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Elsevier

Libros en Ciencias de la Computación

  • Essentials of Big Data Analytics

    Applications in R and Python
    • 1 Edición
    • Pallavi Chavan + 2 más
    • Inglés
    Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments.

  • Learning-Driven Game Theory for AI

    Concepts, Models, and Applications
    • 1 Edición
    • Mehdi Salimi + 1 más
    • Inglés
    Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science. In this book, the authors bridge the gap between traditional game theory and its modern applications in artificial intelligence (AI) and related technological fields. The dynamic nature of contemporary problems in robotics, cybersecurity, machine learning, and multi-agent systems requires game-theoretic solutions that go beyond classical methods. The book delves into the rapidly growing intersection of pursuit differential games and AI, focusing on how these advanced game-theoretic models can be applied to modern AI systems, making it an indispensable resource for both academics and professionals. The book also provides a variety of applications demonstrating the practical integration of AI and game theory across various disciplines, such as autonomous systems, federated learning, and distributed decision-making frameworks. The book also explores the use of game theory in reinforcement learning, swarm intelligence, multi-agent coordination, and cybersecurity. These are critical areas where AI and dynamic games converge. Each chapter covers a different facet of dynamic games, offering readers a comprehensive yet focused exploration of topics such as differential and discrete-time games, evolutionary dynamics, and repeated and stochastic games. The absence of static games ensures a concentrated focus on the dynamic, evolving problems that are most relevant today.

  • Engineering Generative AI-Based Software

    • 1 Edición
    • Miroslaw Staroń
    • Inglés
    Engineering Generative-AI Based Software discusses both the process of developing this kind of AI-based software and its architectures, combining theory with practice. Sections review the most relevant models and technologies, detail software engineering practices for such systems, e.g., eliciting functional and non-functional requirements specific to generative AI, explore various architectural styles and tactics for such systems, including different programming platforms, and show how to create robust licensing models. Finally, readers learn how to manage data, both during training and when generating new data, and how to use generated data and user feedback to constantly evolve generative AI-based software.As generative AI software is gaining popularity thanks to such models as GPT-4 or Llama, this is a welcomed resource on the topics explored. With these systems becoming increasingly important, Software Engineering Professionals will need to know how to overcome challenges in incorporating GAI into the products and programs they develop.

  • Multimodal Learning Using Heterogeneous Data

    • 1 Edición
    • Saeid Eslamian + 3 más
    • Inglés
    Multimodal Learning Using Heterogeneous Data is a comprehensive guide to the emerging field of multimodal learning, which focuses on integrating diverse data types such as text, images, and audio within a unified framework. The book delves into the challenges and opportunities presented by multimodal data and offers insights into the foundations, techniques, and applications of this interdisciplinary approach. It is intended for researchers and practitioners interested in learning more about multimodal learning and is a valuable resource for those working on projects involving data analysis from multiple modalities.The book begins with a comprehensive introduction, focusing on multimodal learning's foundational principles and the intricacies of heterogeneous data. It then delves into feature extraction, fusion techniques, and deep learning architectures tailored for multimodal data. It also covers transfer learning, pre-processing challenges, and cross-modal information retrieval. The book highlights the application of multimodal learning in specialized contexts such as sentiment analysis, data generation, medical imaging, and ethical considerations. Real-world case studies are woven into the narrative, illuminating the applications of multimodal learning in diverse domains such as natural language processing, multimedia content analysis, autonomous systems, and cognitive computing. The book concludes with an insightful exploration of multimodal data analytics across social media, surveillance, user behavior, and a forward-looking examination of future trends and practical implementations. As a collective resource, Multimodal Learning Using Heterogeneous Data illuminates the powerful utility of multimodal learning to elevate machine learning tasks while also highlighting the need for innovative solutions and methodologies. The book acknowledges the challenges associated with deep learning and the growing importance of ethical considerations in the collection and analysis of multimodal data.Overall, Multimodal Learning Using Heterogeneous Data provides an expansive panorama of this rapidly evolving field, its potential for future research and application, and its vital role in shaping machine learning's evolution.

  • Computer Animation

    Algorithms and Techniques
    • 4 Edición
    • Andrew Hogue + 1 más
    • Inglés
    Computer Animation: Algorithms and Techniques, Fourth Edition surveys computer algorithms and programming techniques for specifying and generating motion for graphical objects, that is, computer animation. It is primarily concerned with three-dimensional (3D) computer animation. In this edition, the most current techniques are covered along with the theory and high-level computation that have earned the book a reputation as the best technically oriented animation resource. As in previous editions, the book addresses practical issues, provides accessible techniques, and offers straightforward implementations.

