Provides insight into the skill set that requires leveraging strength to move further to act as a good data analyst Discusses how big data along with deep learning holds the potential to significantly increase data understanding and in turn, helps to make decisions Covers the numerous potential applications in healthcare, education, communications, media, and the entertainment industry Offers innovative platforms for integrating big data and deep learning Presents issues related to adequate data storage, sematic indexing, data tagging, and fast information retrieval from big data

This book provides readers with an up-to-date account of the use of machine learning frameworks, methodologies, algorithms and techniques in the context of computer-aided design (CAD) for very-large-scale integrated circuits (VLSI). Coverage includes the various machine learning methods used in lithography, physical design, yield prediction, post-silicon performance analysis, reliability and failure analysis, power and thermal analysis, analog design, logic synthesis, verification, and neuromorphic design. Provides up-to-date information on machine learning in VLSI CAD for device modeling, layout verifications, yield prediction, post-silicon validation, and reliability; Discusses the use of machine learning techniques in the context of analog and digital synthesis; Demonstrates how to formulate VLSI CAD objectives as machine learning problems and provides a comprehensive treatment of their efficient solutions; Discusses the tradeoff between the cost of collecting data and prediction accuracy and provides a methodology for using prior data to reduce cost of data collection in the design, testing and validation of both analog and digital VLSI designs. From the Foreword As the semiconductor industry embraces the rising swell of cognitive systems and edge intelligence, this book could serve as a harbinger and example of the osmosis that will exist between our cognitive structures and methods, on the one hand, and the hardware architectures and technologies that will support them, on the other....As we transition from the computing era to the cognitive one, it behooves us to remember the success story of VLSI CAD and to earnestly seek the help of the invisible hand so that our future cognitive systems are used to design more powerful cognitive systems. This book is very much aligned with this on-going transition from computing to cognition, and it is with deep pleasure that I recommend it to all those who are actively engaged in this exciting transformation. Dr. Ruchir Puri, IBM Fellow, IBM Watson CTO & Chief Architect, IBM T. J. Watson Research Center

This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.

This book is based on the 18 tutorials presented during the 26th workshop on Advances in Analog Circuit Design. Expert designers present readers with information about a variety of topics at the frontier of analog circuit design, with specific contributions focusing on hybrid ADCs, smart sensors for the IoT, sub-1V and advanced-node analog circuit design. This book serves as a valuable reference to the state-of-the-art, for anyone involved in analog circuit research and development.

Fueled by ubiquitous computing ambitions, the edge is at the center of confluence of many emergent technological trends such as hardware-rooted trust and code integrity, 5G, data privacy and sovereignty, blockchains and distributed ledgers, ubiquitous sensors and drones, autonomous systems and real-time stream processing. Hardware and software pattern maturity have reached a tipping point so that scenarios like smart homes, smart factories, smart buildings, smart cities, smart grids, smart cars, smart highways are in reach of becoming a reality. While there is a great desire to bring born-in-the-cloud patterns and technologies such as zero-downtime software and hardware updates/upgrades to the edge, developers and operators alike face a unique set of challenges due to environmental differences such as resource constraints, network availability and heterogeneity of the environment. The first part of the book discusses various edge computing patterns which the authors have observed, and the reasons why these observations have led them to believe that there is a need for a new architectural paradigm for the new problem domain. Edge computing is examined from the app designer and architect's perspectives. When they design for edge computing, they need a new design language that can help them to express how capabilities are discovered, delivered and consumed, and how to leverage these capabilities regardless of location and network connectivity. Capability-Oriented Architecture is designed to provide a framework for all of these. This book is for everyone who is interested in understanding what ubiquitous and edge computing means, why it is growing in importance and its opportunities to you as a technologist or decision maker. The book covers the broad spectrum of edge environments, their challenges and how you can address them as a developer or an operator. The book concludes with an introduction to a new architectural paradigm called capability-based architecture, which takes into consideration the capabilities provided by an edge environment. .

