Despite increasing scholarly attention to artificial intelligence (AI), studies at the intersection of AI and communication remain ripe for exploration, including investigations of the social, political, cultural, and ethical aspects of machine intelligence, interactions among agents, and social artifacts. This book tackles these unexplored research areas with special emphasis on conditions, components, and consequences of cognitive, attitudinal, affective, and behavioural dimensions toward communication and AI. In doing so, this book epitomizes communication, journalism and media scholarship on AI and its social, political, cultural, and ethical perspectives. Topics vary widely from interactions between humans and robots through news representation of AI and AI-based news credibility to privacy and value toward AI in the public sphere. Contributors from such countries as Brazil, Netherland, South Korea, Spain, and United States discuss important issues and challenges in AI and communication studies. The collection of chapters in the book considers implications for not only theoretical and methodological approaches, but policymakers and practitioners alike. The chapters in this book were originally published as a special issue of Communication Studies.

Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders' attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system's ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.

The Department of Architecture at ETH Zurich has been researching the integration of robots into the architectural practice, both in design and the fabrication process, for some time. This book-created in collaboration with the chair of Christophe Girot, Gramazio Kohler Research, and Marco Hutter at ETH Zurich's Robotic Systems Lab-is the first to investigate the use of robot-based construction equipment for large-scale soil grading in landscape architecture. As landscapes are continuously changing due to ever-changing environmental conditions, the application of autonomous systems that respond to the environment rather than perform predefined and static earthwork is of particular interest in this field. Robotic Landscapes sheds light on a series of groundbreaking experiments in an interdisciplinary collaboration of landscape design, environmental engineering, and robotics that aims to make landscape architecture sustainable and ecological in the long term.

A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference. While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art. Features: Contributions by leading researchers from a range of disciplines Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications Balanced coverage of concepts, theory, methods, examples, and applications Chapters can be read mostly independently, while cross-references highlight connections The handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models.

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables. Sufficient Dimension Reduction: Methods and Applications with R introduces the basic theories and the main methodologies, provides practical and easy-to-use algorithms and computer codes to implement these methodologies, and surveys the recent advances at the frontiers of this field. Features Provides comprehensive coverage of this emerging research field. Synthesizes a wide variety of dimension reduction methods under a few unifying principles such as projection in Hilbert spaces, kernel mapping, and von Mises expansion. Reflects most recent advances such as nonlinear sufficient dimension reduction, dimension folding for tensorial data, as well as sufficient dimension reduction for functional data. Includes a set of computer codes written in R that are easily implemented by the readers. Uses real data sets available online to illustrate the usage and power of the described methods. Sufficient dimension reduction has undergone momentous development in recent years, partly due to the increased demands for techniques to process high-dimensional data, a hallmark of our age of Big Data. This book will serve as the perfect entry into the field for the beginning researchers or a handy reference for the advanced ones. The author Bing Li obtained his Ph.D. from the University of Chicago. He is currently a Professor of Statistics at the Pennsylvania State University. His research interests cover sufficient dimension reduction, statistical graphical models, functional data analysis, machine learning, estimating equations and quasilikelihood, and robust statistics. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association. He is an Associate Editor for The Annals of Statistics and the Journal of the American Statistical Association.

Probability Methods for Cost Uncertainty Analysis: A Systems Engineering Perspective, Second Edition gives you a thorough grounding in the analytical methods needed for modeling and measuring uncertainty in the cost of engineering systems. This includes the treatment of correlation between the cost of system elements, how to present the analysis to decision-makers, and the use of bivariate probability distributions to capture joint interactions between a system's cost and schedule. Analytical techniques from probability theory are stressed, along with the Monte Carlo simulation method. Numerous examples and case discussions illustrate the practical application of theoretical concepts. While the original chapters from the first edition remain unchanged, this second edition contains new material focusing on the application of theory to problems encountered in practice. Highlights include the use of GERM to build development and production cost estimating relationships as well as the eSBM, which was developed from a need in the community to offer simplified analytical alternatives to advanced probability-based approaches. The book also lists the major technical works of the late Dr. Stephen A. Book, a mathematician and world-renowned cost analyst whose contributions advanced the theory and practice of cost risk analysis.

