This book reviews the theoretical concepts, leading-edge techniques and practical tools involved in the latest multi-disciplinary approaches addressing the challenges of big data. Illuminating perspectives from both academia and industry are presented by an international selection of experts in big data science. Topics and features: describes the innovative advances in theoretical aspects of big data, predictive analytics and cloud-based architectures; examines the applications and implementations that utilize big data in cloud architectures; surveys the state of the art in architectural approaches to the provision of cloud-based big data analytics functions; identifies potential research directions and technologies to facilitate the realization of emerging business models through big data approaches; provides relevant theoretical frameworks, empirical research findings, and numerous case studies; discusses real-world applications of algorithms and techniques to address the challenges of big datasets.

Building on the author's earlier Applied Simulation and Optimization, this book presents novel methods for solving problems in industry, based on hybrid simulation-optimization approaches that combine the advantages of both paradigms. The book serves as a comprehensive guide to tackling scheduling, routing problems, resource allocations and other issues in industrial environments, the service industry, production processes, or supply chains and aviation. Logistics, manufacturing and operational problems can either be modelled using optimization techniques or approaches based on simulation methodologies. Optimization techniques have the advantage of performing efficiently when the problems are properly defined, but they are often developed through rigid representations that do not include or accurately represent the stochasticity inherent in real systems. Furthermore, important information is lost during the abstraction process to fit each problem into the optimization technique. On the other hand, simulation approaches possess high description levels, but the optimization is generally performed through sampling of all the possible configurations of the system. The methods explored in this book are of use to researchers and practising engineers in fields ranging from supply chains to the aviation industry.

This book introduces simulation tools and strategies for complex systems of solid-state-drives (SSDs) which consist of a flash multi-core microcontroller plus NAND flash memories. It provides a broad overview of the most popular simulation tools, with special focus on open source solutions. VSSIM, NANDFlashSim and DiskSim are benchmarked against performances of real SSDs under different traffic workloads. PROs and CONs of each simulator are analyzed, and it is clearly indicated which kind of answers each of them can give and at a what price. It is explained, that speed and precision do not go hand in hand, and it is important to understand when to simulate what, and with which tool. Being able to simulate SSD's performances is mandatory to meet time-to-market, together with product cost and quality. Over the last few years the authors developed an advanced simulator named "SSDExplorer" which has been used to evaluate multiple phenomena with great accuracy, from QoS (Quality Of Service) to Read Retry, from LDPC Soft Information to power, from Flash aging to FTL. SSD simulators are also addressed in a broader context in this book, i.e. the analysis of what happens when SSDs are connected to the OS (Operating System) and to the end-user application (for example, a database search). The authors walk the reader through the full simulation flow of a real system-level by combining SSD Explorer with the QEMU virtual platform. The reader will be impressed by the level of know-how and the combination of models that such simulations are asking for.

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

This volume presents a collection of research studies on sophisticated and functional computational instruments able to recognize, process, and store relevant situated interactional signals, as well as, interact with people, displaying reactions (under conditions of limited time) that show abilities of appropriately sensing and understanding environmental changes, producing suitable, autonomous, and adaptable responses to various social situations. These social robotic autonomous systems will improve the quality of life of their end-users while assisting them on several needs, ranging from educational settings, health care assistance, communicative disorders, and any disorder impairing either their physical, cognitive, or social functional activities. The multidisciplinary themes presented in the volume will be interesting for experts and students coming from different research fields and with different knowledge and backgrounds. The research reported is particularly relevant for academic centers, and Research & Development Institutions.

