Mathematics of Discrete Structures for Computer Science

String matching is one of the oldest algorithmic techniques, yet still one of the most pervasive in computer science. The past 20 years have seen technological leaps in applications as diverse as information retrieval and compression. This copiously illustrated collection of puzzles and exercises in key areas of text algorithms and combinatorics on words offers graduate students and researchers a pleasant and direct way to learn and practice with advanced concepts. The problems are drawn from a large range of scientific publications, both classic and new. Building up from the basics, the book goes on to showcase problems in combinatorics on words (including Fibonacci or Thue-Morse words), pattern matching (including Knuth-Morris-Pratt and Boyer-Moore like algorithms), efficient text data structures (including suffix trees and suffix arrays), regularities in words (including periods and runs) and text compression (including Huffman, Lempel-Ziv and Burrows-Wheeler based methods).

This classic undergraduate treatment examines the deductive method in its first part and explores applications of logic and methodology in constructing mathematical theories in its second part. Exercises appear throughout.Alfred Tarski, one of the greatest logicians of all time, is widely thought of as 'the man who defined truth'. His work on the concepts of truth and logical consequence as defined by mathematical theory are cornerstones of modern logic, influencing developments in mathematics, philosophy, linguistics, and computer science. His teaching on logic and mathematics culminated in the 1941 classic INTRODUCTION TO LOGIC, which uses the method of deduction and explores logic and methodology as it pertains to creating mathematical theories.

Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data.This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians. The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in th

Covering both quantitative and qualitative methods, this book examines the breadth of modern market research methods for upper level students across business schools and social science faculties. Modern and trending topics including social networks, machine learning, big data, and artificial intelligence are addressed and real world examples and case studies illustrate the application of the methods. This text examines potential problems, such as researcher bias, and discusses effective solutions in the preparation of research reports and papers, and oral presentations. Assuming no prior knowledge of statistics or econometrics, discrete chapters offer a clear introduction to both, opening up the quantitative methods to all students. Each chapter contains rigorous academic theory, including a synthesis of the recent literature as well as key historical references, applied contextualization and recent research results, making it an excellent resource for practitioners. Online resources i

Covering both quantitative and qualitative methods, this book examines the breadth of modern market research methods for upper level students across business schools and social science faculties. Modern and trending topics including social networks, machine learning, big data, and artificial intelligence are addressed and real world examples and case studies illustrate the application of the methods. This text examines potential problems, such as researcher bias, and discusses effective solutions in the preparation of research reports and papers, and oral presentations. Assuming no prior knowledge of statistics or econometrics, discrete chapters offer a clear introduction to both, opening up the quantitative methods to all students. Each chapter contains rigorous academic theory, including a synthesis of the recent literature as well as key historical references, applied contextualization and recent research results, making it an excellent resource for practitioners. Online resources i

Symbolic dynamics is a mature yet rapidly developing area of dynamical systems. It has established strong connections with many areas, including linear algebra, graph theory, probability, group theory, and the theory of computation, as well as data storage, statistical mechanics, and $C^*$-algebras. This Second Edition maintains the introductory character of the original 1995 edition as a general textbook on symbolic dynamics and its applications to coding. It is written at an elementary level and aimed at students, well-established researchers, and experts in mathematics, electrical engineering, and computer science. Topics are carefully developed and motivated with many illustrative examples. There are more than 500 exercises to test the reader's understanding. In addition to a chapter in the First Edition on advanced topics and a comprehensive bibliography, the Second Edition includes a detailed Addendum, with companion bibliography, describing major developments and new research di

We live in a networked world. Online social networking platforms and the World Wide Web have changed how society thinks about connectivity. Because of the technological nature of such networks, their study has predominantly taken place within the domains of computer science and related scientific fields. But arts and humanities scholars are increasingly using the same kinds of visual and quantitative analysis to shed light on aspects of culture and society hitherto concealed. This Element contends that networks are a category of study that cuts across traditional academic barriers, uniting diverse disciplines through a shared understanding of complexity in our world. Moreover, we are at a moment in time when it is crucial that arts and humanities scholars join the critique of how large-scale network data and advanced network analysis are being harnessed for the purposes of power, surveillance, and commercial gain. This title is also available as Open Access on Cambridge Core.

