Название: Computational Intelligence and Blockchain in Biomedical and Health Informatics
Автор: Раnkаj Вhаmbri, Sitа Rаni, Мuhаmmаd Fаhim
Издательство: CRC Press
Год: 2024
Страниц: 361
Язык: английский
Формат: pdf (true)
Размер: 30.6 MB

Advancements in computational intelligence, which encompasses Artificial Intelligence, Machine Learning, and data analytics, have revolutionized the way we process and analyze biomedical and health data. These techniques offer novel approaches to understanding complex biological systems, improving disease diagnosis, optimizing treatment plans, and enhancing patient outcomes. Computational Intelligence and Blockchain in Biomedical and Health Informatics introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields and provides a framework and summary of the various methods. The book emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. Techniques to analyze the impacts on the biomedical and health Informatics domains are discussed along with major challenges in deployment. Rounding out the book are highlights of the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability along with two case studies. This book is highly beneficial to educators, researchers, and anyone involved with health data. Machine Learning, on the other hand, takes advantage of methods that allow computers to discover patterns and make predictions without being explicitly programmed to do so. Models are trained using labelled data in supervised learning, while unlabelled data is used in unsupervised learning. Decision trees, support vector machines, and neural networks are all examples of common Machine Learning methods.

Название: New Directions on Hybrid Intelligent Systems Based on Neural Networks, Fuzzy Logic, and Optimization Algorithms
Автор: Раtriсiа Меlin, Оsсаr Саstillо
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2024
Страниц: 204
Язык: английский
Формат: pdf (true), epub
Размер: 35.6 MB

We describe in this book new directions on the theoretical developments of fuzzy logic, neural networks, and meta-heuristic algorithms, as well as their hybrid combinations, and their application in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. There are papers with the main topics from type-1 to type-3 fuzzy logic, which basically consists of a group of papers that propose new concepts and algorithms based on type-1, type-2, and type-3 fuzzy logic and their applications. There are also papers that present the theory and practice of meta-heuristics in diverse application areas. There are interesting papers on different applications of fuzzy logic, neural networks, and hybrid intelligent systems in medical problems. In addition, we can find papers describing applications of fuzzy logic, neural networks, and meta-heuristics in robotics problems. Another set of papers presents the theory and practice of neural networks in diverse application areas, including convolutional and deep learning neural networks. There are also a group of papers that present the theory and practice of optimization and evolutionary algorithms in different areas of application. Finally, we can find a group of papers describing the applications of fuzzy logic, neural networks, and meta-heuristics in pattern recognition problems. In conclusion, the edited book comprises contributions on diverse aspects of fuzzy logic, neural networks, and optimization of meta-heuristic algorithms for designing optimal hybrid intelligent systems and their application in areas such as intelligent control and robotics, pattern recognition, decision-making, time series prediction, and optimization of complex problems.

Название: Artificial Intelligence-Based System for Gaze-Based Communication
Автор: B.G.D.А Маdhusаnkа, Surеswаrаn Rаmаdаss, Рrеmkumаr Rаjаgоpаl
Издательство: CRC Press
Год: 2024
Страниц: 173
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book focuses on the artificial neural network-based system for gaze-based communication. It covers the feasible and practical collaboration of human–computer interaction (HCI) in which a user can intuitively express tasks using gaze-based communication. It will target the vast applications of gaze-based communication using computer vision, image processing, and Artificial Intelligence. Artificial Intelligence-Based System for Gaze-Based Communication introduces a novel method to recognize the implicit intention of users by using nonverbal communication in combination with computer vision technologies. A novel HCI framework is developed to enable implicit and intuitive gaze-based intention communications. This framework allows the users to intuitively express their intention using natural gaze cues. The book also focuses on robot caregiving technology, which can understand the user’s intentions using minimal interactions with the user. The authors examine gaze-based tracking applications for the assisted living of elderly people. The book examines detailed applications of eye-gaze communication for real-life problems. It also examines the advantages that most people can handle gaze-based communications because it requires very little effort, and most of the elderly and impaired can retain visual capability. This book is ideally designed for students, researchers, academicians, and professionals interested in exploring and implementing gaze-based communication strategies and those working in the field of Computer Vision and image processing.

