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.

This book presents current progress on challenges related to Big Data management by focusing on the particular challenges associated with context-aware data-intensive applications and services. The book is a state-of-the-art reference discussing progress made, as well as prompting future directions on the theories, practices, standards and strategies that are related to the emerging computational technologies and their association with supporting the Internet of Things advanced functioning for organizational settings including both business and e-science. Apart from inter-operable and inter-cooperative aspects, the book deals with a notable opportunity namely, the current trend in which a collectively shared and generated content is emerged from Internet end-users. Specifically, the book presents advances on managing and exploiting the vast size of data generated from within the smart environment (i.e. smart cities) towards an integrated, collective intelligence approach. The book also presents methods and practices to improve large storage infrastructures in response to increasing demands of the data intensive applications. The book contains 19 self-contained chapters that were very carefully selected based on peer review by at least two expert and independent reviewers and is organized into the three sections reflecting the general themes of interest to the IoT and Big Data communities: Section I: Foundations and Principles Section II: Advanced Models and Architectures Section III: Advanced Applications and Future Trends The book is intended for researchers interested in joining interdisciplinary and transdisciplinary works in the areas of Smart Environments, Internet of Things and various computational technologies for the purpose of an integrated collective computational intelligence approach into the Big Data era.  

With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as “Uncertain�. This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Selection (IFS). The book shows the use of state-of-the-art classification techniques, Random Forests and Support Vector Machines to validate the acquired results. It is concluded that a vast majority of these galaxies are, in fact, of spiral morphology with a small subset potentially consisting of stars, elliptical galaxies or galaxies of other morphological variants.

This book is a selection of results obtained within three years of research performed under SYNAT—a nation-wide scientific project aiming at creating an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland. The book is intended to be the last of the series related to the SYNAT project. The previous books, titled “Intelligent Tools for Building a Scientific Information Platform� and “Intelligent Tools for Building a Scientific Information Platform: Advanced Architectures and Solutions�, were published as volumes 390 and 467 in Springer's Studies in Computational Intelligence. Its contents is based on the SYNAT 2013 Workshop held in Warsaw. The papers included in this volume present an overview and insight into information retrieval, repository systems, text processing, ontology-based systems, text mining, multimedia data processing and advanced software engineering, addressing the problems of implementing intelligent tools for building a scientific information platform.

This book focuses on the use of farm level, micro- and macro-data of cooperative systems and networks in developing new robust, reliable and coherent modeling tools for agricultural and environmental policy analysis. The efficacy of public intervention on agriculture is largely determined by the existence of reliable information on the effects of policy options and market developments on farmers' production decisions and in particular, on key issues such as levels of agricultural and non-agricultural output, land use and incomes, use of natural resources, sustainable-centric management, structural change and the viability of family farms. Over the last years, several methods and analytical tools have been developed for policy analysis using various sets of data. Such methods have been based on integrated approaches in an effort to investigate the above key issues and have thus attempted to offer a powerful environment for decision making, particularly in an era of radical change for both agriculture and the wider economy.

The book you hold in your hands is the outcome of the "ISCS 2013: Interdisciplinary Symposium on Complex Systems" held at the historical capital of Bohemia as a continuation of our series of symposia in the science of complex systems. Prague, one of the most beautiful European cities, has its own beautiful genius loci. Here, a great number of important discoveries were made and many important scientists spent fruitful and creative years to leave unforgettable traces. The perhaps most significant period was the time of Rudolf II who was a great supporter of the art and the science and attracted a great number of prominent minds to Prague. This trend would continue. Tycho Brahe, Niels Henrik Abel, Johannes Kepler, Bernard Bolzano, August Cauchy Christian Doppler, Ernst Mach, Albert Einstein and many others followed developing fundamental mathematical and physical theories or expanding them. Thus in the beginning of the 17th century, Kepler formulated here the first two of his three laws of planetary motion on the basis of Tycho Brahe’s observations. In the 19th century, nowhere differentiable continuous functions (of a fractal character) were constructed here by Bolzano along with a treatise on infinite sets, titled “Paradoxes of Infinity� (1851). Weierstrass would later publish a similar function in 1872. In 1842, Doppler as a professor of mathematics at the Technical University of Prague here first lectured about a physical effect to bear his name later. And the epoch-making physicist Albert Einstein – while being a chaired professor of theoretical physics at the German University of Prague – arrived at the decisive steps of his later finished theory of general relativity during the years 1911–1912. In Prague, also many famous philosophers and writers accomplished their works; for instance, playwright arel ape coined the word "robot" in Prague (“robot� comes from the Czech word “robota� which means “forced labor�).

