This book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in conjunction with PAKDD 2011 in Shenzhen, China, in May 2011: the International Workshop on Behavior Informatics (BI 2011), the Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE 2011), the Workshop on Biologically Inspired Techniques for Data Mining (BDM 2011), the Workshop on Advances and Issues in Traditional Chinese Medicine Clinical Data Mining (AI-TCM 2011), and the Second Workshop on Data Mining for Healthcare Management (DMGHM 2011). The book also includes papers from the First PAKDD Doctoral Symposium on Data Mining (DSDM 2011). The 42 papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics discussing emerging techniques in the field of knowledge discovery in databases and their application domains extending to previously unexplored areas such as data mining based on optimization techniques from biological behavior of animals and applications in Traditional Chinese Medicine clinical research and health care management.

Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. ETL generalizes Transformation Based Learning (TBL) by solving the TBL bottleneck: the construction of good template sets. ETL automatically generates templates using Decision Tree decomposition.

The authors describe ETL Committee, an ensemble method that uses ETL as the base learner. Experimental results show that ETL Committee improves the effectiveness of ETL classifiers. The application of ETL is presented to four Natural Language Processing (NLP) tasks: part-of-speech tagging, phrase chunking, named entity recognition and semantic role labeling. Extensive experimental results demonstrate that ETL is an effective way to learn accurate transformation rules, and shows better results than TBL with handcrafted templates for the four tasks. By avoiding the use of handcrafted templates, ETL enables the use of transformation rules to a greater range of tasks.

Suitable for both advanced undergraduate and graduate courses, Entropy Guided Transformation Learning: Algorithms and Applications provides a comprehensive introduction to ETL and its NLP applications.

This book constitutes the refereed proceedings of the First International Conference on Digital Image Processing and Pattern Recognition, DPPR 2011, held in Tirunelveli, India, in September 2011. The 48 revised full papers were carefully reviewed and selected from about 400 submissions. The conference brought together leading researchers, engineers and scientists in the domain of Digital Image Processing and Pattern Recognition. The papers cover all theoretical and practical aspects of the field and present new advances and current research results in two tracks, namely: digital image processing and pattern recognition, and computer science, engineering and information technology.

Biometrics is becoming increasingly common in establishments that require high security such as state security and financial sectors. The increased threat to national security by terrorists has led to the explosive popularity of biometrics. Biometric devices are now available to capture biometric measurements such as fingerprints, palm, retinal scans, keystroke, voice recognition and facial scanning. However, the accuracy of these measurements varies, which has a direct relevance on the levels of security they offer. With the need to combat the problems related to identify theft and other security issues, society will have to compromise between security and personal freedoms. Securing Biometrics Applications investigates and identifies key impacts of biometric security applications, while discovering opportunities and challenges presented by the biometric technologies available.

This book presents the most recent achievements in some rapidly developing fields within Computer Science. This includes the very latest research in biometrics and computer security systems, and descriptions of the latest inroads in artificial intelligence applications. The book contains over 30 articles by well-known scientists and engineers. The articles are extended versions of works introduced at the ACS-CISIM 2005 conference.

Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability.

This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.

Design of water control structures, reservoir management, economic evaluation of flood protection projects, land use planning and management, flood insurance assessment, and other projects rely on knowledge of magnitude and frequency of floods. Often, estimation of floods is not easy because of lack of flood records at the target sites. Regional flood frequency analysis (RFFA) alleviates this problem by utilizing flood records pooled from other watersheds, which are similar to the watershed of the target site in flood characteristics.

Clustering techniques are used to identify group(s) of watersheds which have similar flood characteristics. This book is a comprehensive reference on how to use these techniques for RFFA and is the first of its kind. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory and artificial neural networks. It also documents research findings on application of clustering techniques to RFFA that remain scattered in various hydrology and water resources journals.

The optimal number of groups defined in an area is based on cluster validation measures and L-moment based homogeneity tests. These form the bases to check the regions for homogeneity.

