. Dananjayan
Professor, Department of Department of ECE, Pondicherry Engineering College, Pondicherry,India
Dr. Sadhana Vishwakarma
Associate Professor, Department of Engineering Chemistry, Technocrat Institute of Technology, Bhopal(M.P.), India
Dr. Kamal Mehta
Associate Professor, Deptment of Computer Engineering, Institute of Technology, NIRMA University, Ahmedabad (Gujarat), India
Dr. CheeFai Tan
Faculty of Mechanical Engineering, University Technical, Malaysia Melaka, Malaysia
Dr. Suresh Babu Perli
Professor& Head, Department of Electrical and Electronic Engineering, Narasaraopeta Engineering College, Guntur, A.P., India
Dr. Binod Kumar
Associate Professor, Schhool of Engineering and Computer Technology, Faculty of Integrative Sciences and Technology, Quest
International University, Ipoh, Perak, Malaysia
Dr. Chiladze George
Professor, Faculty of Law, Akhaltsikhe State University, Tbilisi University, Georgia
Dr. Kavita Khare
Professor, Department of Electronics & Communication Engineering., MANIT, Bhopal (M.P.), INDIA
Dr. C. Saravanan
Associate Professor (System Manager) & Head, Computer Center, NIT, Durgapur, W.B. India
Dr. S. Saravanan
Professor, Department of Electrical and Electronics Engineering, Muthayamal Engineering College, Resipuram, Tamilnadu, India
Dr. Amit Kumar Garg
Professor & Head, Department of Electronics and Communication Engineering, Maharishi Markandeshwar University, Mulllana,
Ambala (Haryana), India
Dr. T.C.Manjunath
Principal & Professor, HKBK College of Engg, Nagawara, Arabic College Road, Bengaluru-560045, Karnataka, India
Dr. P. Dananjayan
Professor, Department of Department of ECE, Pondicherry Engineering College, Pondicherry, India
Dr. Kamal K Mehta
Associate Professor, Department of Computer Engineering, Institute of Technology, NIRMA University, Ahmedabad (Gujarat), India
Dr. Rajiv Srivastava
Director, Department of Computer Science & Engineering, Sagar Institute of Research & Technology, Bhopal (M.P.), India
Dr. Chakunta Venkata Guru Rao
Professor, Department of Computer Science & Engineering, SR Engineering College, Ananthasagar, Warangal, Andhra Pradesh, India
Dr. Anuranjan Misra
Professor, Department of Computer Science & Engineering, Bhagwant Institute of Technology, NH-24, Jindal Nagar, Ghaziabad,
India
Dr. Robert Brian Smith
International Development Assistance Consultant, Department of AEC Consultants Pty Ltd, AEC Consultants Pty Ltd, Macquarie
Centre, North Ryde, New South Wales, Australia
Dr. Saber Mohamed Abd-Allah
Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Yue Yang Road, Shanghai,
China
Dr. Himani Sharma
Professor & Dean, Department of Electronics & Communication Engineering, MLR Institute of Technology, Laxman Reddy Avenue,
Dundigal, Hyderabad, India
Dr. Sahab Singh
Associate Professor, Department of Management Studies, Dronacharya Group of Institutions, Knowledge Park-III, Greater Noida,
India
Dr. Umesh Kumar
Principal: Govt Women Poly, Ranchi, India
Dr. Syed Zaheer Hasan
Scientist-G Petroleum Research Wing, Gujarat Energy Research and Management Institute, Energy Building, Pandit Deendayal
Petroleum University Campus, Raisan, Gandhinagar-382007, Gujarat, India.
Dr. Jaswant Singh Bhomrah
Director, Department of Profit Oriented Technique, 1 – B Crystal Gold, Vijalpore Road, Navsari 396445, Gujarat. India
Technical Advisory Board
Dr. Mohd. Husain
Director, MG Institute of Management & Technology, Banthara, Lucknow (U.P.), India
Dr. T. Jayanthy
Principal, Panimalar Institute of Technology, Chennai (TN), India
Dr. Umesh A.S.
Director, Technocrats Institute of Technology & Science, Bhopal(M.P.), India
Dr. B. Kanagasabapathi
Infosys Labs, Infosys Limited, Center for Advance Modeling and Simulation, Infosys Labs, Infosys Limited, Electronics City,
Bangalore, India
Dr. C.B. Gupta
Professor, Department of Mathematics, Birla Institute of Technology & Sciences, Pilani (Rajasthan), India
Dr. Sunandan Bhunia
Associate Professor & Head,, Dept. of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia, West
Bengal, India
Dr. Jaydeb Bhaumik
Associate Professor, Dept. of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia, West Bengal, India
Dr. Rajesh Das
Associate Professor, School of Applied Sciences, Haldia Institute of Technology, Haldia, West Bengal, India
Dr. Mrutyunjaya Panda
Professor & Head, Department of EEE, Gandhi Institute for Technological Development, Bhubaneswar, Odisha, India
Dr. Mohd. Nazri Ismail
Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia
Dr. Haw Su Cheng
Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia, 63100 Cyberjaya
Dr. Hossein Rajabalipour Cheshmehgaz
Industrial Modeling and Computing Department, Faculty of Computer Science and Information Systems, Universiti Teknologi
Malaysia (UTM) 81310, Skudai, Malaysia
Dr. Sudhinder Singh Chowhan
Associate Professor, Institute of Management and Computer Science, NIMS University, Jaipur (Rajasthan), India
Dr. Neeta Sharma
Professor & Head, Department of Communication Skils, Technocrat Institute of Technology, Bhopal(M.P.), India
Dr. Ashish Rastogi
Associate Professor, Department of CSIT, Guru Ghansi Das University, Bilaspur (C.G.), India
Dr. Santosh Kumar Nanda
Professor, Department of Computer Science and Engineering, Eastern Academy of Science and Technology (EAST), Khurda (Orisa),
India
Dr. Hai Shanker Hota
Associate Professor, Department of CSIT, Guru Ghansi Das University, Bilaspur (C.G.), India
Dr. Sunil Kumar Singla
Professor, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala (Punjab), India
Dr. A. K. Verma
Professor, Department of Computer Science and Engineering, Thapar University, Patiala (Punjab), India
Dr. Durgesh Mishra
Chairman, IEEE Computer Society Chapter Bombay Section, Chairman IEEE MP Subsection, Professor & Dean (R&D), Acropolis
Institute of Technology, Indore (M.P.), India
Dr. Xiaoguang Yue
Associate Professor, College of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China
Dr. Veronica Mc Gowan
Associate Professor, Department of Computer and Business Information Systems,Delaware Valley College, Doylestown, PA, Allman
China
Dr. Mohd. Ali Hussain
Professor, Department of Computer Science and Engineering, Sri Sai Madhavi Institute of Science & Technology, Rajahmundry
(A.P.), India
Dr. Mohd. Nazri Ismail
Professor, System and Networking Department, Jalan Sultan Ismail, Kaula Lumpur, MALAYSIA
Dr. Sunil Mishra
Associate Professor, Department of Communication Skills (English), Dronacharya College of Engineering, Farrukhnagar, Gurgaon
(Haryana), India
Dr. Labib Francis Gergis Rofaiel
Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology,
Mansoura City, Egypt
Dr. Pavol Tanuska
Associate Professor, Department of Applied Informetics, Automation, and Mathematics, Trnava, Slovakia
Dr. VS Giridhar Akula
Professor, Avanthi's Research & Technological Academy, Gunthapally, Hyderabad, Andhra Pradesh, India
Dr. S. Satyanarayana
Associate Professor, Department of Computer Science and Engineering, KL University, Guntur, Andhra Pradesh, India
Dr. Bhupendra Kumar Sharma
Associate Professor, Department of Mathematics, KL University, BITS, Pilani, India
Dr. Praveen Agarwal
Associate Professor& Head, Department of Mathematics, Anand International College of Engineering, Jaipur (Rajasthan), India
Dr. Manoj Kumar
Professor, Department of Mathematics, Rashtriya Kishan Post Graduate Degree, College, Shamli, Prabudh Nagar, (U.P.), India
Dr. Shaikh Abdul Hannan
Associate Professor, Department of Computer Science, Vivekanand Arts Sardar Dalipsing Arts and Science College, Aurangabad
(Maharashtra), India
Dr. K.M. Pandey
Professor, Department of Mechanical Engineering,National Institute of Technology, Silchar, India
Prof. Pranav Parashar
Technical Advisor, International Journal of Soft Computing and Engineering (IJSCE), Bhopal (M.P.), India
Dr. Biswajit Chakraborty
MECON Limited, Research and Development Division (A Govt. of India Enterprise), Ranchi-834002, Jharkhand, India
Dr. D.V. Ashoka
Professor & Head, Department of Information Science & Engineering, SJB Institute of Technology, Kengeri, Bangalore, India
Dr. Sasidhar Babu Suvanam
Professor & Academic Cordinator, Department of Computer Science & Engineering, Sree Narayana Gurukulam College of
Engineering, Kadayiuruppu, Kolenchery, Kerala, India
Dr. C. Venkatesh
Professor & Dean, Faculty of Engineering, EBET Group of Institutions, Kangayam, Erode, Caimbatore (Tamil Nadu), India
Dr. Nilay Khare
Assoc. Professor & Head, Department of Computer Science, MANIT, Bhopal (M.P.), India
Dr. Sandra De Iaco
Professor, Dip.to Di Scienze Dell’Economia-Sez. Matematico-Statistica, Italy
Dr. Yaduvir Singh
Associate Professor, Department of Computer Science & Engineering, Ideal Institute of Technology, Govindpuram Ghaziabad,
Lucknow (U.P.), India
Dr. Angela Amphawan
Head of Optical Technology, School of Computing, School Of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
Dr. Ashwini Kumar Arya
Associate Professor, Department of Electronics & Communication Engineering, Faculty of Engineering and Technology,Graphic Era
University, Dehradun (U.K.), India
Dr. Yash Pal Singh
Professor, Department of Electronics & Communication Engg, Director, KLS Institute Of Engg.& Technology, Director, KLSIET,
Chandok, Bijnor, (U.P.), India
Dr. Ashish Jain
Associate Professor, Department of Computer Science & Engineering, Accurate Institute of Management & Technology, Gr. Noida
(U.P.), India
Dr. Abhay Saxena
Associate Professor&Head, Department. of Computer Science, Dev Sanskriti University, Haridwar, Uttrakhand, India
Dr. Judy. M.V
Associate Professor, Head of the Department CS &IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham,
Brahmasthanam, Edapally, Cochin, Kerala, India
Dr. Sangkyun Kim
Professor, Department of Industrial Engineering, Kangwon National University, Hyoja 2 dong, Chunche0nsi, Gangwondo, Korea
Dr. Sanjay M. Gulhane
Professor, Department of Electronics & Telecommunication Engineering, Jawaharlal Darda Institute of Engineering & Technology,
Yavatmal, Maharastra, India
Dr. K.K. Thyagharajan
Principal & Professor, Department of Informational Technology, RMK College of Engineering & Technology, RSM Nagar,
Thiruyallur, Tamil Nadu, India
Dr. P. Subashini
Asso. Professor, Department of Computer Science, Coimbatore, India
Dr. G. Srinivasrao
Professor, Department of Mechanical Engineering, RVR & JC, College of Engineering, Chowdavaram, Guntur, India
Dr. Rajesh Verma
Professor, Department of Computer Science & Engg. and Deptt. of Information Technology, Kurukshetra Institute of Technology &
Management, Bhor Sadian, Pehowa, Kurukshetra (Haryana), India
Dr. Pawan Kumar Shukla
Associate Professor, Satya College of Engineering & Technology, Haryana, India
Dr. U C Srivastava
Associate Professor, Department of Applied Physics, Amity Institute of Applied Sciences, Amity University, Noida, India
Dr. Reena Dadhich
Prof.& Head, Department of Computer Science and Informatics, MBS MArg, Near Kabir Circle, University of Kota, Rajasthan, India
Dr. Aashis.S.Roy
Department of Materials Engineering, Indian Institute of Science, Bangalore Karnataka, India
Dr. Sudhir Nigam
Professor Department of Civil Engineering, Principal, Lakshmi Narain College of Technology and Science, Raisen, Road, Bhopal,
(M.P.), India
Dr. S.Senthilkumar
Doctorate, Department of Center for Advanced Image and Information Technology, Division of Computer Science and Engineering,
Graduate School of Electronics and Information Engineering, Chon Buk National University Deok Jin-Dong, Jeonju, Chon Buk, 561756, South Korea Tamilnadu, India
Dr. Gufran Ahmad Ansari
Associate Professor, Department of Information Technology, College of Computer, Qassim University, Al-Qassim, Kingdom of
Saudi Arabia (KSA)
Dr. R.Navaneethakrishnan
Associate Professor, Department of MCA, Bharathiyar College of Engg & Tech, Karaikal Puducherry, India
Dr. Hossein Rajabalipour Cheshmejgaz
Industrial Modeling and Computing Department, Faculty of Computer Science and Information Systems, Universiti Teknologi Skudai,
Malaysia
Dr. Veronica McGowan
Associate Professor, Department of Computer and Business Information Systems, Delaware Valley College, Doylestown, PA, Allman
China
Dr. Sanjay Sharma
Associate Professor, Department of Mathematics, Bhilai Institute of Technology, Durg, Chhattisgarh, India
Dr. Taghreed Hashim Al-Noor
Professor, Department of Chemistry, Ibn-Al-Haitham Education for pure Science College, University of Baghdad, Iraq
Dr. Madhumita Dash
Professor, Department of Electronics & Telecommunication, Orissa Engineering College , Bhubaneswar,Odisha, India
Dr. Anita Sagadevan Ethiraj
Associate Professor, Department of Centre for Nanotechnology Research (CNR), School of Electronics Engineering (Sense), Vellore
Institute of Technology (VIT) University, Tamilnadu, India
Dr. Sibasis Acharya
Project Consultant, Department of Metallurgy & Mineral Processing, Midas Tech International, 30 Mukin Street, Jindalee-4074,
Queensland, Australia
Dr. Neelam Ruhil
Professor, Department of Electronics & Computer Engineering, Dronacharya College of Engineering, Gurgaon, Haryana, India
Dr. Faizullah Mahar
Professor, Department of Electrical Engineering, Balochistan University of Engineering and Technology, Pakistan
Dr. K. Selvaraju
Head, PG & Research, Department of Physics, Kandaswami Kandars College (Govt. Aided), Velur (PO), Namakkal DT. Tamil Nadu,
India
Dr. M. K. Bhanarkar
Associate Professor, Department of Electronics, Shivaji University, Kolhapur, Maharashtra, India
Dr. Sanjay Hari Sawant
Professor, Department of Mechanical Engineering, Dr. J. J. Magdum College of Engineering, Jaysingpur, India
Dr. Arindam Ghosal
Professor, Department of Mechanical Engineering, Dronacharya Group of Institutions, B-27, Part-III, Knowledge Park,Greater Noida,
India
Dr. M. Chithirai Pon Selvan
Associate Professor, Department of Mechanical Engineering, School of Engineering & Information Technology, Amity University,
Dubai, UAE
Dr. S. Sambhu Prasad
Professor & Principal, Department of Mechanical Engineering, Pragati College of Engineering, Andhra Pradesh, India.
Dr. Muhammad Attique Khan Shahid
Professor of Physics & Chairman, Department of Physics, Advisor (SAAP) at Government Post Graduate College of Science,
Faisalabad.
Dr. Kuldeep Pareta
Professor & Head, Department of Remote Sensing/GIS & NRM, B-30 Kailash Colony, New Delhi 110 048, India
Dr. Th. Kiranbala Devi
Associate Professor, Department of Civil Engineering, Manipur Institute of Technology, Takyelpat, Imphal, Manipur, India
Dr. Nirmala Mungamuru
Associate Professor, Department of Computing, School of Engineering, Adama Science and Technology University, Ethiopia
Dr. Srilalitha Girija Kumari Sagi
Associate Professor, Department of Management, Gandhi Institute of Technology and Management, India
Dr. Vishnu Narayan Mishra
Associate Professor, Department of Mathematics, Sardar Vallabhbhai National Institute of Technology, Ichchhanath Mahadev Dumas
Road, Surat (Gujarat), India
Dr. Yash Pal Singh
Director/Principal, Somany (P.G.) Institute of Technology & Management, Garhi Bolni Road , Rewari Haryana, India.
Dr. Sripada Rama Sree
Vice Principal, Associate Professor, Department of Computer Science and Engineering, Aditya Engineering College, Surampalem,
Andhra Pradesh. India.
Dr. Rustom Mamlook
Associate Professor, Department of Electrical and Computer Engineering, Dhofar University, Salalah, Oman. Middle East.
Dr. Ramzi Raphael Ibraheem Al Barwari
Assistant Professor, Department of Mechanical Engineering, College of Engineering, Salahaddin University – Hawler (SUH) Erbil –
Kurdistan, Erbil Iraq.
Dr. Kapil Chandra Agarwal
H.O.D. & Professor, Department of Applied Sciences & Humanities, Radha Govind Engineering College, U. P. Technical University,
Jai Bheem Nagar, Meerut, (U.P). India.
Dr. Anil Kumar Tripathy
Associate Professor, Department of Environmental Science & Engineering, Ghanashyama Hemalata Institute of Technology and
Management, Puri Odisha, India.
Managing Editor
Mr. Jitendra Kumar Sen
International Journal of Soft Computing and Engineering (IJSCE)
Editorial Board
Dr. Soni Changlani
Professor, Department of Electronics & Communication, Lakshmi Narain College of Technology & Science, Bhopal (.M.P.), India
Dr. M .M. Manyuchi
Professor, Department Chemical and Process Systems Engineering, Lecturer-Harare Institute of Technology, Zimbabwe
Dr. John Kaiser S. Calautit
Professor, Department Civil Engineering, School of Civil Engineering, University of Leeds, LS2 9JT, Leeds, United Kingdom
Dr. Audai Hussein Al-Abbas
Deputy Head, Department AL-Musaib Technical College/ Foundation of Technical Education/Babylon, Iraq
Dr. Şeref Doğuşcan Akbaş
Professor, Department Civil Engineering, Şehit Muhtar Mah. Öğüt Sok. No:2/37 Beyoğlu Istanbul, Turkey
Dr. H S Behera
Associate Professor, Department Computer Science & Engineering, Veer Surendra Sai University of Technology (VSSUT) A Unitary
Technical University Established by the Government of Odisha, India
Dr. Rajeev Tiwari
Associate Professor, Department Computer Science & Engineering, University of Petroleum & Energy Studies (UPES), Bidholi,
Uttrakhand, India
Dr. Piyush Kumar Shukla
Assoc. Professor, Department of Computer Science and Engineering, University Institute of Technology, RGPV, Bhopal (M.P.), India
Dr. Piyush Lotia
Assoc.Professor, Department of Electronics and Instrumentation, Shankaracharya College of Engineering and Technology, Bhilai
(C.G.), India
Dr. Asha Rai
Assoc. Professor, Department of Communication Skils, Technocrat Institute of Technology, Bhopal (M.P.), India
Dr. Vahid Nourani
Assoc. Professor, Department of Civil Engineering, University of Minnesota, USA
Dr. Hung-Wei Wu
Assoc. Professor, Department of Computer and Communication, Kun Shan University, Taiwan
Dr. Vuda Sreenivasarao
Associate Professor, Department of Computr And Information Technology, Defence University College, Debrezeit Ethiopia, India
Dr. Sanjay Bhargava
Assoc. Professor, Department of Computer Science, Banasthali University, Jaipur, India
Dr. Sanjoy Deb
Assoc. Professor, Department of ECE, BIT Sathy, Sathyamangalam, Tamilnadu, India
Dr. Papita Das (Saha)
Assoc. Professor, Department of Biotechnology, National Institute of Technology, Duragpur, India
Dr. Waail Mahmod Lafta Al-waely
Assoc. Professor, Department of Mechatronics Engineering, Al-Mustafa University College – Plastain Street near AL-SAAKKRA
square- Baghdad - Iraq
Dr. P. P. Satya Paul Kumar
Assoc. Professor, Department of Physical Education & Sports Sciences, University College of Physical Education & Sports Sciences,
Guntur
Dr. Sohrab Mirsaeidi
Associate Professor, Department of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Skudai, Johor, Malaysia
Dr. Ehsan Noroozinejad Farsangi
Associate Professor, Department of Civil Engineering, International Institute of Earthquake Engineering and Seismology (IIEES)
Farmanieh, Tehran - Iran
Dr. Omed Ghareb Abdullah
Associate Professor, Department of Physics, School of Science, University of Sulaimani, Iraq
Dr. Khaled Eskaf
Associate Professor, Department of Computer Engineering, College of Computing and Information Technology, Alexandria, Egypt
Dr. Nitin W. Ingole
Associate Professor & Head, Department of Civil Engineering, Prof Ram Meghe Institute of Technology and Research, Badnera
Amravati
Dr. P. K. Gupta
Associate Professor, Department of Computer Science and Engineering, Jaypee University of Information Technology, P.O. Dumehar
Bani, Solan, India
Dr. P.Ganesh Kumar
Associate Professor, Department of Electronics & Communication, Sri Krishna College of Engineering and Technology, Linyi Top
Network Co Ltd Linyi , Shandong Provience, China
Dr. Santhosh K V
Associate Professor, Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal, Karnataka,
India
Dr. Subhendu Kumar Pani
Assoc. Professor, Department of Computer Science and Engineering, Orissa Engineering College, India
Dr. Syed Asif Ali
Professor/ Chairman, Department of Computer Science, SMI University, Karachi, Pakistan
Dr. Vilas Warudkar
Assoc. Professor, Department of Mechanical Engineering, Maulana Azad National Institute of Technology, Bhopal, India
Dr. S. Chandra Mohan Reddy
Associate Professor & Head, Department of Electronics & Communication Engineering, JNTUA College of Engineering
(Autonomous), Cuddapah, Andhra Pradesh, India
Dr. V. Chittaranjan Das
Associate Professor, Department of Mechanical Engineering, R.V.R. & J.C. College of Engineering, Guntur, Andhra Pradesh, India
Dr. Jamal Fathi Abu Hasna
Associate Professor, Department of Electrical & Electronics and Computer Engineering, Near East University, TRNC, Turkey
Dr. S. Deivanayaki
Associate Professor, Department of Physics, Sri Ramakrishna Engineering College, Tamil Nadu, India
Dr. Nirvesh S. Mehta
Professor, Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, South Gujarat, India
Dr. A.Vijaya Bhasakar Reddy
Associate Professor, Research Scientist, Department of Chemistry, Sri Venkateswara University, Andhra Pradesh, India
Dr. C. Jaya Subba Reddy
Associate Professor, Department of Mathematics, Sri Venkateswara University Tirupathi Andhra Pradesh, India
Dr. TOFAN Cezarina Adina
Associate Professor, Department of Sciences Engineering, Spiru Haret University, Arges, Romania
Dr. Balbir Singh
Associate Professor, Department of Health Studies, Human Development Area, Administrative Staff College of India, Bella Vista,
Andhra Pradesh, India
Dr. D. RAJU
Associate Professor, Department of Mathematics, Vidya Jyothi Institute of Technology (VJIT), Aziz Nagar Gate, Hyderabad, India
Dr. Salim Y. Amdani
Associate Professor & Head, Department of Computer Science Engineering, B. N. College of Engineering, PUSAD, (M.S.), India
Dr. K. Kiran Kumar
Associate Professor, Department of Information Technology, Bapatla Engineering College, Andhra Pradesh, India
Dr. Md. Abdullah Al Humayun
Associate Professor, Department of Electrical Systems Engineering, University Malaysia Perlis, Malaysia
Dr. Vellore Vasu
Teaching Assistant, Department of Mathematics, S.V.University Tirupati, Andhra Pradesh, India
Dr. Naveen K. Mehta
Associate Professor & Head, Department of Communication Skills, Mahakal Institute of Technology, Ujjain, India
Dr. Gujar Anant kumar Jotiram
Associate Professor, Department of Mechanical Engineering, Ashokrao Mane Group of Institutions, Vathar, Maharashtra, India
Dr. Pratibhamoy Das
Scientist, Department of Mathematics, IMU Berlin Einstein Foundation Fellow Technical University of Berlin, Germany
Dr. Messaouda AZZOUZI
Associate Professor, Department of Sciences & Technology, University of Djelfa, Algeria
Dr. Vandana Swarnkar
Associate Professor, Department of Chemistry, Jiwaji University Gwalior, India
Dr. Arvind K. Sharma
Associate Professor, Department of Computer Science Engineering, University of Kota, Kabir Circle, Rajasthan, India
Dr. R. Balu
Associate Professor, Department of Computr Applications, Bharathiar University, Tamilnadu, India
Dr. S. Suriyanarayanan
Associate Professor, Department of Water and Health, Jagadguru Sri Shivarathreeswara University, Karnataka, India
Dr. Dinesh Kumar
Associate Professor, Department of Mathematics, Pratap University, Jaipur, Rajasthan, India
Dr. Sandeep N
Associate Professor, Department of Mathematics, Vellore Institute of Technology, Tamil Nadu, India
Dr. Dharmpal Singh
Associate Professor, Department of Computer Science Engineering, JIS College of Engineering, West Bengal, India
Dr. Farshad Zahedi
Associate Professor, Department of Mechanical Engineering, University of Texas at Arlington, Tehran, Iran
Dr. Atishey Mittal
Associate Professor, Department of Mechanical Engineering, SRM University NCR Campus Meerut Delhi Road Modinagar, Aligarh,
India
Dr. Hussein Togun
Associate Professor, Department of Mechanical Engineering, University of Thiqar, Iraq
Dr. Shrikaant Kulkarni
Associate Professor, Department of Senior faculty V.I.T., Pune (M.S.), India
Dr. Mukesh Negi
Project Manager, Department of Computer Science & IT, Mukesh Negi, Project Manager, Noida, India
Dr. Sachin Madhavrao Kanawade
Associate Professor, Department Chemical Engineering, Pravara Rural Education Society’s,Sir Visvesvaraya Institute of Technology,
Nashik, India
Dr. Ganesh S Sable
Professor, Department of Electronics and Telecommunication, Maharashtra Institute of Technology Satara Parisar, Aurangabad,
Maharashtra, India
Dr. T.V. Rajini Kanth
Professor, Department of Computer Science Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India
Dr. Anuj Kumar Gupta
Associate Professor, Department of Computer Science & Engineering, RIMT Institute of Engineering & Technology, NH-1, Mandi
Godindgarh, Punjab, India
Dr. Hasan Ashrafi- Rizi
Associate Professor, Medical Library and Information Science Department of Health Information Technology Research Center,
Isfahan University of Medical Sciences, Isfahan, Iran
Dr. Golam Kibria
Associate Professor, Department of Mechanical Engineering, Aliah University, Kolkata, India
Dr. Mohammad Jannati
Professor, Department of Energy Conversion, UTM-PROTON Future Drive Laboratory, Faculty of Electrical Enginering, Universit
Teknologi Malaysia,
Dr. Mohammed Saber Mohammed Gad
Professor, Department of Mechanical Engineering, National Research Centre- El Behoos Street, El Dokki, Giza, Cairo, Egypt,
Dr. V. Balaji
Professor, Department of EEE, Sapthagiri College of Engineering Periyanahalli,(P.O) Palacode (Taluk) Dharmapuri,
Dr. Naveen Beri
Associate Professor, Department of Mechanical Engineering, Beant College of Engg. & Tech., Gurdaspur - 143 521, Punjab, India
Dr. Abdel-Baset H. Mekky
Associate Professor, Department of Physics, Buraydah Colleges Al Qassim / Saudi Arabia
Dr. T. Abdul Razak
Associate Professor, Department of Computer Science Jamal Mohamed College (Autonomous), Tiruchirappalli – 620 020 India
Dr. Preeti Singh Bahadur
Associate Professor, Department of Applied Physics Amity University, Greater Noida (U.P.) India
Dr. Ramadan Elaiess
Associate Professor, Department of Information Studies, Faculty of Arts University of Benghazi, Libya
Dr. R . Emmaniel
Professor & Head, Department of Business Administration ST, ANN, College of Engineering & Technology Vetapaliem. Po, Chirala,
Prakasam. DT, AP. India
Dr. C. Phani Ramesh
Director cum Associate Professor, Department of Computer Science Engineering, PRIST University, Manamai, Chennai Campus,
India
Dr. Rachna Goswami
Associate Professor, Department of Faculty in Bio-Science, Rajiv Gandhi University of Knowledge Technologies (RGUKT) DistrictKrishna, Andhra Pradesh, India
Dr. Sudhakar Singh
Assoc. Prof. & Head, Department of Physics and Computer Science, Sardar Patel College of Technology, Balaghat (M.P.), India
Dr. Xiaolin Qin
Associate Professor & Assistant Director of Laboratory for Automated Reasoning and Programming, Chengdu Institute of Computer
Applications, Chinese Academy of Sciences, China
Dr. Maddila Lakshmi Chaitanya
Assoc. Prof. Department of Mechanical, Pragati Engineering College 1-378, ADB Road, Surampalem, Near Peddapuram, East
Godavari District, A.P., India
Dr. Jyoti Anand
Assistant Professor, Department of Mathematics, Dronacharya College of Engineering, Gurgaon, Haryana, India
Dr. Nasser Fegh-hi Farahmand
Assoc. Professor, Department of Industrial Management, College of Management, Economy and Accounting, Tabriz Branch, Islamic
Azad University, Tabriz, Iran
Dr. Ravindra Jilte
Assist. Prof. & Head, Department of Mechanical Engineering, VCET Vasai, University of Mumbai , Thane, Maharshtra 401202, India
Dr. Sarita Gajbhiye Meshram
Research Scholar, Department of Water Resources Development & Management Indian Institute of Technology, Roorkee, India
Dr. G. Komarasamy
Associate Professor, Senior Grade, Department of Computer Science & Engineering, Bannari Amman Institute of Technology,
Sathyamangalam,Tamil Nadu, India
Dr. P. Raman
Professor, Department of Management Studies, Panimalar Engineering College Chennai, India
Dr. M. Anto Bennet
Professor, Department of Electronics & Communication Engineering, Veltech Engineering College, Chennai, India
Dr. P. Keerthika
Associate Professor, Department of Computer Science & Engineering, Kongu Engineering College Perundurai, Tamilnadu, India
Dr. Santosh Kumar Behera
Associate Professor, Department of Education, Sidho-Kanho-Birsha University, Ranchi Road, P.O. Sainik School, Dist-Purulia, West
Bengal, India
Dr. P. Suresh
Associate Professor, Department of Information Technology, Kongu Engineering College Perundurai, Tamilnadu, India
Dr. Santosh Shivajirao Lomte
Associate Professor, Department of Computer Science and Information Technology, Radhai Mahavidyalaya, N-2 J sector, opp.
