The monograph written by John Mullane, Ba-Ngu Vo, Martin Adams and Ba-Tuong Vo is devoted to the field of autonomous robot systems, which have been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the problem of representing the environment and its uncertainty in terms of feature based maps. Random Finite Sets are adopted as the fundamental tool to represent a map, and a general framework is proposed for feature management, data association and state estimation. The approaches are tested in a number of experiments on both ground based and marine based facilities.

This book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book's primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the "spin-net," as a dynamic form of auto-associative memory.

This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.

This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques.

This book provides a general overview of multiple instance learning (MIL), defining the framework and covering the central paradigms. The authors discuss the most important algorithms for MIL such as classification, regression and clustering. With a focus on classification, a taxonomy is set and the most relevant proposals are specified. Efficient algorithms are developed to discover relevant information when working with uncertainty. Key representative applications are included. This book carries out a study of the key related fields of distance metrics and alternative hypothesis. Chapters examine new and developing aspects of MIL such as data reduction for multi-instance problems and imbalanced MIL data. Class imbalance for multi-instance problems is defined at the bag level, a type of representation that utilizes ambiguity due to the fact that bag labels are available, but the labels of the individual instances are not defined. Additionally, multiple instance multiple label learning is explored. This learning framework introduces flexibility and ambiguity in the object representation providing a natural formulation for representing complicated objects. Thus, an object is represented by a bag of instances and is allowed to have associated multiple class labels simultaneously. This book is suitable for developers and engineers working to apply MIL techniques to solve a variety of real-world problems. It is also useful for researchers or students seeking a thorough overview of MIL literature, methods, and tools.

The focus of this book is on three influential cognitive motives: achievement, affiliation, and power motivation. Incentive-based theories of achievement, affiliation and power motivation are the basis for competence-seeking behaviour, relationship-building, leadership, and resource-controlling behaviour in humans. In this book we show how these motives can be modelled and embedded in artificial agents to achieve behavioural diversity. Theoretical issues are addressed for representing and embedding computational models of motivation in rule-based agents, learning agents, crowds and evolution of motivated agents. Practical issues are addressed for defining games, mini-games or in-game scenarios for virtual worlds in which computer-controlled, motivated agents can participate alongside human players. The book is structured into four parts: game playing in virtual worlds by humans and agents; comparing human and artificial motives; game scenarios for motivated agents; and evolution and the future of motivated game-playing agents. It will provide game programmers, and those with an interest in artificial intelligence, with the knowledge required to develop diverse, believable game-playing agents for virtual worlds.

This book focuses on the development of a theory of info-dynamics to support the theory of info-statics in the general theory of information. It establishes the rational foundations of information dynamics and how these foundations relate to the general socio-natural dynamics from the primary to the derived categories in the universal existence and from the potential to the actual in the ontological space. It also shows how these foundations relate to the general socio-natural dynamics from the potential to the possible to give rise to the possibility space with possibilistic thinking; from the possible to the probable to give rise to possibility space with probabilistic thinking; and from the probable to the actual to give rise to the space of knowledge with paradigms of thought in the epistemological space. The theory is developed to explain the general dynamics through various transformations in quality-quantity space in relation to the nature of information flows at each variety transformation. The theory explains the past-present-future connectivity of the evolving information structure in a manner that illuminates the transformation problem and its solution in the never-ending information production within matter-energy space under socio-natural technologies to connect the theory of info-statics, which in turn presents explanations to the transformation problem and its solution. The theoretical framework is developed with analytical tools based on the principle of opposites, systems of actual-potential polarities, negative-positive dualities under different time-structures with the use of category theory, fuzzy paradigm of thought and game theory in the fuzzy-stochastic cost-benefit space. The rational foundations are enhanced with categorial analytics. The value of the theory of info-dynamics is demonstrated in the explanatory and prescriptive structures of the transformations of varieties and categorial varieties at each point of time and over time from parent-offspring sequences. It constitutes a general explanation of dynamics of information-knowledge production through info-processes and info-processors induced by a socio-natural infinite set of technologies in the construction-destruction space.

