This volume is a collection of papers on emerging concepts, approaches and ideas in information systems research. It examines theoretical and methodological issues related to both information systems development in general and the complexity of information systems as socio-technical systems. The book draws on invited papers selected from the proceedings of the 25th International Conference on Information Systems Development (ISD) held in Katowice, Poland, August 24 - 26, 2016. The invited conference papers were revised and expanded and present research that is focused on context, creativity, and cognition in information systems development. These issues are significant as they provide the basis for organizations to identify new markets, support innovative technology deployment, and enable mobile applications to detect, sense, interpret, and respond to the environment.

Classical social choice theory relies heavily on the assumption that all individuals have fixed preference orderings. This highly original book presents a new theory of social preferences that explicitly accounts for important social phenomena such as coordination, compromise, negotiation and altruism. Drawing on cybernetics and network theory, it extends classical social choice theory by constructing a framework that allows for dynamic preferences that are modulated by the situation-dependent social influence that they exert on each other. In this way the book shows how members of a social network may modulate their preferences to account for social context. This important expansion of social choice theory will be of interest to readers in a wide variety of disciplines, including economists and political scientists concerned with choice theory as well as computer scientists and engineers working on network theory.

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.

This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Ito's formula, the optional stopping theorem and Girsanov's theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Ito, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested in such developments. Beginning graduate or advanced undergraduate students will benefit from this detailed approach to an essential area of probability theory. The emphasis is on concise and efficient presentation, without any concession to mathematical rigor. The material has been taught by the author for several years in graduate courses at two of the most prestigious French universities. The fact that proofs are given with full details makes the book particularly suitable for self-study. The numerous exercises help the reader to get acquainted with the tools of stochastic calculus.

This book is an introduction to maximum-entropy models of random graphs with given topological properties and their applications. Its original contribution is the reformulation of many seemingly different problems in the study of both real networks and graph theory within the unified framework of maximum entropy. Particular emphasis is put on the detection of structural patterns in real networks, on the reconstruction of the properties of networks from partial information, and on the enumeration and sampling of graphs with given properties. After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem of network reconstruction and introduces various advanced techniques to reliably infer the topology of a network from partial local information. Chapter 5 is devoted to the reformulation of certain "hard" combinatorial operations, such as the enumeration and unbiased sampling of graphs with given constraints, within a "softened" maximum-entropy framework. A final chapter offers various overarching remarks and take-home messages.By requiring no prior knowledge of network theory, the book targets a broad audience ranging from PhD students approaching these topics for the first time to senior researchers interested in the application of advanced network techniques to their field.

This book presents high-quality original contributions on positive systems, including topics such as: monotone dynamical systems in mathematical biology and game theory; mathematical developments for networked systems in biology, chemistry and the social sciences; linear and nonlinear positive operators; dynamical analysis, observation and control of positive distributed parameter systems; stochastic realization theory; biological systems with positive variables and positive controls; iterated function systems; nonnegative dynamic processes; and dimensioning problems for collaborative systems. The book comprises a selection of the best papers presented at the POSTA 2016, the 5th International Symposium on Positive Systems, which was held in Rome, Italy, in September 2016. This conference series represents a targeted response to the growing need for research that reports on and critically discusses a wide range of topics concerning the theory and applications of positive systems.

Focusing on applications to science and engineering, this book presents the results of the ITN-FP7 SADCO network's innovative research in optimization and control in the following interconnected topics: optimality conditions in optimal control, dynamic programming approaches to optimal feedback synthesis and reachability analysis, and computational developments in model predictive control. The novelty of the book resides in the fact that it has been developed by early career researchers, providing a good balance between clarity and scientific rigor. Each chapter features an introduction addressed to PhD students and some original contributions aimed at specialist researchers. Requiring only a graduate mathematical background, the book is self-contained. It will be of particular interest to graduate and advanced undergraduate students, industrial practitioners and to senior scientists wishing to update their knowledge.

This book presents the proceedings of the 6th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2017), held in Bhubaneswar, Odisha. The event brought together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. The book is divided into two volumes: Information and Decision Sciences, and Intelligent Engineering Informatics. This volume covers broad areas of Information and Decision Sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management & networks, sensor networks, signal processing, wireless networks, protocols & architectures etc. The book also offers a valuable resource for students at the post-graduate level in various engineering disciplines.

This book presents the proceedings of the 6th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2017), held in Bhubaneswar, Odisha. The event brought together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. The book is divided into two volumes: Information and Decision Sciences, and Intelligent Engineering Informatics. This volume covers broad areas of Intelligent Engineering Informatics, with papers exploring both the theoretical and practical aspects of various areas like ANN and genetic algorithms, human-computer interaction, intelligent control optimisation, intelligent e-learning systems, machine learning, mobile computing, multi-agent systems, etc. The book also offers a valuable resource for students at the post-graduate level in various engineering disciplines.

