From past decades, Computational intelligence embraces a number of nature-inspired computational techniques which mainly encompasses fuzzy sets, genetic algorithms, artificial neural networks and hybrid neuro-fuzzy systems to address the computational complexities such as uncertainties, vagueness and stochastic nature of various computational problems practically. At the same time, Intelligent Control systems are emerging as an innovative methodology which is inspired by various computational intelligence process to promote a control over the systems without the use of any mathematical models. To address the effective use of intelligent control in Computational intelligence systems, International Conference on Intelligent Computing, Information and Control Systems (ICICCS 2019) is initiated to encompass the various research works that helps to develop and advance the next-generation intelligent computing and control systems. This book integrates the computational intelligence and intelligent control systems to provide a powerful methodology for a wide range of data analytics issues in industries and societal applications. The recent research advances in computational intelligence and control systems are addressed, which provide very promising results in various industry, business and societal studies. This book also presents the new algorithms and methodologies for promoting advances in common intelligent computing and control methodologies including evolutionary computation, artificial life, virtual infrastructures, fuzzy logic, artificial immune systems, neural networks and various neuro-hybrid methodologies. This book will be pragmatic for researchers, academicians and students dealing with mathematically intransigent problems. It is intended for both academicians and researchers in the field of Intelligent Computing, Information and Control Systems, along with the distinctive readers in the fields of computational and artificial intelligence to gain more knowledge on Intelligent computing and control systems and their real-world applications.

The era of advanced, automated and electric vehicles (AAEVs) has begun; the legal transformation is starting. In July 2018, parliament enacted the Automated and Electric Vehicles Act 2018, legislating for electric vehicle charging and allowing a direct civil claim against the motor insurer of an automated, ‘self-driving’ vehicle. In May 2022, the UK government announced its intention to create a new legal category for e-scooters. In April 2023, a ‘hands free’ advanced driver assistance system was approved for use on certain motorways across England, Wales and Scotland. Motor vehicle technologies have developed since the nineteenth century and have affected numerous aspects of our lives - from road safety to the environment, from the laws of civil liability to the rules of compulsory insurance. As AAEV technologies proliferate, their effects are likely to spread further, into legal areas less associated with motor vehicles such as equality and privacy. This book describes the emerging laws of advanced, automated and electric vehicles in England and Wales, explaining: - The development of motor vehicle laws (including vehicle specification law, the law of motor insurance and the laws of passenger transport) and putting new AAEV laws into their historical and legal contexts - The laws of civil and criminal liability relating to motor vehicles and how those laws are adapting to AAEVs - The public laws relating to motor vehicles which are likely to be affected by AAEVs, including environmental law and the laws of equality, of data protection and privacy This book will help those litigating, adjudicating, regulating and studying AAEV issues. It gives the context and detail of AAEV law in its many applications. It is a map to a fast-changing legal landscape. This title is included in Bloomsbury Professional’s Cyber Law online service.

Self-organization of matter is observed in every context and on all scales, from the nanoscale of quantum fields and subatomic particles to the macroscale of galaxy superclusters. This book analyzes the wide range of patterns of organization present in nature, highlighting their similarities rather than their differences. This unconventional approach results in an illuminating read which should be part of any Physics student's background.

The first half of the book provides an introduction to general topology, with ample space given to exercises and carefully selected applications. The second half of the text includes topics in asymmetric topology, a field motivated by applications in computer science. Recurring themes include the interactions of topology with order theory and mathematics designed to model loss-of-resolution situations.

This authored monograph presents a study on fundamental limits and robustness of stability and stabilization of time-delay systems, with an emphasis on time-varying delay, robust stabilization, and newly emerged areas such as networked control and multi-agent systems. The authors systematically develop an operator-theoretic approach that departs from both the traditional algebraic approach and the currently pervasive LMI solution methods. This approach is built on the classical small-gain theorem, which enables the author to draw upon powerful tools and techniques from robust control theory. The book contains motivating examples and presents mathematical key facts that are required in the subsequent sections. The target audience primarily comprises researchers and professionals in the field of control theory, but the book may also be beneficial for graduate students alike.

This book analyzes the updated principles and applications of nonlinear approaches to solve engineering and physics problems. The knowledge on nonlinearity and the comprehension of nonlinear approaches are inevitable to future engineers and scientists, making this an ideal book for engineers, engineering students, and researchers in engineering, physics, and mathematics. Chapters are of specific interest to readers who seek expertise in optimization, nonlinear analysis, mathematical modeling of complex forms, and non-classical engineering problems. The book covers methodologies and applications from diverse areas such as vehicle dynamics, surgery simulation, path planning, mobile robots, contact and scratch analysis at the micro and nano scale, sub-structuring techniques, ballistic projectiles, and many more.

This book is written for anyone who is interested in how a field of research evolves and the fundamental role of understanding uncertainties involved in different levels of analysis, ranging from macroscopic views to meso- and microscopic ones. We introduce a series of computational and visual analytic techniques, from research areas such as text mining, deep learning, information visualization and science mapping, such that readers can apply these tools to the study of a subject matter of their choice. In addition, we set the diverse set of methods in an integrative context, that draws upon insights from philosophical, sociological, and evolutionary theories of what drives the advances of science, such that the readers of the book can guide their own research with their enriched theoretical foundations. Scientific knowledge is complex. A subject matter is typically built on its own set of concepts, theories, methodologies and findings, discovered by generations of researchers and practitioners. Scientific knowledge, as known to the scientific community as a whole, experiences constant changes. Some changes are long-lasting, whereas others may be short lived. How can we keep abreast of the state of the art as science advances? How can we effectively and precisely convey the status of the current science to the general public as well as scientists across different disciplines? The study of scientific knowledge in general has been overwhelmingly focused on scientific knowledge per se. In contrast, the status of scientific knowledge at various levels of granularity has been largely overlooked. This book aims to highlight the role of uncertainties, in developing a better understanding of the status of scientific knowledge at a particular time, and how its status evolves over the course of the development of research. Furthermore, we demonstrate how the knowledge of the types of uncertainties associated with scientific claims serves as an integral and critical part of our domain expertise.

Nonlinear Model Predictive Control is a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine - the core of any NMPC controller - works. An appendix covering NMPC software and accompanying software in MATLAB (R) and C++(downloadable from www.springer.com/ISBN) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.

This book provides the basic concepts and fundamental principles of dynamic systems including experimental methods, calibration, signal conditioning, data acquisition and processing as well as the results presentation. How to select suitable sensors to measure is also introduced. It is an essential reference to students, lecturers, professionals and any interested lay readers in measurement technology.

Kirk (emeritus, electrical engineering, San Jos State U.) introduces optimal control theory, which has as its objective the maximization of the return from, or the minimization of the cost of, the operation of physical, social, and economic processes. He concentrates on dynamic programming, Pontry

This book provides an introduction to Swarm Robotics, which is the application of methods from swarm intelligence to robotics. It goes on to present methods that allow readers to understand how to design large-scale robot systems by going through many example scenarios on topics such as aggregation, coordinated motion (flocking), task allocation, self-assembly, collective construction, and environmental monitoring. The author explains the methodology behind building multiple, simple robots and how the complexity emerges from the multiple interactions between these robots such that they are able to solve difficult tasks. The book can be used as a short textbook for specialized courses or as an introduction to Swarm Robotics for graduate students, researchers, and professionals who want a concise introduction to the field.

This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) in Boston, MA, March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe, prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.

This self-contained book presents a framework for solving a general class of linear systems with coefficients being continuous functions of parameters varying within prescribed intervals. It also provides a comprehensive overview of the theory related to solving parametric interval linear systems and the basic properties of parametric interval matrices. In particular, it develops several new algorithms delivering sharp rigorous bounds for the solutions of such systems with full mathematical rigor. The framework employs the arithmetic of revised affine forms that enables the readers to handle dependent data. The book is intended not only for researchers interested in developing rigorous methods of numerical linear algebra, but also for engineers dealing with problems involving uncertain data. The theory discussed is also useful in various other fields of numerical analysis, in computer graphics, economics, computational geometry, computer-aided design, computer-assisted proofs, computer graphics, control theory, solving constraint satisfaction problems, and global optimization.

This book presents a collection of research findings and proposals on computer science and computer engineering, introducing readers to essential concepts, theories, and applications. It also shares perspectives on how cutting-edge and established methodologies and techniques can be used to obtain new and interesting results. Each chapter focuses on a specific aspect of computer science or computer engineering, such as: software engineering, complex systems, computational intelligence, embedded systems, and systems engineering. As such, the book will bring students and professionals alike up to date on key advances in these areas.

The book consists of papers on selected topics of dependability analysis in computer systems and networks which were discussed during the 17th DepCoS-RELCOMEX conference held in Wroclaw, Poland, from June 27th to July 1st, 2022. Their collection will be an interesting source material for scientists, researchers, practitioners and students who are dealing with design, analysis and engineering of computer systems and networks and must ensure their dependable operation. Being probably the most complex technical systems ever engineered by man (and also, the most dynamically evolving ones), organization of contemporary computer systems and networks cannot be interpreted only as a structure built on the base of unreliable technical resources. Their evaluation must take into account a unique blend of interacting people, networks (together with mobile properties, cloud organization, Internet of Everything, etc.) and a large number of users dispersed geographically and constantly producing an unconceivable number of applications. Research methods being continuously developed for dependability analyses apply newest results of artificial and computational intelligence. Selection of papers in this book illustrates broad range of topics, often multi-disciplinary, which is considered in present-day dependability explorations; it also reveals an increasing role of the latest methods based on machine/deep learning and neural networks in these studies.

This proceedings volume contains talks and poster presentations from the International Symposium "Self-Organization in Complex Systems: The Past, Present, and Future of Synergetics", which took place at Hanse-Wissenschaftskolleg, an Institute of Advanced Studies, in Delmenhorst, Germany, during the period November 13 - 16, 2012. The Symposium was organized in honour of Hermann Haken, who celebrated his 85th birthday in 2012. With his fundamental theory of Synergetics he had laid the mathematical-physical basis for describing and analyzing self-organization processes in a diversity of fields of research. The quest for common and universal principles of self-organization in complex systems was clearly covered by the wide range of interdisciplinary topics reported during the Symposium. These extended from complexity in classical systems and quantum systems over self-organisation in neuroscience even to the physics of finance. Moreover, by combining a historical view with a present status report the Symposium conveyed an impression of the allure and potency of this branch of research as well as its applicability in the future.

This book presents a collection of authoritative contributions on the concept of time in early twentieth-century philosophy. It is structured in the form of a thematic atlas: each section is accompanied by relevant elementary logic maps that reproduce in a "spatial" form the directionalities (arguments and/or discourses) reported on in the text. The book is divided into three main sections, the first of which covers phenomenology and the perception of time by analyzing the works of Bergson, Husserl, Sartre, Merleau-Ponty, Deleuze, Guattari and Derrida. The second section focuses on the language and conceptualization of time, examining the works of Cassirer, Wittgenstein, Heidegger, Lacan, Ricoeur and Foucault, while the last section addresses the science and logic of time as they appear in the works of Guillaume, Einstein, Reichenbach, Prigogine and Barbour. The purpose of the book is threefold: to provide readers with a comprehensive overview of the concept of time in early twentieth-century philosophy; to show how conceptual reasoning can be supported by accompanying linguistic and spatial representations; and to stimulate novel research in the humanistic field concerning the complex role of graphic representations in the comprehension of concepts.

This book is a concise navigator across the history of cybernetics, its state-of-the-art and prospects. The evolution of cybernetics (from N. Wiener to the present day) and the reasons of its ups and downs are presented. The correlation of cybernetics with the philosophy and methodology of control, as well as with system theory and systems analysis is clearly demonstrated. The book presents a detailed analysis focusing on the modern trends of research in cybernetics. A new development stage of cybernetics (the so-called cybernetics 2.0) is discussed as a science on general regularities of systems organization and control. The author substantiates the topicality of elaborating a new branch of cybernetics, i.e. organization theory which studies an organization as a property, process and system. The book is intended for theoreticians and practitioners, as well as for students, postgraduates and doctoral candidates. In the first place, the target audience includes tutors and lecturers preparing courses on cybernetics, control theory and systems science.

Situated at the intersection of current debates regarding meaning and representation, this text casts doubt on the seeming innocence of the activity of communication. Using poststructuralist literary theory and philosophy, Chang argues that modern communication theories fail to provide an adequate explanation for how communication is possible. Through a detailed examination of the basis of the idea of communication - with its semantic core of "commonality" or the transcendence of difference - Chang argues against the tendency of theorists to value understanding over misunderstanding, clarity over ambiguity, order over disorder. To this end the author revisits the thought of Derrida and considers deconstruction in general. Specifically, he uses the critique of the phenomenological tradition emerging from poststructuralism to clarify the commitments and assumptions inherent in models of communication.

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 presents special systems derived from industrial models, including the complex saturation nonlinear functions and the delay nonlinear functions. It also presents typical methods, such as the classical Liapunov and Integral Inequalities methods. Providing constructive qualitative and stability conditions for linear systems with saturated inputs in both global and local contexts, it offers practitioners more concise model systems for modern saturation nonlinear techniques, which have the potential for future applications. This book is a valuable guide for researchers and graduate students in the fields of mathematics, control, and engineering.

This edited monograph provides a comprehensive and in-depth analysis of sliding mode control, focusing on event-triggered implementation. The technique allows to prefix the steady-state bounds of the system, and this is independent of any boundary disturbances. The idea of event-triggered SMC is developed for both single input / single output and multi-input / multi-output linear systems. Moreover, the reader learns how to apply this method to nonlinear systems. The book primarily addresses research experts in the field of sliding mode control, but the book may also be beneficial for graduate students.

This book touches upon various aspects of a very interesting, and growing in popularity category of models of dynamical systems. These are the so-called fractional-order systems. Such models are not only relevant for many fields of science and technology, but may also find numerous applications in other disciplines applying the mathematical modelling tools. Thus, the book is intended for a very wide audience of professionals who want to expand their knowledge of systems modelling and its applications. The book includes the selections of papers presented at the International Conference on Fractional Calculus and its Applications organized by the Warsaw University of Technology and was held online on 6-8 September 2021. The International Conference on Fractional Calculus and its Applications (ICFDA) has an almost twenty years history. It started in Bordeaux (France) in 2004, followed by Porto (Portugal) 2006, Istanbul (Turkey) 2008, Badajoz (Spain) 2010, Nanjing (China) 2012, Catania (Italy) 2014, Novi Sad (Serbia) 2016, Amman (Jordan) 2018. Next ICFDA was planned in 2020 in Warsaw (Poland), but COVID-19 pandemic shifted it to 6-8 September 2021. Hence, the organizers were forced to change the form of the conference to the online one. In the volume twenty eight high-quality research papers presented during the ICFDA 2021 eleven Regular Sessions with an additional online Discussion Session are presented. The presented papers are scientifically inspiring, leading to new fruitful ideas. They cover a very broad range of many disciplines. Nowadays, and especially in such a subject as fractional calculus, it is very difficult to assign papers to specific scientific areas. So, many of the papers included have an interdisciplinary character.

This volume presents the proceedings of the 12th IFToMM International Symposium on Science of Mechanisms and Machines (SYROM 2017), that was held in "Gheorghe Asachi" Technical University of Iasi, Romania, November 02-03, 2017. It contains applications of mechanisms in several modern technical fields such as mechatronics and robotics, biomechanics, machines and apparatus. The book presents original high-quality contributions on topics related to mechanisms within aspects of theory, design, practice and applications in engineering, including but not limited to: theoretical kinematics, computational kinematics, mechanism design, experimental mechanics, mechanics of robots, dynamics of machinery, dynamics of multi-body systems, control issues of mechanical systems, mechanisms for biomechanics, novel designs, mechanical transmissions, linkages and manipulators, micro-mechanisms, teaching methods, history of mechanism science, industrial and non-industrial applications. In connection with these fields, the book combines the theoretical results with experimental tests.

In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions.