Skip to main content
Elsevier
View Cart
My account

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

    • Designing User Interfaces for an Aging Population

      • 2nd Edition
      • April 1, 2026
      • Jeff Johnson + 1 more
      • English
      Despite the fact that older adults constitute an ever-growing proportion of the technology-using population, they have often been overlooked when researchers study the habits, abilities, and needs of various user groups. Similarly, many developers and researchers come up short when trying to create new technologies, devices, and interfaces that will satisfy a more general user profile. User study participants have tended to be younger, physically and cognitively fit, and technologically savvy. In Designing User Interfaces for an Aging Population, Second Edition, the authors present the demographics of older adults as a broad group, and describe general sensory, cognitive, physical, and emotional characteristics of older adults. Each age-related characteristic is linked to its potential impact on older adults’ use of digital technology, with examples of problematic technology designs. To improve the user satisfaction, success, and overall experience of using (digital) technology, the authors offer specific design guidelines. These guidelines have been derived from the findings and evidence presented in hundreds of research studies. The studies are sourced from around the world, and address a wide range of study participants and technologies. The second edition is thoroughly updated, including examples, guidelines, and case studies to reflect recent developments in the areas of AI, Robotics, Speech Recognition, and other relevant emerging technologies. Readers will benefit from learning: demographics of users of digital technology; age-related factors affecting ability to use digital technology; common design issues that decrease usability for older adults; guidelines that can help designers avoid these common pitfalls; methods for working with older adults on research and design projects.

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

      • 1st Edition
      • March 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.

    • Quantum Communication and Cryptography

      • 1st Edition
      • April 1, 2026
      • Walter O. Krawec
      • English
      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.

    • AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice

      • 1st Edition
      • May 1, 2026
      • Olfa Boubaker + 1 more
      • English
      AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice explores the transformative role of AI and data science in enhancing precision medicine, predictive analytics, and medical practice. The book covers diverse topics such as AI-driven personalized medicine, seizure prediction through EEG analysis, and the application of chaos theory in AI-driven healthcare. The volume also delves into medical practice and education, including ethical considerations, AI-driven supply chain management, and clinical documentation using natural language processing.Furthermo... it examines AI's role in telemedicine, patient engagement, and adherence, offering innovative solutions to improve healthcare delivery and outcomes.

    • The Governance of Artificial Intelligence

      • 1st Edition
      • April 1, 2026
      • Tshilidzi Marwala
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 3 2 2 1
      • eBook
        9 7 8 0 4 4 3 3 6 3 2 3 8
      Artificial Intelligence governance is complicated by the fast pace of technological progress, the opaqueness of AI algorithms, worries about bias and impartiality, the requirement for accountability in AI-based decisions, and the global nature of AI development and deployment. The issue of AI governance is a developing one, and The Governance of AI is the first book that covers all the key topics in one book: AI values, Data, Algorithms, Computing, Applications, and Governance. The Governance of AI provides top-level guidance on all these topics from an engineering and governance perspective, while proposing a unifying framework for AI governance. An essential approach to AI governance is a proactive and comprehensive strategy that efficiently balances innovation and ethical concerns. The strategy presented in this book prioritizes social welfare and upholds human rights by maximizing the benefits of AI while reducing its negative aspects. In order to address these issues, it is essential to implement a versatile governance structure that incorporates several fields of study and encourages diversity. Additionally, utilizing existing regulatory frameworks, ethical standards, and industry benchmarks is essential. Moreover, it is crucial to integrate cooperation between governments, economic organizations, civil society, and the academic community under a multi-stakeholder framework to promote transparency, accountability, and public trust in AI systems. Furthermore, it is imperative to cultivate global cooperation in regulating AI because AI technology and its impacts extend beyond national boundaries. AI governance involves establishing worldwide norms and standards that encourage coordinating governance efforts while recognizing cultural and geographical differences. The Governance of AI is structured into six distinct sections and comprises 33 chapters. The first section comprises the chapters that address the principles that govern artificial AI. The second section has chapters that specifically address data-related topics. The AI algorithms are discussed in the third section. The fourth section has chapters that address the issue of computing. The fifth section has chapters that specifically address applications. The sixth section has chapters that address the topic of AI governance.

    • Cloud-native Architecture (CNA) and Artificial Intelligence (AI) for the Future of Software Engineering: The Principles, Patterns, Platforms and Practices

      • 1st Edition
      • Volume 141
      • March 1, 2026
      • English
      • Hardback
        9 7 8 0 4 4 3 2 2 4 0 1 0
      • eBook
        9 7 8 0 4 4 3 2 2 4 0 2 7
      Cloud-native Architecture (CNA) and Artificial Intelligence (AI) for the Future of Software Engineering: The Principles, Patterns, Platforms and Practices, Volume 141 in the Advances in Computers series, explores the convergence of artificial intelligence, machine learning, and modern software engineering practices. This volume provides a comprehensive overview of how AI technologies—ranging from traditional machine learning and deep learning to generative and explainable AI—are transforming every stage of software development and deployment. Chapters cover agentic AI, MLOps, DevSecOps, CI/CD, and Kubernetes-based scalable systems, emphasizing real-world applications such as cloud-native ERP systems, software testing automation, and secrets management. The volume also addresses pressing concerns around ethical AI, responsible automation, and data privacy, offering a well-rounded perspective on the future of intelligent, agile, and secure software engineering.

    • Quantum Cryptography and Annealing for Securing Industrial IoT

      • 1st Edition
      • March 1, 2026
      • Seifedine Kadry + 5 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 8 3 4 9 6
      • eBook
        9 7 8 0 4 4 3 3 8 3 5 0 2
      The Industrial Internet of Things (IIoT) revolutionizes industry, but with its interconnectedness comes vulnerability. Traditional cybersecurity crumbles before the looming threat of quantum computers. Quantum Cryptography and Annealing for Securing Industrial IoT focuses on the rapidly evolving field of quantum security solutions for Industrial Internet of Things (IIoT) platforms, emphasizing the critical intersection of quantum cryptography, post-quantum cryptography, and their practical applications in IIoT. The book’s primary objective is to drive advancements that significantly intersect quantum cryptography in securing IIoT devices, elevate secure IIoT infrastructures, and optimize the overall delivery. Distinguishing itself by prioritizing practical applications, this book offers a nuanced perspective on how technological integrations in quantum cryptosystems are actively employed in real-world scenarios. The authors meticulously examine the role of quantum cryptosystems in the design, analysis, and optimization of IIoT-specific hardware, examining their resilience to physical and side-channel attacks and evaluating performance. This book strikes a balance between theoretical concepts and practical applications, providing insights into the challenges and solutions encountered in applying quantum cryptographical principles to IIoT engineering problems. It highlights the interdisciplinary collaboration required in the field, recognizing the collaborative nature of quantum cryptography engineering that involves professionals from diverse fields. The book empowers readers with a comprehensive understanding of the pivotal role played by applied quantum cryptography in shaping the future of industrial engineering.

    • Smart City Computational Paradigms

      • 1st Edition
      • March 1, 2026
      • Mohit Kumar + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 7 2 6 9
      • eBook
        9 7 8 0 4 4 3 2 7 7 2 7 6
      The smart city paradigm combines smart homes, smart healthcare, smart transportation, smart industry, smart environment, and smart energy to ensure sustainability, well-being and comfortable living within the urban environment for the city's citizens. IoT enables computational intelligence to leverage the power of data analytics, machine learning, and artificial intelligence to extract meaningful insights from the vast amount of data generated by IoT devices. This synergy empowers connected devices to collect, process, and analyze data in real-time, enabling informed decision-making and predictive insights. Through adaptive algorithms and edge computing, the system can autonomously respond to changing conditions, optimize resource usage, and enhance energy efficiency. Security and anomaly detection mechanisms ensure the integrity of the IoT network, while human-machine interaction capabilities, facilitated by natural language processing, enable intuitive communication. This convergence of computational intelligence and IoT not only transforms data into actionable knowledge but also fosters the development of autonomous, efficient, and adaptive systems across diverse domains, ranging from smart cities to healthcare and industrial applications. The integration of computational intelligence with IoT enhances the capabilities of connected systems, making them smarter, more efficient, and better equipped to handle the complexities of the modern world. Smart City Computational Paradigms describes the connections between these state-of-the-art technologies and provides a comprehensive overview for readers interested in advanced technologies, identifying mentioned challenges and proposed solutions as well as developed framework. It covers the underlying theory, design techniques, classification, taxonomy and analytical tools, focusing primarily on the real time applications, uncertainty solutions and approaches with hands-on demonstration for decision making outcomes.

    • Signal Processing Roadmap

      • 1st Edition
      • March 1, 2026
      • Pushan Kumar Dutta + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 1 7 2 5
      • eBook
        9 7 8 0 4 4 3 3 3 1 7 3 2
      Signal Processing Roadmap: Technologies, Applications, and Future Directions explores cutting-edge and emerging signal-processing techniques across various measurement and monitoring applications, serving as an authoritative reference for engineers, researchers, and technologists. It critically analyses key signal processing considerations like uncertainty modelling that enable more intelligent and reliable next-generation measurement systems, backed by real-world implementation examples in areas ranging from Internet of Things devices to complex biomedical equipment. The book will provide an overview of the latest research in the hybrid information system modelling field, with a particular emphasis on practical applications in various fields. This includes case studies and examples of how these models have been used to solve problems in finance, healthcare, engineering, and other related fields. Additionally, the book reviews the theories and concepts related to non-linear optimization, fuzzy sets, and rough sets. Overall, Signal Processing Roadmap: Technologies, Applications, and Future Directions deals with the dual goals of consolidating the state-of-the-art and charting the future directions across the exciting applications where signal processing will continue playing a pivotal role in building intelligent, reliable, and efficient systems of the future.

    • AI and Data Science in Medical Research

      • 1st Edition
      • March 1, 2026
      • Olfa Boubaker
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 6 3 8 5
      • eBook
        9 7 8 0 4 4 3 2 7 6 3 9 2
      AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies.The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

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