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Lecture Notes in Artificial Intelligence 9120
Subseries of Lecture Notes in Computer Science
LNAI Series Editors
Randy GoebelUniversity of Alberta, Edmonton, Canada
Yuzuru TanakaHokkaido University, Sapporo, Japan
Wolfgang WahlsterDFKI and Saarland University, Saarbrücken, Germany
LNAI Founding Series Editor
Joerg SiekmannDFKI and Saarland University, Saarbrücken, Germany
More information about this series at http://www.springer.com/series/1244
Leszek Rutkowski · Marcin KorytkowskiRafal Scherer · Ryszard TadeusiewiczLotfi A. Zadeh · Jacek M. Zurada (Eds.)
Artificial Intelligenceand Soft Computing14th International Conference, ICAISC 2015Zakopane, Poland, June 14–18, 2015Proceedings, Part II
ABC
EditorsLeszek RutkowskiCzestochowa University of TechnologyCzestochowaPoland
Marcin KorytkowskiCzestochowa University of TechnologyCzestochowaPoland
Rafal SchererCzestochowa University of TechnologyCzestochowaPoland
Ryszard TadeusiewiczAGH University of Science and TechnologyKrakowPoland
Lotfi A. ZadehUniversity of CaliforniaBerkeley, CaliforniaUSA
Jacek M. ZuradaUniversity of LouisvilleLouisville, KentuckyUSA
ISSN 0302-9743 ISSN 1611-3349 (electronic)Lecture Notes in Artificial IntelligenceISBN 978-3-319-19368-7 ISBN 978-3-319-19369-4 (eBook)DOI 10.1007/978-3-319-19369-4Library of Congress Control Number: 2015939285
LNCS Sublibrary: SL7 – Artificial Intelligence
Springer Cham Heidelberg New York Dordrecht Londonc© Springer International Publishing Switzerland 2015
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Preface
This volume constitutes the proceedings of the 14th International Conference onArtificial Intelligence and Soft Computing, ICAISC 2015, held in Zakopane, Poland,during June 14–18, 2015. The conference was organized by the Polish Neural NetworkSociety in cooperation with the University of Social Sciences in Łódz, the Instituteof Computational Intelligence at the Czestochowa University of Technology, and theIEEE Computational Intelligence Society, Poland Chapter. Previous conferences tookplace in Kule (1994), Szczyrk (1996), Kule (1997), and Zakopane (1999, 2000, 2002,2004, 2006, 2008, 2010, 2012, 2013, and 2014) and attracted a large number of papersand internationally recognized speakers: Lotfi A. Zadeh, Hojjat Adeli, Rafal Angryk,Igor Aizenberg, Shun-ichi Amari, Daniel Amit, Piero P. Bonissone, Jim Bezdek,Zdzisław Bubnicki, Andrzej Cichocki, Włodzisław Duch, Pablo A. Estévez, JerzyGrzymala-Busse, Martin Hagan, Yoichi Hayashi, Akira Hirose, Kaoru Hirota, HisaoIshibuchi, Er Meng Joo, Janusz Kacprzyk, Jim Keller, Laszlo T. Koczy, Adam Krzyzak,Soo-Young Lee, Derong Liu, Robert Marks, Evangelia Micheli-Tzanakou, KaisaMiettinen, Henning Müller, Ngoc Thanh Nguyen, Erkki Oja, Witold Pedrycz, Marios M.Polycarpou, José C. Príncipe, Jagath C. Rajapakse, Šarunas Raudys, EnriqueRuspini, Jörg Siekmann, Roman Słowinski, Igor Spiridonov, Boris Stilman, PonnuthuraiNagaratnam Suganthan, Ryszard Tadeusiewicz, Ah-Hwee Tan, Shiro Usui, Fei-YueWang, Jun Wang, Bogdan M. Wilamowski, Ronald Y. Yager, Syozo Yasui, Gary Yen,and Jacek Zurada. The aim of this conference is to build a bridge between traditionalartificial intelligence techniques and so-called soft computing techniques. It was pointedout by Lotfi A. Zadeh that "soft computing (SC) is a coalition of methodologies whichare oriented toward the conception and design of information/intelligent systems. Theprincipal members of the coalition are: fuzzy logic (FL), neurocomputing (NC), evo-lutionary computing (EC), probabilistic computing (PC), chaotic computing (CC), andmachine learning (ML). The constituent methodologies of SC are, for the most part,complementary and synergistic rather than competitive." These proceedings present bothtraditional artificial intelligence methods and soft computing techniques. Our goal is tobring together scientists representing both areas of research. This volume is divided intosix parts:
– Data Mining,– Bioinformatics, Biometrics and Medical Applications,– Concurrent and Parallel Processing,– Agent Systems, Robotics and Control,– Artificial Intelligence in Modeling and Simulation,– Various Problems of Artificial Intelligence.
The conference has attracted a total of 322 submissions from 39 countries and after thereview process, 142 papers have been accepted for publication. The ICAISC 2015 hostedthe Workshop: Large-Scale Visual Recognition and Machine Learning organized by
VI Preface
– Marcin Korytkowski, Czestochowa University of Technology, Poland,– Rafał Scherer, Czestochowa University of Technology, Poland,– Sviatoslav Voloshynovskiy, University of Geneva, Switzerland.
The Workshop was supported by the project "New Perspectives on Intelligent Multi-media Management With Applications in Medicine and Privacy Protecting Systems"cofinanced by a grant from Switzerland through the Swiss Contribution to the EnlargedEuropean Union, and supported by the project "Innovative methods of retrieval andindexing multimedia data using computational intelligence techniques" funded by theNational Science Centre. I would like to thank our participants, invited speakers, andreviewers of the papers for their scientific and personal contribution to the conference.The following reviewers were very helpful in reviewing the papers:
R. AdamczakH. AltrabalsiS. AmariT. BabczynskiM. BaczynskiA. BariM. BiałkoL. BobrowskiL. BorzemskiJ. BotzheimT. BurczynskiR. BurdukK. CetnarowiczL. ChmielewskiW. CholewaM. ChorasK. ChorosP. CichoszR. CierniakP. CiskowskiS. ConcettoB. CyganekJ. CytowskiR. CzabanskiI. CzarnowskiJ. de la RosaK. DembczynskiJ. DembskiN. DerbelG. DobrowolskiW. DuchL. DutkiewiczL. Dymowa
A. DzielinskiP. DziwinskiS. EhteramA. FaneaB. FilipicI. FisterC. FrowdM. GabryelA. GawedaM. GiergielP. GłombZ. GomółkaM. GorawskiM. GorzałczanyG. GosztolyaD. GrabowskiE. GrabskaK. GrabczewskiC. GrosanM. GrzendaJ. Grzymala-BusseJ. HähnerH. HaberdarR. HampelZ. HendzelF. HermannZ. HippeA. HorzykM. HrebienE. HrynkiewiczI. ImaniD. JakóbczakA. Janczak
J. KacprzykW. KaminskiT. KaplonA. KasperskiV. KecmanE. KerreP. KleskJ. KluskaL. KoczyZ. KokosinskiA. KołakowskaJ. KonopackiJ. KorbiczP. KorohodaJ. KoronackiM. KorytkowskiJ. KoscielnyL. KotulskiZ. KowalczukM. KraftM. KretowskiD. KrolB. KryzhanovskyA. KrzyzakA. KubiakE. KucharskaJ. KulikowskiO. KurasovaV. KurkovaM. KurzynskiJ. KusiakN. LabrocheJ. Liao
Preface VII
A. LigezaF. LiuH. LiuM. ŁawrynczukJ. ŁeskiB. MacukowK. MadaniL. MagdalenaW. MalinaR. MallipeddiJ. MandziukU. Markowska-KaczmarM. MarquesA. MaterkaR. Matuk HerreraJ. MazurkiewiczV. MedvedevJ. MendelJ. MichalkiewiczZ. MikrutS. MisinaW. MitkowskiW. MokrzyckiO. MosalovT. MunakataH. NakamotoG. NalepaM. NashedA. NawratF. NeriM. NieniewskiR. NowickiA. ObuchowiczG. OnwuboluS. OsowskiA. OwczarekG. Paragliola
K. PatanA. PieczynskiA. PiegatZ. PietrzykowskiP. ProkopowiczA. PrzybyłA. RadzikowskaE. RafajłowiczE. Rakus-AnderssonM. RaneA. RatajL. RolkaF. RudzinskiA. RusieckiL. RutkowskiS. SakuraiN. SanoJ. SasA. SashimaR. SchererP. SevastjanovA. SedziwyJ. SilcW. SkarbekA. SkowronE. Skubalska-RafajłowiczK. SlotD. SłotaA. SłowikR. SłowinskiC. SmutnickiA. SokołowskiT. SołtysinskiB. StarostaJ. StefanowskiE. StraszeckaV. Štruc
B. StrugP. StrumiłłoM. StudniarskiR. SulejJ. SwachaP. SzczepaniakE. SzmidtM. SzpyrkaJ. SwietekR. TadeusiewiczH. TakagiY. TiumentsevA. TomczykV. TorraF. TrovoM. UrbanskiC. UzorT. VillmannE. VolnaR. VorobelM. WagenknechtT. WalkowiakL. WangJ. WasB. WilamowskiM. WitczakM. WozniakM. WygralakR. WyrzykowskiG. YakhyaevaJ. YeomansJ. ZabrodzkiS. ZadroznyD. ZakrzewskaA. ZamudaR. Zdunek
Finally, I thank my co workers Łukasz Bartczuk, Piotr Dziwinski, Marcin Gabryel,Marcin Korytkowski, and the conference secretary Rafał Scherer, for their enormousefforts to make the conference a very successful event. Moreover, I would like to appre-ciate the work of Marcin Korytkowski who designed the Internet submission system.
June 2015 Leszek RutkowskiPresident of the Polish Neural Network Society
Organization
ICAISC 2015 was organized by the Polish Neural Network Society in cooperation withthe University of Social Sciences in Łódz, the Institute of Computational Intelligenceat Czestochowa University of Technology, and the IEEE Computational IntelligenceSociety, Poland Chapter and with technical sponsorship of the IEEE ComputationalIntelligence Society.
