The overwhelming pace of evolution in technology has made it possible to develop intelligent systems which help users in their dayly life activities. - cordingly, methods of recording, managing and analysing data have evolved from the very simple ?le systems into complex ambient supportive intelligent systems. This book arises as a compilation of methods, techniques and tools c- nected with data related issues: from modelling to analysis. A broad range of approaches such as database self-* techniques for ubiquitous environments, multimedia data, or data driven models will be reviewed. Di?erent areas of applications, in which data models conceptualize nowadays reality, starting from e-learning to electric transformers will be considered. The book is a collection of representative contributions to cover the sp- trum related to data bases, which support decision making and data mining methods as well as conceptualization. Datawarehouse technology and m- eling are presented in the ?rst chapter together with the deep review of datawarehouse techniques for supporting e-learning processes with special emphasis on data cubes, all the tools are considered in the context of imp- mentationofsoftwareapplication.Thesecondchaptercontinueswiththes- ilar technology and deals with the community data warehouse architecture.

This research monograph presents selected areas of applications in the field of control systems engineering using computational intelligence methodologies. A number of applications and case studies are introduced. These methodologies are increasing used in many applications of our daily lives. Approaches include, fuzzy-neural multi model for decentralized identification, model predictive control based on time dependent recurrent neural network development of cognitive systems, developments in the field of Intelligent Multiple Models based Adaptive Switching Control, designing military training simulators using modelling, simulation, and analysis for operational analyses and training, methods for modelling of systems based on the application of Gaussian processes, computational intelligence techniques for process control and image segmentation technique based on modified particle swarm optimized-fuzzy entropy.

This book deals with the issues of modelling management processes of information technology and IT projects while its core is the model of information technology management and its component models (contextual, local) describing initial processing and the maturity capsule as well as a decision-making system represented by a multi-level sequential model of IT technology selection, which acquires a fuzzy rule-based implementation in this work.

In terms of applicability, this work may also be useful for diagnosing applicability of IT standards in evaluation of IT organizations. The results of this diagnosis might prove valid for those preparing new standards so that apart from their own visions they could, to an even greater extent, take into account the capabilities and needs of the leaders of project and manufacturing teams.

The book is intended for IT professionals using the ITIL, COBIT and TOGAF standards in their work. Students of computer science and management who are interested in the issue of IT project and technology management are also likely to benefit from this study. For young students of IT, it can serve as a source of knowledge in the field of information technology evaluation. This book is also designed for specialists in modelling socio-technical systems.

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This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization - the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution.

Knowledge transfer between universities, business and the community is a topical subject of increasing importance. The first International Conference on 'Innovation through Knowledge Transfer: Research with Impact', InnovationKT'09, held in Kingston, London, UK, provided a rare and welcome opportunity to share some of the successes of knowledge transfer. The conference attracted 150 delegates and featured 42 oral presentations. This volume, representing the proceedings of the conference, contains 35 papers based on selected conference presentations. The papers are divided into seven sections entitled 'Key Knowledge Transfer Perspectives', 'Knowledge Transfer Case Studies', 'Innovative Knowledge Transfer Techniques', 'Strategic and Organisational Approaches to Knowledge Transfer', 'Knowledge transfer in the Arts and the Community', 'Knowledge Transfer Methodology and Practice' and 'Innovation and Enterprise'. The first InnovationKT conference was unique in gathering such a tremendous range of knowledge transfer experience and expertise. This volume forms a valuable resource for all those who are involved in knowledge transfer, or wish to know more about it. University academics can read examples of ways in which research can be commercialised, increasing impact and improving relevance. Knowledge transfer practitioners can find out about best practice in their subject and read case studies. Companies can read about how universities can help find solutions to their problems. We recommend this volume as a statement of the benefits that knowledge transfer can bring to all those involved.

The present volume is a compilation of research work in computation, communication, vision sciences, device design, fabrication, upcoming materials and related process design, etc. It is derived out of selected manuscripts submitted to the 2014 National Workshop on Advances in Communication and Computing (WACC 2014), Assam Engineering College, Guwahati, Assam, India which is emerging out to be a premier platform for discussion and dissemination of knowhow in this part of the world. The papers included in the volume are indicative of the recent thrust in computation, communications and emerging technologies. Certain recent advances in ZnO nanostructures for alternate energy generation provide emerging insights into an area that has promises for the energy sector including conservation and green technology. Similarly, scholarly contributions have focused on malware detection and related issues. Several contributions have focused on biomedical aspects including contributions related to cancer detection using active learning, application of clinical information in MECG using sample and channel convolution matrices for better diagnostic decision, etc. Some other works have focused on the DCT-domain linear regression of ECG signals, SVD Analysis on reduced 3-lead ECG data, the quantification of diagnostic information on ECG signal, a compressed sensing approach with application in MRI, learning aided image de-noising for medical applications, etc. Some works have dealt with application of audio fingerprinting for multi-lingual Indian song retrieval, semi-automatic approach to segmentation and the marking of pitch contours for prosodic analysis, semiautomatic syllable labeling for Assamese language, stressed speech recognition, handwriting recognition in Assamese script, speaker verification considering the effect of session variability and the block matching for motion estimation, etc. The primary objective of the present volume is to prepare a document for dissemination of and discussion on emerging areas of research in computation and communication as aimed by WACC 2014. We hope that the volume will serve as a reference book for researchers in these areas.

Design of cognitive systems for assistance to people poses a major challenge to the fields of robotics and artificial intelligence. The Cognitive Systems for Cognitive Assistance (CoSy) project was organized to address the issues of i) theoretical progress on design of cognitive systems ii) methods for implementation of systems and iii) empirical studies to further understand the use and interaction with such systems. To study, design and deploy cognitive systems there is a need to considers aspects of systems design, embodiment, perception, planning and error recovery, spatial insertion, knowledge acquisition and machine learning, dialog design and human robot interaction and systems integration. The CoSy project addressed all of these aspects over a period of four years and across two different domains of application - exploration of space and task / knowledge acquisition for manipulation. The present volume documents the results of the CoSy project. The CoSy project was funded by the European Commission as part of the Cognitive Systems Program within the 6th Framework Program.

This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive and context-aware Information Communication Technologies.

Pervasive computing enables users to interact with information resources in their everyday lives. The development of computational technologies that can exist in ever smaller devices while simultaneously increasing processing power allows such devices to blend seamlessly into tangible environments. Intelligent Technologies and Techniques for Pervasive Computing provides an extensive discussion of such technologies, theories and practices in an attempt to shed light on current trends and issues in the adaption of pervasive systems. Within its pages, students and practitioners of computer science will find both recent developments and practical applications an overview of the field and how intelligent techniques can help to improve user experience in the distribution and consumption of pertinent, timely information. This book is part of the Advances in Computational Intelligence and Robotics series collection.

This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being. This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches. We are proud to offer the readers this book.

At first sight, the concept of web personalization looks deceivingly simple. A web personalization system is a software component that collects information on visitors to a web site and leverages this knowledge to deliver them the right content, tailoring presentation to the user's needs. All over the world, web designers and web content managers rely on web personalization solutions to improve the effectiveness and - ability of their web-based applications. Still, the scientific foundation of web personalization remains a controversial issue. Practitioners know very well that when properly implemented, personalization del- ers a much better user experience; but when it is poorly implemented, personalization may backfire and even distract the user's attention away from some useful (and co- ly-to-develop) enriched content. In other words, tailoring content, and varying it routinely, may make a site more attractive; but an unstable site look can have a negative impact on the overall m- sage. Everybody seems to agree that this is a real danger; but there are specific qu- tions that are much harder to answer convincingly.

The purpose of the 12th Conference Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2011) held on July 6-8, 2011 in Sydney, Australia was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas and research results about all aspects (theory, applications and tools) of computer and information sciences, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

The conference organizers selected 14 outstanding papers from SNPD 2011, all of which you will find in this volume of Springer's Studies in Computational Intelligence. "

This research book presents a sample of recent advances in information hiding techniques and their applications. It includes:

Image data hiding scheme based on vector quantization and image graph coloring

The copyright protection system for Android platform

Reversible data hiding

ICA-based image and video watermarking

Content-based invariant image watermarking

Single bitmap block truncation coding of color images using cat swarm optimization

Genetic-based wavelet packet watermarking for copyright protection

Lossless text steganography in compression coding

Fast and low-distortion capacity acoustic synchronized acoustic-to-acoustic steganography scheme

Video watermarking with shot detection. "

This book introduces state-of-the-art research on simulation and serious games for education. Based partially on work presented at the 3rd Asia-Europe Symposium on Simulation and Serious Games (3rd AESSSG) held in Zhuhai, China as part of the 2016 ACM SIGGRAPH International Conference on Virtual-Reality Consortium and Applications in Industry (VRACI 2016), it includes a selection of the best papers from both. The book is divided into three major domains of education applications that use simulation and serious games: science, technology, engineering and mathematics (STEM) education; special needs education; and humanity and social science education. A valuable resource for researchers and developers in simulation and serious games for education benefit from this book, it also offers educators and professionals involved in training insights into the possible applications of simulation and serious games in various areas.

As the amount of accumulated data across a variety of fields becomes harder to maintain, it is essential for a new generation of computational theories and tools to assist humans in extracting knowledge from this rapidly growing digital data. Global Trends in Intelligent Computing Research and Development brings together recent advances and in depth knowledge in the fields of knowledge representation and computational intelligence. Highlighting the theoretical advances and their applications to real life problems, this book is an essential tool for researchers, lecturers, professors, students, and developers who have seek insight into knowledge representation and real life applications.

This book is a part of the Proceedings of the Seventh International Symposium on Neural Networks (ISNN 2010), held on June 6-9, 2010 in Shanghai, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural networks and related fields, with a successful sequence of ISNN series in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), Beijing (2008), and Wuhan (2009). Following the tradition of ISNN series, ISNN 2010 provided a high-level international forum for scientists, engineers, and educators to present the state-of-the-art research in neural networks and related fields, and also discuss the major opportunities and challenges of future neural network research. Over the past decades, the neural network community has witnessed significant breakthroughs and developments from all aspects of neural network research, including theoretical foundations, architectures, and network organizations, modeling and simulation, empirical studies, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, has provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large scale, and networked brain-like intelligent systems. This long-term goals can only be achieved with the continuous efforts from the community to seriously investigate various issues on neural networks and related topics.

This "Third Edition" provides the latest tools and techniques that enable computers to learn

The "Third Edition" of this internationally acclaimed publication provides the latest theory and techniques for using simulated evolution to achieve machine intelligence. As a leading advocate for evolutionary computation, the author has successfully challenged the traditional notion of artificial intelligence, which essentially programs human knowledge fact by fact, but does not have the capacity to learn or adapt as evolutionary computation does.

Readers gain an understanding of the history of evolutionary computation, which provides a foundation for the author's thorough presentation of the latest theories shaping current research. Balancing theory with practice, the author provides readers with the skills they need to apply evolutionary algorithms that can solve many of today's intransigent problems by adapting to new challenges and learning from experience. Several examples are provided that demonstrate how these evolutionary algorithms learn to solve problems. In particular, the author provides a detailed example of how an algorithm is used to evolve strategies for playing chess and checkers.

As readers progress through the publication, they gain an increasing appreciation and understanding of the relationship between learning and intelligence. Readers familiar with the previous editions will discover much new and revised material that brings the publication thoroughly up to date with the latest research, including the latest theories and empirical properties of evolutionary computation.