Dependence Analysis may be considered to be the second edition of the author's 1988 book, Dependence Analysis for Supercomputing. It is, however, a completely new work that subsumes the material of the 1988 publication. This book is the third volume in the series Loop Transformations for Restructuring Compilers. This series has been designed to provide a complete mathematical theory of transformations that can be used to automatically change a sequential program containing FORTRAN-like do loops into an equivalent parallel form. In Dependence Analysis, the author extends the model to a program consisting of do loops and assignment statements, where the loops need not be sequentially nested and are allowed to have arbitrary strides. In the context of such a program, the author studies, in detail, dependence between statements of the program caused by program variables that are elements of arrays. Dependence Analysis is directed toward graduate and undergraduate students, and professional writers of restructuring compilers. The prerequisite for the book consists of some knowledge of programming languages, and familiarity with calculus and graph theory. No knowledge of linear programming is required.

This book provides an overview of emerging topics in the field of hardware security, such as artificial intelligence and quantum computing, and highlights how these technologies can be leveraged to secure hardware and assure electronics supply chains. The authors are experts in emerging technologies, traditional hardware design, and hardware security and trust. Readers will gain a comprehensive understanding of hardware security problems and how to overcome them through an efficient combination of conventional approaches and emerging technologies, enabling them to design secure, reliable, and trustworthy hardware.

This book provides an insightful guide to the design, testing and optimization of micro-electrode-dot-array (MEDA) digital microfluidic biochips. The authors focus on the characteristics specific for MEDA biochips, e.g., real-time sensing and advanced microfluidic operations like lamination mixing and droplet shape morphing. Readers will be enabled to enhance the automated design and use of MEDA and to develop a set of solutions to facilitate the full exploitation of design complexities that are possible with standard CMOS fabrication techniques. The book provides the first set of design automation and test techniques for MEDA biochips. The methods described in this book have been validated using fabricated MEDA biochips in the laboratory. Readers will benefit from an in-depth look at the MEDA platform and how to combine microfluidics with software, e.g., applying biomolecular protocols to software-controlled and cyberphysical microfluidic biochips.

This reference text presents the usage of artificial intelligence in healthcare and discusses the challenges and solutions of using advanced techniques like wearable technologies and image processing in the sector. Features: Focuses on the use of artificial intelligence (AI) in healthcare with issues, applications, and prospects Presents the application of artificial intelligence in medical imaging, fractionalization of early lung tumour detection using a low intricacy approach, etc Discusses an artificial intelligence perspective on wearable technology Analyses cardiac dynamics and assessment of arrhythmia by classifying heartbeat using electrocardiogram (ECG) Elaborates machine learning models for early diagnosis of depressive mental affliction This book serves as a reference for students and researchers analyzing healthcare data. It can also be used by graduate and post graduate students as an elective course.

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.

Hardware Security: A Hands-On Learning Approach provides a broad, comprehensive and practical overview of hardware security that encompasses all levels of the electronic hardware infrastructure. It covers basic concepts like advanced attack techniques and countermeasures that are illustrated through theory, case studies and well-designed, hands-on laboratory exercises for each key concept. The book is ideal as a textbook for upper-level undergraduate students studying computer engineering, computer science, electrical engineering, and biomedical engineering, but is also a handy reference for graduate students, researchers and industry professionals. For academic courses, the book contains a robust suite of teaching ancillaries. Users will be able to access schematic, layout and design files for a printed circuit board for hardware hacking (i.e. the HaHa board) that can be used by instructors to fabricate boards, a suite of videos that demonstrate different hardware vulnerabilities, hardware attacks and countermeasures, and a detailed description and user manual for companion materials.

This book introduces a new scheduler to fairly and efficiently distribute system resources to many users of varying usage patterns compete for them in large shared computing environments. The Rawlsian Fair scheduler developed for this effort is shown to boost performance while reducing delay in high performance computing workloads of certain types including the following four types examined in this book: i. Class A - similar but complementary workloads ii. Class B - similar but steady vs intermittent workloads iii. Class C - Large vs small workloads iv. Class D - Large vs noise-like workloads This new scheduler achieves short-term fairness for small timescale demanding rapid response to varying workloads and usage profiles. Rawlsian Fair scheduler is shown to consistently benefit workload Classes C and D while it only benefits Classes A and B workloads where they become disproportionate as the number of users increases. A simulation framework, dSim, simulates the new Rawlsian Fair scheduling mechanism. The dSim helps achieve instantaneous fairness in High Performance Computing environments, effective utilization of computing resources, and user satisfaction through the Rawlsian Fair scheduler.

