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Books in Software engineering

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    • Synthetic Media, Deepfakes, and Cyber Deception

      Attacks, Analysis, and Defenses
      • 1st Edition
      • Cameron H. Malin + 2 more
      • English
      Synthetic Media, Deepfakes, and Cyber Deception: Attacks, Analysis, and Defenses introduces the only analytical Synthetic Media Analysis Framework (SMAF) to help describe cyber threats and help security professionals anticipate and analyze attacks. This framework encompasses seven dimensions: Credibility, Control, Medium, Interactivity, Familiarity, Intended Target, and Evocation. Synthetic media is a broad term that encompasses the artificial manipulation, modification, and production of information, covering a spectrum from audio-video deepfakes to text-based chatbots. Synthetic media provides cyber attackers and scammers with a game-changing advantage over traditional ROSE attacks because they have the potential to convincingly impersonate close associates through text, imagery, voice, and video.This burgeoning threat has yet to be meaningfully addressed through any written treatment on the topic. The book is co-authored by three cyber influence and deception experts who have gained deep knowledge and experience on the topic through diverse, true operational pathways and backgrounds. The diversity and perspectives of the author team makes the content in the book the broadest and deepest treatment of synthetic media attacks available to readers.

    • AI, Blockchain and Social Network on Urban Crisis Management: Leveraging Emerging Technologies for Disaster Response and Resilience in Smart Cities

      • 1st Edition
      • Volume 142
      • English
      AI, Blockchain and Social Network on Urban Crisis Management, Volume 142 in the Advances in Computers series, examines how cutting-edge digital technologies are reshaping disaster preparedness and response. This volume highlights the convergence of artificial intelligence, blockchain, and social network analysis to predict, prevent, and manage urban crises. Chapters explore diverse applications, from AI-driven deforestation monitoring in the Colombian Amazon and diffusion modeling for enhanced oil recovery, to blockchain-based citizen voting systems, metaverse-enabled disaster management, and graph-theoretic approaches for resource mobilization. Ethical AI for law enforcement training, social media’s role in disaster resilience, and innovative methods such as YOLO-based pothole detection further showcase how these technologies support sustainable cities and green energy initiatives. Collectively, the volume provides a multidisciplinary perspective on building smarter, safer, and more resilient urban environments.

    • Cloud-native Architecture (CNA) and Artificial Intelligence (AI) for the Future of Software Engineering: The Principles, Patterns, Platforms and Practices

      • 1st Edition
      • Volume 141
      • English
      Cloud-native Architecture (CNA) and Artificial Intelligence (AI) for the Future of Software Engineering: The Principles, Patterns, Platforms and Practices, Volume 141 in the Advances in Computers series, explores the convergence of artificial intelligence, machine learning, and modern software engineering practices. Chapters in this new release include Demystifying the Cloud-native Artificial Intelligence (CNAI) Paradigm, Articulating Machine and Deep Learning Models for Next-Generation Software Development, Delineating Artificial Intelligence (AI) and Its Potentials for Automated Software Engineering, Leveraging Machine and Deep Learning (ML/DL) Algorithms towards AI Models for Automating Software Development, and more.Other sections cover Artificial Intelligence (AI) Technologies and Tools for Accelerated Software Development, Demystifying the Agentic AI Paradigm for Accelerated Software Engineering, Detailing AI Techniques and Tools for Software Engineering Acceleration and Automation, Generative AI Tools for Accelerated Software Engineering, Empowering Software Engineering Automation through Explainable AI, and much more.

    • Consensus

      Fueling Blockchain Innovation and DApp Expansion
      • 1st Edition
      • Ali Ahmadian + 3 more
      • English
      Consensus: Fueling Blockchain Innovation and DApp Expansion explores the complexities of consensus mechanisms in order to shed light on emerging trends, best practices, and real-world applications that can fuel blockchain innovation while encouraging the dissemination of DApps across various industries. Additionally, the book bridges a crucial gap in the literature by providing in-depth insights into the role of consensus mechanisms in shaping the future of blockchain technology and decentralized applications. This book delves into the fundamentals of blockchain technology along with the roles and significance of vital consensus mechanisms, their underlying principles, formal specifications, functional characteristics, architecture, frameworks, and potential across diverse blockchain applications. Moreover, the book meticulously explores classification, performance metrics, and design parameters. It offers a comprehensive comparative analysis of these mechanisms, shedding light on their computational and communication complexity, strengths, weaknesses, and suitability. Additionally, the book delves into future research directions, highlighting emerging trends and areas requiring further investigation. It also addresses the efforts underway to address existing challenges and open issues within the realm of consensus mechanisms, ensuring a comprehensive understanding of the state-of-the-art in this pivotal aspect of blockchain technology. Due to the wide range of availability and evolving new consensus mechanisms, selecting an optimal and suitable consensus for a specific blockchain application is one of the crucial challenges in the development and innovation of blockchain systems. This book has also a discussion on appropriate selection algorithms based on multi-attribute decision-making for specific blockchain systems and DApps development.

    • Quantum Computing

      Principles and Paradigms
      • 1st Edition
      • Rajkumar Buyya + 1 more
      • English
      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.

    • Python Fast Track

      A Complete Guide to Rapidly Mastering and Applying Python Programming
      • 1st Edition
      • Sanjiban Sekhar Roy + 2 more
      • English
      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.

    • The Convergence of Artificial Intelligence (AI) and 6G Communication Networks: The Needs and Implications

      • 1st Edition
      • Volume 139
      • English
      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.

    • Quantum Process Algebra

      • 1st Edition
      • Yong Wang
      • English
      Quantum Process Algebra introduces readers to the algebraic properties and laws for quantum computing. The book provides readers with all aspects of algebraic theory for quantum computing, including the basis of semantics and axiomatization for quantum computing. With the assumption of a quantum system, readers will learn to solve the modeling of the three main components in a quantum system: the unitary operator, quantum measurement, and quantum entanglement, with full support of quantum and classical computing in closed systems. Next, the book establishes the relationship between probabilistic quantum bisimilarity and classical probabilistic bisimilarity, including strong probabilistic bisimilarity and weak probabilistic bisimilarity, which makes an axiomatization of quantum processes possible. With this framework, quantum and classical computing mixed processes are unified with the same structured operational semantics. Finally, the book establishes a series of axiomatizations of quantum process algebras. These process algebras support nearly all the main computation properties. Quantum and classical computing in closed quantum systems are unified with the same equational logic and the same structured operational semantics under the framework of ACP-like probabilistic process algebra. This unification means that the mathematics in the book can be used widely for verification of quantum and classical computing mixed systems, for example, most quantum communication protocols. ACP-like axiomatization also inherits the advantages of ACP, for example, and modularity means that it can be extended in an elegant way.

    • Probability for Deep Learning Quantum

      A Many-Sorted Algebra View
      • 1st Edition
      • Charles R. Giardina
      • English
      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.

    • Soft Computing in Smart Manufacturing and Materials

      • 1st Edition
      • Sudan Jha + 4 more
      • English
      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.