Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Opportunities From The Integration Of Simulation Science And Data Science
Download Opportunities From The Integration Of Simulation Science And Data Science full books in PDF, epub, and Kindle. Read online Opportunities From The Integration Of Simulation Science And Data Science ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309481899 Total Pages :49 pages Book Rating :4.3/5 (94 download)
Book Synopsis Opportunities from the Integration of Simulation Science and Data Science by : National Academies of Sciences, Engineering, and Medicine
Download or read book Opportunities from the Integration of Simulation Science and Data Science written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-07-31 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convergence has been a key topic of discussion about the future of cyberinfrastructure for science and engineering research. Convergence refers both to the combined use of simulation and data-centric techniques in science and engineering research and the possibilities for a single type of cyberinfrastructure to support both techniques. The National Academies of Science, Engineering, and Medicine convened a Workshop on Converging Simulation and Data-Driven Science on May 10, 2018, in Washington, D.C. The workshop featured speakers from universities, national laboratories, technology companies, and federal agencies who addressed the potential benefits and limitations of convergence as they relate to scientific needs, technological capabilities, funding structures, and system design requirements. This publication summarizes the presentations and discussions from the workshop.
Book Synopsis Data Science and Simulation in Transportation Research by : Davy Janssens
Download or read book Data Science and Simulation in Transportation Research written by Davy Janssens and published by Information Science Reference. This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book highlights entirely new and detailed spatial-temporal micro-simulation methodologies for human mobility and the emerging dynamics of our society, offering novel ideas grounded in big data from various data mining and transportation science sources"--
Book Synopsis Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics by : Taser, Pelin Yildirim
Download or read book Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics written by Taser, Pelin Yildirim and published by IGI Global. This book was released on 2021-11-05 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :152251760X Total Pages :3095 pages Book Rating :4.5/5 (225 download)
Book Synopsis Artificial Intelligence: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources
Download or read book Artificial Intelligence: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-12-12 with total page 3095 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ongoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications provides a comprehensive overview of the latest breakthroughs and recent progress in artificial intelligence. Highlighting relevant technologies, uses, and techniques across various industries and settings, this publication is a pivotal reference source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of artificial intelligence.
Book Synopsis Foundations of Data Science by : Avrim Blum
Download or read book Foundations of Data Science written by Avrim Blum and published by Cambridge University Press. This book was released on 2020-01-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309483700 Total Pages :61 pages Book Rating :4.3/5 (94 download)
Book Synopsis Recoverability as a First-Class Security Objective by : National Academies of Sciences, Engineering, and Medicine
Download or read book Recoverability as a First-Class Security Objective written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-11-01 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Forum on Cyber Resilience of the National Academies of Sciences, Engineering, and Medicine hosted the Workshop on Recoverability as a First-Class Security Objective on February 8, 2018, in Washington, D.C. The workshop featured presentations from several experts in industry, research, and government roles who spoke about the complex facets of recoverabilityâ€"that is, the ability to restore normal operations and security in a system affected by software or hardware failure or a deliberate attack. This publication summarizes the presentations and discussions from the workshop.
Book Synopsis Introduction to Computational Science by : Angela B. Shiflet
Download or read book Introduction to Computational Science written by Angela B. Shiflet and published by Princeton University Press. This book was released on 2014-03-30 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to computational science—now fully updated and expanded Computational science is an exciting new field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. This textbook provides students with a versatile and accessible introduction to the subject. It assumes only a background in high school algebra, enables instructors to follow tailored pathways through the material, and is the only textbook of its kind designed specifically for an introductory course in the computational science and engineering curriculum. While the text itself is generic, an accompanying website offers tutorials and files in a variety of software packages. This fully updated and expanded edition features two new chapters on agent-based simulations and modeling with matrices, ten new project modules, and an additional module on diffusion. Besides increased treatment of high-performance computing and its applications, the book also includes additional quick review questions with answers, exercises, and individual and team projects. The only introductory textbook of its kind—now fully updated and expanded Features two new chapters on agent-based simulations and modeling with matrices Increased coverage of high-performance computing and its applications Includes additional modules, review questions, exercises, and projects An online instructor's manual with exercise answers, selected project solutions, and a test bank and solutions (available only to professors) An online illustration package is available to professors
Book Synopsis Data Science and Machine Learning by : Dirk P. Kroese
Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code
Book Synopsis Modern Data Science with R by : Benjamin S. Baumer
Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2021-03-31 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.
Book Synopsis The Data Science Design Manual by : Steven S. Skiena
Download or read book The Data Science Design Manual written by Steven S. Skiena and published by Springer. This book was released on 2017-07-01 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
Book Synopsis Big Data Science and Analytics for Smart Sustainable Urbanism by : Simon Elias Bibri
Download or read book Big Data Science and Analytics for Smart Sustainable Urbanism written by Simon Elias Bibri and published by Springer. This book was released on 2019-05-30 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.
Book Synopsis Applied Data Science by : Martin Braschler
Download or read book Applied Data Science written by Martin Braschler and published by Springer. This book was released on 2019-06-13 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.
Book Synopsis Digital Twin and Blockchain for Smart Cities by : Amit Kumar Tyagi
Download or read book Digital Twin and Blockchain for Smart Cities written by Amit Kumar Tyagi and published by John Wiley & Sons. This book was released on 2024-09-11 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book uniquely explores the fundamentals of blockchain and digital twin technologies and their uses in smart cities. In the previous decade, many governments explored artificial intelligence, digital twin, and blockchain, and their roles in smart cities. This book discusses the convergence of two transformative technologies, digital twin and blockchain, to address urban challenges and propel the development of smarter, more sustainable cities. This convergence empowers cities to create real-time replicas of urban environments (digital twins) and secure, transparent data management (blockchain) to improve city planning, management, and civic services. In this application, the concept of a digital twin involves creating a virtual, data-driven replica of a city or specific urban systems, such as transportation, energy, or infrastructure. This digital twin mirrors the real world, gathering data from various sensors, IoT devices, and other sources to provide a holistic view of the city’s operations. Furthermore, blockchain technology offers a decentralized and tamper-resistant ledger for securely storing and managing data. In the context of smart cities, blockchain can ensure data integrity, privacy, and transparency, enabling trust and collaboration among various stakeholders. This book covers many important topics, including real-time city modeling; data security and the trustworthy storage of sensitive urban data; transparent governance to facilitate accountable governance and decision-making processes in smart cities; improved city services; disaster resilience (by providing insights into vulnerabilities and efficient resource allocation during crises); sustainable urban planning that optimizes resource allocation, reduces energy consumption, and minimizes environmental impact, which fosters sustainable development; citizen engagement; and much more. This book will not only provide information about more efficient, resilient, and sustainable urban environments, but it also empowers citizens to be active participants in shaping the future of their cities. By converging these technologies, cities can overcome existing challenges, encourage innovation, and create more livable, connected, and responsive urban spaces. Audience This book has a wide audience in computer science, artificial intelligence, and information technology as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and government/city policymakers working on smart cities, the circular economy, clean tech investors, urban decision-makers, and environmental professionals.
Book Synopsis The Oxford Handbook of Archaeological Network Research by : Tom Brughmans
Download or read book The Oxford Handbook of Archaeological Network Research written by Tom Brughmans and published by Oxford University Press. This book was released on 2024-01-12 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network research has recently been adopted as one of the tools of the trade in archaeology, used to study a wide range of topics: interactions between island communities, movements through urban spaces, visibility in past landscapes, material culture similarity, exchange, and much more. This Handbook is the first authoritative reference work for archaeological network research, featuring current topical trends and covering the archaeological application of network methods and theories. This is elaborately demonstrated through substantive topics and case studies drawn from a breadth of periods and cultures in world archaeology. It highlights and further develops the unique contributions made by archaeological research to network science, especially concerning the development of spatial and material culture network methods and approaches to studying long-term network change. This is the go-to resource for students and scholars wishing to explore how network science can be applied in archaeology through an up-to-date overview of the field.
Book Synopsis Quantitative Asset Management by : William Johnson
Download or read book Quantitative Asset Management written by William Johnson and published by HiTeX Press. This book was released on 2024-10-12 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Quantitative Asset Management: Techniques for Optimizing Portfolio Returns" is an authoritative guide that expertly bridges theory and practice, equipping readers with the essential tools and strategies to navigate the complex world of finance. This meticulously crafted book unveils the intricate frameworks and advanced methodologies at the core of quantitative asset management, empowering investors, analysts, and financial professionals to achieve superior portfolio performance. From the foundational principles of modern portfolio theory to the cutting-edge application of machine learning in finance, each chapter delivers a rich tapestry of insights that elevate the reader’s understanding and decision-making skills. This volume intricately explores a wide array of topics including risk management, algorithmic trading, behavioral finance, and the ethical considerations that underpin successful asset management. By weaving together practical examples and real-world applications, it ensures readers can apply the learned concepts effectively within their own financial contexts. Whether navigating the challenges of market dynamics or leveraging emerging technologies, this book stands as a vital resource, ensuring its readers are well-prepared to excel in the ever-evolving landscape of quantitative finance.
Book Synopsis Social Simulation for a Digital Society by : Diane Payne
Download or read book Social Simulation for a Digital Society written by Diane Payne and published by Springer Nature. This book was released on 2019-11-18 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Social Simulation for a Digital Society” provides a cross-section of state-of-the-art research in social simulation and computational social science. With the availability of big data and faster computing power, the social sciences are undergoing a tremendous transformation. Research in computational social sciences has received considerable attention in the last few years, with advances in a wide range of methodologies and applications. Areas of application of computational methods range from the study of opinion and information dynamics in social networks, the formal modeling of resource use, the study of social conflict and cooperation to the development of cognitive models for social simulation and many more. This volume is based on the Social Simulation Conference of 2017 in Dublin and includes applications from across the social sciences, providing the reader with a demonstration of the highly versatile research in social simulation, with a particular focus on public policy relevance in a digital society. Chapters in the book include contributions to the methodology of simulation-based research, theoretical and philosophical considerations, as well as applied work. This book will appeal to students and researchers in the field.
Download or read book Machine Learning written by and published by . This book was released on 2017 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
