This contributed volume explores how data mining, machine learning, and similar statistical techniques can analyze the types of problems arising from Traditional Chinese Medicine (TCM) research. The book focuses on the study of clinical data and the analysis of herbal data. Challenges addressed include diagnosis, prescription analysis, ingredient discoveries, network based mechanism deciphering, pattern-activity relationships, and medical informatics. Each author demonstrates how they made use of machine learning, data mining, statistics and other analytic techniques to resolve their research challenges, how successful if these techniques were applied, any insight noted and how these insights define the most appropriate future work to be carried out. Readers are given an opportunity to understand the complexity of diagnosis and treatment decision, the difficulty of modeling of efficacy in terms of herbs, the identification of constituent compounds in an herb, the relationship between these compounds and biological outcome so that evidence-based predictions can be made. Drawing on a wide range of experienced contributors, Data Analytics for Traditional Chinese Medicine Research is a valuable reference for professionals and researchers working in health informatics and data mining. The techniques are also useful for biostatisticians and health practitioners interested in traditional medicine and data analytics.

This book captures the state of the art in cloud technologies, infrastructures, and service delivery and deployment models. The work provides guidance and case studies on the development of cloud-based services and infrastructures from an international selection of expert researchers and practitioners. Features: presents a focus on security and access control mechanisms for cloud environments, analyses standards and brokerage services, and investigates the role of certification for cloud adoption; evaluates cloud ERP, suggests a framework for implementing “big data� science, and proposes an approach for cloud interoperability; reviews existing elasticity management solutions, discusses the relationship between cloud management and governance, and describes the development of a cloud service capability assessment model; examines cloud applications in higher education, including the use of knowledge-as-a-service in the provision of education, and cloud-based e-learning for students with disabilities.

A network is a mathematical object consisting of a set of points that are connected to each other in some fashion by lines. It turns out this simple description corresponds to a bewildering array of systems in the real world, ranging from technological ones such as the Internet and World Wide Web, biological networks such as that of connections of the nervous systems, food webs or  protein interactions, infrastructural systems such as networks of roads, airports or the power-grid, to patterns of social and professional relationships such as friendship, sex partners, network of Hollywood actors, co-authorship networks and many more. Recent years have witnessed a substantial amount of interest within the scientific community in the properties of these networks. The emergence of the internet in particular, coupled with the widespread availability of inexpensive computing resources has facilitated studies ranging from large scale empirical analysis of networks in the real world, to the development of theoretical models and tools to explore the various properties of these systems. The study of networks is broadly interdisciplinary and central developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology and the social sciences. This book brings together a collection of cutting-edge research in the field from a diverse array of researchers ranging from physicists to social scientists and presents them in a coherent fashion, highlighting the strong interconnections between the different areas. Topics included are social networks and social media, opinion and innovation diffusion, biological and health-related networks, language networks, as well as network theory, community detection, or growth models for Complex Networks.

This book reports the latest advances on the design and development of mobile computing systems, describing their applications in the context of modeling, analysis and efficient resource management. It explores the challenges on mobile computing and resource management paradigms, including research efforts and approaches recently carried out in response to them to address future open-ended issues. The book includes 26 rigorously refereed chapters written by leading international researchers, providing the readers with technical and scientific information about various aspects of mobile computing, from basic concepts to advanced findings, reporting the state-of-the-art on resource management in such environments. It is mainly intended as a reference guide for researchers and practitioners involved in the design, development and applications of mobile computing systems, seeking solutions to related issues. It also represents a useful textbook for advanced undergraduate and graduate courses, addressing special topics such as: mobile and ad-hoc wireless networks; peer-to-peer systems for mobile computing; novel resource management techniques in cognitive radio networks; and power management in mobile computing systems.

This book is devoted to the study of the functional architecture of the visual cortex. Its geometrical structure is the differential geometry of the connectivity between neural cells. This connectivity is building and shaping the hidden brain structures underlying visual perception. The story of the problem runs over the last 30 years, since the discovery of Hubel and Wiesel of the modular structure of the primary visual cortex, and slowly cams towards a theoretical understanding of the experimental data on what we now know as functional architecture of the primary visual cortex. Experimental data comes from several domains: neurophysiology, phenomenology of perception and neurocognitive imaging. Imaging techniques like functional MRI and diffusion tensor MRI allow to deepen the study of cortical structures. Due to this variety of experimental data, neuromathematematics deals with modelling both cortical structures and perceptual spaces. From the mathematical point of view, neuromathematical call for new instruments of pure mathematics: sub-Riemannian geometry models horizontal connectivity, harmonic analysis in non commutative groups allows to understand pinwheels structure, as well as non-linear dimensionality reduction is at the base of many neural morphologies and possibly of the emergence of perceptual units. But at the center of the neurogeometry is the problem of harmonizing contemporary mathematical instruments with neurophysiological findings and phenomenological experiments in an unitary science of vision. The contributions to this book come from the very founders of the discipline.