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs) classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.

The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized twin SVMs for binary classification problems, SVMs for solving multi-classification problems based on ordinal regression, SVMs for semi-supervised problems, and SVMs for problems with perturbations.

To improve readability, concepts, methods, and results are introduced graphically and with clear explanations. For important concepts and algorithms, such as the Crammer-Singer SVM for multi-class classification problems, the text provides geometric interpretations that are not depicted in current literature.

Enabling a sound understanding of SVMs, this book gives beginners as well as more experienced researchers and engineers the tools to solve real-world problems using SVMs.

In Optical Nano and Micro Actuator Technology, leading engineers, material scientists, chemists, physicists, laser scientists, and manufacturing specialists offer an in-depth, wide-ranging look at the fundamental and unique characteristics of light-driven optical actuators. They discuss how light can initiate physical movement and control a variety of mechanisms that perform mechanical work at the micro- and nanoscale. The book begins with the scientific background necessary for understanding light-driven systems, discussing the nature of light and the interaction between light and NEMS/MEMS devices. It then covers innovative optical actuator technologies that have been developed for many applications. The book examines photoresponsive materials that enable the design of optically driven structures and mechanisms and describes specific light-driven technologies that permit the manipulation of micro- and nanoscale objects. It also explores applications in optofluidics, bioMEMS and biophotonics, medical device design, and micromachine control. Inspiring the next generation of scientists and engineers to advance light-driven technologies, this book gives readers a solid grounding in this emerging interdisciplinary area. It thoroughly explains the scientific language and fundamental principles, provides a holistic view of optical nano and micro actuator systems, and illustrates current and potential applications of light-driven systems.

Swarm Intelligence: Principles, Advances, and Applications delivers in-depth coverage of bat, artificial fish swarm, firefly, cuckoo search, flower pollination, artificial bee colony, wolf search, and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization, addressing basic concepts related to swarm intelligence, such as randomness, random walks, and chaos theory. The text then: Describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possible Discusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizers Depicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function design Details the similarities, differences, weaknesses, and strengths of each swarm optimization method Draws parallels between the operators and searching manners of the different algorithms Swarm Intelligence: Principles, Advances, and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods, complete with illustrative examples and an extendable MATLAB (R) package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals, and offers experts valuable insight into new directions and hybridizations.

Engineering technology development and implementation play an important role in making the industry more sustainable in an increasingly competitive world. This book covers significant recent developments in both fundamental and applied research in the engineering field. Domains of application include, but are not limited to, Intelligent Control Systems and Optimization, Signal Processing, Sensors, Systems Modeling and Control, Robotics and Automation, Industrial and Electric Engineering, Production and Management. This book is an excellent reference work to get up to date with the latest research and developments in the fields of Automation, Mechatronics and Industrial Engineering. It aims to provide a platform for researchers and professionals in all relevant fields to gain new ideas and establish great achievements in scientific development.

Human-Robot Interaction in Social Robotics explores important issues in designing a robot system that works with people in everyday environments. Edited by leading figures in the field of social robotics, it draws on contributions by researchers working on the Robovie project at the ATR Intelligent Robotics and Communication Laboratories, a world leader in humanoid interactive robotics. The book brings together, in one volume, technical and empirical research that was previously scattered throughout the literature. Taking a networked robot approach, the book examines how robots work in cooperation with ubiquitous sensors and people over telecommunication networks. It considers the use of social robots in daily life, grounding the work in field studies conducted at a school, train station, shopping mall, and science museum. Critical in the development of network robots, these usability studies allow researchers to discover real issues that need to be solved and to understand what kinds of services are possible. The book tackles key areas where development is needed, namely, in sensor networks for tracking humans and robots, humanoids that can work in everyday environments, and functions for interacting with people. It introduces a sensor network developed by the authors and discusses innovations in the Robovie humanoid, including several interactive behaviors and design policies. Exploring how humans interact with robots in daily life settings, this book offers valuable insight into how robots may be used in the future. The combination of engineering, empirical, and field studies provides readers with rich information to guide in developing practical interactive robots.

