Video has rich information including meta-data, visual, audio, spatial and temporal data which can be analysed to extract a variety of low and high-level features to build predictive computational models using machine-learning algorithms to discover interesting patterns, concepts, relations, and associations. This book includes a review of essential topics and discussion of emerging methods and potential applications of video data mining and analytics. It integrates areas like intelligent systems, data mining and knowledge discovery, big data analytics, machine learning, neural network, and deep learning with focus on multimodality video analytics and recent advances in research/applications. Features: Provides up-to-date coverage of the state-of-the-art techniques in intelligent video analytics. Explores important applications that require techniques from both artificial intelligence and computer vision. Describes multimodality video analytics for different applications. Examines issues related to multimodality data fusion and highlights research challenges. Integrates various techniques from video processing, data mining and machine learning which has many emerging indoors and outdoors applications of smart cameras in smart environments, smart homes, and smart cities. This book aims at researchers, professionals and graduate students in image processing, video analytics, computer science and engineering, signal processing, machine learning, and electrical engineering.

• Utilizes case studies from different disciplines and sectors within engineering and other related technical areas to demonstrate how to go from data, to insight, and to decision making • Introduces various approaches to build models that exploits different algorithms • Discusses predictive models that can be built through machine learning and used to mine patterns from large datasets • Explores the augmentation of technical and mathematical materials with explanatory worked examples • Includes a glossary, lecture notes, self-assessments, and worked-out practice exercises

Introduces different optimization algorithms together to solve complex combinatorial optimization problems related to hospital management system or healthcare Applies machine learning-based analytics such as GAN networks, autoencoders, computational imaging, and quantum computing to authentic hospital management problems Discusses metaheuristic algorithms such as evolutionary algorithms to cope with the fundamental steps of image processing, image analysis, and computer vision pipeline (e.g., restoration, segmentation, registration, classification, reconstruction, or tracking) Creates a bridge between Computational Intelligence and Industrial Engineering towards designing complex and convoluted hospital management problems

As data is an important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. This volume of a two-volume handbook set provides a roadmap for new trends and future developments of data science with semantic technologies. Data Science with Semantic Technologies: New Trends and Future Developments highlights how data science enables the user to create intelligence through these technologies. In addition, this book offers the answers to various questions such as can semantic technologies be able to facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists get benefited from these technologies? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of the researchers? What should be the vision 2030 for data science? This volume can serve as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field.

Gone are the days when data was interlinked with related data by humans and to find insights coherently, human interpretation was required. Data is no more just data. It is now considered a Thing or Entity or Concept- to bring the meaning to it, so that a machine not only understands the concept but also extrapolates the way humans do. Data Science with Semantic Technologies: Deployment and Exploration volume of a two-volume handbook set provides a roadmap for the deployment of semantic technologies in the field of data science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book offers the answer to various questions like What makes a technology semantic as opposed to other approaches to data science? What is knowledge data science? How does knowledge data science relate to other fields? This book explores the optimal use of these technologies to provide the highest benefit to the user under one comprehensive source and title. As there is no dedicated book available in the market on this topic at this time, this proposed new book becomes a unique and only resource for scholars, researchers, data scientists, professionals, and practitioners. This volume can serve as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field.

Coding for Channels with Feedback presents both algorithms for feedback coding and performance analyses of these algorithms, including analyses of perhaps the most important performance criterion: computational complexity. The algorithms are developed within a single framework, termed the compressed-error-cancellation framework, where data are sent via a sequence of messages: the first message contains the original data; each subsequent message contains a source-coded description of the channel distortions introduced on the message preceding it. Coding for Channels with Feedback provides an easily understood and flexible framework for deriving low-complexity, practical solutions to a wide variety of feedback communication problems. It is shown that the compressed-error-cancellation framework leads to coding schemes with the lowest possible asymptotic order of growth of computations and can be applied to discrete memoryless channels, finite state channels, channels with memory, unknown channels, and multiple-access channels, all with complete noiseless feedback, as well as to channels with partial and noisy feedback. This framework leads to coding strategies that have linear complexity and are capacity achieving, and illustrates the intimate connection between source coding theory and channel coding theory. Coding for Channels with Feedback is an excellent reference for researchers and communication engineers in the field of information theory, and can be used for advanced courses on the topic.

The Internet gives the consumer almost unlimited choice in products. At the same time, it causes a globalization of consumer habits and tastes. One important question that arises is: Does the Internet and the World Wide Web offer the same opportunities for choice of services as they do for products? Service Customization Using Web Technologies aims to advance our understanding of Web-related concepts, approaches, and technologies revolving around the core theme of e-service customization. Limitless e-service choice can become possible on the Web only through customization. Understanding such customization on the Web, applied at a mass market level, in a cost efficient manner, will present an unprecedented opportunity for both the industry and the consumers. For both researchers and practitioners, understanding that as service customization accelerates through other types of industries and consumers, we will experience, the benefits of service customization in many more areas of everyday life.

