This book focuses on and promotes the applications of the diverse tools and techniques of industrial engineering to the design and operation of systems in industry, business, the government, and the military. Industrial engineering is growing rapidly as an educational option and is a practice favorite in Asia, South America, and many parts of Europe. This book will meet the needs of those growth markets. Industrial Engineering in Systems Design: Guidelines, Practical Examples, Tools, and Techniques offers a wide range of engineering tools from checklists to in-depth analysis guidelines for systems design and operation. The book discusses the integration of industrial and systems engineering from both qualitative and quantitative techniques for systems design. In addition, guidelines for operational resiliency for industry in the case of disruptions, such as a pandemic are covered, and the book provides case examples for industries in developing and under-developed nations. The inclusion of practical examples of where industrial engineering has contributed to the advancement and survival of industries makes this book a very interesting and useful resource. This is a practical guide for professional engineers and consultants involved in the design and operation of systems, particularly manufacturing, production, and supply chain systems, and can also be used as a reference for students.

The concept of the smart grid promises the world an efficient and intelligent approach of managing energy production, transportation, and consumption by incorporating intelligence, efficiency, and optimality into the power grid. Both energy providers and consumers can take advantage of the convenience, reliability, and energy savings achieved by real-time and intelligent energy management. To this end, the current power grid is experiencing drastic changes and upgrades. For instance, more significant green energy resources such as wind power and solar power are being integrated into the power grid, and higher energy storage capacity is being installed in order to mitigate the intermittency issues brought about by the variable energy resources. At the same time, novel power electronics technologies and operating strategies are being invented and adopted. For instance, Flexible AC transmission systems and phasor measurement units are two promising technologies for improving the power system reliability and power quality. Demand side management will enable the customers to manage the power loads in an active fashion. As a result, modeling and control of modern power grids pose great challenges due to the adoption of new smart grid technologies. In this book, chapters regarding representative applications of smart grid technologies written by world-renowned experts are included, which explain in detail various innovative modeling and control methods.

The book focuses on new theoretical results and techniques in the field of intelligent systems and control. It provides in-depth studies on a number of major topics such as Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles and so on. Given its scope, the book will benefit all researchers, engineers, and graduate students who want to learn about cutting-edge advances in intelligent systems, intelligent control, and artificial intelligence.

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

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

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.

This book provides readers to the vision of Society 5.0, which was originally proposed in the fifth Basic Science and Technology Plan by Japan's government for a technology-based, human-centered society, emerging from the 4th industrial revolution (Industry 4.0). The implementation of AI and other modern techniques in a smart society requires automated data scheduling and analysis using smart applications, a smart infrastructure, smart systems, and a smart network. Features Provides an overview of basic concepts of Society 5.0 as well as the main pillars that supports the implementation of Society 5.0. Contains the most recent research analysis in the domain of computer vision, signal processing and computing sciences for facilitating the smart homes, buildings, transport, facilities, environmental conditions and cities, and the benefits these offer to a nation. Presents the readers with practical approaches of using AI and other algorithms for smart ecosystem to deals with human dynamics, the social objects, and their relations. Deals with the utilization of AI tools and other modern techniques for smart society as well as the current challenging issues and its solutions for transformation to Society 5.0. This book is aimed at graduate and post graduate students, researchers, academicians working in the field of computer science, artificial intelligence, and machine learning.

This book introduces readers to numerous multiplicative inverse functional equations and their stability results in various spaces. This type of functional equation can be of use in solving many physical problems and also has significant relevance in various scientific fields of research and study. In particular, multiplicative inverse functional equations have applications in electric circuit theory, physics, and relations connecting the harmonic mean and arithmetic mean of several values. Providing a wealth of essential insights and new concepts in the field of functional equations, the book is chiefly intended for researchers, graduate schools, graduate students, and educators, and can also used for seminars in analysis covering topics of functional equations.

