This book provides insights into the First International Conference on Communication, Devices and Computing (ICCDC 2017), which was held in Haldia, India on November 2-3, 2017. It covers new ideas, applications and the experiences of research engineers, scientists, industrialists, scholars and students from around the globe. The proceedings highlight cutting-edge research on communication, electronic devices and computing, and address diverse areas such as 5G communication, spread spectrum systems, wireless sensor networks, signal processing for secure communication, error control coding, printed antennas, analysis of wireless networks, antenna array systems, analog and digital signal processing for communication systems, frequency selective surfaces, radar communication, and substrate integrated waveguide and microwave passive components, which are key to state-of-the-art innovations in communication technologies.

This book explains the fundamentals of the Internet of Things - from different architectures for managing IoT platforms to the insights on trust, security, and privacy in IoT environments, including consumer electronic devices or home applications. This opens the doors to new innovations that will build novel interactions among things and humans, and enables the realization of smart cities, infrastructures, and services. The book presents a complete overview on the research and the technology of this rapidly emerging topic.

This volume highlights new trends and challenges in research on agents and the new digital and knowledge economy, and includes 23 papers classified into the following categories: business process management, agent-based modeling and simulation, and anthropic-oriented computing. All papers were originally presented at the 11th International KES Conference on Agents and Multi-Agent Systems - Technologies and Applications (KES-AMSTA 2017) held June 21-23, 2017 in Vilamoura, Algarve, Portugal. Today's economy is driven by technologies and knowledge. Digital technologies can free, shift and multiply choices, and often intrude on the territory of other industries by providing new ways of conducting business operations and creating value for customers and companies. The topics covered in this volume include software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems and nature inspired manufacturing, etc., all of which contribute to the modern Digital Economy. The results presented here will be of theoretical and practical value to researchers and industrial practitioners working in the fields of artificial intelligence, collective computational intelligence, innovative business models, the new digital and knowledge economy and, in particular, agent and multi-agent systems, technologies, tools and applications.

This book presents state-of-the-art research advances in the field of biologically inspired cooperative control theories and their applications. It describes various biologically inspired cooperative control and optimization approaches and highlights real-world examples in complex industrial processes. Multidisciplinary in nature and closely integrating theory and practice, the book will be of interest to all university researchers, control engineers and graduate students in intelligent systems and control who wish to learn the core principles, methods, algorithms, and applications.

This book describes load modeling approaches for complex work pieces and batch forgings, and demonstrates analytical modeling and data-driven modeling approaches for known and unknown complex forging processes. It overcomes the current shortcomings of modeling, analysis and control approaches, presenting contributions in three major areas: In the first, several novel modeling approaches are proposed: a process/shape-decomposition modeling method to help estimate the deformation force; an online probabilistic learning machine for the modeling of batch forging processes; and several data-driven identification and modeling approaches for unknown forging processes under different work conditions. The second area develops model-based dynamic analysis methods to derive the conditions of stability and creep. Lastly, several novel intelligent control methods are proposed for complex forging processes. One of the most serious problems in forging forming involves the inaccurate forging conditions, velocity and position offered by the hydraulic actuator due to the complexity of both the deformation process of the metal work piece and the motion process of the hydraulic actuator. The book summarizes the current weaknesses of modeling, analysis and control approaches. are summarized as follows: a) With the current modeling approaches it is difficult to model complex forging processes with unknown parameters, as they only model the dynamics in local working areas but do not effectively model unknown nonlinear systems across multiple working areas; further, they do not take the batch forging process into account, let alone its distribution modeling. b) All previous dynamic analysis studies simplify the forging system to having a single-frequency pressure fluctuation and neglect the influences of non-linear load force. Further, they fail to take the flow equation in both valves and cylinders into account. c) Conventional control approaches only consider the linear deformation force and pay no attention to sudden changes and the motion synchronization for the multi-cylinder system, making them less effective for complex, nonlinear time-varying forging processes subject to sudden changes.

