Introduction to Quantum Natural Language Processing. Overview of Leadership and AI. The Age of Quantum Superiority. Challenges To Today's Leadership. AI-induced Strategic Implementation and Organizational Performance.

This book describes simple to complex ASIC design practical scenarios using Verilog. It builds a story from the basic fundamentals of ASIC designs to advanced RTL design concepts using Verilog. Looking at current trends of miniaturization, the contents provide practical information on the issues in ASIC design and synthesis using Synopsys DC and their solution. The book explains how to write efficient RTL using Verilog and how to improve design performance. It also covers architecture design strategies, multiple clock domain designs, low-power design techniques, DFT, pre-layout STA and the overall ASIC design flow with case studies. The contents of this book will be useful to practicing hardware engineers, students, and hobbyists looking to learn about ASIC design and synthesis.

With the rapid penetration of technology in varied application domains, the existing cities are getting connected more seamlessly. Cities becomes smart by inducing ICT in the classical city infrastructure for its management. According to McKenzie Report, about 68% of the world population will migrate towards urban settlements in near future. This migration is largely because of the improved Quality of Life (QoL) and livelihood in urban settlements. In the light of urbanization, climate change, democratic flaws, and rising urban welfare expenditures, smart cities have emerged as an important approach for society's future development. Smart cities have achieved enhanced QoL by giving smart information to people regarding healthcare, transportation, smart parking, smart traffic structure, smart home, smart agronomy, community security etc. Typically, in smart cities data is sensed by the sensor devices and provided to end users for further use. The sensitive data is transferred with the help of internet creating higher chances for the adversaries to breach the data. Considering the privacy and security as the area of prime focus, this book covers the most prominent security vulnerabilities associated with varied application areas like healthcare, manufacturing, transportation, education and agriculture etc. Furthermore, the massive amount of data being generated through ubiquitous sensors placed across the smart cities needs to be handled in an effective, efficient, secured and privacy preserved manner. Since a typical smart city ecosystem is data driven, it is imperative to manage this data in an optimal manner. Enabling technologies like Internet of Things (IoT), Natural Language Processing (NLP), Blockchain Technology, Deep Learning, Machine Learning, Computer vision, Big Data Analytics, Next Generation Networks and Software Defined Networks (SDN) provide exemplary benefits if they are integrated in the classical city ecosystem in an effective manner. The application of Artificial Intelligence (AI) is expanding across many domains in the smart city, such as infrastructure, transportation, environmental protection, power and energy, privacy and security, governance, data management, healthcare, and more. AI has the potential to improve human health, prosperity, and happiness by reducing our reliance on manual labor and accelerating our progress in the sciences and technologies. NLP is an extensive domain of AI and is used in collaboration with machine learning and deep learning algorithms for clinical informatics and data processing. In modern smart cities, blockchain provides a complete framework that controls the city operations and ensures that they are managed as effectively as possible. Besides having an impact on our daily lives, it also facilitates many areas of city management.

Features contributions from thought leaders across academia, industry, and government Focuses on novel algorithms and practical applications

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. The book identifies potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications. To help realize Big Data's full potential, the book addresses numerous challenges, offering the conceptual and technological solutions for tackling them. These challenges include life-cycle data management, large-scale storage, flexible processing infrastructure, data modeling, scalable machine learning, data analysis algorithms, sampling techniques, and privacy and ethical issues.

This book presents fundamental new techniques for understanding and processing geospatial data. These "spatial gems" articulate and highlight insightful ideas that often remain unstated in graduate textbooks, and which are not the focus of research papers. They teach us how to do something useful with spatial data, in the form of algorithms, code, or equations. Unlike a research paper, Spatial Gems, Volume 1 does not focus on "Look what we have done!" but rather shows "Look what YOU can do!" With contributions from researchers at the forefront of the field, this volume occupies a unique position in the literature by serving graduate students, professional researchers, professors, and computer developers in the field alike.

