Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)


Book Description

This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances in instrument — driven data generation and analytics, establishing the links between the big data and predictive theories, and outlining the emerging field of data and physics-driven predictive and autonomous systems.




Handbook Of Solar Thermal Technologies: Concentrating Solar Power And Fuels (In 3 Volumes)


Book Description

The three-volume handbook showcases the state of the art in the use of concentrated sunlight to produce electricity, industrial process heat, renewable fuels, including hydrogen and low-carbon synthesis gas, and valuable chemical commodities. The handbook illustrates the value and diversity of applications for concentrating solar power to contribute to the expanding decarbonization of multiple cross-cutting energy sectors.Volume 1: Concentrating Solar Thermal Power, provides an overview of key technologies, principles, and challenges of concentrating solar power (CSP) as well as the use of concentrating solar thermal for process heating and district markets. The ten chapters of this volume provide the reader with the technical background on the solar resource for concentrating solar thermal, the principles and design of concentrating optics, and descriptions of state-of-the-art and emerging solar collector and receiver technologies, thermal storage and thermal-to-electric conversion and power cycles for CSP. It also contains a comprehensive summary of operations and maintenance requirements for CSP plants, and commercial CSP plants and markets around the world.Volume 2, Solar Thermochemical Processes and Products, covers the use of concentrated solar radiation as the heat source to drive endothermic chemical reactions to produce renewable fuels and valuable chemical commodities, equivalently storing solar energy in chemical bonds. The thermodynamic underpinnings of a number of approaches to produce fuel and results of demonstrations of solar thermochemical reactors for these processes at prototype scale are presented. Processes presented include thermochemical metal oxide reduction/oxidation cycles to split water and carbon dioxide solar chemical looping reformation of methane to produce synthesis gas, high temperature electrochemistry, and gasification of biomass. Research on the thermochemical storage for CSP and high temperature production of cement and ammonia to illustrate the use concentrated solar energy to produce valuable chemical products are also included.Volume 3 contains reprinted archival papers to support and supplement the material in Volumes 1 and 2. These papers provide background information on the economics and alternative use cases of CSP not covered in Volume 1, and expand on the material related to the chapter topics presented in Volume 2. Potential commercialization, such as prototype and demonstration projects, are highlighted. The papers are intended as a starting point for a more in-depth study of the topics.




Path To Transformational Space Exploration, The (In 2 Volumes)


Book Description

In this book Professor Lubin lays out the fundamental physics and mathematics required to radically alter our capabilities in propulsion to enable extreme high-speed space flight both in our solar system and beyond. The case is made that the only currently viable solution to enable this transformation, including relativistic flight for the first interstellar robotic missions, is using large-scale directed energy. Traditional methods of propulsion are not capable of achieving the speed required for these missions, including fast crewed missions to Mars as well as the many robotic missions desired both in our solar system and to the nearest stars. Humanity has now reached a technological tipping point with the ability to project power over vast distances with transformational implications in a wide variety of areas, from propulsion to beaming power throughout our solar system to planetary defence. In a series of over 60 technical papers, the fundamentals of this transformation are outlined and synthesized in this book, allowing a detailed understanding of the many challenges ahead and a roadmap for human exploration far beyond our solar system. While the road ahead is long and challenging, it provides the path to radically alter humanity's future.Related Link(s)







Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry


Book Description

The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.




Handbook On Computer Learning And Intelligence (In 2 Volumes)


Book Description

The Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)




Encyclopedia of Data Science and Machine Learning


Book Description

Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.




Cybersecurity and High-Performance Computing Environments


Book Description

In this fast-paced global economy, academia and industry must innovate to evolve and succeed. Today’s researchers and industry experts are seeking transformative technologies to meet the challenges of tomorrow. Cutting-edge technological advances in cybersecurity solutions aid in enabling the security of complex heterogeneous high-performance computing (HPC) environments. On the other hand, HPC facilitates powerful and intelligent innovative models for reducing time to response to identify and resolve a multitude of potential, newly emerging cyberattacks. Cybersecurity and High-Performance Computing Environments provides a collection of the current and emergent research innovations, practices, and applications focusing on the interdependence of cybersecurity and HPC domains for discovering and resolving new emerging cyber-threats. KEY FEATURES Represents a substantial research contribution to the state-of-the-art solutions for addressing the threats to confidentiality, integrity, and availability (CIA triad) in HPC environments Covers the groundbreaking and emergent solutions that utilize the power of the HPC environments to study and understand the emergent, multifaceted, anomalous, and malicious characteristics The content will help university students, researchers, and professionals understand how HPC research fits broader cybersecurity objectives and vice versa.




Statistical and Machine-Learning Data Mining


Book Description

The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has completely revised, reorganized, and repositioned the original chapters and produced 14 new chapters of creative and useful machine-learning data mining techniques. In sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. The statistical data mining methods effectively consider big data for identifying structures (variables) with the appropriate predictive power in order to yield reliable and robust large-scale statistical models and analyses. In contrast, the author's own GenIQ Model provides machine-learning solutions to common and virtually unapproachable statistical problems. GenIQ makes this possible — its utilitarian data mining features start where statistical data mining stops. This book contains essays offering detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. They address each methodology and assign its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.




Principles of Electron Optics, Volume 4


Book Description

Principles of Electron Optics: Second Edition, Advanced Wave Optics provides a self-contained, modern account of electron optical phenomena with the Dirac or Schrödinger equation as a starting point. Knowledge of this branch of the subject is essential to understanding electron propagation in electron microscopes, electron holography and coherence. Sections in this new release include, Electron Interactions in Thin Specimens, Digital Image Processing, Acquisition, Sampling and Coding, Enhancement, Linear Restoration, Nonlinear Restoration – the Phase Problem, Three-dimensional Reconstruction, Image Analysis, Instrument Control, Vortex Beams, The Quantum Electron Microscope, and much more. - Includes authoritative coverage of many recent developments in wave electron optics - Describes the interaction of electrons with solids and the information that can be obtained from electron-beam techniques - Includes new content on multislice optics, 3D reconstruction, Wigner optics, vortex beams and the quantum electron microscope