When the pressure is on to resolve an elusive software or hardware glitch, what's needed is a cool head courtesy of a set of rules guaranteed to work on any system, in any circumstance. Written in a frank but engaging style, this book provides simple, foolproof principles guaranteed to help find any bug quickly. Recognized tech expert and author David Agans changes the way you think about debugging, making those pesky problems suddenly much easier to find and fix. Agans identifies nine simple, practical rules that are applicable to any software application or hardware system, which can help detect any bug, no matter how tricky or obscure. Illustrating the rules with real-life bug-detection war stories, Debugging shows you how to: Understand the system: how perceiving the ""roadmap"" can hasten your journey Quit thinking and look: when hands-on investigation can't be avoided Isolate critical factors: why changing one element at a time can be an essential tool Keep an audit trail: how keeping a record of the debugging process can win the day Whether the system or program you're working on has been designed wrong, built wrong, or used wrong, Debugging helps you think correctly about bugs, so the problems virtually reveal themselves.

- Unlike other AI titles, this book takes a step further towards the real applicability and transferability of AI, through detailed examples in a very important region of Spain - Includes chapters on health and social welfare, transportation, digital economy, energy efficiency and sustainability, agro-industry and tourism - Great diversity of authors, expert in the varied sectors and problems addressed, belonging to powerful research groups from the University of Seville with proven experience in the transfer of knowledge to the productive sector and agents attached to the Andalucia TECH Campus

The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations. Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.

Provides a comprehensive guide about how to use machine vision for Industry 4.0 applications like analysis of images for automated inspections, object detection, object tracking etc. Includes case studies of Robotics Internet of Things with its current and future applications in Healthcare, Agriculture, Transportation, etc. It highlights the inclusion of impaired people in industry, like intelligent assistant that helps deaf-mute people to transmit instructions and warnings in a manufacturing process. It examines the significant technological advancements in machine vision for industrial Internet of things and explores the commercial benefits using the real world applications from healthcare to transportation. Provides a conceptual framework of Machine vision for the various Industrial applications. Addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and post-graduate students, researchers, and anyone else interested in the trends, development, and opportunities for the Machine Vision for Industry 4.0 applications.

This book discusses IoT in healthcare and how it enables interoperability, machine-to-machine communication, information exchange, and data movement. It also covers how healthcare service delivery automates patient care with the help of mobility solutions, new technologies, and next-gen healthcare facilities with challenges faced and suggested solutions prescribed. Reinvention of Health Applications with IoT: Challenges and Solutions presents the latest applications of IoT in healthcare along with challenges and solutions. It looks at a comparison of advanced technologies such as Deep Learning, Machine Learning, and AI and explores the ways they can be applied to sensed data to improve prediction and decision-making in smart health services. It focuses on society 5.0 technologies and illustrates how they can improve society and the transformation of IoT in healthcare facilities to support patient independence. Case studies are included for applications such as smart eyewear, smart jackets, and smart beds. The book will also go into detail on wearable technologies and how they can communicate patient information to doctors in medical emergencies. The target audiences for this edited volume is researchers, practitioners, students, as well as key stakeholders involved in and working on healthcare engineering solutions.

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

Discusses wide range of magnetic field assisted finishing processes in a comprehensive manner. Covers different process parameters by considering their effects on the finishing output. Provides process limitations to achieve optimal yield. Covers numerical explanations for better selection of process parameters. Discusses automation of processes with state-of-the-art technologies.

Proposes to employ robots to improve the treatment of patients and leverage the load of the medical system. Demonstrates the concept of various robotics in healthcare telepresence, rehabilitation, therapy, and delivery robots to provide social distancing. Explores social robot aesthetics and how social interaction and embodied experience could be useful during social isolation. Includes anecdotes from applications used during the COVID-19 pandemic.

Discusses various aspects of role of Internet of Things (IoT) and Machine Learning in smart buildings. Explains pertinent system architecture focusing on power generation and distribution. Covers power enabling technologies for smart cities. Includes Photovoltaic System Integrated Smart Buildings.

Considers both time-domain and frequency domain robust design techniques of partial differential systems Illustrates both theoretical robust design techniques and practical applications Discusses partial differential systems with both Dirichlet and Neuman boundary conditions in robust design procedure Addresses deterministic and stochastic partial differential systems Explores theoretical mathematical background, robust signal processing design, robust control system design and robust biological system design with application

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

The author has spent approximately 50 years in the field of systems engineering. This Focus book provides a "looking back" at his 50-year run and the lessons he learned and would like to share with other engineers, so they can use these lessons in their day-to-day work in systems engineering and related fields. The book is written from a systems engineering perspective. It offers 50 lessons learned working for a variety of different companies, which can be used across many other engineering fields. The book will be of interested to students and engineers across many fields, as well as students and engineers working in business and management fields.

In the last decade, both scholars and practitioners have sought novel ways to address the problem of cybersecurity. Innovative outcomes have included applications such as blockchain as well as creative methods for cyber forensics, software development, and intrusion prevention. Accompanying these technological advancements, discussion on cyber matters at national and international levels has focused primarily on the topics of law, policy, and strategy. The objective of these efforts is typically to promote security by establishing agreements among stakeholders on regulatory activities. Varying levels of investment in cyberspace, however, comes with varying levels of risk; in some ways, this can translate directly to the degree of emphasis for pushing substantial change. At the very foundation or root of cyberspace systems and processes are tenets and rules governed by principles in mathematics. Topics such as encrypting or decrypting file transmissions, modeling networks, performing data analysis, quantifying uncertainty, measuring risk, and weighing decisions or adversarial courses of action represent a very small subset of activities highlighted by mathematics. To facilitate education and a greater awareness of the role of mathematics in cyber systems and processes, a description of research in this area is needed. Mathematics in Cyber Research aims to familiarize educators and young researchers with the breadth of mathematics in cyber-related research. Each chapter introduces a mathematical sub-field, describes relevant work in this field associated with the cyber domain, provides methods and tools, as well as details cyber research examples or case studies. Features One of the only books to bring together such a diverse and comprehensive range of topics within mathematics and apply them to cyber research. Suitable for college undergraduate students or educators that are either interested in learning about cyber-related mathematics or intend to perform research within the cyber domain. The book may also appeal to practitioners within the commercial or government industry sectors. Most national and international venues for collaboration and discussion on cyber matters have focused primarily on the topics of law, policy, strategy, and technology. This book is among the first to address the underpinning mathematics.

Provides the basic concepts of process mining techniques for pattern recognition for readers to analyze, predict, forecast, and enhance the workflow of processes Covers the entire spectrum of process mining from process discovery to operational support Discusses several process mining techniques in the context of data science and big data Contains real-life applications and case studies related to process mining theories and practices Includes detailed examples, figures, and tables for easy understanding of concepts discussed

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

This book offers the latest research advances in the field of Industry 4.0, focusing on enabling technologies for its deployment in a comprehensive way. This book offers successful implementation of technologies such as artificial intelligence, augmented and virtual reality, autonomous and collaborative robots, cloud computing, and up-to-date guidelines. It investigates how the technologies and principles surrounding Industry 4.0 (e.g., interoperability, decentralized decisions, information transparency, etc.) serve as support for organizational routines and workers (and vice versa). Included are applications of technologies for different sectors and environments as well as for the supply chain management. It also offers a domestic and international mix of case studies that spotlight successes and failures. Features Provides a historical review of Industry 4.0 and its roots Discusses the applications of technologies in different sectors and environments (e.g., public vs. private) Presents key enabling technologies for successful implementation in any industrial and service environment Offers case studies of successes and failures to illustrate how to put theory into practice Investigates how technologies serve as support for organizational routines and workers

Provides a comprehensive introduction to multi-robot systems planning and task allocation; Explores multi robot aerial planning, flight planning, orienteering and coverage, and deployment, patrolling, and foraging; Includes real-world case studies; Treats different aspects of cooperation in multi-agent systems.

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained-including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author's website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.

Road Vehicle Dynamics: Fundamentals and Modeling with MATLAB (R), Second Edition combines coverage of vehicle dynamics concepts with MATLAB v9.4 programming routines and results, along with examples and numerous chapter exercises. Improved and updated, the revised text offers new coverage of active safety systems, rear wheel steering, race car suspension systems, airsprings, four-wheel drive, mechatronics, and other topics. Based on the lead author's extensive lectures, classes, and research activities, this unique text provides readers with insights into the computer-based modeling of automobiles and other ground vehicles. Instructor resources, including problem solutions, are available from the publisher.

Systematically defines energy-efficient buildings, employing power consumption optimization techniques with inclusion of renewable energy sources. Covers data centre and cyber security with excellent data storage features for smart buildings. Includes systematic and detailed strategies for building air conditioning and lighting. Details smart building security propulsion.

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained-including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author's website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.

The book begins with an overview of automation history and followed by chapters on PLC, DCS, and SCADA -describing how such technologies have become synonymous in process instrumentation and control. The book then introduces the niche of Fieldbuses in process industries. It then goes on to discuss wireless communication in the automation sector and its applications in the industrial arena. The book also discusses theall-pervading IoT and its industrial cousin,IIoT, which is finding increasing applications in process automation and control domain. The last chapter introduces OPC technology which has strongly emerged as a defacto standard for interoperable data exchange between multi-vendor software applications and bridges the divide between heterogeneous automation worlds in a very effective way. Key features: Presents an overall industrial automation scenario as it evolved over the years Discusses the already established PLC, DCS, and SCADA in a thorough and lucid manner and their recent advancements Provides an insight into today's industrial automation field Reviews Fieldbus communication and WSNs in the context of industrial communication Explores IIoT in process automation and control fields Introduces OPC which has already carved out a niche among industrial communication technologies with its seamless connectivity in a heterogeneous automation world Dr. Chanchal Dey is Associate Professor in the Department of Applied Physics, Instrumentation Engineering Section, University of Calcutta. He is a reviewer of IEEE, Elsevier, Springer, Acta Press, Sage, and Taylor & Francis Publishers. He has more than 80 papers in international journals and conference publications. His research interests include intelligent process control using conventional, fuzzy, and neuro-fuzzy techniques. Dr. Sunit Kumar Sen is an ex-professor, Department of Applied Physics, Instrumentation Engineering Section, University of Calcutta. He was a coordinator of two projects sponsored by AICTE and UGC, Government of India. He has published around70 papers in international and national journals and conferences and has published three books - the last one was published by CRC Press in 2014. He is a reviewer of Measurement, Elsevier. His field of interest is new designs of ADCs and DACs.

is the first book to set out a range of machine learning methods for efficient resource management in a large distributed network of clouds. predictive analytics is an integral part of efficient cloud resource management, and this book gives a future research direction to researchers in this domain. it is written by leading international researchers.

The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects. Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT. This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.

Covers deep learning fundamentals; Focuses on applications; Covers human emotion analysis and deep learning; Explains how to use web based techniques for deep learning applications; Includes coverage of autonomous vehicles and deep learning