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB (R) code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains analytical techniques such as modeling, data mining, and multivariate analysis for social big data. This book is different from other similar books in that presents the overall picture of social big data from fundamental concepts to applications while standing on academic bases.

This book covers theory and practical knowledge of Probabilistic data structures (PDS) and Blockchain (BC) concepts. It introduces the applicability of PDS in BC to technology practitioners and explains each PDS through code snippets and illustrative examples. Further, it provides references for the applications of PDS to BC along with implementation codes in python language for various PDS so that the readers can gain confidence using hands on experience. Organized into five sections, the book covers IoT technology, fundamental concepts of BC, PDS and algorithms used to estimate membership query, cardinality, similarity and frequency, usage of PDS in BC based IoT and so forth.

Facilities increasingly rely on computerized systems to optimize their buildings' systems operation and reduce the costs of maintenance and management. Therefore, facility managers and engineers must rise to the challenge of a new discipline-systems networking and integration-as more and more computerized systems become implemented.

The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost mapping, object recognition, intelligent control of ground and aerial robots, and clustering, with real-time implementations. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures. Includes real-time examples for various robotic platforms. Discusses real-time implementation for land and aerial robots. Presents solutions for problems encountered in autonomous navigation. Explores the mathematical preliminaries needed to understand the proposed methodologies. Integrates computing, communications, control, sensing, planning, and other techniques by means of artificial neural networks for robotics.

The First International Conference on Signal and Information Processing, Networking and Computers (ICSINC) focuses on the key technologies and challenges of signal and information processing schemes, network application, computer theory and application, etc. Topics in this conference include: Information TheoryThe work contains state-of-the-art research work in the field of information theory from traditional media coding theory, compressing and streaming theory to the latest quantum theory & statistics and big data analytics, featuring the most active research interests in this field. Communication SystemAs a traditional and fundamental aspect of the conference in the field of signal processing and networking, ICSINC publications includes research works focusing on physical layer transmission theory such as MIMO transmission, adaptive antenna theory, and radar and satellite transmission, etc. Research works in the field of SDN, wireless security and 5G related theories are also included. Computer ScienceThe conference also encompasses relevant topics in computer science such as AI & neural network, patter recognition & learning, and medical image processing etc. Other topics such as internet application, biometric & authentication are also included. WorkshopICSINC features workshops hosted by experts from the industrial world. The workshop on Telecom Big Data based Research and Application promotes the in-depth exploration of the most recent research and development findings on the basis of telecom big data. This workshop provides participation of the industry to showcase and commercialize their relevant technology and application as well as products. All materials will be included in publication.

Dreamers may envision our future, but it is the pragmatists who build it. Solve the right problem in the right way, mankind moves forward. Solve the right problem in the wrong way or the wrong problem in the right way, however clever or ingenious the solution, neither credits mankind. Instead, this misfire demonstrates a failure to appreciate a crucial step in pragmatic problem solving: systems integration.

The first book to address the underlying premises of systems integration and how to exposit them in a practical and productive manner, Engineering Systems Integration: Theory, Metrics, and Methods looks at the fundamental nature of integration, exposes the subtle premises to achieve integration, and posits a substantial theoretical framework that is both simple and clear. Offering systems managers and systems engineers the framework from which to consider their decisions in light of systems integration metrics, the book isolates two basic questions, 1) Is there a way to express the interplay of human actions and the result of system interactions of a product with its environment?, and 2) Are there methods that combine to improve the integration of systems? The author applies the four axioms of General Systems Theory (holism, decomposition, isomorphism, and models) and explores the domains of history and interpretation to devise a theory of systems integration, develop practical guidance applying the three frameworks, and formulate the mathematical constructs needed for systems integration.

The practicalities of integrating parts when we build or analyze systems mandate an analysis and evaluation of existing integrative frameworks of causality and knowledge. Integration is not just a word that describes a best practice, an art, or a single discipline. The act of integrating is an approach, operative in all disciplines, in all we see, in all we do.