Aurangabad Gymkhana, Jalna Road Aurangabad, India
Dr. Altaf Ali Siyal
Professor, Department of Land and Water Management, Sindh Agriculture University Tandojam, Pakistan
Dr. Mohammad Valipour
Associate Professor, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
Dr. Prakash H. Patil
Professor and Head, Department of Electronics and Tele Communication, Indira College of Engineering and Management Pune, India
Dr. Smolarek Małgorzata
Associate Professor, Department of Institute of Management and Economics, High School of Humanitas in Sosnowiec, Wyższa
Szkoła Humanitas Instytut Zarządzania i Ekonomii ul. Kilińskiego Sosnowiec Poland, India
Volume-2 Issue-1, March 2012, ISSN: 2231-2307 (Online)
S.
No
1.
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.
Authors:
Sumit Kumar Banchhor, Arif Khan
Paper Title:
Musical Instrument Recognition using Spectrogram and Autocorrelation
Page
No.
Abstract: Traditionally, musical instrument recognition is mainly based on frequency domain analysis (sinusoidal
analysis, cepstral coefficients) and shape analysis to extract a set of various features. Instruments are usually
classified using k-NN classifiers, HMM, Kohonen SOM and Neural Networks. Recognition of musical instruments
in multi-instrumental, polyphonic music is a difficult challenge which is yet far from being solved. Successful
instrument recognition techniques in solos (monophonic or polyphonic recordings of single instruments) can help to
deal with this task. We introduce an instrument recognition process in solo recordings of a set of instruments (flute,
guitar and harmonium), which yields a high recognition rate. A large solo database is used in order to encompass the
different sound possibilities of each instrument and evaluate the generalization abilities of the classification process.
The basic characteristics are computed in 1sec interval and result shows that the estimation of spectrogram and
autocorrelation reflects more effectively the difference in musical instruments.
Keywords: Speech/music classification, audio segmentation, spectrogram, autocorrelation.
1-4
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A. Eronen, A. Klapuri: Musical Instrument Recognition Using Cepstral Coefficients and Temporal Features, Proc. of the IEEE International
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A. Eronen: Musical instrument recognition using ICA-based transform of features and discriminatively trained HMMs, Proc. of the Seventh
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1997
Authors:
A.R. Eskandari, M. Naser-Moghaddasi and M. Eskandari
Paper Title:
Reconstruction of Shape and Position for Scattering Objects by Linear Sampling Method
Abstract: This paper presents an approach for shape and position reconstruction of a scattering object using
microwaves where the scatterer is assumed to be a homogenous dielectric medium. The employed technique assumes
no prior knowledge of the scatter’s material properties like electric permittivity and conductivity, and the far-field
pattern is used as the only primary information in identification. The approach proposed consists of retrieving the
shape and the position of the scattering object using a linear sampling method. The technique results in high
computational speed and efficiency. In addition, the technique can be generalized for any scatterer structure.
Numerical results are used to validate the feasibility of the proposed approach.
Keywords: Shape Reconstruction, Inverse Scattering, Microwave Imaging, Linear Sampling Method (LSM).
References:
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Authors:
Shiv Kumar, Aditya Shastri
Paper Title:
Design of Simulator for Automatic Voice Signal Detection and Compression (AVSDC)
Abstract: A good amount of work has been done in the field of compression, voice signal detection, and spectrum
analysis which has been generated a number of results in the past few decades. In this research, following three
important problems have been identified:
1. To distinguish between constitutional and unconstitutional Voice: It is an important task to identify authenticity
of recorded voice of the specific person. Here it has been tried to develop a Simulator which identifies
constitutional and unconstitutional voice.
2. To identify words sequence:It is an important task to recognize words sequence in the recorded voice.
Sometimes voice may be recorded fast, clear, or loud. Here it has been tried to develop a simulator to checkout
whether recorded words are in proper sequence are not.
3. To develop a simulator which does not change file extension and quality of voice signal after compression:
Normally, after compression, file extension is changed and quality of the voice signal is deteriorated. Here it
has been tried not to change extension of the file after compression with minor distortion in voice signal.
As per review of above three problems, it is being considered a simulator may be designed which may resolve above
problems. With this view, the research title is chosen as “Design of Simulator for Automatic Voice Signal Detection
and Compression (AVSDC)” which is suitable for pervasive computing, voice signal detection, and spectrum
analysis. AVSDC is divided into following two parts:
1. Automatic Voice Signal Detection (AVSD)
2. Automatic Voice Signal Compression (AVSC)
Automatic Voice Signal Detection (AVSD) is used to identify constitutional and unconstitutional voice signal
automatically which is performed on the basis of frequency, pitch value, formant value, and sequence of words in the
voice signal for several samples of the same voice. An underline purpose of AVSD is to identify fake voice in the
security system. Frequency is being mapped to the frequency domain by computing its DFT using the FFT algorithm.
Sequence of words is computed by continuously computing difference between absolute averages of two adjacent
significant windows and comparing it to a predefined threshold. Word Identification System is part of AVSD which
is designed to checkout whether recorded words in proper sequence are not. Normally, sometimes spoken words of
voice may be recorded very fast, smoothly, or loudly. The main idea behind the word identification system is to first
train it with several versions of the same word, thus yielding a “reference fingerprint”. Then, subsequent words can
be identified based on how close they are to this fingerprint. The whole idea is evaluated on the basis of Euclidean
distance theory. Automatic Voice Signal Compression (AVSC) takes .wav stereo file as an input and compress 50 to
60 percent of the source file at about 45 kbps with high quality voice signal by taking the help of adaptive wavelet
packet decomposition and psychoacoustic model. AVSC takes .wav stereo file as an input and creates .wav mono file
after compression. After compression minor distortion is also possible. The main feature of AVSC is that file
extension does not change after compression. In other words, compression is done from .wav to .wav extension.
AVSC takes .wav stereo file as an input and after compression it creates .wav mono file as an output. AVSC also
computes entropy and SNR (Signal to Noise Ratio) of the source file during the compression.
Keywords:
Window
MatLab7.0, Euclidean Distance Theory, Wavelet, Frequency Volue, Pitch Value, Average Significant
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Institute of Science, Department of Electrical Engineering, Bangalore, India
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Network Security, VOL.8 No.8, August 2008
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Transforms” Proceeding in IEEE 0-7803-3192-3/96 @1996
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Informatica-32 (2008) 283-288
Jong-Tzy Wang, Ming-Shan Lai, Kai-Wen Liang, Pao-Chi Chang, “Adaptive wavelet quantization Index Modulation Technique for audio
watermarking”, National Central University-Tiwan
N. Ruiz Reyes, M. Rosa Zurera, F. Lopez Ferreras, D. Martínez Munoz, “A New Perceptual Entropy-based Methods to Achieve Signal
Adpted Wavelet Tree in A low Bit Rate Perceptual Audio Coder”, SPAIN
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Applied to a Wavelet Based Perceptual Audio Coder”, Escuela Universitaria Politénica 23700 Linares - Jaén (SPAIN)
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Science, National Science Council, under the Grand No: MU-I-003/96, Proceeding in 2001. Sofia
Frank Kurth, Michael Clausen, “Filter Bank Tree and M-Band Wavelet Packet Algorithms in Audio Signal Processing”, Universit¨at Bonn,
Institut f¨ur Informatik V, R¨omerstr. 164, D-53117 Bonn, Germany.
O. Farooq, S. Datta, J. Blackledge, “Blind Tamper Detection in Audio using Chirp based Robust Watermarking”, Proceeding in WSEAS
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Latha Pillai, "Quantization", XAPP615 (v1.1) June 25, 2003, 1-800-255-7778
George Tzanetakis, Georg Essl, Perry Cook, "Audio Analysis using the Discrete Wavelet Transform", Computer Science Department *also
Music Department
HE Dong-Mei and GAO Wen, "Wideband Speech And Audio Coding Based On Wavelet Transform And Psychoacoustic Model",
Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin 150001
Ciprian Doru Giurc¢aneanu , Ioan T¢abus¸ and Jaakko Astola, "Integer wavelet Transform Based Lossless Audio Compression", Signal
Processing Laboratory, Tampere University of Technology-Finland
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Audio Effects (DAFX-02), Hamburg, Germany, September 26-28, 2002
Claudia Schremmer, Thomas Haenselmann , Florian Bömers, "Wavelets In Real-Time Digital Audio Processing: A Software For
Understanding Wavelets In Applied Computer Science", Department of Praktische Informatik IV, University of Mannheim, Germany
F. Abramovich and B.W. Silverman, "Wavelet Decomposition Approaches to statistical Inverse Problem", University of Bristol (U.K.)
Gavriel Yarmish, "The Simplex Method Applied to Wavelet Decomposition", Proceedings of the 10th WSEAS International Confenrence
on Applied Mathematics, Dallas, Texas, USA, November 1-3, 2006
Deepa Kundur , Dimitrios Hatzinakos, "Digital Watermarking Using Multi-resolution Wavelet Decomposition", Natural Sciences and
Engineering Research Council (NSERC) of Canada and by Communications and Information Technology Ontario (CITO).
Caroline Chaux, Laurent Duval2 and Jean-Christophe Pesquet,"2D Dual-Tree M-Bandwavelet Decomposition", Universit de Marne-laVall¥ee, Champs-sur-Marne, France
Chalermchon Satirapod, Clement Ogaja, Jinling Wang and Chris Rizos, "An Approach to GPS Analysis incorporating Wavelet
Decomposition", School of Geomatic Engineering, The University of New South Wales, Sydney NSW 2052, AUSTRALIA
V. A. Baturin and I. V. Mironova, "Low-Degree Solar Oscillation Spectrum with Wavelet Decomposition", PACS numbers : 96.60.Ly,
95.75.Wz, 95.75Pq, DOI: 10.1134/S1063773706020071
Sina Jahanbin, Hyohoon Choi, Alan C. Bovik, Kenneth R. Castleman, "Three Dimensional Face Recognition Usingwavelet Decomposition
Of Range Images", Laboratory for Image and Video Engineering, The University of Texas, Austin, Texas
K. Kwak and W. Pedrycz, "Review on “Face Recognition Using Fuzzy Integral and Wavelet Decomposition Method” IEEE Trans. Syst.
Man Cyb. 34, 1 (Aug. 2004)
A.S. RYBAKOV, "Wavelet Decomposition And Fractal Analysis For Joint Measurements Of Laser Signal Delay And Amplitude",
Automatic Control and Computer Sciences, Vol.35, No.3, pp.11-19, 2001, Avtomatika I Vychislitel’naya Tekhnika, Vol.35, No.3, pp.1424, 2001
W. Kosek And W. PopiNski, " Forecasting Pole Coordinates Data By Combination Of The Wavelet Decomposition And Auto-covariance
Prediction", Space Research Centre, Polish Academy Of Sciences, Warsaw, Poland
G. A. Blackburn , J. G. Ferwerda, "Improving The Quantification Of Leaf Biochemistry And Water Content Through Wavelet
Decomposition Of Reflectance Spectra", Department of Geography, Lancaster University, Lancaster, LA1 4YB, UK Rade Kutil and Andreas Uhl, "Optimization of 3-D Wavelet Decomposition on Multiprocessors", Journal of Computing and Information
Technology - CIT 8, 2000, 1, 31–40
R. Martinez-Noriega, H. Kang, B. Kurkoski, K. Yamaguchi and M. Nakano-Miyatake, "Audio Watermarking Based on Wavelet Transform
and Quantization Index Modulation", National Polytechnic Institute of Mexico
Needeljko Cvejic, Tapio Seppanen, "A Wavelet Domain LSB Insertion Algorithm for high capacity audio Stegnography", Media Team
Oulu, Information Processing laboratory, Finland
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S.Manikandan, "Speech Enhancement Based On Wavelet De-noising", Academic Open Internet Journal, Valume17, 2006, ISSN-1311-4360
Rachid Moussaoui, Jean Rouat, Roch Lefebvre, "Wavelet Based Independent Component Analysis For Multi-Channel Source Separation",
Departement de genie electrique et de genie informatique, Universite de Sherbrooke, Quebec, Canada
Pavel Rajmic and Jan Vlach, "Real-Time Audio Processing Via Segmented wavelet Transform" Proc. of the 10th Int. Conference on Digital
Audio Effects (DAFx-07), Bordeaux, France, September 10-15, 2007
Bastiaan Kleijn , “Speech Signal Processing”, Speech, Music and Hearing TMH/KTH Annual Report 2001
Turkish Word Recognition Using Discrete Wavelet Neural Network Based on Adaptive Entropy”, International Conference-Elazig, TurkeyDec 06, 2007, the Arabian Journal for Science and Engineering, Volume 32, Number 2B.
Murtaza Bulut, “Mult-level emotional speech analysis resynthesis”, Proposed thesis for Ph.D. in Electrical Engineering, University of
Southern California (USC), Los Angeles, CA, (graduation expected in November 2007).
Michael I Mandel, “Recognition and Organization of Speech and Audio (LabROSA)”, Ph.D. candidate in the department of Electrical
Engineering at Columbia University, Proposed work for 2009 (Jan) exp.
Graziano Bertini, Federico Fontana, Diego Gonzalez, Lorenzo Grassi, Massimo Magrini “Voice Transformation Algorithms With Real
Time Dsp Rapid Prototyping Tools”, Proceeding In International Conference –Eusipco 2005
Marcos Faundez-Zanuy, “Non Liner speech Processing”, Proceeding in ISCpad 66, 19-22 April-2005, Barcelona, Spain
Keikichi HIROSE, “Speech Prosody 2004”, Proceeding in ISCApad 56,
International Conference: Speech Prosody 2004 on March 23 -26, 2004-Japan,
Kyogu Lee,"Pitch Perception: Place Theory, Temporal Theory, and Beyond", IEE 391 Special Report (Autumn 2004), Center for Computer
Research in Music and Acoustics (CCRMA), Music Department, Stanford University
Douglas A. Reynolds, Larry P. Heck, “Automatic Speaker Recognition” Presented at the AAAS 2000 Meeting Humans, Computers and
Speech Symposium 19 February 2000, Nuance Communications United States Air Force.
Matti Karjalainen, Tero Tolonen,"Multi-Pitch and Periodicity Analysis Model for Sound Separation and Auditory Scene Analysis",
Laboratory of Acoustics and Audio Signal Processing-Helsinki University of Technology
Brett A. St. George, Ellen C. Wooten, Louiza Sellami “Speech Coding and Phoneme classification Using MATLAB and NeuralWorks”
Department of Ellectrical Engineering,U.S. Naval Academy-Annapolis, MD 21402
John-Paul Hosom, Lawrence Shriberg, Jordan R. Green, “Diagnostic Assessment of Childhood Apraxia of Speech Using Automatic Speech
Recognition (ASR) Methods”, Oregon Health & Science University –Beaverton, Accepted for Publications by NIH Public access.
Dalibor Mitrovic, Matthias Zeppelzauer, Christian Breiteneder, “ Discrimination and Retrieval of Animal Sounds”,
Viresh Moonsasar, Ganesh k. Venayagamoorty,"Artificial Neural Network Based Automatic Speaker Recognition using a hybrid technique
for feature extraction", Proceedings, IEEE Trans on Acoustics, Speech and Signal,
Fracarro Radioindustrie, CitecVoice, Alpikom, “Robust Speech Recognition”, Copyright © Partners of the DICIT consortium.
Nachiappan, PM Abdul Manan Ahmad “Speech Coding Effects On Recognition Accuracy For Timit”, Postgraduate Annual Research
Seminar 3-4 July 2007,( PARS-07)
M. Herrera Martinez, "Evaluation of Audio Compression Artifacts", Acta Polytechnica Vol. 47 No. 1/2007
Nadine E. Miner, Thomas P. Caudell, "Using Wavelets to Synthesize Stochastic-based Sounds for Immersive Virtual Environments", Dept.
of Electrical and Computer Engineering, University of New Mexico
D Kumar, P Carvalho, M Antunes, J Henriques, M Maldonado, R Schmidt, J Habetha, "Wavelet Transform And Simplicity Based Heart
Murmur Segmentation", ISSN 0276-6547 Computers in Cardiology 2006;33:173-176
Dmitriy Genzel and Eugene Charniak, “Entropy Rate Constancy in Text”, Proceedings of the 40th Annual Meeting of the Association for
Computational Linguistics (ACL), Philadelphia, July 2002, pp. 199-206.
Rong Zhang1, Rongshan Yu, Qibin Sun, Wai-Choong Wong, “A New Bit-Plane Entropy Coder for Scalable Image Coding” 0-7803-93325/05/$20.00 ©2005 IEEE
Hariharan Subramanian, “Audio Signal Classification” M.Tech. Credit Seminar Report, Electronic Systems Group, EE. Dept, IIT Bombay,
Submitted November2004
M. Bank, S. Podoxin, V. Tsingouz, “Estimation of non distortion audio signal compression”, Department of Communication Engineering,
Center for Technological Education Holon.
Guillaume Gravier, Scott Axelrod, Gerasimos Potamianos, Chalapathy Neti, “Maximum Entropy And Mce Based Hmm Stream Weight
Estimation For Audio-Visual Asr” IBM T. J. Watson Research Center-USA
Chi-Min Liu, Wen-Chieh Lee, and Yo-Hua Hsiao, “M/S Coding Based On Allocation Entropy”, Proc. of the 6th Int. Conference on Digital
Audio Effects (DAFX-03), London, UK, September 8-11, 2003
Authors:
T. D. Dongale, T .G. Kulkarni, P. A. Kadam, R. R. Mudholkar
Paper Title:
Simplified Method for Compiling Rule Base Matrix
Abstract: The main paradigm shift of fuzzy control lies in the implementation of control strategies in the form of
knowledge based algorithm described by fuzzy logic. The fuzzy logic system designer either explores his own
knowledge or elicits from domain expert. The knowledge pertaining to control strategy is expressed in the form of
IF-THEN fuzzy rules. In Fuzzy Logic Control (FLC), the rules are expressed in the form of matrix table. Filling up
consequent premises in the rule table is a tedious job. We present here simple numeric method to compile consequent
part of fuzzy rules. This greatly reduces an over burden on system designer. The method reported in this paper is
quite handy for those were not expert in writing fuzzy rules for FLC of interest. The paper demonstrates the
numerical approach to frame the rule base. It involves simple arithmetic addition and subtraction operation. In case
of highly non-linear system the straight forward approach fails. In such cases, we suggest corrective terms to the rule
base. The comparison of rule base designed by direct human logic with that of numerical approach practiced in case
studies validates the success of the numeric approach for compiling rule base matrix presented in paper.
Keywords: Decision Matrix, Fuzzy Logic, Fuzzy logic control, Fuzzy Reasoning, IF-THEN Rules.
