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.

Industrial Tomography: Systems and Applications, Second Edition thoroughly explores the important techniques of industrial tomography, also discusses image reconstruction, systems, and applications. This book presents complex processes, including the way three-dimensional imaging is used to create multiple cross-sections, and how computer software helps monitor flows, filtering, mixing, drying processes, and chemical reactions inside vessels and pipelines. This book is suitable for materials scientists and engineers and applied physicists working in the photonics and optoelectronics industry or in the applications industries.

Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model's adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.

DIRECTING, DIALOGUE AND ACTING From Richard Williams' The Animator's Survival Kit comes key chapters in mini form. The Animator's Survival Kit is the essential tool for animators. However, sometimes you don't want to carry the hefty expanded edition around with you to your college or studio if you're working on just one aspect of it that day. The Animation Minis take some of the most essential chapters and make them available in smaller, lightweight, hand-bag/backpack size versions. Easy to carry. Easy to study. This Mini focuses on Directing, Dialogue and Acting. As a director, whatever your idea is, you want to put it over, so the main thing with directing is to be clear - very clear. The Director's job is to hold everything together so that the animator can give the performance. Richard Williams shows how that performance can be achieved with flexibility and contrast. With Acting and Dialogue, the temptation is to try to do everything at once - Williams' advice: do one thing at a time.

C++ 11 delivered strong support for multithreaded applications, and the subsequent C++14 and 17 updates have built on this baseline. C++ has better options for concurrency than ever before, which means it's an incredibly powerful option for multicore and parallel applications. This bestseller has been updated and revised to cover all the latest changes to C++ 14 and 17! C++ Concurrency in Action, Second Edition teaches readers everything they need to write robust and elegant multithreaded applications in C++17. Along the way, they’ll learn how to navigate the trickier bits of programming for concurrency while avoiding the common pitfalls. KEY FEATURES • Completely updated • Hands-on learning • In depth guide Written for C++ programmers who are new to concurrency and others who may have written multithreaded code using other languages, APIs, or platforms. ABOUT THE TECHNOLOGY Concurrency in terms of computers is a single system performing multiple independent activities in parallel, rather than sequentially, or one after the other. AUTHOR BIO Anthony Williams is a UK-based developer and consultant with many years' experience in C++. He has been an active member of the BSI C++ Standards Panel since 2001, and is the author or co-author of many of the C++ Standards Committee papers that led up to the inclusion of the thread library in the C++11 Standard. He was the maintainer of the Boost Thread library, and is the developer of the just::thread Pro extensions to the C++11 thread library from Just Software Solutions Ltd.

Synthesis and Operability Strategies for Computer-Aided Modular Process intensification presents state-of-the-art methodological developments and real-world applications for computer-aided process modeling, optimization and control, with a particular interest on process intensification systems. Each chapter consists of basic principles, model formulation, solution algorithm, and step-by-step implementation guidance on key procedures. Sections cover an overview on the current status of process intensification technologies, including challenges and opportunities, detail process synthesis, design and optimization, the operation of intensified processes under uncertainty, and the integration of design, operability and control. Advanced operability analysis, inherent safety analysis, and model-based control strategies developed in the community of process systems engineering are also introduced to assess process operational performance at the early design stage.

Biomedical Image Synthesis and Simulation: Methods and Applications presents the basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. The first part of the book introduces and describes the simulation and synthesis methods that were developed and successfully used within the last twenty years, from parametric to deep generative models. The second part gives examples of successful applications of these methods. Both parts together form a book that gives the reader insight into the technical background of image synthesis and how it is used, in the particular disciplines of medical and biomedical imaging. The book ends with several perspectives on the best practices to adopt when validating image synthesis approaches, the crucial role that uncertainty quantification plays in medical image synthesis, and research directions that should be worth exploring in the future.

BLOCKCHAIN TECHNOLOGY IN CORPORATE GOVERANCE This book investigates the recent applications of blockchain technology in financial services, energy sector, and summarizes regulatory responses, to set the scene for future work on corporate governance. This edited book highlights the current governance framework for the blockchain and its development as a self-governing framework. It discusses blockchain technology's effectiveness in developing solutions for supply chains, trade finance, and banking. Moreover, it shows how banking and financial institutions are the major beneficiaries of this decentralized technology. Furthermore, the book outlines the link between company governance theories, regulatory, ethical, and social controls, and blockchain adoption. It also investigates the recent applications of blockchain technology in financial services, the health sector, and the energy sector. Audience The book is specially designed for researchers, industrialists, engineers, graduate students, and policymakers, who aspire to learn, discuss, and carry out further research into the opportunities offered by blockchain and the possible ways of regulating it.

Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods to enhance our scientific understanding of planetary data and serves as a guide for selecting the right methods and tools for solving a variety of everyday problems in planetary science using machine learning. Illustrating ways to employ machine learning in practice with case studies, the book is clearly organized into four parts to provide thorough context and easy navigation. The book covers a range of issues, from data analysis on the ground to data analysis onboard a spacecraft, and from prioritization of novel or interesting observations to enhanced missions planning. This book is therefore a key resource for planetary scientists working in data analysis, missions planning, and scientific observation.

