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Efficiently using data structures to collect, organise and retrieve information is one of the core abilities modern computer engineers are expected to have. This student-friendly textbook provides a complete view of data structures and algorithms using the Python programming language, striking a balance between theory and practical application. All major algorithms have been discussed and analysed in detail, and the corresponding codes in Python have been provided. Diagrams and examples have been extensively used for better understanding. Running time complexities are also discussed for each algorithm, allowing the student to better understand how to select the appropriate one. Written with both undergraduate and graduate students in mind, the book will also be helpful with competitive examinations for engineering in India such as GATE and NET. As such, it will be a vital resource for students as well as professionals who are looking for a handbook on data structures in Python.
String diagrams are a powerful graphical language used to represent computational phenomena across diverse scientific fields, including computer science, physics, linguistics, amongst others. The appeal of string diagrams lies in their multi-faceted nature: they offer a simple, visual representation of complex scientific ideas, while also allowing rigorous mathematical treatment. Originating in category theory, string diagrams have since evolved into a versatile formalism, extending well beyond their abstract algebraic roots, and offering alternative entry points to their study. This text provides an accessible introduction to string diagrams from the perspective of computer science. Rather than starting from categorical concepts, the authors draw on intuitions from formal language theory, treating string diagrams as a syntax with its own semantics. They survey the basic theory, outline fundamental principles, and highlight modern applications of string diagrams in different fields. This title is also available as open access on Cambridge Core.
This book applies rotation theory to problems involving vectors and coordinates, with an approach that combines easily visualised procedures with smart mathematics. It constructs rotation theory from the ground up, building from basic geometry through to the motion and attitude equations of rockets, and the tensor analysis of relativity. The author replaces complicated pictures of superimposed axes with a simple and intuitive procedure of rotating a model aircraft, to create rotation sequences that are easily turned into mathematics. He combines the best of the 'active' and 'passive' approaches to rotation into a single coherent theory, and discusses many potential traps for newcomers. This volume will be useful to astronomers and engineers sighting planets and satellites, computer scientists creating graphics for movies, and aerospace engineers designing aircraft; also to physicists and mathematicians who study its abstract aspects.
The 1994 discovery of Shor's quantum algorithm for integer factorization—an important practical problem in the area of cryptography—demonstrated quantum computing's potential for real-world impact. Since then, researchers have worked intensively to expand the list of practical problems that quantum algorithms can solve effectively. This book surveys the fruits of this effort, covering proposed quantum algorithms for concrete problems in many application areas, including quantum chemistry, optimization, finance, and machine learning. For each quantum algorithm considered, the book clearly states the problem being solved and the full computational complexity of the procedure, making sure to account for the contribution from all the underlying primitive ingredients. Separately, the book provides a detailed, independent summary of the most common algorithmic primitives. It has a modular, encyclopedic format to facilitate navigation of the material and to provide a quick reference for designers of quantum algorithms and quantum computing researchers.
This book explores the intersection of miracle cures and technology with a unique methodology. Unravelling the intricate connections between social, technological, biomedical and non-biomedical spheres, it makes a significant contribution to debates on technology and health.
This book introduces relevant and established data-driven modeling tools currently in use or in development, which will help readers master the art and science of constructing models from data and dive into different application areas. It presents statistical tools useful to individuate regularities, discover patterns and laws in complex datasets, and demonstrates how to apply them to devise models that help to understand these systems and predict their behaviors. By focusing on the estimation of multivariate probabilities, the book shows that the entire domain, from linear regressions to deep learning neural networks, can be formulated in probabilistic terms. This book provides the right balance between accessibility and mathematical rigor for applied data science or operations research students, graduate students in CSE, and machine learning and uncertainty quantification researchers who use statistics in their field. Background in probability theory and undergraduate mathematics is assumed.
Automated Agencies is the definitive account of how automation is transforming government explanations of the law to the public. Joshua D. Blank and Leigh Osofsky draw on extensive research regarding the federal government's turn to automated legal guidance through chatbots, virtual assistants, and other online tools. Blank and Osofsky argue that automated tools offer administrative benefits for both the government and the public in terms of efficiency and ease of use, yet these automated tools may also mislead members of the public. Government agencies often exacerbate this problem by making guidance seem more personalized than it is, not recognizing how users may rely on the guidance, and not disclosing that the guidance cannot be relied upon as a legal matter. After analyzing the potential costs and benefits of the use of automated legal guidance by government agencies, Automated Agencies charts a path forward for policymakers by offering detailed policy recommendations.