References:
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Bart Kosko,“Neural network and fuzzy system- a dynamic approach to machine Intelligence”, University of south California, Pentice Hall of
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India. J. Asha Professor, I.F.E.T. College of engineering, India. “Fuzzy logic controller for cascaded H-bridge multi level Inverter”, ISSN:
0975-5462 Vol. 2 no. 2 Feb. 2011.
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Mohan Akole, Barjeev Tyagi, “Design of Fuzzy controller for non-linear model of inverted Pendulum-cart system”, XXXII National systems
conference, NSC 2008, December 17-19, 2008.
Navin Govind, Senior systems engineer, Intel Corporation, Chandler, “Fuzzy logic control With the Intel 8XC196 Embedded
Microcontroller”.
R.Aruimozhiyal, K.Bhaskaran, N.Devarajan, J.Kanagraj, “Real time matlab interface for speed Control of induction motor drive using dspic
30f4011”, International journal of computer application (0975-8887) Volume 1 No.5.
39-43
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in photo-voltaic energy conversion Scheme”.
9. R.R.Yagar and D.P. Filev, “Essentials of fuzzy modeling and Control”, Essentials of fuzzy modeling and control, Institute of lona college, A
Wiley interscience publication, 1994.
10. Salman Mohagheghi, member, IEEE, Ganesh K.Venayagamoorthy, Senior member, IEEE, Satish Rajagopalan, member, IEEE and G.
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system”.
11. Stamations V. Kartalopoulos, “Understanding Neural network and fuzzy logic, basic concept and application”, AT & T Bell lab, IEEE
Neural Network Counsil, sponsor, Prentice Hall of India, 2005.
12. Sungchul Jee, Yoram Korean, “Adaptive fuzzy controller for feed drives of a CNC machine tool”, Mechatronics14 2004, 299-326. 2003
Elsevier Ltd
7.
Authors:
P.K.Dhal, C.Christober Asir Rajan
Paper Title:
Transient Stability Improvement using Hybrid Controller Design for STATCOM
Abstract:
This paper proposes a transient stability improvement using hybrid controller design for STATCOM
with static synchronous time critical error and better damping system oscillations after a short circuit fault. This
article on a STATCOM Control for transient stability improvement has proposed a hybrid system with fuzzy and
neural controller to meet with the addition of Lyapunov stability criterion to the ability and conditions as well. The
performance is analyzed using digital simulation with (SMIB) with infinite bus.
Keywords: Fuzzy Logic, Neural Network, lyapunov energy function, STATCOM, transient stability.
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Authors:
6.
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Manisha Sharma, Harendra Kumar, Deepak Garg
An Optimal Task Allocation Model through Clustering with Inter-Processor Distances in
Paper Title:
Heterogeneous Distributed Computing Systems
Abstract: Distributed computing systems (DCS) are of current interest due to the advancement of microprocessor
technology and computers networks. It consists of multiple computing nodes that communicate with each other by
message passing mechanism. Reliability and communication over distances are the main reasons for building the
DCS. In distributed computing systems, partitioning of applications software in to modules and proper allocation of
modules among processors are important factors for efficient utilization of resources. We consider the problem of mmodules and n-processors (m >> n). In this paper a mathematical model for finding optimal cost and optimal
reliability to the problem is presented considering DCS with heterogeneous processors in such a way that the
allocated load on each processor is balanced. The results obtained by the present model are compared with the recent
models and comparison results show that the model is very effective.
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Keywords: Distributed computing system, Module allocation, Inter module communication, Reliability, Data
transfer rate, Inter processor distance.
References:
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Ghafoor and J. Yang, “A Distributed Heterogeneous Supercomputing Management System”, IEEE Comput., 1993Vol.6, pp. 78-86 .
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Computer,Vol.C-31, 1982,pp.41-47.
Min-Sheng Lin, “A Linear-Time Algorithm for Computing K-Terminal Reliability on Proper Interval Graphs”,IEEE Trans.Reliability,
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Kumar, V. Singh, M.P. and Yadav, P.K., “An Efficient Algorithm for Allocating Tasks to Processors in a Distributed Systems”, Proc. of the
19th National System Conference, SSI, Held at Combatore, India, 1995, pp.82-87 .
Kumar, V., Singh, M.P. and Yadav, P.K., “A Fast Algorithm for Allocating Tasks in Distributed Processing System”, Proc. of the 30th
Annual Convention of CSI held at Hyderabad, India, 1995, pp.347-358.
Peng, D.T.,Shin, K.G.and Abdel, Z. T.F., “Assignment Scheduling Communication Periodic Tasks in Distributed Real Time System”,
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Vol.XXVM, 1999, pp. 437-444.
Srinivasan, S., Jha. K.N.,“Safety and Reliability Driven Task Allocation in Distributed Systems”, IEEE Trans. on Parallel and Distributed
System, Vol.10, 1999, pp. 238-250.
Yadav, P.K., Kumar, A.,“An Efficient Static Approach for Allocation through Reliability Optimization in Distributed Systems”,
Presented at the International Conference on Operations Research for Development (ICORD 2002) held at Chennai.
Zahedi, E., Ashrafi, N., “Software Reliability Allocation based on structure, Utility, Price and Cost”, IEEE Trans. on Software Engineering,
Vol.-17, 1991, pp. 345-356 .
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International Journal Of Modeling, Simulation, and Scientific Computing, Vol.2, No.2, 2011, pp.131-149.
Yadav P.K., Singh M.P., Kumar H., “Scheduling Algorithm: Tasks Scheduling Algorithm for Multiple Processors with Dynamic
Reassignment”, Journal of Computer Systems, Networks and Communications, Article ID-578180, 2008, pp.1-9.
Bokhari, S.H., “Dual Processor Scheduling with Dynamic Re-Assignment”, IEEE Transactions on Software Engineering, vol. 5, 1979, pp.
341-349.
Authors:
Kapil Jain, Pradyumn Chaturvedi
Paper Title:
Matlab -based Simulation & Analysis of Three - level SPWM Inverter
Abstract: The multilevel began with the three level converters. The elementary concept of a multilevel converter
to achieve higher power to use a series of power semiconductor switches with several lower voltage dc source to
perform the power conversion by synthesizing a staircase voltage waveform. However, the output voltage is
smoother with a three level converter, in which the output voltage has three possible values. This results in smaller
harmonics, but on the other hand it has more components and is more complex to control. In this paper, different
three level inverter topologies and SPWM technique has been applied to formulate the switching pattern for three
level inverter that minimize the harmonic distortion at the inverter output. Simulation result has discussed.
Keywords: SPWM, THD, PWM
References:
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2.
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J. S. Lai and F.Z. Peng “Multilevel Converters – A new breed of power converters” IEEE Trans. Ind Applicant , Vol. 32, May/June 1996.
Jose Roderiguez, Jih-Sheng Lai and Fang Zheng Reng, “Multilevel Inverters” A survey of topologies ,control, and applications “,IEEE
Trans. On Ind.Electronics, vol No.[4], August 2002.
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P.K.Chaturvedi, S. Jain, Pramod Agrawal “ Modeling , Simulation and Analysis of Three level Neutral Point CLAMPED inverter using
matlab/Simulink/Power System Blockst”
Bor-Ren Lin & Hsin – Hung Lu “ A Novel Multilevel PWM Control Scheme of the AC/DC/AC converter for AC Drives”IEEE Trans on
ISIE, 1999.
B. R. Lin & H- H Lu “ multilevel AC/DC/AC Converter for AC Drives” IEEE Proceding electronics Power application, Vol 146, No. 4, July
1999.
DAI Bin “ A new control scheme for voltage Source Inverter Without DC Link Capacitor Under Abnormal Input Voltage Conditions” IEEE
Tran.2009.
K. Arab tehrani, H. Andriasioharana, I. Rasonarivo & F.M. Sargos “A Multilevel Inverter Model” IEEE Trans. 2008.
Siriroj Sirisukprasert, Jih- Sheng Lai & Tina – Hua Liu “Optimum harmonics Reduction With A wide Range Of Modulation Indexes for
Multilevel Converters” IEEE Trans Ind Application Electronics ,Vol 49 , No. 4, August 2002.
G.Bhuvaneshwari and Nagaraju “Multilevel inverters – a comparative study” vol .51 No.2 march – April 2005.
Siriroj Sirisukprasert “Optimum harmonics reduction”.
A. M. Massoud, S.J. Finney and B.W. Williams “Control Techniques for Multilevel Voltage Source Inverters” IEEE proce. 2003.
B.R. Lin and H.H. Lu “Multilevel AC/DC/AC converter for AC drives” IEE E Proc.—Electr. Power Application, Vol. 146, No. 4, July 1999.
M. A. EL- Barky, S.H. Arafah “Simulation and Implemetaion of Three Phase Three Level Inverter” SICE july 25- 27, 2001, nagoya..
Authors:
Abhishek Arvind Gulhane, Abrar Shaukat Alvi
Paper Title:
Noise Reduction of an Image by using Function Approximation Techniques.
Abstract: In this proposed work, an efficient simple, fast technique is given to remove noise of an image which is
mostly introduced due to environmental changes. We focus on the noise issues that changes image pixels value either
on or off. The pixels are easily identified as noisy pixels in grayscale image but it is difficult to recognize in RGB
color image. Reason behind it is that, any color combination with white (pixel on) or black (pixel off) generate other
color. This paper focus on such technique that reduces the noise in both grayscale and RGB image with recovery of
originality of source image.
Keywords: Random Function Approximation, Salt Peeper Noise, Luminance, Noise Blur.
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References:
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3. M. Nachtegael and E. E.Kerre, “Connections between binary, gray-scaleand fuzzy mathematical morphologies,” Fuzzy Sets Syst., to be
published.
4. “Decomposing and constructing fuzzy morphological operations over-cuts: Continuous and discrete case,” IEEE Trans. Fuzzy Syst., vol. 8,
pp. 615–626, Oct. 2000.
5. Shuqun Zhang and Mohammad A. Karim. A new impulse detector for switching median filters. IEEE SIGNAL PROCESSING LETTERS,
VOL. 9, NO. 11, NOVEMBER 2002, 2002.
6. Tao Chen and Hong Ren Wu. Adaptive impulse detection using center- weighted median filters. IEEE SIGNAL PROCESSING LETTERS,
VOL. 8, NO. 1, JANUARY 2001, 2001.
7. Constantine Butakoff Igor Aizenberg, Member and Dmitriy Paliy. Impulsive noise removal using threshold boolean filtering based on the
impulse detecting functions. IEEE SIGNAL PROCESSING LETTERS, VOL. 12, NO. 1, JANUARY 2005, 2005.
8. E. Davies Machine Vision: Theory, Algorithms and Practicalities, Academic Press, 1990, Chap. 3.
9. A. C. Bovik, “Streaking in median filtered images,” IEEE Trans.
10. J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, “Image denoising using scale mixture of Gaussian in the wavelet domain,”
IEEE Trans. Image Processing, vol. 12, no. 11, 2003, pp. 1338-1351.
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1.
Authors:
Hala M. A. Mansour, Labib Francis Gergis, Mostafa A. R. Eltokhy, Hoda Z. Said
Paper Title:
Performance Analysis for Concatenated Coding schemes with Efficient Modulation Techniques
Abstract:
In digital communication systems, channel coding is the method of adding redundancy to the data in
order to reduce the frequency of errors or to increase the capacity of a channel. Concatenated codes are the most
superior class of codes making achievable channel capacity almost at par with the Shannon limits. Concatenated
codes are error correcting codes constructed by combining two or more simple codes through an interleaver in order
to obtain powerful coding schemes. In this paper a special construction of concatenated convolutional coding scheme
called parallel-serial concatenated convolutional code (P-SCCC) is presented. The upper bound to the bit error
probability of the proposed code is evaluated. Results showed that the error performance of this proposed code
scheme is better than that of both classical serial and parallel concatenated convolutional codes. The performance of
the proposed code has been studied with different types of digital modulation schemes.
Keywords: Code concatenation, convolutional code, frequency shift keying, phase shift keying, and quadrature
amplitude modulation.
References:
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Information Theory, vol. 42 No. 2, March 1996.
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decoding” IEEE Transactions on Information Theory, vol. 44, No. 3, May 1998.
Sason, I., Shamai S. “Improved upper bounds on the performance of Parallel and Serial Concatenated Turbo codes via their ensemble
distance spectrum” Information Theory, 1998 Proceedings. 1998 IEEE International Symposium, Issue date: 16-21 Aug. 1998, pp 30, Date
of current version: Aug. 2002.
Barg A., Zemor G. “Concatenated codes: Serial and Parallel” Information Theory, IEEE Transaction, vol. 51, Issue: 5, Apr. 2005.
National Taipei University of Technology, Department of Electrical Engineering,, Chung-Hsiao E. Rd., Taipei, Taiwan “Bandwidth
efficient concatenated coding schemes” IET Commun., 5 January 2010, Vol. 4, Iss. 1, pp. 26–31.
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Processing, 2007 6th International Conference, pp.1-4, Issue date 10-13-Dec. 2007.
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using constellation shaping” Communications, IEEE Proceedings, vol. 152, Issue: 6, pp. 1125-1133, Dec. 2005.
Graell I Amat, Rasmussen L.K, Brannstrom “Unifying analysis and design of rate-combatable concatenated codes” IEEE Transactions on
Communications, Vol. 59, Issue: 2, pages 343-351. Feb. 2011.
Vahid Asghari, Sonia Aıssa, “Parallel-Serial concatenated coding: design and bit error probability performance” Electrical and Computer
Engineering, CCECE 2008 Canadian Conference on 4-7 May 2008, pp489 – 492.
Fuqin Xiong, Digital Modulation Techniques. ARTECH HOUSE, INC. 2006.
Krishna R. Narayanan, Gordon L. Stuber” Performance of Trellis-Coded CPM with Iterative Demodulation and Decoding” IEEE
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International Symposium on spread spectrum techniques & applications, 1998.
Authors:
Sandeep Kumar, Gourav Sharma, Gurdeepinder Singh
Paper Title:
AGC & AVR of Interconnected Thermal Power System While Considering the Effect of GRCs
Abstract: As the interconnected power system transmits the power from one area to another system frequency will
inevitable deviate from scheduled frequency, resulting in a frequency error. A control system is essential to correct
the deviation in the presence of external disturbances and structural uncertainties to ensure a safe and smooth
operation of power system. Thus design of Automatic Generation Control (AGC) and Automatic Voltage Regulator
(AVR) system play a vital role in the automation of power system. This paper deals with automation of three area
interconnected reheat thermal power with consideration of Generation Rate Constraint (GRCs). The primary object
of the AGC is to balance the total system generation against system load and losses, while considering the effect of
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Generation Rate Constraint (GRCs). So that the desired frequency and power interchange with neighboring systems
are maintained in order to minimize the transient deviations and to provide zero steady state error in appropriate short
time. Further the role of automatic voltage control is to maintain the terminal voltage of synchronous generator in
order to maintain the bus bar voltage. Otherwise bus bar voltage goes beyond permitted limit.
Keywords: Area Control Error (ACE), Automatic Generation Control (AGC), Automatic Voltage Control (AVC),
Automatic Voltage Regulator (AVR), Generation Rate Constraints (GRCs).
References:
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Li Pingkang and Ma Yongzhen, “Some New Concept in Modern Automatic Generation Control Realization,” IEEE Trans. on Power System,
1998, pp. 1232.
Dong Yao and Zhiqiang Gao, “Load Frequency Control for Multiple-Area Power Systems,” American Control Conference Hyatt Regency
Riverfront, St. Louis, MO, USA, 2009.
Authors:
Gurudatt Kulkarni, Niraj Patil, Pradip Patil
Paper Title:
Private Cloud Secure Computing
Abstract: Cloud computing is an increasingly popular paradigm for accessing computing resources. In practice,
cloud service providers tend to offer services that can be grouped into three categories: software as a service,
platform as a service, and infrastructure as a service. This paper discuss the characteristics and benefits of private
cloud computing. It proceeds to discuss the private cloud characteristics and formation as well as implementation.
This paper aims to provide a means of understanding and investigating Private cloud... This paper also outlines the
responsibilities of private cloud provider and the facilities to consumer
11.
Keywords: Private, public Cloud, Pass, Azure.
75-77
References:
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12.
http://blogs.gartner.com/thomas_bittman/2010/05/18/clarifying-private-cloud-computing/
“Adopting Cloud Computing: Enterprise Private Clouds”, Shyam Kumar Doddavula and Amit Wasudeo Gawande, SETLabs Briefings,
VOL 7 NO 7 2009
http://www.cisco.com/en/US/solutions/collateral/ns340/ns517/ns224/ns836/ns976/white_paper_c11-543729.html
Cloud Computing: A Study of Infrastructure As A Service (Iaas), Sushil Bhardwaj, Leena Jain, Sandeep Jain, International Journal Of
Engineering And Information Technology.
http://www.esri.com/technology-topics/cloud-gis/public-vs-private.html
http://www.tatvasoft.com/blog/2011/04/what-is-cloud-computing.html
Authors:
Shrikrishan Yadav, Santosh Kumar Singh, Krishna Chandra Roy
Paper Title:
A Smart and Secure Wireless Communication System: Cognitive Radio
Abstract:
Trust is an important concept in human interactions which facilitates the formation and continued
existence of functional human societies. The radio frequency spectrum is a limited natural resource and hence its
efficient use is of the greatest importance. Cognitive radio is a smart wireless communication system that is
conscious of its surrounding environment, learns from the environment and adapts its internal states by making
corresponding changes in certain operating parameters in real time. In this paper, we search the adaptive
characteristics of cognitive radio in secure and reliable communication. But how a communication system can be
made reliable such that there occur no eavesdropping and information leakage. The possible solutions include
integrating the merits of spread spectrum modulation, using encryption algorithms and it’s potential to switch over
various frequency bands. In the development of future wireless communication systems, the spectrum utilization will
play an important key role due to the shortage of unallocated spectrum. The main tasks of the cognitive radio are to
provide highly reliable communications whenever and wherever needed and how to utilize the radio spectrum
efficiently. Cognitive radio can be the best communication system in an emergency condition as Earthquake, flood
and Tsunami etc when all communication systems are failed to provide information and to communicate each other.
Keywords: Decryption, Encryption, Primary User, Radio Frequency Spectrum, Secondary User, Spectrum Analysis.
References:
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Authors:
Amir Aliabadian, Esmaeil Akbarpour, Mohammad Yosefi
Paper Title:
Kernel Based Approach toward Automatic object Detection and Tracking in Surveillance Systems
Abstract:
A modified object-tracking algorithm that uses the flexible Metric Distance Transform kernel and
multiple features for the Mean shift procedure is proposed and tested. The Faithful target separation based on RGB
joint pdf of the target region and that of a neighborhood surrounding the object is obtained. The non-linear loglikelihood function maps the multimodal object/background distribution as positive values for colors associated with
foreground, while negative values are marked for background. This replaces the more usual Epanechnikov kernel (Ekernel), improving target representation and localization without increasing the processing time, minimizing the
similarity measure using the Bhattacharya coefficient. The algorithm is tested on several image sequences and shown
to achieve robust and reliable frame-rate tracking.
Keywords: Modified Object tracking, Distance Transform kernel, Mean Shift, Bhattacharyya coefficient, loglikelihood function maps.
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Processing (ICIP): 689-692.
Authors:
Shailesh S. Dhok
Paper Title:
Credit Card Fraud Detection Using Hidden Markov Model
Abstract: The most accepted payment mode is credit card for both online and offline in today’s world, it provides
cashless shopping at every shop in all countries. It will be the most convenient way to do online shopping, paying
bills etc. Hence, risks of fraud transaction using credit card has also been increasing. In the existing credit card fraud
detection business processing system, fraudulent transaction will be detected after transaction is done. It is difficult to
find out fraudulent and regarding loses will be barred by issuing authorities. Hidden Markov Model is the statistical
tools for engineer and scientists to solve various problems. In this paper, it is shown that credit card fraud can be
detected using Hidden Markov Model during transactions. Hidden Markov Model helps to obtain a high fraud
coverage combined with a low false alarm rate.
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88-92
Keywords: Internet, online shopping, credit card, e-commerce security, fraud detection, Hidden Markov Model.
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e-Commerce and e Service, pp. 177-181, 2004.
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Columbia Univ., 1999.
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V. Vatsa, S. Sural, and A.K. Majumdar, “A Game-theoretic Approach to Credit Card Fraud Detection,” Proc. First Int’l Conf. Information
Systems Security, pp. 263-276, 2005
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Regional Conf., vol. 1, pp. 98-103, 2005.
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vol. 22, no. 1, pp. 45-55, 2003.
D. Ourston, S. Matzner, W. Stump, and B. Hopkins, “Applications of Hidden Markov Models to Detecting Multi-Stage Network Attacks,”
Proc. 36th Ann. Hawaii Int’l Conf. System Sciences, vol. 9, pp. 334-344, 2003.
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Proc. 11th IEEE Int’l Conf. Networks, pp. 531-536, 2003.
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Learning about Users, pp. 35-44, 1999.
Authors:
P. S. Anish, S. Ramarajan, T. Arun Srinivas, M. Sasikumar
Paper Title:
Voltage Balancing in SVM Controlled Diode Clamped Multilevel Inverter for Adjustable drives
Abstract: The work describes a transformer less medium voltage adjustable-speed induction motor drive consisting
of two back-to-back connected five-level diode-clamped converters. Due to the feedback from the load to the dc link
nodes, there is a chance of voltage imbalance. In this paper the methods for voltage balancing are discussed and
simulated. The usage of switching techniques to employ voltage balancing rather than the external circuitry is being
discussed. Proper switching results in the control of average current through the nodes and hence the non
symmetrical charging and discharging of the dc split capacitors can be avoided. The first phase of work explains the
output using the multicarrier pulse width modulation technique and the second phase deals with the modification
done using the Space vector Pulse Width Modulation (SVPWM) technique. Voltage balancing is achieved with lesser
harmonic content while using the SVPWM technique.
Keywords: Medium-voltage drives, multilevel inverters, Space vector modulation, voltage balancing.
References:
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Electron., vol. 12, no. 2, pp. 213–220, Mar. 1997.
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202–208,Jan./Feb. 1997.
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rectifier/inverter systems,” IEEE Trans. Ind. Appl., vol. 41, no. 6, pp. 1698–1706, Nov./Dec. 2005.
9. H. Akagi, H. Fujita, S. Yonetani, and Y. Kondo, “A 6.6-kV transformerless STATCOM based on a five-level diode-clamped PWM
converter: System design and experimentation of a 200-V, 10-kVA laboratory model,” in Conf. Rec. IEEE IAS Annu. Meeting, 2005, pp.
557–564.
10. Newton, M. Sumner, and T. Alexander, “Multi-level converters: A real solution to high voltage drives?” IEE Colloq. Dig., no. 1997/091, pp.
3/1–3/5, 1997.
11. L. M. Tolbert, F. Z. Peng, and T. G. Habetler, “Multilevel converters for large electric drives,” IEEE Trans. Ind. Appl., vol. 35, no. 1, pp.
36–44, Jan./Feb. 1999.
12. J. C. Das and R. H. Osman, “Grounding of AC and DC low-voltage and medium-voltage drive system,” IEEE Trans. Ind. Appl., vol. 34, no.
1, pp. 205–216, Jan./Feb. 1998
1.
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16.
Authors:
Mukesh Kumar, Anand Chauhan, Rajat Kumar
93-98
A Deterministic Inventory Model for Deteriorating Items with Price Dependent Demand and Time
Varying Holding Cost under Trade Credit
Abstract:
In this proposed research, we developed a deterministic inventory model for price dependent demand
with time varying holding cost and trade credit under deteriorating environment, supplier offers a credit limit to the
customer during whom there is no interest charged, but upon the expiry of the prescribed time limit, the supplier will
charge some interest. However, the customer has the reserve capital to make the payments at the beginning, but
decides to take the benefit of the credit limit. This study has two main purposes, first the mathematical model of an
inventory system are establish under the above conditions. Second this study demonstrate that the optimal solution
not only exists but also feasible. Computational analysis illustrates the solution procedure and the impact of the
related parameter on decision and profits.
Paper Title:
Keywords: Deterioration, price dependent Demand, Trade credit, time varying holding cost.
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and Permissible Delay in Payments, International Journal of Strategic Decision Sciences (IJSDS) 2( 2), 20-35.
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Authors:
Seyed Zeinolabedin Moussavi, Aliakbar Rahmani
Paper Title:
Comparison and Inspection of Harmonic Effects in PMSM and Induction Motors
Abstract:
Regarding to different kinds of load, domestic electrical appliances, increasing application of further
electrical equipment’s which leads to consumption of electric energy, destructive electromagnetic sources EMI
added. Recognizing this source and it's side effects on performance of electronic and electrical equipment that could
be in form of conductive, inductive and radiated is outstanding. An ideal electric machine is a system that electric
energy is applied in pure sinusoid waveform flow has no loss in the heat form. However in practice, elements and
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equipment’s with nonlinear characteristic, specially power electronic equipment’s and storage elements of energy
could arise higher frequency harmonics causing losses in the form of heat. Numerous electrical motors used in
industrial manufacturing companies cause notably heat losses especially then induction motors. The fact that
complexity of interconnection between stator and rotor can consider as source of higher harmonics and energy losses,
attention is paying from induction motors into Permanent Magnet Synchronous Motors (PMSM). The paper, make a
comparison between PMSM and widely used induction motors from the view point of higher frequency harmonics
and shows the advantage of PMSM in this regards.