The volume contains latest research on software reliability assessment, testing, quality management, inventory management, mathematical modeling, analysis using soft computing techniques and management analytics. It links researcher and practitioner perspectives from different branches of engineering and management, and from around the world for a bird's eye view on the topics. The interdisciplinarity of engineering and management research is widely recognized and considered to be the most appropriate and significant in the fast changing dynamics of today's times. With insights from the volume, companies looking to drive decision making are provided actionable insight on each level and for every role using key indicators, to generate mobile-enabled scorecards, time-series based analysis using charts, and dashboards. At the same time, the book provides scholars with a platform to derive maximum utility in the area by subscribing to the idea of managing business through performance and business analytics.

To learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field.

The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know.

The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.

The book presents laboratory experiments concerning ARM microcontrollers, and discusses the architecture of the Tiva Cortex-M4 ARM microcontrollers from Texas Instruments, describing various ways of programming them. Given the meager peripherals and sensors available on the kit, the authors describe the design of Padma - a circuit board with a large set of peripherals and sensors that connects to the Tiva Launchpad and exploits the Tiva microcontroller family's on-chip features. ARM microcontrollers, which are classified as 32-bit devices, are currently the most popular of all microcontrollers. They cover a wide range of applications that extend from traditional 8-bit devices to 32-bit devices. Of the various ARM subfamilies, Cortex-M4 is a middle-level microcontroller that lends itself well to data acquisition and control as well as digital signal manipulation applications. Given the prominence of ARM microcontrollers, it is important that they should be incorporated in academic curriculums. However, there is a lack of up-to-date teaching material - textbooks and comprehensive laboratory manuals. In this book each of the microcontroller's resources - digital input and output, timers and counters, serial communication channels, analog-to-digital conversion, interrupt structure and power management features - are addressed in a set of more than 70 experiments to help teach a full semester course on these microcontrollers. Beyond these physical interfacing exercises, it describes an inexpensive BoB (break out board) that allows students to learn how to design and build standalone projects, as well a number of illustrative projects.

This book focuses on grammatical inference, presenting classic and modern methods of grammatical inference from the perspective of practitioners. To do so, it employs the Python programming language to present all of the methods discussed. Grammatical inference is a field that lies at the intersection of multiple disciplines, with contributions from computational linguistics, pattern recognition, machine learning, computational biology, formal learning theory and many others. Though the book is largely practical, it also includes elements of learning theory, combinatorics on words, the theory of automata and formal languages, plus references to real-world problems. The listings presented here can be directly copied and pasted into other programs, thus making the book a valuable source of ready recipes for students, academic researchers, and programmers alike, as well as an inspiration for their further development.>

Automatic Differentiation (AD) is a maturing computational technology and has become a mainstream tool used by practicing scientists and computer engineers. The rapid advance of hardware computing power and AD tools has enabled practitioners to quickly generate derivative-enhanced versions of their code for a broad range of applications in applied research and development. "Automatic Differentiation of Algorithms" provides a comprehensive and authoritative survey of all recent developments, new techniques, and tools for AD use. The book covers all aspects of the subject: mathematics, scientific programming ( i.e., use of adjoints in optimization) and implementation (i.e., memory management problems). A strong theme of the book is the relationships between AD tools and other software tools, such as compilers and parallelizers. A rich variety of significant applications are presented as well, including optimum-shape design problems, for which AD offers more efficient tools and techniques. Topics and features: * helpful introductory AD survey chapter for brief overview of the field *extensive applications chapters, i.e., for circuit simulation, optimization and optimal-control shape design, structural mechanics, and multibody dynamical systems modeling *comprehensive bibliography for all current literature and results for the field *performance issues *optimal control sensitivity analysis *AD use with object oriented software tool kits The book is an ideal and accessible survey of recent developments and applications of AD tools and techniques for a broad scientific computing and computer engineering readership. Practitioners, professionals, and advanced graduates working in AD development will find the book a useful reference and essential resource for their work.

