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

Dependable Network Computing provides insights into various problems facing millions of global users resulting from the internet revolution'. It covers real-time problems involving software, servers, and large-scale storage systems with adaptive fault-tolerant routing and dynamic reconfiguration techniques. Also included is material on routing protocols, QoS, and dead- and live-lock free related issues. All chapters are written by leading specialists in their respective fields. Dependable Network Computing provides useful information for scientists, researchers, and application developers building networks based on commercially off-the-shelf components.

This book presents MOSFET-based current mode logic (CML) topologies, which increase the speed, and lower the transistor count, supply voltage and power consumption. The improved topologies modify the conventional PDN, load, and the current source sections of the basic CML gates. Electronic system implementation involves embedding digital and analog circuits on a single die shifting towards mixed-mode circuit design. The high-resolution, low-power and low-voltage analog circuits are combined with high-frequency complex digital circuits, and the conventional static CMOS logic generates large current spikes during the switching (also referred to as digital switching noise), which degrade the resolution of the sensitive analog circuits via supply line and substrate coupling. This problem is exacerbated further with scaling down of CMOS technology due to higher integration levels and operating frequencies. In the literature, several methods are described to reduce the propagation of the digital switching noise. However, in high-resolution applications, these methods are not sufficient. The conventional CMOS static logic is no longer an effective solution, and therefore an alternative with reduced current spikes or that draws a constant supply current must be selected. The current mode logic (CML) topology, with its unique property of requiring constant supply current, is a promising alternative to the conventional CMOS static logic.

The book provides knowledge in the Building Information Model (BIM)-enabled cognitive computing methods for smart built environment involving cognitive network capabilities for smart buildings, integrating Augmented Reality/Mixed Reality in cognitive building concepts, cognitive Internet of Things (CIoT) for smart cities, Artificial Intelligence applications for cognitive cities, and cognitive smart cities using big data and machine learning. It focuses on the potential, requirements and implementation of CIoT paradigm to buildings, Artificial Intelligence techniques, reasoning, and Augmented Reality/Mixed Reality in cognitive building concepts, the concept of cognitive smart cities in its complexity, heterogeneity, and scope, and the challenge of utilizing the big data generated by smart cities from a machine learning perspective. The book comprises BIM-based and data-analytic research on cognitive IoT for smart buildings and cognitive cities using big data and machine learning as complex and dynamic systems. It presents applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the motivating physical and informational settings. It reviews ongoing development of BIM-based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to cognitive systems that will advance different aspects of future cognitive cities. The book also analyses the required material to inform pertinent research communities of the state-of-the-art research and the latest development in the area of cognitive smart cities development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of CIoT based on big data analytics and context-aware computing.

Amid recent interest in Clifford algebra for dual quaternions as a more suitable method for Computer Graphics than standard matrix algebra, this book presents dual quaternions and their associated Clifford algebras in a new light, accessible to and geared towards the Computer Graphics community. Collating all the associated formulas and theorems in one place, this book provides an extensive and rigorous treatment of dual quaternions, as well as showing how two models of Clifford algebras emerge naturally from the theory of dual quaternions. Each chapter comes complete with a set of exercises to help readers sharpen and practice their knowledge. This book is accessible to anyone with a basic knowledge of quaternion algebra and is of particular use to forward-thinking members of the Computer Graphics community. .

This book provides an introduction to decision making in a distributed computational framework. Classical detection theory assumes a centralized configuration. All observations are processed by a central processor to produce the decision. In the decentralized detection system, distributed detectors generate decisions based on locally available observations; these decisions are then conveyed to the fusion center that makes the global decision. Using numerous examples throughout the book, the author discusses such distributed detection processes under several different formulations and in a wide variety of network topologies.

Topics covered include: elements of detection theory; distributed Bayesian detection in parallel fusion networks and in other network topologies; distributed detection with false-alarm rate constraints; distributed sequential detection; and information theory and distributed hypotheses testing.

By providing a unified treatment of the recent advances, this book should prove valuable not only to researchers active in the field, but also to graduate students and others embarking on research in detection, signal processing, and statistical decision theory.

This book addresses dynamic modelling methodology and analyses of tree-type robotic systems. Such analyses are required to visualize the motion of a system without really building it. The book contains novel treatment of the tree-type systems using concept of kinematic modules and the corresponding Decoupled Natural Orthogonal Complements (DeNOC), unified representation of the multiple-degrees-of freedom-joints, efficient recursive dynamics algorithms, and detailed dynamic analyses of several legged robots. The book will help graduate students, researchers and practicing engineers in applying their knowledge of dynamics for analysis of complex robotic systems. The knowledge contained in the book will help one in virtual testing of robot operation, trajectory planning and control.

