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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.

BooksJournals

    • Decentralized Optimization in Networks

      • 1st Edition
      • July 23, 2025
      • Qingguo Lü, + 5 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 3 3 7 8
      • eBook
        9 7 8 0 4 4 3 3 3 3 3 8 5
      Decentralized Optimization in Networks: Algorithmic Efficiency and Privacy Preservation provides the reader with theoretical foundations, practical guidance, and solutions to decentralized optimization problems. The book demonstrates the application of decentralized optimization algorithms to enhance communication and computational efficiency, solve large-scale datasets, maintain privacy preservation, and address challenges in complex decentralized networks. The book covers key topics such as event-triggered communication, random link failures, zeroth-order gradients, variance-reduction, Polyak’s projection, stochastic gradient, random sleep, and differential privacy. It also includes simulations and practical examples to illustrate the algorithms' effectiveness and applicability in real-world scenarios.

    • Artificial Intelligence

      • 1st Edition
      • July 22, 2025
      • Yu-Gang Jiang + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 4 8 4 0 5
      • eBook
        9 7 8 0 4 4 3 2 4 8 4 1 2
      Artificial Intelligence Data and Model Safety: Risks, Attacks and Defenses offers a comprehensive overview of the evolution of AI and its security concerns. The book delves into how historical advancements in AI have both bolstered and complicated the issue of safeguarding data and models. By reflecting on the interplay between machine learning innovations and vulnerabilities, it sets the stage for readers to understand the critical importance of robust defenses in this era of digital and algorithmic reliance. In addition to contextualizing the historical trajectory of AI security, the book examines foundational elements of machine learning, emphasizing the mechanisms that contribute to, or mitigate, risks.Readers are guided through case studies of real-world attacks, illustrating the practical implications of security weaknesses, while proposed defense strategies provide actionable insights for strengthening AI systems.

    • Mastering Prompt Engineering

      • 1st Edition
      • July 13, 2025
      • Anand Nayyar + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 9 0 4 2
      • eBook
        9 7 8 0 4 4 3 3 3 9 0 5 9
      Mastering Prompt Engineering: Deep Insights for Optimizing Large Language Models (LLMs) is a comprehensive guide that takes readers on a journey through the world of Large Language Models (LLMs) and prompt engineering. Covering foundational concepts, advanced techniques, ethical considerations, and real-world case studies, this book equips both novices and experts to navigate the complex LLM landscape. It provides insights into LLM architecture, training, and prompt engineering methods, while addressing ethical concerns such as bias and privacy. Real-world case studies showcase the practical application of prompt engineering in a wide range of settings. This resource is not just for specialists but is a practical and ethically conscious guide for AI practitioners, students, scientific researchers, and anyone interested in harnessing the potential of LLMs in natural language processing and generation. Mastering Prompt Engineering serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization through its comprehensive, ethical, and practical approach.

    • The Decentralized Hydrogen Revolution Using Artificial Intelligence, Internet of Things, and Blockchain

      • 1st Edition
      • July 11, 2025
      • Hossein Pourrahmani + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 1 4 6 7 1
      • eBook
        9 7 8 0 4 4 3 4 1 4 6 8 8
      The Decentralized Hydrogen Revolution Using Artificial Intelligence, Internet of Things, and Blockchain provides an essential guide to understanding the transformative potential of advanced technologies in decentralized hydrogen communities. This comprehensive resource covers the intersection of AI, IoT, and blockchain with sustainable energy, offering insights from foundational principles to advanced applications. Readers will learn about the environmental benefits of hydrogen over fossil fuels, electrolysis, and the integration of innovative technologies to enhance hydrogen production and distribution. The book delves into the role of fuel cells in clean energy, advanced AI algorithms in hydrogen production, blockchain trust in hydrogen networks, and IoT connectivity.Economi... considerations, policy frameworks, and the future of decentralized hydrogen communities are also explored, making this an invaluable reference for researchers, industry professionals, policymakers, and students interested in the hydrogen economy.

    • Advanced Topics in Inverse Data Envelopment Analysis

      • 1st Edition
      • July 10, 2025
      • Mehdi Soltanifar + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 4 8 8 4
      • eBook
        9 7 8 0 4 4 3 3 6 4 8 9 1
      Advanced Topics in Inverse Data Envelopment Analysis: Approaches for Handling Ratio Data explores and tackles the most significant challenges encountered by researchers and practitioners in decision analysis and performance evaluation. This book delves into the sophisticated realm of Ratio Data Envelopment Analysis (DEA-R), offering a thorough examination of advanced methodologies, practical examples, and insights into managing complex problems involving both non-negative and negative data. Filling crucial gaps in existing literature, this comprehensive resource focuses on the emerging field of Inverse DEA-R, equipping readers with the necessary tools and knowledge to address a wide range of challenging data types. This book serves as an essential guide for making informed and efficient decisions, guiding researchers and graduate students in computer science, applied mathematics, industrial engineering, and finance, navigating the complexities of decision analysis in today's data-driven world.