Membrane Computing was introduced as a computational paradigm in Natural Computing. The models introduced, called Membrane (or P) Systems, provide a coherent platform to describe and study living cells as computational systems. Membrane Systems have been investigated for their computational aspects and employed to model problems in other fields, like: Computer Science, Linguistics, Biology, Economy, Computer Graphics, Robotics, etc. Their inherent parallelism, heterogeneity and intrinsic versatility allow them to model a broad range of processes and phenomena, being also an efficient means to solve and analyze problems in a novel way. Membrane Computing has been used to model biological systems, becoming with time a thorough modeling paradigm comparable, in its modeling and predicting capabilities, to more established models in this area. This book is the result of the need to collect, in an organic way, different facets of this paradigm. The chapters of this book, together with the web pages accompanying them, present different applications of Membrane Systems to Biology. Deterministic, non-deterministic and stochastic systems paired with different algorithms and methodologies show the full potential of this framework. The book is addressed to researchers interested in applications of discrete biological models and the interplay between Membrane Systems and other approaches to analyze complex systems.

Computational Intelligence techniques have been widely explored in various domains including forensics. Analysis in forensic encompasses the study of pattern analysis that answer the question of interest in security, medical, legal, genetic studies and etc. However, forensic analysis is usually performed through experiments in lab which is expensive both in cost and time. Therefore, this book seeks to explore the progress and advancement of computational intelligence technique in different focus areas of forensic studies. This aims to build stronger connection between computer scientists and forensic field experts. This book, Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, is the first volume in the Intelligent Systems Reference Library series. The book presents original research results and innovative applications of computational intelligence in digital forensics. This edited volume contains seventeen chapters and presents the latest state-of-the-art advancement of Computational Intelligence in Digital Forensics; in both theoretical and application papers related to novel discovery in intelligent forensics. The chapters are further organized into three sections: (1) Introduction, (2) Forensic Discovery and Investigation, which discusses the computational intelligence technologies employed in Digital Forensic, and (3) Intelligent Forensic Science Applications, which encompasses the applications of computational intelligence in Digital Forensic, such as human anthropology, human biometrics, human by products, drugs, and electronic devices.

The Internet of Things (IoT) usually refers to a world-wide network of interconnected heterogeneous objects (sensors, actuators, smart devices, smart objects, RFID, embedded computers, etc) uniquely addressable, based on standard communication protocols. Beyond such a definition, it is emerging a new definition of IoT seen as a loosely coupled, decentralized system of cooperating smart objects (SOs). A SO is an autonomous, physical digital object augmented with sensing/actuating, processing, storing, and networking capabilities. SOs are able to sense/actuate, store, and interpret information created within themselves and around the neighbouring external world where they are situated, act on their own, cooperate with each other, and exchange information with other kinds of electronic devices and human users. However, such SO-oriented IoT raises many in-the-small and in-the-large issues involving SO programming, IoT system architecture/middleware and methods/methodologies for the development of SO-based applications. This Book will specifically focus on exploring recent advances in architectures, algorithms, and applications for an Internet of Things based on Smart Objects. Topics appropriate for this Book include, but are not necessarily limited to: - Methods for SO development - IoT Networking - Middleware for SOs - Data Management for SOs - Service-oriented SOs - Agent-oriented SOs - Applications of SOs in Smart Environments: Smart Cities, Smart Health, Smart Buildings, etc. Advanced IoT Projects.

This collection of papers, celebrating the contributions of Swedish logician Dag Prawitz to Proof Theory, has been assembled from those presented at the Natural Deduction conference organized in Rio de Janeiro to honour his  seminal  research. Dag Prawitz’s work forms the basis of intuitionistic type theory and his inversion principle constitutes the foundation of most modern accounts of proof-theoretic semantics in Logic, Linguistics and  Theoretical Computer Science. The range of contributions includes material on the extension of natural deduction with higher-order rules, as opposed to higher-order connectives, and a paper discussing the application of natural deduction rules to dealing with equality in predicate calculus. The volume continues with a key chapter summarizing work on the extension of the Curry-Howard isomorphism (itself a by-product of the work on natural deduction), via methods of category theory that have been successfully applied to linear logic, as well as many other contributions from highly regarded authorities. With an illustrious group of contributors addressing a wealth of topics and applications, this volume is a valuable addition to the libraries of academics in the multiple disciplines whose development has been given added scope by the methodologies supplied by natural deduction. The volume is representative of the rich and varied directions that Prawitz work has inspired in the area of natural deduction.