The Designer's Guide to the Cortex-M Microcontrollers, Third Edition provides an easy-to-understand introduction to the concepts required to develop programs in C with a Cortex-M based microcontroller. Sections cover architectural descriptions that are supported with practical examples, enabling readers to easily develop basic C programs to run on the Cortex-M0/M0+/M3 and M4 and M7 and examine advanced features of the Cortex architecture, such as memory protection, operating modes and dual stack operation. Final sections examine techniques for software testing and code reuse specific to Cortex-M microcontrollers. Users will learn the key differences between the Cortex-M0/M0+/M3 and M4 and M7; how to write C programs to run on Cortex-M based processors; how to make the best use of the CoreSight debug system; the Cortex-M operating modes and memory protection; advanced software techniques that can be used on Cortex-M microcontrollers, and much more.

Emerging technologies in education are dramatically reshaping the way we teach, learn, and create meaning-both formally and informally. The use of emerging technologies within educational contexts requires new methodological approaches to teaching, learning, and educational research. This leads educational technology developers, researchers, and practitioners to engage in the creation of diverse digital learning tools that can be used in a wide range of learning situations and scenarios. Ultimately, the goal of today's digital learning experiences includes situational experiences wherein learners and teachers symbiotically enroll in meaning-making processes. Discussion, critical reflection, and critique of these emerging technologies, tools, environments, processes, and practices require scholars to involve themselves in critical conversation about the challenges and promises afforded by emerging technologies and to engage in deliberate thinking about the critical aspects of these emerging technologies that are drastically reshaping education. Global Education and the Impact of Institutional Policies on Educational Technologies deepens this discussion of emerging technologies in educational contexts and is centered at the intersection of educational technology, learning sciences, and socio-cultural theories. This book engages a critical conversation that will further the discussion about the pedagogical potential of emerging technologies in contemporary classrooms. Covering topics such as communication networks, online learning environments, and preservice teacher education, this text is an essential resource for educational professionals, preservice teachers, professors, teachers, students, and academicians.

A level of decision making is concerned with deciding the organization's objectives, resources, and policies. A significant problem at this decision-making level is predicting the organization's future and its environment as well as matching the organization's characteristics to that environment. This process generally involves technology and knowledge from the market and clients. In the current era, the implementation of marketing information systems supported with AI techniques is crucial to being a unique opportunity to leverage marketing strategies with cutting-edge technologies. Global Perspectives on the Strategic Role of Marketing Information Systems communicates the recent advances in marketing information systems. Covering topics such as digital entrepreneurship, international business, and micro and small enterprises, this premier reference source is a cutting-edge resource for marketers, entrepreneurs, business leaders and managers, IT managers, students and educators of higher education, librarians, researchers, and academicians.

Network Science Network Science offers comprehensive insight on network analysis and network optimization algorithms, with simple step-by-step guides and examples throughout, and a thorough introduction and history of network science, explaining the key concepts and the type of data needed for network analysis, ensuring a smooth learning experience for readers. It also includes a detailed introduction to multiple network optimization algorithms, including linear assignment, network flow and routing problems. The text is comprised of five chapters, focusing on subgraphs, network analysis, network optimization, and includes a list of case studies, those of which include influence factors in telecommunications, fraud detection in taxpayers, identifying the viral effect in purchasing, finding optimal routes considering public transportation systems, among many others. This insightful book shows how to apply algorithms to solve complex problems in real-life scenarios and shows the math behind these algorithms, enabling readers to learn how to develop them and scrutinize the results. Written by a highly qualified author with significant experience in the field, Network Science also includes information on: Sub-networks, covering connected components, bi-connected components, community detection, k-core decomposition, reach network, projection, nodes similarity and pattern matching Network centrality measures, covering degree, influence, clustering coefficient, closeness, betweenness, eigenvector, PageRank, hub and authority Network optimization, covering clique, cycle, linear assignment, minimum-cost network flow, maximum network flow problem, minimum cut, minimum spanning tree, path, shortest path, transitive closure, traveling salesman problem, vehicle routing problem and topological sort With in-depth and authoritative coverage of the subject and many case studies to convey concepts clearly, Network Science is a helpful training resource for professional and industry workers in, telecommunications, insurance, retail, banking, healthcare, public sector, among others, plus as a supplementary reading for an introductory Network Science course for undergraduate students.

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.

Case Studies in Geospatial Applications to Groundwater Resources provides thorough the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, through detailed case studies that prove real-world applications of remote sensing applications to this subject. Groundwater is the primary source of fresh water in many parts of the world, while come regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. India is the largest user of groundwater in the world followed by China and the USA, with developing countries using groundwater at an unsustainable rate. Systematic planning of groundwater usage using modern techniques is essential for the proper utilization, management and modeling of this precious but shrinking natural resource. With the advent of powerful and highspeed personal computers, efficient techniques for water management have evolved, of which remote sensing, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Geostatistical techniques are of great significance. This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. Case Studies in Geospatial Applications to Groundwater Resources is a valuable reference for researchers and postgraduate students in Earth and Environmental Sciences, especially GIS, agriculture, hydrology, natural resources, and soil science, who need to be able to apply the latest technologies in groundwater research in a practical manner.

Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!

In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.

Build a Large Language Model (from Scratch) teaches you how to:

• Plan and code all the parts of an LLM
• Prepare a dataset suitable for LLM training
• Fine-tune LLMs for text classification and with your own data
• Use human feedback to ensure your LLM follows instructions
• Load pretrained weights into an LLM

Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.