This book includes the original, peer-reviewed research papers from the 2nd International Conference on Electrical Systems, Technology and Information (ICESTI 2015), held in September 2015 at Patra Jasa Resort & Villas Bali, Indonesia. Topics covered include: Mechatronics and Robotics, Circuits and Systems, Power and Energy Systems, Control and Industrial Automation, and Information Theory. It explores emerging technologies and their application in a broad range of engineering disciplines, including communication technologies and smart grids. It examines hybrid intelligent and knowledge-based control, embedded systems, and machine learning. It also presents emerging research and recent application in green energy system and storage. It discusses the role of electrical engineering in biomedical, industrial and mechanical systems, as well as multimedia systems and applications, computer vision and image and signal processing. The primary objective of this series is to provide references for dissemination and discussion of the above topics. This volume is unique in that it includes work related to hybrid intelligent control and its applications. Engineers and researchers as well as teachers from academia and professionals in industry and government will gain valuable insights into interdisciplinary solutions in the field of emerging electrical technologies and its applications.

Control of Power Electronic Converters and Systems examines the theory behind power electronic converter control, including operation, modeling and control of basic converters. The book explores how to manipulate components of power electronics converters and systems to produce a desired effect by controlling system variables. Advances in power electronics enable new applications to emerge and performance improvement in existing applications. These advances rely on control effectiveness, making it essential to apply appropriate control schemes to the converter and system to obtain the desired performance.

Sketching is a natural and intuitive communication tool used for expressing concepts and ideas that are difficult to communicate through text or speech alone. In design applications, drawings are used at various stages of the design process: from the early concept drawings scribbled on a piece of paper to immersive interactions in which users manipulate and adjust the 3D form of an object in virtual or augmented reality environments. This variety in drawing activities brings about the need for different interpretation strategies that support not only the sketching activity itself, but also allow sketch-based interactions, such as sketch-based queries, to take place. In this book, we explore the different drawing approaches used in design and the algorithms required for processing and interpreting the different sketches and drawings in design. The book is divided into two parts. The first part focuses on sketching in the 2D domain. This includes the digitization of offline and paper-based sketches, techniques for online sketch recognition, observations of user drawing habits, algorithms for inferring depth from 2D drawings, as well as non-photorealistic rendering techniques that are then applied to sketch-based queries. The second part of the book focuses on 3D sketching in virtual or augmented reality spaces. Here, we present the processing and rendering of the 3D strokes, the different interaction devices available for 3D sketching, and look at different applications where immersive 3D sketching has been applied with success.

Covers material characterization techniques and the development of advanced characterization technology Includes multiple length scale characterization approaches for a large variety of materials, from nano- to micron-scale, as well as their constraints Discusses advanced material characterization technology in the microstructural and property characterization fields Reviews both practical and theoretical explanations of approaches for characterizing microstructure and properties Offers fundamentals, basic instrumentation details, experimental approaches, analyses, and applications with case studies

This book is a compendium of various applications and current progress in a powerful technology known as the Internet of Things (IoT). IoT provides a system of interconnecting things such as vehicles, electrical equipment, agriculture devices, etc. Such items are allocated with the computing device so that they can use a network to transfer data to one another and automate their actions on certain events. Internet of Things: Applications for Sustainable Development will throw light on recent developments in the latest field and will be of great interest to know various application areas for sustainable development. This book mainly focuses on the current state of the art, including protocol design and low-cost sensor design, for the sustainable development of society using IoT. The sustainable development areas include climate, healthcare systems, electrical systems, and energy that can meet present and next-generation advancement using IoT. Sustainable development faces various issues, challenges, opportunities, and future enhancements with the latest technologies, hardware, and software. Features: A real-world problem-solving approach for diversified problems Potential contributors from industries/academia have been given the opportunity to publish their work Identification of various challenges in IoT for future contributions Diversified coverage of the book, including applications, securities, industrialization, automation, etc IoT for the sustainable development areas This book will offer strong support as a reference book for students, practitioners, researchers, and scientific investigators worldwide, as well as anyone who wants to set up IoT-enabled industries. It provides pertinent industries with new ideas and innovations to visionaries.

Key features Provides an in-depth understanding of emerging technologies and integration of artificial intelligence, deep learning, big data, IoT in healthcare Details specific applications for the use of AI, big data, and IoT in healthcare Discusses how AI technology can help in formulating protective measures for COVID-19 and other diseases Includes case studies

The manufacturing industries remain the foundation of local, regional, and global economies. Manufacturing plants operate in dynamic markets that demand upgrading with transformational technologies for maintaining profitability, competitiveness, and business sustainability. Yet most manufacturing plants currently use technologies that are no longer competitive and industry leaders face an overwhelming array of operational challenges that require agile and enhanced transformational solutions. This book offers manufacturers effective strategies and tools for the adoption and implementation of advanced operational technologies to ensure long-term innovation, efficiency, and profitability. The book covers advanced automation integration in manufacturing, including digitization, AI, machine learning, IIoT, and cybersecurity. It describes innovation, development, and integration of control technologies for sustainable manufacturing. It explains how to upgrade existing manufacturing plants for the global market. It shows how to apply emerging technologies including asset optimization and process integration for product lifecycle improvements, plant operation and maintenance enhancement, and supply chain integration. This book serves as a strategic guide to applying advanced operational technologies for engineers, industry professionals, and management in the manufacturing sector.

