Many computer scientists, engineers, applied mathematicians, and physicists use geometry theory and geometric computing methods in the design of perception-action systems, intelligent autonomous systems, and man-machine interfaces. This handbook brings together the most recent advances in the application of geometric computing for building such systems, with contributions from leading experts in the important fields of neuroscience, neural networks, image processing, pattern recognition, computer vision, uncertainty in geometric computations, conformal computational geometry, computer graphics and visualization, medical imagery, geometry and robotics, and reaching and motion planning. For the first time, the various methods are presented in a comprehensive, unified manner.

This handbook is highly recommended for postgraduate students and researchers working on applications such as automated learning; geometric and fuzzy reasoning; human-like artificial vision; tele-operation; space maneuvering; haptics; rescue robots; man-machine interfaces; tele-immersion; computer- and robotics-aided neurosurgery or orthopedics; the assembly and design of humanoids; and systems for metalevel reasoning.

This Three-Volume-Set constitutes the refereed proceedings of the Second International Conference on Software Engineering and Computer Systems, ICSECS 2011, held in Kuantan, Malaysia, in June 2011. The 190 revised full papers presented together with invited papers in the three volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on software engineering; network; bioinformatics and e-health; biometrics technologies; Web engineering; neural network; parallel and distributed e-learning; ontology; image processing; information and data management; engineering; software security; graphics and multimedia; databases; algorithms; signal processing; software design/testing; e- technology; ad hoc networks; social networks; software process modeling; miscellaneous topics in software engineering and computer systems.

This book constitutes the refereed proceedings of the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2011, held in Moscow, Russia in June 2011.
The 49 revised full papers presented together with 5 invited and 2 tutorial papers were carefully reviewed and selected from a total of 83 submissions. The papers are organized in topical sections on rough sets and approximations, coverings and granules, fuzzy set models, fuzzy set applications, compound values, feature selection and reduction, clusters and concepts, rules and trees, image processing, and interactions and visualization.

This two-volume set LNCS 6691 and 6692 constitutes the refereed proceedings of the 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, held in Torremolinos-M laga, Spain, in June 2011. The 154 revised papers were carefully reviewed and selected from 202 submissions for presentation in two volumes. The second volume includes 76 papers organized in topical sections on video and image processing; hybrid artificial neural networks: models, algorithms and data; advances in machine learning for bioinformatics and computational biomedicine; biometric systems for human-machine interaction; data mining in biomedicine; bio-inspired combinatorial optimization; applying evolutionary computation and nature-inspired algorithms to formal methods; recent advances on fuzzy logic and soft computing applications; new advances in theory and applications of ICA-based algorithms; biological and bio-inspired dynamical systems; and interactive and cognitive environments. The last section contains 9 papers from the International Workshop on Intelligent Systems for Context-Based Information Fusion, ISCIF 2011, held at IWANN 2011.

This book constitutes the refereed proceedings of the 10th International Workshop on Multiple Classifier Systems, MCS 2011, held in Naples, Italy, in June 2011. The 36 revised papers presented together with two invited papers were carefully reviewed and selected from more than 50 submissions. The contributions are organized into sessions dealing with classifier ensembles; trees and forests; one-class classifiers; multiple kernels; classifier selection; sequential combination; ECOC; diversity; clustering; biometrics; and computer security.

Welcome to the proceedings of the Third International Conference on Contemporary Computing, which was held in Noida (outskirts of New Delhi), India. Computing is an exciting and evolving area. This conference, which was jointly organized by the Jaypee Institute of Information Technology, Noida, India and the University of Fl- ida, Gainesville, USA, focused on topics that are of contemporary interest to computer and computational scientists and engineers. The conference had an exciting technical program of 79 papers submitted by - searchers and practitioners from academia, industry, and government to advance the algorithmic, systems, applications, and educational aspects of contemporary comp- ing. These papers were selected from 350 submissions (with an overall acceptance rate of around 23%). The technical program was put together by a distinguished int- national Program Committee consisting of more than 150 members. The Program Committee was led by the following Track Chairs: Arunava Banerjee, Kanad Kishore Biswas, Summet Dua, Prabhat Mishra, Rajat Moona, Sheung-Hung Poon, and Cho-Li Wang. I would like to thank the Program Committee and the Track Chairs for their tremendous effort. I would like to thank the General Chairs, Prof. Sartaj Sahni and Prof. Sanjay Goel, for giving me the opportunity to lead the technical program. Sanjay Ranka