Oriented matroids appear throughout discrete geometry, with applications in algebra, topology, physics, and data analysis. This introduction to oriented matroids is intended for graduate students, scientists wanting to apply oriented matroids, and researchers in pure mathematics. The presentation is geometrically motivated and largely self-contained, and no knowledge of matroid theory is assumed. Beginning with geometric motivation grounded in linear algebra, the first chapters prove the major cryptomorphisms and the Topological Representation Theorem. From there the book uses basic topology to go directly from geometric intuition to rigorous discussion, avoiding the need for wider background knowledge. Topics include strong and weak maps, localizations and extensions, the Euclidean property and non-Euclidean properties, the Universality Theorem, convex polytopes, and triangulations. Themes that run throughout include the interplay between combinatorics, geometry, and topology, and the idea of oriented matroids as analogs to vector spaces over the real numbers and how this analogy plays out topologically.
In this original and modern book, the complexities of quantum phenomena and quantum resource theories are meticulously unravelled, from foundational entanglement and thermodynamics to the nuanced realms of asymmetry and beyond. Ideal for those aspiring to grasp the full scope of quantum resources, the text integrates advanced mathematical methods and physical principles within a comprehensive, accessible framework. Including over 760 exercises throughout, to develop and expand key concepts, readers will gain an unrivalled understanding of the topic. With its unique blend of pedagogical depth and cutting-edge research, it not only paves the way for a deep understanding of quantum resource theories but also illuminates the path toward innovative research directions. Providing the latest developments in the field as well as established knowledge within a unified framework, this book will be indispensable to students, educators, and researchers interested in quantum science's profound mysteries and applications.
Harnessing the power of data and AI methods to tackle complex societal challenges requires transdisciplinary collaborations across academia, industry, and government. In this compelling book, Munther A. Dahleh, founder of the MIT Institute for Data, Systems, and Society (IDSS), offers a blueprint for researchers, professionals, and institutions to create approaches to problems of high societal value using innovative, holistic, data-driven methods. Drawing on his experience at IDSS and knowledge of similar initiatives elsewhere, Dahleh describes in clear, non-technical language how statistics, data science, information and decision systems, and social and institutional behavior intersect across multiple domains. He illustrates key concepts with real-life examples from optimizing transportation to making healthcare decisions during pandemics to understanding the media's impact on elections and revolutions. Dahleh also incorporates crucial concepts such as robustness, causality, privacy, and ethics and shares key lessons learned about transdisciplinary communication and about unintended consequences of AI and algorithmic systems.
Can you trust results from modeling and simulation? This text provides a framework for assessing the reliability of and uncertainty included in the results used by decision makers and policy makers in industry and government. The emphasis is on models described by PDEs and their numerical solution. Procedures and results from all aspects of verification and validation are integrated with modern methods in uncertainty quantification and stochastic simulation. Methods for combining numerical approximation errors, uncertainty in model input parameters, and model form uncertainty are presented in order to estimate the uncertain response of a system in the presence of stochastic inputs and lack of knowledge uncertainty. This new edition has been extensively updated, including a fresh look at model accuracy assessment and the responsibilities of management for modeling and simulation activities. Extra homework problems and worked examples have been added to each chapter, suitable for course use or self-study.
This is the first book to revisit the theory of rewriting in the context of strict higher categories, through the unified approach provided by polygraphs, and put it in the context of homotopical algebra. The first half explores the theory of polygraphs in low dimensions and its applications to the computation of the coherence of algebraic structures. Illustrated with algorithmic computations on algebraic structures, the only prerequisite in this section is basic category theory. The theory is introduced step-by-step, with detailed proofs. The second half introduces and studies the general notion of n-polygraph, before addressing the homotopy theory of these polygraphs. It constructs the folk model structure on the category on strict higher categories and exhibits polygraphs as cofibrant objects. This allows the formulation of higher-dimensional generalizations of the coherence results developed in the first half. Graduate students and researchers in mathematics and computer science will find this work invaluable.