Keywords: Torque Control, Induction Motors, Energy Consumption, Harmonic Sources, Permanent Magnetic
Synchronous Motors (PMSM), Ripple.
References:
Theory of Synchronous Machines Generalized Method of Analysis –Part I" AIEE Trans., Vol. 48, July 1929, PP.716-727.
www.nashrepardazesh.ir
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Mohammadreza Hassan Zadeh1,Arash Kiyoumarsi2 Electrical Engineering Department,Abhar Islamic Azad University,22,Iran startup and
steady-state performance of interior- permanent magnet induction Motors
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6. C. Mi, G. R. Slemon, and R. Bonert, “Modeling of iron losses of permanent- magnet synchronous motors,” IEEE Trans. Ind. Appl., vol. 39,
no. 3, pp. 734–742, May/Jun. 2003
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onvers.,vol. 20, no. 1, pp. 121–127, Mar. 2005.
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9. Peter Campbell. Permanent Magnet Materials and Their Application. Cambridge University Press, Cambridge, 1994
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1.
2.
3.
4.
Authors:
Sangeetha.M, Arumugam.C, Sapna P.G, Senthil Kumar .K.M
Reliability Data Analysis Procedures for Comparing Failure Rates of the System Using Optimal
Paper Title:
Truncation of Short Tests
Abstract: A test was described for two systems, long term and short term with an exponentially distributed time
between failures. The test is intended for checking the ratio MTBFl /MTBFs exceeds or equals a prescribed value,
versus one that it is less than the prescribed value, by means of long term tests with large average sample number in
the earlier system. Our proposed system focus on improving test by using low average sample number in short term
which is having the advantage of economy in time requirement and cost. It produces optimum truncated test called
binomial Sequential Probability Ratio Test. Criteria are proposed for determining the characteristics of truncated test
followed with the discretizing effect of truncation on error probabilities with a view to optimization of its parameters.
The search algorithm for truncation apex used in this system achieves closeness to the optimum which depends on
successful choice of the initial approximation, search boundaries and on the search step. The enhanced reliability of
modern technological systems, combined with the reduced time quotas allotted for creating new system is capable of
yielding a highly efficacious test which increases reliability and feasibility of decisions.
18.
Keywords: MTBF, Short Truncate Test, Long Term, ADP
References:
Y. H. Michlin and G. Grabarnik, “Sequential testing for comparison of the mean time between failures for two systems,” IEEE Trans.
Reliab.,vol. 56, no. 2, pp. 321–331, June 2007.
2. A. Wald, Sequential Analysis. NY: John Wiley & Sons, 1947, pp. 22–180.
3. Y. H. Michlin and R. Migdali, “Test duration in choice of helicopter maintenance policy,” Rel. Eng. & Syst. Safety, vol. 86, no. 3, pp. 317–
321, Dec. 2004.
4. L. A. Aroian, “Sequential analysis-direct method,” Technometrics, vol. 10, pp. 125–132, 1968.
5. Y. H. Michlin and Y. Shai, “Sequential testing for MTBF ratio in comparative reliability evaluation,” in Proc. 15th Int. Conf. Israel Society
for Quality, Jerusalem, 2004, pp. 264–268.
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Eds. New York: Marcel Dekker, 1991, pp. 67–119.
7. A.Wald and J.Wolfowitz, “Optimum character of the sequential probability ratio test,” Ann. of Math. Stat., vol. 19, no. 3, pp. 326–339, 1948.
8. B. Eisenberg and B. K Ghosh, “The sequential probability ratio test,” in Handbook of Sequential Analysis, B. K. Ghosh and P. K. Sen,
Eds.New York: Marcel Dekker, 1991, pp. 47–66.
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10. “Reliability test methods, plans, and environments for engineering, development, qualification, and production,” pp. 32–42, MIL-HDBK781A, US DOD, 1996.
11. “Reliability data analysis techniques-procedures for comparison of two constant failure rates and two constant failure (event) intensities,”
IEC 61650, 1997.
1.
19.
Authors:
Sanjay Patel, O. P. Vyas, Hansa Mehra
Paper Title:
Interfacing of Sensor Network to Communication Network for Disaster Management
Abstract: This paper deals with the sensor network and communication network for disaster management, in which
the concerned authorities dealing in disaster management get the message on their mobile phones about disaster
information. Now a days number of small disasters like fire, chemical leakage, pollution etc, happen frequently and
need immediate relief action. In this paper the authors have developed a technique for immediate information release
for quick action to such events. In this technique, we have used sensors which sense the disaster information and
transfer this information to the mobile user using GSM RS 232 Modem and MDE 8051 development board.
Keywords: GSM, MDE0851 board, KEIL, AT command
111-115
116-119
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Monitoring 2002, 4, 688-694.
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3. Vijay K. Garg, Joseph E.Wilkes,”principles and applications of GSM”, Prentice Hall, 1999.
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7. McLoughlin, M. P., Allmon, W. R., Anderson, C. W., Carlson,M. A., DeCicco, D. J., and Evancich, N. H., “Development of a Field-Portable
Time-of-Flight Mass Spectrometer System,” Johns HopkinsAPL Tech.
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or Radiological Attacks, DHHS (NIOSH) Pub. 2002-139 (May2002).
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20.
Authors:
Chinmay Chandrakar, M.K. Kowar
Paper Title:
Denoising ECG Signals Using Adaptive Filter Algorithm
Abstract: One of the main problem in biomedical data processing like electrocardiography is the separation of the
wanted signal from noises caused by power line interference, external electromagnetic fields, random body
movements and respiration. Different types of digital filters are used to remove signal components from unwanted
frequency ranges. It is difficult to apply filters with fixed coefficients to reduce Biomedical Signal noises, because
human behavior is not exact known depending on the time. Adaptive filter technique is required to overcome this
problem. In this paper type of adaptive filters are considered to reduce the ECG signal noises like PLI and Base Line
Interference. Results of simulations in MATLAB are presented. In this we have used Recursive Least Squares (RLS).
RLS algorithm is proposed for removing artifacts preserving the low frequency components and tiny features of the
ECG. Least-squares algorithms aim at the minimization of the sum of the squares of the difference between the
desired signal and the model filter output .When new samples of the incoming signals are received at every iteration,
the solution for the least-squares problem can be computed in recursive form resulting in the recursive least-squares
(RLS) algorithms. The RLS algorithms are known to pursue fast convergence even when the Eigen value spread of
the input signal correlation matrix is large. These algorithms have excellent performance when working in timevarying environments. All these advantages come with the cost of an increased computational complexity and some
stability problems, which are not as critical in LMS-based algorithms.
120-123
Keywords: ECG Signal, Dirichlet’s Condition, Adaptive Filter.
References:
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Paulo S.R. Denis, "Adaptive filtering Algorithms and Practical implementation”.
O. Sayadi and M. B. Shamsollahi, “Model-based fiducial points extraction for baseline wander electrocardiograms,” IEEE Trans. Biomed.
Eng., vol.55, pp. 347-351, Jan.2008.
Y. Der Lin and Y. Hen Hu, “Power-line interference detection and suppression in ECG signal Processing,”. IEEE Trans. Biomed.
Eng.,vol.55, pp. 354-357, Jan.2008.
N. V. Thakor and Y.-S. Zhu,Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection,”.
IEEETransactionson Biomedical Engineering, vol. 38, no. 8, pp. 785-794, 1991.
Farhang-Boroujeny, B., Adaptive Filters- Theory and Applications, John Wiley and Sons.Chichester,UK, 1998.
P. E.McSharry, G. D. Clifford, L. Tarassenko, and L. A. Smith, “A dynamical model for generating synthetic elctrocardiogram signals,”
IEEE Transactions on Biomedical Engineering, vol. 50, no.3, pp. 289-294, 2003.
Authors:
Seyed Zeinolabedin Moussavi, Aliakbar Rahmani
Paper Title:
Position and Speed Control of Permanent Magnet Motors, State Space Approach
Abstract:
Present paper is analyzing the permanent magnet dc motor (PMDC) through state space variables so
that command speed without consequence resulted from voltage and power and load fluctuations can be obtained.
For this purpose, we should write equations of permanent magnetic motor and then by applying these equations and
known methods of control, try for making desirable behavior of these motors, and by using MATLAB software in
coding, analyzing real behavior of motor could be possible, and regarding to these results, planning for future of a
system in front of short circuit and load fluctuation could be possible. We are trying to reduce dangers resulted from
mistakes in experiments.
21.
Keywords: Permanent magnetic motor, modern control, efficiency, permanent magnetic motors, control, permanent
magnet motor, sensorless, torque fluctuation.
References:
1.
2.
3.
4.
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po ieee transactions on industrial electronics, vol. 49, no. 1, february 2002sition-Sensorless Control of Surface-Mount Permanent-Magnet
AC (PMAC) Motors at Low Speeds
J.FGeras and M.Wing"permanent Magnet Motor Technology". New York: Marcel Dekker,(1998)
E/ Ch.Andresenand R. Keller, 'Squirrel Cage Induction Motor or permanent Magnet Motor synchronous Motor". Symp. On Power
Electronnics,Electr. Drives. Advanced Electr. Motor SPEED AM,96, Capri, Italy (1996)
G.R.Slemon,"High-efficiency drives using permanent Magnet motors" in proc. Int. conf.
Industrial Electronics, control and
Instrumentation, Maui, HI, 1991, vol. 2. Pp. 725-730.
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and steady-state analysis,” IEEE Trans. Power App. Syst., vol. PAS-102, Aug. 1983.
G. Bertotti, Hysteresis in Magnetism for Physicists, Material Scientists, and Engineers. New York: Academic, 1998.
124-127
7.
Investigation of Influences of Various Losses on Electromagnetic Torque for Surface- Mounted Permanent Magnet Synchronous Motor
ieee transactions on power electronics, vol. 18, no. 1, january 2003
8. Iron Loss Model for Permanent-Magnet Synchronous Motors ieee transactions on magnetics, vol. 43, no. 8, august 2007
9. IBM Corporation and sspower Technology, Hilliard, OH 43026 USA. Iron Loss Model for Permanent-Magnet Synchronous Motors.IEEE
Transactions on Magnetics, VOl,43,no.8
10. Mohammadreza Hassan Zadeh1,Arash Kiyoumarsi2 Electrical Engineering Department,Abhar Islamic Azad University,22,Iran startup and
steady-state performance of interior- permanent magnet induction Motors.
22.
Authors:
R.Hari Kumar, C.Ganesh Babu, P.Shri Vignesh
Paper Title:
Earlier Detection of Oral Cancer from Fuzzy Based Photo Plethysmography
Abstract: The main objective of this paper is to detect the occurrence of cancer in its early stages from Fuzzy
based photoplethysmography. One of the key problems in the treatment of cancer is the early detection of the disease.
Often, cancer is detected in its advanced stages, when it has compromised the function of one or more vital organ
systems and is widespread throughout the body. Methods for the early detection of cancer are of utmost importance
and are an active area of current research. The photo Plethysmography readings are taken for the patients in Madurai,
Chennai, and Coimbatore regions and are converted to a quantized value and then classified using the fuzzy logic in
accordance with clinical standards of TNM (Tumor Node Metastatic) codes. This method helps people to get rid of
the glitches of cancer and also to cure the cancer in its early stage. It is a cost effective method and it needs no trained
persons to operate. This paper can be further improved by a designing of VLSI fuzzy processor, which is capable of
dealing with complex fuzzy inferences systems. It can also be made user friendly and it can be made available in all
health care centers. The results can be made within short period without any delay for further processing.
128-133
Keywords: Early Detection of Cancer, TNM Codes, photo Plethysmography, Fuzzy logic.
References:
1.
2.
3.
4.
5.
6.
7.
Jindal G.D.,Nerukkar S.N.,Pendukar S.A.,Babu.J.P.,Kelkar M.D.,Despande A.K., and Parulkar G.B(1990a):’diagnosis of peripheral arterial
occlusive disease using impedance plethysmography’ J.Postgrad.Med.,36,pp.147-153.
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Int.Med.,105,pp.264-276.
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F Martin Mc Neil and Ellen Thro,’ Fuzzy logic a practical approach ‘, forwarded by R.Vage Ap Professional, 1994.
Berenji.H.R.,’A reinforcement learning based architecture for fuzzy logic control’, Int J. Approximate reasoning, Vol.6,pp.267-292,1992.
Fuzzy Logic Toolbox User’s Guide, Revised for MATLAB R2007a, the Mathworks inc.,2007.
G.Ascia, V.Ctania, and M. Russo-VLSI Hardware Architecture for Complex fuzzy systems, IEEE transactions on Fuzzy systems Vol.7,
No.5 Oct 1999.pp 553-570
Authors:
K.M. Pandey, A.P. Singh
Paper Title:
Numerical Simulation of Combustion Chamber without Cavity at Mach 3.12
Abstract: In this Simulation, supersonic combustion of hydrogen at Mach 3.12 has been presented. The combustor
has a single fuel injection perpendicular to the main flow from the base. Finite rate chemistry model with K-ε model
have been used for modeling of supersonic combustion. The pressure rise due to the combustion is not very high on
account of global equivalence ratio being quite low. Within the inlet the shock-wave-boundary- layer interactions
play a significant role. The combustor without cavity is found to enhance mixing and combustion while increasing
the pressure loss, compared with the case without cavity to the experimental results. The OH mass fraction is less
almost by an order to that of water mass fraction The OH mass fraction decreases as the gas expands around the
injected jet and the local mixture temperature falls, However OH species are primarily produced in the hot separation
region upstream of the jet exit and behind the bow shock and convected downstream with shear layer. The geometry
results shows the better mixing in combustion chamber, caused by more extreme shear layers and stronger shocks are
induced which leads loss in total pressure of the supersonic stream.
Keywords: Hydrogen, Shear layers, Stabilization, stagnation temperature, Supersonic combustion.
References:
23.
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V.A. Zabaykin and A.A. Smogolev, “3-D Structure Of Hydrogen Flame In Supersonic high-Enthalpy Flow,” West-East High Speed Flow
Field Conference 19-22, November 2007 Moscow, Russia.
AntonellaIngenito and Claudio Bruno, “Physics and Regimes of Supersonic Combustion”, AIAA Journal, Vol. 48, No. 3, March 2010.
J. H. Tien, and R. J. Stalker, “Release of Chemical Energy by Combustion in a Supersonic Mixing Layer of Hydrogen and Air”,
COMBUSTION AND FLAME 130:329–348 (2002).
Adela Ben-Yakar and Ronald K. Hanson, “Cavity Flame-Holders for Ignition and Flame Stabilization in Scramjets: An Overview”, Journal
Of Propulsion And Power Vol. 17, No. 4, July–August 2001.
Jeong-Yeol Choi, Fuhua Ma and Vigor Yang, “ Dynamics Combustion Characteristics in Scramjet Combustors with Transverse Fuel
Injection”, 41st AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit 10 - 13 July 2005, Tucson, Arizona, AIAA 2005-4428.
T. K. G. Anavaradham, B. U. Chandra, V. Babu and S. R. Chakravarthy and S. Panneerselvam Experimental and numerical investigation
of confined unsteady supersonic flow over cavities”, The Aeronautical Journal March 2004 pp.135-144.
A. Ben-Yakar and R. K. Hanson, “Experimental Investigation Of Flame-Holding Capability of Hydrogen Transverse Jet In Supersonic
Cross-Flow”, Twenty-Seventh Symposium (International) on Combustion/The Combustion Institute, 1998/pp. 2173–2180.
Tianwen Fang, Meng Ding, Jin Zhou, “Supersonic Flows Over Cavities”, Front. Energy Power Engineering. China 2008, 2(4): 528–533
In-Seuck Jeung and Jeong-Yeol Choi, “Numerical Simulation of Supersonic Combustion for Hypersonic Propulsion”, 5th Asia-Pacific
Conference on Combustion,The University of Adelaide, Adelaide, Australia 18-20 July 2005.
Kyung Moo Kim, Seung Wook Baek and Cho Young Han Numerical study on supersonic combustion with cavity-based fuel injection”,
International Journal of Heat and Mass Transfer 47 (2004) 271–286.
Tarun Mathur, “Supersonic Combustion Experiments with a Cavity-Based Fuel Injector”, Journal of Propulsion and Power Vol. 17, No. 6,
November–December 2001.
J. Philip Drummond, Glenn S. Diskin, and Andrew D. Cutler, “Fuel-Air Mixing And Combustion In Scramjets”, American Institute of
Astronautics and Aeronautics (AIAA-.2002-3878).
Yves Burtschell, GhislainTchuenb and David E. Zeitoun, “H2 injection and combustion in a Mach 5 air inlet through a ViscousMach
134-141
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Interaction”, European Journal of Mechanics B/Fluids 29 (2010) pp.351-356.
D. Haworth, B. Cuenot, T. Poinsot, and R. Blint, “Numerical simulation of turbulentpropane-air combustion with non-homogeneous
reactants: initial results”, Center for Turbulence Research Proceedings of the Summer Program 1998, pp.5-24.
YiguangJu and Takashi Niioka, “Ignition Simulation of Methane/Hydrogen Mixtures in a Supersonic Mixing Layer”, Combustionand
Flame 102:462-470 (1995)
Nitin K. Gupta, Basant K. Gupta, Narayan Ananthkrishnan_Gopal R. Shevare,IkSoo Park and Hyun Gull Yoon, “Integrated Modeling and
Simulation of an Air-breathing Combustion System Dynamics”, American Institute of Aeronautics and Astronautics, pp.1-31.
M. Akbarzadeh and M. J. Kermani, “Numerical Computation of Supersonic-Subsonic Ramjet Inlets; a Design Procedure”, 15th. Annual
(International) Conference on Mechanical Engineering-ISME2007 May 15-17, 2007, Amirkabir University of Technology, Tehran, Iran
ISME2007-3056.
Stephen J. Mattick and Steven H. Frankel, “Numerical Modeling of Supersonic Combustion:Validation and Vitiation Studies Using
FLUENT”, 41st AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 10 - 13 July 2005, Tucson, Arizona, AIAA 2005-4287
A. Balabel, A.M. Hegab, S. Wilson, M. Nasr, S. El-Behery, “Numerical Simulation of Turbulent Gas Flow in a Solid Rocket Motor
Nozzle”, 13th International Conference on Aerospace Sciences & Aviation Technology, ASAT- 13, May 26 – 28, 2009, Paper: ASAT-13pp-13.
A.T. Sriram and D. Chakroborty “Numerical Simulations Of Staged Transverse Injection Into Mach 2 Flow Behind Backward-Facing
Step”, Proceedings of the International Conference on Aerospace Science and Technology,26 - 28 June 2008, Bangalore, India, INCAST
2008-119.
Authors:
K.M. Pandey, S.K. Reddy K.K.
Paper Title:
Numerical Simulation of Wall Injection with Cavity in Supersonic Flows of Scramjet Combustion
Abstract: A supersonic combustion ramjet engine (scramjet) is one of the most promising air-breathing propulsive
systems for future hypersonic vehicles, and it has drawn the attention of an ever increasing number of researchers.
This work involves an application of computational fluid dynamics to a problem associated with the flow in the
combustor region of a scramjet. A cavity wall injector is an integrated fuel injection approach, and it is a new concept
for flame holding and stabilization in supersonic combustors. The presence of a cavity on an aerodynamic surface
could have a large impact on the air flow surrounding it, and this makes a large difference to the performance of the
engine, namely it may improve the combustion efficiency and increase the drag force. The objective of the work was
to design the four wall injector model with cavity using gambit, study the combustion processes of air- fuel (h2)
mixture for the wall injector models with inlet air at Mach number 2 and inlet fuel at Mach number 2 and compare
the performance of the different wall injector models. There are several key issues that must be considered in the
design of an efficient fuel injector. Of particular importance are the total pressure losses created by the injector and
the injection processes that must be minimized since the losses reduce the thrust of the engine. In this analysis, the
two-dimensional coupled implicit Reynolds averaged Navier-Stokes (RANS) equations, the standard k-ε Turbulence
model, sst-kω Turbulence and the eddy-dissipation reaction model have been employed to investigate the flow field
in a hydrogen-fuelled scramjet combustor with a cavity design and to analyze the combustion processes. Numerical
results are obtained with the fluent solving sst-kω Turbulence model to have the best results of all models. The grid
independent test was also carried out. The profiles of static pressure, static temperature, and two components of
velocity and mole fraction of hydrogen at various locations of the flow field are presented. Computed values using
sst-kω turbulence model are found to have good overall agreement with results obtained from literature reviews and
some discrepancies were observed for static pressure and static temperature in the vicinity of the jets due to
unsteadiness in the shock system.
Keywords: Scramjet engine, Mach number 2, RANS Equations, Turbulence model.
142-150
References:
Wei Huang, Shi-bin Luo, Mohamed Pourkashanian, Lin Ma, Derek B.Ingham, Jun Liu and Zhen-guo Wang; “Numerical Simulations of a
Typical Hydrogen Fueled Scramjet Combustor with a Cavity Flameholder”; WCE 2010, London, UK, July 2010.
2. In-Seuck Jeung, Jeong-Yeol Choi; “Numerical Simulation of Supersonic Combustion for Hypersonic Propulsion”; 5th Asia-Pacific
Conference on Combustion, 18-20 July 2005.
3. Jeong-Yeol Choi, Fuhua Mab, Vigor Yang; “Combustion oscillations in a scramjet engine combustor with transverse fuel injection”;
Proceedings of the Combustion Institute 30, 2005, pp:2851–2858.
4. K.M. Pandey, A.P. Singh; “Numerical analysis of combustor flow fields in Supersonic flow regime with finite rate Chemistry model”; ISST
Journal of Mechanical Engineering, Vol. 1 No.2, (July - December 2010), p.p. 81-90.
5. K.M.Pandey, T.Sivasakthivel; “Recent Advances in Scramjet Fuel Injection - A Review”; International Journal of Chemical Engineering and
Applications, ISSN: 2010-0221, Vol. 1, No. 4, December 2010.
6. Weipeng Li, Taku Nonomura, Akira Oyama and Kozo Fujii; “LES Study of Feedback-loop Mechanism of Supersonic Open Cavity Flows”;
40th Fluid Dynamics Conference and Exhibit, AIAA 2010-5112, 28 June - 1 July 2010.
7. Y. Moriyoshi, K. Suga, M. Kubota; “Modeling of Cavitation Phenomenon inside a Nozzle under High Fuel Pressure Condition”; 11th
ICLASS July 2009.
8. Michael K. Smart; “Scramjet Inlets”; Brisbane 4072 AUSTRALIA
9. Md. Mahbubul Alam, Shigeru Matsuo, Toshiaki Setoguchi; “Passive Suppression of Cavity-Induced Pressure Oscillation in An
Axisymmetric Supersonic Flow”; 29- 31 December 2007, Dhaka, Bangladesh, ICME 2007
10. B.V.N. Charyulu1, R. Manoj, B. Rajinikant, D.K. Tripathi, A. Rolex, Vikrant Satya, V. Ramanujachari, S. Panneerselvam; “Experimental
investigations of ramp-cavity based Supersonic combustor”; International Conference on Aerospace Science and Technology, Bangalore,
India, 26-28 June, 2008.
11. Sean M. Torrez, James F. Driscoll, Matthias Ihme, Matthew L. Fotia; “Reduced-Order Modeling of Turbulent Reacting Flows with
Application to Ramjets and Scramjets”; Journal of propulsion and power; vol. 27, No. 2, March–April 2011.
12. Kathleen Tran; “One Dimensional Analysis Program for Scramjet and Ramjet Flow paths”; Blacksburg, VA, December 8, 2010.
1.
25.
Authors:
Anurag Porwal, Rohit Maheshwari, B.L.Pal, Gaurav Kakhani
Paper Title:
An Approach for Secure Data Transmission in Private Cloud
Abstract: In the cloud, the data is transferred among the server and client. Cloud security is the current discussion
in the IT world. This research paper helps in securing the data without affecting the network layers and protecting the
data from unauthorized entries into the server, the data is secured in server based on users’ choice of security method
so that data is given high secure priority.
151-155
Keywords: Cloud, Private Cloud, Security, Secure data Transmission.
References:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Lombardi F, Di Pietro R. Secure virtualization for cloud computing. Journal of Network Computer Applications (2010),
doi:10.1016/j.jnca.2010.06.008.
Subashini S, Kavitha V., “A survey on security issues in service delivery models of cloud computing,” Journal of Network and Computer
Applications (2011) vol. 34 Issue 1, January 2011 pp. 1-11.
Sudha.M, Bandaru Rama Krishna rao, M.Monica, “A Comprehensive approach to ensure secure data communication in cloud environment”
International Jornal Of computer Applications, vol. 12. Issue 8, pp. 19-23.
Balachander R.K, Ramakrishna P, A. Rakshit, “Cloud Security Issues, IEEE International Conference on Services Computing (2010),” pp.
517-520.
Cong Wang, Qian Wang, Kui Ren, and Wenjing Lou, “Ensuring Data Storage Security in Cloud Computing” proceeding of International
workshop on Quality of service 2009”, pp.1-9.
Gary Anthes, “Security in the cloud,” In ACM Communications (2010), vol.53, Issue11, pp. 16-18.
Kresimir Popovic, Željko Hocenski, “Cloud computing security issues and challenges,” MIPRO 2010, pp. 344-349.
Kikuko Kamiasaka, Saneyasu Yamaguchi, Masato Oguchi, “Implementation and Evaluation of secure and optimized IP-SAN Mechanism,”
Proceedings of the IEEE International Conference on Telecommunications, May 2007, pp. 272-277.
Luis M. Vaquero, Luis Rodero-Merino, Juan Caceres1, Maik Lindner, “A Break in Clouds: Towards a cloud Definition,” ACM
SIGCOMM Computer Communication Review, vol. 39, Number 1, January 2009, pp. 50-55.
Patrick McDaniel, Sean W. Smith, “Outlook:
Cloudy with a chance of security challenges and improvements,” IEEE Computer and
reliability societies (2010), pp. 77-80.
Sameera Abdulrahman Almulla, Chan Yeob Yeun, “Cloud Computing Security Management,” Engineering systems management and its
applications (2010), pp. 1-7.
Steve Mansfield-Devine, “Danger in Clouds”, Network Security (2008), 12, pp. 9-11.
Anthony T. Velte, Toby J.Velte, Robert Elsenpeter, Cloud Computing: A Practical Approach, Tata Mc GrawHill 2010.
Authors:
T.P.Mote, S.D.Lokhande
Paper Title:
Temperature Control System Using ANFIS
Abstract: This paper describes three important aspects: design, simulation and Implementation of Adaptive Neuro
fuzzy system applied to the temperature variable of a thermal system with a range of 250C to 500C.An Adaptive
Neuro Fuzzy Inference System (ANFIS) based controller is proposed for water temperature control. The generation
of membership function is a challenging problem for fuzzy sytems and the response of fuzzy systems depends mainly
on the membership functions. The ANFIS based input – output model is used to tune the membership functions in
fuzzy system. Experimental results are compared with the conventional PID Controller and Neural Network
Controller. All the controllers are tested in various operating conditions and varying set point changes and also for
disturbance rejection. This shows that better performance can be achieved with ANFIS tuning.
26.
Keywords: ANFIS, Artificial neural network, PID, Temperature control.
156-161
References:
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27.
Kaijun Xu, Xiaoping Qiu ,Xiaobing ,Li Yang Xu “A dynamic neuro-fuzzy controller for gas-Fired water heater”, 3304-9/08 /2008 IEEE.
Valdez D., Ortiz V., Cabrera A. and Chairez I “Extended Kalman FilterWeights Adjustment For Neonatal Incubator Neurofuzzy
Identification”, 0-7803-9489-5/06/$20.00/©2006 IEEE.
Otman M. Ahtiwash and Mohd Zaki Abdulmuin, V.N. Alexandrov “An Adaptive Neuro-Fuzzy Approach for Modeling and Control of
Nonlinear Systems”, ICCS 2001, LNCS 2074, 198–207, 2001. Springer-Verlag Berlin Heidelberg.
J. A. Vieira, F. Morgado Dias and A. M. Mota “Hybrid Neuro-Fuzzy Network-Priori Knowledge Model in Temperature Control of a Gas
Water Heater System”, 0-7695-2457-5/0 /2005, IEEE.
S.Ravi P .A.Balakrishnan, “Modeling And Control of an ANFIS Temperature Controller For Plastic Extrusion Process”, 978-1-4244-77708/10/2010 IEEE.
Advanced Control Schemes for Temperature Regulation of Air Heat Plant 0-7803-5406- 0/99/1999, IEEE.
Marzuki Khalid and Sigeru Omatu “A Neural Network Controller for Temperature Control System”, 0272- 1708/92/1992IEEE.
Ajay B Patil “Adaptive Neuro Fuzzy Controller for Process Control System”, 978-1-4244-2806-9/08/2008, IEEE.
Authors:
Prashana Balaji V., Anvita Gupta Malhotra, Khushhali Menaria
Paper Title:
Flux Balance Analysis of Melanogenesis Pathway
Abstract: A computational model could serve as a conventional engineering approach to uncover the biochemistry
of the metabolic pathways. These would dynamically mimic the pathways in-silico. Flux Balance Analysis (FBA) is
one such method wherein characterization of growth yields, bio-energy production, environmental conditions and
robustness under knock out & knock down can be studied. We have built a comprehensive dynamic platform of
integrated network for melanogenesis pathway containing 6 major reactions. Wherein detailed stoichiometric matrix
of the pathway reactions is constructed followed by defining constrains and objective function. Subsequently, these
are optimized using linear programming to give us resultant fluxes. Using this model, vulnerability of the enzymes in
these pathways are studied; essentiality of participating enzymes are established and varied computational gene
knock-out experiments which can decipher effect of inhibition on metabolic circuit are performed. Results of the
simulations were in corroboration with published results and predictions were validated. However, this platform can
enables us to make elaborate prediction in the known modeled domain and later with amalgamation of more
modelled pathways into this network; a comprehensive virtual cell can be constructed.
Keywords: Melanogenesis, Flux Balance Analysis (FBA), Pheomelanin, Eumelanin, Systems Biology.
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The Fourth International Conference on Computational Systems Biology, 2010 (September 9-11), pp. 331-338
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of Sciences, Vol. 270(3), 2003, pp. 415-421
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data", Nature Biotechnology, Vol. 19(2), 2001, pp. 125-130
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Authors:
N.Manikandan, M.Sakthiganesh, P.J.Kumar, M.Senthil Kumar
Paper Title:
Web based Farmers Bulletin for agricultural development using PAP Approach
Abstract: In the present era entire world is focusing on agricultural development because of increased population
and decreased agricultural production. Reason for decrease in production of agricultural products differs from place
to place. The main aim here is to support the farmers in their decision making on which mechanism to choose best
for a better productivity at their arms reach. The proposed system focused to increase the profit of the farmer by
increasing the efficiency of agricultural input and reducing the cost and risk of production. This can be achieved by
providing timely advice to the farmer like, dynamic weather forecasting and use of knowledge engineering to extract
best suitable Agricultural information from various source. The PAP (Preprocess Associate and Predict) architecture
is used for performing knowledge extraction and prediction process. This technique can handle all type of
information.
Keywords: Agricultural Input, PAP
References:
1.
2.
3.
4.
5.
Semantic Web based Integrated Agriculture Information Framework by Muhammad Shoaib, Amna Basharat, Second International
Conference on Computer Research and Development-2010
2008 SAARC AGRINET(www.saarcagri.net) has been formed and that was the good initiative for making the Library of Agricultural
Information.
An ongoing research at MOTOROLA Corporation on the topic “Precision Agriculture- A smart farming technique “ which aims at
Information based Agriculture development.
O. Folorunso, et al.. An Agent-based model for Agricultural Ecommerce System. Informantion Technology Journal, 2006,(2):230.
Cui Hai-xia, Cui ling-yun Analysis of Agricultural Applications of E-commerce Model Based on Construction of Modern Agricultural
System and “The paper is sponsored by the project of Hebei Agricultural University” IEEE-2010
171-174
6.
A Building an e-Agriculture
Business Integration Platform with Web Services Composition by Jianqiang Hu, FengE Luo, Guiping Liao
IEEE conference of information sphere-2008
7. Network Computing for Agricultural information System by Seishi Ninomiya, Matthew Laurenson and Takuji Kiura.
8. Developing agricultural models using MetBroker by Laurenson, M. R., A. Otuka and S. Ninomiya.
9. S.Chaudhuri, Umeshwar Dayal, V.Ganti, Database Technology for decision support system, IEEE Computer.
10. Role of Information Technology in Agriculture and its scope in India, S.C. Mittal.
11. DEMBroker -Consistent access for software applications to digital elevation models by Lurenson, M. R. and S. Ninomiya.
12. A model of decision-making and information flows for information-intensive agriculture by Fountas, S.
Authors:
M.A.P. Chamikara, Y.P.R. D. Yapa, S.R.Kodituwakku, J. Gunathilake
Paper Title:
SL-SecureNet: Intelligent Policing Using Data Mining Techniques
Abstract: Many police departments all around the world lack of good and efficient crime recording and analysis
systems. The vast geographical diversity and the complexity of crime patterns have made the analyzing and
recording of crime data even difficult. According to the Sri Lankan police department, they face these problems for
many years. This paper presents an intelligent crime analysis and recording system designed to overcome problems
that appear mainly in the Sri Lankan police department. The proposed system is a GIS based system which comprises
of data mining techniques such as Hotspot detection, Crime clock, Crime comparison, Crime pattern visualization,
Outbreaks detection and the Nearest police station detection. Salient features of the proposed system include a rich
environment for crime data analysis and a simplified environment for location based data analysis. It facilitates the
identification of various types of crimes in detail and assists the police personals to control and prevent such incident
efficiently. The SL-SecureNet was tested for about 1000 crime records. The test results indicated that it functions in
an efficient and reliable manner.
29.
Keywords: Crime Analysis, Crime Investigation, Data Mining, Intelligent Policing
175-180
References:
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Craig Walls & Ryan Breidenbach, Spring in Action, 2nd Edition, Manning Publications, USA(2005).
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Chen, H.,W.Chung, et al.(2004). Crime data mining: a general framework and some examples. Computer 37 (4):50-56.
Authors:
Pravin D. Pardhi, Prashant L. Paikrao, Devendra S. Chaudhari
Paper Title:
Introduction to Query Techniques for Large CBIR Systems
Abstract: Content-based image retrieval (CBIR) has received much research interest since couple of decades. The
query technique for CBIR using relevance feedback is being used by the researchers, to search desired image from
huge collection of visual data. This paper reviews various processes of image search and few query techniques.
Keywords: Content-based image retrieval (CBIR), image search, query technique, relevance feedback (RF).
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Authors:
Chetna Chand, Amit Thakkar, Amit Ganatra
Paper Title:
Sequential Pattern Mining: Survey and Current Research Challenges
Abstract:
The concept of sequence Data Mining was first introduced by Rakesh Agrawal and Ramakrishnan
Srikant in the year 1995. The problem was first introduced in the context of market analysis. It aimed to retrieve
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185-193
frequent patterns in the sequences of products purchased by customers through time ordered transactions. Later on its
application was extended to complex applications like telecommunication, network detection, DNA research, etc.
Several algorithms were proposed. The very first was Apriori algorithm, which was put forward by the founders
themselves. Later more scalable algorithms for complex applications were developed. E.g. GSP, Spade, PrefixSpan
etc. The area underwent considerable advancements since its introduction in a short span. In this paper, a systematic
survey of the sequential pattern mining algorithms is performed. This paper investigates these algorithms by
classifying study of sequential pattern-mining algorithms into two broad categories. First, on the basis of algorithms
which are designed to increase efficiency of mining and second, on the basis of various extensions of sequential
pattern mining designed for certain application. At the end, comparative analysis is done on the basis of important
key features supported by various algorithms and current research challenges are discussed in this field of data
mining.
Keywords: Sequential Pattern, Sequence Database, Itemsets, Apriori.
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Data Mining and Knowledge Discovery (PKDD’98), Nantes, France, Sept. 1998, pp. 176–184.
M. Garofalakis, R. Rastogi, and K. Shim, "SPIRIT: Sequential pattern mining with regular expression constraints", VLDB'99, 1999.
Han J., Dong G., Mortazavi-Asl B., Chen Q., Dayal U., Hsu M.-C., ”Freespan: Frequent pattern-projected sequential pattern mining”,
Proceedings 2000 Int. Conf. Knowledge Discovery and Data Mining (KDD’00), 2000, pp. 355-359.
Han, J., Pei, J., Mortazavi-Asl, B. and Zhu, H., “Mining access patterns efficiently from web logs”, In Proceedings of the Pacific- Asia
Conference on Knowledge Discovery and Data Mining (PAKDD’00) Kyoto Japan, 2000.
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ICDE'01, 2001.
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Knowledge Management (CIKM’01), Atlanta, GA, Nov. 2001 pp. 81–88.
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8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining-2002.
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on Data Mining (SDM), San Fransico, CA, 2003, pp. 166–177.
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,2007, pp. 133 –160.
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43, No. 1, Article 3, Publication date: November 2010.
J. Han, J. Pei, and X. Yan, StudFuzz,”Sequential Pattern Mining by Pattern-Growth: Principles and Extensions”, 180, 2005, pp. 183–220.
J.Pei, J.Han, B.MortazaviAsl, J.Wang, H.Pinto, Q.Chen, U.Dayal and M.-C.Hsu, “Mining sequential patterns by pattern-growth: The
PrefixSpan approach”, IEEE Transactions on Knowledge and Data Engineering, vol.16, no.11, 2004, pp. 1424-1440.
Yen-Liang Chen, Mi-Hao Kuo, Shin-Yi Wu, Kwei Tang, ”Discovering Recency, frequency, and monetary (RFM) sequential patterns from
customers’ purchasing data”, Electronic Commerce Research and Applications 8 (2009), 2009, pp. 241–251.
Hao-En Chueh, “Mining Target-Oriented Sequential Patterns with Time-Interval”, International journal of computer science & information
Technology (IJCSIT) Vol.2, No.4, August 2010.
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workshop on Knowledge Economy and Electronic Commerce, Vol. 42, Iss. 2 ,pp. 1203-1215, 2006.
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Authors:
Rakesh Kumar, Jyotishree
Paper Title:
Effect Of Polygamy With Selection In Genetic Algorithms
Abstract: Genetic algorithms are based on evolutionary ideas of natural selection and genetics. Important operators
used in GA are selection, crossover and mutation, where selection operator is used to select the individuals from a
population to create a mating pool which will participate in reproduction process. A number of selection operators
have been used in the past like roulette wheel selection, ranked selection, elitism etc. where elitism is used to enforce
the preservation of best solution found so far unless a new best individual is discovered. Elitism is implemented by
copying the best individual of a generation into the next generation without any change. In this paper a particular
form of elitism, polygamy, is proposed and implemented in which in each generation the best individual is selected
and that participates in crossover with all other individuals in the mating pool created by any other selection
mechanism. Polygamy has also been observed in a number of animals like lion, elk, baboons etc. Results obtained
show the improvement over traditional selection operators available in literature.
194-199
Keywords: genetic algorithm, polygamy, rank selection, roulette wheel, selection.
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algorithms”, Proceedings of the 2005 International Conference on Computational Intelligence for Modelling, Control and Automation and
International Conference on Intelligent Agents, Web Technologies and Internet Commerce, 2005
Francisco B. Pereira and Jorge M. C. Marques, “A Hybrid Evolutionary Algorithm for Cluster Geometry Optimization: the importance of
structural elitism”, Proceedings of Eighth International Conference on Hybrid Intelligent Systems, 2008, pp 911-914.
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Authors:
Ram Krishna Rathore, Amit Sarda, Rituraj Chandrakar
An Approach to optimize ANN Meta model with Multi Objective Genetic Algorithm for multiPaper Title:
disciplinary shape optimization
Abstract: In several design cases, designers need to optimize a number of responses concurrently. A general
approach for the multiple response cases optimization start with using the regression models to calculate the
correlations between response functions and control factors. Then, a system for collecting various response functions
together into a one quantity, such as an objective function, is engaged and, at last, an optimization technique is used
to calculate the best combinations for the control functions. A different method proposed in this paper is to use an
artificial neural network (ANN) to calculate the parameter response functions. At the optimization stage, a multi
objective genetic algorithm (MOGA) is used in combination with an objective functions to establish the optimum
conditions for the control functions. A crane hook example has been taken to optimize multiple shape parameter
responses to with stand a new loading condition. The results estimate the reduction in mass and sufficient factor of
safety to show the proposed approach for the optimization of multi- disciplinary shape optimization problems.
Keywords: ANN, MOGA, Shape optimization, Meta modeling
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(2008)
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with Moving Least-Square approximation”, journal of materials processing technology 209 ( 2009 ) pp. 289–296
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Account of Practical Requirement”, Institute of Materials, London England ,2011, ISBN No- 1861250045
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Authors:
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Paper Title:
Architecture Of Wireless Network
Abstract: To allow for wireless communications among a specific geographic area, an base stations of
communication network must be deployed to allow sufficient radio coverage to every mobile users. The base
stations, successively, must be linked to a central hub called the MSC (mobile switching centre). The mobile
switching centre allow connectivity among the PSTN (public switched telephone network) and the numerous
wireless base stations, and finally among entirely of the wireless subscribers in a system. The global
telecommunications control grid of PSTN which associate with conventional (landline) telephone switching centre
(called central office) with MSCs all around the world.
Keywords: Network, MSC, PSTN, Cellular system.
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Abstract:
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techniques along with some clustering algorithms are described. Further k-means algorithm, its limitations and a new
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An Empirical Evaluation of Density-Based Clustering Techniques
212-215
Abstract: Emergence of modern techniques for scientific data collection has resulted in large scale accumulation
of data pertaining to diverse fields. Conventional database querying methods are inadequate to extract useful
information from huge data banks. Cluster analysis is one of the major data analysis methods. It is the art of detecting
groups of similar objects in large data sets without having specified groups by means of explicit features. The
problem of detecting clusters of points is challenging when the clusters are of different size, density and shape. The
development of clustering algorithms has received a lot of attention in the last few years and many new clustering
algorithms have been proposed. This paper gives a survey of density based clustering algorithms. DBSCAN [15] is a
base algorithm for density based clustering techniques. One of the advantages of using these techniques is that
method does not require the number of clusters to be given a prior nor do they make any kind of assumption
concerning the density or the variance within the clusters that may exist in the data set. It can detect the clusters of
different shapes and sizes from large amount of data which contains noise and outliers. OPTICS [14] on the other
hand does not produce a clustering of a data set explicitly, but instead creates an augmented ordering of the database
representing its density based clustering structure. This paper shows the comparison of two density based clustering
methods i.e. DBSCAN [15] & OPTICS [14] based on essential parameters such as distance type, noise ratio as well
as run time of simulations performed as well as number of clusters formed needed for a good clustering algorithm.
We analyze the algorithms in terms of the parameters essential for creating meaningful clusters. Both the algorithms
are tested using synthetic data sets for low as well as high dimensional data sets.
Keywords: DBSCAN, OPTICS, DENCLUE, Spatial Data, Intra Cluster, Inter Cluster.
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Tutorial for WEKA https://blog.itu.dk/SPVC-E2010/files/2010/11/wekatutorial.pdf
Weka manual for version3.6.3 by Eibe Frank and Mark Hall
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Authors:
Pushpaja V. Saudagare, D.S. Chaudhari
Paper Title:
Facial Expression Recognition using Neural Network –An Overview
Abstract:
In many face recognition systems the important part is face detection. The task of detecting face is
complex due to its variability present across human faces including color, pose, expression, position and orientation.
So using various modeling techniques it is convenient to recognize various facial expressions. In the field of image
processing it is very interesting to recognize the human gesture by observing the different movement of eyes, mouth,
nose, etc. Classification of face detection and token matching can be carried out any neural network for recognizing
the facial expression. This paper reviews various techniques of facial expression recognition systems using
MATLAB (neural network) toolbox.
Keywords: face recognition, neural network, and facial expression recognition.
216-223
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Authors:
Hadi Razmi, Atabak Mashhadi Kashtiban
Nonlinear PID-Based Analog Neural Network Control for a Two Link Rigid Robot Manipulator And
Paper Title:
Determining the Maximum Load Carrying Capacity
Abstract:
An adaptive controller of nonlinear PID-based analog neural networks is developed for the point to
point and orientation-tracking control of a two link rigid robot manipulator. In each case, the maximum load carrying
capacity of robot manipulator subject to accuracy and actuators constraints is obtained. In comparison with
conventional PID method, the use of neural network controller can increase maximum load carrying capacity of
robot manipulators. A superb mixture of a conventional PID controller and a neural network, which has powerful
capability of continuously online learning, adaptation and tackling nonlinearity, brings us the novel nonlinear PIDbased analog neural network controller. Computer simulations were carried out in two axes manipulator and the
effectiveness of the proposed control algorithm was demonstrated through the experiments, which suggests its
superior performance and increasing the maximum load carrying capacity of this manipulator.
Keywords: Analog neural network, Adaptive control, Maximum load carrying capacity, Nonlinear PID control.
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Authors:
Ashish B. Ingale, D. S. Chaudhari
Paper Title:
Speech Emotion Recognition
Abstract: In human machine interface application, emotion recognition from the speech signal has been research
topic since many years. To identify the emotions from the speech signal, many systems have been developed. In this
paper speech emotion recognition based on the previous technologies which uses different classifiers for the emotion
recognition is reviewed. The classifiers are used to differentiate emotions such as anger, happiness, sadness, surprise,
neutral state, etc. The database for the speech emotion recognition system is the emotional speech samples and the
features extracted from these speech samples are the energy, pitch, linear prediction cepstrum coefficient (LPCC),
Mel frequency cepstrum coefficient (MFCC). The classification performance is based on extracted features.
Inference about the performance and limitation of speech emotion recognition system based on the different
classifiers are also discussed.
Keywords: Classifier, Emotion recognition, Feature extraction, Feature Selection.
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235-238
Authors:
Nikita Bhatt, Amit Thakkar, Amit Ganatra
A Survey & Current Research Challenges in Meta Learning Approaches based on Dataset
Paper Title:
Characteristics
Abstract: Classification is a process that predicts class of objects whose class label is unknown. According to No
Free Lunch (NFL) theorem, there is no single classifier that performs better on all datasets. Meta learning is one of
the approaches that acquired knowledge based on the past experience. The knowledge in Meta-Learning is acquired
from a set of meta-examples which stores the features of the problem and the performance obtained by executing a
set of candidate algorithms on Meta Features. Based on the experience acquired by the system during training phase,
ranking of the classifiers is provided based on considering various measures of classifiers.
Keywords: Classification, Meta Learning, Ranking
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Authors:
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Paper Title:
A Survey and Current Research Challenges in Multi-Label Classification Methods
Abstract: Classification is used to predict class of unseen instance as accurate as possible. Multi label classification
is a variant of single label classification where set of labels associated with single instance. Multi label classification
is used by modern applications, such as text classification, functional genomics, image classification, music
categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification
and evolution measure for multi-label classification. Also done comparative analysis of multi label classification
methods on the basis of theoretical study and than on the basis of simulation done on various data sets.
Keywords: Classification, Single label problem, Multi label problem
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Authors:
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Numerical Analysis of Helicopter Rotor at 400 RPM
248-252
Abstract:
In this paper the main objective of this simulation is to analyze the flow around an isolated main
helicopter rotor at a particular main rotor speed of 400 rpm, and angle of attack of 8 degrees and blades of the
helicopter Eurocopter AS350B3 which uses the blade profile of standard ONERA OA209 airfoil during hovering
flight conditions. For CFD analysis, the Motion Reference Frame (MRF) method with standard viscous k-ε turbulent
flow model was used on modeling the rotating rotor operating in hovering flight. The Ansys fluent was used for the
purpose of analysis.
Keywords: Aerodynamics, CFD, helicopter, hovering, MRF, rpm.
42.
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Authors:
R.Gomathi, A.K.Gnanasekar, V.Nagarajan
Performance Analysis using Adaptive Decision for Parallel Interference Cancellation Receiver in
Paper Title:
Asynchronous Multicarrier DS-CDMA Systems
Abstract: In this paper, we present and analyze the performance of asynchronous multicarrier direct-sequence code
division multiple-access (DS-CDMA) system using adaptive decision at the receiver. In addition to that parallel
interference cancellation (PIC) scheme is presented at the receiver. The PIC scheme offers better interference
suppression capability. At the last stage, the interference cancelled outputs from all the subcarriers are maximal ratio
combined (MRC) and feeds viterbi decoder. Convolutionally coded multicarrier DS-CDMA system compares BER
from the decision which helps in further improvement.
Keywords: Interference cancellation, Multiple access Interference.
43.
