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Ramanathan Shriram: Introduction to
Neuromorphic Computing

Introduction to Neuromorphic Computing

Quantum Computing and Machine Learning for 6G

This practical introduction to the field focuses on the design, architecture, and operation of technologies based on organic compounds and conjugating molecules. It shows the reader how material structure relates to semiconducting properties, and then explores in detail the electronic devices that harness their unique properties. The author also extends the discussion to printed electronics, covering large-area, low-cost film deposition, patterning, processing, and encapsulation. The reader will gain a deep understanding of how the devices work and how the applications are designed and operate.

Science, Technology, Devices and Applications

Organic and Hybrid Electronics

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

Using SAS Enterprise Miner

Data Science and Machine Learning for Non-Programmers

This book covers a broad range of questions related to the importance of cell geometry in many areas, including nuclear positioning, chromosome dynamics, cytoskeletal remodeling, tissue patterning, cell-matrix and multicellular contacts. It also addresses medical implications, from its implication in the development of tumors to its role in fibrosis. Together, the chapters in this book will highlight current knowledge and modern approaches to investigating the biophysical design principles underlying key biological functions, with the overall goal of elucidating the connections between cell geometry and nuclear mechanics.

Cell Geometry

New Directions in Contemporary Art

The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual's capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.

AI Art, Machine Learning and the Stakes for Art Criticism

Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions-How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world.

Decoding Bias, Algorithms, and Trust

Minds, Machines, and Misinformation

Partial Discharge, Breakdown, Aging and Life Assessment in Electric Power Assets

Digital twins represent an emerging technology of immense potential across various industries. Their significance is particularly pronounced within Industry 4.0 and smart manufacturing paradigms, which strive to elevate efficiency and quality through seamless digital integration. By amassing and scrutinizing extensive data streams, digital twins empower data-centric decision-making-a pivotal asset in contemporary industry. Digital Twins of Advanced Materials Processing bridges the gap in comprehensive resources concerning advanced materials processing, a domain characterized by rapid evolution. It provides pragmatic remedies and real-world case studies, catering to tangible implementation needs. Moreover, digital twins hold the capacity to amplify efficiency and innovation within materials processing-a perspective deeply explored within this book, rendering it invaluable for professionals, researchers, and students alike. The prospects of employing digital twins in materials processing span diverse horizons: refining materials innovation, streamlining processes, enabling data-driven maintenance, enhancing product quality, and unearthing insights rooted in data. The book also undertakes the challenge of addressing key issues encompassing data amalgamation and integrity, model validation and calibration, software and data safeguarding, scalability, and cost considerations.

Digital Twins of Advanced Materials Processing

Intelligent Manufacturing and Industrial Engineering

Smart Industries in the Gig Economy: Scope, Opportunities, and Challenges discusses topics from manufacturing to service sectors, from startups to established corporations, and from localized operations to global networks using the threads of Smart Industries and the Gig Economy to weave a tapestry of innovation and change.

Scope, Opportunities, and Challenges

Smart Industries in the Gig Economy

Autonomous Cyber Resilience

Radiography, or X-ray imaging, is not only the first medical imaging modality but continues to be the most commonly used. This book provides complete coverage of the fundamentals, from technology to image acquisition, storage, display, analysis, and quality assurance methods to applications for improved disease detection and diagnosis. It is written for anyone looking for a comprehensive, accessible treatment of the basic physics and technology, radiological principles, imaging methodologies, applications, and their impact on the clinical practice of radiography.

Technology, Imaging, and Applications

Digital Radiography

Wind Energy Engineering

Artificial Intelligence of Things for Wind Energy Systems covers the novel concept of Artificial Intelligence (AI) combined with Internet of Things (IoT), for efficient data acquisition, analytics, and automated control, in wind energy systems. The book begins by introducing Artificial Intelligence of Things (AIoT), technologies, challenges, and future directions. Subsequent chapters provide in-depth coverage of specific technical areas and their applications in wind forecasting, generation, energy management, anomaly detection, digital twins, inspection of generators, recommendation systems, security concerns, and microgrid monitoring and control. Throughout the book, the information presented is supported by visuals, case studies, simulations, and code. A Volume in the Elsevier Wind Energy Engineering Series, this is a valuable resource for researchers, graduate students, engineers, operators, and other industry personnel with an interest in the use of AI and IoT in wind energy production and integration.

Artificial Intelligence of Things for Wind Energy Systems

Introduction to Neuromorphic Computing

Informations bibliographiques

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