New technologies that allow us to investigate mechanisms and functions of the brain have shown considerable promise in treating brain disease and injury. These emerging technologies also provide a means to assess and manipulate human consciousness, cognitions, emotions, and behaviors, bringing with them the potential to transform society. Neurotechnology: Premises, Potential, and Problems explores the technical, moral, legal, and sociopolitical issues that arise in and from today s applications of neuroscience and technology and discusses their implications for the future.

Some of the issues raised in this thought-provoking volume include:

• Neurotechnology in education: an enablement, a treatment, or an enhancement?
• The potential and limitations of neuroimaging technology in determining patient prognoses
• Tissue implantation technology as a way of engendering personalized medicine
• Neuroprostheses: restoration of functions of the disabled vs. enhancement to transhuman capabilities
• Deep brain stimulation and its use in restoring, preserving, or changing patients personal identity
• The benefit and risk of cognitive performance tools
• Cyborg technology and its potential to change our vision of humanity
• Methodologies for reducing the risk of neurotechnology s impact on ethical, legal, and social issues

With contributions from an international group of experts working on the cutting edge of neurotechnology, this volume lays the groundwork to appreciate the ethical, legal, and social aspects of the science in ways that keep pace with this rapidly progressing field.

Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish-Fisher expansion and other useful but hard-to-find statistical techniques. It then describes common and unusual linear methods as well as popular nonlinear modeling approaches, including additive models, trees, support vector machine, fuzzy systems, clustering, naive Bayes, and neural nets. The authors go on to cover methodologies used in time series and forecasting, such as ARIMA, GARCH, and survival analysis. They also present a range of optimization techniques and explore several special topics, such as Dempster-Shafer theory. An in-depth collection of the most important fundamental material on predictive analytics, this self-contained book provides the necessary information for understanding various techniques for exploratory data analysis and modeling. It explains the algorithmic details behind each technique (including underlying assumptions and mathematical formulations) and shows how to prepare and encode data, select variables, use model goodness measures, normalize odds, and perform reject inference. Web ResourceThe book's website at www.DataMinerXL.com offers the DataMinerXL software for building predictive models. The site also includes more examples and information on modeling.

Multivariable Feedback Control: Analysis and Design, Second Edition presents a rigorous, yet easily readable, introduction to the analysis and design of robust multivariable control systems. Focusing on practical feedback control and not on system theory in general, this book provides the reader with insights into the opportunities and limitations of feedback control.
Taking into account the latest developments in the field, this fully revised and updated second edition:
* features a new chapter devoted to the use of linear matrix inequalities (LMIs);
* presents current results on fundamental performance limitations introduced by RHP-poles and RHP-zeros;
* introduces updated material on the selection of controlled variables and self-optimizing control;
* provides simple IMC tuning rules for PID control;
* covers additional material including unstable plants, the feedback amplifier, the lower gain margin and a clear strategy for incorporating integral action into LQG control;
* includes numerous worked examples, exercises and case studies, which make frequent use of Matlab and the new Robust Control toolbox.
Multivariable Feedback Control: Analysis and Design, Second Edition is an excellent resource for advanced undergraduate and graduate courses studying multivariable control. It is also an invaluable tool for engineers who want to understand multivariable control, its limitations, and how it can be applied in practice. The analysis techniques and the material on control structure design should prove very useful in the new emerging area of systems biology.
Reviews of the first edition:
"Being rich in insights and practical tips on controller design, the book should also prove to be very beneficial to industrial control engineers, both as a reference book and as an educational tool." Applied Mechanics Reviews
"In summary, this book can be strongly recommended not only as a basic text in multivariable control techniques for graduate and undergraduate students, but also as a valuable source of information for control engineers." International Journal of Adaptive Control and Signal Processing