This book is the fourth in a multidisciplinary series which brings together leading researchers in the STEAM-H disciplines (Science, Technology, Engineering, Agriculture, Mathematics and Health) to present their perspective on advances in their own specific fields, and to generate a genuinely interdisciplinary collaboration that transcends parochial subject-matter boundaries. All contributions are carefully edited, peer-reviewed, reasonably self-contained, and pedagogically crafted for a multidisciplinary readership. Contributions are drawn from a variety of fields including mathematics, statistics, game theory and behavioral sciences, biomathematics and physical chemistry, computer science and human-centered computing. This volume is dedicated to Professor Christiane Rousseau, whose work inspires the STEAM-H series, in recognition of her passion for the mathematical sciences and her on-going initiative, the Mathematics of Planet Earth paradigm of interdisciplinarity. The volume's primary goal is to enhance interdisciplinary understanding between these areas of research by showing how new advances in a particular field can be relevant to open problems in another and how many disciplines contribute to a better understanding of relevant issues at the interface of mathematics and the sciences. The main emphasis is on important methods, research directions and applications of analysis within and beyond each field. As such, the volume aims to foster student interest and participation in the STEAM-H domain, as well as promote interdisciplinary research collaborations. The volume is valuable as a reference of choice and a source of inspiration for a broad spectrum of scientists, mathematicians, research students and postdoctoral fellows.

This volume is a collection of research studies on the modeling of emotions in complex autonomous systems. Several experts in the field are reporting their efforts and reviewing the literature in order to shed lights on how the processes of coding and decoding emotional states took place in humans, which are the physiological, physical, and psychological variables involved, invent new mathematical models and algorithms to describe them, and motivate these investigations in the light of observable societal changes and needs, such as the aging population and the cost of health care services. The consequences are the implementation of emotionally and socially believable machines, acting as helpers into domestic spheres, where emotions drive behaviors and actions. The contents of the book are highly multidisciplinary since the modeling of emotions in robotic socially believable systems requires a holistic perspective on topics coming from different research domains such as computer science, engineering, sociology, psychology, linguistic, and information communication. The book is of interest both to experts and students since last research works on a so complex multidisciplinary topic are described in a neat and didactical scientific language.

This book introduces the Vienna Simulator Suite for 3rd-Generation Partnership Project (3GPP)-compatible Long Term Evolution-Advanced (LTE-A) simulators and presents applications to demonstrate their uses for describing, designing, and optimizing wireless cellular LTE-A networks. Part One addresses LTE and LTE-A link level techniques. As there has been high demand for the downlink (DL) simulator, it constitutes the central focus of the majority of the chapters. This part of the book reports on relevant highlights, including single-user (SU), multi-user (MU) and single-input-single-output (SISO) as well as multiple-input-multiple-output (MIMO) transmissions. Furthermore, it summarizes the optimal pilot pattern for high-speed communications as well as different synchronization issues. One chapter is devoted to experiments that show how the link level simulator can provide input to a testbed. This section also uses measurements to present and validate fundamental results on orthogonal frequency division multiplexing (OFDM) transmissions that are not limited to LTE-A. One chapter exclusively deals with the newest tool, the uplink (UL) link level simulator, and presents cutting-edge results. In turn, Part Two focuses on system-level simulations. From early on, system-level simulations have been in high demand, as people are naturally seeking answers when scenarios with numerous base stations and hundreds of users are investigated. This part not only explains how mathematical abstraction can be employed to speed up simulations by several hundred times without sacrificing precision, but also illustrates new theories on how to abstract large urban heterogeneous networks with indoor small cells. It also reports on advanced applications such as train and car transmissions to demonstrate the tools' capabilities.

This book focuses on the principles of wireless sensor networks (WSNs), their applications, and their analysis tools, with meticulous attention paid to definitions and terminology. This book presents the adopted technologies and their manufacturers in detail, making WSNs tangible for the reader. In introductory computer networking books, chapter sequencing follows the bottom-up or top-down architecture of the 7-layer protocol. This book addresses subsequent steps in this process, both horizontally and vertically, thus fostering a clearer and deeper understanding through chapters that elaborate on WSN concepts and issues. With such depth, this book is intended for a wide audience; it is meant to be a helper and motivator for senior undergraduates, postgraduates, researchers, and practitioners. It lays out important concepts and WSN-relate applications; uses appropriate literature to back research and practical issues; and focuses on new trends. Senior undergraduate students can use it to familiarize themselves with conceptual foundations and practical project implementations. For graduate students and researchers, test beds and simulators provide vital insights into analysis methods and tools for WSNs. Lastly, in addition to applications and deployment, practitioners will be able to learn more about WSN manufacturers and components within several platforms and test beds.