ICAISC Chairpersons
Honorary chairmen
Lotfi A. Zadeh University of California, Berkeley, USAHojjat Adeli The Ohio State University, USAJacek Zurada University of Louisville, USA
General chairman
Leszek Rutkowski Czestochowa University of Technology, Poland
Co-chairmen
Włodzisław Duch Nicolaus Copernicus University, PolandJanusz Kacprzyk Polish Academy of Sciences, PolandJózef Korbicz University of Zielona Góra, PolandRyszard Tadeusiewicz AGH University of Science and Technology,
Poland
ICAISC Program Committee
Rafał Adamczak, PolandCesare Alippi, ItalyShun-ichi Amari, JapanRafal A. Angryk, USAJarosław Arabas, PolandRobert Babuska, NetherlandsIldar Z. Batyrshin, RussiaJames C. Bezdek, AustraliaMarco Block-Berlitz, GermanyLeon Bobrowski, PolandPiero P. Bonissone, USA
Bernadette Bouchon-Meunier, FranceTadeusz Burczynski, PolandAndrzej Cader, PolandJuan Luis Castro, SpainYen-Wei Chen, JapanWojciech Cholewa, PolandFahmida N. Chowdhury, USAAndrzej Cichocki, JapanPaweł Cichosz, PolandKrzysztof Cios, USAIan Cloete, Germany
X Organization
Oscar Cordón, SpainBernard De Baets, BelgiumNabil Derbel, TunisiaEwa Dudek-Dyduch, PolandLudmiła Dymowa, PolandAndrzej Dzielinski, PolandDavid Elizondo, UKMeng Joo Er, SingaporePablo Estevez, ChileJános Fodor, HungaryDavid B. Fogel, USARoman Galar, PolandAlexander I. Galushkin, RussiaAdam Gaweda, USAJoydeep Ghosh, USAJuan Jose Gonzalez de la Rosa, SpainMarian Bolesław Gorzałczany, PolandKrzysztof Grabczewski, PolandGarrison Greenwood, USAJerzy W. Grzymala-Busse, USAHani Hagras, UKSaman Halgamuge, AustraliaRainer Hampel, GermanyZygmunt Hasiewicz, PolandYoichi Hayashi, JapanTim Hendtlass, AustraliaFrancisco Herrera, SpainKaoru Hirota, JapanAdrian Horzyk, PolandTingwen Huang, USAHisao Ishibuchi, JapanMo Jamshidi, USAAndrzej Janczak, PolandNorbert Jankowski, PolandRobert John, UKJerzy Józefczyk, PolandTadeusz Kaczorek, PolandWładysław Kaminski, PolandNikola Kasabov, New ZealandOkyay Kaynak, TurkeyVojislav Kecman, New ZealandJames M. Keller, USAEtienne Kerre, BelgiumFrank Klawonn, GermanyJacek Kluska, PolandLeonid Kompanets, Poland
Przemysław Korohoda, PolandJacek Koronacki, PolandJan M. Koscielny, PolandZdzisław Kowalczuk, PolandRobert Kozma, USALászló Kóczy, HungaryRudolf Kruse, GermanyBoris V. Kryzhanovsky, RussiaAdam Krzyzak, CanadaJuliusz Kulikowski, PolandVera Kurkova, Czech RepublicMarek Kurzynski, PolandHalina Kwasnicka, PolandSoo-Young Lee, KoreaGeorge Lendaris, USAAntoni Ligeza, PolandZhi-Qiang Liu, Hong KongSimon M. Lucas, UKJacek Łeski, PolandBohdan Macukow, PolandKurosh Madani, FranceLuis Magdalena, SpainWitold Malina, PolandKrzysztof Malinowski, PolandJacek Mandziuk, PolandAntonino Marvuglia, LuxembourgAndrzej Materka, PolandJacek Mazurkiewicz, PolandJaroslaw Meller, PolandJerry M. Mendel, USARadko Mesiar, SlovakiaZbigniew Michalewicz, AustraliaZbigniew Mikrut, PolandSudip Misra, USAWojciech Moczulski, PolandJavier Montero, SpainEduard Montseny, SpainKazumi Nakamatsu, JapanDetlef D. Nauck, GermanyAntoine Naud, PolandEdward Nawarecki, PolandNgoc Thanh Nguyen, PolandAntoni Niederlinski, PolandRobert Nowicki, PolandAndrzej Obuchowicz, PolandMarek Ogiela, Poland
Organization XI
Erkki Oja, FinlandStanisław Osowski, PolandNikhil R. Pal, IndiaMaciej Patan, PolandWitold Pedrycz, CanadaLeonid Perlovsky, USAAndrzej Pieczynski, PolandAndrzej Piegat, PolandVincenzo Piuri, ItalyLech Polkowski, PolandMarios M. Polycarpou, CyprusDanil Prokhorov, USAAnna Radzikowska, PolandEwaryst Rafajłowicz, PolandSarunas Raudys, LithuaniaOlga Rebrova, RussiaVladimir Red’ko, RussiaRaúl Rojas, GermanyImre J. Rudas, HungaryEnrique H. Ruspini, USAKhalid Saeed, PolandDominik Sankowski, PolandNorihide Sano, JapanRobert Schaefer, PolandRudy Setiono, SingaporePawel Sevastianow, PolandJennie Si, USAPeter Sincak, SlovakiaAndrzej Skowron, PolandEwa Skubalska-Rafajłowicz, PolandRoman Słowinski, PolandTomasz G. Smolinski, USACzesław Smutnicki, PolandPilar Sobrevilla, SpainJanusz Starzyk, USAJerzy Stefanowski, Poland
Vitomir Štruc, SloveniaPawel Strumillo, PolandRon Sun, USAJohan Suykens, BelgiumPiotr Szczepaniak, PolandEulalia J. Szmidt, PolandPrzemysław Sliwinski, PolandAdam Słowik, PolandJerzy Swiatek, PolandHideyuki Takagi, JapanYury Tiumentsev, RussiaVicenc Torra, SpainBurhan Turksen, CanadaShiro Usui, JapanMichael Wagenknecht, GermanyTomasz Walkowiak, PolandDeliang Wang, USAJun Wang, Hong KongLipo Wang, SingaporeZenon Waszczyszyn, PolandPaul Werbos, USASlawo Wesolkowski, CanadaSławomir Wiak, PolandBernard Widrow, USAKay C. Wiese, CanadaBogdan M. Wilamowski, USADonald C. Wunsch, USAMaciej Wygralak, PolandRoman Wyrzykowski, PolandRonald R. Yager, USAXin-She Yang, United KingdomGary Yen, USAJohn Yen, USASławomir Zadrozny, PolandAli M.S. Zalzala, United Arab Emirates
ICAISC Organizing Committee
Rafał Scherer SecretaryŁukasz Bartczuk Organizing Committee MemberPiotr Dziwinski Organizing Committee MemberMarcin Gabryel Finance ChairMarcin Korytkowski Databases and Internet Submissions