A complete and authoritative discussion of systems engineering and neural networks In Systems Engineering Neural Networks, a team of distinguished researchers deliver a thorough exploration of the fundamental concepts underpinning the creation and improvement of neural networks with a systems engineering mindset. In the book, you'll find a general theoretical discussion of both systems engineering and neural networks accompanied by coverage of relevant and specific topics, from deep learning fundamentals to sport business applications. Readers will discover in-depth examples derived from many years of engineering experience, a comprehensive glossary with links to further reading, and supplementary online content. The authors have also included a variety of applications programmed in both Python 3 and Microsoft Excel. The book provides: A thorough introduction to neural networks, introduced as key element of complex systems Practical discussions of systems engineering and forecasting, complexity theory and optimization and how these techniques can be used to support applications outside of the traditional AI domains Comprehensive explorations of input and output, hidden layers, and bias in neural networks, as well as activation functions, cost functions, and back-propagation Guidelines for software development incorporating neural networks with a systems engineering methodology Perfect for students and professionals eager to incorporate machine learning techniques into their products and processes, Systems Engineering Neural Networks will also earn a place in the libraries of managers and researchers working in areas involving neural networks.

This book describes digital design techniques with exercises. The concepts and exercises discussed are useful to design digital logic from a set of given specifications. Looking at current trends of miniaturization, the contents provide practical information on the issues in digital design and various design optimization and performance improvement techniques at logic level. The book explains how to design using digital logic elements and how to improve design performance. The book also covers data and control path design strategies, architecture design strategies, multiple clock domain design and exercises , low-power design strategies and solutions at the architecture and logic-design level. The book covers 60 exercises with solutions and will be useful to engineers during the architecture and logic design phase. The contents of this book prove useful to hardware engineers, logic design engineers, students, professionals and hobbyists looking to learn and use the digital design techniques during various phases of design.

This book uses automotive embedded systems as an example to introduce functional safety assurance and safety-aware cost optimization. The book explores functional safety assurance from the perspectives of verification, enhancement, and validation. The functional safety assurance methods implement a safe and efficient assurance system that integrates safety verification, enhancement, and validation. The assurance methods offered in this book could provide a reasonable and scientific theoretical basis for the subsequent formulation of automotive functional safety standards. The safety-aware cost optimization methods divide cost types according to the essential differences of various costs in system design and establish reasonable models based on different costs. The cost optimization methods provided in this book could give appropriate cost optimization solutions for the cost-sensitive automotive industry, thereby achieving effective cost management and control. Functional safety assurance methods and safety-aware cost optimization support each other and jointly build the architecture of functional safety design methodologies for automotive embedded systems. The work aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in hardware cost optimization and development cost optimization design methods based on ensuring functional safety in general.

Providing an in-depth introduction to fundamental classical and non-classical logics, this textbook offers a comprehensive survey of logics for computer scientists. Logics for Computer Science contains intuitive introductory chapters explaining the need for logical investigations, motivations for different types of logics and some of their history. They are followed by strict formal approach chapters. All chapters contain many detailed examples explaining each of the introduced notions and definitions, well chosen sets of exercises with carefully written solutions, and sets of homework. While many logic books are available, they were written by logicians for logicians, not for computer scientists. They usually choose one particular way of presenting the material and use a specialized language. Logics for Computer Science discusses Gentzen as well as Hilbert formalizations, first order theories, the Hilbert Program, Godel's first and second incompleteness theorems and their proofs. It also introduces and discusses some many valued logics, modal logics and introduces algebraic models for classical, intuitionistic, and modal S4 and S5 logics. The theory of computation is based on concepts defined by logicians and mathematicians. Logic plays a fundamental role in computer science, and this book explains the basic theorems, as well as different techniques of proving them in classical and some non-classical logics. Important applications derived from concepts of logic for computer technology include Artificial Intelligence and Software Engineering. In addition to Computer Science, this book may also find an audience in mathematics and philosophy courses, and some of the chapters are also useful for a course in Artificial Intelligence.

This book describes novel methods for network-on-chip (NoC) design, using source-synchronous high-speed resonant clocks. The authors discuss NoCs from the bottom up, providing circuit level details, before providing architectural simulations. As a result, readers will get a complete picture of how a NoC can be designed and optimized.Using the methods described in this book, readers are enabled to design NoCs that are 5X better than existing approaches in terms of latency and throughput and can also sustain a significantly greater amount of traffic."

During a meeting in Toronto last winter, Mike Jenkins, Bob Bernecky and I were discussing how the two existing theories on arrays influenced or were in fluenced by programming languages and systems. More's Army Theory was the basis for NIAL and APL2 and Mullin's A Mathematics of A rmys(MOA), is being used as an algebra of arrays in functional and A-calculus based pro gramming languages. MOA was influenced by Iverson's initial and extended algebra, the foundations for APL and J respectively. We discussed that there is a lot of interest in the Computer Science and Engineering communities concerning formal methods for languages that could support massively parallel operations in scientific computing, a back to-roots interest for both Mike and myself. Languages for this domain can no longer be informally developed since it is necessary to map languages easily to many multiprocessor architectures. Software systems intended for parallel computation require a formal basis so that modifications can be done with relative ease while ensuring integrity in design. List based lan guages are profiting from theoretical foundations such as the Bird-Meertens formalism. Their theory has been successfully used to describe list based parallel algorithms across many classes of architectures."

BASIC Microcomputing and Biostatistics is designed as the first practical "how to" guide to both computer programming in BASIC and the statis tical data processing techniques needed to analyze experimental, clinical, and other numerical data. It provides a small vocabulary of essential com puter statements and shows how they are used to solve problems in the bio logical, physical, and medical sciences. No mathematical background be yond algebra and an inkling of the principles of calculus is assumed. All more advanced mathematical techniques are developed from "scratch" before they are used. The computing language is BASIC, a high-level lan guage that is easy to learn and widely available using time-sharing com puter systems and personal microcomputers. The strategy of the book is to present computer programming at the outset and to use it throughout. BASIC is developed in a way reminiscent of graded readers used in human languages; the first programs are so sim ple that they can be read almost without an introduction to the language. Each program thereafter contains new vocabulary and one or more con cepts, explained in the text, not used in the previous ones. By gradual stages, the reader can progress from programs that do nothing more than count from one to ten to sophisticated programs for nonlinear curve fitting, matrix algebra, and multiple regression. There are 33 working programs and, except for the introductory ones, each performs a useful function in everyday data processing problems encountered by the experimentalist in many diverse fields."

This book applies both industrial engineering and computational intelligence to demonstrate intelligent machines that solve real-world problems in various smart environments. The title presents fundamental concepts and the latest advances in Multi-Criteria Decision Making (MCDM) techniques and their application to smart environments. Though managers and engineers often use multi-criteria analysis in making complex decisions, many core problems are too difficult to model mathematically or have simply not yet been modelled. In response, as well as AI-based approaches, this book covers various optimization techniques, decision analytics and data science in applying soft computing techniques to a defined set of smart environments, including smart and sustainable cities, disaster response systems and smart campuses. This state-of-the-art book will be essential reading for both undergraduate and graduate students, researchers, practitioners and decision makers interested in advanced MCDM techniques for management and engineering in relation to smart environments.

Provides comprehensive research ideas about Edge-AI technology that can assist doctors in making better data-driven decisions and will provide insights to researchers about healthcare industry, trends and future perspective. Examines how healthcare systems of the future will operate, by augmenting clinical resources and ensuring optimal patient outcomes. Provides insight about how Edge-AI is revolutionizing decision making, early warnings for conditions, and visual inspection in healthcare. Highlight trends, challenges, opportunities and future areas where Healthcare informatics deal with accessing vast data sets of potentially life-saving information.

This book is timely and discusses the effects from the pandemic. Written for longevity, and may be useful to compare this pandemic and the response to future events. The book is written for academia: social sciences, public health, information science, emergency management, and policy fields, and is easier informational reading for the layperson.

This open access book presents theoretical framework and sample applications of variant construction. The first part includes the components variant logic, variant measurements, and variant maps, while the second part covers sample applications such as variation with functions, variant stream ciphers, quantum interference, classical/quantum random sequences, whole DNA sequences, and multiple-valued pulse sequences. Addressing topics ranging from logic and measuring foundation to typical applications and including various illustrated maps, it is a valuable guide for theoretical researchers in discrete mathematics; computing-, quantum- and communication scientists; big data engineers; as well as graduate and upper undergraduate students.

Distributed and Parallel Systems: Cluster and Grid Computing is the proceedings of the fourth Austrian-Hungarian Workshop on Distributed and Parallel Systems organized jointly by Johannes Kepler University, Linz, Austria and the MTA SZTAKI Computer and Automation Research Institute.

The papers in this volume cover a broad range of research topics presented in four groups. The first one introduces cluster tools and techniques, especially the issues of load balancing and migration. Another six papers deal with grid and global computing including grid infrastructure, tools, applications and mobile computing. The next nine papers present general questions of distributed development and applications. The last four papers address a crucial issue in distributed computing: fault tolerance and dependable systems.

This volume will be useful to researchers and scholars interested in all areas related to parallel and distributed computing systems.

Today's healthcare organizations must focus on a lot more than just the health of their clients. The infrastructure it takes to support clinical-care delivery continues to expand, with information technology being one of the most significant contributors to that growth. As companies have become more dependent on technology for their clinical, administrative, and financial functions, their IT departments and expenditures have had to scale quickly to keep up. However, as technology demands have increased, so have the options for reliable infrastructure for IT applications and data storage. The one that has taken center stage over the past few years is cloud computing. Healthcare researchers are moving their efforts to the cloud because they need adequate resources to process, store, exchange, and use large quantities of medical data. Cloud Computing in Medical Imaging covers the state-of-the-art techniques for cloud computing in medical imaging, healthcare technologies, and services. The book focuses on Machine-learning algorithms for health data security Fog computing in IoT-based health care Medical imaging and healthcare applications using fog IoT networks Diagnostic imaging and associated services Image steganography for medical informatics This book aims to help advance scientific research within the broad field of cloud computing in medical imaging, healthcare technologies, and services. It focuses on major trends and challenges in this area and presents work aimed to identify new techniques and their use in biomedical analysis.

1. The book will discuss most relevant real-life applications and case studies of Network Technologies. 2. The book will provide deeper knowledge regarding emerging research trends and future research directions in Network Technologies. 3. The book will provide theoretical, algorithmic, simulation, and implementation-based research developments in Network Technologies. 4. The book will follow theoretical approach to describe fundamentals of Network Technologies for the beginners as well as practical approach to depict simulation and implementation of real-life applications for intermediate and advanced readers.

This textbook is ideal for senior undergraduate and graduate courses in RF CMOS circuits, RF circuit design, and high-frequency analog circuit design. It is aimed at electronics engineering students and IC design engineers in the field, wishing to gain a deeper understanding of circuit fundamentals, and to go beyond the widely-used automated design procedures. The authors employ a design-centric approach, in order to bridge the gap between fundamental analog electronic circuits textbooks and more advanced RF IC design texts. The structure and operation of the building blocks of high-frequency ICs are introduced in a systematic manner, with an emphasis on transistor-level operation, the influence of device characteristics and parasitic effects, and input-output behavior in the time and frequency domains. This second edition has been revised extensively, to expand some of the key topics, to clarify the explanations, and to provide extensive design examples and problems. New material has been added for basic coverage of core topics, such as wide-band LNAs, noise feedback concept and noise cancellation, inductive-compensated band widening techniques for flat-gain or flat-delay characteristics, and basic communication system concepts that exploit the convergence and co-existence of Analog and Digital building blocks in RF systems. A new chapter (Chapter 5) has been added on Noise and Linearity, addressing key topics in a comprehensive manner. All of the other chapters have also been revised and largely re-written, with the addition of numerous, solved design examples and exercise problems.

This book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware.

While most discoverability evaluation studies in the Library and Information Science field discuss the intersection of discovery layers and library systems, this book looks specifically at digital repositories, examining discoverability from the lenses of system structure, user searches, and external discovery avenues. Discoverability, the ease with which information can be found by a user, is the cornerstone of all successful digital information platforms. Yet, most digital repository practitioners and researchers lack a holistic and comprehensive understanding of how and where discoverability happens. This book brings together current understandings of user needs and behaviors and poses them alongside a deeper examination of digital repositories around the theme of discoverability. It examines discoverability in digital repositories from both user and system perspectives by exploring how users access content (including their search patterns and habits, need for digital content, effects of outreach, or integration with Wikipedia and other web-based tools) and how systems support or prevent discoverability through the structure or quality of metadata, system interfaces, exposure to search engines or lack thereof, and integration with library discovery tools. Discoverability in Digital Repositories will be particularly useful to digital repository managers, practitioners, and researchers, metadata librarians, systems librarians, and user studies, usability and user experience librarians. Additionally, and perhaps most prominently, this book is composed with the emerging practitioner in mind. Instructors and students in Library and Information Science and Information Management programs will benefit from this book that specifically addresses discoverability in digital repository systems and services.