l.INTRODUCTION For example, multiple linear MISSING DATA

l.INTRODUCTION For example, multiple linear MISSING DATA

lh International Quality Conference
May 24'n 2013
Center for Quality, Faculty of Engineering, University of Kragujevac
MISSING DATA ESTIMATION IN D.4TM
STRUCTURES USING MULTIPLE
IMPUTATION METHOD
Aleksandar Novakovicr)
Vesna Rankovicr)
Dejan Divac2)
Nenad Grujovicr)
Nikola Milivojevic2)
I)
Abstract: The ffictive dam safety monitoring prog'ams
,s essential for dqm and rs widely accepted'
Instrumentation ss part of dam safety program's is
installed to measure a particular parameter of interest.
These parameters might include water levels, seepqge
flows, deformations or displacements, pressures,
loading conditions, temperature variations, seepage
water clarity, piezometric levels, etc. The aim o1" the
Departmentfor Applied
Mechanics and Aut omatic
Control, Faculty of
Engineer ing, Univ ersity of
Kragujevac, Serbia
timely detection of abnormal behaviour of the dam does
2)
necessarily imply frequent monitoring or the
collection of a great deal of data. h is important that
this information is representative and adequ,ztely
interpreted. Interpretation ofthe availqble data is very
substqntial for dam health monitoring. The dstq
interpretation csn be dfficult when data are missing or
incomplete. In this paper nultiple imputation method
not
Institutefor
Development of Water
Resources "Jarosl w Cerni",
Belgrade, Serbia
was used to estimate replacement values for the mis:sing
data. The results of simulotion show that the mulltiple
linear regression model for prediction of the water trevel
in piezometers with estimated missing values prcwide
better results.
Keywords: dam, missing data, multiple imputtttion
method, piezometric
w
ater level
as the amount of missing data irLcreases,
and if the missing data is not disitributed
l.INTRODUCTION
Most learning algorithms generally
completely randomly, can result in
assume that training and test datasets are
complete. However, real data sets are often
severely biased models [1-2].
incomplete and they contain a proportion
of missing values due to various reasons
affected
such as equipment elrors, manual data
entry
procedures,
and
incorrect
measurements.
For
example, multiple linear
are unable to
directly handle missing data. Many
regression techniques
software implementations
of
multiple
linear regression ommits all instances with
missing data before
the model
is
constructed. Such an approach may lead to
significant loss of informations, especially
7ft
Prediction performances are not
if there is less than lVo missing
instances, although l%-5% is manageable.
However, sophisticated handling rnLethod is
5%-15% missing
there
required
greater
than l5o/o missing
instances, while
data can severely degrade the prediction
performance of learning algorithmsr [3].
In response to these issues various
solutions have been developed in statistics
if
is
[a-5] and data mining [6-7].
The ffeatment of missing v'alues is
determined by the type of missing data'
There are three types of missing data, as
IQc May,242013
411
fl,,-.
ffiwfl*w"*tw$$*,ggm$4,w*x$$W 4'g:$$$*ge$H*"*
follows [8]: a) Missing completety at
random
(MCAR)
There
is
no
dependency between missing value for an
afibute and any other observed data or
missing attribute; b) Missing at random
(MAR) - The missing value for an atribute
depends on other known data; c) Missing
not at random (MNAR) - The missing
value for an attribute depends on other
missing values, and thus missing data
cannot be estimated from observed data.
The objective
of this study is
p,
the squares ofthe errors:
(",- z.r)' +(2,- z^r)' +...+(r, "*)' Q)
in which 2., denotes the MLR output
s=
value from the i-th input element:
z*
Bru*,
= Fo + Bru.,, + flur, +...+
The matrix form of Eq. (2) is:
where:
f:
to predict the piezometric water level in
dam. Two models were compared, one
with and one without estimated missing
values in their dataset. In this paper it is
MAR, which implies that the missing
values are deductible in some complex
manner from the remaining data. In order
to estimate replacement values for the
missing data, multiple imputation method
u,
o =lt.
l:
(4)
uzr
:
:
lt il,, uro
P={fof,
(3)
(z-af)
e:(z-up)'
to
develop a multiple linear regression model
assumed that missing values appear to be
by which the sum of
can be estimated
.-.
"*,f
:
:
I
urrl
Fr}', ,={r, r,
and the least squares estimator
-.- zr\',
of 1f is
given by:
/
n
r-l
f =la'U)
U'
z
(5)
was used.
3. MTTLTIPLE
2. REGRESSION ANALYSIS
a
Regression analysis is
statistical
technique for investigatrng and modeling
the relationship between variables [9]. The
multiple linear regression model is widely
used for data analysis or prediction in dam
engineering [10].