This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. The book's chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval.The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

As interactive hypermedia systems take an increasingly prevalent role in the workplace, at home and on the web, their usability becomes vitally important to meeting the expectations of users and fulfilling the promise integrating technology into daily life. Quality and Communicability for Interactive Hypermedia Systems: Concepts and Practices for Design explores ways to overcome obstacles to successful communication from theories of communicability to the various levels of design and integration. With a heuristic focus on how current system design affects user understanding, this reference source goes beyond simple usability and fills an important gap in present research by illustrating the importance of communicability in modern technological advancements.

This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, with an emphasis on exploratory and unsupervised data analysis, an area of increasing significance with the pace of growth of data vastly outpacing any chance of labeling them manually. The book looks at the underlying algorithms and technologies that facilitate the area within big data analytics, it covers their applications across domains such as smarter transportation, social media, fake news detection and enterprise search among others. This book enables readers to understand a spectrum of advances in this emerging area, and it will hopefully empower them to leverage and develop methods in multi-source data fusion and analytics with applications to a variety of scenarios. Includes advances on unsupervised, semi-supervised and supervised approaches to heterogeneous data linkage and fusion; Covers use cases of analytics over multi-view and heterogeneous data from across a variety of domains such as fake news, smarter transportation and social media, among others; Provides a high-level overview of advances in this emerging field and empowers the reader to explore novel applications and methodologies that would enrich the field.

The only integrative approach to chaos and random fractal theory

Chaos and random fractal theory are two of the most important theories developed for data analysis. Until now, there has been no single book that encompasses all of the basic concepts necessary for researchers to fully understand the ever-expanding literature and apply novel methods to effectively solve their signal processing problems. Multiscale Analysis of Complex Time Series fills this pressing need by presenting chaos and random fractal theory in a unified manner.

Adopting a data-driven approach, the book covers:

DNA sequence analysis

EEG analysis

Heart rate variability analysis

Neural information processing

Network traffic modeling

Economic time series analysis

And more

Additionally, the book illustrates almost every concept presented through applications and a dedicated Web site is available with source codes written in various languages, including Java, Fortran, C, and MATLAB, together with some simulated and experimental data. The only modern treatment of signal processing with chaos and random fractals unified, this is an essential book for researchers and graduate students in electrical engineering, computer science, bioengineering, and many other fields.

This book offers a systematic introduction to an understanding-oriented approach to multimedia content analysis. It integrates the visual understanding and learning models into a unified framework, within which the visual understanding guides the model learning while the learned models improve the visual understanding. More specifically, it discusses multimedia content representations and analysis including feature selection, feature extraction, image tagging, user-oriented tag recommendation and understanding-oriented multimedia applications. The book was nominated by the University of Chinese Academy of Sciences and China Computer Federation as an outstanding PhD thesis. By providing the fundamental technologies and state-of-the-art methods, it is a valuable resource for graduate students and researchers working in the field computer vision and machine learning.

This book presents a comprehensive framework for IoT, including its architectures, security, privacy, network communications, and protocols. The book starts by providing an overview of the aforementioned research topics, future directions and open challenges that face the IoT development. The authors then discuss the main architectures in the field, which include Three- and Five-Layer Architectures, Cloud and Fog Based Architectures, a Social IoT Application Architecture. In the security chapter, the authors outline threats and attacks, privacy preservation, trust and authentication, IoT data security, and social awareness. The final chapter presents case studies including smart home, wearables, connected cars, industrial Internet, smart cities, IoT in agriculture, smart retail, energy engagement, IoT in healthcare, and IoT in poultry and farming. Discusses ongoing research into the connection of the physical and virtual worlds; Includes the architecture, security, privacy, communications, and protocols of IoT; Presents a variety of case studies in IoT including wearables, smart cities, and energy management.