The subjectivity involved and the effort needed to identify homogeneous groups of watersheds with conventional approaches are greatly reduced by using efficient clustering techniques discussed in this book. Furthermore, better flood estimates with smaller confidence intervals are obtained by analysis of data from homogeneous watersheds. Consequently, the problem of over- or under-designing by using these flood estimates is reduced. This leads to optimal economic design of structures. The advantages of better regionalization of watersheds and their utility are entering into hydrologic practice.

Audience
This book will be of interest to researchers in stochastic hydrology, practitioners in hydrology and graduate students.

A mathematically rigorous but accessible treatment of digital signal processing that intertwines basic theoretical techniques with hands-on laboratory instruction is provided by this book. The book covers various aspects of the digital signal processing (DSP) "problem." It begins with the analysis of discrete-time signals and explains sampling and the use of the discrete and fast Fourier transforms. The second part of the book - covering digital to analog and analog to digital conversion - provides a practical interlude in the mathematical content before Part III lays out a careful development of the Z-transform and the design and analysis of digital filters.

"Intelligent Data Mining - Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.

This book constitutes the refereed proceedings of the 18th International Multimedia Modeling Conference, MMM 2012, held in Klagenfurt, Austria, in January 2012. The 38 revised regular papers, 12 special session papers, 15 poster session papers, and 6 demo session papers were carefully reviewed and selected from 142 submissions. The papers are organized in the following topical sections: annotation, annotation and interactive multimedia applications, event and activity, mining and mobile multimedia applications, search, summarization and visualization, visualization and advanced multimedia systems, and the special sessions: interactive and immersive entertainment and communication, multimedia preservation: how to ensure multimedia access over time, multi-modal and cross-modal search, and video surveillance.

Human and animal vision systems have been driven by the pressures of evolution to become capable of perceiving and reacting to their environments as close to instantaneously as possible. Casting such a goal of reactive vision into the framework of existing technology necessitates an artificial system capable of operating continuously, selecting and integrating information from an environment within stringent time delays. The YAP (Vision As Process) project embarked upon the study and development of techniques with this aim in mind. Since its conception in 1989, the project has successfully moved into its second phase, YAP II, using the integrated system developed in its predecessor as a basis. During the first phase of the work the "vision as a process paradigm" was realised through the construction of flexible stereo heads and controllable stereo mounts integrated in a skeleton system (SA V A) demonstrating continuous real-time operation. It is the work of this fundamental period in the V AP story that this book aptly documents. Through its achievements, the consortium has contributed to building a strong scientific base for the future development of continuously operating machine vision systems, and has always underlined the importance of not just solving problems of purely theoretical interest but of tackling real-world scenarios. Indeed the project members should now be well poised to contribute (and take advantage of) industrial applications such as navigation and process control, and already the commercialisation of controllable heads is underway.

Fuzzy sets were first proposed by Lotfi Zadeh in his seminal paper [366] in 1965, and ever since have been a center of many discussions, fervently admired and condemned. Both proponents and opponents consider the argu ments pointless because none of them would step back from their territory. And stiH, discussions burst out from a single sparkle like a conference pa per or a message on some fuzzy-mail newsgroup. Here is an excerpt from an e-mail messagepostedin1993tofuzzy-mail@vexpert. dbai. twvien. ac. at. by somebody who signed "Dave". , . . . Why then the "logic" in "fuzzy logic"? I don't think anyone has successfully used fuzzy sets for logical inference, nor do I think anyone wiH. In my admittedly neophyte opinion, "fuzzy logic" is a misnomer, an oxymoron. (1 would be delighted to be proven wrong on that. ) . . . I carne to the fuzzy literature with an open mind (and open wal let), high hopes and keen interest. I am very much disiHusioned with "fuzzy" per se, but I did happen across some extremely interesting things along the way. " Dave, thanks for the nice quote! Enthusiastic on the surface, are not many of us suspicious deep down? In some books and journals the word fuzzy is religiously avoided: fuzzy set theory is viewed as a second-hand cheap trick whose aim is nothing else but to devalue good classical theories and open up the way to lazy ignorants and newcomers.

