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Morgan Kaufmann

  • Usability Testing Essentials

    Ready, Set ...Test!
    • 3rd Edition
    • Carol M. Barnum
    • English
    Usability Testing Essentials: Ready, Set ...Test!, Third Edition presents a practical, step-by-step approach to learning the entire process of planning and conducting a usability test. The book explains how to analyze and apply results and what to do when confronted with budgetary and time restrictions. This is the ideal book for anyone involved in usability or user-centered design—from students to seasoned professionals. Updated throughout, this book reflects the latest approaches, tools, and techniques needed to begin usability testing or to advance in this area.

  • 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.

  • 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.

  • Mastering Java Full Stack Development

    From Spring Boot to ReactJS
    • 1st Edition
    • Usharani Bhimavarapu
    • English
    Mastering Java Full Stack Development 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 APIs to microservices and cloud-native deployment. Structured for progressive learning, the 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. Mastering Java Full Stack Development offers a unified, full-stack view of enterprise application development, integrating backend, frontend, database, and cloud layers. The book provides an integrated, end-to-end guide that shows how Spring, Hibernate, React, and Microservices work together in a cohesive architecture. The book also addresses the growing interest and practical implementation challenges associated with applying the most current development methodology 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. The book is written for full stack developers and Java backend developers who want to expand into frontend technologies, as well as frontend developers looking to master enterprise-level backend development.

  • 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 insight 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 and our place within it. 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, the book bridges abstract ideas with real-world phenomena and demonstrates the role of randomness and noise in predictive models and simulations, helping readers understand the limits of computational systems in mimicking real-world processes.

  • Quantum Communication and Cryptography

    • 1st Edition
    • 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.

  • 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.

  • 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

  • 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. 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. The book is structured into four parts—Foundational Principles, Hybrid Models and Techniques, Real-World Applications, and Emerging Challenges. It brings together cutting-edge research and expert perspectives to highlight how Neuro-Symbolic AI enhances interpretability, reasoning capabilities, and trust in intelligent systems. This book addresses the critical challenge faced by AI researchers and practitioners: how to build intelligent systems that combine the learning capacity of neural networks with the reasoning ability of symbolic methods. Readers often struggle with the lack of unified frameworks, practical tools, and clear guidance for integrating these two approaches. This book provides readers with a comprehensive, structured, and interdisciplinary resource that captures the evolving landscape of Neuro-Symbolic AI.

  • Development of Multi-Agent System Infrastructures

    A Practical Approach
    • 1st Edition
    • Andrei Olaru
    • English
    Development of Multi-Agent Systems Infrastructure: A Practical Approach explores the creation of modular frameworks to support the deployment of real-world software applications utilizing multi-agent systems (MAS). Drawing from the author’s hands-on experience with the FLASH-MAS framework—a Fast Lightweight Agent Shell—the book delves into both theoretical models and practical solutions for MAS implementation. It addresses the complexities of deploying autonomous agents across diverse fields such as manufacturing, robotics, health care, and supply chain management, highlighting the shared challenges developers face when managing distributed, networked, or large-scale agent interactions. The book is organized into three main sections, covering models and languages for MAS, the deployment and interaction between system entities, and practical guidance for implementing robust MAS frameworks. Emphasizing modularity, the author presents adaptable tools and solutions that can be independently utilized for system development and maintenance. Practical issues such as entity lifecycle management, environmental interactions, and system robustness are thoroughly examined, making this resource valuable for both new and experienced MAS developers.

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