This volume provides the international multibody dynamics community with an up-to-date view on the state of the art in this rapidly growing field of research which now plays a central role in the modeling, analysis, simulation and optimization of mechanical systems in a variety of fields and for a wide range of industrial applications.

This book contains selected contributions delivered at the ECCOMAS Thematic Conference on Multibody Dynamics, which was held in Brussels, Belgium and organized by the Universite catholique de Louvain, from 4th to 7th July 2011. Each paper reflects the State-of-Art in the application of Multibody Dynamics to different areas of engineering. They are enlarged and revised versions of the communications, which were enhanced in terms of self-containment and tutorial quality by the authors. The result is a comprehensive text that constitutes a valuable reference for researchers and design engineers which helps to appraise the potential for the application of multibody dynamics methodologies to a wide range of areas of scientific and engineering relevance.

"

This book is the first research collection by the Malaysian Society for Automatic Control Engineers (MACE). Numerous applications of control engineering, sensor, and instrumentation technology in robotics, industrial automation, and other mechatronic systems are presented in this book. The book begins by introducing control engineering in robotics and industrial automation. It progresses through a series of chapters, discussing the application of control engineering in various areas such as: brake-by-wire technology; web scrubber systems; robot localization; and, autonomous navigation systems. Coverage of swarm robotics behaviors and applications of sensor technology in the field of music, biomedical technology, and structural analysis takes the book beyond its core of mechatronic systems and demonstrates a more diverse application of the ideas it presents. Each chapter provides comprehensive and detailed coverage of the main ideas, design methods, and practical needs of its chosen topic, making this book accessible and useful to researchers, engineers, postgraduates, and undergraduate students.

This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation. The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.

Unique selling point: Combines theory with practice and applications for advanced intelligent healthcare informatics Core audience: Researchers and academics in healthcare informatics and machine learning Place in the market: Reference work

Smart shipping is a future method for transporting ocean cargo and exploring the resources of oceans for medical drugs, food, energy resources, and other products. A smart ship is an integration of shipping with many fields such as fishing, manufacturing, navigation, communication, computing, control, sensing, etc., to provide better shipping and services. The purpose of this edited book is to provide state-of-the-art approaches and novel technologies for smart ships, covering a range of topics in these areas so that it will be an excellent reference book for the researchers, students, and professionals in these areas. It presents the fundamental technologies needed to build smart ships, and gives a clear explanation of them. This book will serve as a good reference for researchers to know the state of the art and to discover uncovered territory and develop new applications, as well as being a guideline for building future smart ships. Yang Xiao is a Full Professor in the Department of Computer Science at the University of Alabama, Tuscaloosa, Alabama, USA. Tieshan Li is a Full Professor in the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China.

This book highlights the recent research advances in the area of operation, management and control of electricity distribution networks. It addresses various aspects of distribution network management, including operation, customer engagement and technology accommodation. Electricity distribution networks are an important part of the power delivery system, and the smart control and management of distribution networks is vital in order to satisfy technical, economic, and customer requirements. A new management philosophy, techniques, and methods are essential to handle uncertainties, security, and stability associated with the integration of renewable-based distributed generation units, demand forecast and customer needs. This book discusses these topics in the context of managing the capacity of distribution networks while addressing the future needs of electricity systems. Furthermore, the efficient and economic operation of distribution networks is an essential part of management of system for effective use of resources, and as such the also addresses operation and control approaches and techniques suitable for future distribution networks.

This book presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. Written as a guide for assessing the roles that these techniques play, the book also highlights implementation strategies, lists problem-solving solutions, and paves the way for future research endeavors in smart and next-generation healthcare systems. This book provides applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles that various techniques, such as machine learning, fuzzy logic, and statical mathematics, play in the advancements of smart healthcare systems. The book presents the basics as well as the advanced concepts to help beginners, as well as industry professionals, get up to speed on the latest developments in healthcare systems. The book examines descriptive, predictive, and social network techniques and discusses analytical tools and the important role they play in finding solutions to problems in healthcare systems. A framework of robust and novel healthcare techniques is highlighted, as well as implementation strategies and a setup for future research endeavors. Healthcare Systems Using Soft Computing Techniques is a valuable resource for researchers and postgraduate students in healthcare systems engineering, computer science, information technology, and applied mathematics. The book introduces beginners to-and at the same time brings industry professionals up to speed with-the important role soft computing techniques play in smart healthcare systems.

