The subject of this book is theory, principles and methods used in radar algorithm development with a special focus on automotive radar signal processing. In the automotive industry, autonomous driving is currently a hot topic that leads to numerous applications for both safety and driving comfort. It is estimated that full autonomous driving will be realized in the next twenty to thirty years and one of the enabling technologies is radar sensing. This book presents both detection and tracking topics specifically for automotive radar processing. It provides illustrations, figures and tables for the reader to quickly grasp the concepts and start working on practical solutions. The complete and comprehensive coverage of the topic provides both professionals and newcomers with all the essential methods and tools required to successfully implement and evaluate automotive radar processing algorithms.

This book takes a deep dive into ubiquitous computing for applications in health, business, education, tourism, and transportation. The rich interdisciplinary contents of the book appeal to readers from diverse disciplines who aspire to create new and innovative research initiatives and applications in ubiquitous computing. Topics include condition monitoring and diagnostics; multi-objective optimization in design, multi-objective optimization of machining parameters, and more. The book benefits researchers, advanced students, as well as practitioners interested in applications of ubiquitous computing. Features practical, tested applications in ubiquitous computing Includes applications such as health, business, education, electronics, tourism, and transportation Applicable to researchers, academics, students, and professionals

This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.

The book offers a comprehensive survey of interval-valued intuitionistic fuzzy sets. It reports on cutting-edge research carried out by the founder of the intuitionistic fuzzy sets, Prof. Krassimir Atanassov, giving a special emphasis to the practical applications of this extension. A few interesting case studies, such as in the area of data mining, decision making and pattern recognition, among others, are discussed in detail. The book offers the first comprehensive guide on interval-valued intuitionistic fuzzy sets. By providing the readers with a thorough survey and important practical details, it is expected to support them in carrying out applied research and to encourage them to test the theory behind the sets for new advanced applications. The book is a valuable reference resource for graduate students and researchers alike.

Data mining is still a relatively young field, expanding at the rate of technology while advancing tools and techniques for gaining knowledge, finding patterns, and managing databases. Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends is an updated look at the state of technology in the field of data mining and analytics. As processor speeds, database size, network capabilities, artificial intelligence, and most fields of hardware and software continue to improve at a staggering rate of increased capability and pace, it is vital for practitioners to stay abreast of the current issues and research in the field. This volume is perfect for IT specialists, data analysts, practitioners and academics alike, offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining.

This book bridges the communication gap between neuroscientists and engineers through the unifying theme of correlation-based learning

Developing brain-style signal processing or machine learning algorithms has attracted many sharp minds from a range of disciplines. Now, coauthored by four researchers with varying backgrounds in signal processing, neuroscience, psychology, and computer science, Correlative Learning unifies the many cross-fertilized ideas in computational neuroscience and signal processing in a common language that will help engineers understand and appreciate the human brain as a highly sophisticated biosystem for building more intelligent machines.

First, the authors present the necessary neuroscience background for engineers, and then go on to relate the common intrinsic structures of the learning mechanisms of the brain to signal processing, machine learning, kernel learning, complex-valued domains, and the ALOPEX learning paradigm.

This correlation-based approach to building complex, reliable (robust), and adaptive systems is vital for engineers, researchers, and graduate students from various fields of science and engineering. Figures, tables, worked examples, and case studies illustrate how to use computational tools for either helping to understand brain functions or fitting specific engineering applications, and a comprehensive bibliography covering over 1,000 references from major publications is included for further reading.

This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and its application areas. These computing methods also play a significant role in the design and optimization in diverse engineering disciplines. With the influence and the development of the Internet of things (IoT) concept, the need for using soft computing techniques has become more significant than ever. In general, soft computing methods are closely similar to biological processes than traditional techniques, which are mostly based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis. Soft computing techniques are anticipated to complement each other. The aim of these techniques is to accept imprecision, uncertainties, and approximations to get a rapid solution. However, recent advancements in representation soft computing algorithms (fuzzy logic,evolutionary computation, machine learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machine-firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine-wavelet (SVM-Wavelet) have emerged as powerful computational models. These have also shown significant success in dealing with massive data analysis for large number of applications. All the researchers and practitioners will be highly benefited those who are working in field of computer engineering, medicine, biology application, signal processing, and mechanical engineering. This book is a good collection of state-of-the-art approaches for soft computing-based applications to various engineering fields. It is very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health. This book is very useful because there is no book in the market which provides a good collection of state-of-the-art methods of soft computing-based models for multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, and biomedical and health informatics.

This book presents high-quality papers from the Third International Conference on Smart Computing and Informatics (SCI 2018 19), organized by the School of Computer Engineering and School of Computer Application, Kalinga Institute of Industrial Technology Deemed to be University, Bhubaneswar, from 21 to 22 December 2018. It includes advanced and multi-disciplinary research on the design of smart computing and informatics, focusing on innovation paradigms in system knowledge, intelligence and sustainability that have the potential to provide realistic solutions to various problems in society, the environment and industry. The papers featured provide a valuable contribution to the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in varied disciplines of science, technology and health care.

