This book contains all refereed papers accepted during the tenth edition of the conference that took place at the Cite Internationale Universitaire de Paris on December 12-13, 2019. Mastering complex systems requires an integrated understanding of industrial practices as well as sophisticated theoretical techniques and tools. This explains the creation of an annual go-between forum in Paris dedicated to academic researchers & industrial actors working on complex industrial systems architecture, modeling & engineering. These proceedings cover the most recent trends in the emerging field of Complex Systems, both from an academic and a professional perspective. A special focus is put on "Systems Engineering through the ages". The CSD&M Paris 2019 conference is organized under the guidance of CESAM Community. It has been developed since 2010 by the non-profit organization CESAMES Association to organize the sharing of good practices in Enterprise and Systems Architecture and to certify the level of knowledge and proficiency in this field through CESAM certification.

This book is for anyone who wants to gain an understanding of Blockchain technology and its potential. The book is research-oriented and covers different verticals of Blockchain technology. It discusses the characteristics and features of Blockchain, includes techniques, challenges, and future trends, along with case studies for deeper understanding. Blockchain Technology: Exploring Opportunities, Challenges, and Applications covers the core concepts related to Blockchain technology starting from scratch. The algorithms, concepts, and application areas are discussed according to current market trends and industry needs. It presents different application areas of industry and academia and discusses the characteristics and features of this technology. It also explores the challenges and future trends and provides an understanding of new opportunities. This book is for anyone at the beginner to intermediate level that wants to learn about the core concepts related to Blockchain technology.

The proceedings collect the latest research trends, methods and experimental results in the field of electrical and information technologies for rail transportation. The topics cover intelligent computing, information processing, communication technology, automatic control, and their applications in rail transportation etc. The proceedings can be a valuable reference work for researchers and graduate students working in rail transportation, electrical engineering and information technologies.

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

Provides essential insight on uses of different AI techniques for pattern recognition, classification, prediction and estimation, exclusive to power system protection issues Presents introduction to enhanced electricity system analysis using decision-making tools Covers AI Applications in different protective relaying functions Discusses Issues and challenges in the protection of transmission and distribution systems Includes dedicated chapter on case studies, and applications

This book explores the design of optimal trajectories for space maneuver vehicles (SMVs) using optimal control-based techniques. It begins with a comprehensive introduction to and overview of three main approaches to trajectory optimization, and subsequently focuses on the design of a novel hybrid optimization strategy that combines an initial guess generator with an improved gradient-based inner optimizer. Further, it highlights the development of multi-objective spacecraft trajectory optimization problems, with a particular focus on multi-objective transcription methods and multi-objective evolutionary algorithms. In its final sections, the book studies spacecraft flight scenarios with noise-perturbed dynamics and probabilistic constraints, and designs and validates new chance-constrained optimal control frameworks. The comprehensive and systematic treatment of practical issues in spacecraft trajectory optimization is one of the book's major features, making it particularly suited for readers who are seeking practical solutions in spacecraft trajectory optimization. It offers a valuable asset for researchers, engineers, and graduate students in GNC systems, engineering optimization, applied optimal control theory, etc.

Data science is an emerging field and innovations in it need to be explored for the success of society 5.0. This book not only focuses on the practical applications of data science to achieve computational excellence, but also digs deep into the issues and implications of intelligent systems. This book highlights innovations in data science to achieve computational excellence that can optimize performance of smart applications. The book focuses on methodologies, framework, design issues, tools, architectures, and technologies necessary to develop and understand data science and its emerging applications in the present era. Data Science and Innovations for Intelligent Systems: Computational Excellence and Society 5.0 is useful for the research community, start-up entrepreneurs, academicians, data-centered industries, and professeurs who are interested in exploring innovations in varied applications and the areas of data science.

Learning by Doing with National Instruments Development Boards starts with a brief introduction to LabVIEW programming, which is required to explore the National Instrument platform, an introduction that includes detailed installation and licensing setup. Further, it gives the features and configuration setup of NI SPEEDY-33, NI ELVIS and myRIO boards. The focus of the book is on worked-out case studies for students working in different areas of electronics such as basic digital design, biomedical instrumentation, sensors and measurement. Data acquisition using SPEEDY-33, NI -ELVIS and myRIO kits is also odiscussed. The book also examines the myRIO platform.