  • Video Health Monitoring in Hospitals

    • 1 Edición
    • Wenjin Wang + 3 más
    • Inglés
    Video Health Monitoring in Hospitals discusses the emergence of camera-based, contactless physiological measurement as a groundbreaking solution in healthcare monitoring. The book highlights the technology's non-invasiveness, capacity for continuous and long-term monitoring, and its ability to capture not only vital signs but also contextual information and behaviors. A unique aspect of this book is its rich set of compelling healthcare applications that will attract broader audiences (including researchers, engineers, clinicians, and students) from multidisciplinary fields.Finally, the book discusses the role of artificial intelligence in enhancing healthcare applications and aims to engage the healthcare industry in adopting this innovative approach to improve patient care and outcomes.

  • A History of Angiogenesis

    Discoveries, Research and the Therapeutic Potential
    • 1 Edición
    • Gianfranco Natale + 2 más
    • Inglés
    A History of Angiogenesis: Discoveries, Research and the Therapeutic Potential presents a recent history of discoveries in the angiogenic field that contribute to the development of the anatomical knowledge of the process, experimental models, and new pharmacological approaches in different angiogenesis-related diseases. This multifaceted book is enriched with deep scientific contents, and each chapter clearly defines historical steps, the emerging role during the years of new morphological findings, molecular pathways, and targets. Focus is also directed on key challenges associated and future directions.The history of angiogenesis research is an intriguing tool for discovering answers to a wide array of queries arising in the biological and medical world. This comprehensive resource skillfully integrates all the key aspects related to angiogenesis, and will be of immense help to students, researchers, and industry experts who want to explore the last two decades of angiogenesis discoveries and research.

  • Transforming Industries, Empowering Societies

    A Comprehensive Examination of Industry 5.0 and Society 5.0
    • 1 Edición
    • Parikshit Narendra Mahalle + 3 más
    • Inglés
    With the ever-increasing use of AI technologies, ethical considerations take on greater importance. Human-centric AI emphasizes transparency, making sure that AI systems work in a way that users can comprehend and trust. Additionally, it addresses bias and discrimination issues, ensuring fairness and inclusion in the design and implementation of AI apps. By emphasizing user experience, security, and human-centric AI, the goal is to improve collaboration between people and machines, rather than replacing human decisions, creating a future where technology is a force for good, benefiting both businesses and society. Written from a technological point of view, Industry 5.0 for Society 5.0 explores the impact of cutting-edge technologies, including the Internet of Things, cloud, artificial intelligence, and digital twin, on individuals and community, and considers how they can be used to solve societal problems. The book considers how these technologies can positively affect industry, healthcare, agriculture, design and manufacture, contributing to the development of a sustainable environment that ultimately creates a positive and mutually beneficial relationship between people and AI.

  • Consensus

    Fueling Blockchain Innovation and DApp Expansion
    • 1 Edición
    • Ali Ahmadian + 3 más
    • Inglés
    Consensus: Fueling Blockchain Innovation and DApp Expansion explores the complexities of consensus mechanisms in order to shed light on emerging trends, best practices, and real-world applications that can fuel blockchain innovation while encouraging the dissemination of DApps across various industries. Additionally, the book bridges a crucial gap in the literature by providing in-depth insights into the role of consensus mechanisms in shaping the future of blockchain technology and decentralized applications. This book delves into the fundamentals of blockchain technology along with the roles and significance of vital consensus mechanisms, their underlying principles, formal specifications, functional characteristics, architecture, frameworks, and potential across diverse blockchain applications. Moreover, the book meticulously explores classification, performance metrics, and design parameters. It offers a comprehensive comparative analysis of these mechanisms, shedding light on their computational and communication complexity, strengths, weaknesses, and suitability. Additionally, the book delves into future research directions, highlighting emerging trends and areas requiring further investigation. It also addresses the efforts underway to address existing challenges and open issues within the realm of consensus mechanisms, ensuring a comprehensive understanding of the state-of-the-art in this pivotal aspect of blockchain technology. Due to the wide range of availability and evolving new consensus mechanisms, selecting an optimal and suitable consensus for a specific blockchain application is one of the crucial challenges in the development and innovation of blockchain systems. This book has also a discussion on appropriate selection algorithms based on multi-attribute decision-making for specific blockchain systems and DApps development.

  • Advances in Image Processing, Reliability, and Artificial Intelligence

    Data Centred-Techniques and Applications in Edge Computing
    • 1 Edición
    • Mario J. Divan + 4 más
    • Inglés
    Advances in Image Processing, Reliability, and Artificial Intelligence: Data Centred-Techniques and Applications in Edge Computing provides a clear outlook of the mechanisms, risks, challenges, and opportunities in system reliability for image processing and AI applications running on edge devices. It provides Best Known Configuration (BKC) and Methods (BKM) while discussing trends and future works based on current research. The content serves as a reference for practitioners and provides a state-of-the-art for researchers in the area. It provides foundations to analyse and replicate different applications through use cases. It tackles concerns for how reliability aspects (i.e., fault tolerance, availability, maturity, and recoverability) are addressed for applications running in an environment that is not fully controlled and exposed to environmental variations.

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