The "Third Edition" also features new knowledge-building aids. Readers will find a hostof new and revised examples. New questions at the end of each chapter enable readers to test their knowledge. Intriguing assignments that prepare readers to manage challenges in industry and research have been added to the end of each chapter as well.

This is a must-have reference for professionals in computer and electrical engineering; it provides them with the very latest techniques and applications in machine intelligence. With its question sets and assignments, the publication is also recommended as a graduate-level textbook.

This book offers a novel perspective on abduction. It starts by discussing the major theories of abduction, focusing on the hybrid nature of abduction as both inference and intuition. It reports on the Peircean theory of abduction and discusses the more recent Magnani concept of animal abduction, connecting them to the work of medieval philosophers. Building on Magnani's manipulative abduction, the accompanying classification of abduction, and the hybrid concept of abduction as both inference and intuition, the book examines the problem of visual perception together with the related concepts of misrepresentation and semantic information. It presents the author's views on caricature and the caricature model of science, and then extends the scope of discussion by introducing some standard issues in the philosophy of science. By discussing the concept of ad hoc hypothesis generation as enthymeme resolution, it demonstrates how ubiquitous the problem of abduction is in all the different individual scientific disciplines. This comprehensive text provides philosophers, logicians and cognitive scientists with a historical, unified and authoritative perspective on abduction.

This book presents a set of theoretical and experimental results that describe the features of the wide family of -stable distributions (the normal distribution also belongs to this class) and their various applications in the mutation operator of evolutionary algorithms based on real-number representation of the individuals, and, above all, equip these algorithms with features that enrich their effectiveness in solving multi-modal, multi-dimensional global optimization problems. The overall conclusion of the research presented is that the appropriate choice of probabilistic model of the mutation operator for an optimization problem is crucial. Mutation is one of the most important operations in stochastic global optimization algorithms in the n-dimensional real space. It determines the method of search space exploration and exploitation. Most applications of these algorithms employ the normal mutation as a mutation operator. This choice is justified by the central limit theorem but is associated with a set of important limitations. Application of -stable distributions allows more flexible evolutionary models to be obtained than those with the normal distribution. The book presents theoretical analysis and simulation experiments, which were selected and constructed to expose the most important features of the examined mutation techniques based on -stable distributions. It allows readers to develop a deeper understanding of evolutionary processes with stable mutations and encourages them to apply these techniques to real-world engineering problems.

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing.

This book describes recent advances on hybrid intelligent systems using soft computing techniques for diverse areas of application, such as intelligent control and robotics, pattern recognition, time series prediction and optimization complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of type-2 fuzzy logic, which basically consists of papers that propose new models and applications for type-2 fuzzy systems. The second part contains papers with the main theme of bio-inspired optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application. The third part contains papers that deal with new models and applications of neural networks in real world problems. The fourth part contains papers with the theme of intelligent optimization methods, which basically consider the proposal of new methods of optimization to solve complex real world optimization problems. The fifth part contains papers with the theme of evolutionary methods and intelligent computing, which are papers considering soft computing methods for applications related to diverse areas, such as natural language processing, recommending systems and optimization.

What Is BCI2000? BCI2000 is a general-purpose software platform for brain-computer interface (BCI) research. It can also be used for a wide variety of data acquisition, stimulus p- sentation, and brain monitoring applications. BCI2000 has been in development since 2000 in a project led by the Brain-Computer Interface R&D Program at the Wadsworth Center of the New York State Department of Health in Albany, New York, USA, with substantial contributions by the Institute of Medical Psychology and Behavioral Neurobiology at the University of Tubingen, Germany. In addition, many laboratories around the world, most notably the BrainLab at Georgia State University in Atlanta, Georgia, and Fondazione Santa Lucia in Rome, Italy, have also played an important role in the project's development. Mission The mission of the BCI2000 project is to facilitate research and the development of applications in all areas that depend on real-time acquisition, processing, and feedback of biosignals. Vision Our vision is that BCI2000 will become a widely used software tool for diverse areas of research and development.