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Elsevier

Morgan Kaufmann

  • Neuro-Symbolic AI

    Integrating Neural Networks and Symbolic Reasoning
    • 1st Edition
    • Sarika Jain + 3 more
    • English
    Neuro-Symbolic AI: Integrating Neural Networks and Symbolic Reasoning explores the convergence of two historically distinct paradigms in artificial intelligence—data-dr... neural networks and logic-based symbolic reasoning. This book presents a comprehensive roadmap of this emerging hybrid discipline, offering deep theoretical insights, practical methodologies, and transformative applications across diverse research sectors, including healthcare, finance, engineering, and autonomous systems. It is structured into four parts—Foundational Principles, Hybrid Models and Techniques, Real-World Applications, and Emerging Challenges, bringing together cutting-edge research and expert perspectives to highlight how Neuro-Symbolic AI enhances interpretability, reasoning capabilities, and trust in intelligent systems.While neural networks have achieved remarkable success in perception and pattern recognition tasks, they often lack the reasoning, transparency, and generalizability that symbolic systems excel at. Conversely, symbolic AI lacks the flexibility and scalability of deep learning. This handbook directly addresses these challenges by providing a structured approach to Neuro-symbolic AI, presenting rigorous theoretical foundations, state-of-the-art hybrid techniques (e.g., knowledge graphs, compositionality, category theory), and diverse real-world applications. This book consolidates research insights, methodological innovations, and practical use cases into a single, accessible volume.

  • 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

  • Explainable AI for Transparent and Trustworthy Medical Decision Support

    • 1st Edition
    • Abhishek Kumar + 4 more
    • English
    Explainable AI for Transparent and Trustworthy Medical Decision Support equips readers with a comprehensive and timely resource that presents the principles, methodologies, and real-world applications of explainable AI (XAI) within the medical context. Covering a wide range of use cases—from radiology and pathology to genomics and clinical decision support systems—the book provides in-depth discussions on how XAI techniques can enhance interpretability, improve clinician trust, meet regulatory requirements, and ultimately lead to better patient outcomes. The book demystifies the workings of machine learning models and highlights techniques that make them interpretable.It is designed to empower not only AI researchers and developers but also healthcare administrators and policymakers with the knowledge needed to evaluate, adopt, and trust AI solutions in critical medical applications. The book's authors bring together theory, implementation strategies, ethical implications, and case studies under one cover, offering a multidisciplinary perspective that aligns computer science with medical practice and healthcare policy.

  • Full-Stack Web Development from the Ground Up

    Principles, Practices, and Technologies
    • 1st Edition
    • Christopher D. Hundhausen
    • English
    Web development is one of the most highly sought after skills in the software industrytoday. Full-Stack Web Development From the Ground Up: Principles, Practices, andTechnologies presents a systematic and modern treatment of this core area of softwaredevelopment, starting with the fundamentals of front-end development using HTML, CSS,and JavaScript; moving to front-end development with React; and culminating in server-sidedevelopme... using Express.js, Node.js, and MongoDB.Using the widely adopted MERN stack (MongoDB, Express.js, React.js, and Node.js), thisundergraduate textbook explores full-stack web development through the step-bystepconstruct... of a pedagogical version of SpeedScore (see https://speedscore.o... asophisticated full-stack web application that supports the international speedgolf community.The book’s emphasis is not on specific web development technologies, but rather on theunderlying concepts, principles, and best practices of web development. This approach laysa solid foundation for students to become proficient web developers who can adapt to therapidly changing landscape of web development technologies.

  • Advanced Intelligence Methods for Data Science and Optimization

    • 1st Edition
    • Amir Hossein Gandomi + 2 more
    • English
    Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains.It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.

  • Advanced Computational and Mathematical Approaches in Applied Differential Equations

    • 1st Edition
    • Snehashish Chakraverty + 2 more
    • English
    Advanced Computational and Mathematical Approaches in Applied Differential Equations explores cutting-edge techniques and methodologies in solving complex differential equations, a cornerstone of mathematical modeling across science and engineering. The book bridges theory and application, offering advanced computational strategies and innovative mathematical insights to address real-world problems. Beginning with an overview that presents a unified framework that defines the types of differential equations covered (e.g. ordinary, partial, fractional, fuzzy), the book then progresses to foundations and methods such as Lie symmetries, homotropy, Adomian, FEM, FDM, spectral, machine learning, fuzzy, and fractional derivatives, addressing both computational and mathematical dimensions.Different... equations are fundamental to modeling complex systems, yet solving them often involves significant challenges due to their complexity and nonlinearity. The book equips readers with advanced tools and methodologies to overcome these challenges, providing innovative solutions that improve accuracy, efficiency, and applicability in real-world scenarios. Ideal for researchers, practitioners, and advanced students, it provides a comprehensive resource for tackling challenging applied differential equations with better precision and efficiency.