Robotic engineering inspired by biology-biomimetics-has many potential applications: robot snakes can be used for rescue operations in disasters, snake-like endoscopes can be used in medical diagnosis, and artificial muscles can replace damaged muscles to recover the motor functions of human limbs. Conversely, the application of robotics technology to our understanding of biological systems and behaviors-biorobotic modeling and analysis-provides unique research opportunities: robotic manipulation technology with optical tweezers can be used to study the cell mechanics of human red blood cells, a surface electromyography sensing system can help us identify the relation between muscle forces and hand movements, and mathematical models of brain circuitry may help us understand how the cerebellum achieves movement control. Biologically Inspired Robotics contains cutting-edge material-considerably expanded and with additional analysis-from the 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). These 16 chapters cover both biomimetics and biorobotic modeling/analysis, taking readers through an exploration of biologically inspired robot design and control, micro/nano bio-robotic systems, biological measurement and actuation, and applications of robotics technology to biological problems. Contributors examine a wide range of topics, including: A method for controlling the motion of a robotic snake The design of a bionic fitness cycle inspired by the jaguar The use of autonomous robotic fish to detect pollution A noninvasive brain-activity scanning method using a hybrid sensor A rehabilitation system for recovering motor function in human hands after injury Human-like robotic eye and head movements in human-machine interactions A state-of-the-art resource for graduate students and researchers.

The arrival of the digital age has created the need to be able to store, manage, and digitally use an ever-increasing amount of video and audio material. Thus, video cataloguing has emerged as a requirement of the times. Video Cataloguing: Structure Parsing and Content Extraction explains how to efficiently perform video structure analysis as well as extract the basic semantic contents for video summarization, which is essential for handling large-scale video data. This book addresses the issues of video cataloguing, including video structure parsing and basic semantic word extraction, particularly for movie and teleplay videos. It starts by providing readers with a fundamental understanding of video structure parsing. It examines video shot boundary detection, recent research on video scene detection, and basic ideas for semantic word extraction, including video text recognition, scene recognition, and character identification. The book lists and introduces some of the most commonly used features in video analysis. It introduces and analyzes the most popular shot boundary detection methods and also presents recent research on movie scene detection as another important and critical step for video cataloguing, video indexing, and retrieval. The authors propose a robust movie scene recognition approach based on a panoramic frame and representative feature patch. They describe how to recognize characters in movies and TV series accurately and efficiently as well as how to use these character names as cataloguing items for an intelligent catalogue. The book proposes an interesting application of highlight extraction in basketball videos and concludes by demonstrating how to design and implement a prototype system of automatic movie and teleplay cataloguing (AMTC) based on the approaches introduced in the book.

Revised and updated, the second edition includes several new chapters with projects and applications. The authors keep pace with the ever-growing and rapidly expanding field of robotics. The new edition reflects technological developments and includes programs and activities for robot enthusiasts. Using photographs, illustrations, and informative text, Mobile Robots guides the reader through the step-by-step process of constructing two different and inexpensive yet fully functional robots.

This book examines the nature of emergence in context of man-made (i.e. engineered) systems, in general, and system of systems engineering applications, specifically. It investigates emergence to interrogate or explore the domain space from a modeling and simulation perspective to facilitate understanding, detection, classification, prediction, control, and visualization of the phenomenon. Written by leading international experts, the text is the first to address emergence from an engineering perspective. "System engineering has a long and proud tradition of establishing the integrative view of systems. The field, however, has not always embraced and assimilated well the lessons and implications from research on complex adaptive systems. As the editors' note, there have been no texts on Engineering Emergence: Principles and Applications. It is therefore especially useful to have this new, edited book that pulls together so many of the key elements, ranging from the theoretical to the practical, and tapping into advances in methods, tools, and ways to study system complexity. Drs. Rainey and Jamshidi are to be congratulated both for their vision of the book and their success in recruiting contributors with so much to say. Most notable, however, is that this is a book with engineering at its core. It uses modeling and simulation as the language in which to express principles and insights in ways that include tight thinking and rigor despite dealing with notably untidy and often surprising phenomena." - Paul K. Davis, RAND and Frederick S. Pardee RAND Graduate School The first chapter is an introduction and overview to the text. The book provides 12 chapters that have a theoretical foundation for this subject. Includes 7 specific example chapters of how various modeling and simulation paradigms/techniques can be used to investigate emergence in an engineering context to facilitate understanding, detection, classification, prediction, control and visualization of emergent behavior. The final chapter offers lessons learned and the proposed way-ahead for this discipline.