MLR is used for modelling the linear
relationship between a dependent variable
and one or more independent variables.
Consider
{(u,
a training data
r,),{ur,
where4
rr),. -.,(u o, z o)} e
[
={u,ur,...rr,\' is a
set
n
""
vector of
input variables and z, is the corresponding
output value, p is the number of training
data points. The multiple linear regression
model is given by:
z* = 0o+ pp,
+
prur+...+
B*u,
IMPUTATIOI{
METIIOD
(l)
where B, represents unknown parameters,
Multiple imputation
is
sttatistical
approach to the analysis of incomplete
data, and in this section its main features
are summarized. Detailed description is
given in the literature [1 l].
p data
matrixo which can be thought of as
Lets assume that
X
is the
X = (Xo6o,X*r"), where Xo6,
n><
axtd
X*;,
are the observed and the missing parts,
respectively.
is considered ar model
It
P(Xl?)
for the data
vector parameter.
In
X,
where
0
is
a
M
the beginning,
complete
datasets are created, using an apprropriate
imputation model to generate a prlausible
values for the missing observatiions. In
order to obtain the imputed valups data
augmentation, [12], is used. Practiically, it
is a MCMC (Markov Chain Montr: Carlo)
procedure in which, given the values d(fr)
4t2
A, Novakovic, V. Rankovic, D, Divac, N. Grujovic, N. Milivojevic
$
wx$ww se+e$$
t#)
at the fr -th iteration, these
values are updated by drawing random
and
values from the conditional distributions
follows:
xX:',
D
P(x^,1x"^,e@)
qx*m
$
q;sem$
$
and testing
$'s { c :y$$q}$ #
$$** $]'-&$i$
S.t S$ L#.* I'
MLR models.
as
(6)
n P(olx"^,x*:t\
(i)
(6)
Step
is called the Imputation step,
g(r+r)
while (7) is known as the Parameter step.
When # -+ oo, the sequence
(t o, ,r*])
has a stationary distribution whose
marginals are P(el Xrbr) and
P(X^ul Xotr), respectively. After
convergence, the imputations are acquired
from (6).
Finally lets *$) =(X"b".XH), i =1,...M
denote the imputed-data estimates
Under general condition,
imputation estimate
follows
x
M
I
l]:
of
X
of X.
multiple
is calculated
as
(8)
4. CASE STUDY: PRVOT\-EK
DAM
The dam and the reservoir Prvonek
(Fig. l) were built in 2005, in order to
solve the water supply problem of the
towns Vranje, Bujanovac, and the
surrounding villages in south-east Serbia.
They are located on the Vranjsko-Banjska
River, the right tributary of the river Juhta
km upstream of Vranjska
Moravq
9
5.
SIMI]LATION RESI]LTS
For the purpose of construcrting the
MLR model, a program was written in R
by the authors. The program impk:mented
classes provided by the Amelia II package,
which offers a comprehensive rimge of
functions, necessaxy for implementation of
multiple imputation method.
Accuracy of the MLR model depends
=l?t't
Banja-Spa, near
Figure 1. The view of Prvonek dum
the village
Prvonek.
Prvonek dam is rockfill embankment dam,
with sloped central clay core within the
dam body. The height of the dam is 90 m.
At maximum water levels, the volume of
the reservoir is 20 million m'.
For the purpose of this paper, one of
piezometers,
installed on the section of
the
the dam, was observed. The water level in
examined piezometer have been measured
every day. The data collected from June
2010 to April 20ll were used for training
7tr IQC
on the appropriate choice of the input
variables. The input variables of both
MLR models were measurementsl of the
tailwater levels taken on the same day
(hlr), I day before (hlz) and 2 days before
(hl3) the
measurements
taken
by
piezometers.
For the purpose of training ancl testing
MLR models, respectively, T0o/o and 30Yo
of randomly chosen data points collected
during the period of June 20l0-April 201 I
were used. Collected dataset contained
24% of missing data. The MLR models for
prediction of water level in the examined
piezometer, one without and one with
estimated missing values in their dataset,
are respectively:
hpff
-- 194.52 + 0.64. hl, + 0.08 - hl,
- 0.06. hl3
(e)
hpY =
169.50 + 0.68' hl, + 0.07'
hl,
-
0.05' hl3
(10)
The performance of two MLR models
was evaluated by comparing the erstimates
of the models with experimental d,ata. The
performance parameters of the trairring and
test sets are presented in Table l.
