This book explores the dynamic intersection of three cutting-edge technologies—Artificial Intelligence (AI), Internet of Things (IoT), and Cloud Computing—and their profound impact on diverse domains. Beginning with an introduction to AI and its challenges, it delves into IoT applications in fields like transportation, industry 4.0, healthcare, and agriculture. The subsequent chapter explores AI in the cloud, covering areas such as banking, e-commerce, smart cities, healthcare, and robotics. Another section investigates the integration of AI and IoT-Cloud, discussing applications like smart meters, smart cities, smart agriculture, smart healthcare, and smart industry. Challenges like data privacy and security are examined, and the future direction of these technologies, including fog computing and quantum computing, is explored. The book concludes with use cases that highlight the real-world applications of these transformative technologies across various sectors. Each chapter is also supplemented with a list of scholarly references for advanced readers. The book is intended primarily as a resource for students in information technology and technology courses. And as a secondary resource for industry professionals who want to learn about these technologies in the context of digital transformation.

Artificial Intelligence (AI) is an interdisciplinary science with multiple approaches to solve a problem. Advancements in machine learning (ML) and deep learning are creating a paradigm shift in virtually every tech industry sector. This handbook provides a quick introduction to concepts in AI and ML. The sequence of the book contents has been set in a way to make it easy for students and teachers to understand relevant concepts with a practical orientation. This book starts with an introduction to AI/ML and its applications. Subsequent chapters cover predictions using ML, and focused information about AI/ML algorithms for different industries (health care, agriculture, autonomous driving, image classification and segmentation, SEO, smart gadgets and security). Each industry use-case demonstrates a specific aspect of AI/ML techniques that can be used to create pipelines for technical solutions such as data processing, object detection, classification and more. Additional features of the book include a summary and references in every chapter, and several full-color images to visualize concepts for easy understanding. It is an ideal handbook for both students and instructors in undergraduate level courses in artificial intelligence, data science, engineering and computer science who are required to understand AI/ML in a practical context.

This volume reviews cutting-edge innovations in blockchain technology that are propelling the healthcare industry into a new era of efficiency and security. It brings 14 reviews contributed by experts in blockchain and Web3 technologies into a single volume. Each contribution includes a summary for easy understanding and scientific references for advanced readers. Key Themes: Empowering Decentralized Healthcare: Learn about the future of decentralized healthcare, powered by blockchain, ensuring a seamless and patient-centric experience. Clinical Trials: Discover how blockchain is reshaping clinical trials, offering a glimpse into a future of optimized medical research. Data Security: Uncover the strategic use of blockchain in securing vital clinical trials data, ensuring confidentiality and integrity at every step. Blockchain-based Healthcare delivery: Delve into a comprehensive review of blockchain technology in the health sector, revealing its potential to transform healthcare systems with efficient and precise solutions. Predict, Prevent, and Protect: Understand how blockchain technology serves as a predictive tool, aiding in the prevention and control of the spread of COVID-19. This volume is a must-read for healthcare practitioners and administrators seeking to harness the power of blockchain in medicine and healthcare. It also provides information for researchers and business professionals who want to understand the innovative role of blockchain technology in the healthcare sector.

Basics of Python Programming: A Quick Guide for Beginners is an essential companion to mastering the Python programming language. The book presents information about Python in 12 structured chapters with a strong emphasis on fundamentals and practical information. Starting with basic operators, functions and expressions, contents explain file handling, exception handling and modules. The book concludes with advanced topics such as object oriented programming and machine learning. Key Features: Fundamental Focus: Covers the core concepts of Python programming to build a strong foundation in python programming in an easy-to-understand format. Practical Demonstrations: Learn by doing. This textbook includes hands-on practical demonstrations that reinforce your understanding of Python concepts. IDE Guidance: Includes programming and installation guidance for Python-supporting Integrated Development Environments (IDEs). Explores Python Frameworks: Introduces Python frameworks such as Matplotlib, TensorFlow, PyTorch, Scikit-Learn, and NLTK for complex projects. Python for Machine Learning: Gives a preliminary understanding of Python for machine learning tasks for data science and AI applications. Basics of Python Programming: A Quick Guide for Beginners is the perfect starting point for aspiring students, programmers and tech enthusiasts. Whether you're a student looking to build a solid foundation in Python or an industry professional venturing into machine learning and artificial intelligence, this textbook has you covered.

This book deals with the methods of theoretical and experimental research of antennas, which are based on the electromagnetic (EM) theory. The theory of thin antennas explains antenna analysis, as thin antennas represent one of the main types of radiators and are extensively applied as both independent antennas and as elements of more complicated antennas.

The contents of the book cover new methods of antenna analysis and design, including the theory of electrically coupled lines, the methods of complex potential, compensation, impedance line, and mathematical programming among others. New results from these experiments are also detailed. The complex potential method is generalized to inhomogeneous media and is employed in conical and parabolic problems. The theory of electrically coupled lines allows considering theoretical problems of multi-conductor cables and multi-radiator antennas. The compensation method permits creating a weak field area in the near region of a transmitting antenna. The method of impedance line is applied to antennas with loads, and the method of mathematical programming deals with selecting loads to develop antennas with the required characteristics.

The methods described within this text enable engineers to calculate parameters for new types of antennas, particularly, the self-complementary antennas. In the general case, similar properties pertain to the three-dimensional self-complementary antennas, their variants are also considered in the book. Close attention is also paid to the field compensation in the near region of a transmitting antenna and to the creation of the ‘dark spot’.

The book is an essential reference for graduates and researchers requiring knowledge on the design and engineering of new antennas as well as the underlying electromagnetic and mathematical principles.