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Elsevier

Libros en Ciencias de la Computación

  • Data Science, Interactive Visualizations, and Generative AI Tools for the Analysis of Qualitative, Mixed-Methods, and Multimodal Evidence

    • 1 Edición
    • Manuel González Canché
    • Inglés
    Too many qualitative and mixed-methods researchers are currently being asked to make an impossible choice: either remain outside the world of advanced data science and artificial intelligence, or enter it by learning programming, relying on expensive proprietary platforms, and uploading sensitive data to external servers. This book begins from a different premise: researchers should not have to choose between rigor, accessibility, privacy, and interpretive depth. Data Science, Interactive Visualizations, and Generative AI Tools for the Analysis of Qualitative, Mixed-Methods, and Multimodal Evidence presents an integrated methodological ecosystem for ethical and equity-driven data science in qualitative and mixed-methods research. It is designed for scholars working with textual, relational, temporal, affective, spatial, visual, and multimodal evidence who want access to rigorous data science and AI-supported analytic tools without needing to master programming, pay recurring fees, or surrender control of sensitive materials.The book introduces a fully local, no-code ecosystem of software tools for analyzing complex evidence across multiple layers of inquiry—from language and structure to time, emotion, interaction, and context. Special attention is given to ISARI (Intelligent Systems for Academic Research Integration), a fully offline, open-source, multimodal brainstorming partner designed to support scholarly memoing, comparison, synthesis, and evidence-grounded writing. ISARI is presented not as a substitute for interpretation, but as part of a broader local analytic environment in which computational outputs remain accountable to researchers’ judgment and to participants’ original evidence.This is not a book about replacing researchers with AI. It is a book about giving researchers ethical, privacy-conscious, and equity-driven access to advanced analytic tools that have too often remained restricted to those with programming expertise or privileged institutional support. By bringing together interactive visualizations, machine learning, natural language processing, geocontextualization... temporal analysis, relational modeling, and local generative AI, this book offers a practical and forward-looking vision for doing rigorous research without compromising transparency, scholarly control, or data sovereignty. It is intended for researchers, faculty, graduate students, institutional analysts, and interdisciplinary scholars interested in expanding their analytic toolkit while preserving methodological accountability and interpretive authority.

  • Integrated Photonics for Sensing Applications

    • 1 Edición
    • Anu Agarwal + 2 más
    • Inglés
    Integrated Photonics for Sensing Applications introduces sensors as an important application area for integrated photonics. It provides a brief historical perspective and highlights key free-space spectroscopic sensing techniques such as FTIR, Raman, SPR, and reflectometry, and it thoroughly explores the advantages of photonic integrated circuit (PIC) sensor systems, which have the potential for low SWAP-C and high performance.The topics covered include sensor system components such as waveguides (for optical wavelengths less than and greater than 1550 nm), ring resonators and toroids, photonic crystals, MZ interferometers, light input and output, light sources (wavelengths less than and greater than 1550 nm), and spectrometers and detectors. The book considers integrated systems that employ biofunctionalization... for applications in chem–bio sensing, and it also addresses sensor manufacturing at scale, including materials, PDK development, and sensor packaging.

  • Intelligent Cyber-Physical Systems for Sustainable Healthcare

    • 1 Edición
    • Vandana Bajaj + 5 más
    • Inglés
    Intelligent Cyber-Physical Systems for Sustainable Healthcare addresses the integration of emerging technologies like Virtual Reality, Smart Robotics, and Human-Computer Interaction, which are crucial for maximizing digital health's potential. The book includes case studies that highlight challenges faced by medical practitioners and industry professionals, providing valuable insights for designing sustainable iCPS solutions. Aimed at biomedical engineers, researchers, and industry professionals, it offers guidance for developing practical applications in sustainable healthcare. Additionally, shared, cross-disciplinary experiences assist engineers with less clinical expertise in enhancing healthcare applications in the intelligent digital health sector. Overall, case studies illustrate past challenges in the healthcare industry and present effective solutions to overcome them, making the book a comprehensive resource for advancing sustainable healthcare practices.

  • Digital Twins

    Core Principles and AI Integration
    • 1 Edición
    • Bedir Tekinerdogan + 1 más
    • Inglés
    Digital Twins: Core Principles, System Engineering, and AI Integration provides a comprehensive overview of digital twin technology, a cutting-edge innovation that bridges the physical and digital worlds. The book addresses common challenges such as data integration, security, scalability, and the alignment of digital twin models with actual physical processes. After presenting core concepts of digital twins for software engineering, the book discusses integration with advanced digital solutions such as AI, IoT, Cloud computing, Big Data Analytics, and Extended Reality (XR). Next, the authors provide readers with a thorough presentation of digital twins' applications in a variety of settings and industry/research topics.Finally, the book concludes with a discussion of challenges and solutions, along with future trends in digital twins research and development. As digital twin technology evolves, its integration with various advanced digital solutions is becoming essential for achieving real-time insights and autonomous decision-making. Challenges include understanding the interoperability of these technologies, managing data complexity, ensuring security, and optimizing for low-latency environments.