This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has become a well-established series of popular and high-quality conferences on neural computation and its applications. ISNN aims at providing a platform for scientists, researchers, engineers, as well as students to gather together to present and discuss the latest progresses in neural networks, and applications in diverse areas. Nowadays, the field of neural networks has been fostered far beyond the traditional artificial neural networks. This year, ISNN 2010 received 591 submissions from more than 40 countries and regions. Based on rigorous reviews, 170 papers were selected for publication in the proceedings. The papers collected in the proceedings cover a broad spectrum of fields, ranging from neurophysiological experiments, neural modeling to extensions and applications of neural networks. We have organized the papers into two volumes based on their topics. The first volume, entitled "Advances in Neural Networks- ISNN 2010, Part 1," covers the following topics: neurophysiological foundation, theory and models, learning and inference, neurodynamics. The second volume en- tled "Advance in Neural Networks ISNN 2010, Part 2" covers the following five topics: SVM and kernel methods, vision and image, data mining and text analysis, BCI and brain imaging, and applications.

This special compendium provides a concise and unified vision of facial image processing. It addresses a collection of state-of-the-art techniques, covering the most important areas for facial biometrics and behavior analysis. These techniques also converge to serve an emerging practical application of interactive distance learning.Readers will get a broad picture of the fundamental science of the field and technical details that make the research interesting. Moreover, the intellectual investigation motivated by the demand of real-life application will make this volume an inspiring read for current and prospective researchers and engineers in the fields of computer vision, machine learning and image processing.

These proceedings containall the papers that werepresented at the 4th Inter- tional Conference on Language and Automata Theory and Applications (LATA 2010), held in Trier, Germany, during May 24-28, 2010. The scope of LATA is rather broad, including: algebraic language theory; algorithms on automata and words; automata and logic; automata for system analysis and program veri?cation; automata, concurrency and Petri nets; cel- lar automata; combinatorics on words; computability; computational compl- ity; computer linguistics; data and image compression; decidability questions on words and languages; descriptional complexity; DNA and other models of bio-inspired computing; document engineering; foundations of ?nite state te- nology; fuzzy and rough languages; grammars (Chomsky hierarchy, contextual, multidimensional, uni?cation, categorial, etc. ); grammars and automata arc- tectures; grammatical inference and algorithmic learning; graphs and graph transformation; language varieties and semigroups; language-based cryptog- phy; language-theoretic foundations of arti?cial intelligence and arti?cial life; neuralnetworks;parallelandregulatedrewriting;parsing;patternmatching and pattern recognition; patterns and codes; power series; quantum, chemical and optical computing; semantics; string and combinatorial issues in computational biology and bioinformatics; symbolic dynamics; term rewriting; text algorithms; textretrieval;transducers;trees, treelanguagesandtreemachines;andweighted machines. LATA 2010 received 115 submissions, many among them of good quality. Each one was reviewed by at least three Program Committee members plus, in mostcases, byadditionalexternalreferees. Afterathoroughandvividdiscussion phase, the committee decided to accept 47 papers (which means an acceptance rate of 40. 86%). The conference program also included four invited talk

It givesus greatpleasureto presentthe proceedings of the 9th Asian Conference on Computer Vision (ACCV 2009), held in Xi'an, China, in September 2009. This was the ?rst ACCV conference to take place in mainland China. We received a total of 670 full submissions, which is a new record in the ACCV series. Overall, 35 papers were selected for oral presentation and 131 as posters, yielding acceptance rates of 5.2% for oral, 19.6% for poster, and 24.8% in total. In the paper reviewing, we continued the tradition of previous ACCVsbyconductingtheprocessinadouble-blindmanner.Eachofthe33Area Chairs received a pool of about 20 papers and nominated a number of potential reviewers for each paper. Then, Program Committee Chairs allocated at least three reviewers to each paper, taking into consideration any con?icts of interest and the balance of loads. Once the reviews were ?nished, the Area Chairs made summaryreportsforthepapersintheirpools, basedonthereviewers'comments and on their own assessments of the papers.

