Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model's adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.

5G IoT and Edge Computing for Smart Healthcare addresses the importance of a 5G IoT and Edge-Cognitive-Computing-based system for the successful implementation and realization of a smart-healthcare system. The book provides insights on 5G technologies, along with intelligent processing algorithms/processors that have been adopted for processing the medical data that would assist in addressing the challenges in computer-aided diagnosis and clinical risk analysis on a real-time basis. Each chapter is self-sufficient, solving real-time problems through novel approaches that help the audience acquire the right knowledge. With the progressive development of medical and communication - computer technologies, the healthcare system has seen a tremendous opportunity to support the demand of today's new requirements.

Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field. The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision making. This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning.

This book experiences the future of patient-centered healthcare and dives into the latest advancements and transformative technologies that are revolutionizing the well-being of individuals around the globe. The readers can join authors on an engaging journey as the authors explore the captivating realm of ambient assisted living and unlock its immense potential for improving healthcare outcomes. This book goes beyond mere exploration; it invites readers to embark on a voyage of discovery as authors unveil the outcomes of groundbreaking research ideas. With a diverse range of applications, from deep learning in healthcare to cutting-edge models, the authors offer a comprehensive view of the opportunities and challenges that lie ahead. Whether you're a healthcare professional, an academic seeking the latest insights, or a researcher delving into the realms of ambient assistive technology, biomedical engineering, or computational intelligence, this book is an invaluable resource. Additionally, postgraduate students pursuing data engineering systems find it to be an essential guide. Each chapter stands independently, providing a comprehensive overview of problem formulation and its tangible outcomes. The readers can immerse themselves in the world of patient-centered healthcare today and become part of the forefront of innovation.

This book is a single-source solution for anyone who is interested in exploring emerging reconfigurable nanotechnology at the circuit level. It lays down a solid foundation for circuits based on this technology having considered both manual as well as automated design flows. The authors discuss the entire design flow, consisting of both logic and physical synthesis for reconfigurable nanotechnology-based circuits. The authors describe how transistor reconfigurable properties can be exploited at the logic level to have a more efficient circuit design flow, as compared to conventional design flows suited for CMOS. Further, the book provides insights into hardware security features that can be intrinsically developed  using the runtime reconfigurable features of this nanotechnology.

This book discusses analysis, design and optimization techniques for streaming multiprocessor systems, while satisfying a given area, performance, and energy budget. The authors describe design flows for both application-specific and general purpose streaming systems. Coverage also includes the use of machine learning for thermal optimization at run-time, when an application is being executed. The design flow described in this book extends to thermal and energy optimization with multiple applications running sequentially and concurrently.

Modern multimedia systems are becoming increasingly multiprocessor and heterogeneous to match the high performance and low power demands placed on them by the large number of applications. The concurrent execution of these applications causes interference and unpredictability in the performance of these systems. In Multimedia Multiprocessor Systems, an analysis mechanism is presented to accurately predict the performance of multiple applications executing concurrently. With high consumer demand the time-to-market has become significantly lower. To cope with the complexity in designing such systems, an automated design-flow is needed that can generate systems from a high-level architectural description such that they are not error-prone and consume less time. Such a design methodology is presented for multiple use-cases -- combinations of active applications. A resource manager is also presented to manage the various resources in the system, and to achieve the goals of performance prediction, admission control and budget enforcement.

Green Energy Systems: Design, Modelling, Synthesis and Applications provides a comprehensive introduction to the design, modeling, optimization and application of predictable and alternative energy systems. With a strong focus on the fundamentals, the book provides an overview of the energy potential and conversion topology of green energy sources, the design and analysis of off grid solar and wind energy sources, and their application in effective energy management in rural communities. Sections address energy systems from solar, wind, biomass, and hybrid energy sources, and include discussions of power electronic circuit topologies for energy conversion in both off and on grid systems. The second part of the book addresses energy harvesting at different scales, with a particular emphasis on micro energy harvesting for low power electronics like wearable devices. A wide range of applications are also discussed, alongside their challenges and solutions. Finally, case studies are presented on select topics to give readers deeper insights into the real-world applications discussed.

The healthcare industry is predominantly moving towards affordable, accessible, and quality health care. All organizations are striving to build communication compatibility among the wide range of devices that have operated independently. Recent developments in electronic devices have boosted the research in the medical imaging field. It incorporates several medical imaging techniques and achieves an important goal for health improvement all over the world. Despite the significant advances in high-resolution medical instruments, physicians cannot always obtain the full amount of information directly from the equipment outputs, and a large amount of data cannot be easily exploited without a computer. Machine Learning and AI Techniques in Interactive Medical Image Analysis discusses how clinical efficiency can be improved by investigating the different types of intelligent techniques and systems to get more reliable and accurate diagnostic conclusions. This book further introduces segmentation techniques to locate suspicious areas in medical images and increase the segmentation accuracy. Covering topics such as computer-aided detection, intelligent techniques, and machine learning, this premier reference source is a dynamic resource for IT specialists, computer scientists, diagnosticians, imaging specialists, medical professionals, hospital administrators, medical students, medical technicians, librarians, researchers, and academicians.

THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

This book presents various novel architectures for FPGA-optimized accurate and approximate operators, their detailed accuracy and performance analysis, various techniques to model the behavior of approximate operators, and thorough application-level analysis to evaluate the impact of approximations on the final output quality and performance metrics. As multiplication is one of the most commonly used and computationally expensive operations in various error-resilient applications such as digital signal and image processing and machine learning algorithms, this book particularly focuses on this operation. The book starts by elaborating on the various sources of error resilience and opportunities available for approximations on various layers of the computation stack. It then provides a detailed description of the state-of-the-art approximate computing-related works and highlights their limitations.

Dieses Buch beschreibt eine neue, grobkörnige rekonfigurierbare Architektur (CGRA), genannt Blocks, und stellt sie in den Kontext von Computerarchitekturen und insbesondere von anderen CGRAs. Das Buch beginnt mit einer ausführlichen Bewertung historischer und bestehender CGRAs und deren Stärken und Schwächen. Dies führt auch zu einem besseren Verständnis und einer neuen Definition dessen, was CGRAs von anderen Architekturansätzen unterscheidet. Die Autoren stellen Blocks als einzigartig vor, da es über separate programmierbare Steuer- und Datenpfade verfügt, so dass leichtgewichtige Befehlsdekodiereinheiten über eine statisch konfigurierte Verbindung beliebig mit einer oder mehreren Funktionseinheiten (FUs) verbunden werden können. In der Diskussion wird erläutert, wie Architekturen modelliert werden können, was zu einem Flächen- und Energiemodell für Blöcke führt. Die Genauigkeit dieses Modells wird anhand vollständig implementierter Architekturen bewertet, wobei sich zeigt, dass die Fehlerspanne sehr akzeptabel ist, obwohl es um drei Größenordnungen schneller ist als die Synthese. Das Buch schließt mit einer Fallstudie zu einem echten System-on-Chip, einschließlich einer RISC-Architektur, der Blocks CGRA und Peripheriegeräten.

The book presents the analysis and control of numerous DC-DC converters widely used in several applications such as standalone, grid integration, and motor drives-based renewable energy systems. The book provides extensive simulation and practical analysis of recent and advanced DC-DC power converter topologies. This self-contained book contributes to DC-DC converters design, control techniques, and industrial as well as domestic applications of renewable energy systems. This volume will be useful for undergraduate/postgraduate students, energy planners, designers, system analysis, and system governors.

This book presents the state of the art of Internet of Things (IoT) from the perspective of healthcare and Ambient Assisted Living (AAL). It discusses the emerging technologies in healthcare services used for healthcare professionals and patients for enhanced living environments and public health. The topics covered in this book include emerging eHealth IoT applications, Internet of Medical Things, health sensors, and wearable sensors for pervasive and personalized healthcare, and smart homes applications for enhanced health and well-being. The book also presents various ideas for the design and development of IoT solutions for healthcare and AAL. It will be useful for bioengineers and professionals working in the areas of healthcare as well as health informatics.

This book comprises select proceedings of the international conference ETAEERE 2020. This volume covers latest research in advanced approaches in automation, control based devices, and adaptive learning mechanisms. The contents discuss the complex operations and behaviors of different systems or machines in different environments. Some of the areas covered include control of linear and nonlinear systems, intelligent systems, stochastic control, knowledge-based systems applications, fault diagnosis and tolerant control, and real-time control applications. The contents of this volume can be useful for researchers as well as professionals working in control and automation.

This book discusses advanced technologies for applications in renewable energy and power systems. The topics covered include neural network applications in power electronics, deep learning applications in power systems, design and simulation of multilevel inverters, solid state transformers, neural network applications for fault detection in power electronics, etc. The book also discusses the important role of artificial intelligence in power systems, and machine learning for renewable energy. This book will be of interest to researchers, professionals, and technocrats looking at power systems, power distribution, and grid operations.

This book comprises select proceedings of the international conference ETAEERE 2020, and covers latest research in the areas of electronics, communication and computing. The book includes different approaches and techniques for specific applications using particle swarm optimization, Otsu's function and harmony search optimization algorithm, DNA-NAND gate, triple gate SOI MOSFET, micro-Raman and FTIR analysis, high-k dielectric gate oxide, spectrum sensing in cognitive radio, microstrip antenna, GPR with conducting surfaces, energy efficient packet routing, iBGP route reflectors, circularly polarized antenna, double fork shaped patch radiator, implementation of Doppler radar at 24 GHz, iris image classification using SVM, digital image forgery detection, secure communication, spoken dialog system, and DFT-DCT spreading strategies. Given the range of topics covered, this book can be useful for both students and researchers working in electronics and communication.

This book presents ongoing research activities of currently available renewable energy technologies and the approaches towards clean technology for enabling a socio-economic model for the present and future generations to live in a clean and healthy environment. The book provides chapter wise implementation of research works in the area of green energy technologies with proper methods used with solution strategies and energy efficiency approaches by combining theory and practical applications. Readers are introduced to practical problems of green computation and hybrid resources optimization with solution based approaches from the current research outcomes. The book will be of use to researchers, professionals, and policy-makers alike.

With rise of smart medical sensors, cloud computing and the health care technologies, "connected health" is getting remarkable consideration everywhere. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality. Cloud computing fits well in this scenario as it can provide high quality of clinical experience. Thus an IoT-cloud convergence can play a vital role in healthcare by offering better insight of heterogeneous healthcare content supporting quality care. It can also support powerful processing and storage facilities of huge data to provide automated decision making. This book aims to report quality research on recent advances towards IoT-Cloud convergence for smart healthcare, more specifically to the state-of-the-art approaches, design, development and innovative use of those convergence methods for providing insights into healthcare service demands. Students, researchers, and medical experts in the field of information technology, medicine, cloud computing, soft computing technologies, IoT and the related fields can benefit from this handbook in handling real-time challenges in healthcare. Current books are limited to focus either on soft computing algorithms or smart healthcare. Integration of smart and cloud computing models in healthcare resulting in connected health is explored in detail in this book.

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future. The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become 'black-box' to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

This book provides detail on applying Internet of Things (IoT) and Internet of Everything (IoE) in smart cities and their design aspects related to physical and network layer models. The authors explore the possibilities of utilizing communication technologies like multi-input multi-output (MIMO), narrow-band IoT (NB-IoT), ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC) for successful implementation of the IoT/IoE. The authors also address the development and advancement in cloud computing to support IoT and IoE. Research on the challenges and future predictions for efficiently implementing and exploring the benefits of smart cities are also explored. The book pertains to researchers, academics, and professionals in the field. Discusses the applicability of Internet of Things (IoT) and Internet of Everything (IoE) for smart cities; Addresses different protocols, networks, and technologies related to the implementation of IoT and IoE for smart cities; Provides a detailed overview on the physical and network layer design and signal processing algorithms related to IoT and IoE.

In recent years, new applications on computer-aided technologies for telemedicine have emerged. Therefore, it is essential to capture this growing research area concerning the requirements of telemedicine. This book presents the latest findings on soft computing, artificial intelligence, Internet of Things and related computer-aided technologies for enhanced telemedicine and e-health. Furthermore, this volume includes comprehensive reviews describing procedures and techniques, which are crucial to support researchers in the field who want to replicate these methodologies in solving their related research problems. On the other hand, the included case studies present novel approaches using computer-aided methods for enhanced telemedicine and e-health. This volume aims to support future research activities in this domain. Consequently, the content has been selected to support not only academics or engineers but also to be used by healthcare professionals.

This book comprises select proceedings of the international conference ETAEERE 2020, and primarily focuses on renewable energy resources and smart grid technologies. The book provides valuable information on the technology and design of power grid integration on microgrids of green energy sources. Some of the topics covered include solar PV array, hybrid microgrid, daylight harvesting, green computing, photovoltaic applications, nanogrid applications, AC/DC/AC converter for wind energy systems, solar photovoltaic panels, PEM fuel cell system, and biogas run dual-fueled diesel engine. The contents of this book will be useful for researchers and practitioners working in the areas of smart grids and renewable energy generation, distribution, and management.

This book addresses the challenges associated with efficient Mixed-Criticality (MC) system design. We focus on application analysis through execution time analysis and task scheduling analysis in order to execute more low-criticality tasks in the system, i.e., improving the Quality-of-Service (QoS), while guaranteeing the correct execution of high-criticality tasks. Further, this book addresses the challenge of enhancing QoS using parallelism in multi-processor hardware platforms.

With rise of smart medical sensors, cloud computing and the health care technologies, “connected health� is getting remarkable consideration everywhere. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality. Cloud computing fits well in this scenario as it can provide high quality of clinical experience. Thus an IoT-cloud convergence can play a vital role in healthcare by offering better insight of heterogeneous healthcare content supporting quality care. It can also support powerful processing and storage facilities of huge data to provide automated decision making. This book aims to report quality research on recent advances towards IoT-Cloud convergence for smart healthcare, more specifically to the state-of-the-art approaches, design, development and innovative use of those convergence methods for providing insights into healthcare service demands. Students, researchers, and medical experts in the field of information technology, medicine, cloud computing, soft computing technologies, IoT and the related fields can benefit from this handbook in handling real-time challenges in healthcare. Current books are limited to focus either on soft computing algorithms or smart healthcare. Integration of smart and cloud computing models in healthcare resulting in connected health is explored in detail in this book.