This book presents both the importance of energy transition and its associated difficulties. Energy Transition, Second Edition, provides an explanation of the physical concepts of energy and power and also reviews global energy consumption and our dependence on energy. The book discusses the links between the economy and energy. It explains the drawbacks and dangers of different energy sources and tries to compare them. By reviewing future energy resources, it evaluates several transition scenarios. The book shows that the laws of physics prevent the emergence of simple, pleasant solutions, but it proposes potential solutions and encourages readers to develop better processes from energy sources to production to consumption. This book will be of interest to engineers and undergraduate and graduate students studying and working in various fields of energy; producers of fossil, gas, oil, coal, electric, renewable, and nuclear energy; and anyone interested in better understanding these fundamental problems for our future. FEATURES Discusses the current issues with energy transition Covers several energy transition scenarios and their associated difficulties Presents the links between economy and energy Highlights the importance of a global discussion of energy Encourages the development of better, improved processes in energy sources from production to consumption

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.

i. This book will contain AI, ML, DL, big data and security never before considered ii. Innovative artificial intelligence techniques and algorithms iii. Only emerging from recent research and development, e.g. AI for big data from security perspective, which are not covered in any existing texts iv. Artificial Intelligence for big data and security Applications with advanced features v. Key new finding of machine learning and deep learning for Security Applications

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.

This edited volume on "Recent Advances in Renewable Energy" presents a selection of refereed papers presented at the 1st International Conference on Electrical Systems and Automation. The book provides rigorous discussions, the state of the art, and recent developments in the field of renewable energy sources supported by examples and case studies, making it an educational tool for relevant undergraduate and graduate courses. The book will be a valuable reference for beginners, researchers, and professionals interested in renewable energy.

This book provides insights on how to approach and utilize data science tools, technologies and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI-technologies, and their inter-connections. Description of various technology and methodology approaches, and their purpose and benefits when developing AI-solution in industrial contexts is included. In addition, it summarizes experiences from AI technology deployment projects from several industrial sectors. Features: Presents compendium of methodologies and technologies in Industrial AI and digitalization. Illustrates sensor to actuation approach showing complete cycle, that defines and differences AI and digitalization concept. Covers a broad range of academic and industrial issues within the field of asset management. Discusses impact of Industry 4.0 in other sectors. Includes a dedicated chapter on real-time case studies. This book is aimed at researchers and professionals in industrial and software engineering, network security, AI and ML, engineering managers, operational and maintenance specialists, asset managers, digital and AI manufacturing specialists.

Focuses on several core aspects of Industry 4.0 on computer vision & imaging. Highlights several exciting techniques for disease prediction, NLP, image captioning, flood level assessment, crop classifications, and fabrication of smart wheelchairs. Covers several chapters on Natural Language Processing (NLP), focusing on Bangla language. Chapters presented in a step-by-step manner so that young minds can understand and implement easily.

The text focuses on mathematical modeling and applications of advanced techniques of machine learning, and artificial intelligence, including artificial neural networks, evolutionary computing, data mining, and fuzzy systems to solve performance and design issues more precisely. Intelligent computing encompasses technologies, algorithms, and models in providing effective and efficient solutions to a wide range of problems including the airport's intelligent safety system. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields including industrial engineering, manufacturing engineering, computer engineering, and mathematics. The book- Discusses mathematical modeling for traffic, sustainable supply chain, vehicular Ad-Hoc networks, internet of things networks with intelligent gateways. Covers advanced machine learning, artificial intelligence, fuzzy systems, evolutionary computing, data mining techniques for real-world problems. Presents applications of mathematical models in chronic diseases such as kidney and coronary artery diseases. Highlights advances in mathematical modeling, strength, and benefits of machine learning and artificial intelligence, including driving goals, applicability, algorithms, and processes involved. Showcases emerging real-life topics on mathematical models, machine learning, and intelligent computing using an interdisciplinary approach. The text presents emerging real-life topics on mathematical models, machine learning, and intelligent computing in a single volume. It will serve as an ideal text for senior undergraduate, graduate students, and researchers in diverse fields domains including industrial and manufacturing engineering, computer engineering, and mathematics.

Gives broad perspective on 5G communications with a focus on smart cities Discusses artificial intelligence in future wireless communication and its applications Provides a systemic and comprehensive coverage of 6G technologies, challenges and use cases Explores role of future wireless in safety, health, and transport in smart cities Includes case studies of future wireless communications

This book presents a differential geometric method for designing nonlinear observers for multiple types of nonlinear systems, including single and multiple outputs, fully and partially observable systems, and regular and singular dynamical systems. It is an exposition of achievements in nonlinear observer normal forms. The book begins by discussing linear systems, introducing the concept of observability and observer design, and then explains the difficulty of those problems for nonlinear systems. After providing foundational information on the differential geometric method, the text shows how to use the method to address observer design problems. It presents methods for a variety of systems. The authors employ worked examples to illustrate the ideas presented. Observer Design for Nonlinear Dynamical Systems will be of interest to researchers, graduate students, and industrial professionals working with control of mechanical and dynamical systems.

Stochastic modeling is a set of quantitative techniques for analyzing practical systems with random factors. This area is highly technical and mainly developed by mathematicians. Most existing books are for those with extensive mathematical training; this book minimizes that need and makes the topics easily understandable. Fundamentals of Stochastic Models offers many practical examples and applications and bridges the gap between elementary stochastics process theory and advanced process theory. It addresses both performance evaluation and optimization of stochastic systems and covers different modern analysis techniques such as matrix analytical methods and diffusion and fluid limit methods. It goes on to explore the linkage between stochastic models, machine learning, and artificial intelligence, and discusses how to make use of intuitive approaches instead of traditional theoretical approaches. The goal is to minimize the mathematical background of readers that is required to understand the topics covered in this book. Thus, the book is appropriate for professionals and students in industrial engineering, business and economics, computer science, and applied mathematics.

Python for Scientific Computation and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web.

This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks in the field of diagnosis of neurological disorders. Along with this, data pre-processing including scaling, correction, trimming, normalization is also included. Offers a detailed description of the deep learning approaches used for the diagnosis of neurological disorders Demonstrates concepts of deep learning algorithms using diagrams, data tables, and examples for the diagnosis of neurodegenerative disorders; neurodevelopmental, and psychiatric disorders. Helps build, train, and deploy different types of deep architectures for diagnosis Explores data pre-processing techniques involved in diagnosis Include real-time case studies and examples This book is aimed at graduate students and researchers in biomedical imaging and machine learning.

China Satellite Navigation Conference (CSNC 2021) Proceedings presents selected research papers from CSNC 2021 held during 22nd-25th May, 2021 in Nanchang, China. These papers discuss the technologies and applications of the Global Navigation Satellite System (GNSS), and the latest progress made in the China BeiDou System (BDS) especially. They are divided into 10 topics to match the corresponding sessions in CSNC2021 which broadly covered key topics in GNSS. Readers can learn about the BDS and keep abreast of the latest advances in GNSS techniques and applications.

A practical guide to semiconductor manufacturing from process control to yield modeling and experimental design
Fundamentals of Semiconductor Manufacturing and Process Control covers all issues involved in manufacturing microelectronic devices and circuits, including fabrication sequences, process control, experimental design, process modeling, yield modeling, and CIM/CAM systems. Readers are introduced to both the theory and practice of all basic manufacturing concepts.
Following an overview of manufacturing and technology, the text explores process monitoring methods, including those that focus on product wafers and those that focus on the equipment used to produce wafers. Next, the text sets forth some fundamentals of statistics and yield modeling, which set the foundation for a detailed discussion of how statistical process control is used to analyze quality and improve yields.
The discussion of statistical experimental design offers readers a powerful approach for systematically varying controllable process conditions and determining their impact on output parameters that measure quality. The authors introduce process modeling concepts, including several advanced process control topics such as run-by-run, supervisory control, and process and equipment diagnosis.
Critical coverage includes the following:
* Combines process control and semiconductor manufacturing
* Unique treatment of system and software technology and management of overall manufacturing systems
* Chapters include case studies, sample problems, and suggested exercises
* Instructor support includes electronic copies of the figures and an instructor's manual
Graduate-level students and industrial practitioners will benefit from the detailed exami?nation of how electronic materials and supplies are converted into finished integrated circuits and electronic products in a high-volume manufacturing environment.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
An Instructor Support FTP site is also available.