Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

Books Journals

ARM Processors for Power Electronic Applications

1st Edition
February 2, 2026
P. Ponnambalam + 2 more
English

ARM Processors for Power Electronic Applications: Fundamentals to Programming teaches the concept of controlling power converters using the ARM processor, from its fundamentals to implementation procedure, including using advanced controllers for energy management. The book discusses coding the ARM processor for different power converters and a variety of applications. It covers the step-by-step procedure in the design of advanced controllers, the ARM processor and parallel processing, creating driver circuits to interface the ARM processor with power circuits, the peripherals to ARM processors so it can used to control power converters and coding for power circuits.

Quantum Communication and Cryptography

1st Edition
February 1, 2026
Walter O. Krawec
English
Paperback
9 7 8 0 4 4 3 2 1 5 3 2 2
eBook
9 7 8 0 4 4 3 2 1 5 3 3 9

Quantum Communication and Cryptography introduces readers to the theory of quantum cryptography, with a focus will on quantum key distribution (QKD) and more advanced quantum cryptographic protocols beyond QKD. It contains a brief introduction to the field of modern cryptography that is needed to fully appreciate and understand how quantum cryptographic systems are proven secure, and how they can be safely used in combination with current day classical systems. Readers are then introduced to quantum key distribution (QKD) - perhaps the most celebrated, and currently the most practical, of quantum cryptographic techniques.Basic protocols are described, and security proofs are given, providing readers with the knowledge needed to understand how QKD protocols are proven secure using modern, state- of-the-art definitions of security. Following this, more advanced QKD protocols are discussed, along with alternative quantum and classical methods to improve QKD performance. Finally, alternative quantum cryptographic protocols are covered, along with a discussion on some of the practical considerations of quantum secure communication technology. Throughout, protocols are described in a clear and consistent manner that still provides comprehensive, theoretical proofs and methods.

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

1st Edition
February 1, 2026
Manuel González Canché
English
Paperback
9 7 8 0 4 4 3 2 1 9 6 1 0
eBook
9 7 8 0 4 4 3 2 1 9 6 0 3

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools—just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

Integrated Photonics for Sensing Applications

1st Edition
February 1, 2026
Anu Agarwal + 2 more
English

Photonic Integrated Circuits for Sensing Applications delves into the fascinating world of sensors within the realm of integrated photonics. The book begins with a historical overview, tracing the evolution of spectroscopic sensing techniques such as FTIR, Raman, SPR, and reflectometry, each contributing to the field’s growth. It emphasizes the transformative potential of photonic integrated circuit (PIC) sensor systems by showcasing their advantages in achieving low SWAP-C metrics (size, weight, power, and cost) while maintaining high performance. Complete with technical insights, the book sets the stage for understanding how PICs are revolutionizing sensing applications across diverse industries.Beyond the introductory scope, the book thoroughly examines the components that constitute PIC sensor systems, including waveguides (operating below and above 1550 nm), ring resonators, photonic crystals, and MZ interferometers. It also explores integrated systems designed for chem–bio sensing applications, leveraging biofunctionalization and sorbent technologies. With attention to manufacturing scalability, topics such as materials, PDK development, and sensor packaging are addressed, ensuring readers grasp the practical aspects of producing advanced sensor systems at scale.

Medical Imaging and Behavioral Science

1st Edition
February 1, 2026
Dilber Uzun Ozsahin + 4 more
English

Medical Imaging and Behavioral Science provides comprehensive coverage of the fundamental principles of medical imaging and behavioral science. This book presents the latest research, techniques, and technological advancements in medical imaging and behavioral science for researchers and professionals working in the fields of image processing, computer science, and healthcare enabling them to solve problems at different stages of the research workflow. The book examines machine learning and deep-learning based approaches to medical image analysis. Chapters investigate the design and application of software and diagnostic tools across all aspects of medical imaging and behavioral sciences, including autism spectrum disorders, memory and learning, stress, eating disorders, among others. Researchers and professionals working in the fields of medical image processing, computer science, radiology, psychology, and neuroscience will benefit from the unique multidisciplinary perspective.

Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics

1st Edition
February 1, 2026
Sayooj Aby Jose + 2 more
English

Mathematical Modeling and AI-Driven Computational Techniques for Epidemiology and Disease Dynamics offers a comprehensive exploration of innovative methodologies at the intersection of mathematics, biology, and medicine. This book delves into advanced mathematical modeling, artificial intelligence, and computational intelligence, providing essential tools for understanding and managing complex disease dynamics. Covering a wide range of topics, including fractional-order modeling, optimal control strategies, and privacy-preserving technologies, it addresses critical challenges in public health and healthcare systems. With contributions from leading experts, this volume bridges theoretical advancements and practical applications, making it an invaluable resource for researchers, healthcare professionals, and academics seeking interdisciplinary solutions to global health issues.