- Ties together the three (now) competing modern disciplines in Program and Project Management - Tells you how to do it, not just some theory based on a one of a kind project - Provides clear and concise definitions for the three disciplines helping with career choices, separation of duties and when to use - Perfect desktop reference usable for many years to come

The insertion of communication networks in feedback control loops complicates analysis and synthesis of cyber-physical systems (CPSs), and network-induced uncertainties may degrade system control performance. Thus, this book researches networked delay compensation and event-triggered control approaches for a series of CPSs subject to network-induced uncertainties. The authors begin with an introduction to the concepts and challenges of CPSs, followed by an overview of networked control approaches and event-triggered control strategies in CPSs. Then, networked delay compensation and event-triggered control approaches are proposed for CPSs with network communication delay, data dropout, signal quantization, and event-triggered communication. More specifically, networked delay compensation approaches are proposed for linear/nonlinear networked controlled plants with time-varying and random network communication delays and data dropouts. To reduce computational burden and network communication loads in CPSs, event-triggered control, self-triggered control, co-design of event-triggered control and quantized control techniques, and event-triggered disturbance rejection control approaches are also presented. This book is an essential text for researchers and engineers interested in cybersecurity, networked control, and CPSs. It would also prove useful for graduate students in the fields of science, engineering, and computer science.

- Ties together the three (now) competing modern disciplines in Program and Project Management - Tells you how to do it, not just some theory based on a one of a kind project - Provides clear and concise definitions for the three disciplines helping with career choices, separation of duties and when to use - Perfect desktop reference usable for many years to come

Dynamics is what characterizes virtually all phenomenae we face in the real world, and processes that proceed in practically all kinds of inanimate and animate systems, notably social systems. For our purposes dynamics is viewed as time evolution of some characteristic features of the phenomenae or processes under consideration. It is obvious that in virtually all non-trivial problems dynamics can not be neglected, and should be taken into account in the analyses to, first, get insight into the problem consider, and second, to be able to obtain meaningful results.

A convenient tool to deal with dynamics and its related evolution over time is to use the concept of a dynamic system which, for the purposes of this volume can be characterized by the input (control), state and output spaces, and a state transition equation. Then, starting from an initial state, we can find a sequence of consecutive states (outputs) under consecutive inputs (controls). That is, we obtain a trajectory. The state transition equation may be given in various forms, exemplified by differential and difference equations, linear or nonlinear, deterministic or stochastic, or even fuzzy (imprecisely specified), fully or partially known, etc. These features can give rise to various problems the analysts may encounter like numerical difficulties, instability, strange forms of behavior (e.g. chaotic), etc.

This volume is concerned with some modern tools and techniques which can be useful for the modeling of dynamics. We focus our attention on two important areas which play a key role nowadays, namely automation and robotics, and biological systems. We also add some new applications which can greatly benefit from the availability of effective and efficient tools for modeling dynamics, exemplified by some applications in security systems.

This book presents the entire body of thought of Norbert Wiener (1894-1964), knowledge of which is essential if one wishes to understand and correctly interpret the age in which we live. The focus is in particular on the philosophical and sociological aspects of Wiener's thought, but these aspects are carefully framed within the context of his scientific journey. Important biographical events, including some that were previously unknown, are also highlighted, but while the book has a biographical structure, it is not only a biography. The book is divided into four chronological sections, the first two of which explore Wiener's development as a philosopher and logician and his brilliant interwar career as a mathematician, supported by his philosophical background. The third section considers his research during World War II, which drew upon his previous scientific work and reflections and led to the birth of cybernetics. Finally, the radical post-war shift in Wiener's intellectual path is considered, examining how he came to abandon computer science projects and commenced ceaseless public reflections on the new sciences and technologies of information, their social effects, and the need for responsibility in science.

Provides a proficient guide on the relationship between AI and healthcare and how AI is changing all aspects of the health care industry Covers how deep learning will help in the diagnosis and the prediction of disease spread Presents a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing Highlights various challenges in applying the deep learning in health care Promotes research in deep learning application in understanding the biomedical process

This book focuses on the development of three novel approaches to build up a framework for the frequency domain analysis and design of nonlinear systems. The concepts are derived from Volterra series representation of nonlinear systems which are described by nonlinear difference or differential equations. Occupying the middle ground between traditional linear approaches and more complex nonlinear system theories, the book will help readers to have a good start to analyse and exploit the nonlinearities. Analysis and Design of Nonlinear Systems in the Frequency Domain provides clear illustrations and examples at the beginning and the end of each chapter, respectively, making it of interest to both academics and practicing engineers.