"Contemporary Issues in Database Design and Information" presents the latest research ideas and topics on databases and software development. The chapters in this innovative publication provide a representation of topnotch research in all areas of the database and information systems development.

The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe-Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.

This book highlights new trends and challenges in intelligent systems, which play an essential part in the digital transformation of many areas of science and practice. It includes papers offering a deeper understanding of the human-centred perspective on artificial intelligence, of intelligent value co-creation, ethics, value-oriented digital models, transparency, and intelligent digital architectures and engineering to support digital services and intelligent systems, the transformation of structures in digital business and intelligent systems based on human practices, as well as the study of interaction and co-adaptation of humans and systems. All papers were originally presented at the International KES Conference on Human Centred Intelligent Systems 2021 (KES HCIS 2021) held on June 14-16, 2021 in the KES Virtual Conference Centre.

This textbook is designed for graduate-level courses, and for self-study, in analog and sampled-data, including switched-capacitor, circuit theory and design for ongoing, or active electrical engineers, needing to become proficient in analog circuit design on a system, rather than on a device, level. After decades of experience in industry and teaching this material in academic settings, the author has extracted many of the most important and useful features of analog circuit theory and design and presented them in a manner that is easy to digest and utilize. The methodology and analysis techniques presented can be applied to areas well beyond those specifically addressed in this book. This book is meant to enable readers to gain a 'general knowledge' of one aspect of analog engineering (e.g., that of network theory, filter design, system theory and sampled-data signal processing). The presentation is self-contained and should be accessible to anyone with a first degree in electrical engineering.

This book has a focus on the development and deployment of the Industrial Internet of Things (IIoT) paradigm, discussing frameworks, methodologies, benefits and limitations, as well as providing case studies of employing the IoT vision in the industrial domain. IIoT is becoming an attractive business reality for many organisations such as manufacturing, logistics, oil and gas, energy and other utilities, mining, aviation, and many more. The opportunities for this paradigm are huge, and according to one report, the IIoT market is predicted to reach $125 billion by 2021. The driving philosophy behind the IIoT is that smart machines are better than humans at accurately capturing, analysing and communicating real-time data. The underlying technologies include distributed computing, machine learning, artificial intelligence, and machine-to-machine communication, with a typical IIoT system consisting of intelligent systems (applications, controllers, sensors, and security mechanisms), data communication infrastructure (cloud computing, edge computing, etc.), data analytics (to support business intelligence and corporate decision making), and most importantly the human element. The promised benefits of the IIoT include enhanced safety, better reliability, smart metering, inventory management, equipment tracking, and facilities management. There are, however, numerous issues that are also becoming the focus of active research, such as concerns regarding service availability, data security, and device communication. Lack of ubiquitous interoperability between heterogeneous devices is also a major concern. This book intends to fill a gap in the IIoT literature by providing the scientific contributions and latest developments from researchers and practitioners of international repute, focusing on frameworks, methodologies, benefits, and inherent issues/barriers to connected environments, especially in industrial settings. The intended audience includes network specialists, hardware engineers, and security experts who wish to adopt newer approaches for device connectivity, IoT security, and sensor-based devices design. University level students, researchers and practitioners will also find the latest innovation in technology and newer approaches relevant to the IIoT from a distributed computing perspective.

This book reports on the latest advances in using BIM modelling to achieve the semantic enrichment of objects, allowing them to be used both as multidimensional databases - as comprehensive sources of information for finalizing various types of documentation in the building industry - and as modelling tools for the construction of virtual environments. Having advanced to a new stage of development, BIM modelling is now being applied in a range of increasingly complex contexts, and for various new purposes. This book examines the role that virtual reality and related technologies such as AI and IoT can play in preserving and disseminating our cultural heritage and built environment.

The book proposes new technologies and discusses innovative solutions to various problems in the field of communication, circuits, and systems, as reflected in high-quality papers presented at International Conference on Communication, Circuits, and Systems (IC3S 2020) held at KIIT, Bhubaneswar, India from 16 - 18 October 2020. It brings together new works from academicians, scientists, industry professionals, scholars, and students together to exchange research outcomes and open up new horizons in the areas of signal processing, communications, and devices.

Facial recognition software has improved by leaps and bounds over the past few decades, with error rates decreasing significantly within the past ten years. Though this is true, conditions such as poor lighting, obstructions, and profile-only angles have continued to persist in preventing wholly accurate readings. Face Recognition in Adverse Conditions examines how the field of facial recognition takes these adverse conditions into account when designing more effective applications by discussing facial recognition under real world PIE variations, current applications, and the future of the field of facial recognition research. The work is intended for academics, engineers, and researchers specializing in the field of facial recognition.

