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Elsevier

Morgan Kaufmann

  • Successful User Experience

    Strategies and Roadmaps
    • 2nd Edition
    • Elizabeth Rosenzweig
    • English
    Successful User Experience: Strategy and Roadmaps, Second Edition provides a hands-on guide for pulling all of the User Experience (UX) pieces together to create a strategy that includes tactics, tools, and methodologies. Leveraging material honed in user experience courses and over 35 years in the field, the author explains the value of strategic models to refine goals against available data and resources. You will learn how to think about UX from a high level, design the UX while setting goals for a product or project, and how to turn that into concrete actionable steps.This book demonstrates how to translate high-level planning into concrete, actionable steps. It explains the connection between Design Thinking and creating a great user experience, and guides the reader in setting effective UX goals for their product or project You’ll learn how to choose the right tools and methodologies at each stage of the product lifecycle. Starting with UX acceptance as a foundation, the book builds on this with practical steps and real-world case studies, helping you develop a comprehensive strategy-from the big picture of product design, development, and commercialization, to leveraging UX for stronger, more successful products.

  • Computer Architecture

    A Quantitative Approach
    • 7th Edition
    • John L. Hennessy + 2 more
    • English
    Computer Architecture: A Quantitative Approach, has been considered essential reading by instructors, students and practitioners of computer design for nearly 30 years. The seventh edition of this classic textbook from John Hennessy and David Patterson, winners of the 2017 ACM A.M. Turing Award recognizing contributions of lasting and major technical importance to the computing field, along with new author Christos Kozyrakis, is fully revised with the latest developments in processor and system architecture.True to its original mission of demystifying computer architecture, this edition continues the longstanding tradition of focusing on areas where the most exciting computing innovation is happening, while always keeping an emphasis on good engineering design.

  • Foundations of Computer Engineering

    • 1st Edition
    • Marilyn Wolf
    • English
    Foundations of Computer Engineering is a complete introductory textbook for freshman and sophomore students taking a first course in computer engineering. This new text covers everything today’s students will need to go from almost no computer-specific knowledge to understanding the design of computer systems, from their fundamental hardware components and mathematical abstractions to their use in solving real-world problems. Covering all the major themes of 21st century computer engineering, including logic and computers, software, and circuits, instructors will find that this book provides a single coherent reference to guide students through their course.

  • Quantum Computational AI

    Algorithms, Systems, and Applications
    • 1st Edition
    • Long Cheng + 2 more
    • English
    Quantum Computational AI: Algorithms, Systems, and Applications is an emerging field that bridges quantum computing and artificial intelligence. With rapid advancements in both areas, this book serves as a vital resource, capturing the latest theories, algorithms, and practical applications at their intersection. It aims to be both informative and accessible, making it perfect for academics, researchers, industry professionals, and students eager to lead in these technologies. The book explores quantum algorithms, system design, and demonstrates real-world applications across various sectors. It provides a comprehensive understanding of how quantum principles can advance AI, revealing unprecedented possibilities and benefits.

  • Recent Developments in Theory and Applications of Fractional Order Systems

    • 1st Edition
    • Mehmet Yavuz + 2 more
    • English
    Recent Developments in Theory and Applications of Fractional Order Systems presents a rigorous and thorough analysis of various aspects of Fractional Calculus. The book provides readers with a thorough understanding of fundamental concepts and methods of applied mathematics utilized in a variety of scientific and engineering disciplines. The authors present each computational modeling concept with a definition, methods, theorems, and observations followed by typical application problems and step-by-step solutions. Each topic is covered in detail, followed typically by several meticulously worked out examples and a problem set containing many additional related problems.In addition, the book discusses recent developments and the latest research on Fractional Calculus and its applications, demonstrating important applications in Engineering, Computer Science, Management, Social Science, and the Humanities.

  • Data Science for Teams

    20 Lessons from the Fieldwork
    • 1st Edition
    • Harris V. Georgiou
    • English
    Managing human resources, time allocation, and risk management in R&D projects, particularly in Artificial Intelligence/Machine Learning/Data Analysis, poses unique challenges. Key areas such as model design, experimental planning, system integration, and evaluation protocols require specialized attention. In most cases, the research tends to focus primarily on one of the two main aspects: either the technical aspect of AI/ML/DA or the teams’ effort, or the typical management aspect and team members’ roles in such a project. Both are equally import for successful real-world R&D, but they are rarely examined together and tightly correlated. Data Science for Teams: 20 Lessons from the Fieldwork addresses the issue of how to deal with all these aspects within the context of real-world R&D projects, which are a distinct class of their own. The book shows the everyday effort within the team, and the adhesive substance in between that makes everything work. The core material in this book is organized over four main Parts with five Lessons each. Author Harris Georgiou goes into the difficulties progressively and dives into the challenges one step at a time, using a typical timeline profile of an R&D project as a loose template. From the formation of a team to the delivery of final results, whether it is a feasibility study or an integrated system, the content of each Lesson revisits hints, ideas and events from real-world projects in these fields, ranging from medical diagnostics and big data analytics to air traffic control and industrial process optimization. The scope of DA and ML is the underlying context for all, but most importantly the main focus is the team: how its work is organized, executed, adjusted, and optimized. Data Science for Teams presents a parallel narrative journey, with an imaginary team and project assignment as an example, running an R&D project from day one to its finish line. Every Lesson is explained and demonstrated within the team narrative, including personal hints and paradigms from real-world projects.

  • Theoretical Foundations of Quantum Computing

    • 1st Edition
    • Daowen Qiu
    • English
    Theoretical Foundations of Quantum Computing is an essential textbook for introductory courses in the quantum computing discipline. Quantum computing represents a paradigm shift in understanding computation. This textbook delves into the principles of quantum mechanics that underpin this revolutionary technology, making it invaluable for undergraduate and graduate students in computer science and related fields. Structured into eight meticulously crafted chapters, it covers everything from the historical context of quantum computing to advanced theories and applications. The book includes core topics such as basic models, quantum algorithms, cryptography, communication protocols, complexity, and error correction codes.Each chapter builds upon the last, ensuring a robust understanding of foundational concepts and cutting-edge research. It serves as both a foundational resource for students and a comprehensive guide for researchers interested in quantum computing. Its clarity makes it an excellent reference for deepening understanding or engaging in advanced research.

  • Data-Driven Insights and Analytics for Measurable Sustainable Development Goals

    • 1st Edition
    • Tilottama Goswami + 2 more
    • English
    Data-Driven Insights and Analytics for Measurable Sustainable Development Goals discusses the growing imperative to understand, measure, and guide actions using data-driven insights. The SDGs encompass a broad spectrum of global challenges, from eradicating poverty and hunger to preserving the environment and fostering peace. To address these issues, one should be able to measure and analyze progress. This book bridges the gap between qualitative and quantitative assessments, recognizing that goals are not solely about numbers but also encompass complex social, environmental, and economic dynamics. By merging data science with qualitative analysis, readers can explore how SDGs intersect and influence each other.The book provides readers with an understanding of how to effectively leverage data science models and algorithms using descriptive analytics, allowing us to assess the current state of SDG performance and offering valuable insights into where we stand on these critical goals. Prescriptive analytics guides actions by offering actionable recommendations, while predictive analytics anticipates future trends and challenges, helping us navigate our path toward the SDGs effectively.

  • Decentralized Optimization in Networks

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

  • Mastering Prompt Engineering

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

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