Contents – Part II
Data Mining
Improvement of the Multiple-View Learning Based on theSelf-Organizing Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Tomasz Galkowski, Artur Starczewski, and Xiuju Fu
Natural Language Processing Methods Used for Automatic PredictionMechanism of Related Phenomenon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Krystian Horecki and Jacek Mazurkiewicz
Visual Exploration of Data with Multithread MIC Computer Architectures 25Piotr Pawliczek, Witold Dzwinel, and David A. Yuen
Random Forests with Weighted Voting for Anomalous Query AccessDetection in Relational Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
Charissa Ann Ronao and Sung-Bae Cho
Performance Evaluation of the Silhouette Index . . . . . . . . . . . . . . . . . . . . . . 49Artur Starczewski and Adam Krzyzak
Convex Nonnegative Matrix Factorization with Rank-1 Update forClustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Rafa�l Zdunek
Bioinformatics, Biometrics and Medical Applications
On the Convergence of Quantum and Distributed ComputationalModels of Consciousness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Susmit Bagchi
Nature-Inspired Algorithms for Selecting EEG Sources for MotorImagery Based BCI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Sebastian Basterrech, Pavel Bobrov, Alexander Frolov,and Dusan Husek
PROCESS: Projection-Based Classification of ElectroencephalographSignals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Krisztian Buza, Julia Koller, and Kristof Marussy
Feature Extraction of Palm Vein Patterns Based on Two-DimensionalDensity Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Mariusz Kubanek, Dorota Smorawa, and Taras Holotyak
XIV Contents – Part II
Segmentation Based Feature Selection on Classifying ProteomicSpectral Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Hsun-Chih Kuo and Sheng-Tzung Yeh
SOM vs FCM vs PCA in 3D Face Recognition . . . . . . . . . . . . . . . . . . . . . . . 120Sebastian Pabiasz, Janusz T. Starczewski, and Antonino Marvuglia
The Fuzzified Quasi-Perceptron in Decision Making ConcerningTreatments in Necrotizing Fasciitis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
Elisabeth Rakus-Andersson, Janusz Frey, and Danuta Rutkowska
Mobile Fuzzy System for Detecting Loss of Consciousness and EpilepticSeizure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Pawe�l Staszewski, Piotr Woldan, and Sohrab Ferdowsi
Customization of Joint Articulations Using Soft Computing Methods . . . 151Arkadiusz Szarek, Marcin Korytkowski, Leszek Rutkowski,Magdalena Scherer, Janusz Szyprowski, and Dimce Kostadinov
A New Method for the Dynamic Signature Verification Based on theStable Partitions of the Signature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Marcin Zalasinski, Krzysztof Cpa�lka, and Meng Joo Er
New Fast Algorithm for the Dynamic Signature Verification UsingGlobal Features Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Marcin Zalasinski, Krzysztof Cpa�lka, and Yoichi Hayashi
Concurrent Parallel Processing
Parallelization of a Block Cipher Based on Chaotic Neural Networks . . . 191Dariusz Burak
Acceleration of Neighborhood Evaluation for a Multi-objective VehicleRouting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
Szymon Jagie�l�lo, Jaros�law Rudy, and Dominik Zelazny
A Concurrent Inconsistency Reduction Algorithm for the PairwiseComparisons Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
Konrad Ku�lakowski, Rados�law Juszczyk, and Sebastian Ernst
OpenCL Implementation of PSO Algorithm for the QuadraticAssignment Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
Piotr Szwed, Wojciech Chmiel, and Piotr Kad�luczka
Agent Systems, Robotics and Control
Towards a Better Understanding and Behavior Recognition ofInhabitants in Smart Cities. A Public Transport Case . . . . . . . . . . . . . . . . 237
Rados�law Klimek and Leszek Kotulski
Contents – Part II XV
Aspects of Structure and Parameters Selection of Control SystemsUsing Selected Multi-Population Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . 247
Krystian �Lapa, Jacek Szczypta, and Rajasekar Venkatesan
Optimization of Controller Structure Using Evolutionary Algorithm . . . . 261Andrzej Przyby�l, Jacek Szczypta, and Lipo Wang
Multi-Criteria Fuel Distribution: A Case Study . . . . . . . . . . . . . . . . . . . . . . 272Jaros�law Rudy and Dominik Zelazny
A Robust Heuristic for the Multidimensional A-star/Wavefront HybridPlanning Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282
Igor Wojnicki, Sebastian Ernst, and Wojciech Turek
Human-Agent Interaction Design for Decreasing Indebtedness . . . . . . . . . 292Saori Yamamoto and Yugo Takeuchi
Artificial Intelligence in Modeling and Simulation
Fuzzy Xor Classes from Quantum Computing . . . . . . . . . . . . . . . . . . . . . . . 305Anderson Avila, Murilo Schmalfuss, Renata Reiser,and Vladik Kreinovich
New Method for Non-linear Correction Modelling of Dynamic Objectswith Genetic Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 318