This is a textbook and reference for readers interested in quasilinear control (QLC). QLC is a set of methods for performance analysis and design of linear plant or nonlinear instrumentation (LPNI) systems. The approach of QLC is based on the method of stochastic linearization, which reduces the nonlinearities of actuators and sensors to quasilinear gains. Unlike the usual - Jacobian linearization - stochastic linearization is global. Using this approximation, QLC extends most of the linear control theory techniques to LPNI systems. A bisection algorithm for solving these equations is provided. In addition, QLC includes new problems, specific for the LPNI scenario. Examples include Instrumented LQR/LQG, in which the controller is designed simultaneously with the actuator and sensor, and partial and complete performance recovery, in which the degradation of linear performance is either contained by selecting the right instrumentation or completely eliminated by the controller boosting.

First-hand technical expertise – torch has been developed in/by the author’s team at RStudio. Presupposes only a minimal background in mathematics. Presupposes no background in optimization and/or deep learning (but some general ideas about machine learning). Entertaining and fun to read (at least that’s the intention!). Concept-first approach

First-hand technical expertise – torch has been developed in/by the author’s team at RStudio. Presupposes only a minimal background in mathematics. Presupposes no background in optimization and/or deep learning (but some general ideas about machine learning). Entertaining and fun to read (at least that’s the intention!). Concept-first approach

Designed to offer an accessible set of case studies and analyses of ethical dilemmas in data science. This book will be suitable for technical readers in data science who want to understand diverse ethical approaches to AI.

Designed to offer an accessible set of case studies and analyses of ethical dilemmas in data science. This book will be suitable for technical readers in data science who want to understand diverse ethical approaches to AI.

With the aim to better understand nature, mathematical tools are being used nowadays in many different fields. The concept of integral transforms, in particular, has been found to be a useful mathematical tool for solving a variety of problems not only in mathematics, but also in various other branches of science, engineering, and technology. Integral Transforms and Engineering: Theory, Methods, and Applications presents a mathematical analysis of integral transforms and their applications. The book illustrates the possibility of obtaining transfer functions using different integral transforms, especially when mapping any function into the frequency domain. Various differential operators, models, and applications are included such as classical derivative, Caputo derivative, Caputo-Fabrizio derivative, and Atangana-Baleanu derivative. This book is a useful reference for practitioners, engineers, researchers, and graduate students in mathematics, applied sciences, engineering, and technology fields.

An introduction to the model-based approach and the mclust R package A detailed description of mclust and the underlying modeling strategies An extensive set of examples, color plots and figures along with the R code for reproducing them Supported by a companion website including the R code to reproduce the examples and figures presented in the book, errata, and other supplementary material

This book reviews and presents several approaches to advanced decision-making models for safety and risk assessment. Each introduced model provides case studies indicating a high level of efficiency, robustness, and applicability, which allow readers to utilize them in their understudy risk-based assessment applications. The book begins by introducing a novel dynamic DEMATEL for improving safety management systems. It then progresses logically, dedicating a chapter to each approach, including advanced FMEA with probabilistic linguistic preference relations, Bayesian Network approach and interval type-2 fuzzy set, advanced TOPSIS with spherical fuzzy set, and advanced BWM with neutrosophic fuzzy set and evidence theory. This book will be of interest to professionals and researchers working in the field of system safety and reliability and postgraduate and undergraduate students studying applications of decision-making tools and expert systems.

• Introduces the principles of system dynamics, and demonstrates them with respect to problems in pavement engineering. • Provides useful models for readers to download and further modify and improve for their own use. • Serves as a practical guide for both students and practitioners to explore systems concepts, and develop insights for sustainable and resilient pavements.

This book explores various intelligent algorithms including evolutionary algorithms, swarm intelligence-based algorithms for analysis and control of dynamical systems. Both single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems are explored for analysis and control purposes. The applications of intelligent algorithm vary from approximation to optimal control design. The applications of intelligent algorithms not only improve understanding of a dynamical system but also enhance the control efficacy. The intelligent algorithms are now readily applied to all fields of control including linear control, nonlinear control, digital control, optimal control, etc. The book also discusses the main benefits attained due to the application of algorithms to analyze and control.

Control networks span a wide range of application areas. These networks are put into action in the `Digital Home', industrial applications, commercial buildings, transportation systems, gas stations, security systems, and they are found in most instances where smart sensors and smart actuators are used to exchange information. The authors of this volume provide an overview of various control network protocols and discuss LonTalk (R) protocol, Neuron (R) chip, programming model, network structures, network management, interoperability between nodes, application profiles, development and maintenance tools, performance analysis, and standardization activities. Open Control Networks: LonWorks/EIA 709 Technology will be an important resource for advanced students of control systems and embedded systems, engineers designing distributed networks, systems designers and architects, and others developing smart buildings and intelligent transportation systems.