Recently, there has been a dramatic increase in the use of sensors in the non-visible bands. As a result, there is a need for existing computer vision methods and algorithms to be adapted for use with non-visible sensors, or for the development of completely new methods and systems. Computer Vision Beyond the Visible Spectrum is the first book to bring together state-of-the-art work in this area. It presents new & pioneering research across the electromagnetic spectrum in the military, commercial, and medical domains. By providing a detailed examination of each of these areas, it focuses on the development of state-of-the-art algorithms and looks at how they can be used to solve existing & new challenges within computer vision. Essential reading for academics & industrial researchers working in the area of computer vision, image processing, and medical imaging, it will also be useful background reading for advanced undergraduate & postgraduate students.

As a graduate student at Ohio State in the mid-1970s, I inherited a unique c- puter vision laboratory from the doctoral research of previous students. They had designed and built an early frame-grabber to deliver digitized color video from a (very large) electronic video camera on a tripod to a mini-computer (sic) with a (huge ) disk drive-about the size of four washing machines. They had also - signed a binary image array processor and programming language, complete with a user's guide, to facilitate designing software for this one-of-a-kindprocessor. The overall system enabled programmable real-time image processing at video rate for many operations. I had the whole lab to myself. I designed software that detected an object in the eldofview, trackeditsmovementsinrealtime, anddisplayedarunningdescription of the events in English. For example: "An object has appeared in the upper right corner...Itismovingdownandtotheleft...Nowtheobjectisgettingcloser...The object moved out of sight to the left"-about like that. The algorithms were simple, relying on a suf cient image intensity difference to separate the object from the background (a plain wall). From computer vision papers I had read, I knew that vision in general imaging conditions is much more sophisticated. But it worked, it was great fun, and I was hooked.

Principles of Visual Information Retrieval introduces the basic concepts and techniques in VIR and develops a foundation that can be used for further research and study.
Divided into 2 parts, the first part describes the fundamental principles. A chapter is devoted to each of the main features of VIR, such as colour, texture and shape-based search. There is coverage of search techniques for time-based image sequences or videos, and an overview of how to combine all the basic features described and integrate context into the search process.
The second part looks at advanced topics such as multimedia query, specification, visual learning and semantics, and offers state-of-the-art coverage that is not available in any other book on the market.
This book will be essential reading for researchers in VIR, and for final year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, Computer Vision and Pattern Recognition.

This book features a collection of articles presented at the 2007 Workshop on Advances in Pattern Recognition, which was organized in conjunction with the 5th International Summer School on Pattern Recognition. It provides readers with the state-of-the-art algorithms in the area of pattern recognition as well as a presentation of the cutting edge applications within the field.

This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.

In order to build successful video processing systems, it is important to consider not only traditional image processing methods, but also techniques which account for temporal aspects like object motion and changes in lighting.

This "Introduction to Video and Image Processing" presents the fundamental concepts and methods in an unique, easy-to-read style which ensures the material is accessible to a wide audience. Exploring more than just the basics of image processing, the text provides a specific focus on the practical design and implementation of real systems for processing video data.

Topics and features: includes more than 100 exercises, as well as C-code snippets of the key algorithms; equips the reader with a solid foundation for understanding and working with images and video, including basic methods for image manipulation and image analysis; covers topics on image acquisition, color images, point processing, neighborhood processing, morphology, BLOB analysis, segmentation in video, tracking, geometric transformation, and visual effects; requires only a minimal understanding of mathematics, with the necessary basics covered in an appendix; presents two chapters dedicated to applications, in which the different methods are applied in real systems, supported by further application examples at an associated website; concludes each chapter with pointers to additional concepts, methods and details not covered in the book; provides a guide to defining suitable values for parameters in video and image processing systems, and to conversion between the RGB color representation and the HIS, HSV and YUV/YC"b"C"r" color representations.