The proposed book provides a comprehensive coverage of theory and methods in the areas of continuous optimization and variational inequality. It describes theory and solution methods for optimization with smooth and non-smooth functions, for variational inequalities with single-valued and multivalued mappings, and for related classes such as mixed variational inequalities, complementarity problems, and general equilibrium problems. The emphasis is made on revealing generic properties of these problems that allow creation of efficient solution methods. Salient Features The book presents a deep, wide-ranging introduction to the theory of the optimal control of processes governed by optimization techniques and variational inequality Several solution methods are provided which will help the reader to develop various optimization tools for real-life problems which can be modeled by optimization techniques involving linear and nonlinear functions. The book focuses on most recent contributions in the nonlinear phenomena, which can appear in various areas of human activities. This book also presents relevant mathematics clearly and simply to help solve real life problems in diverse fields such as mechanical engineering, management, control behavior, traffic signal, industry, etc. This book is aimed primarily at advanced undergraduates and graduate students pursuing computer engineering and electrical engineering courses. Researchers, academicians and industry people will also find this book useful.

This book statistically confirms that complexity and changing technologies that affect the way operators interact within the systems of the nuclear facili-ties exacerbate the severity of incidents caused by human error and details the application of the systems engineering process to reduce human error given industries' rapidly advancing technology. Technology, Human Performance, and Nuclear Facilities: A Systems Engineering Approach to Reduce Human Error provides a basic understand-ing of Human Error/ P erformance and its relation to industrial operations and advancing technologies incorporated into facilities. The book discusses the context surrounding the complexity of changing technologies at nuclear facili-ties and the potential worsening of problems caused by human error when technology advancements concerning operator interaction with control sys-tems are implemented. It presents how to reduce human error propensity given the incorporation of advanced technology and covers ways to reduce human error using the systems engineering process. Also offered are several concepts related to the operator's involvement in the systems engineering process and the human performance integration with system operational requirements and system testing, evaluation, and validation, and the procedures and training development in the systems engineering process. This book presents empirical evidence for the importance of human performance management in the con-text of nuclear facilities and offers practical recommendations for the improve-ment of this function. Systems engineers, plant/ design engineers, the nuclear industry, plant operations management, and those involved in industrial and nuclear safety will find something of interest in this book.

Human Action Recognition is a challenging area presently. The vigor of research effort directed towards this domain is self indicative of this. With the ever-increasing involvement of Computational Intelligence in our day to day applications, the necessity of human activity recognition has been able to make its presence felt to the concerned research community. The primary drive of such an effort is to equip the computing system capable of recognizing and interpreting human activities from posture, pose, gesture, facial expression etc. The intent of human activity recognition is a formidable component of cognitive science in which researchers are actively engaged of late. Features: A systematic overview of the state-of-the-art in computational intelligence techniques for human action recognition. Emphasized on different intelligent techniques to recognize different human actions. Discussed about the automation techniques to handle human action recognition. Recent research results and some pointers to future advancements in this arena. In the present endeavour the editors intend to come out with a compilation that reflects the concerns of relevant research community. The readers would be able to come across some of the latest findings of active researchers of the concerned field. It is anticipated that this treatise shall be useful to the readership encompassing students at undergraduate and postgraduate level, researchers active as well as aspiring, not to speak of the senior researchers.

The processing of medical images in a reasonable timeframe and with high definition is very challenging. This volume helps to meet that challenge by presenting a thorough overview of medical imaging modalities, its processing, high-performance computing, and the need to embed parallelism in medical image processing techniques to achieve efficient and fast results. With contributions from researchers from prestigious laboratories and educational institutions, High-Performance Medical Image Processing provides important information on medical image processing techniques, parallel computing techniques, and embedding parallelism in different image processing techniques. A comprehensive review of parallel algorithms in medical image processing problems is a key feature of this book. The volume presents the relevant theoretical frameworks and the latest empirical research findings in the area and provides detailed descriptions about the diverse high-performance techniques. Topics discussed include parallel computing, multicore architectures and their applications in image processing, machine learning applications, conventional and advanced magnetic resonance imaging methods, hyperspectral image processing, algorithms for segmenting 2D slices for 3D viewing, and more. Case studies, such as on the detection of cancer tumors, expound on the information presented. Key features: Provides descriptions of different medical imaging modalities and their applications Discusses the basics and advanced aspects of parallel computing with different multicore architectures Expounds on the need for embedding data and task parallelism in different medical image processing techniques Presents helpful examples and case studies of the discussed methods This book will be valuable for professionals, researchers, and students working in the field of healthcare engineering, medical imaging technology, applications in machine and deep learning, and more. It is also appropriate for courses in computer engineering, biomedical engineering and electrical engineering based on artificial intelligence, parallel computing, high performance computing, and machine learning and its applications in medical imaging.

