Artificial Intelligence and Machine Learning in Smart City Planning shows the reader practical applications of AIML techniques and describes recent advancements in this area in various sectors. Owing to the multidisciplinary nature, this book primarily focuses on the concepts of AIML and its methodologies such as evolutionary techniques, neural networks, machine learning, deep learning, block chain technology, big data analytics, and image processing in the context of smart cities. The text also discusses possible solutions to different challenges posed by smart cities by presenting cutting edge AIML techniques using different methodologies, as well as future directions for those same techniques.

Integrated Human-Machine Intelligence: Beyond Artificial Intelligence focuses on deep situational awareness in human-computer integration, covering the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. The book also details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making to provide basic theoretical support for a development strategy in the field of national intelligence. Sections focus on describing a new form of intelligence produced by the interaction of human, machine and environmental systems which will become the next generation of AI. From the perspective of deep situational awareness in human-computer integration, the book studies the interaction and integration mechanisms of human intelligence, machine intelligence and environmental systems. In addition, it details the cognitive, philosophical, social, scientific and technological, and military theories and methods of human-computer division, cooperation and collaborative decision-making, so as to provide basic theoretical support for a development strategy in the field of national intelligence.

Algebraic Theory for True Concurrency presents readers with the algebraic laws for true concurrency. Parallelism and concurrency are two of the core concepts within computer science. This book covers the different realms of concurrency, which enables programs, algorithms or problems to be broken out into order-independent or partially ordered components to improve computation and execution speed. There are two primary approaches for executing concurrency: interleaving concurrency and true concurrency. The main representative of interleaving concurrency is bisimulation/rooted branching bisimulation equivalences which is also readily explored. This work eventually founded the comprehensive axiomatization modulo bisimulation equivalence -- ACP (Algebra of Communicating Processes).The other approach to concurrency is true concurrency. Research on true concurrency is active and includes many emerging applications. First, there are several truly concurrent bisimulation equivalences, including: pomset bisimulation equivalence, step bisimulation equivalence, history-preserving (hp-) bisimulation equivalence, and hereditary history-preserving (hhp-) bisimulation equivalence, the most well-known truly concurrent bisimulation equivalence.

Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications. Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis.

Statistical Modeling in Machine Learning: Concepts and Applications presents the basic concepts and roles of statistics, exploratory data analysis and machine learning. The various aspects of Machine Learning are discussed along with basics of statistics. Concepts are presented with simple examples and graphical representation for better understanding of techniques. This book takes a holistic approach - putting key concepts together with an in-depth treatise on multi-disciplinary applications of machine learning. New case studies and research problem statements are discussed, which will help researchers in their application areas based on the concepts of statistics and machine learning. Statistical Modeling in Machine Learning: Concepts and Applications will help statisticians, machine learning practitioners and programmers solving various tasks such as classification, regression, clustering, forecasting, recommending and more.

Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical prerequisites, and conceptual approaches to provide readers with a solid foundation. After presenting multi-objective optimization, constrained optimization, and problem formation for metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains. The book takes a much-needed holistic approach, putting the most widely used metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using metaheuristics. New case studies and research problem statements are also discussed, which will help researchers in their application of the concepts.

Handbook of HydroInformatics Volume III: Water Data Management Best Practices presents the latest and most updated data processing techniques that are fundamental to Water Science and Engineering disciplines. These include a wide range of the new methods that are used in hydro-modeling such as Atmospheric Teleconnection Pattern, CONUS-Scale Hydrologic Modeling, Copula Function, Decision Support System, Downscaling Methods, Dynamic System Modeling, Economic Impacts and Models, Geostatistics and Geospatial Frameworks, Hydrologic Similarity Indices, Hydropower/Renewable Energy Models, Sediment Transport Dynamics Advanced Models, Social Data Mining, and Wavelet Transforms. This volume is an example of true interdisciplinary work. The audience includes postgraduates and above interested in Water Science, Geotechnical Engineering, Soil Science, Civil Engineering, Chemical Engineering, Computer Engineering, Engineering, Applied Science, Earth and Geoscience, Atmospheric Science, Geography, Environment Science, Natural Resources, Mathematical Science, and Social Sciences. It is a fully comprehensive handbook which provides all the information needed related to the best practices for managing water data.