  • Understanding Models Developed with AI

    Including Applications with Python and MATLAB Code
    • 1 Edición
    • Ömer Faruk Ertuğrul + 2 más
    • Inglés
    Understanding Models Developed by AI: Including Applications with Python and MATLAB Code is a comprehensive guide on the intricacies of AI models and their real-world applications. The book demystifies complex AI methodologies by providing clear explanations and practical examples that are reinforced with Python and MATLAB program codes. Its content structure emphasizes a practical, applications-driven approach to understanding AI models, with hands-on coding examples throughout each chapter. Readers will find the tools they need to build AI models, along with the knowledge to make these models accessible and interpretable to stakeholders, thus fostering trust and reliability in AI systems.As the primary issues with the adoption of AI/ML models are reliability, transparency, interpretation of results, and bias (data and algorithm) management, this resource give researchers and developers what they need to be able to not only implement AI models, but also interpret and explain them. This is crucial in industries where decision-making processes must be transparent and understandable.

  • Foundations of Digital Twins

    • 1 Edición
    • Tuan Anh Nguyen + 2 más
    • Inglés
    Foundations of Digital Twins explains the fundamentals of digital twins, how digital twin technologies can gather real world data using the sensor networks that comprise the Internet of Things, and how that data can be sorted, analyzed, and used to improve services and increase sustainability. Structured in five sections, the book begins with an introductory overview of each technology, establishing a clear understanding of their individual roles and their potential when combined. The second section delves into data acquisition, featuring advanced sensors, drones, robots and actuators. Part Three considers data exchange and security, focusing on CPS, the internet of things, and blockchain.Part Four looks at how digital twins can impact on data computing, such as video streaming, cloud computing, fog computing and edge-computing. The final section explores the future opportunities and risks of adopting advanced technologies in this evolving field, including artificial intelligence, the ethical issues concerned when collecting and using data, and the security implications.

  • AI and Computational Intelligence for Environmental Sustainability

    • 1 Edición
    • Rakesh Kumar + 2 más
    • Inglés
    Climate change, biodiversity loss, resource depletion, and pollution are intensifying. Addressing these global issues requires fresh perspectives and cutting-edge solutions that integrate AI with environmental sustainability. AI and computational intelligence technologies are evolving at an unprecedented pace, offering new tools and methodologies for tackling environmental challenges. Yet existing resources often fail to capture the latest breakthroughs and interdisciplinary approaches needed to harness these innovations effectively.AI and Computational Intelligence for Environmental Sustainability showcases the potential of artificial intelligence and computational intelligence in tackling critical environmental challenges. As the urgency to combat climate change, optimize resource utilization, and promote sustainable practices grows, this book provides a comprehensive resource that bridges the gap between AI research and its practical applications in environmental sustainability, and offers insights into the latest developments and methodologies. It highlights real-world applications and case studies to inspire researchers, developers, and policymakers to create and implement AI-driven solutions for a more sustainable future, foster collaboration by bringing together experts from diverse fields to share knowledge and foster interdisciplinary collaboration in the pursuit of environmental sustainability. It also addresses the ethical and practical challenges of applying AI in sustainability, advocating for responsible AI development and low-energy computing practices.

  • GeoAI for Earth Observation Imagery

    Fundamentals and Practical Applications
    • 1 Edición
    • Dalton Lunga + 1 más
    • Inglés
    GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications comprehensively covers methodologies of AI and Machine Learning applications of image processing for Earth Observation (EO) Imagery. As traditional image processing methods face challenges with handling vast volumes of EO imagery, leading to efficiencies and limitations when extracting meaningful insights, AI-driven approaches can enhance the efficiency, accuracy, and scalability of image processing. Chapters cover essential methodologies including atmospheric compensation, image enhancement techniques like deblurring and superresolution, and advanced analysis methods such as semantic segmentation and object detection.Cutting-ed... approaches to computing, automating, and optimizing image processing tasks are also covered. Additionally, emerging trends in GeoAi and their implication on future research are reviewed. The book serves as an essential guide for navigating the complexities of spatial data and equips readers with knowledge to enhance their analytical capabilities.

  • Federated Learning

    Foundations and Applications
    • 1 Edición
    • Rajkumar Buyya + 2 más
    • Inglés
    Federated Learning: Foundations and Applications provides a comprehensive guide to the foundations, architectures, systems, security, privacy, and applications of federated learning. Sections cover fundamental concepts, including machine learning, deep learning, centralized learning, and distributed learning processes. The book then progresses to coverage of the architectures, algorithms, and system models of Federated Learning, as well as security, privacy, and energy-efficiency techniques. Finally, the book presents various applications of Federated Learning through real-world case studies, illustrating both centralized and decentralized Federated Learning.Federated Learning has become an increasingly important machine learning technique because it introduces local data analysis within clients and requires exchange of only model parameters between clients and servers, hence the addition of this new release is ideal for those interested in the topics presented.

  • Digital Outcasts

    Moving Technology Forward without Leaving People Behind
    • 2 Edición
    • Kel Smith
    • Inglés
    Digital Outcasts: Moving Technology Forward without Leaving People Behind, Second Edition comprehensively explores inclusive design in human-computer interaction. The book examines the real-life experiences of people with disabilities as they navigate systemic barriers in employment, education, healthcare, and social connectivity. This new edition covers the intersectionality of disability with other forms of economic and political discrimination, uncovering how biases related to race, gender, and ability are reflected in language models and AI algorithms. With digital access a foundational element of human existence, the consequences of exclusion are far-reaching and increasingly urgent.Citing case studies in law, creative arts, and social science, this updated edition also examines the historical and emergent impact people with disabilities have on culture and industry. Digital Outcasts emphases that disability has long served as a powerful catalyst for design innovation, driving transformational benefit for consumers of all abilities and backgrounds. Taking into account new legal and technological perspectives, this revision stands as an update on the progress we have made—and how far we have yet to go.

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