This book presents a model of electromagnetic (EM) information leakage based on electromagnetic and information theory. It discusses anti-leakage, anti-interception and anti-reconstruction technologies from the perspectives of both computer science and electrical engineering. In the next five years, the threat posed by EM information leakage will only become greater, and the demand for protection will correspondingly increase. The book systematically introduces readers to the theory of EM information leakage and the latest technologies and measures designed to counter it, and puts forward an EM information leakage model that has established the foundation for new research in this area, paving the way for new technologies to counter EM information leakage. As such, it offers a valuable reference guide for all researchers and engineers involved in EM information leakage and countermeasures.

The notion of swarm intelligence was introduced for describing decentralized and self-organized behaviors of groups of animals. Then this idea was extrapolated to design groups of robots which interact locally to cumulate a collective reaction. Some natural examples of swarms are as follows: ant colonies, bee colonies, fish schooling, bird flocking, horse herding, bacterial colonies, multinucleated giant amoebae Physarum polycephalum, etc. In all these examples, individual agents behave locally with an emergence of their common effect. An intelligent behavior of swarm individuals is explained by the following biological reactions to attractants and repellents. Attractants are biologically active things, such as food pieces or sex pheromones, which attract individuals of swarm. Repellents are biologically active things, such as predators, which repel individuals of swarm. As a consequence, attractants and repellents stimulate the directed movement of swarms towards and away from the stimulus, respectively. It is worth noting that a group of people, such as pedestrians, follow some swarm patterns of flocking or schooling. For instance, humans prefer to avoid a person considered by them as a possible predator and if a substantial part of the group in the situation of escape panic (not less than 5%) changes the direction, then the rest follows the new direction, too. Some swarm patterns are observed among human beings under the conditions of their addictive behavior such as the behavior of alcoholics or gamers. The methodological framework of studying swarm intelligence is represented by unconventional computing, robotics, and cognitive science. In this book we aim to analyze new methodologies involved in studying swarm intelligence. We are going to bring together computer scientists and cognitive scientists dealing with swarm patterns from social bacteria to human beings. This book considers different models of simulating, controlling, and predicting the swarm behavior of different species from social bacteria to humans.

1) Provides a levelling approach, bringing students at all stages of programming experience to the same point 2) Focuses Python, a general language, to an engineering and scientific context 3) Uses a classroom tested, practical approach to teaching programming 4) Teaches students and professionals how to use Python to solve engineering calculations such as differential and algebraic equations

A comprehensive reference book for detailed explanations for every algorithm and techniques related to the transformers. 60+ transformer architectures covered in a comprehensive manner. A book for understanding how to apply the transformer techniques in speech, text, time series, and computer vision. Practical tips and tricks for each architecture and how to use it in the real world. Hands-on case studies and code snippets for theory and practical real-world analysis using the tools and libraries, all ready to run in Google Colab.

Classifies the optimization problems of the ports into five scheduling decisions. For each decision, it supplies an overview, formulates each of the decisions as constraint satisfaction and optimization problems, and then covers possible solutions, implementation, and performance. Part One explores the various optimization problems in modern container terminals, while Part Two details advanced algorithms for the minimum cost flow (MCF) problem and for the scheduling problem of AGVs in ports. A complete package that can help readers address the scheduling problems of AGVs in ports.