  • Mastering Java Full Stack Development

    From Spring Boot to ReactJS
    • 1st Edition
    • Usharani Bhimavarapu
    • English
    Mastering Java Full Stack Development: From Spring Boot to ReactJS is an essential handbook for building robust, scalable, and future-ready enterprise applications using today’s most in-demand technologies. Written for full-stack developers, software engineers stepping into enterprise systems, as well as students preparing for real-world architecture challenges, this comprehensive guide walks readers through every layer of modern application design—from Spring Boot and Hibernate to Node. js and ReactJS, and from secure RESTful application programming interfaces to microservices and cloud-native deployment. Structured for progressive learning, this book blends theory with hands-on examples to help readers build applications that are not just functional, but maintainable, secure, and scalable. Each chapter provides the why behind the how—enabling readers to make informed technical decisions grounded in industry best practices. This book offers a unified, full-stack view of enterprise application development, integrating back-end, front-end, database, and cloud layers. It provides an integrated, end-to-end guide that shows how Spring, Hibernate, React, and Microservices work together in a cohesive architecture. It also addresses the growing interest and practical implementation challenges associated with applying the most current development methodologies to Java software engineering environments, offering a deep dive into foundational concepts, the challenges faced in real-world applications, and potential future developments. Java remains an integral programming language in modern web-based software development, which enables smoother collaboration, faster deployment, and improved quality of software products. This book is written for full-stack developers and Java back-end developers who want to expand into front-end technologies, as well as front-end developers looking to master enterprise-level back-end development.

  • Grey Wolf Optimizer

    A Pack of Solutions for Your Optimization Problems
    • 1st Edition
    • Seyedali Mirjalili
    • English
    Grey Wolf Optimizer: A Pack of Solutions for Your Optimization Problems offers in-depth coverage of recent theoretical advancements in GWO, as well as several variants, improvements, and hybrid approaches developed to enhance the GWO's performance and adaptability. 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. The book offers a deep dive into the algorithm's foundations and presents new developments to help researchers overcome common challenges.It features numerous case studies and real-world examples across various fields, such as engineering, healthcare, finance, and environmental management. These applications demonstrate the versatility and effectiveness of the GWO in addressing complex, interdisciplinary challenges, making the content highly relevant and practical for readers. 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 essential resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer.

  • Essential Kubeflow

    Engineering ML Workflows on Kubernetes
    • 1st Edition
    • Prashanth Josyula + 2 more
    • English
    Essential Kubeflow: Engineering ML Workflows on Kubernetes provides the tools needed to transform ML workflows from experimental notebooks to production-ready platforms. Through hands-on examples and production-tested patterns, readers will master essential skills for building enterprise-grade Machine Learning platforms, including architecting production systems on Kubernetes, designing end-to-end ML pipelines, implementing robust model serving, efficiently scaling workloads, managing multi-user environments, deploying automated MLOps workflows, and integrating with existing ML tools. Whether you're a Machine Learning engineer looking to operationalize models, a platform engineer diving into ML infrastructure, or a technical leader architecting ML systems, this book provides solutions for real-world challenges.With this comprehensive guide to Kubeflow, a widely adopted open source MLOps platforms for automating ML workloads, readers will have the expertise to build and maintain scalable ML platforms that can handle the demands of modern enterprise AI initiatives.

  • Complexity in Mathematical Biology for Sustainable Development

    Modeling Climate, Disease, and Ecosystems through Difference, Differential, and Fractional Theory
    • 1st Edition
    • Fatma Bozkurt
    • English
    Complexity in Mathematical Biology for Sustainable Development: Modeling Climate, Disease, and Ecosystems through Difference, Differential, and Fractional Theory introduces new mathematical methods to derive complex modeling solutions for a wide range of engineering and scientific research applications. The book strikes a balance between high-level mathematical theory and technical derivations, offering step-by-step explanations, real-world case studies, and clear introductions to advanced mathematical models. Solutions include modeling and quantifying complexity, with emphasis placed on the growing need for interdisciplinary collaboration, the integration of real-time data into models, and the development of adaptive frameworks challenges such as pandemics, biodiversity loss, and climate uncertainty.The book is designed to meet the needs of a diverse primary audience, from graduate students to professionals in fields such as computer science, public health, environmental policy, applied mathematics, and biotechnology. By providing both theoretical foundations and practical applications, the book equips readers with the skills and knowledge to tackle pressing global challenges through mathematical models, making it a valuable resource for both academic and professional development.

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