Details multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems.

Reveals the substantial advantages of multimodal systems over conventional identification methods.

This book introduces a new way to analyze multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a tra- tional multivariate analysis relying on the assumption of multivariate normality: the L norm is just replaced by different L norms, observation vectors are replaced by 2 1 their(standardizedandcentered)spatial signsandranks, andso on.Themethodsare fairly ef?cient and robust, and no moment assumptions are needed. A uni?ed t- ory starting with the simple one-sample location problem and proceeding through the several-sample location problems to the general multivariate linear regression model and ?nally to the analysis of cluster-dependent data is presented. The material is divided into 14 chapters. Chapter 1 serves as a short introd- tion to the general ideas and strategies followed in the book. Chapter 2 introduces and discusses different types of parametric, nonparametric, and semiparametric s- tistical models used to analyze the multivariate data. Chapter 3 provides general descriptive tools to describe the properties of multivariate distributions and mul- variate datasets. Multivariate location and scatter functionals and statistics and their use is described in detail. Chapter 4 introduces the concepts of multivariate spatial sign, signed-rank, andrank, and shows their connectionto certain L objectivefunc- 1 tions. Also sign and rank covariance matrices are discussed carefully. The ?rst four chapters thus provide the necessary tools to understand the remaining part of the b

This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has become a well-established series of popular and high-quality conferences on neural computation and its applications. ISNN aims at providing a platform for scientists, researchers, engineers, as well as students to gather together to present and discuss the latest progresses in neural networks, and applications in diverse areas. Nowadays, the field of neural networks has been fostered far beyond the traditional artificial neural networks. This year, ISNN 2010 received 591 submissions from more than 40 countries and regions. Based on rigorous reviews, 170 papers were selected for publication in the proceedings. The papers collected in the proceedings cover a broad spectrum of fields, ranging from neurophysiological experiments, neural modeling to extensions and applications of neural networks. We have organized the papers into two volumes based on their topics. The first volume, entitled "Advances in Neural Networks- ISNN 2010, Part 1," covers the following topics: neurophysiological foundation, theory and models, learning and inference, neurodynamics. The second volume en- tled "Advance in Neural Networks ISNN 2010, Part 2" covers the following five topics: SVM and kernel methods, vision and image, data mining and text analysis, BCI and brain imaging, and applications.

This volume contains the papers presented at the 23rd Canadian Conference on Arti?cial Intelligence (AI 2010). The conference was held in Ottawa, Ontario, fromMay31toJune2,2010,andwascollocatedwiththe36thGraphicsInterface Conference(GI2010),andthe7thCanadianConferenceonComputerandRobot Vision (CRV 2010). The Program Committee received 90 submissions for the main conference, AI2010,fromacrossCanadaandaroundtheworld.Eachsubmissionwasreviewed byuptofourreviewers.Forthe?nalconferenceprogramandforinclusioninthese proceedings, 22 regular papers, with allocation of 12 pages each, were selected. Additionally,26 shortpapers,with allocationof 4 pageseach,wereaccepted. The papers from the Graduate Student Symposium are also included in the proceedings:sixoral(fourpages)andsixposter(twopages)presentationpapers. The conference programfeatured three keynote presentations by Dekang Lin (Google Inc.), Guy Lapalme (Universit'edeMontr' eal), and Evangelos Milios (Dalhousie University). The one-page abstracts of their talks are also included in the proceedings. Two pre-conference workshops, each with their own proceedings, were held on May 30, 2010. The Workshop on Intelligent Methods for Protecting Privacy and Con?dentiality in Data was organized by Khaled El Emam and Marina Sokolova. The workshop on Teaching AI in Computing and Information Te- nology (AI-CIT 2010) was organized by Danny Silver, Leila Kosseim, and Sajid Hussain. This conference wouldnot havebeen possible without the hardworkofmany people.WewouldliketothankallProgramCommitteemembersandexternal- viewers for their e?ort in providing high-quality reviews in a timely manner. We thank all the authors of submitted papers for submitting their work,and the - thors of selected papers for their collaboration in preparation of the ?nal copy. ManythankstoEbrahimBagheriandMarinaSokolovafororganizingtheGra- ateStudentSymposium,andchairingtheProgramCommitteeofthesymposium. We are in debt to Andrei Voronkov for developing the EasyChair conference managementsystemandmakingitfreelyavailabletotheacademicworld.Itisan amazinglyelegantand functionalWeb-basedsystem,whichsavedus muchtime.