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259-264
Authors:
Reema Patel, Amit Thakkar, Amit Ganatra
A Survey and Comparative Analysis of Data Mining Techniques for Network Intrusion Detection
Paper Title:
Systems
Abstract:
Despite of growing information technology widely, security has remained one challenging area for
computers and networks. In information security, intrusion detection is the act of detecting actions that attempt to
compromise the confidentiality, integrity or availability of a resource. Currently many researchers have focused on
intrusion detection system based on data mining techniques as an efficient artifice. Data mining is one of the
technologies applied to intrusion detection to invent a new pattern from the massive network data as well as to reduce
the strain of the manual compilations of the intrusion and normal behavior patterns. This article reviews the current
state of art data mining techniques, compares various data mining techniques used to implement an intrusion
detection system such as Decision Trees, Artificial Neural Network, Naïve Bayes, Support Vector Machine and KNearest Neighbour Algorithm by highlighting advantages and disadvantages of each of the techniques. Finally, a
discussion of the future technologies and methodologies which promise to enhance the ability of computer systems to
detect intrusion is provided and current research challenges are pointed out in the field of intrusion detection system.
44.
Keywords: Classification, Data Mining, Intrusion Detection System
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Volume 2, pp. 8-14. ISSN 2047-3338 .
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265-271
Techniques”. IJCA, Volume 35 –No.8, December 2011.
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Authors:
Rajesh Shrivastava, Pooja Mehta (Gahoi)
Paper Title:
Analysis of Secure Mobile Agent System
Abstract: As a recently emerging distributed computing paradigm, mobile-agent technology attracts great interests
because of its salient merits. However, it also brings significant security concerns, among which the security
problems between a mobile agent and its platforms are of primary importance. While protecting a platform (platform
or host security) can benefit from the security measures in a traditional client-server system, protecting a mobile
agent (mobile-agent or code security) has not been met in traditional client-server systems and is a new area
emerging with mobile-agent technology. We analyzed the different types of security issues related to mobile agent.
After analysis, we found that there are many kind of technology available to ensure mobile agent security. But not a
single technology provides complete solution for the same. We proposed an algorithm in which we use monitoring
agent and dummy agent in place of original mobile agent. Monitoring agent checks the behavior of next node in the
network. If monitoring agent finds the node suspicious, it sends the alert acknowledgment to original agent and
original agent doesn’t travel to that suspicious node.
Keywords: Mobile agent, distributed systems, security.
References:
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Network Computing and Information Security, pp 218-222.
Rajwinder Singh and Mayank Dave, "Rescuing Data of Mobile Agents Blocked by Malicious Hosts in e-Service Applications", 2011
International Conference on Multimedia, Signal Processing and Communication Technologies, pp 24-27.
Fan Linna and Liu Jun, "A Free-Roaming Mobile Agent Security Protocol against Colluded Truncation Attack without Trusted Third Party",
Business Management and Electronic Information (BMEI), 2011 International Conference, Volume: 2, pp 14 - 18.
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Minnesota,1998.
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Authors:
D.Sasirekha, E.Chandra
Paper Title:
Text To Speech: A Simple Tutorial
272-274
Abstract: Research on Text to Speech (TTS) conversion is a large enterprise that shows an impressive improvement
in the last couple of decades. This article has two main goals. The first goal is to summarize the published literatures
on Text to Speech (TTS), with discussing about the efforts taken in each paper. The second goal is to describe
specific tasks concentrated during Text to Speech (TTS) conversion namely, Preprocessing & text detection,
Linearization, Text normalization, prosodic phrasing, OCR, Acoustic processing and Intonation. We illustrate these
topics by describing the TTS synthesis. This system will be highly useful for an illiterate and vision impaired people
to hear and understand the content, where they face many problems in their daily life due to the differences in their
script system. This paper starts with the introduction to some basic concepts on TTS synthesis, which will be useful
for the readers who are less familiar in this area of research.
Keywords: TTS.
References:
1.
2.
3.
4.
5.
Frances Alias, Xavier Servillano, Joan Claudi socoro and Xavier Gonzalvo “Towards High-Quality Next Generation Text-to-Speech
Synthesis:A multi domain Approach by Automatic Domain Classification”,IEEE Transactions on AUDIO,SPEECH AND LANGUAG
PROCESSING, VOL16,NO,7 september 2008.
Qing Guo, Jie Zhang, Nobuyuki Katae, Hao Yu , “High –Quality Prosody Generation in Mandrain Text-to-Speech system”, FujiTSu
Sci.Tech,J., vol.46, No.1,pp.40-46 ,2010.
Gopalakrishna anumanchipalli,Rahul Chitturi, Sachin Joshi, Rohit Kumar, Satinder Pal Singh,R.n.v Sitaram,D.P.Kishore, “Development of
Indian Language Speech Databases for Large Vocabulary Speech Recognition System”,
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G.Bailly, N.Campbell and b.Mobius, “ISCA special session: Hot topics in speech synthesis”, in proc.Eurospeech,Genea, Switzerland, 2003,
pp 37-40.
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Monica,2002,pp. 99-106.
Text To Speech Synthesis - a knol by Jaibatrik Dutta .
Silvio Ferreia,Celina Thillou, Bernaud Gosselin, “From Picture to Speech: an Innovative Application for Embedded Environment”,
M.Nageshwara Rao, Samuel Thomas, T.Nagarajan and Hema A.Muthy, “Text-to-Speech Syntheis using syllable line units”
Jindrich Matousek, Josef Psutks, Jiri Krita, “Design of speech Corpus for Text-to-Speech Synthesis”
Authors:
Miriyala Markandeyulu, Bussa V.R.R.Nagarjuna, Akula Ratna Babu, A.S.K.Ratnam
Paper Title:
A Study of Role Based Access Control policies and Constraints
Abstract: Access control policies are constraints that protect computer-based information resources from
unauthorized access. Role-Based Access Control (RBAC) is used by many organizations to protect their information
resources from unauthorized access. RBAC policies are defined in terms of permissions that are associated with roles
assigned to users. A permission determines what operations a user assigned to a role can perform on information
resources. Role-based access control (RBAC) is also a powerful means for laying out higher-level organizational
policies such as separation of duty, and for simplifying the security management process. One of the important
aspects of RBAC is authorization constraints that express such organizational policies. This paper presents an
overview of Role- based access control policies and constraints.
47.
Keywords: Constraints, RBAC, Policies, UML.
279-282
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G.J. Ahn and M. E. Shin. Role-based authorization constraints specification using object constraint language. In Proceedings of the 10th
IEEE International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WET ICE ’01), pages 157–162,
Cambridge, Massachusetts, June 2001.
J. Warmer and A. Kleppe. The Object Constraint Language, Second Edition. Addison-Wesley, 2003.
D.F. Ferraiolo, D.R. Kuhn, R. Chandramouli, Role-based access control, Artec House, Boston, 2003.
J. Rumbaugh, I. Jacobson, G. Booch. The Unified Modeling Language Reference Manual, Second Edition. Reading, Mass., Addison Wesley
Longman, 2004.
Authors:
Hota H.S., Sahu Pushpanjali
A Comparative Study of Different Statistical Techniques Applied to Predict Share Value of State
Paper Title:
Bank of India (SBI)
Abstract: Prediction of share value is one of the critical job and is necessary for the current financial scenario, due
to the high uncertainty prediction system can not predict the share value with high accuracy. In this piece of research
work an attempt is made to analyze the prediction based on statistical techniques with special reference to the share
value of State Bank of India (SBI). The data that is downloaded consists share value for open, close, volume, high,
and low in equal interval of time from Jan-2003 to May-2011. Two different techniques ARIMA and Exponential
Smoothing is used to compare the accuracy. Statistical measure are carried out and it is found that expert modeler is
working well for the prediction of share value of SBI. The future value for the next 5 months from May-2011 from
both the models are also evaluated
48.
Keywords: Expert modeler, Exponential Smoothing, Auto Regressive Integrated Moving Average (ARIMA).
283-293
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hall 1994.
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Vatsal H. Shah,”Machine Learning Techniques for Stock Prediction”.
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Dr.B.N.Gupta(1995),”Statistics”, Sahitya Bhawan Publishers
R.J.Frank, N.Davey, S.P.Hunt Department of Computer Science, University of Hertfordshire,
Javier Contreras ,Francisco J. Nogales and Autonio J.Conejo “ ARIMA models to prtedict next-day electricity prices “ IEEE transcation
on power systems vol 18 ,No 3 august 2003.
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Authors:
K.Poornima, R.Kanchana
Paper Title:
A Method to Align Images Using Image Segmentation
Abstract:
Most high level interpretation task rely on image alignment process. In this work, a method for
automated image alignment through image segmentation is proposed. The image data need to be analyzed, preferably
by automatic processing techniques because of the huge amount of data. This new approach mainly consists in
combining several segmentations of the pair of images to be registered. It can be applied to a pair of satellite images
with simulated translation, and to real remote sensing examples comprising different viewing angles, different
acquisition dates and different sensors. This process allows the alignment of pairs of images (multitemporal and
multisensor) with differences in rotation and translation, with small differences in the spectral content, leading to the
subpixel accuracy.
Keywords: Image alignment, Image segmentation, Wiener filtering.
References:
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2.
L.G. Brown, “A Survey of image registration techniques”, comput. Surv., vol. 24, no. 4, pp. 325-376,1992.
C.I. Chang, Y. Du, J. Wang, S.M. Guo, and P.D. Yhouin, “Survey and comparative analysis of entropy and relative entropy thresholding
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simulations,” IEEE Trans.
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91–110, Nov. 2004.
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subpixel image registration of multiangle CHRIS/Proba data,” IEEE Trans.
Geosci. Remote Sens., vol. 48, no. 7, pp. 2829–2839, Jul. 2010.
K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool, “A comparison of affine
region detectors,” Int. J. Comput. Vis., vol. 65, no. 1/2, pp. 43–72, Nov. 2004
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pp. 1615–1630, Oct. 2005.
K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool, “A comparison of affine
region detectors,” Int. J. Comput. Vis., vol. 65, no. 1/2, pp. 43–72, Nov. 2004.
Authors:
S. J. Suji Prasad, Susan Varghese, P. A. Balakrishnan
Paper Title:
Particle Swarm Optimized I-PD Controller for Second Order Time Delayed System
Abstract:
In this paper, I-PD controller is optimized using particle swarm intelligence for a Second Order Time
Delayed System. Optimization is done on the basis of performance indices like settling time, rise time, peak
overshoot, ISE (integral square error) and IAE (integral absolute error). In industrial processes, PID controllers and
its variants are most preferred though there are significant developments in the control systems. If the parameter of
controller is not properly designed, then desired control output may fail. The simulation results with optimized I-PD
controller proved to be giving better performances compared with Ziegler Nichols and Arvanitis tuning.
Keywords: Proportional integral and derivative (PID); Proportional kick; Derivative kick; Settling time; Rise time
and Tuning.
References:
50.
J. Astrom, and T. Hagglund. “The future of PID control”, Control Engineering Practice, vol. 9, November 2001, pp. 1163–1175.
Nagaraj B, P. Vijayakumar (2011), ‘A Comparative Study Of PID Controller Tuning Using GA, EP, PSO AND ACO’, Journal of
Automation, Mobile Robotics & Intelligent Systems,Volume 5, No 2 pp 42-48
3. Kiam Heong Ang, Gregory Chong and Yun Li (2005), ‘PID Control System Analysis, Design, and Technology’, IEEE Transactions on
control systems technology, vol. 13, no. 4
4. Yun li, Kiam Heong Ang, and Gregory c.y. Chong (2006), ‘PID Control System Analysis and Design - Problems, Remedies and Future
Directions’, IEEE Control systems magazine, pp32-41
5. Aidan O'Dwyer (2006), ‘Handbook of PI and PID Controller Tuning Rules’, (2nd Edition),Published by ICP
6. Riccardo Poli ,James Kennedy and Tim Blackwell (2007), ‘Particle swarm optimization-An overview’, Springer Science , Business Media,
LLC
7. Russell C Eberhart and Yuhui Shi (2001), ‘Particle Swarm Optimization: Developments, Applications and Resources’, IEEE conference
8. Tushar Jain and M. J. Nigam, “Optimization of PD-PI Controller Using Swarm Intelligence”, International journal of computational
cognition, vol. 6, no. 4, December 2008.
9. Wen-wen Cai, Li-xin Jia, Yan-bin Zhang,Nan Ni (2010), ‘Design and Simulation of Intelligent PID Controller Based on Particle Swarm
Optimization’, IEEE conferences
10. Jacqueline Wilkie, Michael Johnson, Reeza Katebi (2002), ‘Control Engineering an Introductory Course’, pp 529-565
11. Giriraj Kumar S.M, Deepak Jayaraj and Anoop R Kishan (2010), ‘PSO based Tuning of a PID Controller for a High Performance Drilling
Machine’ International journal of computer applications, volume I-No.19
12. Rania Hassan, Babak Cohanim and Olivier de Weck (2004), ‘A Copmarison of Particle Swarm Optimization and the Genetic Algorithm’,
American Institute of Aeronautics and Astronautics.
1.
2.
299-302
Authors:
K.M.Pandey, Jagannath Rajshekharan and Sukanta Roga
Wall Static Pressure Variation In Sudden Expansion In Flow Through De Laval Nozzles At Mach 1.74
Paper Title:
And 2.23 In Circular Ducts Without Cavities: A Fuzzy Logic Approach
Abstract:
In this paper the analysis of wall static pressure variation has been done with fuzzy logic approach to
have smooth flow in the duct. Here there are three area ratio choosen for the enlarged duct, 2.89, 6.00 and 10.00. The
primary pressure ratio is taken as 2.65 and cavity aspect ratio is taken as 1 and 2. The study is analysed for length to
diameter ratio of 1,2,4 and 6. The nozzles used are De Laval type and with a Mach number of 1.74 and 2.23. The
analysis based on fuzzy logic theory indicates that the length to diameter ratio of 1 is sufficient for smooth flow
development if only the basis of wall static pressure variations is considered. Although these results are not
consistent with the earlier findings but this opens another method through which one can analyse this flow. This
result can be attributed to the fact that the flow coming out from these nozzles are parallel one.
51.
Keywords: wall static pressure, area ratio, pressure ratio, De Laval nozzle, Mach number.
References:
1.
2.
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recent advances in Mechanical Engineering, Dec 20-22, 1995, pp 1511-1518, Narosa publications, New Delhi, India, 1995, Volume 2
Pandey K M, Base flow in flow though nozzles with sudden expansion: a study in supersonic regime-2nd National Conference on Fluid
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International Conference on Advances in Mechanical and Industrial Engg, Dept of Mechanical and Industrial Engg., Roorkee, India, Feb 6-8,
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Dixit, U.S., Dixit, P.M., ‘Application of fuzzy set theory in the scheduling of a Tandem cold-Rolling Mill’, ASME, Vol. 122, p.494- 500
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121, p. 69- 76 (2002).
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Pandey, K.M., and Rathakrishnan E., ‘Influence of cavities on flow development in sudden expansion’, International Journal of Turbo and
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Pandey, K.M., and Rathakrishnan E., ‘Annular cavities for Base flow control’, International Journal of Turbo and Jet Engines, Vol. 23, p.
113- 127 (2006).
Authors:
S.Joshuwa, E.Sathishkumar, S.Ramsankar
Paper Title:
Advanced Rotor Position Detection Technique for Sensorless BLDC Motor Control
Abstract:
Brushless DC Motor drives have made a successful entrance into various sectors of industry such as
aerospace, automotive and home appliances due to its simple structure. The accurate knowledge of the rotor position
is required for good performance of brushless DC motors the need for the rotor angle information in BLDC has been
satisfied by use of some form of rotor position sensor. The position sensor used in BLDC drives have the
disadvantages of additional cost, electrical connections, mechanical alignment problems, and disadvantage of being
inherent source of unreliability. These bottlenecks results in several sensor less technique in recent years. A proposed
sensor less scheme is used to overcome the disadvantages of sensored scheme. The rotor position detection can be
estimated even at standstill and running conditions. The methods which is proposed in this project is 1. Back EMF
ZCD 2. RF Injection method.
Keywords: Brushless DC Motor, Back EMF ZCD
52.
References:
P. P. Carney and J. F Watson, “Review of position-sensor less operation of permanent-magnet machines,” IEEE Trans. Ind. Electron., vol.
53, no. 2, pp. 352–362, Apr. 2006.
2. C.-H. Chen and M.-Y. Cheng, “New cost effective sensor less commutation method for brushless dc motors without phase shift circuit and
neutral voltage,” IEEE Trans. Power Electron., vol. 22, no. 2, pp. 644–653, Mar.2007
3. C.-G. Kim, J.-H. Lee, H.-W. Kim, and M.-J. You, “Study on maximum torque generation for sensor less controlled brushless DC motor
with trapezoidal back EMF,” IEE Proc.-Electro. Power Appl., vol. 152, no. 2, pp. 277–291, Mar. 2005
4. J.X. She and S. Iwasaki, “Sensor less control of ultrahigh-speed PM brushless motor using PLL and third harmonic back EMF,” IEEE
Trans. Ind. Electron., vol. 53, no. 2, pp. 421–428, Apr. 2006.
5. P. Damodharan, R. Sandeep, and K. Vasudevan, “Simple position sensor less starting method for brushless DC motor,” IEEE Electro. Power
Appl., vol. 2, no. 1, pp. 49–55, Jan. 2008.
6. D. K. Kim, K. W. Lee, and B. I. Kwon, “Commutation torque ripple reduction in a position sensor less brushless dc motor drive,” IEEE
Trans. Power Electron., vol. 21, no. 6, pp. 1762–1768, Nov. 2006
7. C.-G. Kim, J.-H. Lee, H.-W. Kim, and M.-J. Youn, “Study on maximum torque generation for sensor less controlled brushless DC motor
with trapezoidal back EMF,” IEE Proc.-Electro. Power Appl., vol. 152, no. 2, pp. 277–291, Mar. 2005.
8. J. H. Song and I. Choy, “Commutation torque ripple reduction in brushless dc motor drives using a single dc current sensor,” IEEE Trans.
Power Electron., vol. 19, no. 2, pp. 312–319, Mar. 2004.
9. S. Wu, Y. Li, X. Miao, “Comparison of Signal Injection Methods for sensor less control of PMSM at Very Low Speeds”, IEEE Power
Electronics Specialists Conference, PESC 2007, June 2007 pp. 568 – 573.
10. M. Eskola, H. Tuusa, “Sensor less Control of Salient Pole PMSM Using a Low –Frequency Signal Injection”, European Conference on
1.
311-315
Power Electronics and Applications, Sept. 2005, pp. 1- 10
11. S. Ogasawara, H. Akagi, “An Approach to Real-Time Position Estimation at Zero and Low Speed for a PM Motor Based on Saliency”, IEEE
Transactions on Industry Applications, Vol. 34, No. 1, Jan./Feb 1998, pp. 163-168
12. Joohn Sheok Kim, Seung Ki Sul, “New Stand-Still Position Detection Strategy for PMSM Drive without Rotational Transducers”,
Conference Proceedings of the Ninth Annual Applied Power Electronics Conference and Exposition, APEC '94., Vol. 1, 13-17 Feb. 1994,
pp.363 – 369.
Authors:
Diponkar Kundu, Dilip Kumar Sarker, Md. Galib Hasan, Pallab Kanti Podder, Md. Masudur
Rahman
Paper Title:
Performance Analysis of an InGaAs Based p-i-n Photodetector
Abstract:
an InGaAs based p-i-n photodetector model is chosen in order to find out quantum efficiency,
photocurrent density, and normalized frequency response with and without RC effect. Normalized frequency
response is the most important factor in order to analysis the performance of p-i-n photodetector. Quantum
efficiency, photocurrent density, normalized frequency response curves are obtained by formulation which is done
from structure and MATLAB simulation. A relation for the fiber-to-waveguide coupling efficiency has also been
used to calculate the overall quantum-efficiency of waveguide photodetector [1]. Normalized frequency response is
obtained by varying value of frequency dependent transfer function of equivalent circuit model of p-i-n photodetector
with frequency. For enhancing bandwidth of photodetector, the parametric values of photodetector such as reverse
bias junction capacitance and resistance, has been optimized. The effect of carrier trapping at a heterointerface has
also been considered to study the frequency dependence of the photocurrent at low-bias voltages [1].
53.
Keywords: p-i-n photodetector, quantum efficiency, photocurrent density, normalized frequency response.
316-321
References:
1.
2.
3.
4.
5.
6.
7.
8.
Nikhil Ranjan Das, Senior Member, IEEE and M. Jamal Deen, Fellow, IEEE “A Model for the Performance Analysis and Design of
Waveguide p-i-n Photodetectors” IEEE Transactions on Electron Devices Vol. 53 No. 4 , April 2005.
Nikhil Ranjan Das, Senior Member, IEEE and M. Jamal Deen, Fellow, IEEE “Calculating the Photocurrent and Transit-Time-Limited
Bandwidth of a Hetero structure p-i-n Photodetector”IEEE Journal of Quantum Electronics Vol. 37 No.12 December 2001.
Paul K. Yu UCSD, Jacobs School of Engineering “Equivalent Circuit Analysis of Harmonic Distortions in Photodiode” University of
California Post prints 1998.
Kazutoshi Kato, Member, ZEEE, Susumu Hata, Kenji Kawano, Junichi Yoshida, SeniorMember, IEEE, and Atsuo Kozen “ A HighEfficiency 50 GHz InGaAs Multimode Waveguide Photodetector” IEEE Journal of Quantum Electronics Vol. 28 No.12 December 1992.
S. D. McDougall, M. J. Jubber, O. P. Kowalski, J. H. Marsh, and J.S. Aitchison, “GaAs/AlGaAs waveguide pin photodiodes with
nonabsorbing input facets fabricated by quantum well intermixing,” Electron. Lett., vol. 36, pp. 749–750, 2000.
C. L. Ho, M. C. Wu, W. J. Ho, J. W. Liaw, and H. L. Wang, “Effectiveness of the Pseudowindow for edge-coupled InP-InGaAs-InP PIN
photodiodes,” IEEE J. Quantum Electron., vol. 36, no. 3, pp. 333–338, Mar. 2000.
Jasprit Singh “ Optoelectronics, An Introduction To Materials And Devices” (Book)
John M. Senior “ Optical Fiber Communication Principles and Practice” Second Edition Prentice Hall of India (Book)
Authors:
Shah Kruti R., Bhavika Gambhava
Paper Title:
New Approach of Data Encryption Standard Algorithm
Abstract: The principal goal guiding the design of any encryption algorithm must be security against unauthorized
attacks. Within the last decade, there has been a vast increase in the accumulation and communication of digital
computer data in both the private and public sectors. Much of this information has a significant value, either directly
or indirectly, which requires protection. The algorithms uniquely define the mathematical steps required to transform
data into a cryptographic cipher and also to transform the cipher back to the original form. Performance and security
level is the main characteristics that differentiate one encryption algorithm from another. Here introduces a new
method to enhance the performance of the Data Encryption Standard (DES) algorithm is introduced here. This is
done by replacing the predefined XOR operation applied during the 16 round of the standard algorithm by a new
operation depends on using two keys, each key consists of a combination of 4 states
(0, 1, 2, 3) instead of the
ordinary 2 state key (0, 1). This replacement adds a new level of protection strength and more robustness against
breaking methods.
54.
Keywords: DES, Encryption, Decryption.
322-325
References:
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
55.
National Bureau of Standards – Data Encryption Standard, Fips Publication 46,1977.
O.P. Verma, Ritu Agarwal, Dhiraj Dafouti,Shobha Tyagi “ Performance Analysis Of Data Encryption Algorithms “ , 2011
Gurjeevan Singh, Ashwani Kumar Singla, K.S.Sandha “ Performance Evaluation of Symmetric Cryptography Algorithms, IJECT, 2011.
Diaa Salama, Abdul Elminaam, Hatem Mohamed Abdul Kader and Mohie Mohamed Hadhound “ Performance Evaluation of Symmetric
Encryption Algorithm “, IJCSNS, 2008
Dr. Mohammed M. Alani “ Improved DES Security” ,International Multi-Conference On System, Signals and Devices, 2010
Tingyuan Nie, Teng Zhang “ A Study of DES and Blowfish Encryption Algorithm”,TENCON, 2009
Afaf M. Ali Al- Neaimi, Rehab F. Hassan “ New Approach for Modified Blowfish Algorithm Using 4 – States Keys” , The 5th
International Conference On Information Technology,2011
J.Orlin Grabbe “The DES Algorithm Illustrated”
Dhanraj, C.Nandini, and Mohd Tajuddin “ An Enhanced Approch for Secret Key Algorithm based on Data Encryption Standard”,
International Journal of Research And Review in Computer Science, August 2011
Gurjeevan Singh, Ashwani Kumar, K.S. Sandha “A Study of New Trends in Blowfish Algorithm ”, International Journal of Engineering
Research and Application,2011
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Authors:
H. S. Behera, Ratikanta Pattanayak, Priyabrata Mallick
Paper Title:
An Improved Fuzzy-Based CPU Scheduling (IFCS) Algorithm for Real Time Systems
Abstract: Till now various types of scheduling algorithms are used for determining which process should be
executed by the CPU when there are multiple no. of processes to be executed.There are many conventional
approaches to schedule the tasks but no one is absolutely ideal. In this paper an improved fuzzy technique has been
proposed to overcome the drawbacks of other algorithms for better CPU utilization,throughput and to minimize
waiting time and turn around time.