Название: Deep Learning in Internet of Things for Next Generation Healthcare
Автор: Lаvаnуа Shаrmа, Рrаdеер Кumаr Gаrg
Издательство: CRC Press
Год: 2024
Страниц: 311
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book presents the latest developments in Deep Learning-enabled healthcare tools and technologies and offers practical ideas for using the IoT with Deep Learning (motion-based object data) to deal with human dynamics and challenges including critical application domains, technologies, medical imaging, drug discovery, insurance fraud detection and solutions to handle relevant challenges. This book covers real-time healthcare applications, novel solutions, current open challenges, and the future of Deep Learning for next-generation healthcare. It includes detailed analysis of the utilization of the IoT with Deep Learning and its underlying technologies in critical application areas of emergency departments such as drug discovery, medical imaging, fraud detection, and genomes. Convolutional neural networks (CNNs), in particular, are excellent at extracting hierarchical characteristics from images using Deep Learning models. These models learn to recognize edges, textures, forms, and even intricate patterns inside images in the context of human vision. CNNs may automatically identify pertinent features for IoT applications from unprocessed visual data without the need for explicit feature engineering. The classifcation and recognition of objects is one of the most important uses of Deep Learning and human vision in IoT. Deep Learning models can be taught to identify and categorize objects in frames of pictures or videos. Security (intruder detection), retail (product identifcation), healthcare (medical image analysis), and other felds all make use of these capabilities. Postgraduate students and researchers in the departments of Computer Science, working in the areas of the IoT, Deep Learning, Machine Learning, image processing, Big Data, cloud computing, and remote sensing will find this book useful.

Название: Data Storytelling with Generative AI: using Python and Altair (MEAP v5)
Автор: Аngеliса Lо Duса
Издательство: Manning Publications
Год: 2024
Страниц: 425
Язык: английский
Формат: pdf, epub
Размер: 46.5 MB

Great data presentations tell a story. Learn how to organize, visualize, and present data using Python, generative AI, and the cutting-edge Altair data analysis toolkit. Data Storytelling with Python Altair and Generative AI teaches you how to turn raw data into effective, insightful data stories. You’ll learn exactly what goes into an effective data story, then combine your Python data skills with the Altair library and AI tools to rapidly create amazing visualizations. Your bosses and decision-makers will love your new presentations—and you’ll love how quick Generative AI makes the whole process! Python is the second ingredient of this book. As a data journalism professor, I have experimented with many Python libraries for data visualization, such as Matplotlib, Plotly, and Seaborn. However, at the end of my experiments, I realized that the simplest library for data visualization is Altair. Unlike other libraries, Altair is declarative, thus enabling you only to focus on the output of your data visualization. Thus, this book will focus on Altair to build data visualization. Although you can find many materials on the web about Altair, they focus only on how to build raw charts. In this book, you’ll learn how to build data stories with Altair and not simply raw charts. Last but not least, you’ll learn how to use Generative AI tools for data storytelling. This book won’t focus on Generative AI concepts and theory. Instead, you will learn how to apply Generative AI tools, including GitHub Copilot, ChatGPT, and DALL-E, to data storytelling.

Название: Data-Centric Artificial Intelligence for Multidisciplinary Applications
Автор: Раrikshit N. Маhаllе, Nаmrаtа N. Wаsаtkаr, Gitаnjаli R. Shindе
Издательство: CRC Press
Год: 2024
Страниц: 309
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB

This book explores the need for a Data-Centric Artificial Intelligence (AI) approach and its application in the multidisciplinary domain, compared to a model‑centric approach. It examines the methodologies for data‑centric approaches, the use of data‑centric approaches in different domains, the need for edge AI and how it differs from cloud‑based AI. It discusses the new category of AI technology, "data‑centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding Machine Learning and Big Data analytics tools, data‑centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods. Data-Centric Artificial Intelligence (AI) denotes an approach within AI and Machine Learning (ML) that places significant emphasis on the pivotal role of meticulously curated, high‑quality data in the development and implementation of AI models and systems. Under this paradigm, data assumes the bedrock upon which AI algorithms are constructed and honed, and its effective handling, preprocessing, and analysis stand as pivotal factors for achieving precise and dependable AI outcomes.

Название: AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications
Автор: Sitа Rаni, Раnkаj Вhаmbri, Sасhin Кumаr
Издательство: CRC Press
Год: 2024
Страниц: 339
Язык: английский
Формат: pdf (true)
Размер: 22.0 MB

AI-Driven Digital Twin and Industry 4.0: A Conceptual Framework with Applications introduces the role of Digital Twin in Smart Manufacturing and focuses on the Digital Twin framework throughout. It provides a summary of the various AI applications in the Industry 4.0 environment and emphasizes the role of advanced computational and communication technologies. The book offers demonstrative examples of AI-Driven Digital Twin in various application domains and includes AI techniques used to analyze the environmental impact of industrial operations along with examples. The book reviews the major challenges in the deployment of AI-Driven Digital Twin in the Industry 4.0 ecosystem and presents an understanding of how AI is used in the designing of Digital Twin for various applications. This literary work delves into the revolutionary convergence of Artificial Intelligence (AI), Digital Twins, and Industry 4.0, providing a detailed examination of the theoretical underpinnings and practical implementations within this swiftly advancing domain. Artificial Intelligence (AI), Machine Learning, Deep Learning, Internet of Things (IoT), Cloud Computing, Digital Twin, and the most recent connectivity services are the most prominent of the era’s cutting-edge technologies that are assisting users intelligently and predicting their behavior, as well as providing the connectivity and convenience of data to satisfy the majority of their needs. The target audience of this book encompasses a broad spectrum, ranging from scholars and learners to practitioners and experts in the fields of research, education, engineering, and industry. The book aims to provide comprehensive insights into the interplay between AI, digital twins, and the Fourth Industrial Revolution, also known as Industry 4.0.