This volume contains extended papers from Sensor-KDD 2008, the Second - ternational Workshop on Knowledge Discovery from Sensor Data. The second Sensor-KDDworkshopwasheldinLasVegasonAugust24,2008, inconjunction with the 14th ACM SIGKDD InternationalConference on KnowledgeDiscovery and Data Mining. Wide-area sensor infrastructures, remote sensors, and wireless sensor n- works, RFIDs, yield massive volumes of disparate, dynamic, and geographically distributeddata.Assuchsensorsarebecomingubiquitous, asetofbroadrequi- ments is beginning to emerge across high-priority applications including dis- ter preparedness and management, adaptability to climate change, national or homelandsecurity, andthe managementofcriticalinfrastructures.Therawdata from sensors need to be e?ciently managed and transformed to usable infor- tion through data fusion, which in turn must be converted to predictive insights via knowledge discovery, ultimately facilitating automated or human-induced tactical decisions or strategic policy based on decision sciences and decision s- port systems. The expected ubiquity of sensors in the near future, combined with the cr- ical roles they are expected to play in high-priority application solutions, points to an era of unprecedented growth and opportunities. The main motivation for the Sensor-KDD series of workshops stems from the increasing need for a forum to exchange ideas and recent research results, and to facilitate coll- oration and dialog between academia, government, and industrial stakeho- ers. This is clearly re?ected in the successful organization of the ?rst workshop (http: //www.ornl.gov/sci/knowledgediscovery/SensorKDD-2007/)alongwiththe ACMKDD-2007conference, whichwasattendedbymorethanseventyregistered participants, and resulted in an edited book (CRC Press, ISBN-9781420082326, 2008), and a special issue in the Intelligent Data Analysis journal (Volume 13, Number 3, 2

In den letzten Jahren hat sich der Workshop "Bildverarbeitung fur die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2010 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gesprache zwischen Wissenschaftlern, Industrie und Anwendern. Die Beitrage dieses Bandes - einige in englischer Sprache - behandeln alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung, CAD, Segmentierung, Bildanalyse, Visualisierung und Animation, Roboter und Manipulatoren, Chirurgische Simulatoren, Diagnose, Therapieplanung sowie deren klinische Anwendungen.

The 4th IAPR TC3 Workshop on Arti?cial Neural Networks in Pattern Rec- nition, ANNPR 2010, was held at Nile University (Egypt), April 11-13, 2010. The workshop was organized by the Technical Committee on Neural Networks and Computational Intelligence (TC3) that is one of the 20 technical comm- tees (TC) of the International Association for Pattern Recognition (IAPR). The scope of TC3 includes computational intelligence approaches, such as fuzzy s- tems, evolutionary computing and arti?cial neural networks and their use in various pattern recognition applications. The major topics of ANNPR are supervised and unsupervised learning, f- ture selection, pattern recognition in signal and image processing, and appli- tions in data mining or bioinformatics. High quality across such a diverse ?eld of research is achieved through a rigorous and selective review process. For this workshop, 42 papers were submitted and 23 of them were selected for inc- sion in the proceedings. The workshop was enriched by three invited talks given by Barbara Hammer, University of Bielefeld, Germany, Amir F. Atiya, Cairo University, Egypt, and Mohamed Kamel, University of Waterloo, Canada. We would like to thank all authors for the e?ort they put into their subm- sions, and the Scienti?c Committee for taking the time to provide high-quality reviews and selecting the best contributions for the ?nal workshop program. Special thanks are due to the members of the Nile University Organizing C- mittee,AhmedSalah,AmiraElBaroudy,EsraaAly,HebaEzzat,NesrineSameh, Rana Salah and Mohamed Zahhar for their indispensable contributions to the registration management and local organization.