Interoperability in IoT for Smart Systems discusses the different facets of interoperability issues among the IoT devices and their solutions, the scalability issues in an IoT network, and provides solutions for plug-n-play of new devices with the existing IoT system. It also addresses the possible usage of interoperable and plug-n-play IoT networks in different systems to make them smarter. Aimed at researchers and graduate students in computer science, computer engineering, computer networks, electronics engineering, this bookExclusively covers interoperability of IoT systems in parallel with their use towards the development of smart systems Discusses the requirements of interoperability in smart IoT systems and their solutions Reviews IoT applications in different smart and intelligent systems Explores dealing with interoperability of heterogeneous participating devices Provides different case studies and open problems related to interoperability in IoT systems

Probability theory has diverse applications in a plethora of fields, including physics, engineering, computer science, chemistry, biology and economics. This book will familiarize students with various applications of probability theory, stochastic modeling and random processes, using examples from all these disciplines and more. The reader learns via case studies and begins to recognize the sort of problems that are best tackled probabilistically. The emphasis is on conceptual understanding, the development of intuition and gaining insight, keeping technicalities to a minimum. Nevertheless, a glimpse into the depth of the topics is provided, preparing students for more specialized texts while assuming only an undergraduate-level background in mathematics. The wide range of areas covered - never before discussed together in a unified fashion – includes Markov processes and random walks, Langevin and Fokker–Planck equations, noise, generalized central limit theorem and extreme values st

Probability theory has diverse applications in a plethora of fields, including physics, engineering, computer science, chemistry, biology and economics. This book will familiarize students with various applications of probability theory, stochastic modeling and random processes, using examples from all these disciplines and more. The reader learns via case studies and begins to recognize the sort of problems that are best tackled probabilistically. The emphasis is on conceptual understanding, the development of intuition and gaining insight, keeping technicalities to a minimum. Nevertheless, a glimpse into the depth of the topics is provided, preparing students for more specialized texts while assuming only an undergraduate-level background in mathematics. The wide range of areas covered - never before discussed together in a unified fashion – includes Markov processes and random walks, Langevin and Fokker–Planck equations, noise, generalized central limit theorem and extreme values st

The first edition of this book appeared in 1981 as a direct continuation of Lectures of von Neumann Algebras (by Ş.V. Strătilă and L. Zsidó) and, until 2003, was the only comprehensive monograph on the subject. Addressing the students of mathematics and physics and researchers interested in operator algebras, noncommutative geometry and free probability, this revised edition covers the fundamentals and latest developments in the field of operator algebras. It discusses the group-measure space construction, Krieger factors, infinite tensor products of factors of type I (ITPFI factors) and construction of the type III_1 hyperfinite factor. It also studies the techniques necessary for continuous and discrete decomposition, duality theory for noncommutative groups, discrete decomposition of Connes, and Ocneanu's result on the actions of amenable groups. It contains a detailed consideration of groups of automorphisms and their spectral theory, and the theory of crossed products.

Statutory interpretation involves the reconstruction of the meaning of a legal statement when it cannot be considered as accepted or granted. This phenomenon needs to be considered not only from the legal and linguistic perspective, but also from the argumentative one - which focuses on the strategies for defending a controversial or doubtful viewpoint. This book draws upon linguistics, legal theory, computing, and dialectics to present an argumentation-based approach to statutory interpretation. By translating and summarizing the existing legal interpretative canons into eleven patterns of natural arguments - called argumentation schemes - the authors offer a system of argumentation strategies for developing, defending, assessing, and attacking an interpretation. Illustrated through major cases from both common and civil law, this methodology is summarized in diagrams and maps for application to computer sciences. These visuals help make the structures, strategies, and vulnerabilities

Microelectronic Circuits, Eighth Edition, is intended as a text for the core courses inelectronic circuits taught to majors in electrical and computer engineering. It shouldalso prove useful to engineers and other professionals wishing to update their knowledgethrough self-study.As was the case with the first seven editions, the objective of this book is to develop inthe reader the ability to analyze and design electronic circuits, both analog and digital,discrete and integrated. While the application of integrated circuits is covered, emphasisis placed on transistor circuit design, This is done because of our belief that even if themajority of those studying this book were not to pursue a career in IC design, knowledgeof what is inside the IC package would enable intelligent and innovative application ofsuch chips. Furthermore, with the advances in VLSI technology and design methodology,IC design itself has become accessible to an increasing number of engineers.