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 book cover wireless communication, security issues, advanced wireless sensor networks, routing protocols of WSNs with cross-layer solutions, emerging trends in the advanced WSNs, power management, distributed sensing and data gathering techniques for WSNs, WSNs Security, applications, research of advanced WSNs with simulation results, and simulation tools for WSNs. Features: Covers technologies supporting advanced wireless communication system, sensor networks and the conceptual development of the subject. Discusses advanced data gathering and sharing/ distributed sensing techniques with its business applicability. Includes numerous worked-out mathematical equations/formulas, and essential principles including figures, illustrations, algorithms, and flow charts are included in the book. Provides pervasive background knowledge including both wireless communications and wireless sensor networks Covers wireless networks as well as sensor network models in detailed. This is aimed at graduate students, researchers and academicians working in the field of computer science, wireless communication technology, and advanced wireless sensor networks.

Automatic Performance Prediction of Parallel Programs presents a unified approach to the problem of automatically estimating the performance of parallel computer programs. The author focuses primarily on distributed memory multiprocessor systems, although large portions of the analysis can be applied to shared memory architectures as well. The author introduces a novel and very practical approach for predicting some of the most important performance parameters of parallel programs, including work distribution, number of transfers, amount of data transferred, network contention, transfer time, computation time and number of cache misses. This approach is based on advanced compiler analysis that carefully examines loop iteration spaces, procedure calls, array subscript expressions, communication patterns, data distributions and optimizing code transformations at the program level; and the most important machine specific parameters including cache characteristics, communication network indices, and benchmark data for computational operations at the machine level. The material has been fully implemented as part of P3T, which is an integrated automatic performance estimator of the Vienna Fortran Compilation System (VFCS), a state-of-the-art parallelizing compiler for Fortran77, Vienna Fortran and a subset of High Performance Fortran (HPF) programs. A large number of experiments using realistic HPF and Vienna Fortran code examples demonstrate highly accurate performance estimates, and the ability of the described performance prediction approach to successfully guide both programmer and compiler in parallelizing and optimizing parallel programs. A graphical user interface is described and displayed that visualizes each program source line together with the corresponding parameter values. P3T uses color-coded performance visualization to immediately identify hot spots in the parallel program. Performance data can be filtered and displayed at various levels of detail. Colors displayed by the graphical user interface are visualized in greyscale. Automatic Performance Prediction of Parallel Programs also includes coverage of fundamental problems of automatic parallelization for distributed memory multicomputers, a description of the basic parallelization strategy and a large variety of optimizing code transformations as included under VFCS.

Cloud Data Center Network Architectures and Technologies has been written with the support of Huawei's vast technical knowledge and experience in the data center network (DCN) field, as well as its understanding of customer service requirements. This book describes in detail the architecture design, technical implementation, planning and design, and deployment suggestions for cloud DCNs based on the service challenges DCNs encounter. It starts by describing the overall architecture and technical evolution of DCNs, with the aim of helping readers understand the development of DCNs. It then proceeds to explain the design and implementation of cloud DCNs, including the service model of a single data center (DC), construction of physical and logical networks of DCs, construction of multiple DCNs, and security solutions of DCs. Next, this book dives deep into practices of cloud DCN deployment based on real-world cases to help readers better understand how to build cloud DCNs. Finally, this book introduces DCN openness and some of the hottest forward-looking technologies. In summary, you can use this book as a reference to help you to build secure, reliable, efficient, and open cloud DCNs. It is intended for technical professionals of enterprises, research institutes, information departments, and DCs, as well as teachers and students of computer network-related majors in colleges and universities. Authors Lei Zhang Mr. Zhang is the Chief Architect of Huawei's DCN solution. He has more than 20 years' experience in network product and solution design, as well as a wealth of expertise in product design and development, network planning and design, and network engineering project implementation. He has led the design and deployment of more than 10 large-scale DCNs for Fortune Global 500 companies worldwide. Le Chen Mr. Chen is a Huawei DCN Solution Documentation Engineer with eight years' experience in developing documents related to DCN products and solutions. He has participated in the design and delivery of multiple large-scale enterprise DCNs. Mr. Chen has written many popular technical document series, such as DCN Handbook and BGP Topic.