The text discusses needs, problems in the implementation of the 5G mobile communication system in the healthcare sector. It covers the issues related to advanced modulation schemes, telehealth, and remote diagnosis. It discusses important topics including virtual healthcare monitoring, spectrum sensing techniques, the role of 5G in medical applications, the role of nano-communication in healthcare informatics, and remote diagnosis. The text will be useful for graduate students, academic researchers, and professionals in the fields of electrical, and electronics and communication engineering, and allied health care. The book- Discusses novel architecture to manage the allocation of resources, interference issue among the existed and advanced radios. Provides focuse to estimate the performance, cost and accommodation of the next generation technologies design for IoT, modern health- care, and education. Covers advanced technologies and its role in health care. Discusses key topics including spectrum access, advanced waveforms, which can help in standardization of 5G based smart hospital. Explores impact of telemedicine in smart health care. This reference text covers the latest advances in the field of 5G Mobile Communication for healthcare informatics, addressing both original algorithm development and new applications of 5G mobile Communications.

Features Introduces the physics of accelerators, lasers, and plasma in tandem with the industrial methodology of inventiveness. Outlines a path from idea to practical implementation of scientific and technological innovation. Contains more than 380 illustrations and numerous end-of-chapter exercises.

Describes how nanomaterial functionalization is being used to create more effective sensors. Discusses various synthesis procedures, characterization techniques, and which nanomaterials should be used for sensing applications. Provides an in-depth look into oxide nanostructures, carbon nanostructures, and 2D material fabrication. Explores the challenges of using nanoscale sensors for large-scale industrial applications.

Covers potential energy storage (rechargeable batteries and supercapacitors) and energy conversion (solar cells and fuel cells) materials. Develops theoretical predictions and experimental observations under a unified quasi-particle framework. Illustrate up-to-date calculation results and experimental measurements. Describes successful synthesis, fabrication, and measurements, as well as potential applications and near future challenges.

This book presents recent advanced techniques in sliding mode control and observer design for industrial power systems, focusing on their applications in polymer electrolyte membrane fuel cells and power converters. Readers will find not only valuable new fault detection and isolation techniques based on sliding mode control and observers, but also a number of robust control and estimation methodologies combined with fuzzy neural networks and extended state observer methods. The book also provides necessary experimental and simulation examples for proton exchange membrane fuel cell systems and power converter systems. Given its scope, it offers a valuable resource for undergraduate and graduate students, academics, scientists and engineers who are working in the field.

This book includes best selected, high-quality research papers presented at the International Conference on Intelligent Manufacturing and Energy Sustainability (ICIMES 2020) held at the Department of Mechanical Engineering, Malla Reddy College of Engineering & Technology (MRCET), Maisammaguda, Hyderabad, India, during August 21-22, 2020. It covers topics in the areas of automation, manufacturing technology and energy sustainability and also includes original works in the intelligent systems, manufacturing, mechanical, electrical, aeronautical, materials, automobile, bioenergy and energy sustainability.

This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, with the overarching goal of balancing the two optimally. The book first motivates extreme-edge computing in the context of the Internet of Things (IoT) paradigm. Then, it briefly reviews the steps involved in the execution of a machine learning task and identifies the implications associated with implementing this type of workload in resource-constrained devices. The core of this book focuses on augmenting and exploiting the properties of Bayesian Networks and Probabilistic Circuits in order to endow them with hardware-awareness. The proposed models can encode the properties of various device sub-systems that are typically not considered by other resource-aware strategies, bringing about resource-saving opportunities that traditional approaches fail to uncover. The performance of the proposed models and strategies is empirically evaluated for several use cases. All of the considered examples show the potential of attaining significant resource-saving opportunities with minimal accuracy losses at application time. Overall, this book constitutes a novel approach to hardware-algorithm co-optimization that further bridges the fields of Machine Learning and Electrical Engineering.

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

This volume helps to address the genuine 21st century need for advances in data science and computing technology. It provides an abundance of new research and studies on progressive and innovative technologies, including artificial intelligence, communication systems, cyber security applications, data analytics, Internet of Things (IoT), machine learning, power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of data science and computing technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and data science problems are included also for an interdisciplinary research perspective. The book addresses recent applications of deep learning and ANN paradigms, the role and impact of big data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security. Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.

Focuses on the latest development in Big IoT Data Analytics Presents different issues of Security and Privacy Analytics for Fog-enabled IoT system Offers the latest Big Data Technologies for security analytics in Fog-enabled IoT Network Discusses the emerging role of Big Data Analytics and Technologies in detection of Cyberattacks in IoT networks Presents the prospects on Big IoT Data Analytics in Fog-enabled IoT system

This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the ‘individual sample as mean’ training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields. Key features: Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classes Discusses range of fuzzy/deep learning models capable to extract specific single class and separates noise Describes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a class Supports multi-sensor and multi-temporal data processing through in-house SMIC software Includes case studies and practical applications for single class mapping This book is intended for graduate/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas.

Features • Provides a cutting edge review of the latest emerging science, technology and applications in the field. • Tackles a topic with fast growing interest in USA, Europe and China. • Explores the simple and cheap design and tests of lasers, and outline the feasible applications.

Provides background material needed to understand digital twin technology Presents computational facet of digital twin Includes physics based and surrogate model representations Addresses the problem of uncertainty in measurements and modeling Discusses practical case studies of implementation of digital twins addressing additive manufacturing, server farms, predictive maintenance, and smart cities

Examine the basic concepts behind today's power systems as well as the tools you need to apply your newly acquired skills to real-world situations with POWER SYSTEM ANALYSIS AND DESIGN, SI, 7th Edition. The latest updates throughout this new edition reflect the most recent trends in the field as the authors highlight key physical concepts with clear explanations of important mathematical techniques. New co-author Adam Birchfield joins this prominent author team with fresh insights into the latest technological advancements. The authors develop theory and modeling from simple beginnings, clearly demonstrating how you can apply the principles you learn to new, more complex situations. New learning objectives and helpful case study summaries help focus your learning, while the updated PowerWorld (R) Simulation works seamlessly with this edition's content to provide hands-on design experience. WebAssign for Glover/Overbye/Sarma's Power System Analysis and Design, SI, 7th Edition, helps you prepare for class with confidence. Its online learning platform for your math, statistics, science and engineering courses helps you practice and absorb what you learn.

This book focuses on control techniques for LCL-type grid-connected inverters to improve system stability, control performance and suppression ability of grid current harmonics. Combining a detailed theoretical analysis with design examples and experimental validations, the book offers an essential reference guide for graduate students and researchers in power electronics, as well as engineers engaged in developing grid-connected inverters for renewable energy generation systems.

Simplify the estimating process with the latest data, materials, and practices Electrical Estimating Methods, Fourth Edition is a comprehensive guide to estimating electrical costs, with data provided by leading construction database RS Means. The book covers the materials and processes encountered by the modern contractor, and provides all the information professionals need to make the most precise estimate. The fourth edition has been updated to reflect the changing materials, techniques, and practices in the field, and provides the most recent Means cost data available. The complexity of electrical systems can make accurate estimation difficult, but this guide contains all the necessary information in one place. An electrical estimate represents the total cost for materials, labor, overhead and profit, but accuracy is virtually impossible without a basic knowledge of the field, and real-world experience in the type of work required. Inaccurate estimates lead to problems with customer satisfaction, which often create payment issues. A thorough, complete, and accurate estimate is in the best interest of all parties involved in the work. Electrical Estimating Methods provides more than just data. Detailed discussions about the work itself help highlight factors that may escape notice, and access to the latest cost data helps tie everything together. Features include: * Discussion of current equipment, materials, and processes * Means data for both residential and commercial projects * Case studies that illustrate best practices * Online access to the latest Means data for fast access on the job The book discusses specific situations as well as general practices, and provides comprehensive guidance to the creation of a true, current, estimation of costs. For electrical contractors and estimators, Electrical Estimating Methods contains must-have content that simplifies the estimating process.

This comprehensive overview of IoT systems architecture includes in-depth treatment of all key components: edge, communications, cloud, data processing, security, management, and uses. Internet of Things: Concepts and System Design provides a reference and foundation for students and practitioners that they can build upon to design IoT systems and to understand how the specific parts they are working on fit into and interact with the rest of the system. This is especially important since IoT is a multidisciplinary area that requires diverse skills and knowledge including: sensors, embedded systems, real-time systems, control systems, communications, protocols, Internet, cloud computing, large-scale distributed processing and storage systems, AI and ML, (preferably) coupled with domain experience in the area where it is to be applied, such as building or manufacturing automation. Written in a reader-minded approach that starts by describing the problem (why should I care?), placing it in context (what does this do and where/how does it fit in the great scheme of things?) and then describing salient features of solutions (how does it work?), this book covers the existing body of knowledge and design practices, but also offers the author's insights and articulation of common attributes and salient features of solutions such as IoT information modeling and platform characteristics.

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.