This unique introduction to the foundational concepts of cyber-physical systems (CPS) describes key design principles and emerging research trends in detail. Several interdisciplinary applications are covered, with a focus on the wide-area management of infrastructures including electric power systems, air transportation networks, and health care systems. Design, control and optimization of cyber-physical infrastructures are discussed, addressing security and privacy issues of networked CPS, presenting graph-theoretic and numerical approaches to CPS evaluation and monitoring, and providing readers with the knowledge needed to operate CPS in a reliable, efficient, and secure manner. Exercises are included. This is an ideal resource for researchers and graduate students in electrical engineering and computer science, as well as for practitioners using cyber-physical systems in aerospace and automotive engineering, medical technology, and large-scale infrastructure operations.

This volume offers a historical and critical analysis of the emerging field of the learning sciences, which takes an interdisciplinary approach to understanding and improving how children and adults learn. It features a wide range of authors, including established scholars who founded and guided the learning sciences through the initial turbulence of forming a new line of academic inquiry, as well as newcomers who are continuing to shape the field. This diversity allows for a broad yet selective perspective on what the learning sciences are, why they came to be, and how contributors conduct their work. Reflections on the Learning Sciences serves both as a starting point for discussion among scholars familiar with the discipline and as an introduction for those interested in learning more. It will benefit graduate students and researchers in computer science, educational psychology, instructional technology, science, engineering, and mathematics.

Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and als

Understanding plant anatomy is not only fundamental to the study of plant systematics and palaeobotany, but is also an essential part of evolutionary biology, physiology, ecology and the rapidly expanding science of developmental genetics. This modernised new edition covers all aspects of comparative plant structure and development, arranged in a series of chapters on the stem, root, leaf, flower, pollen, seed and fruit. Internal structures are described using magnification aids from the simple hand-lens to the electron microscope. Numerous references to recent topical literature are included, and new illustrations reflect a wide range of flowering plant species. The phylogenetic context of plant names has been updated as a result of improved understanding of the relationships among flowering plants. This clearly written text is ideal for students studying a wide range of courses in botany and plant science, and is also an excellent resource for professional and amateur horticulturists

There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.

In this primer to the many-body theory of condensed-matter systems, the authors introduce the subject to the non-specialist in a broad, concise, and up-to-date manner. A wide range of topics are covered including the second quantization of operators, coherent states, quantum-mechanical Green's functions, linear response theory, and Feynman diagrammatic perturbation theory. Material is also incorporated from quantum optics, low-dimensional systems such as graphene, and localized excitations in systems with boundaries as in nanoscale materials. Over 100 problems are included at the end of chapters, which are used both to consolidate concepts and to introduce new material. This book is suitable as a teaching tool for graduate courses and is ideal for non-specialist students and researchers working in physics, materials science, chemistry, or applied mathematics who want to use the tools of many-body theory.

Are you struggling to improve a hostile or uncomfortable environment at work, or interested in how such tension can arise? Experts in organizational psychology, management science, social psychology, and communication science show you how to implement interventions and programs to manage workplace emotion. The connection between workplace affect and relevant challenges in our society, such as diversity and technological changes, is undeniable; thus learning to harness that knowledge can revolutionize your performance in tackling workday issues. Applying major theoretical perspectives and research methodologies, this book outlines the concepts of display rules, emotional labor, work motivation, well-being, and discrete emotions. Understanding these ideas will show you how affect can promote team effectiveness, leadership, and conflict resolution. If you require a foundation for understanding workplace affect or a springboard into deeper, more interdisciplinary research, this book presen