This concise and easy-to-follow textbook/reference is an ideal introduction to the subject for both first-year engineering students and for non-engineering students without a strong mathematical background. Suitable for self-study, professionals outside of the field will also find the work an excellent overview of the basics.

This book presents recent developments in automatic text analysis. Providing an overview of linguistic modeling, it collects contributions of authors from a multidisciplinary area that focus on the topic of automatic text analysis from different perspectives. It includes chapters on cognitive modeling and visual systems modeling, and contributes to the computational linguistic and information theoretical grounding of automatic text analysis.

Correcting the Great Mistake People often mistake one thing for another. That's human nature. However, one would expect the leaders in a particular ?eld of endeavour to have superior ab- ities to discriminate among the developments within that ?eld. That is why it is so perplexing that the technology elite - supposedly savvy folk such as software developers, marketers and businessmen - have continually mistaken Web-based graphics for something it is not. The ?rst great graphics technology for the Web, VRML, has been mistaken for something else since its inception. Viewed variously as a game system, a format for architectural walkthroughs, a platform for multi-user chat and an augmentation of reality, VRML may qualify as the least understood invention in the history of inf- mation technology. Perhaps it is so because when VRML was originally introduced it was touted as a tool for putting the shopping malls of the world online, at once prosaic and horrifyingly mundane to those of us who were developing it. Perhaps those ?rst two initials,"VR,"created expectations of sprawling, photorealistic f- tasy landscapes for exploration and play across the Web. Or perhaps the magnitude of the invention was simply too great to be understood at the time by the many, ironically even by those spending the money to underwrite its development. Regardless of the reasons, VRML suffered in the mainstream as it was twisted to meet unintended ends and stretched far beyond its limitations.

Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it?

The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities.

The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems.

This book presents the thoroughly revised versions of lectures given by leading researchers during the Workshop on Advanced 3D Imaging for Safety and Security in conjunction with the International Conference on Computer Vision and Pattern Recognition CVPR 2005, held in San Diego, CA, USA in June 2005. It covers the current state of the art in 3D imaging for safety and security.

These two volumes, LNCS 7076 and LNCS 7077, constitute the refereed proceedings of the Second International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011, held in Visakhapatnam, India, in December 2011. The 124 revised full papers presented in both volumes were carefully reviewed and selected from 422 submissions. The papers explore new application areas, feature new bio-inspired algorithms for solving specific hard optimization problems, and review the latest progresses in the cutting-edge research with swarm, evolutionary, and memetic computing in both theoretical and practical aspects.

The first edition was released in 1996 and has sold close to 2200 copies.

Provides an up-to-date comprehensive treatment of MDS, a statistical technique used to analyze the structure of similarity or dissimilarity data in multidimensional space.

The authors have added three chapters and exercise sets. The text is being moved from SSS to SSPP.

The book is suitable for courses in statistics for the social or managerial sciences as well as for advanced courses on MDS.

All the mathematics required for more advanced topics is developed systematically in the text.

This book constitutes thoroughly refereed revised selected papers from the First IAPR TC3 Workshop on Partially Supervised Learning, PSL 2011, held in Ulm, Germany, in September 2011. The 14 papers presented in this volume were carefully reviewed and selected for inclusion in the book, which also includes 3 invited talks. PSL 2011 dealt with methodological issues as well as real-world applications of PSL. The main methodological issues were: combination of supervised and unsupervised learning; diffusion learning; semi-supervised classification, regression, and clustering; learning with deep architectures; active learning; PSL with vague, fuzzy, or uncertain teaching signals; learning, or statistical pattern recognition; and PSL in cognitive systems. Applications of PSL included: image and signal processing; multi-modal information processing; sensor/information fusion; human computer interaction; data mining and Web mining; forensic anthropology; and bioinformatics.