Provides insight into the skill set that requires leveraging strength to move further to act as a good data analyst Discusses how big data along with deep learning holds the potential to significantly increase data understanding and in turn, helps to make decisions Covers the numerous potential applications in healthcare, education, communications, media, and the entertainment industry Offers innovative platforms for integrating big data and deep learning Presents issues related to adequate data storage, sematic indexing, data tagging, and fast information retrieval from big data

Examines how digital media and the creation of digital immortals may affect religious understandings of death and the afterlife; Understands the impact of digital media on those living and those working with the bereaved; Explores the impact of digital memorialisation post death; Looks at the ways in which digital media may be changing conceptions and theologies of death

1) Focuses on the concepts and implementation strategies of various Deep Learning algorithms through properly curated examples. 2) The subject area will be valid for the next 10 years or so, as Deep Learning theory/algorithms and their applications will not be outdated easily. Hence there will be demand for such a book in the market. 3) In comparison to other titles, this book rigorously covers mathematical and conceptual details of relevant topics.

Takes the reader on a journey across three broad developments in safety science Focuses on the individual including human error, risk, and the role of cognition in human performance Includes research in safety science that uses organizations as the basic unit of analysis Discusses questions about organizational decision making and the characteristics that dispose towards or against organizational failure Introduces perspectives based on systems science that address issues that arise out of complexity and interdependence

Explains concepts of Internet of Everything problems, research challenge goals, and vision in smart cities Based on the most recent innovations, and covering the major challenges in smart cities, between IoT and Big Data Examines security issues and challenges related to data-intensive advances in IoT Addresses the total information science challenges in Internet of Everything enabled technologies Covers the exploring and creating IoT environment related self-adaptive systems

This monograph focuses on the mathematical modeling of distributed parameter systems in which mass/energy transport or wave propagation phenomena occur and which are described by partial differential equations of hyperbolic type. The case of linear (or linearized) 2 x 2 hyperbolic systems of balance laws is considered, i.e., systems described by two coupled linear partial differential equations with two variables representing physical quantities, depending on both time and one-dimensional spatial variable. Based on practical examples of a double-pipe heat exchanger and a transportation pipeline, two typical configurations of boundary input signals are analyzed: collocated, wherein both signals affect the system at the same spatial point, and anti-collocated, in which the input signals are applied to the two different end points of the system. The results of this book emerge from the practical experience of the author gained during his studies conducted in the experimental installation of a heat exchange center as well as from his research experience in the field of mathematical and computer modeling of dynamic systems. The book presents valuable results concerning their state-space, transfer function and time-domain representations, which can be useful both for the open-loop analysis as well as for the closed-loop design. The book is primarily intended to help professionals as well as undergraduate and postgraduate students involved in modeling and automatic control of dynamic systems.

In many practical applications we deal with a wide class of dynamical systems that are comprised of a family of continuous-time or discrete-time subsystems and a rule orchestrating the switching between the subsystems. This class of systems is frequently called switched system. Switched linear systems provide a framework that bridges the linear systems and the complex and/or uncertain systems. The mo- vation for investigating this class of systems is twofold: ?rst, it has an inherent multi-modal behavior in the sense that several dynamical subsystems are required to describe their behavior, which might depend on various environmental factors. Second, the methods of intelligent control systems are based on the idea of swit- ing between different controllers. Looked at in this light, switched systems provide an integral framework to deal with complex system behaviors such as chaos and multiple limit cycles and gain more insights into powerful tools such as intelligent control, adaptive control, and robust control. Switched systems have been inves- gated for a long time in the control and systems literature and have increasingly attracted more attention for the past three decades. The number of journal articles, books, and conference papers have grown exponentially and a number of fundam- tal concepts and powerful tools have been developed. It has been pointed out that switched systems have been studied from various viewpoints.

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction of data analysis. It includes many recent supervised and unsupervised machine learning methodologies such as recursive partitioning modelling, regularized regression, support vector machine, neural network, clustering, and causal-effect inference. Additionally, it emphasizes statistical thinking of data analysis, use of statistical graphs for data structure exploration, and result presentations. The book includes many real-world data examples from life-science, finance, etc. to illustrate the applications of the methods described therein. Key Features: Contains statistical theory for the most recent supervised and unsupervised machine learning methodologies. Emphasizes broad statistical thinking, judgment, graphical methods, and collaboration with subject-matter-experts in analysis, interpretation, and presentations. Written by statistical data analysis practitioner for practitioners. The book is suitable for upper-level-undergraduate or graduate-level data analysis course. It also serves as a useful desk-reference for data analysts in scientific research or industrial applications.

Provides the details of state-of-the-art machine learning methods used in VLSI Design. Discusses hardware implementation and device modeling pertaining to machine learning algorithms. Explores machine learning for various VLSI architectures and reconfigurable computing. Illustrate latest techniques for device size and feature optimization. Highlight latest case studies and reviews of the methods used for hardware implementation.