Software effort estimation is one of the oldest and most important problems in software project management, and thus today there are a large number of models, each with its own unique strengths and weaknesses in general, and even more importantly, in relation to the environment and context in which it is to be applied. Trendowicz and Jeffery present a comprehensive look at the principles of software effort estimation and support software practitioners in systematically selecting and applying the most suitable effort estimation approach. Their book not only presents what approach to take and how to apply and improve it, but also explains why certain approaches should be used in specific project situations. Moreover, it explains popular estimation methods, summarizes estimation best-practices, and provides guidelines for continuously improving estimation capability. Additionally, the book offers invaluable insights into project management in general, discussing issues including project trade-offs, risk assessment, and organizational learning. Overall, the authors deliver an essential reference work for software practitioners responsible for software effort estimation and planning in their daily work and who want to improve their estimation skills. At the same time, for lecturers and students the book can serve as the basis of a course in software processes, software estimation, or project management.

Analogical reasoning is known as a powerful mode for drawing plausible conclusions and solving problems. It has been the topic of a huge number of works by philosophers, anthropologists, linguists, psychologists, and computer scientists. As such, it has been early studied in artificial intelligence, with a particular renewal of interest in the last decade. The present volume provides a structured view of current research trends on computational approaches to analogical reasoning. It starts with an overview of the field, with an extensive bibliography. The 14 collected contributions cover a large scope of issues. First, the use of analogical proportions and analogies is explained and discussed in various natural language processing problems, as well as in automated deduction. Then, different formal frameworks for handling analogies are presented, dealing with case-based reasoning, heuristic-driven theory projection, commonsense reasoning about incomplete rule bases, logical proportions induced by similarity and dissimilarity indicators, and analogical proportions in lattice structures. Lastly, the volume reports case studies and discussions about the use of similarity judgments and the process of analogy making, at work in IQ tests, creativity or other cognitive tasks. This volume gathers fully revised and expanded versions of papers presented at an international workshop‚ as well as invited contributions. All chapters have benefited of a thorough peer review process.

The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.

The Soft Computing techniques, which are based on the information processing of biological systems are now massively used in the area of pattern recognition, making prediction & planning, as well as acting on the environment. Ideally speaking, soft computing is not a subject of homogeneous concepts and techniques; rather, it is an amalgamation of distinct methods that confirms to its guiding principle. At present, the main aim of soft computing is to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness and low solutions cost. The principal constituents of soft computing techniques are probabilistic reasoning, fuzzy logic, neuro-computing, genetic algorithms, belief networks, chaotic systems, as well as learning theory. This book covers contributions from various authors to demonstrate the use of soft computing techniques in various applications of engineering.

The book discusses intelligent system design using soft computing and similar systems and their interdisciplinary applications. It also focuses on the recent trends to use soft computing as a versatile tool for designing a host of decision support systems.

The proceeding is a collection of research papers presented, at the 8th International Conference on Robotics, Vision, Signal Processing and Power Applications (ROVISP 2013), by researchers, scientists, engineers, academicians as well as industrial professionals from all around the globe. The topics of interest are as follows but are not limited to: • Robotics, Control, Mechatronics and Automation • Vision, Image, and Signal Processing • Artificial Intelligence and Computer Applications • Electronic Design and Applications • Telecommunication Systems and Applications • Power System and Industrial Applications

In the past few decades the use of increasingly large text corpora has grown rapidly in language and linguistics research. This was enabled by remarkable strides in natural language processing (NLP) technology, technology that enables computers to automatically and efficiently process, annotate and analyze large amounts of spoken and written text in linguistically and/or pragmatically meaningful ways. It has become more desirable than ever before for language and linguistics researchers who use corpora in their research to gain an adequate understanding of the relevant NLP technology to take full advantage of its capabilities. This volume provides language and linguistics researchers with an accessible introduction to the state-of-the-art NLP technology that facilitates automatic annotation and analysis of large text corpora at both shallow and deep linguistic levels. The book covers a wide range of computational tools for lexical, syntactic, semantic, pragmatic and discourse analysis, together with detailed instructions on how to obtain, install and use each tool in different operating systems and platforms. The book illustrates how NLP technology has been applied in recent corpus-based language studies and suggests effective ways to better integrate such technology in future corpus linguistics research. This book provides language and linguistics researchers with a valuable reference for corpus annotation and analysis.

