Python Fast Track: A Complete Guide to Rapidly Mastering and Applying Python Programming adopts a simplified writing style and provides clear explanations to ensure ease of understanding, making it an ideal resource for those new to Python. Starting with the basics, the book covers fundamental concepts such as variables, data types, printing and prompting, lists, dictionaries, tuples, control structure, functions, and object-oriented concepts. The book includes everything you need to understand and apply more advanced programming techniques such as file handling, exception handling, and regex.This great resource is created especially for those who want to apply Python for their research and professional work in scientific computing, data analysis and machine learning, including chapters on NumPy and Pandas, two of the most popular Python application libraries. It demonstrates how to effectively master key applications of Python such as web development, software creation, task automation, and data analysis. The book covers data analysis and machine learning tasks that greatly benefit from Python, thanks to libraries such as TensorFlow and Keras that enable efficient coding.
Quantum Computing: Principles and Paradigms covers a broad range of topics, providing a state-of-the-art and comprehensive reference for the rapid progress in the field of quantum computing and related technologies from major international companies (such as IBM, Google, Intel, Rigetti, Q-Control) and academic researchers. This book appeals to a broad readership, as it covers comprehensive topics in the field of quantum computing, including hardware, software, algorithms, and applications, with chapters written by both academic researchers and industry developers.This book presents readers with the fundamental concepts of quantum computing research, along with the challenges involved in developing practical devices and applications.
Advances in Computers, Volume 139 focuses on the convergence of Artificial Intelligence (AI) and 6G communication networks, addressing key advancements and implications across various fields. It explores cybersecurity challenges in 5G networks, solutions for 5G performance evaluation, and the transition to 5G-Advanced. The role of AI in enhancing 6G network performance, resource allocation, and management is discussed alongside the technical foundations of 6G and its ability to power edge AI applications. The volume highlights how 6G will transform industries like logistics through automation and AI-driven decision-making, while also covering strategic management perspectives on AI-driven innovations. Sustainability is a key theme, with discussions on energy-efficient cloud and quantum data centers, as well as the integration of green innovations into AI-6G synergy. The metaverse and its reliance on 5G and 6G for immersive experiences are reviewed, alongside the revolutionary potential of quantum computing in 6G networks. The practical applications of AI, such as a CNN-based model for brain tumor detection using 5G edge cloud, and federated learning for 6G, demonstrate the technology's impact on healthcare and data privacy. Additionally, the volume delves into 6G’s role in enabling next-generation metaverse systems and AI-powered telemedicine, while providing insights into the architecture, communication systems, and industrial use cases of 6G. It concludes by summarizing the advancements, advantages, and challenges of 6G, offering a comprehensive view of its future impact on global connectivity.
To write effective code and applications, software engineers and developers have to be able to frame user/customer needs effectively, capture program requirements and use cases, and then develop suitable software architecture and code to meet the need. Code Chronicles: The Art of Storytelling in Software helps readers write better software by teaching readers how to write stories in the context of software development. The book explains the roots of storytelling, clarifies that storytelling historically has been a very powerful tool used to pass along knowledge, presents where storytelling is already present implicitly in software development, discusses how to make it more effective, and finally present experiences in storytelling from software engineering and other scientific disciplines, to foster a full understanding of its power. The authors comprehensively present the pivotal role of storytelling in writing software, and they explain how to do it in a simple, hands-on approach, also taking advantage of clear case studies written by experts in the field.
Programming Language Pragmatics is the most comprehensive programming language textbook available today, with nearly 1000 pages of content in the book, plus hundreds more pages of reference materials and ancillaries online. Michael Scott takes theperspective that language design and language implementation are tightly interconnected, and that neither can be fully understood in isolation. In an approachable, readable style, he discusses more than 50 languages in the context of understanding how code isinterpreted or compiled, providing an organizational framework for learning new languages, regardless of platform. This edition has been thoroughly updated to cover the most recent developments in programming language design and provides both a solid understanding of the most important issues driving software development today
Soft Computing in Smart Manufacturing and Materials explains the role of soft computing in the manufacturing industries. It presents the techniques, concepts and design principles behind smart soft computing, and describes how they can be applied in the development and manufacture of smart materials. It provides perspectives for design and commissioning of intelligent applications, including in health care, agriculture, and production assembly, and reviews the latest intelligent technologies and algorithms related to the methodologies of monitoring and mitigation of sustainable engineering.
Probability for Deep Learning Quantum provides readers with the first book to address probabilistic methods in the deep learning environment and the quantum technological area simultaneously, by using a common platform: the Many-Sorted Algebra (MSA) view. While machine learning is created with a foundation of probability, probability is at the heart of quantum physics as well. It is the cornerstone in quantum applications. These applications include quantum measuring, quantum information theory, quantum communication theory, quantum sensing, quantum signal processing, quantum computing, quantum cryptography, and quantum machine learning. Although some of the probabilistic methods differ in machine learning disciplines from those in the quantum technologies, many techniques are very similar.Probability is introduced in the text rigorously, in Komogorov’s vision. It is however, slightly modified by developing the theory in a Many-Sorted Algebra setting. This algebraic construct is also used in showing the shared structures underlying much of both machine learning and quantum theory. Both deep learning and quantum technologies have several probabilistic and stochastic methods in common. These methods are described and illustrated using numerous examples within the text. Concepts in entropy are provided from a Shannon as well as a von-Neumann view. Singular value decomposition is applied in machine learning as a basic tool and presented in the Schmidt decomposition. Besides the in-common methods, Born’s rule as well as positive operator valued measures are described and illustrated, along with quasi-probabilities. Author Charles R. Giardina provides clear and concise explanations, accompanied by insightful and thought-provoking visualizations, to deepen your understanding and enable you to apply the concepts to real-world scenarios.
Antivirus Engines: From Methods to Innovations, Design, and Applications offers an in-depth exploration of the core techniques employed in modern antivirus software. It provides a thorough technical analysis of detection methods, algorithms, and integration strategies essential for the development and enhancement of antivirus solutions. The examples provided are written in Python, showcasing foundational, native implementations of key concepts, allowing readers to gain practical experience with the underlying mechanisms of antivirus technology.The text covers a wide array of scanning techniques, including heuristic and smart scanners, hexadecimal inspection, and cryptographic hash functions such as MD5 and SHA for file integrity verification. These implementations highlight the crucial role of various scanning engines, from signature-based detection to more advanced models like behavioral analysis and heuristic algorithms. Each chapter provides clear technical examples, demonstrating the integration of modules and methods required for a comprehensive antivirus system, addressing both common and evolving threats.Beyond simple virus detection, the content illustrates how polymorphic malware, ransomware, and state-sponsored attacks are tackled using multi-layered approaches. Through these examples, students, researchers, and security professionals gain practical insight into the operation of antivirus engines, enhancing their ability to design or improve security solutions in a rapidly changing threat environment.
Performance Computing: Modern Systems and Practices is a fully comprehensive and easily accessible treatment of high performance computing, covering fundamental concepts and essential knowledge while also providing key skills training. With this book, students will begin their careers with an understanding of possible directions for future research and development in HPC, domain scientists will learn how to use supercomputers as a key tool in their quest for new knowledge, and practicing engineers will discover how supercomputers can employ HPC systems and methods to the design and simulation of innovative products.This new edition has been fully updated, and has been reorganized and restructured to improve accessibility for undergraduate students while also adding trending content such as machine learning and a new chapter on CUDA.
Truly Concurrent Process Algebra with Localities introduces localities into truly concurrent process algebras. The book explores all aspects of localities in truly concurrent process algebras, such as Calculus for True Concurrency (CTC), which is a generalization of CCS for true concurrency, Algebra of Parallelism for True Concurrency (APTC), which is a generalization of ACP for true concurrency, and Î Calculus for True Concurrency (Î ). Together, these approaches capture the so-called true concurrency based on truly concurrent bisimilarities, such as pomset bisimilarity, step bisimilarity, history-preserving (hp-) bisimilarity and hereditary history-preserving (hhp-) bisimilarity.This book provides readers with all aspects of algebraic theory for localities, including the basis of semantics, calculi for static localities, axiomatization for static localities, as well as calculi for dynamic localities and axiomatization for dynamic localities.