This book presents best selected research papers presented at the International Conference on Recent Trends in Communication and Intelligent Systems (ICRTCIS 2020), organized by Arya College of Engineering and IT, Jaipur, on 20-21 November 2020. It discusses the latest technologies in communication and intelligent systems, covering various areas of communication engineering, such as signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general. Featuring work by leading researchers and technocrats, the book serves as a valuable reference resource for young researchers and academics as well as practitioners in industry.

This book proposes new control and protection schemes to improve the overall stability and security of future wide-area power systems. It focuses on the high penetration levels of renewable energy sources and distributed generation, particularly with the trend towards smart grids. The control methods discussed can improve the overall stability in normal and abnormal operation conditions, while the protection methods presented can be used to ensure the secure operation of systems under most severe contingencies. Presenting stability, security, and protection methods for power systems in one concise volume, this book takes the reader on a journey from concepts and fundamentals to the latest and future trends in each topic covered, making it an informative and intriguing read for researchers, graduate students, and practitioners alike.

Going Virtual: Distributed Communities in Practice contributes to the understanding of how more subtle kinds of knowledge can be managed in a distributed international environment. It describes academic work in the field of Knowledge Management, with a specific focus on the management of knowledge which cannot be managed by the normal capture-codify-store approach and hopes to answer the question, "what is the nature of the more 'subtle' kind of knowledge and how can it be managed in the distributed environment?"

With the proliferation of devices connected to the internet and connected to each other, the volume of data collected, stored, and processed is increasing every day, which brings new challenges in terms of information security. As big data expands with the help of public clouds, traditional security solutions tailored to private computing infrastructures and confined to a well-defined security perimeter, such as firewalls and demilitarized zones (DMZs), are no longer effective. New security functions are required to work over the heterogenous composition of diverse hardware, operating systems, and network domains. Security, Privacy, and Forensics Issues in Big Data is an essential research book that examines recent advancements in big data and the impact that these advancements have on information security and privacy measures needed for these networks. Highlighting a range of topics including cryptography, data analytics, and threat detection, this is an excellent reference source for students, software developers and engineers, security analysts, IT consultants, academicians, researchers, and professionals.

Tired of writing all your user IDs and passwords on sticky notes and pieces of scrap paper? This convenient address book stores them all in one place. This is not your typical address book There are also special sections for online banking info and one for storing e-mail addresses.

This edited volume explores the intersection between philosophy and computing. It features work presented at the 2016 annual meeting of the International Association for Computing and Philosophy. The 23 contributions to this volume neatly represent a cross section of 40 papers, four keynote addresses, and eight symposia as they cut across six distinct research agendas. The volume begins with foundational studies in computation and information, epistemology and philosophy of science, and logic. The contributions next examine research into computational aspects of cognition and philosophy of mind. This leads to a look at moral dimensions of man-machine interaction as well as issues of trust, privacy, and justice. This multi-disciplinary or, better yet, a-disciplinary investigation reveals the fruitfulness of erasing distinctions among and boundaries between established academic disciplines. This should come as no surprise. The computational turn itself is a-disciplinary and no former discipline, whether scientific, artistic, or humanistic, has remained unchanged. Rigorous reflection on the nature of these changes opens the door to inquiry into the nature of the world, what constitutes our knowledge of it, and our understanding of our place in it. These investigations are only just beginning. The contributions to this volume make this clear: many encourage further research and end with open questions.

This book explores the main elements of e-Democracy, the term normally used to describe the implementation of democratic government processes by electronic means. It provides insights into the main technological and human issues regarding governance, government, participation, inclusion, empowerment, procurement and, last but not least, ethical and privacy issues. Its main aim is to bridge the gap between technological solutions, their successful implementation, and the fruitful utilization of the main set of e-Services totally or partially delivered by governments or non-government organizations. Today, various parameters actively influence e-Services' success or failure: cultural aspects, organisational issues, bureaucracy and workflows, infrastructure and technology in general, user habits, literacy, capacity or merely interaction design. This includes having a significant population of citizens who are willing and able to adopt and use online services; as well as developing the managerial and technical capability to implement applications that meet citizens' needs. This book helps readers understand the mutual dependencies involved; further, a selection of success stories and failures, duly commented on, enables readers to identify the right approach to innovation in governmental e-Services. With its balanced humanistic and technological approach, the book mainly targets public authorities, decision-makers, stakeholders, solution developers, and graduate students.

Hybrid learning is now the single-greatest trend in education today due to the numerous educational advantages when both traditional classroom learning and e-learning are implemented collectively. The Handbook of Research on Hybrid Learning Models: Advanced Tools, Technologies, and Applications collects emerging research and pedagogies related to the convergence of teaching and learning methods. This significant Handbook of Research provides researchers, scholars, students, and professionals access to the latest knowledge related to hybrid learning, discovered and written by an international gathering of e-learning experts.