Transactions on Computational Science VIII PDF
Preview Transactions on Computational Science VIII
Lecture Notes in Computer Science 6260 CommencedPublicationin1973 FoundingandFormerSeriesEditors: GerhardGoos,JurisHartmanis,andJanvanLeeuwen EditorialBoard DavidHutchison LancasterUniversity,UK TakeoKanade CarnegieMellonUniversity,Pittsburgh,PA,USA JosefKittler UniversityofSurrey,Guildford,UK JonM.Kleinberg CornellUniversity,Ithaca,NY,USA FriedemannMattern ETHZurich,Switzerland JohnC.Mitchell StanfordUniversity,CA,USA MoniNaor WeizmannInstituteofScience,Rehovot,Israel OscarNierstrasz UniversityofBern,Switzerland C.PanduRangan IndianInstituteofTechnology,Madras,India BernhardSteffen TUDortmundUniversity,Germany MadhuSudan MicrosoftResearch,Cambridge,MA,USA DemetriTerzopoulos UniversityofCalifornia,LosAngeles,CA,USA DougTygar UniversityofCalifornia,Berkeley,CA,USA MosheY.Vardi RiceUniversity,Houston,TX,USA GerhardWeikum MaxPlanckInstituteforInformatics,Saarbruecken,Germany Marina L. Gavrilova C.J. Kenneth Tan (Eds.) Transactions on Computational Science VIII 1 3 Editors-in-Chief MarinaL.Gavrilova UniversityofCalgary,DepartmentofComputerScience 2500UniversityDriveN.W.,Calgary,AB,T2N1N4,Canada E-mail:[email protected] C.J.KennethTan ExascalaLtd. Unit9,97RickmanDrive,BirminghamB152AL,UK E-mail:[email protected] LibraryofCongressControlNumber:2010935450 CRSubjectClassification(1998):F.2,F.1,I.4,J.3,I.5,G.2 ISSN 0302-9743(LectureNotesinComputerScience) ISSN 1866-4733(TransactiononComputationalScience) ISBN-10 3-642-16235-5SpringerBerlinHeidelbergNewYork ISBN-13 978-3-642-16235-0SpringerBerlinHeidelbergNewYork Thisworkissubjecttocopyright.Allrightsarereserved,whetherthewholeorpartofthematerialis concerned,specificallytherightsoftranslation,reprinting,re-useofillustrations,recitation,broadcasting, reproductiononmicrofilmsorinanyotherway,andstorageindatabanks.Duplicationofthispublication orpartsthereofispermittedonlyundertheprovisionsoftheGermanCopyrightLawofSeptember9,1965, initscurrentversion,andpermissionforusemustalwaysbeobtainedfromSpringer.Violationsareliable toprosecutionundertheGermanCopyrightLaw. springer.com ©Springer-VerlagBerlinHeidelberg2010 PrintedinGermany Typesetting:Camera-readybyauthor,dataconversionbyScientificPublishingServices,Chennai,India Printedonacid-freepaper 06/3180 LNCS Transactions on Computational Science Computational science, an emerging and increasingly vital field, is now widely recognized as an integral part of scientific and technical investigations, affecting researchers and practitioners in areas ranging from aerospace and automotive research to biochemistry, electronics, geosciences, mathematics, and physics. Computer systems research and the exploitation of applied research naturally complement each other. The increased complexity of many challenges in computational science demands the use of supercomputing, parallel processing, sophisticated algorithms, and advanced system software and architecture. It is therefore invaluable to have input by systems research experts in applied computational science research. Transactions on Computational Science focuses on original high-quality research in the realm of computational science in parallel and distributed environments, also encompassing the underlying theoretical foundations and the applications of large- scale computation. The journal offers practitioners and researchers the opportunity to share computational techniques and solutions in this area, to identify new issues, and to shape future directions for research, and it enables industrial users to apply leading- edge, large-scale, high-performance computational methods. In addition to addressing various research and application issues, the journal aims to present material that is validated – crucial to the application and advancement of the research conducted in academic and industrial settings. In this spirit, the journal focuses on publications that present results and computational techniques that are verifiable. Scope The scope of the journal includes, but is not limited to, the following computational methods and applications: • Aeronautics and Aerospace • Astrophysics • Bioinformatics • Climate and Weather Modeling • Communication and Data Networks • Compilers and Operating Systems • Computer Graphics • Computational Biology • Computational Chemistry • Computational Finance and Econometrics • Computational Fluid Dynamics • Computational Geometry VI LNCS Transactions on Computational Science • Computational Number Theory • Computational Physics • Data Storage and Information Retrieval • Data Mining and Data Warehousing • Grid Computing • Hardware/Software Co-design • High-Energy Physics • High-Performance Computing • Numerical and Scientific Computing • Parallel and Distributed Computing • Reconfigurable Hardware • Scientific Visualization • Supercomputing • System-on-Chip Design and Engineering Editorial The Transactions on Computational Science journal is part of the Springer series Lecture Notes in Computer Science, and is devoted to the gamut of computational science issues, from theoretical aspects to application-dependent studies and the validation of emerging technologies. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. Practitioners and researchers share computational techniques and solutions in the area, identify new issues, and shape future directions for research, as well as enable industrial users to apply the techniques presented. The current issue is comprised of two parts. Part 1 focuses on adaptive evolutionary computation, and was prepared by Guest Editors Nadia Nedjah, Abdelhamid Bouchachia and Luiza de Macedo Mourelle. The focus of Part 2 is on computational methods for model visualization and analysis. Part I consists of five manuscripts, each addressing a specific computational problem utilizing adaptive methodologies. It also contains a comprehensive review of the current advancements in the area prepared by the Special Issue Guest Editors. Part II continues the theme. It is comprised of six manuscripts that take an in-depth look at selected computational science research in the areas of geometric computing, Euclidean distance transform, distributed systems, segmentation, visualization of monotone data and data interpolation. Each paper provides a rigorous analysis or a detailed experiment to amplify the impact of the contribution. In conclusion, we would like to extend our sincere appreciation to Special Issue Guest Editors Nadia Nedjah, Abdelhamid Bouchachia and Luiza de Macedo Mourelle for their efficiency and diligence, all authors for submitting their papers, and all Associate Editors and referees for their valuable work. We would also like to express our gratitude to the LNCS editorial staff of Springer, in particular Alfred Hofmann, Ursula Barth and Anna Kramer, who supported us at every stage of the project. It is our hope that the fine collection of papers presented in this journal issue will be a valuable resource for Transactions on Computational Science readers and will stimulate further research into the vibrant area of computational science applications. June 2010 Marina L. Gavrilova C.J. Kenneth Tan Adaptive Evolutionary Computation Special Issue Guest Editors’ Preface Adaptation plays a central role in dynamically changing systems. It is about the ability ofa systemto “responsively”self-adjustin responseto change inthe surrounding environment. Like living creatures that have evolved over millions ofyearsdevelopingecologicalsystemsduetotheirself-adaptationandfitnessca- pacitytothedynamicenvironment,systemsundergosimilarcyclestoimproveor atleastto notweakentheir performancewheninternalorexternalchangestake place.Internalchangebearsonthephysicalstructureofthesystem(thebuilding blocks:hardwareand/orsoftwarecomponents).Externalchangeoriginatesfrom the environment due to reciprocal action and interaction. These two classes of change shed light on the researchavenues towards smart adaptive systems. Thestateoftheartdrawsthepictureofchallengesthatsuchsystemsneedto face before they become reality. A sustainable effort is necessary to develop in- telligent hardware on one level and concepts and algorithms on the other level. The former level concerns various analog and digital accommodations encom- passing self-healing, self-testing, reconfigurationand many other aspects of sys- temdevelopmentandmaintenance.Thelatterlevelisconcernedwithdeveloping algorithms, concepts and techniques that can rely on metaphors of nature and that are inspired from biological and cognitive plausibility. Toface the differenttypes ofchange,systems mustself-adapttheirstructure and self-adjust their controlling parameters over time as changes are sensed. A fundamental issue is the notion of “self”, which refers to the capability of the systemstoactandreactontheirown.Itcoversallstagesofthesystemsworking and maintenance cycle starting from online self-monitoring to self-growing and self-organizing.Relying on the two-fold plausibility, which is the basis for many computationalmodels,neuralnetworkscanbeencounteredinvariousreal-world dynamicalandnon-stationarysystemsthatrequirecontinuousupdateovertime. Thereexistmanyneuralmodelsthataretheoreticallybasedonincremental(i.e., online, sequential) learning, addressing in particular the notions of self-growing and self-organizing. However, their strength in practical situations that involve online adaptation is not as efficient as desirable. Part I of this journal aims to present the latest advances of adaptive models for evolutionary computation and their application in various dynamic environ- ments. The special issue is intended for a wide audience including scientists as well as mathematicians, physicists, engineers, computer scientists, biologists, economists and social scientists. This special section covers various topics of evolutionary computation related to self-organization, self-monitoring and self- growing concepts. It also aims at presenting a coherentview of these issues and athoroughdiscussionaboutthe future researchavenues.Themaincontribution of each of the five papers included is briefly introduced in the following. X Guest Editor’s Preface Inthefirstpaperofthesection,entitled“EnvironmentalModelingandIden- tification Based on Changes in Sensory Information”, the authors present an environmentalmodelingmethodbasedonstaterepresentation,whichrepresents a change in sensory information. The model presentedenables the mobile robot to identify which environment it is in. The results of experiments on a real mo- bilerobotwithonlylow-sensitivityinfraredsensorsshowthe effectivenessofthe method. In the second paper, entitled “Polymorphic Particle Swarm Optimization”, the authorproposesa newconceptcalledpolymorphicparticleswarmoptimiza- tion, which generalizes the standard update rule by a polymorphic update rule. Thispolymorphicupdateruleisanadaptiveupdaterulechangingsymbolsbased on accumulative histogramsand roulette-wheel sampling. The proposed variant is applied to typical benchmark functions and in most cases it outperforms the other PSO existing variants. In the third paper, entitled “C-Strategy: A Dynamic Adaptive Strategy for theCLONALGAlgorithm”,the authorsproposeanewparametercontrolstrat- egy for the immune algorithm CLONALG. The approach presented is based on the concepts behind reinforcement learning. The approach provides an efficient andlow costadaptivetechnique forparametercontrol.The results obtainedare very encouraging. Inthe fourthpaper,entitled“AComparisonofGenotypeRepresentationsto AcquireStockTradingStrategyUsingGeneticAlgorithms”,theauthorscompare somegenotypecodingmethodsoftechnicalindicatorsandtheirparameterstoac- quireastocktradingstrategyusinggeneticalgorithms.Theyshowthatthesecon- ventionalrepresentationsarenotsoeffectivefortheGAsearch.Thereafter,they proposeanewgenotypecodingmethods,namelythe allele-basedindirectrepre- sentationandshowthesuperiorityoftheproposedindividualrepresentation. In the fifth paper,entitled “Automatic Adaptive Modeling ofFuzzy Systems Using Particle Swarm Optimization”, the authors show how to yield adaptive fuzzy models by applying a particle swarm-based optimization method. The resultsofthisautomaticmodelingaregivenforthreecomplexthree-dimensional functions and prove the effectiveness of the proposed method. The Guest Editors are very grateful to the authors of this special section and to the reviewers for their tremendous service in critically reviewing the submitted papers. The editors would also like to thank Prof. Marina Gavrilova, the Editor-in-Chief of Transactions on Computational Science, Springer-Verlag, for the editorial assistance and excellent cooperative collaborationin producing this scientific work. We hope that the reader will share our excitement about the papers on adaptive evolutionary computation and will find them useful. June 2010 Nadia Nedjah Abdelhamid Bouchachia Luiza de Macedo Mourelle LNCS Transactions on Computational Science – Editorial Board Marina L. Gavrilova, Editor-in-chief University of Calgary, Canada Chih Jeng Kenneth Tan, Editor-in-chief OptimaNumerics, UK Tetsuo Asano JAIST, Japan Brian A. Barsky University of California at Berkeley, USA Alexander V. Bogdanov Institute for High Performance Computing and Data Bases, Russia Martin Buecker Aachen University, Germany Rajkumar Buyya University of Melbourne, Australia Hyungseong Choo Sungkyunkwan University, Korea Danny Crookes Queen's University Belfast, UK Tamal Dey Ohio State University, USA Ivan Dimov Bulgarian Academy of Sciences, Bulgaria Magdy El-Tawil Cairo University, Egypt Osvaldo Gervasi Università degli Studi di Perugia, Italy Christopher Gold University of Glamorgan, UK Rodolfo Haber Council for Scientific Research, Spain Andres Iglesias University of Cantabria, Spain Deok-Soo Kim Hanyang University, Korea Ivana Kolingerova University of West Bohemia, Czech Republic Vipin Kumar Army High Performance Computing Research Center, USA Antonio Lagana Università degli Studi di Perugia, Italy D.T. Lee Institute of Information Science, Academia Sinica, Taiwan Laurence Liew Platform Computing, Singapore Nikolai Medvedev Novosibirsk Russian Academy of Sciences, Russia Graham M Megson University of Reading, UK Edward D. Moreno UEA – University of Amazonas state, Brazil Youngsong Mun Soongsil University, Korea Dimitri Plemenos Université de Limoges, France Viktor K. Prasanna University of Southern California, USA Muhammad Sarfraz KFUPM, Saudi Arabia Dale Shires Army Research Lab, USA Masha Sosonkina Ames Laboratory, USA Alexei Sourin Nanyang Technological University, Singapore David Taniar Monash University, Australia Athanasios Vasilakos University of Western Macedonia, Greece Chee Yap New York University, USA Igor Zacharov SGI Europe, Switzerland Zahari Zlatev National Environmental Research Institute, Denmark
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