Computational Intelligence in Surveillance Systems Using Image Processing

1st Edition
February 1, 2026
Jay Kumar Pandey + 3 more
English

Traditional surveillance systems struggle to process large volumes of visual data, identify specific objects or behaviors, and adapt to dynamic environments. Computational intelligence, which encompasses techniques like artificial intelligence (AI), machine learning (ML), and computer vision, offers powerful tools to address these challenges by enabling automated analysis, pattern recognition, and decision-making based on visual data. Computational Intelligence in Surveillance Systems Using Image Processing addresses the unique challenges and ethical considerations of applying AI and ML, offering a nuanced understanding of the regulatory landscape. It provides insights into the responsible development and deployment of technologies to unlock the transformative potential of computational intelligence to revolutionize surveillance systems and advance the capabilities of security and monitoring across various sectors.

Quantum Theory, Decision Making and Social Dynamics

1st Edition
February 1, 2026
Tofigh Allahviranloo + 3 more
English

Quantum Theory, Decision Making and Social Dynamics is an innovative exploration of the intersection of quantum theory, decision-making, and social networks. As quantum theory continues to permeate various fields, there is a growing need for accessible resources that elucidate its principles and applications. This book aims to fill that gap by illuminating the complex interplay between quantum theory and social dynamics, particularly in the context of decision-making. It addresses the challenges of understanding and applying quantum theory in social dynamics and equips readers with the knowledge to harness its potential in decision-making processes. The book is organized into nine chapters, each delving into a specific aspect of quantum theory and its applications. Chapter 1 provides an overview of quantum theory, tracing its historical development and key principles. Chapter 2 explores the integration of quantum theory with fuzzy systems, highlighting real-world applications and emerging trends. In Chapter 3, the focus shifts to the application of quantum theory in social networks, including quantum social network models and case studies. Chapter 4 examines decision-making processes within social networks, while Chapter 5 introduces and analyzes quantum decision-making models. Chapter 6 delves into quantum graph theory, discussing quantum graphs, walks, and algorithms. The subsequent chapters address the challenges and limitations of quantum decision-making (Chapter 7), future directions for the field (Chapter 8), and conclude with a summary of key points and final thoughts (Chapter 9). Quantum Theory, Decision Making and Social Dynamics is an invaluable resource for graduate students, researchers, and professionals in the fields of applied mathematics, computer science, physics, and social sciences interested in applying quantum approaches to the study of decision-making. These readers often face challenges in understanding complex quantum concepts, applying quantum theory to social networks, and utilizing quantum decision-making models. This book provides a solid foundation in quantum theory, introduces its applications in diverse areas, and prepares readers to navigate the quantum age with confidence. By offering a comprehensive overview and practical insights, this book empowers its audience to appreciate the profound impact of quantum theory on social network dynamics and decision-making.

Learning-Driven Game Theory for AI

1st Edition
February 1, 2026
Mehdi Salimi + 1 more
English

Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science. In this book, the authors bridge the gap between traditional game theory and its modern applications in artificial intelligence (AI) and related technological fields. The dynamic nature of contemporary problems in robotics, cybersecurity, machine learning, and multi-agent systems requires game-theoretic solutions that go beyond classical methods. The book delves into the rapidly growing intersection of pursuit differential games and AI, focusing on how these advanced game-theoretic models can be applied to modern AI systems, making it an indispensable resource for both academics and professionals. The book also provides a variety of applications demonstrating the practical integration of AI and game theory across various disciplines, such as autonomous systems, federated learning, and distributed decision-making frameworks. The book also explores the use of game theory in reinforcement learning, swarm intelligence, multi-agent coordination, and cybersecurity. These are critical areas where AI and dynamic games converge. Each chapter covers a different facet of dynamic games, offering readers a comprehensive yet focused exploration of topics such as differential and discrete-time games, evolutionary dynamics, and repeated and stochastic games. The absence of static games ensures a concentrated focus on the dynamic, evolving problems that are most relevant today.

Programming Massively Parallel Processors

5th Edition
February 1, 2026
Wen-mei W. Hwu + 2 more
English

Programming Massively Parallel Processors: A Hands-on Approach shows both students and professionals alike the basic concepts of parallel programming and GPU architecture. Concise, intuitive, and practical, it is based on years of road-testing in the authors' own parallel computing courses. Various techniques for constructing and optimizing parallel programs are explored in detail, while case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This new edition has been updated for the latest trends, incorporating the latest techniques and technologies to ensure that readers are learning the most current and relevant practices in GPU programming.

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