This book focuses on one of the major challenges of the newly created scientific domain known as data science: turning data into actionable knowledge in order to exploit increasing data volumes and deal with their inherent complexity. Actionable knowledge has been qualitatively and intensively studied in management, business, and the social sciences but in computer science and engineering, its connection has only recently been established to data mining and its evolution, 'Knowledge Discovery and Data Mining' (KDD). Data mining seeks to extract interesting patterns from data, but, until now, the patterns discovered from data have not always been 'actionable' for decision-makers in Socio-Technical Organizations (STO). With the evolution of the Internet and connectivity, STOs have evolved into Cyber-Physical and Social Systems (CPSS) that are known to describe our world today. In such complex and dynamic environments, the conventional KDD process is insufficient, and additional processes are required to transform complex data into actionable knowledge. Readers are presented with advanced knowledge concepts and the analytics and information fusion (AIF) processes aimed at delivering actionable knowledge. The authors provide an understanding of the concept of 'relation' and its exploitation, relational calculus, as well as the formalization of specific dimensions of knowledge that achieve a semantic growth along the AIF processes. This book serves as an important technical presentation of relational calculus and its application to processing chains in order to generate actionable knowledge. It is ideal for graduate students, researchers, or industry professionals interested in decision science and knowledge engineering.

This book presents the mathematical background underlying security modeling in the context of next-generation cryptography. By introducing new mathematical results in order to strengthen information security, while simultaneously presenting fresh insights and developing the respective areas of mathematics, it is the first-ever book to focus on areas that have not yet been fully exploited for cryptographic applications such as representation theory and mathematical physics, among others. Recent advances in cryptanalysis, brought about in particular by quantum computation and physical attacks on cryptographic devices, such as side-channel analysis or power analysis, have revealed the growing security risks for state-of-the-art cryptographic schemes. To address these risks, high-performance, next-generation cryptosystems must be studied, which requires the further development of the mathematical background of modern cryptography. More specifically, in order to avoid the security risks posed by adversaries with advanced attack capabilities, cryptosystems must be upgraded, which in turn relies on a wide range of mathematical theories. This book is suitable for use in an advanced graduate course in mathematical cryptography, while also offering a valuable reference guide for experts.

This book focuses on techniques that can be applied at the physical and data-link layers of communication systems in order to secure transmissions against eavesdroppers. It discusses topics ranging from information theory-based security to coding for security and cryptography, and presents cutting-edge research and innovative findings from leading researchers. The characteristic feature of all the contributions in this book is their relevance for the practical application of security principles to a variety of widely used communication techniques, including: multiantenna systems, ultra-wide-band communication systems, power line communications, and quantum key distribution techniques. A further distinctive aspect is the attention paid to both unconditional and computational security techniques, building a bridge between two usually distinct worlds. The book gathers extended versions of contributions delivered at the Second Workshop on Communication Security, held in Paris, France, in April 2017 and affiliated with the conference EUROCRYPT 2017.

Focuses on the definition, engineering, and delivery of AI solutions as opposed to AI itself Reader will still gain a strong understanding of AI, but through the perspective of delivering real solutions Explores the core AI issues that impact the success of an overall solution including i. realities of dealing with data, ii. impact of AI accuracy on the ability of the solution to meet business objectives, iii. challenges in managing the quality of machine learning models Includes real world examples of enterprise scale solutions Provides a series of (optional) technical deep dives and thought experiments.

Cryptography has experienced rapid development, with major advances recently in both secret and public key ciphers, cryptographic hash functions, cryptographic algorithms and multiparty protocols, including their software engineering correctness verification, and various methods of cryptanalysis. This textbook introduces the reader to these areas, offering an understanding of the essential, most important, and most interesting ideas, based on the authors' teaching and research experience.

After introducing the basic mathematical and computational complexity concepts, and some historical context, including the story of Enigma, the authors explain symmetric and asymmetric cryptography, electronic signatures and hash functions, PGP systems, public key infrastructures, cryptographic protocols, and applications in network security. In each case the text presents the key technologies, algorithms, and protocols, along with methods of design and analysis, while the content is characterized by a visual style and all algorithms are presented in readable pseudocode or using simple graphics and diagrams.

The book is suitable for undergraduate and graduate courses in computer science and engineering, particularly in the area of networking, and it is also a suitable reference text for self-study by practitioners and researchers. The authors assume only basic elementary mathematical experience, the text covers the foundational mathematics and computational complexity theory.