Machine learning has become a dominant problem-solving technique in the modern world, with applications ranging from search engines and social media to self-driving cars and artificial intelligence. This lucid textbook presents the theoretical foundations of machine learning algorithms, and then illustrates each concept with its detailed implementation in Python to allow beginners to effectively implement the principles in real-world applications. All major techniques, such as regression, classification, clustering, deep learning, and association mining, have been illustrated using step-by-step coding instructions to help inculcate a 'learning by doing' approach. The book has no prerequisites, and covers the subject from the ground up, including a detailed introductory chapter on the Python language. As such, it is going to be a valuable resource not only for students of computer science, but also for anyone looking for a foundation in the subject, as well as professionals looking for a ready reckoner.
The Cambridge Handbook of Emerging Issues at the Intersection of Commercial Law and Technology is a timely and interdisciplinary examination of the legal and societal implications of nascent technologies in the global commercial marketplace. Featuring contributions from leading international experts in the field, this volume offers fresh and diverse perspectives on a range of topics, including non-fungible tokens, blockchain technology, the Internet of Things, product liability for defective goods, smart readers, liability for artificial intelligence products and services, and privacy in the era of quantum computing. This work is an invaluable resource for academics, policymakers, and anyone seeking a deeper understanding of the social and legal challenges posed by technological innovation, as well as the role of commercial law in facilitating and regulating emerging technologies.
This informative Handbook provides a comprehensive overview of the legal, ethical, and policy implications of AI and algorithmic systems. As these technologies continue to impact various aspects of our lives, it is crucial to understand and assess the challenges and opportunities they present. Drawing on contributions from experts in various disciplines, the book covers theoretical insights and practical examples of how AI systems are used in society today. It also explores the legal and policy instruments governing AI, with a focus on Europe. The interdisciplinary approach of this book makes it an invaluable resource for anyone seeking to gain a deeper understanding of AI's impact on society and how it should be regulated. This title is also available as Open Access on Cambridge Core.
Global platforms present novel challenges. They are powerful conduits of commerce and global community, and their potential to influence behavior is enormous. Defeating Disinformation explores how to balance free speech and dangerous online content to reduce societal risks of digital platforms. The volume offers an interdisciplinary approach, drawing upon insights from different geographies and parallel challenges of managing global phenomena with national policies and regulations. Chapters also examine the responsibility of platforms for their content, which is limited by national laws such as Section 230 of the Communications Decency Act in the US. This balance between national rules and the need for appropriate content moderation threatens to splinter platforms and reduce their utility across the globe. Timely and expansive, Defeating Disinformation develops a global approach to address these tensions while maintaining, and even enhancing, the social contribution of platforms. This title is also available as open access on Cambridge Core.
Providing an in-depth treatment of an exciting research area, this text's central topics are initial algebras and terminal coalgebras, primary objects of study in all areas of theoretical computer science connected to semantics. It contains a thorough presentation of iterative constructions, giving both classical and new results on terminal coalgebras obtained by limits of canonical chains, and initial algebras obtained by colimits. These constructions are also developed in enriched settings, especially those enriched over complete partial orders and complete metric spaces, connecting the book to topics like domain theory. Also included are an extensive treatment of set functors, and the first book-length presentation of the rational fixed point of a functor, and of lifting results which connect fixed points of set functors with fixed points of endofunctors on other categories. Representing more than fifteen years of work, this will be the leading text on the subject for years to come.
In a technologically advanced and competitive landscape dominated by major tech companies and burgeoning start-ups, the key asset lies in boosting monthly active users. Traditionally, product design has relied on fragmented insights from personal experience, common sense, or isolated experiments. This work endeavours to establish a theoretical framework for predicting and influencing the digital behaviour of technology users. Drawing on over a century of scientific research in behaviour, cognition, and physiology, this presents a comprehensive approach to customizing digital stimuli. The objective is to enhance user interactions with digital and virtual environments. Through real and cost-effective examples, diagrams, and formulas, the text offers theoretical knowledge and a practical methodology to elevate digital product designs, setting them apart from the competition. With the potential to reshape the digital design landscape, this book emerges as a game-changer, promising to revolutionize how digital products and services are conceived and delivered.
Published in collaboration with The British Universities Industrial Relations Association (BUIRA), this book critically reviews the future of Industrial Relations (IR) in a changing work landscape and traces its historical evolution. Essential for academics, students and trade unions, it explores IR's significant changes over the past decade and its ongoing influence on our lives.
It is impossible to view the news at present without hearing talk of crisis: the economy, the climate, the pandemic. This book asks how these larger societal issues lead to a crisis with work, making it ever more precarious, unequal and intense. Experts diagnose the nature of the problem and offer a programme for transcending above the crises.