Optimal Impulsive Control explores the class of impulsive dynamic optimization problems-problems that stem from the fact that many conventional optimal control problems do not have a solution in the classical setting-which is highly relevant with regard to engineering applications. The absence of a classical solution naturally invokes the so-called extension, or relaxation, of a problem, and leads to the notion of generalized solution which encompasses the notions of generalized control and trajectory; in this book several extensions of optimal control problems are considered within the framework of optimal impulsive control theory. In this framework, the feasible arcs are permitted to have jumps, while the conventional absolutely continuous trajectories may fail to exist. The authors draw together various types of their own results, centered on the necessary conditions of optimality in the form of Pontryagin's maximum principle and the existence theorems, which shape a substantial body of optimal impulsive control theory. At the same time, they present optimal impulsive control theory in a unified framework, introducing the different paradigmatic problems in increasing order of complexity. The rationale underlying the book involves addressing extensions increasing in complexity from the simplest case provided by linear control systems and ending with the most general case of a totally nonlinear differential control system with state constraints. The mathematical models presented in Optimal Impulsive Control being encountered in various engineering applications, this book will be of interest to both academic researchers and practising engineers.

For courses in Programmable Logic Controllers where the Allen/Bradley programmable logic controller is the controller of choice. This text focuses on the theory and operation of PLC systems with an emphasis on program analysis and development. The book is written in easy-to-read and understandable language with many crisp illustrations and practical examples. It describes the PLC instructions for the Allen-Bradley PLC 5, SLC 500, and Logix processors with an emphasis on the SLC 500 system using numerous figures, tables, and example problems. The text features a new two-column and four-color interior design that improves readability and figure placement. The book's organization also has improved; all the chapter questions and problems are listed in one convenient location in Appendix D with page locations for all chapter references in the questions and problems. This book describes the technology in a clear, concise style that is effective in helping students who have no previous experience in PLCs or discrete and analog system control. For additional resources, visit these web sites: http: //plctext.com/ http: //plcteacher.c

This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum

This book provides a first-of-its-kind approach for using blockchain to enhance resilience in disaster supply chain and logistics management, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources - these are elements of volatility, uncertainty, complexity, and ambiguity (VUCA) describing a dynamic environment that now form the "new norm" for many leaders. Blockchain-Enabled Resilience: An Integrated Approach for Disaster Supply Chain and Logistics Management analyzes the application of blockchain technology used to enable resilience in a disaster supply chain network. It discusses IoT and DVFS algorithms for developing a network-based simulation and presents advancements in disaster supply chain strategies using smart contacts for collaborations. The book covers how success is based on collaboration, coordination, sovereignty, and equality in distributing resources and offers a theoretical analysis that reveals that enhancing resilience can improve collaboration and communication and can result in more time-efficient processing for disaster supply management. This book provides a first-of-its-kind approach for managers and policy-makers as well as researchers interested in using blockchain to enhance resilience in disaster supply chains, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources. Practical guidance is provided for managers interested in implementation. A robust research agenda is also provided for those interested in expanding present research.

Hybrid Computational Intelligent Systems – Modeling, Simulation and Optimization unearths the latest advances in evolving hybrid intelligent modeling and simulation of human-centric data-intensive applications optimized for real-time use, thereby enabling researchers to come up with novel breakthroughs in this ever-growing field. Salient features include the fundamentals of modeling and simulation with recourse to knowledge-based simulation, interaction paradigms, and human factors, along with the enhancement of the existing state of art in a high-performance computing setup. In addition, this book presents optimization strategies to evolve robust and failsafe intelligent system modeling and simulation. The volume also highlights novel applications for different engineering problems including signal and data processing, speech, image, sensor data processing, innovative intelligent systems, and swarm intelligent manufacturing systems. Features: A self-contained approach to integrating the principles of hybrid computational ntelligence with system modeling and simulation Well-versed foundation of computational intelligence and its application to real life engineering problems Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Effective modeling of hybrid intelligent systems forms the backbone of almost every operative system in real-life Proper simulation of real-time hybrid intelligent systems is a prerequisite for deriving any real-life system solution Optimized system modeling and simulation enable real-time and failsafe operations of the existing hybrid intelligent system solutions Information presented in an accessible way for researchers, engineers, developers, and practitioners from academia and industry working in all major areas and interdisciplinary areas of hybrid computational intelligence and communication systems to evolve human-centered modeling and simulations of real-time data-intensive intelligent systems.

This book has been created on the basis of contributions to the 54th International Conference of Machine Design Departments that was held for the 60th anniversary of Technical University of Liberec. This international conference which follows a tradition going back more than 50 years is one of the longest-running series of conferences held in central Europe, dealing with methods and applications inmachine design. The main aim of the conference was to provide an international forum where experts, researchers, engineers and industrial practitioners, managers and Ph.D. students could meet, share their experiences and present the results of their efforts in the broad field of machine design and related fields.

The book has seven chapters which focus on new knowledge of machine design, optimization, tribology, experimental methods and measuring, engineering analyses and product innovation. Authors presented new design methods of machine parts and more complex assemblies with the help of numerical methods such as FEM. Research, measurements and studies of new materials, including composites for energy-efficient constructions are also described. The book also includes solutions and results useful for optimization and innovation of complex design problems in various industries."

Unique selling point: Advanced AI solutions for problems in genetics, virology, and related areas of life science Core audience: Researchers in bioinformatics Place in the market: High-level reference book on advanced applied technology