    • Decision Systems

      • 1st Edition
      • July 9, 2025
      • Pallavi Vijay Chavan + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 7 2 8 4
      • eBook
        9 7 8 0 4 4 3 3 3 7 2 9 1
      Decision-making is a fundamental process that influences outcomes across a wide range of domains, including business, healthcare, scientific research, and automation. With the increasing availability of data and the growing computational power of modern systems, decision-making models have become more sophisticated and capable of providing highly accurate and efficient solutions. The ability to develop, analyze, and implement these models has become crucial for professionals and researchers working in fields that rely on data-driven decision-making.This book explores the evolution and significance of decision systems, covering both foundational theories and advanced methodologies. It introduces readers to the essential principles of decision-making models, illustrating their applications through practical case studies and real-world scenarios. The discussion begins with a focus on traditional decision-making techniques and gradually progresses to more advanced topics, including machine learning-based approaches, the integration of artificial intelligence, and the role of fuzzy logic in decision support systems. Furthermore, ethical considerations in decision-making and strategies for mitigating bias are examined, ensuring that models remain fair and transparent.Througho... this book, each chapter builds on the previous one, providing a structured and comprehensive learning experience. By the time readers complete this book, they will have gained an in-depth understanding of decision-making frameworks, their applications, and the future directions of research in this dynamic field. Whether one is a student, a researcher, or an industry professional, this book serves as a valuable guide to mastering the complexities of decision systems and applying them effectively in various domains.

    • Edge Artificial Intelligence

      • 1st Edition
      • July 7, 2025
      • Parikshit Narendra Mahalle + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 7 2 0 8
      • eBook
        9 7 8 0 4 4 3 2 6 7 2 1 5
      Edge Artificial Intelligence: Algorithms, Applications, Challenges and Ethical Issues introduces the essentials of Edge AI and machine learning. It delves into the architecture, algorithms, and applications of Edge AI, offering insights into regulation and governance. Real-world case studies and practical examples are included, providing readers with the knowledge and tools to harness the transformative power of Edge AI. This book also addresses the ethical considerations and regulatory aspects of deploying AI at the edge.In addition to offering a clear understanding of real-time decision-making, enhanced privacy, and efficient applications, this book empowers both technical and nontechnical readers by providing practical insights, case studies, and ethical considerations. It helps users implement and govern Edge AI in a responsible and effective manner.

    • Quaternion-Based Sparse Image Processing

      • 1st Edition
      • July 2, 2025
      • Satya Prakash Yadav + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 2 4 4 6
      • eBook
        9 7 8 0 4 4 3 2 9 2 4 5 3
      Quaternion-Sparse Image Processing: Advances in Multispectral Processing brings together the technologies, research, and managerial applications of quaternion-sparse based complex algebra in image processing. The book covers the entire range of complicated tasks performed on color images, including denoising, reconstruction, classification, hallucination, feature extraction, dimension reduction, and regularization. It provides easy understanding and smooth adaptability of basic and advanced concepts for graduate students, researchers, doctors, academics, and practitioners.

    • Quantum Computing

      • 1st Edition
      • June 30, 2025
      • Rajkumar Buyya + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 0 9 6 1
      • eBook
        9 7 8 0 4 4 3 2 9 0 9 7 8
      Quantum Computing: Principles and Paradigms covers a broad range of topics, providing a state-of-the-art and comprehensive reference for the rapid progress in the field of quantum computing and related technologies from major international companies (such as IBM, Google, Intel, Rigetti, Q-Control) and academic researchers. This book appeals to a broad readership, as it covers comprehensive topics in the field of quantum computing, including hardware, software, algorithms, and applications, with chapters written by both academic researchers and industry developers.This book presents readers with the fundamental concepts of quantum computing research, along with the challenges involved in developing practical devices and applications.

    • Intelligent Data Analytics for Solar Energy Prediction and Forecasting

      • 1st Edition
      • June 26, 2025
      • Amit Kumar Yadav + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 3 4 8 2 1
      • eBook
        9 7 8 0 4 4 3 1 3 4 8 3 8
      Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization explores the utilization of advanced neural networks, machine learning and data analytics techniques for solar radiation prediction, solar energy forecasting, installation and maximum power generation. The book addresses relevant input variable selection, solar resource assessment, tilt angle calculation, and electrical characteristics of PV modules, including detailed methods, coding, modeling and experimental analysis of PV power generation under outdoor conditions. It will be of interest to researchers, scientists and advanced students across solar energy, renewables, electrical engineering, AI, machine learning, computer science, information technology and engineers. In addition, R&D professionals and other industry personnel with an interest in applications of AI, machine learning, and data analytics within solar energy and energy systems will find this book to be a welcomed resource.

Related subjects

Applications

Artificial intelligence

Business intelligence

Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

Graphics cad hci

Hardware and architecture

Information systems

Internet and web technology

Software

Theory and mathematics