As the title of the book suggests, the topics of this book are organized into two parts. The first part points out the fuzzy differential equations and the second one is related to the fuzzy integral equations. The book contains nine chapters that six chapters are about fuzzy differential equations and three of them are about fuzzy integral equations. In each part, the chapters' authors are going to discuss the topics theoretically and numerically. All researchers and students in the field of mathematical, computer, and also engineering sciences can benefit from the subjects of the book.

Introduction to Theory of Control in Organizations explains how methodologies from systems analysis and control theory, including game and graph theory, can be applied to improve organizational management. The theory presented extends the traditional approach to management science by introducing the optimization and game-theoretical tools required to account for the special nature of human beings being viewed as control objects. The book introduces a version of mechanism design that has been customized to solve the problems that today's managers must contend with. All mathematical models and mechanisms studied are motivated by the most common problems encountered by managers in firms and non-profit organizations. Requiring no prior knowledge of game theory or mechanism design, the book includes a systematic introduction to the underlying methodology of modern theory of control in organizations. The authors use formal methods to construct robust and efficient decision-making procedures which support all aspects and stages of management activity over all decision horizons-from operational to strategic management. The mathematical and methodological backgrounds of the organizational mechanisms discussed are not limited to game theory but also include systems analysis, control theory, operations research, and discrete mathematics. The book includes a set of exercises in each chapter-from simple to advanced-that provide the reader with the understanding required to integrate advanced methods of optimization, game theory, and mechanism design into daily managerial practice.

This book addresses the processes of stochastic structure formation in two-dimensional geophysical fluid dynamics based on statistical analysis of Gaussian random fields, as well as stochastic structure formation in dynamic systems with parametric excitation of positive random fields f(r,t) described by partial differential equations. Further, the book considers two examples of stochastic structure formation in dynamic systems with parametric excitation in the presence of Gaussian pumping. In dynamic systems with parametric excitation in space and time, this type of structure formation either happens - or doesn't! However, if it occurs in space, then this almost always happens (exponentially quickly) in individual realizations with a unit probability. In the case considered, clustering of the field f(r,t) of any nature is a general feature of dynamic fields, and one may claim that structure formation is the Law of Nature for arbitrary random fields of such type. The study clarifies the conditions under which such structure formation takes place. To make the content more accessible, these conditions are described at a comparatively elementary mathematical level by employing ideas from statistical topography.

Optimization, simulation and control play an increasingly important role in science and industry. Because of their numerous applications in various disciplines, research in these areas is accelerating at a rapid pace.

This volume brings together the latest developments in these areas of research as well as presents applications of these results to a wide range of real-world problems. The book is composed of invited contributions by experts from around the world who work to develop and apply new optimization, simulation and control techniques either at a theoretical level or in practice. Some key topics presented include: equilibrium problems, multi-objective optimization, variational inequalities, stochastic processes, numerical analysis, optimization in signal processing, and various other interdisciplinary applications.

This volume can serve as a useful resource for researchers, practitioners, and advanced graduate students of mathematics and engineering working in research areas where results in optimization, simulation and control can be applied.

Your software needs to leverage multiple cores, handle thousands of users and terabytes of data, and continue working in the face of both hardware and software failure. Concurrency and parallelism are the keys, and Seven Concurrency Models in Seven Weeks equips you for this new world. See how emerging technologies such as actors and functional programming address issues with traditional threads and locks development. Learn how to exploit the parallelism in your computer's GPU and leverage clusters of machines with MapReduce and Stream Processing. And do it all with the confidence that comes from using tools that help you write crystal clear, high-quality code. This book will show you how to exploit different parallel architectures to improve your code's performance, scalability, and resilience. Learn about the perils of traditional threads and locks programming and how to overcome them through careful design and by working with the standard library. See how actors enable software running on geographically distributed computers to collaborate, handle failure, and create systems that stay up 24/7/365. Understand why shared mutable state is the enemy of robust concurrent code, and see how functional programming together with technologies such as Software Transactional Memory (STM) and automatic parallelism help you tame it. You'll learn about the untapped potential within every GPU and how GPGPU software can unleash it. You'll see how to use MapReduce to harness massive clusters to solve previously intractible problems, and how, in concert with Stream Processing, big data can be tamed. With an understanding of the strengths and weaknesses of each of the different models and hardware architectures, you'll be empowered to tackle any problem with confidence. What You Need: The example code can be compiled and executed on *nix, OS X, or Windows. Instructions on how to download the supporting build systems are given in each chapter.