These are the proceedings of the 22nd International Conference on Domain Decomposition Methods, which was held in Lugano, Switzerland. With 172 participants from over 24 countries, this conference continued a long-standing tradition of internationally oriented meetings on Domain Decomposition Methods. The book features a well-balanced mix of established and new topics, such as the manifold theory of Schwarz Methods, Isogeometric Analysis, Discontinuous Galerkin Methods, exploitation of modern HPC architectures and industrial applications. As the conference program reflects, the growing capabilities in terms of theory and available hardware allow increasingly complex non-linear and multi-physics simulations, confirming the tremendous potential and flexibility of the domain decomposition concept.

This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamics or biological sequence analysis. The technical material is illustrated by the use of worked examples and methods for training the algorithms are included. Dynamic Systems Models provides researchers in aerospatial engineering, bioinformatics and financial mathematics (as well as computer scientists interested in any of these fields) with a reliable and effective numerical method for nonlinear estimation and solving boundary problems when carrying out control design. It will also be of interest to academic researchers studying inverse problems and their solution.

The articles in this book review hybrid experimental-computational methods applied to soft tissues which have been developed by worldwide specialists in the field. People developing computational models of soft tissues and organs will find solutions for calibrating the material parameters of their models; people performing tests on soft tissues will learn what to extract from the data and how to use these data for their models and people worried about the complexity of the biomechanical behavior of soft tissues will find relevant approaches to address this complexity.

This publication showcases the work of UK mathematicians and statisticians by describing industrial problems that have been successfully solved, together with a summary of the financial and/or societal impact that arose from the work. The articles are grouped by sector, and include contributions to climate modelling, engineering and health. The articles are based on Impact Case Studies that were submitted to the Research Excellence Framework (REF2014), a UK government sponsored exercise that assessed the research quality within UK universities. There are many publications in the realm of 'popular mathematics' as well as a vast research literature that underpins this. This work is aimed at a middle ground between these two. Articles contain some mathematical detail, but the emphasis is on telling the story of a successful collaboration between academia and industry and on the results obtained. UK Success Stories in Industrial Mathematics is therefore accessible to a wide readership with interest in the applications of mathematics and statistics to problems of industrial importance and to those interested in how mathematics and statistics research affects our everyday lives and leads to economic and societal benefits.

This book delivers a methodological approach on the experimentation and/or simulation processes from the disclaiming hypothesis on a physical phenomenon to the validation of the results. The main benefit of the book is that it discusses all the topics related to experimentation and validation of the outcome including state-of-the-art applications and presents important theoretical, mathematical and experimental developments, providing a self-contained major reference that is appealing to both the scientists and the engineers. At the same time, these topics are encountered in a variety of scientific and engineering disciplines. As a first step, it presents the theoretical and practical implications on the formation of a hypothesis, considering the existing knowledge collection, classification and validation of the particular areas of experimenting interest. Afterwards, the transition from the knowledge classes to the experimentation parameters according to the phenomena evolution contributors and the systemic properties of the descriptors are discussed. The major experimenting requirements focus on the conditions to satisfy a potential disclaim of the initial hypothesis as conditions. Furthermore, the experimentation outcome, as derived via the previous experimentation process set-up, would be validate for the similarities among the existing knowledge and derived new one. The whole methodology offers a powerful tool towards the minimization of research effort wastes, as far as it can identify the lacks of knowledge, thus the areas of interest where the current research has to work on. The special features of this book are (a) the use of state-of-the-art techniques for the classification of knowledge, (b) the consideration of a realistic systemic world of engineering approached phenomena, (c) the application of advanced mathematical techniques for identifying, describing and testing the similarities in the research results and conclusions, and (d) the experimental investigation of relevant phenomena.