Teaching and learning paradigms have attracted increased attention especially in the last decade. Immense developments of different ICT technologies and services have paved the way for alternative but effective approaches in educational processes. Many concepts of the agent technology, such as intelligence, autonomy and cooperation, have had a direct positive impact on many of the requests imposed on modern e-learning systems and educational processes. This book presents the state-of-the-art of e-learning and tutoring systems and discusses their capabilities and benefits that stem from integrating software agents. We hope that the presented work will be of a great use to our colleagues and researchers interested in the e-learning and agent technology.    

The book is mainly addressed to young graduate students in engineering and natural sciences who start to face numerical simulation, either at a research level or in the field of industrial applications. The main subjects covered are: Biomechanics, Stochastic Calculus, Geophysical flow simulation and Shock-Capturing numerical methods for Hyperbolic Systems of Partial Differential Equations. The book can also be useful to researchers or even technicians working at an industrial environment, who are interested in the state-of-the-art numerical techniques in these fields. Moreover, it gives an overview of the research developed at the French and Spanish universities and in some European scientific institutions. This book can be also useful as a textbook at master courses in Mathematics, Physics or Engineering.

“Autonomous manipulation� is a challenge in robotic technologies. It refers to the capability of a mobile robot system with one or more manipulators that performs intervention tasks requiring physical contacts in unstructured environments and without continuous human supervision. Achieving autonomous manipulation capability is a quantum leap in robotic technologies as it is currently beyond the state of the art in robotics. This book addresses issues with the complexity of the problems encountered in autonomous manipulation including representation and modeling of robotic structures, kinematic and dynamic robotic control, kinematic and algorithmic singularity avoidance, dynamic task priority, workspace optimization and environment perception. Further development in autonomous manipulation should be able to provide robust improvements of the solutions for all of the above issues. The book provides an extensive tract on sensory-based autonomous manipulation for intervention tasks in unstructured environments. After presenting the theoretical foundations for kinematic and dynamic modelling as well as task-priority based kinematic control of multi-body systems, the work is focused on one of the most advanced underwater vehicle-manipulator system, SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions). Solutions to the problem of target identification and localization are proposed, a number of significant case studies are discussed and practical examples an d experimental/simulation results are presented. The book may inspire the robot research community to further investigate critical issues in autonomous manipulation and to develop robot systems that can profoundly impact our society for the better.

Cyberspace in increasingly important to people in their everyday lives for purchasing goods on the Internet, to energy supply increasingly managed remotely using Internet protocols. Unfortunately, this dependence makes us susceptible to attacks from nation states, terrorists, criminals and hactivists. Therefore, we need a better understanding of cyberspace, for which patterns, which are predictable regularities, may help to detect, understand and respond to incidents better. The inspiration for the workshop came from the existing work on formalising design patterns applied to cybersecurity, but we also need to understand the many other types of patterns that arise in cyberspace.

The new multimedia standards (for example, MPEG-21) facilitate the seamless integration of multiple modalities into interoperable multimedia frameworks, transforming the way people work and interact with multimedia data. These key technologies and multimedia solutions interact and collaborate with each other in increasingly effective ways, contributing to the multimedia revolution and having a significant impact across a wide spectrum of consumer, business, healthcare, education, and governmental domains. This book aims to provide a complete coverage of the areas outlined and to bring together the researchers from academic and industry as well as practitioners to share ideas, challenges, and solutions relating to the multifaceted aspects of this field.

This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer function, and highly distributed genetic programming systems. Application areas include chemical process control, circuit design, financial data mining and bioinformatics. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.

The book shows how eastern and western perspectives and conceptions can be used to addresses recent topics laying at the crossroad between philosophy and cognitive science. It reports on new points of view and conceptions discussed during the International Conference on Philosophy and Cognitive Science (PCS2013), held at the Sun Yat-sen University, in Guangzhou, China, and the 2013 Workshop on Abductive Visual Cognition, which took place at KAIST, in Deajeon, South Korea. The book emphasizes an ever-growing cultural exchange between academics and intellectuals coming from different fields. It juxtaposes research works investigating new facets on key issues between philosophy and cognitive science, such as the role of models and causal representations in science; the status of theoretical concepts and quantum principles; abductive cognition, vision, and visualization in science from an eco-cognitive perspective. Further topics are: ignorance immunization in reasoning; moral cognition, violence, and epistemology; and models and biomorphism. The book, which presents a unique and timely account of the current state-of-the art on various aspects in philosophy and cognitive science, is expected to inspire philosophers, cognitive scientists and social scientists, and to generate fruitful exchanges and collaboration among them.

This book describes the methodology and accompanying technology for reducing the costs of validation of changes by introducing automatic techniques to analyze and test software increments. It builds a unified approach to efficient and reliable validation of changes and upgrades, and may be used as a research monograph and a reference book.