The primary goal of this book is to address the issues faced by teachers in the adoption of digital tools into their teaching and their students learning. This book also addresses the issues confronting educators in the integration of digital technologies into their teaching and their students' learning. Such issues include a skepticism of the added value of technology to educational learning outcomes, the perception of the requirement to keep up with the fast pace of technological innovation, a lack of knowledge of affordable educational digital tools and a lack of understanding of pedagogical strategies to embrace digital technologies in their teaching. This book presents theoretical perspectives of learning and teaching today's digital students with technology and proposes a pragmatic and sustainable framework for teachers' professional learning to embed digital technologies into their repertoire of teaching strategies in a systematic, coherent and comfortable manner so that technology integration becomes an almost effortless pedagogy in their day-to-day teaching. Some of the objectives are given below: Shares valuable insights into the influence of technology on teaching and learning in higher education Provides deeper insights on higher education and sustainability interact Studies innovations from various perspectives Investigates how the educators and students apply the unique innovative and emotional dimensions in modern age of learning Provides a timely overview of changes in education reforms and policy research globally Evaluates the problematic relationship between globalization, the state, and education reforms.

This book is about the behaviour of systems. Systems are important, for we interact with them all the time, and many of the actions we take are influenced by a system - for example, the system of performance measures in an organisation influences, often very strongly, how individuals within that organisation behave. Furthermore, sometimes we are involved in the design of systems, as is any manager contributing to the definition of what those performance measures might be. That manager will want to ensure that all the proposed performance measures will drive the 'right' behaviours rather than (inadvertently) encouraging dysfunctional 'game playing', and so anticipating how the performance measurement system will work in practice is a vital part of a wise design process. Some of the systems with which we interact are local, such as your organisation's performance measurement system. Some systems, however, are distant, but nonetheless very real, such as the healthcare system, the education system, the legal system and the climate system. Systems, therefore, exist on all scales, from the local to the global. And all systems are complex, some hugely so. That's why understanding how systems behave can be very helpful. Systems are complex for two main reasons. First, the manner in which they behave over time can be very hard to anticipate - and anticipating the future sensibly is of course a key objective of management. Second, the 'entities' within a system can be connected together in very complex ways, so that an intervention 'here' can result in an effect 'there', perhaps a long time afterward. Sometimes this can be surprising, and so we talk of 'unintended consequences' - but this is of course a euphemism for 'because I didn't understand how this system behaves, I had not anticipated that'. Systems thinking, the subject matter of this book, is the disciplined study of systems, and causal loop diagrams - the 'pictures' of this 'picture book' - are a very insightful way to represent the connectedness of the entities from which any system is composed, so taming that system's complexity.

Unique selling point: * Brings together insights on various fields, and how IoT and AI combined can help bring about sustainable living Core audience: * Researchers and academics - worldwide applicability Place in the market: * Gives a more comprehensive overview of the potential applications of IoT and AI for sustainability than other books on the market

Introduces performance indicators in a self-controlled Permanent Magnet Synchronous Motor (PMSM) machine to justify the dynamic behavior Discusses comparative performance study and optimization of the drive performance Provides detailed comparative performance analysis between classical and fuzzy logic controllers in a PMSM drive Includes illustrations and case studies using mathematical modeling and real-time test-results Discusses state of the art on solar powered energy efficient PMSM drive with various issues

Helps readers to transition from traditional statistics to modern data science Reviews the pros and cons of open source and commercial software packages, and their proper applications in specific situations. Explores data using dynamic methods rather than counting on dichotomous thinking. Considers alternate models using ensemble models and model comparison rather than fixing a preconceived hypothesis/model on a single method. Shows how to find the hidden pattern in the data by dynamic visualization rather than over-relying on numeric results.

In this book, the authors write about creativity in teaching and how to enhance creativity in learners. They highlight the new reality of teaching and learning in the digital era, specifically the impact of artificial intelligence, data economy, and artificial minds on modern teaching practices, curriculum design, and the role of teachers in classrooms. Creativity in Teaching and Teaching for Creativity: Modern Practices in the Digital Era approaches human intelligence as a universal gift. It emphasizes that the creativity of human beings is not only a natural quality, but one that can be enhanced as a result of learning. The book suggests new teaching models and approaches and discusses how the role of teachers in the classroom has fundamentally changed, emphasizing the emotional connection between students and teachers. The book will find interest among higher education policymakers who believe in the transformation of the education industry, research scholars who are pursuing their Ph.D. in the fields of education technology and education and learning, as well as those working in the area of education technology and artificial intelligence.