In this revolutionary work, the author sets the stage for the science of
the 21st Century, pursuing an unprecedented synthesis of fields previously
considered unrelated. Beginning with simple classical concepts, he ends
with a complex multidisciplinary theory requiring a high level of
abstraction. The work progresses across the sciences in several
multidisciplinary directions: Mathematical logic, fundamental physics,
computer science and the theory of intelligence. Extraordinarily enough,
the author breaks new ground in all these fields.

In the field of
fundamental physics the author reaches the revolutionary conclusion that
physics can be viewed and studied as logic in a fundamental sense, as
compared with Einstein's view of physics as space-time geometry. This opens
new, exciting prospects for the study of fundamental interactions. A
formulation of logic in terms of matrix operators and logic vector spaces
allows the author to tackle for the first time the intractable problem of
cognition in a scientific manner. In the same way as the findings of
Heisenberg and Dirac in the 1930s provided a conceptual and mathematical
foundation for quantum physics, matrix operator logic supports an important
breakthrough in the study of the physics of the mind, which is interpreted
as a fractal of quantum mechanics. Introducing a concept of logic quantum
numbers, the author concludes that the problem of logic and the
intelligence code in general can be effectively formulated as eigenvalue
problems similar to those of theoretical physics. With this important leap
forward in the study of the mechanism of mind, the author concludes that
the latter cannot be fully understood either within classical or quantum
notions. A higher-order covariant theory is required to accommodate the
fundamental effect of high-level intelligence. The landmark results
obtained by the author will have implications and repercussions for the
very foundations of science as a whole. Moreover, Stern's Matrix Logic is
suitable for a broad spectrum of practical applications in contemporary
technologies.

This volume is proceedings of the international conference of the Parallel Computational Fluid Dynamics 2002. In the volume, up-to-date information about numerical simulations of flows using parallel computers is given by leading researchers in this field. Special topics are "Grid Computing" and "Earth Simulator." Grid computing is now the most exciting topic in computer science. An invited paper on grid computing is presented in the volume. The Earth-Simulator is now the fastest computer in the world. Papers on flow-simulations using the Earth-Simulator are also included, as well as a thirty-two page special tutorial article on numerical optimization.

This book presents an authoritative collection of contributions reporting on fuzzy logic and decision theory, together with applications and case studies in economics and management science. Dedicated to Professor Jaume Gil Aluja in recognition of his pioneering work, the book reports on theories, methods and new challenges, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike.

This volume is about ultra high-speed cameras, which enable us to see what we normally do not see. These are objects that are moving very fast, or that we just ignore. Ultra high-speed cameras invite us to a wonderland of microseconds. There Alice (the reader) meets a ultra high-speed rabbit (this volume) and travels together through this wonderland from the year 1887 to 2017. They go to the horse riding ground and see how a horse gallops. The rabbit takes her to a showroom where various cameras and illumination devices are presented. Then, he sends Alice into semiconductor labyrinths, wind tunnels, mechanical processing factories, and dangerous explosive fields. Sometimes Alice is large, and at other times she is very small. She sits even inside a car engine. She falls down together with a droplet. She enters a microbubble, is thrown out with a jet stream, and finds herself in a human body. Waking up from her dream, she sees children playing a game: "I see what you do not see, and this is....". Alice thinks: "The ultra high-speed rabbit showed me many things which I had never seen. Now I will go again to this wonderland, and try to find something new.

This book is a collection of several contributions which show the state of the art in specific areas of Computational Intelligence. This carefully edited book honors the 65th birthday of Rudolf Kruse. The main focus of these contributions lies on treating vague data as well as uncertain and imprecise information with automated procedures, which use techniques from statistics, control theory, clustering, neural networks etc. to extract useful and employable knowledge.