There has been an increased use of technology in educational settings since the start of the COVID-19 pandemic. Despite the benefits of including such technologies to support education, there is still the need for vigilance to counter the inherent risk that comes with the use of such technologies as the protection of students and their information is paramount to the effective deployment of any technology in education. Current Trends in Cybersecurity and Educational Technology explores the full spectrum of cybersecurity and educational technology today and brings awareness to the recent developments and use cases for emergent educational technology. Covering key topics such as artificial intelligence, gamification, robotics, and online learning, this premier reference source is ideal for computer scientists, industry professionals, policymakers, administrators, researchers, academicians, scholars, practitioners, instructors, and students.

Blockchain has potential to revolutionize how manufacturers design, engineer, make and scale their products. Blockchain is gradually proving to be an effective "middleware" solution for enabling seamless interoperability within complex supply chains. Due to its technological nature, blockchain enables secure, transparent and fast data exchanges as well as allowing for the creation of immutable records databases The main advantage of Blockchain in Manufacturing Industries is product traceability, supply chain transparency, compliance monitoring, and auditability. Moreover, leveraging blockchain technology into a manufacturing enterprise can enhance its security and reduce the rates of systematic failures. So, blockchain is now used in various sectors of the manufacturing industry, such as automotive, aerospace, defense, pharmaceutical, consumer electronics, textile, food and beverages, and more. Hence, Blockchain should be seen as an investment in future-readiness and customer-centricity, not as an experimental technology - because, the evidence is overwhelming. This book will explore the strengths of Blockchain adaptation in Manufacturing Industries and Logistics Management, cover different use cases of Blockchain Technology for Manufacturing Industries and Logistics Management, and will discuss the role, impact and challenges of adopting Blockchain in Manufacturing industries and Logistics Management. The chapters will also provide the current open issues and future research trends of Blockchain, especially for Manufacturing Industries and Logistics, and will encapsulate quantitative and qualitative research for a wide spectrum of readers of the book.

Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis.

Digital Manufacturing: The Industrialization of "Art to Part" 3D Additive Printing explains everything needed to understand how recent advances in materials science, manufacturing engineering and digital design have integrated to create exciting new capabilities. Sections discuss relevant fundamentals in mechanical engineering and materials science and complex and practical topics in additive manufacturing, such as part manufacturing, all in the context of the modern digital design environment. Being successful in today's "art to part" cyber-physical manufacturing age requires a strong grounding in science and engineering fundamentals as well as knowledge of the latest techniques, all of which readers will find here. Every chapter is developed by leading specialists and based on first-hand experiences, capturing the essential knowledge readers need to solve problems related to digital manufacturing.

Present the computer concepts and Microsoft (R) Office 2016 skills perfect for your Introduction to Computing course with ILLUSTRATED COMPUTER CONCEPTS AND MICROSOFT (R) OFFICE 365 & OFFICE 2016. This all-in-one book makes the computer concepts and skills your students need to know easily accessible. The user-friendly two-page spread found throughout this and other popular Illustrated Microsoft (R) Office 2016 books clearly demonstrates key application skills. Today's most up-to-date technology developments and concepts are clarified using the distinctive step-by-step approach and the latest content from COMPUTER CONCEPTS ILLUSTRATED BRIEF. This edition highlights new Office features with a new module covering Productivity Apps. You'll find a wealth of instructional support and resources, including MindTap customized learning paths to reinforce the important skills and theories found in ILLUSTRATED COMPUTER CONCEPTS AND MICROSOFT (R) OFFICE 365 & OFFICE 2016.

This insightful book provides a timely review of the potential threats of advertising technologies, or adtech. It highlights the need to protect internet users not only from privacy risks, but also as consumers and citizens online dealing with a highly complex technological setting. Jiahong Chen illustrates a concise overview of the technical, economic and legal aspects of adtech together with coverage of other important areas. These include: the ongoing debates around online advertising and data protection, an up-to-date analysis of the application of the GDPR, and insights into both the practices and theories of the regulation of data protection law. The book provides a clear picture of what is truly at stake with online advertising practices, concluding with a critical assessment of the current regime and a proposed approach to reform data protection laws. This book will provide essential reading for researchers and law students requiring an overview of the legal framework and current practices, alongside legal practitioners and policymakers evaluating the benefits and risks of data-driven technologies.

Contemporary Management of Metastatic Colorectal Cancer: A Precision Medicine Approach summarizes current knowledge and provides evidenced-based practice recommendations on how to treat patients with metastatic colorectal cancer. The book presents topics such as pre-operating imaging, the use of molecular markers in treatment decisions, neoadjuvant therapy, synchronous colorectal liver metastasis, and minimally invasive approaches. In addition, it discusses immunotherapy, targeted therapies and survivorship. This is a valuable resource for practitioners, cancer researchers, oncologists, graduate students and members of biomedical research who need to understand more about novel treatments for colorectal cancer metastasis.