It is indeed a great pleasure to welcome you to the proceedings of the Inter- tional Symposium "Computational Modeling of Objects Represented in Images. Fundamentals,MethodsandApplications"(CompIMAGE2010)heldinBu?alo, NY, May 5-7, 2010. This was the second issue of CompIMAGE symposia, the ?rst one being held in Coimbra, Portugal. The purpose of CompIMAGE 2010 was to provide a common forum for - searchers, scientists, engineers, and practitioners around the world to present their latest research ?ndings, ideas, developments, and applications in the area of computational modeling of objects represented in images. In particular, the symposium aimed to attract scientists who use various approaches - such as ?nite element method, optimization methods, modal analysis, stochastic me- ods, principal components analysis, independent components analysis, distri- tion models, geometrical modeling, digital geometry, grammars,fuzzy logic, and others - to solve problems that appear in a wide range of areas as diverse as medicine, robotics, defense, security, astronomy,materialscience, and manuf- turing. CompIMAGE 2010 was highly international. Its Program Committee m- bersarerenownedexpertscomingfrom25di?erentcountries.Submissionstothe symposium came from 22 countries from Africa, Asia, Europe, North and South America. Overall, representatives of 32 countries contributed to the symposium in di?erent capacities.

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2010, held at the Nile University, Egypt in April 2010. Being the ninth in a well-established series of meetings providing an international forum for d- cussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural n- works, pattern recognition, machine learning and statistics) concerned with this researchtopic.Frommorethan50submissions, theProgramCommitteeselected 31 papers to create an interesting scienti?c program.Paperswere organizedinto sessionsdealingwithclassi?ercombinationandclassi?erselection, diversity, b- ging and boosting, combination of multiple kernels, and applications. The wo- shopprogramandthisvolumewereenrichedbytwoinvitedtalksgivenbyGavin Brown(University of Manchester, UK), and Friedhelm Schwenker(University of Ulm, Germany). As usual, the workshop would not have been possible without the help of many individuals and organizations. First of all, our thanks go to the members of the MCS 2010 Program Committee, whose expertise and dedication helped us create an interesting event that marks the progressmade in this ?eld overthe last year and aspire to chart its future research. The help of James Field from the University of Surrey, who administered the submitted paper reviews, and of Giorgio Fumera who managed the MCS website deserve a particular mention. Special thanks are due to the members of the Nile University Organizing C- mittee, AhmedSalah, AmiraElBaroudy, EsraaAly, HebaEzzat, NesrineSameh, Rana Salah and Mohamed Zahhar for their indispensable contributions to the registration management, local organization, and proceedings pre

Starting with fingerprints more than a hundred years ago, there has been ongoing research in biometrics. Within the last forty years face and speaker recognition have emerged as research topics. However, as recently as a decade ago, biometrics itself did not exist as an independent field. Each of the biometric-related topics grew out of different disciplines. For example, the study of fingerprints came from forensics and pattern recognition, speaker recognition evolved from signal processing, the beginnings of face recognition were in computer vision, and privacy concerns arose from the public policy arena. One of the challenges of any new field is to state what the core ideas are that define the field in order to provide a research agenda for the field and identify key research problems. Biometrics has been grappling with this challenge since the late 1990s. With the matu ration of biometrics, the separate biometrics areas are coalescing into the new discipline of biometrics. The establishment of biometrics as a recognized field of inquiry allows the research community to identify problems that are common to biometrics in general. It is this identification of common problems that will define biometrics as a field and allow for broad advancement."