Название: Handbook of Digital Twins
Автор: Zhihаn Lуu
Издательство: CRC Press
Год: 2024
Страниц: 923
Язык: английский
Формат: pdf (true)
Размер: 13.5 MB

Over the last two decades, Digital Twins (DTs) have become the intelligent representation of future development in industrial production and daily life. Consisting of over 50 chapters by more than 100 contributors, this comprehensive handbook explains the concept, architecture, design specification and application scenarios of DTs. As a virtual model of a process, product or service to pair the virtual and physical worlds, DTs allow data analysis and system monitoring by using simulations. The fast-growing technology has been widely studied and developed in recent years. Featured with centralization, integrity and dynamics, it is cost-effective to drive innovation and performance. Many fields saw the adaptation and implementation across industrial production, healthcare, smart city, transportation and logistics. World-famous enterprises such as Siemens, Tesla, ANSYS and General Electric have built smart factories and pioneered digital production, heading towards Industry 4.0. The Cognitive Digital Twins (CDT) for manufacturing systems was proposed based on advances in cognitive science, Artificial Intelligence (AI) technologies, and Machine Learning techniques. According to the fundamental aspects of cognition, they define CDT as a DT with additional cognitive capabilities, including perception, attention, memory, reasoning, problem‑solving and learning. Recall that a Digital Twin (DT) is a virtual copy of a physical asset that promptly reproduces and alters the state and behavior of the asset. DT intensely employs Industry 4.0 data‑driven Artificial Intelligence technologies and simulations for adaptive monitoring, forecasting, optimization, and controlling asset performance.

Название: Math and Architectures of Deep Learning (Final Release)
Автор: Кrishnеndu Сhаudhurу
Издательство: Manning Publications
Год: 2024
Страниц: 553
Язык: английский
Формат: pdf (true)
Размер: 75.9 MB

Shine a spotlight into the Deep Learning "black box". This comprehensive and detailed guide reveals the mathematical and architectural concepts behind Deep Learning models, so you can customize, maintain, and explain them more effectively. Deep Learning can’t be learned by going through a small fragmented set of simplified recipes from which all math has been scrubbed out. This is a mathematical topic and mastery requires understanding the math along with the programming. What is needed is a resource which presents this topic with the requisite amount of math—no more and no less—with the connection between the Deep Learning and math explicitly spelled out. This is exactly what this book strives to provide with its dual presentation of the math and corresponding PyTorch code snippets. Readers need to know Python and the basics of algebra and calculus.

Название: AI in Material Science: Revolutionizing Construction in the Age of Industry 4.0
Автор: Sуеd Sааd, Sуеd Аmmаd, Кumееl Rаshееd
Издательство: CRC Press
Год: 2025
Страниц: 289
Язык: английский
Формат: pdf (true)
Размер: 11.7 MB

This book explores the transformative impact of Artificial Intelligence (AI) on material science and construction practices in the Industry 4.0 landscape. It enquires into AI history and applications, examining material optimization, smart materials, and AI in construction. Covering automation, robotics, and AI-assisted design, the book provides insights into ethical considerations and future trends. A modern reference for scholars and professionals, it bridges academia and practical applications in the dynamic intersection of AI and materials science. As an academic exploration, this book navigates the ever-evolving landscape of Artificial Intelligence’s (AI) influence on modern materials within the Industry 4.0 era. The comprehensive nature of this work is rooted in the foundational principles and realistic applications of AI, focusing on its integration into material science and construction practices. Our collective goal in crafting this collection stems from a recognition of the widening breach between academic literature and industry-centric publications within the AI and materials science domain. AI has become an industry-wide revolutionary force in the context of Industry 4.0. The book presents a solid case for continuing the investigation of AI in the field of material science through this academic and professional introduction, opening the door for readers to learn about the revolutionary possibilities that lie at the intersection of AI and the construction industry. Learning about Artificial Intelligence, the fundamental concepts and tenets of AI are covered in this section. It examines the idea of AI, the distinctions between specific and general AI, and the many methods and algorithms used in systems that use AI. Readers can comprehend AI’s possible uses and consequences in the setting of material science by developing a solid comprehension of the technology. AI represents one of the most transformative and interesting fields in ultramodern technology and computer wisdom.