This book presents the proceedings of the Thirteenth International Conference on Dependability and Complex Systems (DepCoS-RELCOMEX), which took place in the Brunow Palace in Poland from 2nd to 6th July 2018. The conference has been organized at the Faculty of Electronics, Wroclaw University of Science and Technology since 2006, and it continues the tradition of two other events: RELCOMEX (1977-89) and Microcomputer School (1985-95). The selection of papers in these proceedings illustrates the broad variety of topics that are investigated in dependability analyses of today's complex systems. Dependability came naturally as a contemporary answer to new challenges in the reliability evaluation of these systems. Such systems cannot be considered only as structures (however complex and distributed) built on the basis of technical resources (hardware): their analysis must take into account a unique blend of interacting people (their needs and behaviours), networks (together with mobile properties, cloud-based systems) and a large number of users dispersed geographically and producing an unimaginable number of applications (working online). A growing number of research methods apply the latest advances in artificial intelligence (AI) and computational intelligence (CI). Today's complex systems are really complex and are applied in numerous different fields of contemporary life.

This book reports on innovative research and developments in the broad field of transportation. It covers solutions relating to intelligent vehicles and infrastructure, energy and combustion management, vehicle dynamics and control, as well as research on human factors, logistics and security. Contributions are based on peer-reviewed papers presented at the 12th international scientific conference "Transbaltica: Transportation Science and Technology", held virtually from Vilnius Gediminas Technical University, Lithuania, on September 16-17, 2021. All in all, this book offers extensive information on modern transport systems, with a good balance of theory and practice.

This book gathers the carefully reviewed proceedings of the 19th International Conference on Systems Science, presenting recent research findings in the areas of Artificial Intelligence, Machine Learning, Communication/Networking and Information Technology, Control Theory, Decision Support, Image Processing and Computer Vision, Optimization Techniques, Pattern Recognition, Robotics, Service Science, Web-based Services, Uncertain Systems and Transportation Systems. The International Conference on Systems Science was held in Wroclaw, Poland from September 7 to 9, 2016, and addressed a range of topics, including systems theory, control theory, machine learning, artificial intelligence, signal processing, communication and information technologies, transportation systems, multi-robotic systems and uncertain systems, as well as their applications. The aim of the conference is to provide a platform for communication between young and established researchers and practitioners, fostering future joint research in systems science.

This brief examines mathematical models in nonsmooth mechanics and nonregular electrical circuits, including evolution variational inequalities, complementarity systems, differential inclusions, second-order dynamics, Lur'e systems and Moreau's sweeping process. The field of nonsmooth dynamics is of great interest to mathematicians, mechanicians, automatic controllers and engineers. The present volume acknowledges this transversality and provides a multidisciplinary view as it outlines fundamental results in nonsmooth dynamics and explains how to use them to study various problems in engineering. In particular, the author explores the question of how to redefine the notion of dynamical systems in light of modern variational and nonsmooth analysis. With the aim of bridging between the communities of applied mathematicians, engineers and researchers in control theory and nonlinear systems, this brief outlines both relevant mathematical proofs and models in unilateral mechanics and electronics.

This edited volume highlights the scientific contributions of Volker Mehrmann, a leading expert in the area of numerical (linear) algebra, matrix theory, differential-algebraic equations and control theory. These mathematical research areas are strongly related and often occur in the same real-world applications. The main areas where such applications emerge are computational engineering and sciences, but increasingly also social sciences and economics. This book also reflects some of Volker Mehrmann's major career stages. Starting out working in the areas of numerical linear algebra (his first full professorship at TU Chemnitz was in "Numerical Algebra," hence the title of the book) and matrix theory, Volker Mehrmann has made significant contributions to these areas ever since. The highlights of these are discussed in Parts I and II of the present book. Often the development of new algorithms in numerical linear algebra is motivated by problems in system and control theory. These and his later major work on differential-algebraic equations, to which he together with Peter Kunkel made many groundbreaking contributions, are the topic of the chapters in Part III. Besides providing a scientific discussion of Volker Mehrmann's work and its impact on the development of several areas of applied mathematics, the individual chapters stand on their own as reference works for selected topics in the fields of numerical (linear) algebra, matrix theory, differential-algebraic equations and control theory.

This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.

This book addresses the application of methods used in statistical physics to complex systems-from simple phenomenological analogies to more complex aspects, such as correlations, fluctuation-dissipation theorem, the concept of free energy, renormalization group approach and scaling. Statistical physics contains a well-developed formalism that describes phase transitions. It is useful to apply this formalism for damage phenomena as well. Fractals, the Ising model, percolation, damage mechanics, fluctuations, free energy formalism, renormalization group, and scaling, are some of the topics covered in Statistical Physics of Phase Transitions.

The objective of Kai Zhang and his research is to assess the existing process monitoring and fault detection (PM-FD) methods. His aim is to provide suggestions and guidance for choosing appropriate PM-FD methods, because the performance assessment study for PM-FD methods has become an area of interest in both academics and industry. The author first compares basic FD statistics, and then assesses different PM-FD methods to monitor the key performance indicators of static processes, steady-state dynamic processes and general dynamic processes including transient states. He validates the theoretical developments using both benchmark and real industrial processes.

The book examines the future deployment of renewable power from a normative point of view. It identifies properties characterizing the cost-optimal transition towards a renewable power system and analyzes the key drivers behind this transition. Among those drivers, particular attention is paid to technological cost reductions and the implications of uncertainty. From a methodological perspective, the main contributions of this book relate to the field of endogenous learning and uncertainty in optimizing energy system models. The primary objective here is closing the gap between the strand of literature covering renewable potential analyses on the one side and energy system modeling with endogenous technological change on the other side. The models applied in this book demonstrate that fundamental changes must occur to transform today's power sector into a more sustainable one over the course of this century. Apart from its methodological contributions, this work is also intended to provide practically relevant insights regarding the long-term competitiveness of renewable power generation.

This book systematically interprets and documents new, unifying principles and basic laws describing the most relevant aspects of hierarchy. To do so, it discusses recent experiments and models that are simple and realistic enough to reproduce the observations, and develops concepts for a better understanding of the complexity of systems consisting of many organisms. The book covers systems ranging from flocks of birds to groups of people. Although it focuses on hierarchical collective behavior in general, two aspects pop up in the majority of cases: collective motion and dynamically changing, partially directed networks (and the natural relation between the two). In addition, it offers a brief description of the most relevant definitions and concepts involved in the context of hierarchies, presenting both a review of the current literature and a number of new experimental and computational results in more detail. It is a valuable resource for students and scholars pursuing research on the structure of interactions within the collectives of animals and humans.

The beginning of the 21st century can be characterized as the" time-delay boom" leading to numerous important results. The purpose of this book is two-fold, to familiarize the non-expert reader with time-delay systems and to provide a systematic treatment of modern ideas and techniques for experts. This book is based on the course "Introduction to time-delay systems" for graduate students in Engineering and Applied Mathematics that the author taught in Tel Aviv University in 2011-2012 and 2012-2013 academic years. The sufficient background to follow most of the material are the undergraduate courses in mathematics and an introduction to control. The book leads the reader from some basic classical results on time-delay systems to recent developments on Lyapunov-based analysis and design with applications to the hot topics of sampled-data and network-based control. The objective is to provide useful tools that will allow the reader not only to apply the existing methods, but also to develop new ones. It should be of interest for researchers working in the field, for graduate students in engineering and applied mathematics, and for practicing engineers. It may also be used as a textbook for a graduate course on time-delay systems.

The advantages of periodic control have been known since humanity learned to cultivate crops in rotation to increase production. In more recent times, it has been recognized that some industrial and technological systems also work or function better in a periodic fashion. Moreover, with periodic control laws it has been possible to solve problems for which no time-invariant solution exists. Periodic models are also able to describe the intrinsic periodicity in many natural phenomena and time series.

Periodic Systems gives a comprehensive treatment of the theory of time-varying dynamical systems with periodic coefficients, including the problems of filtering and control.

Topics covered include:

a [ basic issues, including Floquet theory, controllability and observability, canonical decomposition, system norms and Lyapunov and robust stability;

a [ the problem of state estimation in its various forms, filtering, prediction and smoothing;

a [ control design methods, particularly optimal and robust control.

The text focuses on discrete-time signals and systems; however, an overview of the entire field, including the continuous-time case, is provided in the first chapter. The authorsa (TM) presentation of the theory and results is mathematically rigorous while maintaining a readable style, avoiding excessive formalism. This makes the book accessible to graduate students and researchers from the fields of engineering, physics, economics and mathematics.

The book deals with dynamical systems, generated by linear mappings of finite dimensional spaces and their applications. These systems have a relatively simple structure from the point of view of the modern dynamical systems theory. However, for the dynamical systems of this sort, it is possible to obtain explicit answers to specific questions being useful in applications. The considered problems are natural and look rather simple, but in reality in the course of investigation, they confront users with plenty of subtle questions and their detailed analysis needs a substantial effort. The problems arising are related to linear algebra and dynamical systems theory, and therefore, the book can be considered as a natural amplification, refinement and supplement to linear algebra and dynamical systems theory textbooks.

This book, based on a selection of talks given at a dedicated meeting in Cortona, Italy, in June 2013, shows the high degree of interaction between a number of fields related to applied sciences. Applied sciences consider situations in which the evolution of a given system over time is observed, and the related models can be formulated in terms of evolution equations (EEs). These equations have been studied intensively in theoretical research and are the source of an enormous number of applications. In this volume, particular attention is given to direct, inverse and control problems for EEs. The book provides an updated overview of the field, revealing its richness and vitality.

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.