This book describes novel hardware security and microfluidic biochip design methodologies to protect against tampering attacks in cyberphysical microfluidic biochips (CPMBs). It also provides a general overview of this nascent area of research, which will prove to be a vital resource for practitioners in the field.This book shows how hardware-based countermeasures and design innovations can be a simple and effective last line of defense, demonstrating that it is no longer justifiable to ignore security and trust in the design phase of biochips.

The book comprises a new method of solving the integral equation of Leontovich, the most rigorous and most effective equation for the current in thin linear antennas. The book describes the features of the new method in its application in various types of antennas. It considers new ways of analyzing antennas, in particular in the calculation of an antenna gain based on main radiation patterns and the calculation of the directional characteristics of radiators with known distribution of current amplitude. The method of electrostatic analogy proposed by the author, provides the base for comparison of electromagnetic fields of high-frequency currents and electrostatic charges located on linear conductors to improve the directional characteristics of log-periodic and director-type antennas. A new approach to the analysis of the electrical characteristics of a microstrip antenna, which allows expansion of its operation range, is substantiated and developed. New results of antenna synthesis are obtained. The second part of the book is devoted to specific types of antennas (the author had a significant role in their creation). Particular attention is given to ship antennas for different frequency ranges. The book is intended for professionals, working in electrodynamics and those working on development, placement and exploitation of antennas. It will be useful for lecturers (university-level professors), teachers, students of radio engineering and researchers working in various fields of radio electronics and interested in an in-depth study of theoretical problems and designs f antennas. It can also be used for short university courses.

This textbook introduces basic and advanced embedded system topics through Arm Cortex M microcontrollers, covering programmable microcontroller usage starting from basic to advanced concepts using the STMicroelectronics Discovery development board. Designed for use in upper-level undergraduate and graduate courses on microcontrollers, microprocessor systems, and embedded systems, the book explores fundamental and advanced topics, real-time operating systems via FreeRTOS and Mbed OS, and then offers a solid grounding in digital signal processing, digital control, and digital image processing concepts - with emphasis placed on the usage of a microcontroller for these advanced topics. The book uses C language, "the" programming language for microcontrollers, C++ language, and MicroPython, which allows Python language usage on a microcontroller. Sample codes and course slides are available for readers and instructors, and a solutions manual is available to instructors. The book will also be an ideal reference for practicing engineers and electronics hobbyists who wish to become familiar with basic and advanced microcontroller concepts.

This book provides a comprehensive and up-to-date guide to the design of security-hardened, hardware intellectual property (IP). Readers will learn how IP can be threatened, as well as protected, by using means such as hardware obfuscation/camouflaging, watermarking, fingerprinting (PUF), functional locking, remote activation, hidden transmission of data, hardware Trojan detection, protection against hardware Trojan, use of secure element, ultra-lightweight cryptography, and digital rights management. This book serves as a single-source reference to design space exploration of hardware security and IP protection.

Why learn functional programming? Isn't that some complicated ivory-tower technique used only in obscure languages like Haskell? In fact, functional programming is actually very simple. It's also very powerful, as Haskell demonstrates by throwing away all the conventional programming tools and using only functional programming features. But it doesn't have to be done that way. Functional programming is a power tool that you can use in addition to all your usual tools, to whatever extent your current mainstream language supports it. Most languages have at least basic support. In this book we use Python and Java and, as a bonus, Scala. If you prefer another language, there will be minor differences in syntax, but the concepts are the same. Give functional programming a try. You may be surprised how much a single power tool can help you in your day-to-day programming.

Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. The various application areas that are image-centric and video are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering CNN, RNN and its types for learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas

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

1. Covers latest concepts in intelligent analytics for industry 4.0. 2. Presents the applications of intelligent analytics for various industry 4.0 domains. 3. Covers latest research topics in the field. 4. Written in a comprehensive and simple manner. 5. The text is accompanied by tables and illustrative figures for better understanding of the topic.