Rapid growth of the mobile communication market has triggered extensive research on the bulk as well as surface acoustic wave devices in the last decade. Quite a few important results on the modeling and simulation of Film Bulk Acoustic Resonator (FBAR) and Layered SAW devices were reported recently. The other recent advance of acoustic waves in solids is the so-called phononic crystals or phononic band-gap materials. Analogous to the band-gap of light in photonic crystals, acoustic waves in periodic elastic structures also exhibit band-gap. Important applications of phononic band gap materials can potentially be found with creating a vibration free environment in microstructures, and design of advanced acoustic frequency filter, etc. In addition to the wave electronics and phononic crystals, to facilitate the emerging needs in the quantitative nondestructive evaluation of materials, waves in anisotropic solids and/or electro-, magneto- interaction problems also regained much attention recently. Topics treated include: Waves in piezoelectric crystals; Simulation of advanced BAW and SAW devices; Analysis of band gaps in phononic structures; Experimental investigation of phononic structures; Waves in multilayered media;Waves in anisotropic solids and/or electro-, magneto- interaction problems.

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.

Computer Vision and Pattern Recognition (CVPR) together play an important role in the processes involved in environmental informatics due to their pervasive, non-destructive, effective, and efficient natures. As a result, CVPR has made significant contributions to the field of environmental informatics by enabling multi-modal data fusion and feature extraction, supporting fast and reliable object detection and classification, and mining the intrinsic relationship between different aspects of environmental data. Computer Vision and Pattern Recognition in Environmental Informatics describes a number of methods and tools for image interpretation and analysis, which enables observation, modelling, and understanding of environmental targets. In addition to case studies on monitoring and modeling plant, soil, insect, and aquatic animals, this publication includes discussions on innovative new ideas related to environmental monitoring, automatic fish segmentation and recognition, real-time motion tracking systems, sparse coding and decision fusion, and cell phone image-based classification and provides useful references for professionals, researchers, engineers, and students with various backgrounds within a multitude of communities.

Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC'15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.

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.

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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Artificial Intelligence (AI) is penetrating in all sciences as a multidisciplinary approach. However, adopting the theory of AI including computer vision and computer audition to urban intellectual space, is always difficult for architecture and urban planners. This book overcomes this challenge through a conceptual framework by merging computer vision and audition to urban studies based on a series of workshops called Remorph, conducted by Tehran Urban Innovation Center (TUIC).

Dynamic Business Process Formation fuses practical needs with theoretical input to present important research innovations in supporting Instant Virtual Enterprises (IVEs). This new organization type brings a combination of business dynamism and explicit business process structure to domains where on-the-fly formation of well-organized business networks is required to deal with the complexity of new products or services under high time pressure. This book contains the main results of the IST CrossWork project, and, importantly, looks beyond the boundaries of this project and sources input from related projects and general trends in collaborative enterprises and the automotive industry. Both the business and technical aspects of Virtual Enterprise coordination are covered within the modular structure of the book, which enables readers from different backgrounds to benefit from the book according to their interests.

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.

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.

This book presents the development of a theory of social goal-objective formation and its relationship to national interest and social vision under a democratic decision-choice system with imperfect information structure. It provides a framework for the application of fuzzy logic and its mathematics to the analysis in resolving conflicts in individual preferences in the collective decision-choice space without violence. The book demonstrates how to use fuzzy logic and its mathematics in the study of economics, social sciences and other complex systems. It also presents the use of collaborative tools of opposites, duality, polarity, continuum in fuzzy paradigm with its logic, laws of thought and mathematics in developing a new approach to the theory of political economy in order to enhance the constructs of social decision-choice theory.

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 contains the full papers presented at the MICCAI 2013 workshop Computational Methods and Clinical Applications for Spine Imaging. The workshop brought together researchers representing several fields, such as Biomechanics, Engineering, Medicine, Mathematics, Physics and Statistic. The works included in this book present and discuss new trends in those fields, using several methods and techniques in order to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modelling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis.