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Elsevier

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.

  • AI-Driven Robotics in Healthcare

    Ethical, Legal, and Implementation Challenges
    • 1st Edition
    • Rajiv Pandey + 3 more
    • English
    AI-Driven Robotics in Healthcare: Ethical, Legal, and Implementation Challenges presents a comprehensive reference in the rapidly evolving field of AI-driven medical robotics. Addressing the pressing demands of modern healthcare systems, this reference explores the intersection of machine learning, robotics, and healthcare delivery. It responds to the critical need for interdisciplinary understanding as healthcare providers, researchers, and policymakers navigate the complexities of AI integration. The reference is structured to cover foundational machine learning techniques, data processing, and deep learning architectures relevant to surgical robotics, followed by applications such as cognitive assistance, workflow automation, and anomaly detection. Implementation challenges including data privacy, system integration, and energy efficiency are examined alongside ethical, legal, and workforce implications. Contributions from international experts enrich the content with practical insights and case studies. This books benefits a diverse audience by bridging technical innovation with real-world clinical, regulatory, and policy considerations. It equips researchers, postgraduate students, healthcare professionals, and system integrators with the knowledge to responsibly adopt and manage AI robotics in healthcare, fostering safe, effective, and ethical technological advancement.

  • Artificial Intelligence in Healthcare

    • 2nd Edition
    • Adam Bohr + 1 more
    • English
    Artificial Intelligence in Healthcare, Second Edition shows where AI is delivering measurable value in medicine today, where it is failing, and what it takes to deploy it responsibly. Substantially rewritten since the first edition of 2020, it reflects the arrival of foundation models, multimodal data, autonomous and agentic systems, and the regulatory frameworks now shaping their use. Twelve chapters by leading practitioners cover AI-driven healthcare transformation and the gap between hype and real-world impact; next-generation drug discovery and molecular design; intelligent drug delivery and pharmaceutical innovation; oncology, from diagnostics to precision treatment pathways; medical imaging; medical devices; surgical intelligence; next-generation digital care; security, privacy and information sharing; insurance and personalised risk; and the ethical and legal questions that decide whether the machine can be trusted. Throughout, the emphasis is on evidence rather than promise: what problem each application solves, where it works in practice, where it fails, and what it means clinically and economically. Written for clinicians, healthcare leaders, industry and policymakers as well as researchers in computer science, data science, bioinformatics and biomedical engineering, it is a practical decision-making tool rather than a technical manual or an academic survey.

  • Moving Towards Fully Autonomous and Cost-Effective Surgical Robotic Systems with AI

    • 1st Edition
    • Tawanda Mushiri + 3 more
    • English
    Moving Towards Fully Autonomous and Cost-Effective Surgical Robotic Systems with AI offers advanced insights into how AI can be used to optimize the design, manufacturing, and clinical application of these systems. It covers a wide range of topics, including the introduction of surgical robotic systems design and the presentation of a fully autonomous surgical robotic system for minimally invasive surgery. Advanced medical imaging techniques integrated with surgical robots are discussed to enhance surgical precision and safety. The book also highlights the application of machine learning and deep learning models in robotic-assisted surgery, with the development of novel algorithms for autonomous surgical robots. Various AI approaches for optimizing surgical robotic systems and the design considerations for manufacturing and assembly are examined. Additionally, the book includes a thorough analysis of the life cycle and economic aspects of surgical robotic systems, as well as risk assessment and evaluation methods. The final chapters address ethics considerations and explore future enhancements in the realm of fully autonomous surgical robotic systems. Overall, this book aims to contribute to the technical understanding, design aspects, and ethical dimensions of surgical robotics, promoting safer and more efficient surgical procedures.

  • Introduction to Statistical Machine Learning

    • 2nd Edition
    • Masashi Sugiyama + 1 more
    • English
    Introduction to Statistical Machine Learning, Second Edition provides a general introduction to the fundamental concepts of statistics and probability that are used in describing machine learning algorithms, covering the two major approaches of machine learning techniques, generative methods and discriminative methods. The algorithms developed in the book include Python program code to provide readers with the necessary, practical skills needed to accomplish a wide range of data analysis tasks. The new edition also includes an all-new section on Deep Learning.

  • Synthetic Media, Deepfakes, and Cyber Deception

    Attacks, Analysis, and Defenses
    • 1st Edition
    • Cameron H. Malin
    • English
    Synthetic Media, Deepfakes, and Cyber Deception: Attacks, Analysis, and Defenses introduces the only analytical Synthetic Media Analysis Framework (SMAF) to help describe cyber threats and help security professionals anticipate and analyze attacks. This framework encompasses seven dimensions: Credibility, Control, Medium, Interactivity, Familiarity, Intended Target, and Evocation. Synthetic media is a broad term that encompasses the artificial manipulation, modification, and production of information, covering a spectrum from audio-video deepfakes to text-based chatbots. Synthetic media provides cyber attackers and scammers with a game-changing advantage over traditional ROSE attacks because they have the potential to convincingly impersonate close associates through text, imagery, voice, and video. This burgeoning threat has yet to be meaningfully addressed through any written treatment on the topic. The book is co-authored by three cyber influence and deception experts who have gained deep knowledge and experience on the topic through diverse, true operational pathways and backgrounds. The diversity and perspectives of the author team makes the content in the book the broadest and deepest treatment of synthetic media attacks available to readers.

  • Computer Vision

    Principles, Algorithms, Applications, Learning
    • 6th Edition
    • E. R. Davies + 1 more
    • English
    Computer Vision: Principles, Algorithms, Applications, Learning, Sixth Edition clearly and systematically presents the basic methodology of computer vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This new sixth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers and R&D engineers working in this vibrant subject.

  • Federated Learning for the Metaverse

    Applications in Virtual Environments
    • 1st Edition
    • Noor Zaman Jhanjhi + 3 more
    • English
    Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.

  • Handbook of Machine Learning in Oncology

    Foundations and Advanced Techniques
    • 1st Edition
    • Sanjay Saxena + 1 more
    • English
    Machine learning (ML) is transforming oncology by introducing innovative methodologies for early detection, diagnosis, treatment planning, and predicting patient outcomes. Handbook of Machine Learning in Oncology: Foundations and Advanced Techniques provides a detailed guide for applying ML-based methods to cancer research and treatment. The first half of this comprehensive guide covers the basics of cancer biology and ML, including key concepts, algorithms, and data processing techniques. It presents the methodology for supervised and unsupervised learning, Deep Learning, radiomics, radiogenomics, and natural language processing, highlighting their importance in oncology. The second half of the book focuses on practical applications, offering detailed case studies on various cancers such as breast, lung, prostate, colorectal, brain, and pancreatic. This applied handbook discusses predictive modeling, diagnostic applications, treatment planning, and emerging technologies. The book offers a thorough and insightful exploration of how Machine Learning and Deep Learning are revolutionizing oncology, providing readers with the knowledge and tools to contribute to this rapidly evolving field.

  • The Basics of Digital Forensics

    • 3rd Edition
    • John Sammons
    • English
    The Basics of Digital Forensics, Third Edition provides a foundation for people new to the digital forensics field. This book offers guidance on how to conduct examinations by discussing what digital forensics is, the methodologies used, key tactical concepts, and the tools needed to perform examinations. Details on digital forensics for computers, networks, cell phones, GPS, the cloud and the Internet are discussed. Also, learn how to collect evidence, document the scene, and how deleted data can be recovered. The new Third Edition of this book includes four all-new chapters, additional pedagogical features within each chapter, and an expansive appendix with useful information in an easy-to-use format. The book provides readers with real-world examples and all the key technologies used in digital forensics, as well as coverage of network intrusion response, how hard drives are organized, and electronic discovery. This valuable resource also covers how to incorporate quality assurance into an investigation, how to prioritize evidence items to examine (triage), case processing, and what goes into making an expert witness. New chapters in the Third Edition cover imaging and processing, digital forensic analysis, IoT forensics, as well as documentation and reporting.

  • Modeling Systems with SysML v2

    The Systems Modeling Language
    • 1st Edition
    • Sanford Friedenthal + 2 more
    • English
    Whether you have previous experience modeling with SysML v1 or are new to modeling with SysML, Modeling Systems with SysML v2: The Systems Modeling Language provides the understanding and guidance to help you gain a basic level of competency in SysML v2, prepare for SysML v2 certification, and advance your modeling skills over time.SysML v2 is the next generation systems modeling language that can be used to model complex systems that span a wide range of application domains. It provides the ability to specify requirements, behavior, structure, analysis, and verification of interacting systems and their components while maintaining traceability across the system model. SysML v2 enhances the precision, expressiveness, consistency, usability, extensibility and interoperability of systems modeling. It provides both graphical and textual notations that facilitate stakeholder understanding and enable modern practices with agile workflows. SysML v2 is also supported by a standardized application programming interface (API) that facilitates interoperability across digital engineering tools and models. The formal semantic and syntactic foundation for SysML v2 enables technologies such as artificial intelligence (AI) with large language models (LLM) to interact with the SysML model. The combination of SysML v2's textual notation and standard API, along with a formal foundation and consistent usage patterns, facilitate automation to support model validation, workflow enhancements, and integration with other models and tools.This book provides a comprehensive and practical guide for modeling systems with SysML v2. With their unique perspective as leading contributors to the language, the authors provide a full description of the language along with examples that help you understand how to apply the language concepts. The book begins with an introduction to the most commonly used features to help you get started quickly followed by a detailed description that provides you with a more in-depth understanding. The book also includes a detailed example of applying model-based systems engineering with SysML v2 to specify and design an unmanned aerial system.

  • A Comprehensive Guide to R Programming for Data Analytics

    • 1st Edition
    • Parul Acharya
    • English
    A Comprehensive Guide to R Programming for Data Analytics provides a comprehensive presentation of univariate and multivariate statistical models within the general linear model and generalized linear model framework to analyze simple and complex data using R software. This book presents popular R packages that are used in data mining (e.g., caret-classification and regression, lubridate-dates and times, string-R for string data) and visualization (e.g., ggplot, ggthemes, ggtext). The R packages used to analyze data using a particular statistical model are explained through real-world and publicly available datasets. R codes are presented in a manner that helps readers understand the program code syntax.Examples of real-world data sets from a variety of academic disciplines are provided so that a wide audience can learn R programming to analyze data in their research. The book provides tips, recommendations, and strategies to troubleshoot common issues in R syntax, as well as definitions of key terms. Checkpoints are included to recap the concepts learned in each chapter. The book helps readers enhance their conceptual understanding and practical application of statistical models to real-world datasets, and enables readers to gain competency in R programming, which is an important skill in today’s data-driven market.

  • Modern Bioinformatics

    From Molecular Insights to Biomedical Innovation
    • 1st Edition
    • Kolla Bhanu Prakash + 2 more
    • English
    Modern Bioinformatics: From Molecular Insights to Biomedical Innovation explores the rapidly advancing field of bioinformatics, addressing a critical gap in current literature by integrating quantum biology and quantum biosensors with computational bioinformatics. The book offers a thorough exploration of bioinformatics from foundational concepts to translational applications. It begins with molecular structures of proteins, DNA, and RNA, advancing through nano-molecular visualization and structural domain analysis. Readers gain insights into deep learning techniques like AlphaFold for protein structure prediction, AI applications in genomics, and molecular interactions critical to function. The text further covers computational methods in drug discovery, forensic bioinformatics, and molecular evolution.A unique emphasis is placed on the convergence of nanotechnology and quantum innovations in molecular diagnostics and biosensing, including quantum biosensors and quantum computing applications. The final sections focus on computational strategies for drug target identification, biomarker discovery, and clinical trial analysis, providing a holistic view of modern bioinformatics workflows. This book is an indispensable reference for advanced researchers, graduate students, and professionals in bioinformatics, molecular biology, and biomedical engineering seeking to integrate quantum computing and nanotechnology into their work.

  • Deep Learning Approaches for Healthcare Data Analysis and Decision Making

    • 1st Edition
    • Ashish Bagwari + 5 more
    • English
    Deep Learning Approaches for Healthcare Data Analysis and Decision Making demystifies complex data-driven technologies, providing a clear framework for integrating advanced analytics into healthcare practices. With a focus on practical applications, the authors present a comprehensive digital transformation methodology that empowers readers to tackle the multifaceted challenges of healthcare data management. By leveraging deep learning techniques, readers will learn to analyze vast datasets, identify critical patterns, and develop predictive models that enhance diagnosis and treatment strategies while ensuring compliance with stringent data regulations. The book also addresses the pressing need for ethical AI practices, emphasizing patient privacy and data security.Real-world case studies illustrate how to implement personalized healthcare solutions and foster interdisciplinary collaboration, breaking down silos in knowledge and practice. Moreover, it explores innovative business models for sustainable AI integration, offering actionable insights for healthcare providers. This resource equips professionals with the tools to drive innovation, improve patient outcomes, and navigate the complexities of digital transformation in healthcare, making it a must-read for anyone at the intersection of technology and healthcare.

  • Exploring Infant Cry

    Medical and Technical Analysis and Signal Processing Perspectives
    • 1st Edition
    • Carlos Alberto Reyes Garcia + 3 more
    • English
    Exploring Infant Cry: Medical and Technological Analysis and Signal Processing Perspectives is a comprehensive exploration of the latest medical and technical advancements in the study of infant crying. This book presents a unified approach that integrates medical insights and computational techniques for analyzing and classifying cries, aiming to enhance diagnostic capabilities. Authored by experts, it emphasizes the growing significance of cry analysis as a powerful, non-intrusive tool for identifying pathologies from the earliest stages. As the field expands, researchers and clinicians are offered innovative perspectives and practical solutions for interpreting and understanding why babies cry. The book also explores the connection between infant cries and language development, as well as the communicative importance of these signals in human interaction. Addressing gaps in routine neonatal application, the book compiles recent advancements in signal processing, Artificial Intelligence, and soft computing for cry classification. This makes it a valuable resource for biomedical researchers, doctors, and clinicians seeking to deepen their knowledge of the acoustic, neurophysiological, and linguistic aspects of infant crying.

  • Human Intelligence and Artificial Intelligence

    Connecting Cognitive Science with AI
    • 1st Edition
    • Tilottama Goswami + 2 more
    • English
    Human Intelligence and Artificial Intelligence: Connecting Cognitive Science with AI offers a comprehensive, multi-dimensional view of where AI stands today in relation to human intelligence and the opportunities and challenges that lie ahead. While currently cognitive science and AI courses are offered distinctly, this book equips readers with a foundational understanding of human cognition and how it shapes the field of AI. The structure of the book is designed to move progressively from accomplished AI domains to emerging frontiers. Real-world examples, state-of-the-art models, and active research directions are paired with philosophical, psychological, and social insights to ground the technical discussions in human relevance. As human–machine interactions enter a new era with the advent of agentic AI, understanding human cognitive processes becomes essential to designing, operating, and governing agentic systems and to building a safe, trustworthy, and responsible AI ecosystem.

  • Artificial Intelligence and Machine Learning for Safety-Critical Systems

    A Comprehensive Guide
    • 1st Edition
    • Rajiv Pandey + 3 more
    • English
    Artificial Intelligence and Machine Learning for Safety-Critical Systems: A Comprehensive Guide provides engineers and system designers who are exploring the application of AI/ML methods for safety-critical systems with a dedicated resource on the challenges and mitigation strategies involved in their design. The book's authors present ML techniques in safety-critical systems across multiple domains, including pattern recognition, image processing, edge computing, Internet of Things (IoT), encryption, hardware accelerators, and many others. These applications help readers understand the many challenges that need to be addressed in order to increase the deployment of ML models in critical systems. In addition, the book shows how to improve public trust in ML systems by providing explainable model outputs rather than treating the system as a black box for which the outputs are difficult to explain. Finally, the authors demonstrate how to meet legal certification and regulatory requirements for the appropriate ML models. In essence, the goal of this book is to help ensure that AI-based critical systems better utilize resources, avoid failures, and increase system safety and public safety.

  • Digital Signal Processing with MATLAB®

    From Fundamentals to AI Applications
    • 1st Edition
    • Samir I. Abood + 1 more
    • English
    Digital Signal Processing with MATLAB®: From Fundamentals to AI Applications provides coverage of discrete-time signals and systems, and lays out the mathematical fundamentals of digital signal processing (DSP) systems. The book contains a solution to large-scale signal processing problems, namely the development of methods and algorithms that increase (a) operational efficiency under different uncertainty conditions and (b) system stability rate. It offers an algebraic approach to digital signal processing, including algorithms related to digital systems, the setting of parameters, plus operational estimation, detection, classification, resolution, and reliability. Digital Signal Processing with MATLAB®: From Fundamentals to AI Applications begins with a thorough explanation of MATLAB® in recognition of the Accreditation Board for Engineering and Technology (ABET) requirements for integrating computer tools into DSP. The principles of DSP are presented using a step-by-step approach; each chapter starts with an introduction that states the chapter objectives, and ends with a discussion of practical applications of DSP, including providing problems that help the reader understand how the concepts are used in real-life situations. Sometimes, problems are solved in two or three ways to facilitate a deeper understanding and comparison of different approaches. Digital Signal Processing with MATLAB®: From Fundamentals to AI Applications teaches the fundamental principles of digital signal processing, and explains how MATLAB® can be used in the development of methods and algorithms for DSP.

  • Soft and Continuum Robots for Medical Applications

    A Practical Approach
    • 1st Edition
    • Manish Chauhan + 1 more
    • English
    Soft and Continuum Robots for Medical Applications: A Practical Approach introduces present and future technologies of soft and continuum robotics for medical applications. This book dives into the importance of medical device development for electronics, control theory, microcontrollers, MATLAB programming, machine design, biophysics, anatomy, and physiological limitations through a structured approach that clearly presents underlying key concepts to educate readers on the methodology of approaching medical device development. This book also explores soft and continuum robotic technology in various sub-domains such as robotic navigation, robotic navigation, sensing and bio photonics, autonomy, and shared autonomy. Biomedical engineers, doctors, and researchers in biomedical robotics, biomechanics, robotics, biotechnology, engineering in medicine, mechanical and electrical engineering, health science, and technology will find this book helpful in providing theoretical and practical knowledge in using robotics in the medical field.

  • Integrating AI in Psychological and Mental Health Care

    Techniques, Applications, and Ethical Considerations
    • 1st Edition
    • Sandeep Kautish + 4 more
    • English
    Integrating AI in Psychological and Mental Health Care: Techniques, Applications, and Ethical Considerations introduces key concepts and the historical evolution of AI, providing a foundation for understanding its applications in mental health. The content delves into various aspects of AI, including diagnostic tools, machine learning algorithms, and natural language processing, highlighting their roles in enhancing therapeutic outcomes and improving patient care. The discussion encompasses significant mental health conditions such as anxiety, depression, and severe psychological disorders, showcasing how AI technologies can assist in diagnosis, treatment planning, and monitoring. Ethical considerations and privacy issues are critically examined, ensuring a balanced perspective on the benefits and challenges associated with AI-driven interventions. Practical applications, such as virtual psychotherapists and AI-enhanced cognitive behavioral therapy illustrate real-world implementations and their impact on patient care. Additionally, case studies provide insights into successful AI applications in mental health settings, thus enhancing our understanding of potential advantages and obstacles.

  • Design Research Through Practice

    From the Lab, Field, and Showroom
    • 2nd Edition
    • Ilpo Koskinen + 4 more
    • English
    Design Research Through Practice: From the Lab, Field, and Showroom is a revision of the 2011 classic design book. Written by world-renowned experts in the field of design and human-computer interaction (HCI), it focuses on one type of contemporary design research known as constructive design research. It looks at three approaches to constructive design research: laboratory research, field research, and the Showroom. The book shows how theory, research practice, and the social environment create commonalities between these approaches. It illustrates how one can successfully integrate design and research based on work carried out within industrial design and interaction design. Thoroughly revised since the original edition with contemporary case studies, up-to-date modelling, and a brand new chapter on 'Studio: research from the heart of design', the book begins with an overview of the rise of constructive design research, as well as constructive research programs and methodologies. It then describes the logic of studying design in the laboratory, design ethnography and field work, and the origins of the Showroom and its foundation in art and design rather than in science or the social sciences. It also discusses the theoretical background of constructive design research, along with modelling and prototyping of design items. Finally, it considers recent work in Lab that focuses on action and the body instead of thinking and knowing.Design Research Through Practice: From the Lab, Field, and Showroom expands on the original edition to embrace the changes to design research and design-oriented HCI, including: the rise of social design; the rise of GenAI; changes in service design and design thinking; collaborations with scientists; and the rise of craft research and so called practice-based research.

  • AI for Inclusive Education

    Advancements in Assessment, Diagnosis, and Intervention
    • 1st Edition
    • Somaya Al-Maadeed + 2 more
    • English
    AI for Inclusive Education: Advancements in Assessment, Diagnosis, and Intervention is a comprehensive guide to artificial intelligence's (AI) potential to revolutionize inclusive education, offering practical insights, evidence-based strategies, and real-world examples to empower educators, researchers, policymakers, and advocates in fostering equitable learning environments for all learners. In today's diverse classrooms, educators face complex challenges in meeting the needs of every learner. While AI holds tremendous promise in this regard, there is a scarcity of resources that comprehensively explore its application in the context of inclusive education.AI for Inclusive Education: Advancements in Assessment, Diagnosis, and Intervention seeks to equip the reader with innovative tools and approaches grounded in AI to personalize learning experiences, diagnose learning difficulties, and deliver targeted interventions. Additionally, it aims to inspire collaboration among stakeholders in education and technology to drive positive change and advance the cause of inclusive education worldwide.AI for Inclusive Education: Advancements in Assessment, Diagnosis, and Intervention empowers educators, researchers, policymakers, and advocates to harness the transformative potential of AI in fostering equitable and accessible learning environments for all students.

  • Foundations of Smart Sensor Networks

    • 1st Edition
    • Marjan Kuchaki Rafsanjani + 2 more
    • English
    In an interconnected world, smart sensor networks offer a means of gathering data from the internet of things, which can be analysed and utilised to make informed decisions in real world situations. Foundations of Smart Sensor Networks provides a comprehensive guide to understanding the concepts and applications of sensor network technology. This book presents the core concepts, principles, design and architectures of smart sensor networks, and their pivotal role in modern communication. It explores the innovative technologies that use artificial intelligence, machine learning and optimization algorithms for data collection and clustering, routing, security, and energy management. The TOC is structured in five sections, beginning with an introductory overview of smart sensor networks, including a guide to types of smart sensor networks. The second section delves into the fundamental principles of smart sensor networks, including a discussion of energy management, and security and privacy issues. Part Three considers how sensor networks can work with artificial intelligence. Part Four considers applications of smart sensor networks in the real world, for example for monitoring the environment and healthcare. The book closes with an exploration of the future opportunities and risks inherent in adopting smart sensor networks.Overall, Foundations of Smart Sensor Networks equips the reader with the knowledge needed to design, implement, and optimize smart sensor networks for a variety of applications.

  • Smart and Sustainable Healthcare Systems

    From Algorithms to Patient Outcomes
    • 1st Edition
    • Shivi Sharma + 3 more
    • English
    Smart and Sustainable Healthcare Systems: From Algorithms to Patient Outcomes addresses the transformative evolution in healthcare driven by artificial intelligence, machine learning, telemedicine, and digital health technologies. This reference responds to the growing need for sustainable, personalized, and efficient healthcare delivery by bridging technical innovation with clinical application across diverse medical and engineering disciplines. The content spans intelligent decision support systems, IoT and wearable technologies, secure electronic medical records, telemedicine solutions, and automation in diagnostics and treatment. The book includes detailed chapters on AI in clinical pathways, predictive healthcare analytics, brain tumor classification, and sustainable telehealth innovations, complemented by real-world case studies and future outlooks. This reference benefits researchers, healthcare engineers, clinicians, and policymakers by providing in-depth exploration of emerging technologies, challenges, and practical solutions in Healthcare 4.0. It promotes sustainable healthcare practices, ethical AI use, and advances in telemedicine, equipping professionals with knowledge to design and implement intelligent healthcare systems that enhance patient care and resource efficiency.

  • Lightweight Secure and Intelligent Approaches for Medical Devices

    Trends and Future Frontiers
    • 1st Edition
    • R. Praveen + 1 more
    • English
    Lightweight Secure and Intelligent Approaches for Medical Devices: Trends and Future Frontiers addresses the rapidly evolving intersection of artificial intelligence, Internet of Medical Things (IoMT), and edge computing within healthcare. This reference meets the critical demand for resource-efficient, secure, and trustworthy AI models tailored specifically for embedded medical devices operating under stringent constraints. By integrating advances in lightweight AI, medical device security, and intelligent data processing, the book fills a vital gap in current literature, offering researchers, engineers, and healthcare professionals a comprehensive resource to develop next-generation medical technologies. The book is organized into four parts, beginning with foundational concepts including the evolution of AI in healthcare devices, lightweight model design, and medical device security standards. It progresses to predictive intelligence and reliability, covering AI techniques for disease monitoring, device calibration, and personalized medicine. The security and privacy section explores network architectures, privacy-preserving AI, lightweight cryptography, and defenses against adversarial attacks. The final part presents emerging trends such as edge AI, digital twins, explainable AI, augmented and virtual reality applications, and quantum-safe security protocols. Each chapter combines theoretical insights with practical case studies and research perspectives to guide real-world deployment. Lightweight Secure and Intelligent Approaches for Medical Devices: Trends and Future Frontiers serves as an essential reference for researchers, medical device developers, cybersecurity professionals, and graduate students aiming to innovate secure and intelligent healthcare solutions in resource-constrained environments.

  • The Deterministic Universe

    Exploring Chaos, Free Will, Prediction, and Modeling
    • 1st Edition
    • Paul A. Gagniuc
    • English
    The Deterministic Universe: Exploring Chaos, Free Will, Prediction, and Modeling equips readers with the tools to learn the foundational concepts of chaos, randomness, and determinism through examples and applied case studies. The book helps readers gain insights into how deterministic algorithms handle complex, chaotic data, providing an interdisciplinary exploration of chaos theory, determinism, and free will grounded in scientific principles, computational models, and philosophical insights. The content builds on established theories in physics, bioinformatics, and systems biology, weaving them into broader existential questions. The material emphasizes the interplay between randomness, noise, and order, providing a fresh lens to view the universe.The book connects these ideas to practical tools like random number generators and nonlinear equations, machine learning algorithms, computational and predictive models, extending their implications to biological systems, human thought, and decision-making. By addressing both scientific fundamentals and philosophical debates, it bridges abstract ideas with real-world phenomena and demonstrates the role of randomness and noise in predictive models and simulations, thus helping readers understand the limits of computational systems in mimicking real-world processes.

  • Metaheuristic Optimization for Social Good

    • 1st Edition
    • Thompson Stephan + 2 more
    • English
    Metaheuristic Optimization for Social Good presents a comprehensive guide that shows how powerful optimization algorithms—genetic algorithms, swarm intelligence, evolutionary strategies, and other heuristics—can be tailored to address critical societal problems. Whereas existing references tend to focus on either the technical underpinnings of metaheuristics or broad “AI for social impact” overviews, this book demonstrates how metaheuristic approaches can be systematically and ethically applied to domains such as healthcare, urban planning, environmental stewardship, and policy-making. This handbook directly addresses these challenges by providing a structured approach to metaheuristics, presenting rigorous theoretical foundations, state-of-the-art hybrid techniques, and diverse real-world applications. The book consolidates research insights, methodological innovations, and practical use cases into a single, accessible volume. The book presents theoretical advances, hybrid model architectures, and practical applications, providing comprehensive coverage that combines metaheuristics with machine learning and data-driven simulation to enhance decision making for social good. The authors provide real-world case studies that cover the intersection of advanced optimization algorithms and multiple social domains in one volume, with technical depth in each topic. Readers learn how to ensure optimization results align with values such as fairness, equity, and sustainability, preparing readers to not only build effective solutions, but also ones that are socially acceptable and beneficial.

  • System of Systems Engineering

    Innovations, Challenges, and Future Directions
    • 1st Edition
    • Bedir Tekinerdogan + 1 more
    • English
    System of Systems Engineering: Innovations, Challenges, and Future Directions focuses on the many aspects of System of Systems Engineering. Part I, Foundations of System of Systems Engineering, introduces the field, characterizes and classifies SoS, and discusses key concepts. Part II, Governance and Management of SoSE, covers strategic governance, policy and regulatory frameworks, and leadership and decision-making in SoSE projects. Part III, Methodologies and Tools, explores systems thinking and modeling approaches, lifecycle management, and interoperability and integration strategies. Part IV, AI and System of Systems Engineering, delves into leveraging AI for enhanced decision-making, machine learning applications, AI-driven automation and control, and ethical considerations.Final... Part V, Case Studies and Emerging Challenges, presents real-world applications in defense and aerospace, smart cities, healthcare, environmental and energy systems, and discusses future directions and research opportunities. This book offers significant benefits to graduate students, researchers, and professionals in software engineering, systems engineering, aerospace engineering, defense, telecommunications, and other fields where SoSE is relevant.

  • Ensuring AI-enabled Zero Trust Security for Smart City and Healthcare Applications Part A

    • 1st Edition
    • Volume 146
    • English
    Ensuring AI-enabled Zero Trust Security for Smart City and Healthcare Applications Part A, published as Volume 146 of the serial Advances in Computers, provides a comprehensive examination of the convergence of artificial intelligence, Zero Trust security frameworks, smart city infrastructures, and healthcare technologies. The volume explores how AI-driven security architectures can safeguard increasingly interconnected urban and healthcare ecosystems, addressing challenges associated with IoT networks, autonomous vehicles, wearable devices, telemedicine platforms, medical imaging systems, and healthcare data interoperability. It highlights emerging approaches that integrate AI, blockchain, edge computing, digital twins, federated learning, threat intelligence, and quantum computing to strengthen cyber resilience, privacy protection, and trust management across critical applications. By combining foundational concepts with practical implementations and future-oriented perspectives, this volume serves as an authoritative resource for researchers, cybersecurity professionals, healthcare technologists, and smart city stakeholders seeking to develop secure, adaptive, and resilient digital environments.

  • Analytical and Computational Modeling of Complex Systems

    A Systematic Approach to Understanding Real-World Complexity
    • 1st Edition
    • Florentin Paladi + 3 more
    • English
    Analytical and Computational Modeling of Complex Systems: A Systematic Approach to Understanding Real-World Complexity presents modern studies of complex systems by methods of statistical physics, numerical calculation, and computer modeling. Using general methods of investigating the branching (bifurcations) of solutions for nonlinear equations, the authors present an exhaustive analysis of the order parameter dependences on the control parameter in a small vicinity of the equilibrium values of parameters, including the stability analysis of the equilibrium states, and the asymptotic behavior of the order parameter dependences on the control parameter (bifurcation diagrams). The authors also present concepts and techniques used to model heterogeneous multi-agent interactions, complex neural networks, biochemical reaction networks in cells, and the dynamic behavior of economic systems over time. The book serves as both a learning resource and a practical reference for those engaged in the study of complex systems and their diverse real-world implementations. The book also offers a systematic learning path from theory to applications. It provides case studies that bridge the gap between mathematical formalism and complex systems modeling and simulation. Emphasizing hybrid and probabilistic modeling techniques, the book ensures greater flexibility for real-world applications. Covering a broad range of topics, it supports interdisciplinary use across departments such as physics, computer science, engineering, economics, and more.

  • Advanced Methods in Mathematics and Data Science

    Concepts and Applications
    • 1st Edition
    • Mehmet Yavuz + 2 more
    • English
    Advanced Methods in Mathematics and Data Science: Concepts and Applications provides a comprehensive guide to topics in which mathematical modelling and applications play a pivotal role, including computational models in physics and chemistry, statistical models in life science, data analysis in engineering, as well as finance and social science applications. The book provides a clear and step-by-step presentation of advanced mathematical methods at the intersection of machine learning, artificial intelligence, big data analytics, and statistics, including control theory, topology, and nonlinear dynamic systems. The book progresses from concepts and foundational methods in the early chapters, to inter-disciplinary applications in computational mathematics, mathematical biology, fractional calculus, nonlinear dynamical systems, and data-driven optimization. The methods used to analyze data using a particular computational model are thoroughly explained through real-world and publicly available data sets. Examples of real-world data sets from a variety of academic disciplines are provided so that a wide audience can learn to analyze data in their research. The book provides tips, recommendations, and strategies to troubleshoot common issues, as well as definitions of key terms. The book helps readers enhance their conceptual understanding and practical application of computational methods to real-world data sets, and enables readers to gain competency at the intersection of advanced mathematics and AI, which is an important skill in today’s data-driven market.

  • Advanced Methods for Optimizing and Accelerating Deep Learning Models

    • 1st Edition
    • Patrick Siarry + 3 more
    • English
    Advanced Optimization and Acceleration Techniques for Deep Learning Models provides a comprehensive guide to enhancing deep learning models' efficiency, scalability, and performance, including large language models (LLMs). As AI systems grow in complexity, optimizing their training and deployment has become critical for achieving higher accuracy, faster inference, and reduced computational costs. This book explores cutting-edge optimization strategies, from gradient descent refinements and hyperparameter tuning to model compression, pruning, and hardware acceleration. AI is evolving rapidly, but existing deep learning resources often focus on building models rather than optimizing them for efficiency and scalability. As deep learning applications expand into cloud computing, edge AI, and real-time decision-making, a dedicated resource on optimization is essential. This book addresses this gap by providing a structured approach to making deep learning networks faster, more cost-effective, and more sustainable.

  • Artificial Intelligence Modeling for Dynamical Problems

    • 1st Edition
    • Snehashish Chakraverty + 2 more
    • English
    Artificial Intelligence Modeling for Dynamical Problems provides a comprehensive exploration of AI-driven methodologies tailored to address the intricate challenges posed by dynamical systems. The chapters in this book delve into cutting-edge techniques, including scientific machine learning, operator learning, fuzzy logic, and optimization algorithms, highlighting their applications in structural dynamics, fluid dynamics, robotics, and wave dynamics. Readers will gain insights into innovative state-of-the-art approaches such as Physics-Informed Neural Networks (PINNs) for precise navigation and control in autonomous vehicles, convolutional neural networks (CNNs) for frequency dynamics recognition, and data-driven models for market sentiment analysis. Additionally, the book explores the role of uncertainty modeling, statistical inference, and hybrid AI techniques, such as Type-2 fuzzy fractional modeling, in advancing the field of dynamical system analysis. Each chapter combines foundational principles with practical applications, including recent investigations, making it a valuable resource for researchers, practitioners, students of STEM seeking to apply theoretical AI models to real-world dynamical problems.

  • Functional Equations and Stability Theory

    Methods and Applications in Science and Engineering
    • 1st Edition
    • Ali Turab + 2 more
    • English
    Functional Equations and Stability Theory: Methods and Applications in Science and Engineering presents current advancements in the theory of functional equations and their stability, with a particular emphasis on their applications across science, engineering, and computational domains. Functional equations—long-stand... pillars of mathematical analysis—have experienced a transformative evolution through the lens of Hyers–Ulam stability theory and its generalizations, which now intersect with key disciplines including artificial intelligence, cognitive science, and cybersecurity. This book provides readers with both principles of classical theory along with contemporary applications, thereby advancing the discourse on functional equations beyond its traditional confines. The book provides readers with both foundational studies and emerging methodologies, exploring how stability properties—such as Ulam–Hyers and generalized stability—are not only central to pure mathematics but also critically relevant to the modeling of real-world systems. By presenting methods that span theoretical results, fixed point methods, approximation techniques, and interdisciplinary case studies, this book offers a comprehensive perspective for readers interested in both mathematical rigor and real-world impact.The book features chapters on advanced topics including classical and generalized stability of Cauchy, Jensen, Drygas, and Pexider-type equations; functional equations in restricted domains and abstract metric spaces; fixed point techniques for analyzing nonlinear and operatorial equations; stability in functional inequalities and mixed-type systems; applications to cognitive modeling, behavioral dynamics, and learning systems; functional frameworks in information theory, entropy, and communication systems; operator-valued and matrix functional equations; stability-informed modeling in cybersecurity, robotics, and intelligent environments; and, approximation and numerical approaches to stability problems. As such, the authors address both computational and mathematical dimensions, empowering readers to apply functional equations and stability theory to contemporary scientific problems.

  • Trustworthy LLMs

    Principles and Challenges
    • 1st Edition
    • Mohit Kumar
    • English
    Despite numerous advantages, LLMs have trust, transparency, accountability, and reliability issues due to development with "black-box" approaches, which make it difficult to understand how LLMs create specific outputs. Trustworthy LLMs: Principles and Challenges presents the fundamental concepts of trustworthy LLMs, then proceeds to address the foremost challenges researchers and developers face in developing reliable and trustworthy LLMs. The book begins by presenting the main research branches of artificial intelligence along with the principles of LLMs, from pre-training to fine tuning, and, ultimately, trustworthy LLMs. Readers will learn about the chief technical principles of LLMs, including attention mechanism, transformers, and transfer learning. The methodologies used for development of ChatGPT have been explained as a case study for comprehensive understanding of the concepts involved in LLMs. Readers will also learn about the integration of XAI with LLM, and other key frontiers in trustworthy LLM development, including the synergy between deep learning and LLMs, as well as case studies on GPT-4 and OPT-1.3B. The book concludes with chapters on key challenges and future research approaches for developing trustworthy LLMs.

  • Measuring the User Experience

    Collecting, Analyzing, and Presenting UX Metrics
    • 4th Edition
    • Bill Albert + 1 more
    • English
    Measuring the User Experience: Collecting, Analyzing, and Presenting UX Metrics provides the quantitative analysis training that students and professionals need. This book presents an update on the first resource that focused on how to quantify user experience. Now in its fourth edition, the authors have continued to expand on the area of behavioral and physiological metrics. The book also contains new research and updated examples, several new case studies, and new examples using the most recent version of Excel.

  • UX of AI

    Understanding and Designing Intelligent User Experiences
    • 1st Edition
    • Rahul Divekar
    • English
    Artificial Intelligence (AI) has become so ubiquitous within technology that all technological design involves some aspect of AI behind the scenes. Knowing how AI technologies relate to the user experience (UX)/user interface (UI)/product design field and how they can be applied will be a key skill for both designers and technologists. The UX of AI: Understanding and Designing Intelligent User Experiencesoffers a critically understanding of the benefits and limitations of the integration of AI and UX. Bridging the gap between artificial intelligence technologies and experience design, and written for UX/UI/product/servic... designers, researchers, and students, it demystifies complex AI concepts and demonstrates their practical applications in creating intuitive, responsive, and personalized user experiences. The book begins by establishing fundamental AI concepts in accessible language, avoiding unnecessary technical jargon while providing readers with a solid understanding of Large Language Models (LLMs), machine learning, natural language processing, computer vision, and complex architectures that combine various AI technologies to form innovative interactions and products. It then explores the unique design challenges and opportunities presented by AI-powered interfaces. The book also offers exercises that instructors can use as interactive classroom activities or homework assignments.

  • Advances in Multimodal Large Language Models for Healthcare

    Methods and Applications
    • 1st Edition
    • Hari Mohan Pandey + 4 more
    • English
    Advances in Multimodal Large Language Models for Healthcare: Methods and Applications provides valuable insights on Large Language Models in healthcare applications for researchers, academics, and practitioners. The book explains key concepts, including artificial intelligence, machine learning, deep learning, and the evolution of neural networks and transformer models. It then covers generative AI and LLMs for a wide spectrum of healthcare applications, including mental health, clinical decision support, interactive system design, and sensitive analysis. Readers will find this to be a valuable deep dive into the emergent intersection of LLMs and health care, with guidance into applications, technical and programming methods, and more.Although LLMs have shown some promising results in the healthcare sector, numerous challenges need to be addressed before they can be used in patient care. The two key issues with the adoption of LLMs regarding healthcare settings are reliability, transparency, interpretation of results and bias (data and algorithm) management. Unless properly and adequately validated, there may be incorrect medical information provided by the LLM-based systems, which can lead to misdiagnosis or hazardous treatment errors. At this point, LLMs have not only been used for decision making or documentation, they have also proven to be useful in patient engagement through QA systems, medical chatbots, and virtual healthcare.

  • Photogrammetry

    Videogrammetry and Forensic Analysis of Digital Media
    • 1st Edition
    • William T.C. Neale + 1 more
    • English
    Photogrammetry: Videogrammetry and Forensic Analysis of Digital Media is a deep dive into the mechanics of digital media, its structure, its embedded data, and the science of verifying, evaluating, and quantifying photographic and video evidence. In the world of digital media, a single photograph or video is rarely what it appears to be. Beneath the surface lies a complex puzzle of hidden layers, where diverse formats and invisible processing techniques can transform even the simplest clip into a labyrinth of technical challenges. This book serves as a rigorous roadmap for analysts and experts who operate in the realm of measurable facts and verifiable data, even in the face of increasingly sophisticated AI-generated material. The book is organized into two technical pillars: Photo Analysis & Photogrammetry: Spanning both visual interpretation and spatial quantification, this section establishes robust protocols for image authentication and validation before advancing into high-level photogrammetric methodologies. Readers will learn how to extract precise three-dimensional measurements from two-dimensional imagery with defensible, mathematically grounded accuracy. Video Analysis & Videogrammetry: This section traces the evolution of video analysis, from frame-by-frame examination to a comprehensive understanding of compression systems and the artifacts they introduce. It then progresses into advanced videogrammetry, including dynamic reconstruction and object tracking in three-dimensional space. Readers will explore the sophisticated world of videogrammetry: tracking objects through time and space to provide a definitive account of an object’s size and shape, orientation, and detailed dynamics.Written for cybersecurity and infosec professionals, forensic analysts, photogrammetrists, accident reconstructionists, and technical investigators, this authoritative manual provides the foundational knowledge and advanced methodologies required for high-level expert work. It equips readers to confidently address common challenges, correct distortions, and integrate complex data into defensible conclusions. This is an essential resource for professionals tasked with transforming photographic and video evidence into accurate, reliable, and quantifiable representations of reality.

  • Quantum Computing for Internet of Things

    • 1st Edition
    • Volume 145
    • English
    Quantum Computing for Internet of Things, published as Volume 145 of the serial Advances in Computers, provides a comprehensive examination of the convergence of quantum computing and the Internet of Things (IoT). The volume introduces the fundamental principles of quantum computing, including qubits and quantum mechanics, and explores the architectures, enabling technologies, and intelligent applications that underpin modern IoT ecosystems. It highlights how quantum technologies can enhance IoT performance, security, optimisation, and data processing capabilities across diverse application domains.The volume presents emerging advances in quantum-enabled IoT systems, including distributed quantum computing frameworks, quantum machine learning approaches, quantum simulation tools, and novel optimisation techniques tailored to IoT environments. Case studies and application-focused chapters demonstrate the use of quantum methods in military systems, climate change analysis, and healthcare analytics. The volume concludes by addressing key research challenges, implementation barriers, and future directions, making it a valuable resource for researchers and practitioners working at the intersection of quantum technologies and connected intelligent systems.

  • Federated Intelligence in Medicine

    AI-Driven Robotics for Secure and Intelligent Healthcare Systems
    • 1st Edition
    • Manisha Guduri + 3 more
    • English
    Federated Intelligence in Medicine: AI-Driven Robotics for Secure and Intelligent Healthcare Systems explores the rapidly evolving field where medical robotics intersects with cutting-edge artificial intelligence and secure data-sharing technologies. Covering a comprehensive range of topics, the book begins with foundational knowledge in medical robotics and Generative AI, progressing to advanced concepts such as federated learning and architectural modeling tailored for AI-driven robotic systems. Readers will explore algorithms enhancing surgical robotics, remote robotic surgeries, and human-robot interaction. The text also tackles AI-driven diagnostic robots, privacy preservation through homomorphic encryption, and differential privacy and emerging medical imaging techniques integrated with robotics.Later chapters examine the synergy of large language models, agent AI, and edge AI with robotic technologies, providing both theoretical frameworks and practical case studies that illuminate real-world applications and challenges. This book is an invaluable resource for researchers and academicians engaged in artificial intelligence, robotics, and medical technology. It also serves undergraduate and graduate students in Biomedical Engineering, Electronics and Electrical Engineering, and Computer Science and Engineering.

  • Digital Twins and Predictive Modeling in Robotic Surgery

    • 1st Edition
    • Mudassir Khan + 3 more
    • English
    Digital Twins and Predictive Modeling in Robotic Surgery addresses the transformative convergence of digital twin technology, predictive analytics, and robotic surgery. This reference responds to the critical need for a comprehensive resource that bridges simulation science, artificial intelligence, and real-time robotic execution, facilitating enhanced surgical precision, patient-specific planning, and intraoperative decision-making. The content is organized into four parts covering foundational intelligent surgical systems, predictive modeling and simulation, clinical applications with case studies, and challenges alongside future directions. Topics include AI integration, IoT-enabled sensor networks, digital twin architectures encompassing the entire surgical ecosystem, surgical workflow modeling, risk assessment, human-robot interaction, technology acceptance, ethical and regulatory considerations. Real-world examples from smart hospitals worldwide illustrate practical implementation. This books benefits biomedical engineers, researchers, and healthcare system architects by providing interdisciplinary insights, practical implementation frameworks, and cutting-edge case studies. It supports improved surgical planning, precision, and decision-making, empowering end users to advance the adoption of intelligent, AI-powered robotic surgery systems in clinical practice and research environments.

  • Autonomous Intelligence

    Designing the Future of Agentic Systems
    • 1st Edition
    • Shubham Mahajan + 1 more
    • English
    Autonomous Intelligence: Designing the Future of Agentic Systems provides insights on how autonomous technologies—from robots to AI-driven systems— are transforming industries and daily life. The book explores how these intelligent agents operate independently, making decisions and taking actions without constant human intervention. Through clear explanations and real-world examples, the book serves as a gateway for both novices and experts as it simplifies the complexities of autonomous systems. Sections cover Foundations of AI and Autonomy; Understanding Agentic Intelligence; Technology Enablers and Architectures; Design, Safety, and Deployment; Sectoral Applications of Agentic AI; Societal, Ethical, and Future Considerations.The book also considers how these technologies function, while also addressing concerns about their integration, limitations, potential benefits, and possible risks. In a rapidly evolving field, the book looks at latest trends, applications, and research, and at the ethical and legal considerations, especially in areas like employment, privacy, and accountability.

  • Ethics of Blockchain by Design

    • 1st Edition
    • Muthu Ramachandran
    • English
    Ethics of Blockchain by Design offers a comprehensive, design-centered framework that integrates ethical principles into every stage of blockchain system development. Rooted in systems engineering, the book systematically explores how ethical requirements can be specified, implemented, and validated within decentralized technologies. It goes beyond theoretical discussions by providing actionable methodologies, case studies, governance models, and compliance tools, making it essential reading for blockchain architects, developers, students, and policymakers. This book positions itself at the intersection of engineering, ethics, and decentralized innovation, and builds on the author’s extensive contributions to AI ethics, secure software systems, and blockchain in healthcare.The increasing integration of blockchain into critical sectors such as finance, healthcare, and governance has prompted a pressing need to address ethical considerations from the ground up. While blockchain offers revolutionary potential for transparency, decentralization, and trust, it also introduces profound challenges around accountability, privacy, inclusion, and governance. Current literature often focuses on the technological and economic dimensions of blockchain but overlooks its ethical implications, leaving a critical gap in both research and practice.

  • Observing the User Experience

    A Practitioner's Guide to User Research
    • 3rd Edition
    • Elizabeth Goodman + 1 more
    • English
    Observing the User Experience: A Practitioner's Guide to User Research, Third Edition helps readers bridge the gap to understand what users want and need from their product. Filled with real-world experience and a wealth of practical information, the book presents a complete toolbox of techniques to help designers, developers, and other stakeholders see through the eyes of their users. Sections discuss the benefits of end-user research and the ways it fits into the development of useful, desirable, and successful products and present techniques for understanding people’s needs, desires, and abilities, providing a basis for developing better products, whether Web, software, or mobile-based.Final chapters explain the communication and application of research results.

  • Probabilistic Modelling for Advanced Data Analysis

    • 1st Edition
    • Amit Kumar Tyagi
    • English
    Probabilistic Modelling for Advanced Data Analysis provides a practical and rigorous guide for data practitioners to effectively implement probabilistic models in real-world scenarios. The book strikes a balance between high-level intuition and technical derivations, offering step-by-step explanations, real-world case studies, and Python implementation examples. The authors offer specific solutions that include modeling and quantifying uncertainty in data-driven decision-making, applying Bayesian inference to real-world problems and implementing scalable probabilistic models for large-scale datasets, all of which contribute to explainable and trustworthy AI.This book presents readers with theoretical foundations and practical applications of probabilistic modeling, providing a structured approach for researchers, data scientists, and industry professionals. It meets the increasing demand for uncertainty-aware AI models, Bayesian inference, and probabilistic graphical models across various fields of research.

  • Neural Networks

    A Concise Theoretical Foundation
    • 1st Edition
    • Aydin Sarraf + 1 more
    • English
    This book presents deep learning as both a mathematical discipline and an applied field, connecting theoretical principles with the modeling and design choices that shape modern neural systems. It explores how neural networks are formulated and how they learn, from multilayer perceptrons, activation and loss functions, optimization, and backpropagation to questions of expressivity and generalization. These ideas are applied to neural architectures for different forms of data, including convolutional, recurrent, and graph neural networks, with attention to the mathematical principles, training challenges, and design choices that distinguish them. The book then turns to generative models and sequential decision-making, covering variational and adversarial models, diffusion, and reinforcement learning.The later parts follow the evolution of neural networks toward increasingly general systems, exploring attention and transformer architectures, multimodal models, large language models, retrieval-augmented systems, and autonomous agents. The book also considers directions beyond conventional deep learning, including continuous-time and physics-informed neural networks, biologically-inspire... and neuromorphic models, Bayesian approaches to uncertainty, and quantum neural networks.The term “theoretical” in the title, Neural Networks: A Concise Theoretical Foundation, refers to the mathematical formulation of neural networks, not to a comprehensive, proof-oriented treatment of neural network theory. Organized in four parts, the book connects mathematical descriptions with the architectures, learning methods, and emerging directions that continue to shape neural computation.

  • Next-Generation VAPT

    Combining OSINT and AI-ML for Enhanced Vulnerability Assessment and Penetration Testing
    • 1st Edition
    • Ravi Sheth + 4 more
    • English
    Next-Generation VAPT: Combining OSINT and AI/ML for Enhanced Vulnerability Assessment and Penetration Testing empowers information security threat intelligence with the fusion of Open-Source Intelligence Tools (OSINT) and Artificial Intelligence and Machine Learning (AI/ML) to identify and detect vulnerabilities more efficiently and effectively. The book highlights the concept of OSINT for gathering actionable threat intelligence and AI/ML for automating threat detection, which ultimately enhances VAPT processes. The authors explain concepts for assessing the security of networks, wireless networks, performing VAPT on mobile devices, and conducting red teaming, which helps end users deal with upcoming threats at an early stage.It focuses on using machine intelligence for developing and validating exploits and AI-driven exploitation testing, which helps field experts discover and exploit vulnerabilities more quickly and accurately. Readers will find essential ethical and legal considerations in AI/ML and OSINT-based VAPT, ensuring responsible and compliant testing practices, accountability, and transparency. Industry Case Studies with solutions and safeguards are an integral part of the books applied approach.

  • Healthcare 5.0

    Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data
    • 1st Edition
    • Yugal Kumar + 2 more
    • English
    Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data addresses the urgent need for innovation in today’s complex healthcare data landscape that is characterized by pandemics, aging populations, and chronic conditions. The book introduces the concept of ‘Healthcare 5.0’ as an interconnected, data-driven, and patient-centric framework where advanced technologies such as AI, ML, IoMT, Big Data, and Large Language Models (LLMs) converge to optimize care, streamline operations, and deliver personalized, predictive solutions. The book moves from core AI applications in electronic health records, drug discovery, data management, and privacy, through cutting-edge big data analytics for disease forecasting and diagnosis.It explores new research advances in the Internet of Medical Things, including connected device architectures and their fusion with AI for dynamic decision-making. The third section focuses on data analytics in telemedicine, remote care, system usability, and integration in Healthcare 5.0. The personalized healthcare section details analysis and applications in AI- and IoT-powered assistance, and real-time monitoring. The last section explores the development of LLMs and their applications in medical imaging, clinical decision support, predictive analytics, system architectures, as well as the ethical challenges of their deployment in healthcare.

  • Advanced Concepts in Grey Wolf Optimizer

    Leading the Pack in Advanced Optimization
    • 1st Edition
    • Seyedali Mirjalili
    • English
    Advanced Concepts in Grey Wolf Optimizer: Leading the Pack in Advanced Optimization provides in-depth coverage of recent theoretical advancements in GWO, as well as advanced methods to handle issues such as multiple objectives, constraints, binary variables, large search spaces, dynamic goals, and uncertain data. This book assumes familiarity with optimization fundamentals and therefore dives directly into multi-objective, constrained, binary, and dynamic-environment variants, as well as GWO-ML/LLM hybrids. Extensive real-world case studies in areas such as energy systems, supply-chain design, LLM fine-tuning, robotics, and finance ensure that both scholars and engineers can translate the material into deployable solutions. The authors present important new theories, hybrids with Machine Learning/Deep Learning, and hybrid methods that increase GWO’s performance. The use of generative AI to improve this algorithm and make it more generic is also explored, along with diverse applications across multiple fields to illustrate the practical utility and versatility of the methods presented. Written by some of the world’s most highly cited researchers in the field of artificial intelligence, algorithms, and machine learning, the book serves as an advanced resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer.

  • Agile Systems Engineering with SysML v2 and AI

    • 2nd Edition
    • Bruce Powel Douglass
    • English
    Agile Systems Engineering with SysML v2 and AI, Second Edition presents a practical vision of systems engineering in which requirements, structure, behavior, and analysis are captured as precise engineering data—while still addressing the “big system” concerns of safety, security, reliability, privacy, and performance in an agile context. World-renowned author and speaker Dr. Bruce Powel Douglass shows how agile methods, model-based systems engineering (MBSE), and artificial intelligence (AI), work together to reduce ambiguity, expose defects earlier, and sustain end-to-end traceability from stakeholder intent to verification evidence.This edition goes beyond concepts by providing usable, repeatable workflows for modern programs—covering incremental, agile, and DevSecOps-oriented lifecycles and the concrete process steps and gates that make them executable in practice. Rather than treating modeling as documentation, the book treats SysML v2 as a semantic backbone for capturing requirements, architecture, interfaces, behaviors, constraints, and verification intent in one coherent source of truth.New to this edition is an introduction to SysML v2 and an entire chapter on AI and modern MBSE, showing where AI assistants provide leverage, how to apply quality-control gates to keep outputs trustworthy, and how to integrate AI into real engineering workflows without surrendering correctness. Each chapter includes AI prompt patterns for MBSE—ready-to-use prompt structures for generating SysML v2 model elements, extracting and normalizing requirements from external sources, reconciling terminology, and reviewing models against project rules and acceptance criteria. Throughout, Douglass equips systems engineers with concrete methods to prevent specification defects, improve system quality, and reduce rework—so teams can move faster and build with greater confidence

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