The two-volume set LNICST 236-237 constitutes the post-conference proceedings of the 12th EAI International Conference on Communications and Networking, ChinaCom 2017, held in Xi'an, China, in September 2017. The total of 112 contributions presented in these volumes are carefully reviewed and selected from 178 submissions. The papers are organized in topical sections on wireless communications and networking, satellite and space communications and networking, big data network track, multimedia communications and smart networking, signal processing and communications, network and information security, advances and trends of V2X networks.

This textbook reviews the theory, applications, and latest breakthroughs in Delay Tolerant Networks (DTNs). Presenting a specific focus on Opportunistic Mobile Networks (OMNs), the text considers the influence of human aspects, and examines emerging forms of inter-node cooperation. Features: contains review terms and exercises in each chapter, with the solutions and source code available at an associated website; introduces the fundamentals of DTNs, covering OMNs, PSNs, and MOONs; describes the ONE simulator, explaining how to set up a simulation project; provides detailed insights into the development and testing of protocols, together with a set of best practices for increased productivity and optimized performance; examines human aspects in the context of communication networks, from human-centric applications to the impact of emotion on human-network interplay; proposes various schemes for inter-node cooperation in DTNs/OMNs; presents a detailed discussion on aspects of heterogeneity in DTNs.

The book provides suggestions on how to start using bionic optimization methods, including pseudo-code examples of each of the important approaches and outlines of how to improve them. The most efficient methods for accelerating the studies are discussed. These include the selection of size and generations of a study's parameters, modification of these driving parameters, switching to gradient methods when approaching local maxima, and the use of parallel working hardware. Bionic Optimization means finding the best solution to a problem using methods found in nature. As Evolutionary Strategies and Particle Swarm Optimization seem to be the most important methods for structural optimization, we primarily focus on them. Other methods such as neural nets or ant colonies are more suited to control or process studies, so their basic ideas are outlined in order to motivate readers to start using them. A set of sample applications shows how Bionic Optimization works in practice. From academic studies on simple frames made of rods to earthquake-resistant buildings, readers follow the lessons learned, difficulties encountered and effective strategies for overcoming them. For the problem of tuned mass dampers, which play an important role in dynamic control, changing the goal and restrictions paves the way for Multi-Objective-Optimization. As most structural designers today use commercial software such as FE-Codes or CAE systems with integrated simulation modules, ways of integrating Bionic Optimization into these software packages are outlined and examples of typical systems and typical optimization approaches are presented. The closing section focuses on an overview and outlook on reliable and robust as well as on Multi-Objective-Optimization, including discussions of current and upcoming research topics in the field concerning a unified theory for handling stochastic design processes.

The two-volume set LNICST 236-237 constitutes the post-conference proceedings of the 12th EAI International Conference on Communications and Networking, ChinaCom 2017, held in Xi'an, China, in September 2017. The total of 112 contributions presented in these volumes are carefully reviewed and selected from 178 submissions. Aside from the technical paper sessions the book is organized in topical sections on wireless communications and networking, satellite and space communications and networking, big data network track, multimedia communications and smart networking, signal processing and communications, network and information security, advances and trends of V2X networks.

This book constitutes the refereed proceedings of the First International Conference on Advanced Hybrid Information Processing, ADHIB 2017, held in Harbin, China, in July 2017. The 64 full papers were selected from 134 submissions and focus on advanced methods and applications for hybrid information processing.

This book constitutes the refereed proceedings of the 4th International Conference on Tools and Methods for Program Analysis, TMPA 2017, Moscow, Russia, March 3-4, 2017. The 12 revised full papers and 5 revised short papers presented together with three abstracts of keynote talks were carefully reviewed and selected from 51 submissions. The papers deal with topics such as software test automation, static program analysis, verification, dynamic methods of program analysis, testing and analysis of parallel and distributed systems, testing and analysis of high-load and high-availability systems, analysis and verification of hardware and software systems, methods of building quality software, tools for software analysis, testing and verification.