Friction-Induced Vibration in Lead Screw Drives covers the dynamics of lead screw drives with an emphasis on the role of friction. Friction-induced vibration in lead screws can be the cause of unacceptably high levels of audible noise as well as loss of operation accuracy and shortened life. Although lead screw drives have a long history and their mechanical design and manufacturing aspects are very well understood, the role of friction in their dynamical behavior has not been comprehensively treated. The book draws on the vast body of work on the subject of dynamical systems with friction (such as disk brake systems) and offers said treatment, along with: * Unique coverage of modeling of multi-DOF lead screw systems with friction * Detailed analysis of negative damping, mode coupling, and kinematic constraint instability mechanisms in lead screws drives * A practical parameter identification approach for the velocity dependent coefficient of friction in lead screw drives Friction-Induced Vibration in Lead Screw Drives serves as the definitive text on the friction-induced vibration of lead screws, and includes a practical case study where the developed methods are used to study the excessive noise problem of a lead screw drive system and to put forward design modifications that eliminate the friction-induced vibrations.

This volume launches a series that will focus on providing chapters that advance our understanding of human performance in organizational systems as cognitive engineering principles are applied. Topics addressed in this volume include: a historical review of a cognitive engineering research at a national laboratory; an adaptive learning system approach to designing an integrated-embedded training system; application of PRONET, a method that provides a useful representation of sequences of behaviour in a human-machine interaction; application of CTA, a method to explain the mental processes involved in performing a task; application of human performance modelling technologies in system design and evaluation; a review of training critical thinking skills that individuals and teams require in changing environments; a review of commercial simulations for team research; and research paradigms for human performance research in complex systems.

This is the first full-length study about the British artist Roy Ascott, one of the first cybernetic artists, with a career spanning seven decades to date. The book focuses on his early career, exploring the evolution of his early interests in communication in the context of the rich overlaps between art, science and engineering in Britain during the 1950s and 1960s. The first part of the book looks at Ascott's training and early work. The second park looks solely at Groundcourse, Ascott's extraordinary pedagogical model for visual arts and cybernetics which used an integrative and systems-based model, drawing in behaviourism, analogue machines, performance and games. Using hitherto unpublished photographs and documents, this book will establish a more prominent place for cybernetics in post-war British art.

Psychological research into human cognition and judgment reveals a wide range of biases and shortcomings. Whether we form impressions of other people, recall episodes from memory, report our attitudes in an opinion poll, or make important decisions, we often get it wrong. The errors made are not trivial and often seem to violate common sense and basic logic. A closer look at the underlying processes, however, suggests that many of the well known fallacies do not necessarily reflect inherent shortcomings of human judgment. Rather, they partially reflect that research participants bring the tacit assumptions that govern the conduct of conversation in daily life to the research situation. According to these assumptions, communicated information comes with a guarantee of relevance and listeners are entitled to assume that the speaker tries to be informative, truthful, relevant, and clear. Moreover, listeners interpret the speakers' utterances on the assumption that they are trying to live up to these ideals. This book introduces social science researchers to the "logic of conversation" developed by Paul Grice, a philosopher of language, who proposed the cooperative principle and a set of maxims on which conversationalists implicitly rely. The author applies this framework to a wide range of topics, including research on person perception, decision making, and the emergence of context effects in attitude measurement and public opinion research. Experimental studies reveal that the biases generally seen in such research are, in part, a function of violations of Gricean conversational norms. The author discusses implications for the design of experiments and questionnaires and addresses the socially contextualized nature of human judgment.

This open access book presents a comprehensive survey of modern operator techniques for boundary value problems and spectral theory, employing abstract boundary mappings and Weyl functions. It includes self-contained treatments of the extension theory of symmetric operators and relations, spectral characterizations of selfadjoint operators in terms of the analytic properties of Weyl functions, form methods for semibounded operators, and functional analytic models for reproducing kernel Hilbert spaces. Further, it illustrates these abstract methods for various applications, including Sturm-Liouville operators, canonical systems of differential equations, and multidimensional Schroedinger operators, where the abstract Weyl function appears as either the classical Titchmarsh-Weyl coefficient or the Dirichlet-to-Neumann map. The book is a valuable reference text for researchers in the areas of differential equations, functional analysis, mathematical physics, and system theory. Moreover, thanks to its detailed exposition of the theory, it is also accessible and useful for advanced students and researchers in other branches of natural sciences and engineering.

This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of complex networks provide some applicable carriers, which show the importance of theories developed in complex networks. In particular, a general model for studying time evolution of transition networks, deflection routing in complex networks, recommender systems for social networks analysis and mining, strategy selection in networked evolutionary games, integration and methods in computational biology, are discussed in detail.

Systems Thinking, Critical Realism and Philosophy: A Confluence of Ideas seeks to re-address the whole question of philosophy and systems thinking for the twenty first century and provide a new work that would be of value to both systems and philosophy. This is a highly opportune time when different fields - critical realism, philosophy of science and systems thinking - are all developing around the same set of concepts and yet not realizing it. This book will be of interest to the academic systems community worldwide and due to it's interdisciplinary coverage, it will also be of relevance to a wide range of scholars in other disciplines, particularly philosophy but also operational research, information systems, and sociology.

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.

This book focuses on bifurcation and stability in nonlinear discrete systems, including monotonic and oscillatory stability. It presents the local monotonic and oscillatory stability and bifurcation of period-1 fixed-points on a specific eigenvector direction, and discusses the corresponding higher-order singularity of fixed-points. Further, it explores the global analysis of monotonic and oscillatory stability of fixed-points in 1-dimensional discrete systems through 1-dimensional polynomial discrete systems. Based on the Yin-Yang theory of nonlinear discrete systems, the book also addresses the dynamics of forward and backward nonlinear discrete systems, and the existence conditions of fixed-points in said systems. Lastly, in the context of local analysis, it describes the normal forms of nonlinear discrete systems and infinite-fixed-point discrete systems. Examining nonlinear discrete systems from various perspectives, the book helps readers gain a better understanding of the nonlinear dynamics of such systems.

This book is about morphogenesis as the genesis of forms. It is not restricted to plants growing from seed or animals developing from an embryo (although these do supply the most abundant examples) but also addresses kindred processes, from inorganic to social to biomorphic technology. It is about our morphogenetic universe: unplanned, unfair and frustratingly complicated but benevolent in allowing us to emerge, survive, and inquire into its laws.

The chapters in this book originate from the research work and contributions presented at the Sixth International Symposium on Recurrence Plots held in Grenoble, France in June 2015. Scientists from numerous disciplines gathered to exchange knowledge on recent applications and developments in recurrence plots and recurrence quantification analysis. This meeting was remarkable because of the obvious expansion of recurrence strategies (theory) and applications (practice) into ever-broadening fields of science. It discusses real-world systems from various fields, including mathematics, strange attractors, applied physics, physiology, medicine, environmental and earth sciences, as well as psychology and linguistics. Even readers not actively researching any of these particular systems will benefit from discovering how other scientists are finding practical non-linear solutions to specific problems.The book is of interest to an interdisciplinary audience of recurrence plot users and researchers interested in time series analysis in particular, and in complex systems in general.

This book addresses topics of mobile multi-agent systems, pattern formation, biological modelling, artificial life, unconventional computation, and robotics. The behaviour of a simple organism which is capable of remarkable biological and computational feats that seem to transcend its simple component parts is examined and modelled. In this book the following question is asked: How can something as simple as Physarum polycephalum - a giant amoeboid single-celled organism which does not possess any neural tissue, fixed skeleton or organised musculature - can approximate complex computational behaviour during its foraging, growth and adaptation of its amorphous body plan, and with such limited resources? To answer this question the same apparent limitations as faced by the organism are applied: using only simple components with local interactions. A synthesis approach is adopted and a mobile multi-agent system with very simple individual behaviours is employed. It is shown their interactions yield emergent behaviour showing complex self-organised pattern formation with material-like evolution. The presented model reproduces the biological behaviour of Physarum; the formation, growth and minimisation of transport networks. In its conclusion the book moves beyond Physarum and provides results of scoping experiments approximating other complex systems using the multi-agent approach. The results of this book demonstrate the power and range of harnessing emergent phenomena arising in simple multi-agent systems for biological modelling, computation and soft-robotics applications. It methodically describes the necessary components and their interactions, showing how deceptively simple components can create powerful mechanisms, aided by abundant illustrations, supplementary recordings and interactive models. It will be of interest to those in biological sciences, physics, computer science and robotics who wish to understand how simple components can result in complex and useful behaviours and who wish explore the potential of guided pattern formation themselves.

We are often told that we are "living in an information society" or that we are "information workers." But what exactly do these claims mean, and how might they be verified? In this important methodological study, Alistair S. Duff cuts through the rhetoric to get to the bottom of the "information society thesis." Wide-ranging in coverage, this study will be of interest to scholars in information science, communication and media studies and social theory. It is a key text for the newly-unified specialism of information society studies, and an indispensable guide to the future of this discipline.

Big Data and Information Theory are a binding force between various areas of knowledge that allow for societal advancement. Rapid development of data analytic and information theory allows companies to store vast amounts of information about production, inventory, service, and consumer activities. More powerful CPUs and cloud computing make it possible to do complex optimization instead of using heuristic algorithms, as well as instant rather than offline decision-making. The era of "big data" challenges includes analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations. Big data calls for better integration of optimization, statistics, and data mining. In response to these challenges this book brings together leading researchers and engineers to exchange and share their experiences and research results about big data and information theory applications in various areas. This book covers a broad range of topics including statistics, data mining, data warehouse implementation, engineering management in large-scale infrastructure systems, data-driven sustainable supply chain network, information technology service offshoring project issues, online rumors governance, preliminary cost estimation, and information system project selection. The chapters in this book were originally published in the journal, International Journal of Management Science and Engineering Management.

This volume chronicles the 16th Annual Conference on System Engineering Research (CSER) held on May 8-9, 2018 at the University of Virginia, Charlottesville, Virginia, USA. The CSER offers researchers in academia, industry, and government a common forum to present, discuss, and influence systems engineering research. It provides access to forward-looking research from across the globe, by renowned academicians as well as perspectives from senior industry and government representatives. Co-founded by the University of Southern California and Stevens Institute of Technology in 2003, CSER has become the preeminent event for researchers in systems engineering across the globe. Topics include though are not limited to the following: Systems in context: * Formative methods: requirements * Integration, deployment, assurance * Human Factors * Safety and Security Decisions/ Control & Design; Systems Modeling: * Optimization, Multiple Objectives, Synthesis * Risk and resiliency * Collaborative autonomy * Coordination and distributed decision-making Prediction: * Prescriptive modeling; state estimation * Stochastic approximation, stochastic optimization and control Integrative Data engineering: * Sensor Management * Design of Experiments

This contributed volume offers a collection of papers presented at the 2018 Network Games, Control, and Optimization conference (NETGCOOP), held at the New York University Tandon School of Engineering in New York City, November 14-16, 2018. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other related fields.

"Coalescent Argumentation" is based on the concept that arguments can function from agreement, rather than disagreement. To prove this idea, Gilbert first discusses how several components--emotional, visceral (physical) and kisceral (intuitive) are utilized in an argumentative setting by people everyday. These components, also characterized as "modes," are vital to argumentative communication because they affect both the argument and the resulting outcome.
In addition to the components/modes, this book also stresses the goals in argumentation as a means for understanding one's own and one's opposer's positions. Gilbert argues that by viewing positions as complex human events involving a variety of communicative modes, we are better able to find commonalities across positions, and, therefore, move from conflict to resolution. By focusing on agreement and shared goals in all modes, arguers can coalesce diverse positions and more easily distinguish between minor or unrelated differences and core disagreements. This permits much greater latitude for locating shared beliefs, values, and attitudes that will lead to conflict resolution.

In this monograph the authors present Newton-type, Newton-like and other numerical methods, which involve fractional derivatives and fractional integral operators, for the first time studied in the literature. All for the purpose to solve numerically equations whose associated functions can be also non-differentiable in the ordinary sense. That is among others extending the classical Newton method theory which requires usual differentiability of function. Chapters are self-contained and can be read independently and several advanced courses can be taught out of this book. An extensive list of references is given per chapter. The book's results are expected to find applications in many areas of applied mathematics, stochastics, computer science and engineering. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also to be in all science and engineering libraries.

This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory. The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts: theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification; data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; and Koopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control. A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.