Are you struggling to improve a hostile or uncomfortable environment at work, or interested in how such tension can arise? Experts in organizational psychology, management science, social psychology, and communication science show you how to implement interventions and programs to manage workplace emotion. The connection between workplace affect and relevant challenges in our society, such as diversity and technological changes, is undeniable; thus learning to harness that knowledge can revolutionize your performance in tackling workday issues. Applying major theoretical perspectives and research methodologies, this book outlines the concepts of display rules, emotional labor, work motivation, well-being, and discrete emotions. Understanding these ideas will show you how affect can promote team effectiveness, leadership, and conflict resolution. If you require a foundation for understanding workplace affect or a springboard into deeper, more interdisciplinary research, this book presen

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. A focus on both mathematical intuition and carefully worked proofs makes this an excellent reference for established researchers and a helpful resource for graduate students in computer science, engineering, statistics, applied mathematics and economics. Linear bandits receive special attention as one of the most useful models in applications, while other chapters are dedicated to combinatorial bandits, ranking, non-stationary problems, Thompson sampling and pure exploration. The book ends with a peek into the world beyond bandits with an introduction to partial monitoring and learning in Markov decision processes.

Now in its second edition, this popular textbook on game theory is unrivalled in the breadth of its coverage, the thoroughness of technical explanations and the number of worked examples included. Covering non-cooperative and cooperative games, this introduction to game theory includes advanced chapters on auctions, games with incomplete information, games with vector payoffs, stable matchings and the bargaining set. This edition contains new material on stochastic games, rationalizability, and the continuity of the set of equilibrium points with respect to the data of the game. The material is presented clearly and every concept is illustrated with concrete examples from a range of disciplines. With numerous exercises, and the addition of a solution manual for instructors with this edition, the book is an extensive guide to game theory for undergraduate through graduate courses in economics, mathematics, computer science, engineering and life sciences, and will also serve as useful re

Through the fundamental work of Deligne and Lusztig in the 1970s, further developed mainly by Lusztig, the character theory of reductive groups over finite fields has grown into a rich and vast area of mathematics. It incorporates tools and methods from algebraic geometry, topology, combinatorics and computer algebra, and has since evolved substantially. With this book, the authors meet the need for a contemporary treatment, complementing in core areas the well-established books of Carter and Digne–Michel. Focusing on applications in finite group theory, the authors gather previously scattered results and allow the reader to get to grips with the large body of literature available on the subject, covering topics such as regular embeddings, the Jordan decomposition of characters, d-Harish–Chandra theory and Lusztig induction for unipotent characters. Requiring only a modest background in algebraic geometry, this useful reference is suitable for beginning graduate students as well as res

Algorithms permeate our lives in numerous ways, performing tasks that until recently could only be carried out by humans. Artificial Intelligence (AI) technologies, based on machine learning algorithms and big-data-powered systems, can perform sophisticated tasks such as driving cars, analyzing medical data, and evaluating and executing complex financial transactions - often without active human control or supervision. Algorithms also play an important role in determining retail pricing, online advertising, loan qualification, and airport security. In this work, Martin Ebers and Susana Navas bring together a group of scholars and practitioners from across Europe and the US to analyze how this shift from human actors to computers presents both practical and conceptual challenges for legal and regulatory systems. This book should be read by anyone interested in the intersection between computer science and law, how the law can better regulate algorithmic design, and the legal ramificatio

Formal semantics - the scientific study of meaning in natural language - is one of the most fundamental and long-established areas of linguistics. This Handbook offers a comprehensive, yet compact guide to the field, bringing together research from a wide range of world-leading experts. Chapters include coverage of the historical context and foundation of contemporary formal semantics, a survey of the variety of formal/logical approaches to linguistic meaning and an overview of the major areas of research within current semantic theory, broadly conceived. The Handbook also explores the interfaces between semantics and neighbouring disciplines, including research in cognition and computation. This work will be essential reading for students and researchers working in linguistics, philosophy, psychology and computer science.