�Lukasz Bartczuk, Andrzej Przyby�l, and Petia Koprinkova-Hristova
Clustering Algorithm Based on Molecular Dynamics with Nose-HooverThermostat. Application to Japanese Candlesticks . . . . . . . . . . . . . . . . . . . 330
Leszek J. Chmielewski, Maciej Janowicz, and Arkadiusz Or�lowski
Improving the Analysis of Context-Aware Information via Marker-BasedStigmergy and Differential Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341
Mario G.C.A. Cimino, Alessandro Lazzeri, and Gigliola Vaglini
Modeling Manufacturing Processes with Disturbances - A New MethodBased on Algebraic-Logical Meta-Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353
Ewa Dudek-Dyduch
A New Approach to Nonlinear Modeling Based on Significant OperatingPoints Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364
Piotr Dziwinski and Eduard D. Avedyan
An Application of Differential Evolution to Positioning QueueingSystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379
Marcin Gabryel, Marcin Wozniak, and Robertas Damasevicius
Experimental Evaluation of Selected Approaches to Covariance MatrixRegularization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391
Przemys�law G�lomb and Micha�l Cholewa
XVI Contents – Part II
A New Approach to Security Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402Jan Karwowski and Jacek Mandziuk
Proposal of a Context-Aware Smart Home Ecosystem . . . . . . . . . . . . . . . . 412Rados�law Klimek and Grzegorz Rogus
Computational Models of Immediate and Expected Emotions forEmotional BDI Agents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424
Hanen Lejmi-Riahi, Fahem Kebair, and Lamjed Ben Said
A Graph Grammar Tool for Generating Computational GridStructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436
Wojciech Palacz, Iwona Ryszka, and Ewa Grabska
Assessment of Fertilizer Nitrogen Requirement of Sugar Beetroot UsingInfo-Gap Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448
Andrzej Piegat and Karina Tomaszewska
Geometric Approach in Local Modeling: Learning of Mini-modelsBased on n-Dimensional Simplex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 460
Marcin Pietrzykowski and Andrzej Piegat
Immune Optimal Design of 2-D and 3-D Structures . . . . . . . . . . . . . . . . . . 471Arkadiusz Poteralski, Miros�law Szczepanik, and Tadeusz Burczynski
Swarm and Immune Computing of Dynamically Loaded ReinforcedStructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483
Arkadiusz Poteralski, Miros�law Szczepanik, Rados�law Gorski,and Tadeusz Burczynski
The Setup Method of the Order with the Help of the Rough SetsConvention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495
Aleksandra Ptak, Henryk Piech, and Nina Zhou
ALMM Solver: the Idea and the Architecture . . . . . . . . . . . . . . . . . . . . . . . . 504Krzysztof R ↪aczka, Ewa Dudek-Dyduch, Edyta Kucharska,and Lidia Dutkiewicz
Graph-Based Optimization of Energy Efficiency of Street Lighting . . . . . 515Adam S ↪edziwy and Leszek Kotulski
Extended AMUSE Algorithm and Novel Randomness Approach forBSS Model Aggregation with Methodology Remarks . . . . . . . . . . . . . . . . . . 527
Ryszard Szupiluk, Tomasz Z ↪abkowski, and Krzysztof Gajowniczek
Contents – Part II XVII
Various Problems of Artificial Intelligence
Constraint Optimization Production Planning Problem. A Note onTheory, Selected Approaches and Computational Experiments . . . . . . . . . 541
Weronika T. Adrian, Nicola Leone, Antoni Lig ↪eza, Marco Manna,and Mateusz Slazynski
Investigating the Mapping between Default Logic and Inconsistency-Tolerant Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554
Abdallah Arioua, Nouredine Tamani, Madalina Croitoru,Jerome Fortin, and Patrice Buche
Automated Discovery of Mobile Users Locations with ImprovedK-means Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565
Szymon Bobek, Grzegorz J. Nalepa, and Olgierd Grodzki
Capturing Dynamics of Mobile Context-Aware Systems with Rules andStatistical Analysis of Historical Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 578
Szymon Bobek, Mateusz Slazynski, and Grzegorz J. Nalepa
Reasoning over Vague Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591Mustapha Bourahla
Parallel Simulated Annealing Algorithm for Cyclic Flexible Job ShopScheduling Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603
Wojciech Bozejko, Jaros�law Pempera, and Mieczys�law Wodecki
Transactional Forward Chaining: A Functional Approach . . . . . . . . . . . . . 613Konrad Grzanek
Metasets and Opinion Mining in New Decision Support System . . . . . . . . 625Magdalena Kacprzak, Bart�lomiej Starosta,and Katarzyna Wegrzyn-Wolska
Practical Approach to Interoperability in Production Rule Bases withSUBITO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 637
Krzysztof Kaczor
Measuring Complexity of Business Process Models Integratedwith Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 649
Krzysztof Kluza