May,242013
413
fl.,j.ffi*$
$m$*s
seaa
$$s$m
$ $-xs *e$
$
S
€ts:,wt$ex
Tablel. The performance parumeters of
MLR modelsfor prediction of water levets
in the examined
Piezometer
hpff
0.93
Test
0.96
hpY
Training
0.97
Test
0.99
m
se
values in their dataset, were developed to
predict water level in one of the installed
piezometers installed on the sectio,n of the
dam. The performance of the fi\,o MLR
r
Trainins
*
models were tested using co.nelation
coefficients. As it can be easily observed,
both models are capable of predicting
water levels in piezometersi with
reasonable accuracy, although morCel with
estimated missing values
5. CONCLUSION
gives
a
in its
dataset
slightly higher coefficient of
correlation values for training and test sets.
In this paper, two MLR models, one
with and one without estimated missing
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lll
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I2l
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Acknowledgment: The part of this research is supported by Minisf,y of Science in Serbia,
Grants III4I007 and TR37013.
414
A. Novakovic, V Rankovic, D. Divac, N. Grujovic' N. Milivoievic
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T.International
auality
Conference
w@
CONFEREI\CE MANUAL
May 24c 2013, Kragujevac
Faculty of Engineering, University of Kraguievac
ffi15-
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. International Quality Conference
Conference manual
7
ISBN: 978 - 86 - 86663 - 94 - B
Editors:
Dr Slavko Arsovski, full professor
Faculty of Engineering, Kragujevac
Dr Miodrag Lazic, full professor
Faculty of Engineering, Kragujevac
Dr Miladin Stefanovic, associate professor
Faculty of Engineering, Kragujevac
Technical
Editor:
Snezana Nestic
Faculty of Engineering, Kragujevac
Publisher:
FACULTY OF ENGINEERING
34OOO
KRAGUJEVAC
Sestre Janjic 6
CENTER FOR QUALITY
34OOO
KRAGUJEVAC
Sestre Janjic 6
For
pablishers:
No. of
copies:
Printing:
Prof, dr Miroslav Babic
Prof. h Slavko Arsovski
2OO
Faculty of Engineering Kragujevac
Copyright @Faculty of Engineering University of Kragujevac,2013.
C opyright @ C anter for Quality, Kraguj ev ac, 2 0 I 3.
Publication of Conference manual and organization of
7. lnternational Quality Conference is supported by:
Department of Educarion, Science and Technological Development of Reputhlic
Serbia
Izdavanje Zbontkaradova, organizovanje i odrZavanje
7. Intemational Quality Conference podrZalo je:
Ministarstvo prosvete, nauku i tehnoloikog rawoja Republike Srhiie
il
7ft IQC May,24th2ol3
of
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fr
l.
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ti:\'i
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Prof. dr Slavko Arsovski, Faculty
of
Engineering, Kragujevac, serbia,
President
Tadeusz sikora, The Department of euality Management, cracow uni.versity
of Economics, Krak6w, Poland
Prof. drTadeja Jere Lazanski, University of primorska, Slovenia
Prof. dr Milan Perovic, Faculty of Engineering, podgorica, Montenegro
Prof. dr Branislav Marjanovic, University of Johanesburg, SAR
Prof. dr Goran Futnik, Univerzitet Minho, portugal
Prof. dr Biilent Eker, Namik Kemal University, Tekirdag-Turkey
8. Assoc. Prof. Marti Casadesfs, Universitat de Girona, Girona, Spain
Prof. Stanislav Karapehovic, University of Alberta, Edmonton, Canada,
10. Assoc. Prof. Iflaki Heras, Universidad del Pais Vasco, San Sebastian, Spain
I L Miroslav Badida, Technical University of Kosice, Faculty
Engineering,
Department of Environmental, Studies and Information Engineering
12. Prof. dr Mirko Sokovic, Fakultet za strojnistvo Ljubljana, Slovenia
13. Prof. dr Ljupco Arsov, Elektrotehnicki fakultet Skoplje, FYR Macedonia
14. Prof. dr Zdravko Krivokapic, Faculty of Mechanical Engineering, Poclgorica,
2.
3.
4.
5.
6.
7.
9.
of
15.
16.
17.
18.
19.
20.
Montenegro
Prof. Dr. Bernhard Miiller, Leibnizlnstitute of Ecological and Regionall
Prof. dr Miodrag Lazic, Faculty of Engineering, Kragujevac, Serbia
Prof. dr Janko Hodolic, Faculty of Technical Sciences, Novi Sad, Serbia
Prof. dr Miladin Stefanovic, Faculty of Engineering, Kragujevac
Prof. dr Ayqegiil Akdogan Eker, Yrldrz Technical University, Mechanical
Faculty, Beqiktag/istanbul-Turkey
Dr. Prasun Das, SQC & OR Division of the Indian Statistical Institute (ISI),
Kolkata,India
21. Georgeta Rafl, U.S.A.M.V.B. Timigoara, Romdnia
22.Prof. dr. Petroman Ioan, USAMVB Timisoara, Romania
23. Paul M. Andre, AQE Group, Chicago,Illinois, USA
24. Prof. dr Ezendu Ariwa, London Metropolitan Business School, l-ondon
Metropolitan University, UK
25. Paul M. Andre, AQE Group, Chicago,Illinois, USA
26. Nenad Injac, Quality Austria, Wien, Austria
27. dr Kresimir Buntak. Tehnicko veleuciliste Yarazdin. Croatia
7th
IQC May,24th2ol3
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LEARNING IMPACT, LEARNING MODE AND E-LEARNING_
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SCENARIO
.....................3
Petroman cornelia, Petroman I., sdrdndan H., Marin Diana, viduva Loredana,
$ucan Moisina
TMPROVING QUALITY MANAGEMENT rN TTrE BEEF TNDUSTRY .........9
3.
Rouhollah Mojtahedzadeh,Rezalzadi
APPLYING A THEOR-ETICAL MODEL FOR ORGANIZATIONAL
DECISION MAKING BASED ON SCHOOL OF INTELLECTUAL
STAFF (MODERNISM, SYMBOLIC, POST MODERNISM)...........................15
4.
Rouhollah Mojtahedzadeh, Reza Izadi
APPLICATION OF PERFORMANCE APPRAISAL SYSTEM
IN DEVELOPING
5.
COUNTRIES
.........3I
Rouhollah Mojtahedzadeh, Reza Izadi
LOCAL GOVERNMENT ADMINISTRATION IN SOUTH AFRICA:
T}M MYTH, T}IE PARADOX, TI{E CHALENGES AND
THE WAy
6.
FORWARD
.......................37
RouhollahMojtahedzadeh
TI{E RULE OF SCHOOL-BASED MANAGEMENT
IN DEVELOPING
COUNTRIES
.......,,47
7.
Rouhollah Mojtahedzadeh,Rezalzadi
THE IMPACT OF HUMAN RESOURCE MANAGEMENT ON
PERFORMANCE OF OIL AND GAS INDUSTRY IN IRAN ...........................57
8.
Biilent Eker, Aygegiil Akdogan Eker
OPPORTIJNITIES TO USE IMAGE PROCESSING TECHNOLOGY
IN QUALITY-BASED PRACTICES
........................67
9,
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MATLAB-BASED APPLICATIONS FOR IMAGE PROCESSING
AND rMAGE QUALITY ASSESSMENT ..................
...................73
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Dragan Taranovic, Marko Miletic, Sasa Pavlovic
DEVELOPMENT OF EXPERIMENTAL PROCEDURE FOR
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Jasna Glisovic, Jovanka Lukic, Danijela Miloradovic, Dobrivoje Catic
RESEARCH OF THE ruSTIFICATION FORTI{E HIGH
..................85
WARRANTY COST DUE TO DISC BRAKE
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MODIFIED SERVQUAL MODEL OF SERVICE QUALITY
MEASUREMENT IN HOTELS WITH BUSINESS FACILITIES .....................
9
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13. Wieslaw tr ukasiriski
SELF ASSESSMENT AS A SOURCE OF KNOWLEDGE
IN THE PROCESS OF AN ORGANISATION IMPROVEMBNT.... .................9,1,
14.
Predrag Pravdic
AN INTEGRATED MANAGEMENT SYSTEMS
BASED ON STEP
15.
STANDARD
..........109
Predrag Pravdic
MANAGING BUSINESS GOALS OF
MANT]FACTURING ORGANIZATIONS BY
16.
BSC.......
...............I19
Predrag Pravdic
QUALITY OF CAD/CAM SOFTWARES
IN MANUFACTIJRING
17.
INDUSTRY
.,.,.,.,,...,......,..,127
Srdjan Bogetic, Dejan Djordjevic, Dragan Cockalo
ANALYSIS OF THE PROCESS OF PROMOTING
CORPORATE SOCIAL RESPONSIBILITY IN FUNCTION
oF COMPETITIVENESS
IMPROVEMENT.................. ...............143
18. Bojan Stojcetovic, Milan Misic, Zivce Smkocevic
QUALITY TOOLS IN PROJECT MANAGEMENT..........................................153
19. Bedri
Onur Kucukyildirim, Aysegul Akdof,an Eker
QUALITY ASSESSMENT OF CARBON NANOTUBES:
CHOOSING CHARACTERZATION METHOD
.........................I59
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Dragan Lazarevic, Milan Eric, Milan Misic
THE DEVELOPMENT OF DIGITAL FACTORY IN TODAY'S WORLD......165
21.
Boris Agarski, Branislav Milanovic, Darko Milankovic, Milana Ilic,
Igor Budak, Djordje Vukelic, Janko Hodolic
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FOR WEIGHTING OF IMPACT CATEGORIES
INLIFECYCLEIMPACTASSESSMENT..................
22.
Jelena Cadjenovic Milovanovic
KNOWLEDGE
oF MODERN
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...,.............181
-
INDISPENSABLE RESOURCE
COMPANY.
..................189
Jelena Cadjenovic Milovanovic
FROM CRM & KM TO CUSTOMERKNOWLEDGE MANAGEMENT ........197
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JelenaCadjenovic Milovanovic
GREEN OFFICE _ FUTURE OF NEW AGE
27.
TECHNOLOGY...............
Alexandre Patou-Parvedy, Milan Despotovic
MODELING OF A SOLAR CHIMNEY ON
........................2r3
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HOUSE
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221
Ielena Cadjenovic Milovanovic, Maja Angelovski
SOME OF THE I]DEAS HOW TO IMPROVE
YOUTH ENTREPRENEURSHIP IN
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Danijela Nikolic, Milorad Bojic, Jasmina Skerlic,
Jasna Radulovic, Marko Miletic
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rN pHoTovoLTArCS
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............
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Matejic, Mirko Blagoj evic, ZoricaDjordjevic,
Nenad Marjanovic,, Nenad Pefiovic
COMPARATIVE ANALYSIS OF DIFERENT TYPE REDUCERS
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UNIT...........
31.
..,,.....,25.5
Bernard Bincrycki
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32.
Pawel Nowicki
RISK MANAGEIVIENT AN IMPORTANT ISSUE
IN QUALITY MA.NAGEMENT
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SYSTEMS
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FOOD QUALITY PRODUCTS IN EU
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SHORTENED E()UIDISTANT EPITROCHOID GEAR..
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Slobodan Djorde'i,ic, Milorad Bojic, Dragan Cvetkovic,
Jovan Malesevic, Marko Miletic
INFLUENCE OF HOUSE SHADOWING TO
TTIE CONSUMP'NON OF PRIMARY ENERGY FOR
ITEATING, COO.LING, AND
37.
$
.............303
Hajnalka Kovac Sarkanj, Vilmos Kovac
FOOD SAFETY I{ND QUALITY MANAGEMENT SYSTEMS
APPLIED IN SEF|.BIAN AND HUNGARIAN FOOD CHAINS ........................ 309
39. Zeljko Spijunovic,
Radosav Mirkovic, Zoran Nesic,
Miroslav Radojicic, Jasmina Vesic Vasovic
AUTOMATIZATION OF OBTAINING INFORMATION AT
INSPECTION OF'TECHNICAL SAFETY OF RAILWAY VEHICLES ...........3I5
40.
Sasa
Bogicevic, Jasmina Vesic Vasovic,
Miroslav Radojicic, Zoran Nesic
APPLICATION OF CLUSTER ANALYSIS IN FUNCTION
OF IMPROVING DECISION MAKING PROCESS
...,.................325
41,
ZorcnNesic, Jasmina Vesic Vasovic, Miroslav Radojicic
IMPROVEMENT OF TIME ANALYSIS QUALITY IN NETWORK
DIAGRAMS BY IMPLEMENTATION OF SOFTWARE SUPPORT ........,,.....329
42.
Danijela Tadic, Jo'vana Kostic, Marija Zahar Djordjevic, Hrvoje Puskaric
TFIE PLANT WASTE MANAGEMENT PROBLEM
IN UNCERTAIN EWIRONMENT.........
43.
.................335
Jasmina Skerlic, IV[ilorad Bojic, Danijela Nikolic,
Jasna Radulovic, Ivlarko
Miletic
A REVIEWLIFE CYCLE ASSESSMENT OF
A SOLAR THER]\4AL COLLECTOR SENSITIVITY ANALYSIS,
ENERGY AND ENVIRONMENTAL
44. ZoricaDjordjevic,
Sasa
BALANCES
......................34I
Jovanovic, Milorad Bojic,
Dragan Adamovic', Milos Matejic
THE INFLUENC]E OF TV AND VIDEO APPLIANCES AND
INFORMATION TECHNOLOGY EQUIPMENT
ON ENERGY COINSUMPTION IN HOUSEHOLDS............... .....351
VUI
7s IQC May,z4th2oL3
"
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45.
g,#$:
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q
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Jasna Radulovic, lMilorad Bojic, Danijela Nikolic,
Jasmina Skerlic, Dragan Taranovic
TOWARDS NET ZERO ENERGY BUILDINGS:
POSSIBILITIES FORPHOTOVOLTAIC
46.
USE
........3:i7
Jovanovic, IVlarko Miletic, ZoicaDjordjevic,
Ivan Miletic, Miknad Bojic
OPTIMISATION OF ZERO-NET ENERGY HOUSE ORIENTATION
rN CTTIES OF DTFFERENT
....................363
Sasa
LATrTUDE..................
47.
Dragana Rejman Itetrovic, Zora Arsovski, Vladimir Rankovic,
Zoran Kalinic, Igor Milanovic
BUSINESS PROCESSES MAPPING IN E-SUPPLY
CHAIN
48.
....,.369
Fkvoje Puskaric, \fiarijaZahar Djordjevic
DETERMINATION OF A DEVELOPMENT PROCESS
PERFORMANCE; USING DEVELOPED FU ZZY EXPERT SYSTEM..... ....,,,,37
49.
Aleksandar Vujovic, Zdravko Krivokapic, Jelena Jovanovic,
Sanja Pekovic, Radivoje Micunovic
BUSINESS PROCESS IMPROVEMENT
BY APPLYING EIENCHMARKING BASED
50.
5
MODEL
................385
Piotr Kafel, Jelena Jovanovic, Zdravko Krivokapic, Aleksanadm Vujovic
MONITORING, IdEASUREMENT, ANALYSIS AND REVIEW
IN POLISH AND MONTENEGRIN ORGANIZATION ACCORDING
TO THE ISO 9OO,{ MANAGEMENT MATURITY MODEL.............................395
51.
Rouhollah Mojtahr:dzadeh
ROLE OF BOAR]D OF BOARD SIZE
ON FINANCIAL PERFORMANCE OF COMMERCIAL BANKS ...................405
52.
Aleksandar Novakovic, Vesna Rankovic, Dejan Divac,
Nenad Grujovic, llikola Milivojevic
MISSING DATA ESTIMATION IN DAM STRUCTURES
USING MULTIPI,E IMPUTATION METHOD
.....,.411
53. Milan
Despotovic, Sasa Babic, Jovanka Lukic, Branimir Milosavljevic
APPLICATION OF ARTIFICIAL NEURAL NETWORK
FOR PREDICTION OF TRAFFIC NOISE BASED
ON THE TRAFFIC FLOW STRUCTURE
................4I5
54.
Aleksandar Jankulovic, Miroslava Raspopovic
PERFORMANCE MEASURES ANALYSIS FOR ONLINE
AND TRADITIO]\IAL
55.
STUDIES
......,..423
Goran Manojlovic. Slavko Arsovski, Ivica Nikolic
INTRODUCTTO\I OF QUALrry STANDARDS FOR SCHOOLS... ................ 42'9
7fr IQC
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56. Lozica Ivanovic,
lDanica Josifovic, Andreja Ilic, Vukic Lazic
ECOLOGYCAL ASPECTS OF HIGH STRENGTH
LOW ALLOYED STEELS AT MECHANICAL CONSTRUCTIONS ..............435
57.
Lozica lvanovic, ,\ndreja Ilic, Blaza Stojanovic,Katarina Zivkovic
TFIE INFLUENCE OF DESIGN MODIFICATIONS OF CARDAN SHAFT
DRIVEN FORK ON ITS STRESS DISTRIBUTION............... .....,4111
58.
Aleksandar Maric, Zoranapavlovic, Slavko Arsovski
IMPROVING TIIIE QUALITY OF ORGANIZATIONAL AND
FUNCTIONAL CONCEPTS OF PUBLIC ADMINISTRATION
BY INTRODUCING PROJECT FLINCTION............... .,...............4417
59.
Snezana Nestic, Nliladin Stefanovic, Aleksandar Djordjevic,
Slavko Arsovski, Svetlana Stojanovic
AN ASSESSME].{T AND OPTIMIZATION oF QUALITY
oF STRATEGY 1PROCESS..................
60.
.....................453
TudorPendiuc
INDICATORS AI\ID IMPLICATIONS FOR
INFORMATION QUALITY MANAGEMENT rMPROVEMENTS............. .....46 5
61.
Aleksandar Djordjevic, Milan Eric, Aleksandar Aleksic,
Snezana Nestic, Svetlana Stojanovic
OPTIMIZATION OF MACHINING PROCESSES USING
THE ABC METH.OD AND GENETIC
62.
Snezana Pesic-Djokic, Ivan
ALGORITHM............
..,...471
Djokic
QUALITYAND'WORLD CLASS MANUFACTURrNG..................................483
63.
Srdjan Nikezic, Dobrica Stojkovic, Boban Djurovic, Aleksandar Djordjevic
LEADERSHIP NIETWORK BLAKE, MOUTON AND MCCANSE:
CASE STUDY - I.EADERSHIP STYLES AND DIMENSIONS
IN ONE OF TTIE LOCAL SELF-GOVERNMENTS IN SERBIA....,.................489
64.
Goran Boskovic,l{ebojsa Jovicic, Marko Milasinovic,
Gordana Jovicic, Dobrica Milovanovic
METHODOLOG'T FORREDUCTION OF GHG EMISSIONS
FROM MUNICIPAL SOLID WASTE COLLECTION AND TRANSPORT.....5O5
65.
Vesna Rankovic, Irlilorad Bojic, Aleksandar Novakovic,
Dragan Cvetkovic, Marko Miletic
FU ZZY CONTROLLER SYNTHESIS
FORBUILDING SHADING CONTROL
.................517
66. Milorad Bojic, Dragan
Adamovic, Jasna Radulovic,
Marko Miletic, Ljrubisa Bojic
LIGHTING USE IN SERBIAN LOW-RISE
HOUSES.....
X
zft
Iqc May,24h2ol3
.............623
$sx$+w.m*$$+.
67'
*
a*g$ $.,gses*$$
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:{,;q{$
ve.sna Radonjic-Djogatovic, Aleksandra Kostic-Ljubisavljevic,
Mrjana Stojanol,ic
QUALITY OF BUSINESS CONSIDERATIONS
IN TELECOMMUNICATIONNETWORKS
68, Y:!nl
...,....,..5,.2g
Radonjic-Djogatovic, Aleksandra Kostic-Ljubisavljevic, Mirjana
Stojanovic
QUALITY oF E-XPERIENCE MEASUREwNis
IN
TELECOMMI.INICATIONNETWORKS
...........535
69. Milorad Bojic, Dragan
Adamovic, Jasna Radulovic.
Ivan Miletic, Ljubisa Bojic
AIR CONDITIONING IN SERBIAN LOW-RISE HOUSES
70.
Marko Miletic, Milorad Bojic, Ivan Miletic, Nenad Miloradovic,
Jasmina skerlic
WINDOWS SEL]ECTION INFLUENCE ON ENERGY HEAT GAIN
AND Loss IN
71.
........5It1
HousE
........................s4t7
slavko Arsovski, lMiodrag Lazic, srecko curcic, sandra Milunovic
MOBILE PRESS FOR CAR RECYCLING DEVELOPMENT..........................553
72. MilanPavlovic, Sr,ecko curcic, Aleksandar Tomovic, Sandra Milunovic
NATIONAL ECCNOMY RESOURCE CAPABILITY FOR
PRODUCTION R3CYCLING EQUIPMENT FOR MOTOR VEHICLES ........559
73.
Igor Milanovic, Miladin Stefanovic, Zora Arsovski,
Dragana Rejman Petrovic, Vladimir Rankovic, Zoran Kalinic
SUPPLY CHAIN INFORMATION INTEGRATION THROUGH
SERVICE ORTENTED
ARCHITECTURE
74.
..............,567
Pavle Mijovic, Evzrnthia Giagloglou, Branislav Jeremic,
Ivan Macuzic, Marko Djapan, Marko Milosevic
INFLUENCE OF PROCESSING ON COSMETIC, PHARMACEUTICAL
AND FOOD EMLILSIONS QUALITY, STABTLITY AND RHEOLOGY ........s79
75.
Marko Milosevic, lvan Macuzic, Petar Todorovic, Marko Djapan,
Evanthia Giagloglou, Djordje Vuckovic
IMPLENMNTATION OF THE 55 SYSTEM AS A FACTOR
FOR TMPROVTNG THE QUALTTY MANAGEMENT......................................585
76.
Katartna Kanjevac Milovanovic
THE REVIEW OI' PROBLEM AND THE ADVANTAGE
OF INVESTING INA PROJECT OBTAINING CE
MARK
.....,..59I
77. Milan
Radenkovic,, Branislav Jeremic, Petar Todorovic,
Marko Djapan, Marko Milosevic, Pavle Mijovic
IMPROVEMENT OF QUALITY IN PRODUCTION PROCESS
BY APPLYING KAIKAKU
METHOD
7tr
IQC May,z4thzol3
....................60I
XI
78.