The present book includes a set of selected papers from the tenth “International Conference on Informatics in Control Automation and Robotics� (ICINCO 2013), held in Reykjavík, Iceland, from 29 to 31 July 2013. The conference was organized in four simultaneous tracks: “Intelligent Control Systems and Optimization�, “Robotics and Automation�, “Signal Processing, Sensors, Systems Modeling and Control� and “Industrial Engineering, Production and Management�. The book is based on the same structure. ICINCO 2013 received 255 paper submissions from 50 countries, in all continents. After a double blind paper review performed by the Program Committee only 30% were published and presented orally. A further refinement was made after the conference, based also on the assessment of presentation quality, so that this book includes the extended and revised versions of the very best papers of ICINCO 2013.

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation and operators like crossover, mutation, etc, can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.

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.

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

Modern information and communication technologies, together with a cultural upheaval within the research community, have profoundly changed research in nearly every aspect. Ranging from sharing and discussing ideas in social networks for scientists to new collaborative environments and novel publication formats, knowledge creation and dissemination as we know it is experiencing a vigorous shift towards increased transparency, collaboration and accessibility. Many assume that research workflows will change more in the next 20 years than they have in the last 200. This book provides researchers, decision makers, and other scientific stakeholders with a snapshot of the basics, the tools, and the underlying visions that drive the current scientific (r)evolution, often called ‘Open Science.’

This book presents the latest scientific research related to the field of Robotics. It involves different topics such as biomedicine, energy efficiency and home automation and robotics. The book is written by technical experts and researchers from academia and industry working on robotics applications. The book could be used as supplementary material for courses related to Robotics and Domotics.

This book presents the state of the art in reinforcement learning applied to robotics both in terms of novel algorithms and applications. It discusses recent approaches that allow robots to learn motor. skills and presents tasks that need to take into account the dynamic behavior of the robot and its environment, where a kinematic movement plan is not sufficient. The book illustrates a method that learns to generalize parameterized motor plans which is obtained by imitation or reinforcement learning, by adapting a small set of global parameters and appropriate kernel-based reinforcement learning algorithms. The presented applications explore highly dynamic tasks and exhibit a very efficient learning process. All proposed approaches have been extensively validated with benchmarks tasks, in simulation and on real robots. These tasks correspond to sports and games but the presented techniques are also applicable to more mundane household tasks. The book is based on the first author’s doctoral thesis, which won the 2013 EURON Georges Giralt PhD Award.

The book compiles technologies for enhancing and provisioning security, privacy and trust in cloud systems based on Quality of Service requirements. It is a timely contribution to a field that is gaining considerable research interest, momentum, and provides a comprehensive coverage of technologies related to cloud security, privacy and trust. In particular, the book includes - Cloud security fundamentals and related technologies to-date, with a comprehensive coverage of evolution, current landscape, and future roadmap. - A smooth organization with introductory, advanced and specialist content, i.e. from basics of security, privacy and trust in cloud systems, to advanced cartographic techniques, case studies covering both social and technological aspects, and advanced platforms. - Case studies written by professionals and/or industrial researchers. - Inclusion of a section on Cloud security and eGovernance tutorial that can be used for knowledge transfer and teaching purpose. - Identification of open research issues to help practitioners and researchers. The book is a timely topic for readers, including practicing engineers and academics, in the domains related to the engineering, science, and art of building networks and networked applications. Specifically, upon reading this book, audiences will perceive the following benefits: 1. Learn the state-of-the-art in research and development on cloud security, privacy and trust. 2. Obtain a future roadmap by learning open research issues. 3. Gather the background knowledge to tackle key problems, whose solutions will enhance the evolution of next-generation secure cloud systems.

The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer. Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years, dermoscopy has proved valuable in visualizing the morphological structures in pigmented lesions. However, it has also been shown that dermoscopy is difficult to learn and subjective. Newer technologies such as infrared imaging, multispectral imaging, and confocal microscopy, have recently come to the forefront in providing greater diagnostic accuracy. These imaging technologies presented in this book can serve as an adjunct to physicians and  provide automated skin cancer screening. Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.

This book carries forward recent work on visual patterns and structures in digital images and introduces a near set-based a topology of digital images. Visual patterns arise naturally in digital images viewed as sets of non-abstract points endowed with some form of proximity (nearness) relation. Proximity relations make it possible to construct uniform topologies on the sets of points that constitute a digital image. In keeping with an interest in gaining an understanding of digital images themselves as a rich source of patterns, this book introduces the basics of digital images from a computer vision perspective. In parallel with a computer vision perspective on digital images, this book also introduces the basics of proximity spaces. Not only the traditional view of spatial proximity relations but also the more recent descriptive proximity relations are considered. The beauty of the descriptive proximity approach is that it is possible to discover visual set patterns among sets that are non-overlapping and non-adjacent spatially. By combining the spatial proximity and descriptive proximity approaches, the search for salient visual patterns in digital images is enriched, deepened and broadened. A generous provision of Matlab and Mathematica scripts are used in this book to lay bare the fabric and essential features of digital images for those who are interested in finding visual patterns in images. The combination of computer vision techniques and topological methods lead to a deep understanding of images.

  Humanoid robotics have made remarkable progress since the dawn of robotics. So why don't we have humanoid robot assistants in day-to-day life yet? This book analyzes the keys to building a successful humanoid robot for field robotics, where collisions become an unavoidable part of the game. The author argues that the design goal should be real anthropomorphism, as opposed to mere human-like appearance. He deduces three major characteristics to aim for when designing a humanoid robot, particularly robot hands: - Robustness against impacts - Fast dynamics - Human-like grasping and manipulation performance Instead of blindly copying human anatomy, this book opts for a holistic design methodology. It analyzes human hands and existing robot hands to elucidate the important functionalities that are the building blocks toward these necessary characteristics. They are the keys to designing an anthropomorphic robot hand, as illustrated in the high performance anthropomorphic Awiwi Hand presented in this book. This is not only a handbook for robot hand designers. It gives a comprehensive survey and analysis of the state of the art in robot hands as well as the human anatomy. It is also aimed at researchers and roboticists interested in the underlying functionalities of hands, grasping and manipulation. The methodology of functional abstraction is not limited to robot hands, it can also help realize a new generation of humanoid robots to accommodate a broader spectrum of the needs of human society.

As cities are rapidly expanding and encroaching into agricultural and natural areas, a question of primary concern is how this expansion affects surrounding agriculture and natural landscapes. This book presents a wide spectrum of both theoretical and empirical approaches to simulation and assessment of landscape dynamics. The first part presents state-of-the-art modelling approaches pertaining to land-use changes entailed by the urban sprawl, at different spatial resolutions and temporal time scales. The second part is dedicated to case studies of the effects and consequences of the emerging urban-agriculture open space patterns.

This book describes analytical models and estimation methods to enhance performance estimation of pipelined multiprocessor systems-on-chip (MPSoCs). A framework is introduced for both design-time and run-time optimizations. For design space exploration, several algorithms are presented to minimize the area footprint of a pipelined MPSoC under a latency or a throughput constraint. A novel adaptive pipelined MPSoC architecture is described, where idle processors are transitioned into low-power states at run-time to reduce energy consumption. Multi-mode pipelined MPSoCs are introduced, where multiple pipelined MPSoCs optimized separately are merged into a single pipelined MPSoC, enabling further reduction of the area footprint by sharing the processors and communication buffers. Readers will benefit from the authors’ combined use of analytical models, estimation methods and exploration algorithms and will be enabled to explore billions of design points in a few minutes.

Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.

Intelligent Decision-Making Support Systems (i-DMSS) are specialized IT-based systems that support some or several phases of the individual, team, organizational or inter-organizational decision making process by deploying some or several intelligent mechanisms. This book pursues the following academic aims: (i) generate a compendium of quality theoretical and applied contributions in Intelligent Decision-Making Support Systems (i-DMSS) for engineering and management IT-based service systems (ITSS); (ii)  diffuse scarce knowledge about foundations, architectures and effective and efficient methods and strategies for successfully planning, designing, building, operating, and evaluating i-DMSS for ITSS, and (iii) create an awareness of, and a bridge between ITSS and i-DMSS academicians and practitioners in the current complex and dynamic engineering and management ITSS organizational. The book presents a collection of 11 chapters referring to relevant topics for both IT service systems and i-DMSS including: problems of selection of IT service providers, optimization of supply chain systems, IT governance decisions, clinical decision support, dynamic user-interface adaptation, re-engineering of processes, and generic decision problems. Advanced IT technologies used in some chapters are:  fuzzy multi-criteria mechanisms, semantic processing, data mining processing, and rough sets. Other chapters report traditional DSS mechanisms but used or suggested to be used in innovative mode for IT service engineering and management tasks.

This book introduces a novel transcoding algorithm for real time video applications, designed to overcome inter-operability problems between MPEG-2 to H.264/AVC. The new algorithm achieves 92.8% reduction in the transcoding run time at a price of an acceptable Peak Signal-to-Noise Ratio (PSNR) degradation, enabling readers to use it for real time video applications. The algorithm described is evaluated through simulation and experimental results. In addition, the authors present a hardware implementation of the new algorithm using Field Programmable Gate Array (FPGA) and Application-specific standard products (ASIC). • Describes a novel transcoding algorithm for real time video applications, designed to overcome inter-operability problems between H.264/AVC to MPEG-2; • Implements algorithm presented using Field Programmable Gate Array (FPGA) and Application-specific Integrated Circuit (ASIC); • Demonstrates the solution to real problems, with verification through simulation and experimental results.

This edited collection will provide an overview of the field of physiological computing, i.e. the use of physiological signals as input for computer control. It will cover a breadth of current research, from brain-computer interfaces to telemedicine.

This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.

This book analyzes the philosophical foundations of sensorimotor theory and discusses the most recent applications of sensorimotor theory to human computer interaction, child’s play, virtual reality, robotics, and linguistics. Why does a circle look curved and not angular? Why does red not sound like a bell? Why, as I interact with the world, is there something it is like to be me? An analytic philosopher might suggest: ``if we ponder the concept of circle we find that it is the essence of a circle to be round’’. However, where does this definition come from? Was it set in stone by the Gods, in other words by divine arbiters of circleness, redness and consciousness? Particularly, with regard to visual consciousness, a first attempt to explain why our conscious experience of the world appears as it does has been attributed to Kevin O’Regan and Alva Noe, who published their sensorimotor account of vision and visual consciousness in 2001. Starting with a chapter by Kevin O’Regan, Contemporary Sensorimotor Theory continues by presenting fifteen additional essays on as many developments achieved in recent years in this field. It provides readers with a critical review of the sensorimotor theory and in so doing introduces them to a radically new enactive approach in cognitive science.