On Perturbation Measure for Binary Vectors . . . . . . . . . . . . . . . . . . . . . . . . 660Maciej Krawczak and Grazyna Szkatu�la
A Quick Method for Dynamic Difficulty Adjustment of a ComputerPlayer in Computer Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 669
Ewa Lach
XVIII Contents – Part II
UCT-Based Approach to Capacitated Vehicle Routing Problem . . . . . . . . 679Jacek Mandziuk and Cezary Nejman
An Improved Magnetotactic Bacteria Moment Migration OptimizationAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 691
Hongwei Mo, Jingwen Ma, and Yanyan Zhao
SBVRwiki a Web-Based Tool for Authoring of Business Rules . . . . . . . . . 703Grzegorz J. Nalepa, Krzysztof Kluza, and Krzysztof Kaczor
Classification in Sparse, High Dimensional Environments Applied toDistributed Systems Failure Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 714
Jose M. Navarro, Hugo A. Parada G., and Juan C. Duenas
Balanced Support Vector Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 727Marcin Orchel
Adaptation Mechanism of Feedback in Quaternion Kalman Filteringfor Orientation Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 739
Przemys�law Pruszowski, Agnieszka Szcz ↪esna, Andrzej Polanski,Janusz S�lupik, and Konrad Wojciechowski
Using Graph Grammar Systems with Memory in ComputerAided Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 749
Iwona Ryszka and Barbara Strug
Software Framework for Modular Machine Learning Systems . . . . . . . . . . 760Marcin Korytkowski, Magdalena Scherer, and Sohrab Ferdowsi
Using Co-occurring Graph Patterns in Computer Aided DesignEvaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 768
Barbara Strug
Parallel Cost Function Determination on GPU for the Vehicle RoutingProblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 778
Mieczys�law Wodecki, Wojciech Bozejko, Szymon Jagie�l�lo,and Jaros�law Pempera
A DSS Based on Hybrid Meta-Heuristic ILS-VND for Solving the1-PDTSP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 789
Hiba Yahyaoui and Saoussen Krichen
On Enhancing the Label Propagation Algorithm for Sentiment AnalysisUsing Active Learning with an Artificial Oracle . . . . . . . . . . . . . . . . . . . . . . 799
Anis Yazidi, Hugo Lewi Hammer, Aleksander Bai,and Paal Engelstad
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 811
Contents – Part I
Neural Networks and Their Applications
Parallel Approach to the Levenberg-Marquardt Learning Algorithmfor Feedforward Neural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Jaros�law Bilski, Jacek Smolag, and Jacek M. Zurada
Microarray Leukemia Gene Data Clustering by Means of GeneralizedSelf-Organizing Neural Networks with Evolving Tree-Like Structures . . . 15
Marian B. Gorza�lczany, Jakub Piekoszewski, and Filip Rudzinski
Innovative Types and Abilities of Neural Networks Based on AssociativeMechanisms and a New Associative Model of Neurons . . . . . . . . . . . . . . . . 26
Adrian Horzyk
Complexity of Shallow Networks Representing Finite Mappings . . . . . . . . 39Vera Kurkova
Probabilistic Neural Network Training Procedure with the Use ofSARSA Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Maciej Kusy and Roman Zajdel
Extensions of Hopfield Neural Networks for Solvingof Stereo-Matching Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
�Lukasz Laskowski, Jerzy Jelonkiewicz, and Yoichi Hayashi
Molecular Approach to Hopfield Neural Network . . . . . . . . . . . . . . . . . . . . . 72�Lukasz Laskowski, Magdalena Laskowska, Jerzy Jelonkiewicz,and Arnaud Boullanger
Toward Work Groups Classification Based on Probabilistic NeuralNetwork Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Christian Napoli, Giuseppe Pappalardo, Emiliano Tramontana,Robert K. Nowicki, Janusz T. Starczewski, and Marcin Wozniak
Adaptation of RBM Learning for Intel MIC Architecture . . . . . . . . . . . . . . 90Tomasz Olas, Wojciech K. Mleczko, Robert K. Nowicki,Roman Wyrzykowski, and Adam Krzyzak
Using an Artificial Neural Network to Predict LoopTransformation Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Marek Palkowski and Wlodzimierz Bielecki
XX Contents – Part I
Using Parity-N Problems as a Way to Compare Abilities of Shallow,Very Shallow and Very Deep Architectures . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Pawe�l Rozycki, Janusz Kolbusz, Tomasz Bartczak,and Bogdan M. Wilamowski
Product Multi-kernels for Sensor Data Analysis . . . . . . . . . . . . . . . . . . . . . . 123Petra Vidnerova and Roman Neruda
Fuzzy Systems and Their Applications
A Fuzzy Approach to Competitive Clusters Using Moore Families . . . . . . 137Victor Gerardo Alfaro-Garcia, Anna Maria Gil-Lafuente,and Anna Klimova
A Fingerprint Retrieval Technique Using Fuzzy Logic-Based Rules . . . . . 149Rosario Arjona and Iluminada Baturone
Initial Comparison of Formal Approaches to Fuzzy and Rough Sets . . . . . 160Adam Grabowski and Takashi Mitsuishi
Comparative Approach to the Multi-Valued Logic Constructionfor Preferences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
Krystian Jobczyk, Antoni Lig ↪eza, Maroua Bouzid,and Jerzy Karczmarczuk
Learning Rules for Type-2 Fuzzy Logic System in the Control ofDeNOx Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
Marcin Kacprowicz, Adam Niewiadomski, and Krzysztof Renkas
Selected Applications of P1-TS Fuzzy Rule-Based Systems . . . . . . . . . . . . 195Jacek Kluska
Fuzzy Agglomerative Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207Michal Konkol
An Exponential-Type Entropy Measure on Intuitionistic Fuzzy Sets . . . . 218Yessica Nataliani, Chao-Ming Hwang, and Miin-Shen Yang
Comparative Analysis of MCDM Methods for Assessing the Severity ofChronic Liver Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
Andrzej Piegat and Wojciech Sa�labun
Solving Zadeh’s Challenge Problems with the Application ofRDM-Arithmetic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
Marcin Plucinski
The Directed Compatibility Between Ordered Fuzzy Numbers - A BaseTool for a Direction Sensitive Fuzzy Information Processing . . . . . . . . . . . 249
Piotr Prokopowicz and Witold Pedrycz
Contents – Part I XXI
Learning Rules for Hierarchical Fuzzy Logic Systems with SelectiveFuzzy Controller Activation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260
Krzysztof Renkas, Adam Niewiadomski, and Marcin Kacprowicz
A New Approach to the Rule-Base Evidential Reasoningwith Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
Pavel Sevastjanov, Ludmila Dymova, and Krzysztof Kaczmarek
Bias-Correction Fuzzy C-Regressions Algorithm . . . . . . . . . . . . . . . . . . . . . . 283Miin-Shen Yang, Yu-Zen Chen, and Yessica Nataliani
Interval Type-2 Locally Linear Neuro Fuzzy Model Based on LocallyLinear Model Tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
Zahra Zamanzadeh Darban and Mohammad Hadi Valipour
Evolutionary Algorithms and Their Applications
Hybrids of Two-Subpopulation PSO Algorithm with Local SearchMethods for Continuous Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307
Aneta Bera and Dariusz Sychel
Parallel Coevolutionary Algorithm for Three-Dimensional Bin PackingProblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
Wojciech Bozejko, �Lukasz Kacprzak, and Mieczys�law Wodecki
Adaptive Differential Evolution: SHADE with Competing CrossoverStrategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329
Petr Bujok and Josef Tvrdık
A Parallel Approach for Evolutionary Induced Decision Trees.MPI+OpenMP Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340
Marcin Czajkowski, Krzysztof Jurczuk, and Marek Kretowski
Automatic Grammar Induction for Grammar BasedGenetic Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350
Dariusz Palka and Marek Zachara
On the Ability of the One-Point Crossover Operator to Search theSpace in Genetic Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 361
Zbigniew Pliszka and Olgierd Unold
Multiple Choice Strategy for PSO Algorithm Enhanced withDimensional Mutation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 370
Michal Pluhacek, Roman Senkerik, Ivan Zelinka,and Donald Davendra
A Hybrid Differential Evolution-Gradient Optimization Method . . . . . . . . 379Wojciech Rafaj�lowicz
XXII Contents – Part I
On the Tuning of Complex Dynamics Embedded into DifferentialEvolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389
Roman Senkerik, Michal Pluhacek, Ivan Zelinka, Donald Davendra,Zuzana Kominkova Oplatkova, and Roman Jasek
Classification and Estimation
Mathematical Characterization of Sophisticated Variantsfor Relevance Learning in Learning Matrix QuantizationBased on Schatten-p-norms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403
Andrea Bohnsack, Kristin Domaschke, Marika Kaden,Mandy Lange, and Thomas Villmann
Adaptive Active Learning with Ensemble of Learners and MulticlassProblems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
Wojciech Marian Czarnecki
Orthogonal Series Estimation of Regression Functions in NonstationaryConditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 427
Tomasz Galkowski and Miroslaw Pawlak
A Comparison of Shallow Decision Trees Under Real-Boost Procedurewith Application to Landmine Detection Using Ground PenetratingRadar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436
Przemys�law Kl ↪esk, Mariusz Kapruziak, and Bogdan Olech
A New Interpretability Criteria for Neuro-Fuzzy Systems for NonlinearClassification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448
Krystian �Lapa, Krzysztof Cpa�lka, and Alexander I. Galushkin
Multi-class Nearest Neighbour Classifier for IncompleteData Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469
Bartosz A. Nowak, Robert K. Nowicki, Marcin Wozniak,and Christian Napoli
Cross-Entropy Clustering Approach to One-Class Classification . . . . . . . . 481Przemysaw Spurek, Mateusz Wojcik, and Jacek Tabor
Comparison of the Efficiency of Time and Frequency Descriptors Basedon Different Classification Conceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491