Keywords:
effeciency
Task, process, fuzzification, priority, cpu utilization,fuzzy scheduler, turnaround time,scheduling
References:
1.
2.
3.
4.
5.
6.
7.
8.
Shata J. Kadhim , Kasim M. Al-Aubidy : ComputerEng. Dept, AlBlaqa’’Design and Evaluation of a Fuzzy Based CPU schedulilnlg
Algorithm’’ Applied University, Al-Salt, Jordan Computer Eng. Dept, Philadelphia University, Amman, Jordan,Springer-verlag Berlin
Heidelberg 2010, CCIS 70,pp. 45-52,2010
Stallings, Stallings, W.: Operating Systems Internals and Design Principles, 5th edn. Prentice-Hall,Englewood Cliffs (2004).
Yaashuwanth .C, Dr. R. Ramesh: ,”Design of Real Time Scheduler Simulator and Devlopment of Modified Round Robin Architecture
“,IJCSNS ,VOL.10 No.3,March (2010)
C. Lin and S. A. Brandt, "Efficient soft real-time processing in an integrated system," in Proc. 25th IEEE Real-Time Systems Symp.,(2004).
I. E. W. Giering and T. P. Baker, "A tool for the deterministic scheduling of real-time programs implemented as periodic Ada tasks," Ada
Lett., vol. XIV, pp. 54-73, (1994).
Shahzad, B., Afzal, M.T.: ,”Optimized Solution to Shortest Job First by Eliminating the Starvation”. In: The 6th Jordanian Inr. Electrical an
Jordan (2006)
Mr . Jeegar A Trivedi and Dr.Priti Srinivas Sajja ,”Improving efficiency of round robin scheduling using neuro fuzzy approach ” ,IJRRCS
vol.2,No. 2,April 2011
Mahdi Hamzeh,Sied Mehdi Fakhraie and Caro Lucas ,”Soft real time fuzzy task scheduling for multiprocessor systems”,world academy of
science,engineering and technology 28 (2007).
326-331
Authors:
Sripathy Mallaiah, Krishna Vinayak Sharma, M Krishna
Paper Title:
Development and Comparative Studies of Bio-based and Synthetic Fiber Based Sandwich Structures
Abstract: The present work was to focus on the investigation of the flexural and fatigue behaviour of flatwise,
edgewise compression and water absorption of E-glass/ epoxy, jute/ epoxy, bamboo/epoxy, glass-jute/epoxy, glassbamboo, Jute/bamboo /Polyurethane foam sandwich composites. Both natural and synthetic based sandwich
composites were synthesized with different fabric and polyurethane foam. The fiber/ resin ration for glass/epoxy is
65:35 and all other natural fibers composites are 50:50 ratio of fibre to resin weight fraction. The sandwich
specimens were prepared by hand adopting the lay-up method. This was followed by compression at room
temperature. Bamboo/glass hybrid structure yields higher value of core shear stress and facing bending stress. This
is higher than both pure glass, bamboo. This shows how effectively hybridization can be used to tailor materials for
our specific use.
Keywords: Natural fiber, polyurethane foam, sandwih structure, synthatic fiber.
References:
56.
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Williams GI, Wool RP. (2000), Composites from natural fibers and soy oil resins. Appl Compos Mater, vol. 7: pp. 421–32.
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Steeves C.A. and Fleck N. A. (2004) Material selection in sandwich beam construction. Scripta materialia, Vol.50, pp.1335-1339.
Gassan J. (2002), A study of fibre and interface parameters affecting the fatigue behaviour of natural fibre composites. Compos Part A:
Appl Sci Manuf, vol. 33(3): pp. 369–74.
Wool RP, Kusefoglu S, Zhao R, Palmese GI, Khot SN. High modulus polymers and composites from plant oils. Patent number: 6,121,398.
Can E, Kusefoglu S, Wool RP (2002). Rigid thermosetting liquid molding resins from renewable resources: (2) copolymers of soyoil
monoglycerides maleates with neopentyl glycol and bisphenol-A maleates. J Appl Polym Sci 2002;83:972.
Anon. (2002) The competitiveness of natural fibers based composites in the automotive sector: the Sisal Agribusiness in Brazil.
In:Materials Research Society Symposium––Proceedings, vol. 702, p. 113–39.
Santulli C. (2001) Post-impact damage characterisation on natural fibre reinforced composites using acoustic emission. NDT and E
International vol. 34(8): pp. 531–6.
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60.
Mohanty AK, Misra M, Drzal LT (2001). Surface modifications of natural fibers and performance of the resulting biocomposites: an
overview. Compos Interfaces, vol.8(5): pp. 313–43.
Gassan J, Chate A, Bledzki AK. (2001) Calculation of elastic properties of natural fibers. J Mater Sci vol..36(15): pp.3715–20.
Eichhorn SJ, Baillie CA, Zafeiropoulos N, Mwaikambo LY, Ansell MP, Dufresne A, (2001). Current international research into cellulosic
fibres and composites. J Mater Sci vol.36(9): pp. 2107–31.
Steeves C.A. and Fleck N. A. (2004) Collapse mechanisms of sandwich beams with composite faces and a foam core, loaded in three-point
bending. Part I; analytical models and minimum weight design. International Journal of Mechanical Sciences, Vol.46, pp. 561-583.
Authors:
Shyama M, P.Swaminathan
Paper Title:
Digital Linear and Nonlinear Controllers for Buck Converter
Abstract:
Both linear PID controllers and fuzzy controllers are designed and implemented for a buck converter.
Comparison between the two controllers is made in the aspect of design, implementation and experimental results.
Design of fuzzy controllers is based on heuristic knowledge of the converter and tuned using trial and error, while the
design of linear PID and PI controllers is based on the frequency response of the buck converter. Implementation of
linear controllers is quite straightforward, while implementation of fuzzy controllers has its unique issues. A
comparison of experimental results indicates that the performance of the fuzzy controller is superior to that of the
linear PID and PI controllers. The fuzzy controller is able to achieve faster transient response, has more stable steadystate response, and is more robust under different operating points.
Keywords: DC-DC Converter, Buck Converter,PID controller, Fuzzy logic controller
332-335
336-342
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Authors:
U.L.Sindhu, V.Sindhu, P.S.Balamurugan
Paper Title:
Privacy Aware Monitoring Framework For Moving Top-K Spatial Join Queries
Abstract: In moving object environment, it’s unfeasible for database to track the random object movement and to
store the locations of object exactly all the times. The basic issue in case of moving object monitoring is efficiency
and privacy. We used a framework for moving object to hide their own identities by execution of probabilistic range
monitoring queries. The Privacy-aware monitoring framework for spatial join queries which is flexible, it addresses
two issues; such as “efficiency and privacy” in monitoring moving object. Because of blurring exact position of
object and increase in unnecessary updates costs it’s not possible to provide accurate result. So, we propose an
efficient processing of continuously moving top-k spatial keyword (MkSK) queries over spatial query processing for
the problem of privacy aware monitoring framework. This develop an efficient query processing, evaluation and
reevaluation based on spatial queries which could be effective for computing safe zones that guarantee correct results
until the user remains in safe zone, the reported results will be valid and no limiting of frequent updates from objects.
The Voronoi Cell Optimization technique which accelerates depth sorting by clustering polygon has been
implemented. Our solution is common for moving queries employ safe zones. In our performance study, we compare
it with an existing approach using simulation. Our proposed approach outperforms than the conventional approaches
without compromising much on the concept of safe zone to save computation and communication costs.
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Keywords: Nearest-neighbor queries; probabilistic queries; range queries; spatial databases
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Beresford, A.; Stajano, F. (2003): Location Privacy in Pervasive Computing, IEEE Pervasive Computing, vol. 2, no. 1, pp. 46-55.
Cai, Y.; Hua K.A,; Cao, G. (2004): Processing Range-Monitoring Queries on Heterogeneous Mobile Objects, Proc. IEEE Int’l Conf. Mobile
Data Management (MDM),.
Chen, J.; Cheng, R. (2007): Efficient Evaluation Of Imprecise Location- Dependent Queries, Proc. IEEE Int’l Conf. Data Eng. (ICDE), pp.
586-595.
Cong, G.; Jensen, C. S; Wu, D. (2009): Efficient retrieval of the top-k most relevant spatial web objects, in PVLDB, pp. 337–348.
Gedik B.; Liu, L. (2005): Location Privacy in Mobile Systems: A Personalized Anonymization Model, Proc. IEEE Int’l Conf. Distributed
Computing Systems (ICDCS), pp. 620-629.
Gedik B.; Liu, L. (2008): Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms, IEEE Trans. Mobile
Computing, vol. 7, no. 1, and pp.1-18.
Hu, H; X Xu, J.; Lee, D.L. (2005): A Generic Framework for Monitoring Continuous Spatial Queries over Moving Objects, Proc. ACM
SIGMOD, pp. 479-490.
Authors:
Swagatika Devi
Paper Title:
K-ANONYMITY: The History of an IDEA
Abstract:
Publishing data about individuals without revealing sensitive information about them is an important
problem. In recent years, a new definition of privacy called k-anonymity has gained popularity. In a k-anonymized
dataset, each record is indistinguishable from at least k−1 other records with respect to certain “identifying”
attributes. In this paper, we discuss the concept of k-anonymity, from its original proposal illustrating its enforcement
via generalization and suppression. We also discuss different ways in which generalization and suppressions can be
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applied to satisfy k- anonymity. By shifting the concept of k-anonymity from data to patterns, we formally
characterize the notion of a threat to anonymity in the context of pattern discovery. We provide an overview of the
different techniques and how they relate to one another. The individual topics will be covered in sufficient detail to
provide the reader with a good reference point. The idea is to provide an overview of the field for a new reader from
the perspective of the data mining community.
Keywords: K-Anonymity, Generalization, Suppression, Pattern discovery.
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S. Zhong S., Z. Yang , R. Wright : Privacy-enhancing k-anonymization of customer data, In Proceedings of the ACM SIGMOD-SIGACTSIGART Principles of Database Systems, Baltimore, MD. 2005.
Authors:
V.Sindhu, U.L.Sindhu, P.S.Balamurugan
Paper Title:
Efficient and Dynamic Behaviour of Continuous Query in Unstructure Overlay Network
Abstract: The main objective of the peer to peer content distribution systems are to register for a long term presence
in a network and to publish its own data to that network. These requirements can be done by having some set of
indexing and routing techniques. For this solution, a sequence of approaches has been already proposed by the
existing researchers. But these approaches are not flexible for these systems and too complex. In the unstructured p2p
system it uses to retrieve the data if it matches. Also, certain limitations are obtained. In order to solve this problem,
we propose an approach of continuous query in unstructured overlay network with consistency maintenance. In peerto-peer, consistency maintenance is widely used techniques for high system performance. This approach is to support
the continuous queries in unstructured overlay networks. It achieves high efficiency and consistency maintenance at a
significantly low cost. Simulation results demonstrate the effectiveness of our proposed approach in comparison with
other existing approaches.
Keywords: consistency maintenance, continuous query, peer to peer
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1.
Authors:
61.
353-356
K.Thirumalai kannan, B.Senthil Kumar
Heat Transfer and Fluid Flow Analysis in Plate-Fin and Tube Heat Exchangers with Different Shaped
Paper Title:
Vortex Generators
Abstract:
Numerical analyses were carried out to study the heat transfer and flow in the plate-fin and tube heat
exchangers with different shaped vortex generators mounted behind the tubes. The effects of different span angles a
(α = 30°, 45° and 60°) are investigated in detail for the Reynolds number ranging from 500 to 2500. Numerical
357-361
simulation was performed by computational fluid dynamics of the heat transfer and fluid flow. The results indicated
that the triangle shaped winglet is able to generate longitudinal vortices and improve the heat transfer performance
in the wake regions. The case of α = 45° provides the best heat transfer augmentation than rectangle shape winglet
generator in case of inline tubes. Common flow up configuration causes significant separation delay, reduces form
drag, and removes the zone of poor heat transfer from the near wake of the tubes.
Keywords: Vortex generator; Common flow up; Heat transfer enhancement; Plate-fin and tube heat exchanger.
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generators for fin-tube heat exchangers” International Journal of Heat and Mass Transfer 45, pp.3795–3801
Jainender Dewatwal “Design of Compact Plate Fin Heat Exchanger”
Yunus A.Cengel “Heat and Mass transfer”
Yunus A.Cengel “Fluid mechanics”
Authors:
K.M.Pandey, S.Chakraborty, K.Deb
Paper Title:
CFD Analysis of Flow through Compressor Cascade
Abstract:
This work aims at analyzing the flow behavior through a compressor cascade with the help of
Computational Fluid Dynamics using the FLUENT software. An attempt has been made to study the effect of angle
of attack or flow incidence angle on various flow parameters viz. static pressure, dynamic pressure, turbulence and
their distribution in the flow field and predict the optimum range of angle of attack based on the above observations.
Particularly, two principle parameters viz. the static pressure rise for the compressor cascade and the turbulence
kinetic energy are considered in this analysis. It is observed that maintaining a slightly positive angle of flow
incidence of +2 to +6 degrees is advantageous.
Keywords: Cascade, CFD, Total Pressure, Temperature Magnitude, Viscosity, Thermal Conductivity
62.
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Authors:
63.
362-371
K.M.Pandey, Sushil Kumar, Jyoti Prakash Kalita
Wall Static Pressure variation in sudden expansion in cylindrical ducts with cavities for supersonic
Paper Title:
flow for Mach 1.58 and 2.06: A Fuzzy Logic Approach
Abstract:
In this paper the analysis of wall static pressure variation has been done with fuzzy logic approach to
have smooth flow in the duct. Here there are three area ratio chosen for the enlarged duct, 2.89, 6.00 and 10.00. The
primary pressure ratio is taken as 2.65 and cavity aspect ratio is taken as 1 and 2. The study is analyzed for length to
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diameter ratio of 1,2,4 and 6. The nozzles used are De Laval type and with a Mach number of 1.74 and 2.23 and
conical nozzles having Mach numbers of 1.58 and 2.06. The analysis based on fuzzy logic theory indicates that the
length to diameter ratio of 1 is sufficient for smooth flow development if only the basis of wall static pressure
variations is considered.
Keywords: air ratio, De Laval nozzle, Mach number, pressure ratio, wall static pressure.
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Authors:
Paper Title:
64.
Wiqas Ghai, Navdeep Singh
Analysis of Automatic Speech Recognition Systems for Indo-Aryan Languages: Punjabi A Case Study
Abstract:
Punjabi, Hindi, Marathi, Gujarati, Sindhi, Bengali, Nepali, Sinhala, Oriya, Assamese, Urdu are
prominent members of the family of Indo-Aryan languages. These languages are mainly spoken in India, Pakistan,
Bangladesh, Nepal, Sri Lanka and Maldive Islands. All these languages contain huge diversity of phonetic content. In
the last two decades, few researchers have worked for the development of Automatic Speech Recognition Systems
for most of these languages in such a way that development of this technology can reach at par with the research
work which has been done and is being done for the different languages in the rest of the world. Punjabi is the 10th
most widely spoken language in the world for which no considerable work has been done in this area of automatic
speech recognition. Being a member of Indo-Aryan languages family and a language rich in literature, Punjabi
language deserves attention in this highly growing field of Automatic speech recognition. In this paper, the efforts
made by various researchers to develop automatic speech recognition systems for most of the Indo-Aryan languages,
have been analysed and then their applicability to Punjabi language has been discussed so that a concrete work can
be initiated for Punjabi language.
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Keywords:
Maximum likelihood linear regression, Learning vector quantization, Multi layer perceptron,
Cooperative heterogeneous artificial neural network.
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Processing, Image Processing and Pattern Recognition, Vol. 2, No. 4, December 2011.
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Mohanty, S.; Swain, B. K., “Continuous Oriya Digit Recognition using Bakis Model of HMM”, International Journal of Computer
Information Systems, Vol. 2, No. 1, 2011.
Mohanty, S.; Swain, B. K., “Markov Model Based Oriya Isolated Speech Recognizer-An Emerging Solution for Visually Impaired Students
in School and Public Examination”, Special Issue of IJCCT Vol. 2 Issue 2, 3, 4; International Conference On Communication Technology2010.
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Development, Alexandria, Egypt, May 2011.
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Sarfraz, H.; Hussain, S.; Bokhari, R.; Raza, A. A.; Ullah, I.; Sarfraz, Z.; Pervez, S.; Mustafa, A.; Javed, I.; Parveen, R., “Large Vocabulary
Continuous Speech Recognition for Urdu”, International Conference on Frontiers of Information Technology, Islamabad, 2010.
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Technique”, 2004.
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Computing 5(3):88-92, 2010.
Authors:
R. Kandiban, R. Arulmozhiyal
Paper Title:
Design of Adaptive Fuzzy PID Controller for Speed control of BLDC Motor
Abstract: Brushless DC motors (BLDCM) are widely used for many industrial applications because of their high
efficiency, high torque and low volume. This paper proposed an improved Adaptive Fuzzy PID controller to control
speed of BLDCM. This paper provides an overview of performance conventional PID controller, Fuzzy PID
controller and Adaptive Fuzzy PID controller. It is difficult to tune the parameters and get satisfied control
characteristics by using normal conventional PID controller. As the Adaptive Fuzzy has the ability to satisfied
control characteristics and it is easy for computing. The experimental results verify that a Adaptive Fuzzy PID
controller has better control performance than the both Fuzzy PID controller and conventional PID controller. The
modeling, control and simulation of the BLDC motor have been done using the software package
MATLAB/SIMULINK.
65.
Keywords: Brushless DC (BLDC) motors, proportional integral derivative (PID) controller, Fuzzy PID controller,
Adaptive Fuzzy PID controller.
286-291
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Algorithm”, 2011 UKSim 13th International Conference on Modelling and Simulation,pp.189-194.
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559-576, July 2005.
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Research 26-28 July 2009, vol. 35, pg 198-203.
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Chuen Chien Lee, “Fuzzy Logic in Control Systems : Fuzzy Logic controller Part 2” 1990 IEEE.
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international, 2002.
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Power Electronics, Vol.10, No.1, Jan 2010, pp.65-71
Authors:
Shreya Jain, Samta Gajbhiye
Paper Title:
Comparing and Selecting Appropriate Measuring Parameters for K-means Clustering Technique
Abstract: Clustering is a powerful technique for large scale topic discovery from text. It involves two phases: first,
feature extraction maps each document or record to a point in a high dimensional space, then clustering algorithms
automatically group the points into a hierarchy of clusters. Hence to improve the efficiency & accuracy of mining
task on high dimensional data the data must be pre-processed by an efficient dimensionality reduction method.
Recently cluster analysis is popularly used data analysis method in number of areas. K-Means is one of the well
392-396
known partitioning based clustering technique that attempts to find a user specified number of clusters represented by
their centroids. In this paper, a certain k-means algorithm for clustering the data sets is used and the algorithm
outputs k disjoint clusters each with a concept vector that is the centroid of the cluster normalized to have unit
Euclidean norm. Also in this paper, we deal with the analysis of different sets of k-values for better performance of
the k-means clustering algorithm.
Keywords: Data Mining, Text Mining, Clustering, K-Means Clustering, Silhouette plot.
References:
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Vishal Gupta & Gurpreet S.Lehal ,”A Survey of Text Mining Techniques & Application “ ,Journal of Emerging Technologies in Web
Intelligence ,Aug 2009.
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Extraction and Categorization”, International Journal of Multimedia and Ubiquitous Engineering , Vol. 4, No. 2, April, 2009 .
Raymond J.Mooney & Razvan Bunescu , “Mining Knowledge from Text using Information Extraction “.
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, and Angela Y. Wu , “An Efficient k-Means
Clustering Algorithm: Analysis and Implementation” , IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE
INTELLIGENCE, VOL. 24, NO. 7, JULY 2002.
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Publishers ,1998.
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dataset” , International Journal of Engineering, Science and Technology, Vol. 66 2, No. 2, 2010, pp. 59-66.
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Learning (ICML-2003), Washington DC, 2003 .
Authors:
Vimala.C, V.Radha
Paper Title:
A Family of Spectral Subtraction Algorithms for Tamil Speech Enhancement
Abstract:
Speech enhancement aims to improve the speech quality by using various techniques and algorithms.
Over the past several years there has been considerable attention focused on the enhancement of speech degraded by
several types of noise. The degradation of speech due to the presence of noise causes severe difficulties in various
communication environments. Noise suppression has numerous applications like Human Computer Interaction,
hands-free communications, Voice over IP (VoIP), hearing aids, teleconferencing system etc. For this issue there is
always a unique need for the technique which offers expected outcome with limited complexity in implementation.
Hence, in this paper a family of spectral subtraction techniques is employed for Tamil speech noise cancellation due
to its simplicity. The algorithms adopted for this research work are namely basic spectral subtraction, Non linear
Spectral Subtraction, MultiBand Spectral Subtraction, Minimum Mean Square Error (MMSE), and Log Spectral
MMSE. All these algorithms are analyzed and implemented for two types of noises namely white and babble noise.
The performances of these algorithms are estimated based on SNR and MSE measures. Based on the experimental
results, the Non linear spectral subtraction algorithm provides better results than any other adopted algorithms.
Keywords: Speech enhancement, Tamil Speech, Spectral Subtraction, Non linear Spectral Subtraction, MMSE,
Log Spectral MMSE, SNR and MSE.
67.
References:
Anuradha R. Fukane, Shashikant L. Sahare, “Different Approaches of Spectral Subtraction method for Enhancing the Speech Signal in
Noisy Environments”, International Journal of Scientific & Engineering Research, Volume 2, Issue 5, May-2011,ISSN 2229-5518.
2. M. Berouti, R. Schwartz, and J. Makhoul, Enhancement of speech corrupted by acoustic noise,Proc. IEEE ICASSP , Washington DC, April
1979, 208-211.
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Computer Science, 38:1, IJCS_38_1_10.
5. Gupta, V.K, Bhowmick, A, Chandra, M. and Sharan, S.N, “Speech Enhancement Using MMSE Estimation and Spectral Subtraction
Methods”,978-1-4244-9190-2/11/$26.00© 2011 IEEE.
6. P.Krishnamoorthy and S.R. Mahadeva Prasanna, “Temporal and spectral processing Methods for Processing of Degraded Speech: A
Review”, IETE Technical Review,Vol 26,Issue 2,Mar-Apr 2009.
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speech recognition in cars,” Speech Communication, Vol. 11, Nos. 2-3, pp. 215-228, 1992.
8. Nicholas W. D. Evans, John S. Mason, Wei M. Liu and Benot Fauve, “On the fundamental limitations of spectral subtraction: An assessment
by automatic speech recognition”, School of Engineering, University of Wales Swansea,Singleton Park, Swansea, SA2 8PP, UK.
9. Paurav Goel1, Anil Garg, “Developments in Spectral Subtraction for Speech Enhancement”, International Journal of Engineering Research
and Applications (IJERA), ISSN: 2248-9622, Vol. 2, Issue 1, Jan-Feb 2012, pp.055-063.
10. R. Singaram, P. Guru Raghavendran, S. Shivaramakrishnan and R. Srinivasan*, “Real time speech enhancement using Blackfin processor
BF533”, J. Instrum. Soc. India 37(2) 67-79.
11. Sunil D. Kamath and Philipos C. Loizou, “A multi-band spectral subtraction method for enhancing speech corrupted by colored noise”,
Electrical Engineering (2002), Volume: 4, Issue: 2, Publisher: IEEE, Pages: 2-5, ISBN: 0780374029, DOI: 10.1109/ICASSP.2002.1004852.
1.
68.
Authors:
Sachin Kumar, Niraj Singhal
Paper Title:
A Study on the Assessment of Load Balancing Algorithms in Grid Based Network
Abstract: Grid computing comprises of distributed computer systems which are geographically dispersed to share
the combination of resources in a heterogeneous environment. The ever varying and increasing demands of the
computational resources have generated the need for solutions that are more flexible. With the use of a high tech
computer that has more and faster processors and auxiliary storage space or more RAM (random access memory), it
is not well enough for a solution as the system usage patterns differ. A grid based distributed system can solve this
problem by allowing multiple independent jobs to run over a network with heterogeneous computing nodes. A
397-401
402-405
network-aware load balancing algorithms that are dynamic as well as quick are the requirement of a network of
computers to keep the workload balanced, represented by these jobs. The purpose of this paper is to review various
different load balancing algorithms for the grid based distributed network, identify several comparison metrics for the
load balancing algorithms and to carry out the comparison based on these identified metrics between them.
Keywords: dynamic load balancing algorithms; grid based distributed network; comparison metrics; Heterogeneous
node; Load Balancing Policy
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Authors:
Sonam Shukla, Pradeep Mishra
Paper Title:
A Hybrid Model of Multimodal Biometrics System using Fingerprint and Face as Traits
Abstract:
The issues associated with identity usurpation are currently at the heart of numerous concerns in our
modern society. Establishing the identity of individuals is recognized as fundamental to the numerous
administrative operations. Identity documents (IDs) are tools that permit the bearers to prove or confirm their identity
with a high degree of certainty. In response to the dangers posed by theft or fraudulent use of identity documents and
security threats, a wide range of biometric technologies is emerging, covering e.g. face, fingerprint and iris. They
are also proposed to enforce border control and check-in procedures. These are positive developments and they
offer specific solutions to enhance document integrity and ensure that the bearer designated on the document is
truly the person holding it. Biometric identifiers - conceptually unique attributes - are today portrayed as the
panacea for identity verification. Biometrics is the science and technology of measuring and analyzing biological
data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set
in the database. Experimental studies show that Unimodal biometric systems had many disadvantages regarding
performance and accuracy. Multimodal biometric systems perform better than unimodal biometric systems and are
popular even more complex also. We examine the accuracy and performance
of
multimodal biometric
authentication systems using state of the art Commercial Off- The-Shelf (COTS) products. Here we discuss
fingerprint and face biometric systems, decision and fusion techniques used in these systems. We also discuss
their advantage over unimodal biometric systems.
69.
Keywords: Fingerprint Recognition; Binarization; Block Filter Method; Matching score and Minutia; Face
Recognition; Face Mask; Mask Fitting and Warping.
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Authors:
M.Vijay, L.Saranya Devi
Image Denoising by Multiscale - LMMSE in Wavelet Domain and Joint Bilateral Filter in Spatial
Paper Title:
Domain
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represented by the wavelet coefficients at the same spatial locations at two adjacent scales and the LMMSE is applied
to the vector. Compare to Orthogonal Wavelet Transform (OWT), Overcomplete Wavelet Expansion (OWE)
provides better results hence it is employed. While applying the LMMSE rule, the important features in an image like
edges, curves and textures can be identified. Also spatial domain method output provides a high quality denoising
image than wavelet method with fewer artifacts; hence this wavelet domain output as a reference image for the Joint
Bilateral Filter (JBF) .By using this reference image and the non-linear combination of information of adjacent pixel,
the edge details of the images can be preserved in a well manner. The experimental results prove that the proposed
approach is competitive when compared to other denoising methods in reducing various types of noise. Also the
proposed algorithm outperforms other methods both visually and in case of objective quality peak-signal-to-noise
ratio (PSNR).
Keywords: Image Denoising; Joint Bilateral Filter; Multiscale LMMSE; Interscale Wavelet Model.
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Wavelet Domain and
Joint Bilateral Filter in the Spatial Domain,”IEEE Transactions On Image Processing, Vol. 18, No. 10, October 2009
Authors:
Arshdeep Kaur, Amrit Kaur
411-416
Paper Title:
Comparison of Fuzzy Logic and Neuro Fuzzy Algorithms for Air Conditioning System
Abstract:
This paper provides the design for air conditioning system using fuzzy logic as well as neuro-fuzzy
method. Inputs taken for the air conditioning system are from temperature and humidity sensors and the output is to
control the compressor speed. The simulation results of both systems using fuzzy logic and neuro-fuzzy are shown as
well as compared to signify better of the two.
Keywords: Air Conditioning system, fuzzy logic control, neuro-fuzzy, rule base.
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Authors:
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Paper Title:
Cloud Computing: Different Approach & Security Challenge
417-420
Abstract: Cloud computing has generated a lot of interest and competition in the industry and it is recognize as one
of the top 10 technologies of 2010[1]. It is an internet based service delivery model which provides internet based
services, computing and storage for users in all market including financial, health care & government. In this paper
we did systematic review on different types of clouds and the security challenges that should be solved. Cloud
security is becoming a key differentiator and competitive edge between cloud providers. This paper discusses the
security issues arising in different type of clouds.
Keywords: Cloud, Security, Security challenges, Cloud computing
421-424
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3.
Tripathi, A.; Mishra, A.; IT Div., Gorakhpur Centre, Gorakhpur, India “Cloud Computing Security Considerations”, Signal Processing,
Communications and Computing (ICSPCC), 2011 IEEE International Conference.
UNDERSTANDING The Cloud Computing Stack SaaS, Paas, IaaS, © Diversity Limited, 2011 Non-commercial reuse with attribution
permitted.
Laura Smith on “ A health care community cloud takes shape” http://searchcio.techtarget.com/news/2240026119/a-health-care-communitycloud-takes-shape
Authors:
Alagendran B, Manimurugan S
Paper Title:
A Survey on Various Medical Image Compression Techniques
Abstract:
Medical images are much important in the field of medicine ,all these medical images are need to be
stored for future reference of the patients and their hospital findings hence, the medical image need to undergo the
process of compression before storing it. On these days of medical advancement there exist many compression
techniques. This paper investigates mainly on the various types of medical image compression techniques that are
existing, and putting it all together for a literature survey. Scope of this study focuses on the different available
medical image compression techniques with their performance results.
Keywords: Discrete Cosine Transform, Discrete Wavelet Transform, Medical Image Compression, Set Partitioning
in Hierarchical Trees,
73.
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of Systems Architecture, Vol.53, pp.369–378, 2007
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425-428
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Process, Vol.16, pp. 825–831,2006.
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Processing,Vol.21,pp.100-109,2010.
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Authors:
John Justin M, Manimurugan S
Paper Title:
A Survey on Various Encryption Techniques
Abstract: This paper focuses mainly on the different kinds of encryption techniques that are existing, and framing
all the techniques together as a literature survey. Aim an extensive experimental study of implementations of various
available encryption techniques. Also focuses on image encryption techniques, information encryption techniques,
double encryption and Chaos-based encryption techniques. This study extends to the performance parameters used in
encryption processes and analyzing on their security issues.
Keywords: Chaotic Encryption, Double Encryption, Image Encryption, Information Encryption
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Transactions pp. 1168-1172,2010
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conference on the Intelligent Signal Processing and Communication Systems, 2010
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Method” IEEE Transactions, 2011
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Standard(AES) Based Algorithm for Image Encryption”, IEEE Transactions on Electronics and Information Engineering, Vol 1,pp.141145,2010
Mohammad Reza Keyvanpour, Famoosh Merrikh-Bayat, “A New Encryption Method For Secure Embedding In Image Watermarking”
IEEE Transactions on Advanced Computer Theory and Engineering pp. 403-407,2011.
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and Engineering, Vol. 02, No. 09, pp.2801-2804, 2010.
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Applied Optics, pp. 5933-5947, 2009.
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494-498,2008.
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Computation Technology and Automation pp. 143-146,2011.
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Technology, Vol. 6,pp. 2359-2363, 2010.
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Applications,2011.
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Optics Communications, Vol 283, pp. 2092-2096, 2010.
Jolly shah and Dr. Vikas Saxena, “Video Encryption: A Survey” International Journal of Computer Science Issues, Vol. 8, pp. 525-534,
2011.
Authors:
N.Devi, V.Nagarajan
Paper Title:
FPGA Based High Performance Optical Flow Computation Using Parallel Architecture
Abstract: The proposed work describes a highly parallel architecture for high performance optical flow
computation. This system implements the efficient Lucas and Kanade algorithm with multi-scale extension for the
computation of large motion estimations. This work deals with the architecture, evaluation of the accuracy and
system performance. It also has extension to the original L&K algorithm. So the capable of working is larger than the
standard mono scale approaches. In this proposed system, Matlab and Modelsim simulation are selected for local
optical flow algorithms due to their potential for a high-performance massive parallelization. The results are obtained
with a throughput of one pixel per clock cycle along the whole processing scheme by using the fine-pipeline based
architecture.
Keywords: FPGA, Lukas kanade algorithm, Pipelining
References:
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J. Diaz, E. Ros, F. Pelayo, E. M. Ortigosa, and S. Mota, “FPGA-based real-time optical-flow system,” IEEE Trans. Circuits Syst. for Video
Technol., vol. 16, no. 2, pp. 274–279, Feb. 2006.
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M. M. Abutaleb, A. Hamdy, M. E. Abuelwafa, and E. M. Saad “A Reliable FPGA-based Real-time Optical-flow Estimation” International
Journal of Electrical and Electronics Engineering 2010.
Guillermo Botella, Antonio Garcia, Manuel Rodriguez-Alvarez, Eduardo Ros, Uwe Meyer-Baese María C. Molina “Robust Bioinspired
Architecture for Optical-Flow Computation” IEEE Transactions On Very Large Scale Integration Systems, Vol. 18, No. 4, April 2010.
Francisco Barranco, Matteo Tomasi, Javier Diaz, Mauricio Vanegas, and Eduardo Ros “Parallel Architecture for Hierarchical Optical Flow
Estimation Based on FPGA” IEEE journal 2011.
Kui Liu, Qian Du, He Yang, and Ben Ma “Optical Flow and Principal Component Analysis-Based Motion Detection in Outdoor Videos”,
Mississippi State University, MS 39762, USA January 2010.
James R. Bergen, P. Anandan, Keith J. Hanna, and Rajesh Hingorani “Hierarchical Model-Based Motion Estimation” David Sarnoff
Research Center, Princeton NJ 08544,USA.
Authors:
M.Jenath, V.Nagarajan
Paper Title:
FPGA Implementation On Reversible Floating Point Multiplier
Abstract:
Field programmable gate arrays (FPGA) are increasingly being used in the high performance and
scientific computing community to implement floating-point based system. The reversible single precision floating
decomposition approach. Reversible logic is used to reduce the power dissipation than classical logic and do not loss
the information bit which finds application in low power computing, quantum computing, optical computing, and
other emerging computing technologies. Among the reversible logic gates, Peres gate is utilized to design the
multiplier since it has lower quantum cost. Operands of the multiplier is decomposed into three partitions of 8 bits
e multiplication is performed through nine
reversible 8x8 bit multipliers and output is summed to yield an efficient multiplier optimized in terms of quantum
cost, delay, and garbage outputs. This proposed work is designed and developed in the VHSIC hardware description
language (VHDL) code and simulation is done using Xilinx 9.1simulation tool.
76.
Keywords: Reversible logic gates, reversible logic circuits, reversible multiplier circuits, quantum computing,
Nanotechnology based systems.
438-443
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H.Thapliyal and M.B.Srinivas, “Novel reversible 'TSG' gate and its application for designing components of primitive/reversible quantum
ALU,” Proc. the 5th IEEE International Conference on Information, Communications and Signal Processing, Bangkok, Thailand, December
6-9, 2005.
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decomposition,’’10thIEEE international conference on Nanotechnology Joint symposium with Nano Korea, August 2010.
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Authors:
M.Amarendra, S.Srikanth, G. Siva Suteja, B.Prasanna lakshmi, K.Madhavi latha
Paper Title:
Fast and Slow Transient Response of WECS with Simultaneous Actions
Abstract: This paper details the transient operation of a wind energy conversion system (WECS) used
simultaneously as an ac- tive filter and power generator. This study is intended to address the system response to two
types of transient phenomena: voltage dips (fast transients) and wind speed variations (slow transients). The system
response to voltage dips is governed by the electrical system dynamics and control method and results in the
evaluation of the WECS low-voltage ride through capability. The study of the system response to wind speed
variations requires a complete mechanical model to be included. Simulation results are presented for a typical
WECS, and a discussion is carried out dealing with the generalization of the present work to other configurations.
77.
Keywords: Doubly fed induction generator(DFIG), Harmonic compensation, Low- voltage ride through (LVRT),
Transients, Wind energy conversion systems(WECSs).
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for wind turbines,” in Proc. 27th Annu. Conf. IEEE Ind. Electron. Soc., Denver, CO, Nov. 29–Dec. 1, pp. 2000–2005.
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Authors:
K.Nageswara rao, D.RajyaLakshmi, T.Venkateswara Rao
Paper Title:
Robust Statistical Outlier based Feature Selection Technique for Network Intrusion Detection
Abstract:
For the last decade, it has become essential to evaluate machine learning techniques for web based
intrusion detection on the KDD Cup 99 data set. Most of the computer security breaches cannot be prevented using
access and data flow control techniques. This data set has served well to identify attacks using data mining.
Furthermore, selecting the relevant set of attributes for data classification is one of the most significant problems in
designing a reliable classifier. Existing C4.5 decision tree technology has a problem in their learning phase to detect
automatic relevant attribute selection, while some statistical classification algorithms require the feature subset to be
selected in a preprocessing phase. Also, C4.5 algorithm needs strong preprocessing algorithm for numerical attributes
in order to improve classifier accuracy in terms of Mean root square error. Irrelevant features in the network attack
data may degrade the performance of attack detection in the decision tree classifiers. In this paper, we evaluated the
influence of attribute pre-selection using Statistical techniques on real-world kddcup99 data set. Experimental result
shows that accuracy of the C4.5 classifier could be improved with the robust pre-selection approach when compare to
traditional feature selection techniques.
78.
Keywords: Normalization, Network security, data mining, intrusion detection, filtering.
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Daniel Owen “Network-Based Intrusion Detection Systems in the Small/Midsize Business” November of 2005, http://danielowen.com/NIDS
Lixin Wang “Artificial Neural Network for Anomaly Intrusion Detection”
http://www.cs.auckland.ac.nz/courses/compsci725s2c/archive/termpapers/725wang.pdf
Kumar Das” Protocol Anomaly Detection for Network-based Intrusion Detection “GSEC Practical Assignment Version 1.2f (amended
August, 13, 2001)
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Threshold Verification Technique for Network Intrusion Detection System Faizal M. A., Mohd Zaki M., Shahrin S., Robiah Y, Siti Rahayu
S., Nazrulazhar B,IJCSIS VOL2NO1(JUNE 2009).
yue zhang,Jie Liu o.song,“A NEW ALGORITHM FOR OUTLIER DETECTION BASED ON OFFSET”, 2009 FITth international
454-459
conference on information assurance and security Chengdu “Combining Classifier based on Decision Tree”( 18-20 Aug. 2009)
10. KNN Based Outlier Detection Algorithm in Large Dataset Peng Yang Chongqing University of Arts and Science Chongqing, China
[email protected]
11. kdd.ics.uci.edu/databases/kddcup99/kddcup99.html
Authors:
Vatsal Shah, Viral Kapadia
Paper Title:
Load Balancing by Process Migration in Distributed Operating System
Abstract: Distributed operating system is nothing but the more than one cpu are connected with each other, but
user can feel it as virtual uniprocessor. Now as more than one cpu are connected with each other its obvious that load
will be increase. To compete with this load it is necessary to balance it. So in this paper I have focus on process
migration technique for load balancing. For that I have describe two algorithms. 1) sender-initiated algorithm. 2)
receiver-initiated algorithm.
79.
Keywords: To compete with this load it is necessary to balance it.
460-463
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Narayan Joshi, Dr. D. B. Choksi, “Checkpointing Process Virtual Memory Area for Process Migration”; International journal of Emerging
Technologies and Applications in Engineering Technology and Sciences; June-2010; pp-42-44
Authors:
V. Nourani, A. Hosseini Baghanam, F. Daneshvar Vousoughi, M.T. Alami
Paper Title:
Classification of Groundwater Level Data Using SOM to Develop ANN-Based Forecasting Model
Abstract:
Prediction of groundwater level in a watershed plays a crucial role in management of groundwater
resources, especially in a semi-arid area where there is immense need to groundwater resources in order to prepare
the requirement water for agriculture, municipal and industrial affairs.
The aim of this study is to present a mathematical based model to estimate the groundwater level (GWL) in Ardabil
located at northwest of Iran, with association of some hydrological data (e.g., rainfall, discharge, etc.). In this way
identifying various zones with similar groundwater level can be a promising idea which leads to appropriate
overview on water table of the study area as well as efficient modeling.
For this purpose, the Self Organizing Map (SOM) was used to cluster the homogenous monitoring piezometers in the
plain by utilizing GWL and Universal Transverse Mercator (UTM) data. The sensitivity analysis was performed over
normalized and non-normalized data of GWL and UTM in order to investigate their effects on clustering.
Conventional K-Means method was applied to verify the results of SOM method. The central piezometer of each
cluster was selected as a representative by means of statistical technique. Afterwards the three layer feed forward
Artificial Neural Network (ANN) model was utilized to calibrate a model via historical groundwater level records
from the representative wells and relevant hydro-meteorological data. The last step was performed by simulating
water table level of the representative piezometer from each zone of the plain via proposed model, to compare the
computed and observed data. The results reveal the suitability of SOM clustering method with normalized data of
GWL and also identify the specific piezometers that the GWL of them can represent the GWL in a particular region.
Thus, adequate measures should be devoted on preserving such important monitoring piezometers and reliable data
can be obtained from them in order to generalize the GWL data to that specific region. The modeling results can be
utilized to frame the corresponding strategies to reduce the monitoring cost and to enhance the cost-effective
benefits. The proposed methodology can be referred as a management plan for groundwater resources.
Keywords: Ardabil Plain, Artificial Neural Network, Clustering, Groundwater level, Self Organizing Map.
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Authors:
CheeFai Tan, Ranjit Singh Sarban Singh, Mohd. Rizal Alkahari
Paper Title:
Water Pressure Loss Analysis of Mobile Machine for Fire Fighting Purpose
Abstract: Fire fighting is risky profession. They are not only extinguishing fires in tall buildings but also must drag
heavy hoses, climb high ladders and carry people from buildings and other situations. There are many fire fighters
lost their lives in the line of duty each year throughout the world. The statistics of the fire fighter fatalities are still
maintain at high level every year and it may continue to increase if there is no improvement in fire fighting
techniques and technology. The paper describes the water pressure loss analysis of mobile fire fighting machine
prototype.
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Authors:
A.Nirmal Kumar, B.G.Geetha
Paper Title:
Achieving Software Engineering Knowledge Items with an Unit Testing Approach
Abstract: Classification makes a vital role to advancing knowledge in both science and engineering. It is a process
of investigating the relationships between the objects to be classified and identifies gaps in knowledge. Classification
in engineering also has a practical application. They can help maturing Software Engineering knowledge, as
classifications constitute an organized structure of knowledge items. Till date, in existing system, there have been
few attempts at classifying in test cases. In this research, we examine how useful classifications in Software
Engineering are for advancing knowledge by trying to classify testing techniques. This paper presents a preliminary
classification of a set of unit testing techniques. To obtain this classification, we enacted a generic process for
developing useful Software Engineering classifications. The proposed classification has been proven useful for
maturing knowledge about testing techniques. SE helps to: 1) provide a systematic description of the techniques,2)
understand testing techniques by studying the relationships among techniques (measured in terms of differences and
similarities), 3) identify potentially useful techniques that do not yet exist by analyzing gaps in the classification, and
4) support practitioners in testing technique selection by matching technique characteristics to project characteristics.
Keywords: Classification, software engineering, software testing, test design techniques, testing techniques, unit
testing techniques.
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Authors:
Sumit Kumar Banchhor, Om Prakash Sahu, Prabhakar
Paper Title:
A Speech/Music Discriminator based on Frequency energy, Spectrogram and Autocorrelation
Abstract:
Over the last few years major efforts have been made to develop methods for extracting information
from audio-visual media, in order that they may be stored and retrieved in databases automatically, based on their
content. In this work we deal with the characterization of an audio signal, which may be part of a larger audio-visual
system or may be autonomous, as for example in case of an audio recording stored digitally on disk. Our goal was
first to develop a system for segmentation of the audio signal, and then classify into one of two main categories:
speech or music. Segmentation is based on mean signal amplitude distribution, whereas classification utilizes an
additional characteristic related to frequency. The basic characteristics are computed in 2sec intervals, resulting in the
segments' limits being specified within an accuracy of 2sec. The result shows the difference in human voice and
musical instrument.
Keywords: Speech/music classification, audio segmentation, zero crossing rate, short time energy, spectrum flux.
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Authors:
Patimakorn Jantaraprim, Pornchai Phukpattaranont
Paper Title:
Fall Detection for the Elderly using a Support Vector Machine
Abstract: We propose a short time min-max feature for improving fall detection performance based on the specific
signatures of critical phase fall signal, acquired using a tri-axial accelerometer on a torso. Our proposed feature has
been validated by a Support Vector Machine with two-fold cross-validation. Fall and scripted activities were tested in
the experiment. Performance was evaluated by comparing the short time min-max with a maximum peak feature. The
results obtained from 420 sequences show that the performances of short time min-max feature can approach 98.2%
480-483
484-490
sensitivity and 100% specificity for a radial basis function kernel, which are better than those from the maximum
peak feature for all testing kernels. The short time min-max feature also uses one sensor for the body’s position
without a fixed threshold for 100% sensitivity or specificity, and without additional processing of a posture after a
fall. The simplicity and high performance of our proposed feature makes it suitable for implementation on a
microcontroller for use in practical situations. Chusak Limsakul, Booncharoen Wongkittisuksa
Keywords: Fall detection, Critical phase, Short time min-max feature, Support Vector Machine.
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Authors:
Pooja Yadav, Ravindra Prakash Gupta
Paper Title:
Weighted Code Transmission In Optical CMDA
Abstract: In this Paper, the comparative analysis of a fibre optics CDMA system with or without weighted code is
presented using Matlab simulation. By changing various parameters of the systems, we compare two systems in
terms of BER. As the number of active users increases the BER increases. It is found that the system using weighted
code is better.
Keywords: CDMA, BER, Weighted Code
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Authors:
Nidhi Pandey, Shashank Sahu, P. Ahmed
Paper Title:
Automated Requirements Gathering using Intelligent Agents for e-Learning System
Abstract: The software requirements gathering process can be automated using intelligent agents. Such agents can
be created to capture the requirements, as and when they may evolve during the requirements elicitation, analysis and
negotiations, specification, documentation and validation phases.
In this paper we present an intelligent agent-based model for e-learning system environment. In this system three
types of agents namely: Adviser Agent, Content Managing Agent and Personalization Agents have been developed.
The major advantage of this model is that these agents can evolve in the course of their operations by enhancing their
capabilities through their ever increasing learning abilities.
491-492
493-496
Keywords: e-learning environment, Intelligent Agent, Requirement Engineering
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Villach, Austria, ICL September 26 - 28, 2007.
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e-learning System”, International Journal of Computer Science Issues, Vol. 8, Issue, IJCSI 3,May 2011.
Juneidi, S.J.; Vouros, G.A.: Engineering an E-learning Application using the ARL Theory for Agent Oriented Software Engineering, 2005
AAAI Fall Symposium, MIT press, 2005.
Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis and Spiridon D. Likothanassis, “Computational Intelligence
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WSEAS TRANSACTIONS on SYSTEMS, December 2008.
Authors:
P. Samundiswary, S. R. Anandkumar
Paper Title:
Throughput Analysis of Energy Aware Reactive Routing Protocol for Wireless Sensor Networks
Abstract: Wireless Sensor Networks (WSNs) consist of thousands of small sensor nodes with sensing, computation
and wireless communication capabilities. The main challenging task in WSN is routing. There are various types of
routing protocols available for WSN. Ad hoc On-demand Distance Vector (AODV) routing protocol is one of routing
protocols for mobile sensor networks. AODV avoids the counting-to-infinity problem of other distance-vector
protocols by using sequence numbers on route updates, a technique pioneered by Destination Sequence Distance
Vector (DSDV). This protocol utilizes the shortest route for communication between nodes. Hence, energy
consumption and battery power of nodes is increased by using the same nodes with shortest route for communication
several times. Energy efficient Ad hoc On-demand Distance Vector (EAODV) routing protocol is developed by
incorporating energy aware algorithm along with the shortest route in the existing Ad hoc On-demand Distance
Vector Routing protocol to reduce battery power and lifetime of WSN. In this paper, throughput performance of
EAODV and AODV protocol has been examined and compared by varying packet size in CBR traffic, packet rate,
coverage area and number of packets with the help of ns-2 simulator.
Keywords: DSDV, WSNs, AODV
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Authors:
N. Rajasekhar Reddy, R.J.Ramasree
Paper Title:
Software Quality Modeling and Current State of the Art
Abstract: Software Quality Assurance plays a key role in software development. The research is mainly aimed at
considering prior researches, present working status and to restore the gaps between them with present known
information. Here, we conduct a review on current state of the art in software quality evaluation and assurance
models.
Keywords: SQA, Product metrics, software science, size-defect relationship, measurement applied to SQA,
Terms—Software as a service (SaaS), software selection, service utility
497-501
502-511
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