Stunning advances in digital technology have given us a new wave of disarmingly human-like AI systems. Chatbots like ChatGPT, Claude and Gemini put the knowledge of all the world’s experts at our fingertips, and can generate meaningful sentences, equations and computer code. The march of this new technology is set to upturn our economies, challenge our democracies, and refashion society in unpredictable ways. We can expect these AI systems to soon be making autonomous decisions on the user’s behalf, with transformative impact on everything we do. It is vital we understand how they work. Can AI systems ‘think’, ‘know’ and ‘understand’? Could they manipulate or deceive you, and if so, what might they make you do? Whose interests do they ultimately represent? And when will they be able to move beyond words and take actions for themselves in the real world?

To answer these questions, neuroscientist and AI researcher Christopher Summerfield explains how these strange new minds work. He charts the evolution of AI, from the earliest inklings about thinking machines in the seventeenth century to today’s gargantuan deep neural networks. The resulting book is the most accessible, up-to-date and authoritative exploration of this radical new technology. Ultimately, armed with an understanding of AI’s mysterious inner workings, we can begin to grapple with the existential question of our age: can we look forward to a technological utopia, or are we in the process of writing ourselves out of history?

In today's digital society, organizations must utilize technology in order to engage their audiences. Innovative game-like experiences are an increasingly popular way for businesses to interact with their customers; however, correctly implementing this technology can be a difficult task. To ensure businesses have the appropriate information available to successfully utilize gamification in their daily activities, further study on the best practices and strategies for implementation is required. The Handbook of Research on Gamification Dynamics and User Experience Design considers the importance of gamification in the context of organizations' improvements and seeks to investigate game design from the experience of the user by providing relevant academic work, empirical research findings, and an overview of the field of study. Covering topics such as digital ecosystems, distance learning, and security awareness, this major reference work is ideal for policymakers, technology developers, managers, government officials, researchers, scholars, academicians, practitioners, instructors, and students.

Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on adversarial attack, defense and veri?cation. Sections cover adversarial attack, veri?cation and defense, mainly focusing on image classi?cation applications which are the standard benchmark considered in the adversarial robustness community. Other sections discuss adversarial examples beyond image classification, other threat models beyond testing time attack, and applications on adversarial robustness. For researchers, this book provides a thorough literature review that summarizes latest progress in the area, which can be a good reference for conducting future research. In addition, the book can also be used as a textbook for graduate courses on adversarial robustness or trustworthy machine learning. While machine learning (ML) algorithms have achieved remarkable performance in many applications, recent studies have demonstrated their lack of robustness against adversarial disturbance. The lack of robustness brings security concerns in ML models for real applications such as self-driving cars, robotics controls and healthcare systems.

All over the world, educational institutions confronted emergency policy changes caused by the COVID-19 pandemic. Due to this, academic activities were provided mostly by remote teaching and learning solutions. The transition to emergency remote teaching and learning raised some challenges regarding technical, pedagogical, and organizational issues. It is important for higher education institutions to prepare themselves to deal with future emergency scenarios, promoting an in-depth reflection about the future challenges in the post-pandemic era. Developing Curriculum for Emergency Remote Learning Environments supports creating and promoting an education-as-a-business strategy for higher education institutions by sharing possible business models. It provides a collection of different approaches to online education in the perspective of the future of education environments. Covering topics such as distance learning experiences, online practice improvement, and remote testing, this premier reference source is an excellent resource for educators and administrators of higher education, pre-service educators, IT professionals, librarians, researchers, and academicians.

Intelligent Nanotechnology: Merging Nanoscience and Artificial Intelligence provides an overview of advances in science and technology made possible by the convergence of nanotechnology and artificial intelligence (AI). Sections focus on AI-enhanced design, characterization and manufacturing and the use of AI to improve important material properties, with an emphasis on mechanical, photonic, electronic and magnetic properties. Designing benign nanomaterials through the prediction of their impact on biology and the environment is also discussed. Other sections cover the use of AI in the acquisition and analysis of data in experiments and AI technologies that have been enhanced through nanotechnology platforms. Final sections review advances in applications enabled by the merging of nanotechnology and artificial intelligence, including examples from biomedicine, chemistry and automated research.