Krzysztof Tyburek, Piotr Prokopowicz, Piotr Kotlarz,and Repka Micha�l
CNC Milling Tool Head Imbalance Prediction Using ComputationalIntelligence Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503
Tomasz Zabinski, Tomasz M ↪aczka, Jacek Kluska, Maciej Kusy,Piotr Gierlak, Robert Hanus, S�lawomir Prucnal, and Jaros�law S ↪ep
Contents – Part I XXIII
Computer Vision, Image and Speech Analysis
A Feature-Based Machine Learning Agent for Automatic Rice andWeed Discrimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517
Beibei Cheng and Eric T. Matson
Relation of Average Error in Prolate Spheroidal Wave FunctionsAlgorithm for Bandlimited Functions Approximation to Radius ofInformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 528
Micha�l Cholewa
Algebraic Logical Meta-Model of Decision Processes -New Metaheuristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541
Ewa Dudek-Dyduch
Specific Object Detection Scheme Based on Descriptors Fusion UsingBelief Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555
Mariem Farhat, Slim Mhiri, and Moncef Tagina
Video Key Frame Detection Based on SURF Algorithm . . . . . . . . . . . . . . . 566Rafa�l Grycuk, Micha�l Knop, and Sayantan Mandal
Automatic Diagnosis of Melanoid Skin Lesions Using Machine LearningMethods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 577
Katarzyna Grzesiak-Kopec, Leszek Nowak, and Maciej Ogorza�lek
An Edge Detection using 2D Gaussian Function inComputed Tomography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 586
Michal Knas, Robert Cierniak, and Olga Rebrova
Facial Displays Description Schemas for Smiling vs. Neutral EmotionRecognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 594
Karolina Nurzynska and Bogdan Smo�lka
Image Segmentation in Liquid Argon Time ProjectionChamber Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 606
Piotr P�lonski, Dorota Stefan, Robert Sulej, and Krzysztof Zaremba
Massively Parallel Change Detection with Application to VisualQuality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 616
Ewaryst Rafaj�lowicz and Karol Nizynski
A Fuzzy Logic Approach for Gender Recognition from Face Imageswith Embedded Bandlets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 626
Zain Shabbir, Absar Ullah Khan, Aun Irtaza,and Muhammad Tariq Mahmood
Interpretation of Image Segmentation in Termsof Justifiable Granularity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 638
Piotr S. Szczepaniak
XXIV Contents – Part I
Information Granules in Application to Image Recognition . . . . . . . . . . . . 649Krzysztof Wiaderek, Danuta Rutkowska,and Elisabeth Rakus-Andersson
Can We Process 2D Images Using Artificial Bee Colony? . . . . . . . . . . . . . . 660Marcin Wozniak, Dawid Po�lap, Marcin Gabryel, Robert K. Nowicki,Christian Napoli, and Emiliano Tramontana
Workshop: Large-Scale Visual Recognition andMachine Learning
Improving Effectiveness of SVM Classifier for Large Scale Data . . . . . . . . 675Jerzy Balicki, Julian Szymanski, Marcin K ↪epa, Karol Draszawka,and Waldemar Kor�lub
Reducing Time Complexity of SVM Modelby LVQ Data Compression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 687
Marcin Blachnik
Secure Representation of Images Using Multi-layer Compression . . . . . . . 696Sohrab Ferdowsi, Sviatoslav Voloshynovskiy, Dimche Kostadinov,Marcin Korytkowski, and Rafa�l Scherer
Image Indexing and Retrieval Using GSOM Algorithm . . . . . . . . . . . . . . . . 706Marcin Gabryel, Rafa�l Grycuk, Marcin Korytkowski,and Taras Holotyak
Multi-layer Architecture For Storing Visual Data Based on WCF andMicrosoft SQL Server Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 715
Rafa�l Grycuk, Marcin Gabryel, Rafa�l Scherer,and Sviatoslav Voloshynovskiy
Object Localization Using Active Partitionsand Structural Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 727
Mateusz Jadczyk and Arkadiusz Tomczyk
Supervised Transform Learning for Face Recognition . . . . . . . . . . . . . . . . . 737Dimche Kostadinov, Sviatoslav Voloshynovskiy, Sohrab Ferdowsi,Maurits Diephuis, and Rafa�l Scherer
Fast Dictionary Matching for Content-Based Image Retrieval . . . . . . . . . . 747Patryk Najgebauer, Janusz Ryga�l, Tomasz Nowak,Jakub Romanowski, Leszek Rutkowski, Sviatoslav Voloshynovskiy,and Rafa�l Scherer
Recognition and Modeling of Atypical Children Behavior . . . . . . . . . . . . . . 757Aleksandra Postawka and Przemys�law Sliwinski
Contents – Part I XXV
Intelligent Fusion of Infrared and Visible Spectrum for VideoSurveillance Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 768
Rania Rebai Boukhriss, Emna Fendri, and Mohamed Hammami
Visual Saccades for Object Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 778Janusz A. Starzyk
Improving Image Processing Performance Using Database User-DefinedFunctions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 789
Michal Vagac and Miroslav Melichercık
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 801