Aleksandar Aleksic, Marko Djapan, Miladin Stefanovic,
Slavko Arsovski, Danijela Tadic, Ivan Macuzic
ANP AS A TOO]L FORDETERMINING THE
RESILIENCE F/TCTORS'INTERACTION IN
79.
SMES..........
........607
srdjan Nikezic, D'obrica Stojkovic, Boban Djurovic, Aleksandar Djordjevic
LEADERSHIP TRAITS: RESEARCH oF LEADERSHIP AND
COLEADERSHIP PERSONAL CHARACTERISTICS IN LOCAL
GOVERNMENTS OF SERBIA AS A
FRAMEWORK I'OR SOCIAL
CHANGE....
.............613
80.
Dobrivoje Catic, lvlilorad Bojic, Jasna Glisovic,
Zorica Dj ordjevic, Nada Ratkovic
FAULT TREE A]VALYSIS OF SOLAR CONCENTRATORS.......... .......,........62:"9
81.
Evanthia Giagloglou
TOXIC MIXTURES A PROBLEMATIC CASE OF
TOXICTTY QUALITY
INDEXES....
.........................639
rJQR..........
.........64s
82. Rouhollah Mojtahedzadeh, Reza lzadi
THE EFFECT OF'COMPETITIVE ADVANTAGE AS AN
INTERVENING'VARI,ABLE BETWEEN CRITICAL SUCCESS FACTORS
OF SUPPLY CHI\IN MANAGEMENT IMPLEMENTATION AND
PERFORMANCE; IN THE IRANIAN AUTOMOBILE INDUSTRY ....,.,........647
83. Rouhollah Mojtahe,dzadeh, Reza Izadi
ACHIEVING ORGANIZATIONAL EFFECTIVENESS
THROUGH TQM. PRINCIPLES IN DEVELOPING INDUSTRY:
A CASE STUDY OF PALM OIL MECHANDISING BUSINESS
rN cRoss RrvElt
STATE........
84. ElizabetaMitreva
THE SUPERIOR CUSTOMER'S VALUE OF
THE NEW ECONOMY IMPLEMENTED W]THIN
MACEDONTAN COMPANrES..............
85. Vanya Zhivkova
CURRENT TRE}IDS IN THE USE OF
...........6s7
...................669
SOLARENERGY
.,.,,,,.,.675
86. TuRunsheng
BEHAVIOR QUA.LITY DECIDES OUR CONDITIONS
OF SURVIVAL AND
DEVELOPMENT..................
.....................683
87. Karin Kandananond
THE APPLICATION OF BOX-BEHNKEN METHOD
TO OPTIMIZE T]IE DESIGN OF EWMA CHART
FOR AUTOCORITELATED
XII
PROCESSES................
7tr
Iec May,24th2ol3
....................691
$+r$qi$"liifi{+ +**$
88.
Shahab Alam
{ tt,ufilu, {
'l
ggil'u**u* *,
if',fit,i
Malik
MEASURING S]ERVICE QUALITY PERCEPTIONS
OF THE CUSTOIMERS oF RESTAURANTS IN PAKISTAN..........................7I)5
89. SantoshKadam
WHYMANAGEMENT
SYSTEMFAILS
zfr
Iqc May,z4h2ot3
................71g
XIII
CIP - Haraaoruaaquja y nytSnuxa4nlu
Hapo4na 6n6nnorexa Cptiuje, Eeorpa.q
00s.6(082)
INTERNATIONAL
euality Conference
(7 ;2013 ;
Kragujevac)
Conference Manual / 7. lnternational
Quality Conference, May 24rd 2013, Kragujevac
; [organized by] Faculty of Engineering
University of Kragujevac ; [editors Slavko
Arsovski, Miodrag Lazic, Miladin Stefanovicl.
- Kragujevac : Faculty of Engineerin g, ZO1r3
(Kragujevac : Maiinac). - Xil, 706 str.
:
ilustr. ; 24 cm
Tekst Stampan dvostubacno. - Tirai 100. Str. lV: [Preface] / Slavko Arsovski. Napomene i bibliografske reference uz tekst.
- Bibliografija uz svaki rad.
rsBN 978-86-86663-94-8
1. Faculty of Engineering (Kragujevac)
a) MeHapnneHT rorarHilM KBarrreroM - 36opxr,rqra
coBtss.sR-tD 198330635