The first part of this book covers the key concepts of cryptography on an undergraduate level, from encryption and digital signatures to cryptographic protocols. Essential techniques are demonstrated in protocols for key exchange, user identification, electronic elections and digital cash. In the second part, more advanced topics are addressed, such as the bit security of one-way functions and computationally perfect pseudorandom bit generators. The security of cryptographic schemes is a central topic. Typical examples of provably secure encryption and signature schemes and their security proofs are given. Though particular attention is given to the mathematical foundations, no special background in mathematics is presumed. The necessary algebra, number theory and probability theory are included in the appendix. Each chapter closes with a collection of exercises. In the second edition the authors added a complete description of the AES, an extended section on cryptographic hash functions, and new sections on random oracle proofs and public-key encryption schemes that are provably secure against adaptively-chosen-ciphertext attacks. The third edition is a further substantive extension, with new topics added, including: elliptic curve cryptography; Paillier encryption; quantum cryptography; the new SHA-3 standard for cryptographic hash functions; a considerably extended section on electronic elections and Internet voting; mix nets; and zero-knowledge proofs of shuffles. The book is appropriate for undergraduate and graduate students in computer science, mathematics, and engineering.

This book offers an introduction to applications prompted by tensor analysis, especially by the spectral tensor theory developed in recent years. It covers applications of tensor eigenvalues in multilinear systems, exponential data fitting, tensor complementarity problems, and tensor eigenvalue complementarity problems. It also addresses higher-order diffusion tensor imaging, third-order symmetric and traceless tensors in liquid crystals, piezoelectric tensors, strong ellipticity for elasticity tensors, and higher-order tensors in quantum physics. This book is a valuable reference resource for researchers and graduate students who are interested in applications of tensor eigenvalues.

Metaheuristic algorithms are considered as generic optimization tools that can solve very complex problems characterized by having very large search spaces. Metaheuristic methods reduce the effective size of the search space through the use of effective search strategies. Book Features: Provides a unified view of the most popular metaheuristic methods currently in use Includes the necessary concepts to enable readers to implement and modify already known metaheuristic methods to solve problems Covers design aspects and implementation in MATLAB (R) Contains numerous examples of problems and solutions that demonstrate the power of these methods of optimization The material has been written from a teaching perspective and, for this reason, this book is primarily intended for undergraduate and postgraduate students of artificial intelligence, metaheuristic methods, and/or evolutionary computation. The objective is to bridge the gap between metaheuristic techniques and complex optimization problems that profit from the convenient properties of metaheuristic approaches. Therefore, engineer practitioners who are not familiar with metaheuristic computation will appreciate that the techniques discussed are beyond simple theoretical tools, since they have been adapted to solve significant problems that commonly arise in such areas.

This volume contains the texts of the principal survey papers presented at ALGORITHMS -and ORDER, held. at Ottawa, Canada from June 1 to June 12, 1987. The conference was supported by grants from the N.A.T.O. Advanced Study Institute programme, the University of Ottawa, and the Natural Sciences and Engineering Research Council of Canada. We are grateful for this considerable support. Over fifty years ago, the Symposium on Lattice Theory, in Charlottesville, U.S.A., proclaimed the vitality of ordered sets. Only twenty years later the Symposium on Partially Ordered Sets and Lattice Theory, held at Monterey, U.S.A., had solved many of the problems that had been originally posed. In 1981, the Symposium on Ordered Sets held at Banff, Canada, continued this tradition. It was marked by a landmark volume containing twenty-three articles on almost all current topics in the theory of ordered sets and its applications. Three years after, Graphs and Orders, also held at Banff, Canada, aimed to document the role of graphs in the theory of ordered sets and its applications. Because of its special place in the landscape of the mathematical sciences order is especially sensitive to new trends and developments. Today, the most important current in the theory and application of order springs from theoretical computer seience. Two themes of computer science lead the way. The first is data structure. Order is common to data structures."