Blockchain for IoT provides the basic concepts of Blockchain technology and its applications to varied domains catering to socio-technical fields. It also introduces intelligent Blockchain platforms by way of infusing elements of computational intelligence into Blockchain technology. With the help of an interdisciplinary approach, it includes insights into real-life IoT applications to enable the readers to assimilate the concepts with ease. This book provides a balanced approach between theoretical understanding and practical applications. Features: A self-contained approach to integrating the principles of Blockchain with elements of computational intelligence A rich and novel foundation of Blockchain technology with reference to the internet of things conjoined with the tenets of artificial intelligence in yielding intelligent Blockchain platforms Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Information presented in an accessible way for research students of computer science and information technology, as well as software professionals who can inherit the much-needed developmental ideas to boost up their computing knowledge on distributed platforms This book is aimed primarily at undergraduates, postgraduates, and researchers studying Blockchain.

This book presents the state of the art, challenges and future trends in automotive software engineering. The amount of automotive software has grown from just a few lines of code in the 1970s to millions of lines in today's cars. And this trend seems destined to continue in the years to come, considering all the innovations in electric/hybrid, autonomous, and connected cars. Yet there are also concerns related to onboard software, such as security, robustness, and trust. This book covers all essential aspects of the field. After a general introduction to the topic, it addresses automotive software development, automotive software reuse, E/E architectures and safety, C-ITS and security, and future trends. The specific topics discussed include requirements engineering for embedded software systems, tools and methods used in the automotive industry, software product lines, architectural frameworks, various related ISO standards, functional safety and safety cases, cooperative intelligent transportation systems, autonomous vehicles, and security and privacy issues. The intended audience includes researchers from academia who want to learn what the fundamental challenges are and how they are being tackled in the industry, and practitioners looking for cutting-edge academic findings. Although the book is not written as lecture notes, it can also be used in advanced master's-level courses on software and system engineering. The book also includes a number of case studies that can be used for student projects.

The book provides insights of International Conference in Communication, Devices and Networking (ICCDN 2017) organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India during 3 - 4 June, 2017. The book discusses latest research papers presented by researchers, engineers, academicians and industry professionals. It also assists both novice and experienced scientists and developers, to explore newer scopes, collect new ideas and establish new cooperation between research groups and exchange ideas, information, techniques and applications in the field of electronics, communication, devices and networking.

Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML

This book discusses the Sliding Mode Control (SMC) problems of networked control systems (NCSs) under various communication protocols including static/dynamic/periodic event-triggered mechanism, and stochastic communication, Round-Robin, weighted try-once-discard, multiple-packet transmission, and the redundant channel transmission protocol. The super-twisting algorithm and the extended-state-observer-based SMC scheme are described in this book for suppressing chattering. Besides, the SMC designs for two-dimensional (1-D) and two-dimensional (2-D) NCSs are illustrated as well. Features: Captures recent advances of theories, techniques, and applications of networked sliding mode control from an engineering-oriented perspective. Includes new design ideas and optimization techniques of networked sliding mode control theory. Provides advanced tools to apply networked sliding mode control techniques in the practical applications. Discusses some new tools to the engineering applications while dealing with the model uncertainties and external disturbances. This book aims at Researchers and professionals in Control Systems, Computer Networks, Internet of Things, and Communication Systems.

This monograph provides the reader with a systematic treatment of robust filter design, a key issue in systems, control and signal processing, because of the fact that the inevitable presence of uncertainty in system and signal models often degrades the filtering performance and may even cause instability. The methods described are therefore not subject to the rigorous assumptions of traditional Kalman filtering. The monograph is concerned with robust filtering for various dynamical systems with parametric uncertainties and focuses on parameter-dependent approaches to filter design. Classical filtering schemes, like "H"2 filtering and "H"Y filtering, are addressed and emerging issues such as robust filtering with constraints on communication channels and signal frequency characteristics are discussed. The text features:

. design approaches to robust filters arranged according to varying complexity level and emphasizing robust filtering in the parameter-dependent framework for the first time;

. guidance on the use of special realistic phenomena or factors to describe problems more accurately and to improve filtering performance;

. a unified linear matrix inequality formulation of design approaches for easy and effective filter design;

. demonstration of the techniques of matrix decoupling technique, the generalized Kalman Yakubovich Popov lemma, the free weighting matrix technique and the delay modelling approach, in robust filtering;

. numerous easy-to-follow simulation examples, graphical and tabular illustrations to help the reader understand the filter design approaches developed; and

. an account of emerging issues on robust filtering for research to inspire future investigation.

"Robust Filtering for Uncertain Systems" will be of interest to academic researchers specializing in linear, robust and optimal control and estimation and to practitioners working in tracking and network control or signal filtering, detection and estimation. Graduate students learning control and systems theory, signal processing or applied mathematics will also find the book to be a valuable resource.

"

This book introduces the reader to a novel method of mathematical description, analysis and design of digital control systems, which makes it possible to take into account, in the most complete form, specific features of interaction between continuous-time and discrete time processes.