In this collection of 16 articles, top scholars synthesize and analyze scholarship on this widely used tool of policy analysis, setting forth its accomplishments, difficulties, and means of implementation. Though CGE modeling does not play a prominent role in top US graduate schools, it is employed universally in the development of economic policy. This collection is particularly important because it presents a history of modeling applications and examines competing points of view.
Presents coherent summaries of CGE theories that inform major model types Covers the construction of CGE databases, model solving, and computer-assisted interpretation of results Shows how CGE modeling has made a contribution to economic policy

This book is a collection of selected papers presented at the 10th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in Wuppertal, Germany in 2014. The book is divided into five parts, reflecting the main directions of SCEE 2014: 1. Device Modeling, Electric Circuits and Simulation, 2. Computational Electromagnetics, 3. Coupled Problems, 4. Model Order Reduction, and 5. Uncertainty Quantification. Each part starts with a general introduction followed by the actual papers. The aim of the SCEE 2014 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, with the goal of fostering intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The methodological focus was on model order reduction and uncertainty quantification.

Interest in the area of control of systems defined by partial differential Equations has increased strongly in recent years. A major reason has been the requirement of these systems for sensible continuum mechanical modelling and optimization or control techniques which account for typical physical phenomena. Particular examples of problems on which substantial progress has been made are the control and stabilization of mechatronic structures, the control of growth of thin films and crystals, the control of Laser and semi-conductor devices, and shape optimization problems for turbomachine blades, shells, smart materials and microdiffractive optics. This volume contains original articles by world reknowned experts in the fields of optimal control of partial differential equations, shape optimization, numerical methods for partial differential equations and fluid dynamics, all of whom have contributed to the analysis and solution of many of the problems discussed. The collection provides a state-of-the-art overview of the most challenging and exciting recent developments in the field. It is geared towards postgraduate students and researchers dealing with the theoretical and practical aspects of a wide variety of high technology problems in applied mathematics, fluid control, optimal design, and computer modelling.

This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.

These proceedings present the latest information on intelligent- transportation technologies and their applications in real-world cases. The Second International Conference on Intelligent Transportation was held in Chengdu, China on November 25-27, 2015, to present the latest research in the field, including intelligent-transportation management, intelligent vehicles, rail transportation systems, traffic transportation networks, as well as road traffic element simulations and their industrial development. The aim of conference was to bring together academics, researchers, engineers and students from across the world to discuss state-of-the-art technologies related to intelligent transportation.

This unique work introduces the basic principles of artificial intelligence with applications in geographical teaching and research, GIS, and planning. Written in an accessible, non-technical and witty style, this book marks the beginning of the Al revolution in geography with major implications for teaching and research. The authors provide an easy to understand basic introduction to Al relevant to geography. There are no special mathematical and statistical skills needed, indeed these might well be a hindrance. Al is a different way of looking at the world and it requires a willingness to experiment, and readers who are unhindered by the baggage of obsolete technologies and outmoded philosophies of science will probably do best. The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry.

• A major methodological milestone in geography
• The first geographical book on artificial intelligence (Al)
• No need for previous mathematical or statistical skills/knowledge
• Accessible style makes a difficult subject available to a wide audience
• Stan Openshaw is one of the world s leading researchers into geographical computing, spatial analysis and GIS.

This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.

This unique book succinctly summarizes the need to measure how ontologies (one of the building blocks of the Semantic Web) are currently being utilized, providing insights for various stakeholders. Where possible it improves and reuses terms in existing vocabularies/ontologies, as recommended by the Linked Data community. Recent advances in the Semantic Web have led to a proliferation of Resource Description Framework (RDF) data, which employ ontologies to semantically describe the information on the Web making it equally understandable for both humans and machines. However, to create a network effect, it is important that selective ontologies are used by more data publishers to improve the value of that ontology. For this to happen, it is vital to discover what is being used from an ontology to semantically annotate the information on the Web specific to a given domain. Answers to such basic but crucial questions can only be achieved by ascertaining how ontologies in the current semantic web are being utilized and adopted. The proposed frameworks to obtain such insights are explained with real-world examples to provide a clear and detailed description of ontology usage analysis. Both theoretical and practical, the book is of value to academics and professionals working in industry. Specifically, it is of primary interest to researchers, graduate students and practitioners in the area of the Semantic Web and its various real-world applications.