The two-volume set LNCS 10671 and 10672 constitutes the thoroughly refereed proceedings of the 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017, held in Las Palmas de Gran Canaria, Spain, in February 2017. The 117 full papers presented were carefully reviewed and selected from 160 submissions. The papers are organized in topical sections on: pioneers and landmarks in the development of information and communication technologies; systems theory, socio-economic systems and applications; theory and applications of metaheuristic algorithms; stochastic models and applications to natural, social and technical systems; model-based system design, verification and simulation; applications of signal processing technology; algebraic and combinatorial methods in signal and pattern analysis; computer vision, deep learning and applications; computer and systems based methods and electronics technologies in medicine; intelligent transportation systems and smart mobility.

This book addresses the problems involved in the modelling and simulation of shale gas reservoirs, and details recent advances in the field. It discusses various modelling and simulation challenges, such as the complexity of fracture networks, adsorption phenomena, non-Darcy flow, and natural fracture networks, presenting the latest findings in these areas. It also discusses the difficulties of developing shale gas models, and compares analytical modelling and numerical simulations of shale gas reservoirs with those of conventional reservoirs. Offering a comprehensive review of the state-of-the-art in developing shale gas models and simulators in the upstream oil industry, it allows readers to gain a better understanding of these reservoirs and encourages more systematic research on efficient exploitation of shale gas plays. It is a valuable resource for researchers interested in the modelling of unconventional reservoirs and graduate students studying reservoir engineering. It is also of interest to practising reservoir and production engineers.

This volume constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Verified Software: Theories, Tools, and Experiments, VSTTE 2017, held in Heidelberg, Germany, in July 2017. The 12 full papers presented were carefully revised and selected from 20 submissions. The papers describe large-scale verification efforts that involve collaboration, theory unification, tool integration, and formalized domain knowledge as well as novel experiments and case studies evaluating verification techniques and technologies.

This book proposes complex hierarchical deep architectures (HDA) for predicting bankruptcy, a topical issue for business and corporate institutions that in the past has been tackled using statistical, market-based and machine-intelligence prediction models. The HDA are formed through fuzzy rough tensor deep staking networks (FRTDSN) with structured, hierarchical rough Bayesian (HRB) models. FRTDSN is formalized through TDSN and fuzzy rough sets, and HRB is formed by incorporating probabilistic rough sets in structured hierarchical Bayesian model. Then FRTDSN is integrated with HRB to form the compound FRTDSN-HRB model. HRB enhances the prediction accuracy of FRTDSN-HRB model. The experimental datasets are adopted from Korean construction companies and American and European non-financial companies, and the research presented focuses on the impact of choice of cut-off points, sampling procedures and business cycle on the accuracy of bankruptcy prediction models. The book also highlights the fact that misclassification can result in erroneous predictions leading to prohibitive costs to investors and the economy, and shows that choice of cut-off point and sampling procedures affect rankings of various models. It also suggests that empirical cut-off points estimated from training samples result in the lowest misclassification costs for all the models. The book confirms that FRTDSN-HRB achieves superior performance compared to other statistical and soft-computing models. The experimental results are given in terms of several important statistical parameters revolving different business cycles and sub-cycles for the datasets considered and are of immense benefit to researchers working in this area.

This three volume set, CCIS 771, 772, 773, constitutes the refereed proceedings of the CCF Chinese Conference on Computer Vision, CCCV 2017, held in Tianjin, China, in October 2017. The total of 174 revised full papers presented in three volumes were carefully reviewed and selected from 465 submissions. The papers are organized in the following topical sections: biological vision inspired visual method; biomedical image analysis; computer vision applications; deep neural network; face and posture analysis; image and video retrieval; image color and texture; image composition; image quality assessment and analysis; image restoration; image segmentation and classification; image-based modeling; object detection and classification; object identification; photography and video; robot vision; shape representation and matching; statistical methods and learning; video analysis and event recognition; visual salient detection.