We are pleased to present this set of peer-reviewed papers from the ?rst MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support. The MICCAI conference has been the ?agship conference for the m- ical imaging community re?ecting the state of the art in techniques of segm- tation, registration, and robotic surgery. Yet, the transfer of these techniques to clinical practice is rarely discussed in the MICCAI conference. To address this gap, we proposed to hold this workshop with MICCAI in London in September 2009. The goal of the workshop was to show the application of content-based retrieval in clinical decision support. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now bec- ing available. These data sets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structuredclinicaldata). Analyzing thesemultimodalsourcesfordisease-speci?c information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disea- speci?c information in modalities to ?nd supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past ?ve years to include large m- ical image collections for testing various algorithms for medical image retrieval and classi?cation.

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.

Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview.

The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.

Image analysis is a computational feat which humans show excellence in, in comp- ison with computers. Yet the list of applications that rely on automatic processing of images has been growing at a fast pace. Biometric authentication by face, ?ngerprint, and iris, online character recognition in cell phones as well as drug design tools are but a few of its benefactors appearing on the headlines. This is, of course, facilitated by the valuable output of the resarch community in the past 30 years. The pattern recognition and computer vision communities that study image analysis have large conferences, which regularly draw 1000 parti- pants. In a way this is not surprising, because much of the human-speci?c activities critically rely on intelligent use of vision. If routine parts of these activities can be automated, much is to be gained in comfort and sustainable development. The - search ?eld could equally be called visualintelligence because it concerns nearly all activities of awake humans. Humans use or rely on pictures or pictorial languages to represent, analyze, and develop abstract metaphors related to nearly every aspect of thinking and behaving, be it science, mathematics, philosopy, religion, music, or emotions. The present volume is an introductory textbook on signal analysis of visual c- putation for senior-level undergraduates or for graduate students in science and - gineering. My modest goal has been to present the frequently used techniques to analyze images in a common framework-directional image processing.

In its lucky 12+1 edition, during April 7-9, 2010, the European Conference on Genetic Programming (EuroGP) travelled to its most easterly location so far, theEuropeanCityof Culture2010,Istanbul,Turkey.EuroGPisthe onlyconf- enceworldwideexclusivelydevotedtogeneticprogrammingandtheevolutionary generation of computer programs. For over a decade, genetic programming (GP) has been considered the new form of evolutionary computation. With nearly 7,000 articles in the online GP bibliography maintained by William B. Langdon, we can say that it is now a mature ?eld. EuroGP has contributed to the success of the ?eld substantially, by being a unique forum for expressing new ideas, meeting, and starting up collaborations. The wide rangeoftopics in this volume re?ectthecurrentstateof researchin the ?eld, including representations, theory, operators and analysis, novel m- els, performance enhancements, extensions of genetic programming,and various applications. The volume contains contributions in the following areas: - Understanding GP behavior andGP analysis include articles on cro- over operators and a new way of analyzing results. -GPperformance presents work on performance enhancements through phenotypic diversity, simpli?cation, ?tness and parallelism. - Novel models and their application present innovative approaches with arti?cial biochemical networks, genetic regulatory networks and geometric di?erential evolution. - Grammatical evolution introduces advances in crossover, mutation and phenotype-genotype maps in this relatively new area. - Machine learning and data mining include articles that present data miningormachinelearningsolutionsusingGPandalsocombinedatamining and machine learning with GP. - Applications rangefromsolvingdi?erentialequations,routingproblems to ?le type detection, object-oriented testing, agents. This year we received 48 submissions, of which 47 were sent to the reviewers.

Metaheuristicscontinuetodemonstratetheire?ectivenessforanever-broadening range of di?cult combinatorial optimization problems appearing in a wide - riety of industrial, economic, and scienti?c domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization and estimation of distribution algorithms. Problems solved successfully include scheduling,timetabling,networkdesign,transportationanddistribution,vehicle routing, the travelling salesman problem, packing and cutting, satis?ability and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It is the ?rst event speci?cally dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop,EvoCOPbecameaconferencein2004.Theeventsgaveresearchersan excellent opportunity to present their latest research and to discuss current - velopments and applications. Following the general trend of hybrid metaheur- tics and diminishing boundaries between the di?erent classes of metaheuristics, EvoCOPhas broadenedits scope in recent years and invited submissions on any kind of metaheuristic for combinatorial optimization.