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.

Download or read book Data Science and Simulation in Transportation Research written by Janssens, Davy and published by IGI Global. This book was released on 2013-12-31 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given its effective techniques and theories from various sources and fields, data science is playing a vital role in transportation research and the consequences of the inevitable switch to electronic vehicles. This fundamental insight provides a step towards the solution of this important challenge. Data Science and Simulation in Transportation Research highlights entirely new and detailed spatial-temporal micro-simulation methodologies for human mobility and the emerging dynamics of our society. Bringing together novel ideas grounded in big data from various data mining and transportation science sources, this book is an essential tool for professionals, students, and researchers in the fields of transportation research and data mining.

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 2018-10-01 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.

Download or read book Simulation for Data Science with R written by Matthias Templ and published by Packt Publishing Ltd. This book was released on 2016-06-30 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness actionable insights from your data with computational statistics and simulations using R About This Book Learn five different simulation techniques (Monte Carlo, Discrete Event Simulation, System Dynamics, Agent-Based Modeling, and Resampling) in-depth using real-world case studies A unique book that teaches you the essential and fundamental concepts in statistical modeling and simulation Who This Book Is For This book is for users who are familiar with computational methods. If you want to learn about the advanced features of R, including the computer-intense Monte-Carlo methods as well as computational tools for statistical simulation, then this book is for you. Good knowledge of R programming is assumed/required. What You Will Learn The book aims to explore advanced R features to simulate data to extract insights from your data. Get to know the advanced features of R including high-performance computing and advanced data manipulation See random number simulation used to simulate distributions, data sets, and populations Simulate close-to-reality populations as the basis for agent-based micro-, model- and design-based simulations Applications to design statistical solutions with R for solving scientific and real world problems Comprehensive coverage of several R statistical packages like boot, simPop, VIM, data.table, dplyr, parallel, StatDA, simecol, simecolModels, deSolve and many more. In Detail Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. The book will provide a computational and methodological framework for statistical simulation to the users. Through this book, you will get in grips with the software environment R. After getting to know the background of popular methods in the area of computational statistics, you will see some applications in R to better understand the methods as well as gaining experience of working with real-world data and real-world problems. This book helps uncover the large-scale patterns in complex systems where interdependencies and variation are critical. An effective simulation is driven by data generating processes that accurately reflect real physical populations. You will learn how to plan and structure a simulation project to aid in the decision-making process as well as the presentation of results. By the end of this book, you reader will get in touch with the software environment R. After getting background on popular methods in the area, you will see applications in R to better understand the methods as well as to gain experience when working on real-world data and real-world problems. Style and approach This book takes a practical, hands-on approach to explain the statistical computing methods, gives advice on the usage of these methods, and provides computational tools to help you solve common problems in statistical simulation and computer-intense methods.

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.

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 337 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.

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.

Download or read book Data Science written by Sebastian Maneth and published by Springer. This book was released on 2015-06-10 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the 30th British International Conference on Databases, BICOD 2015 - formerly known as BNCOD (British National Conference on Databases) - held in Edinburgh, UK, in July 2015. The 19 revised full papers, presented together with three invited keynotes and three invited lectures were carefully reviewed and selected from 37 submissions. Special focus of the conference has been "Data Science" and so the papers cover a wide range of topics related to databases and data-centric computation.

Download or read book America s Next Generation Supercomputer written by United States. Congress. House. Committee on Science, Space, and Technology (2011). Subcommittee on Energy and published by . This book was released on 2013 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Science in Applications written by Gintautas Dzemyda and published by Springer Nature. This book was released on 2023-03-09 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of a wide range of relevant applications and reveals how to solve them. Many of the latest applications in finance, technology, education, medicine and other important and relevant fields are data-driven. The volumes of data are enormous. Specific methods need to be developed or adapted to solve a particular problem. It illustrates data science in applications. These applications have in common the discovery of knowledge in data and the use of this knowledge to make real decisions. The set of examples presented serves as a recipe book for their direct application to similar problems or as a guide for the development of new, more sophisticated approaches. The intended readership is data scientists looking for appropriate solutions to their problems. In addition, the examples provided serves as material for lectures at universities.

Download or read book Simulating Science written by Ramón Alvarado and published by Springer Nature. This book was released on 2023-08-23 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a philosophical framework to understand computer simulations as scientific instruments. This is in sharp contrast to existing philosophical approaches on the subject, which have historically understood computer simulations as either formal abstractions or as broadly construed empirical practices. In order to make its case, the volume contains a thorough examination of conventional philosophical approaches as well as their respective limitations. Yet, also, unlike other accounts of computer simulations from the perspective of the philosophy of science, this book incorporates insights from the philosophy of technology and the history of science. Hence, the book offers philosophers of science, technologists and other researchers interested in the topic, a thorough overview of the philosophical issues regarding the design, development and deployment of computer simulations in science and science-based policy making.

Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2017-03-16 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. 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 statistical questions. Contemporary data science requires a tight integration of knowledge from statistics, computer science, mathematics, and a domain of application. This book will help readers with some background in statistics and modest prior experience with coding develop and practice the appropriate skills to tackle complex data science projects. The book features a number of exercises and has a flexible organization conducive to teaching a variety of semester courses.

Download or read book Cyberinfrastructure Vision for 21st Century Discovery written by and published by . This book was released on 2007 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Clinical Simulations in Nursing Education written by Pamela Jeffries and published by Lippincott Williams & Wilkins. This book was released on 2022-09-21 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s quickly changing healthcare environment, simulation has become an indispensable strategy for preparing nursing students to deliver optimal patient care. Clinical Simulations in Nursing Education: Advanced Concepts, Trends, and Opportunities, Second Edition, takes the use of simulations to the next level, exploring innovative teaching/learning methods, new clinical models, and up-to-date best practices for providing high-quality education. From the evolution of clinical simulations to the use of more virtual simulations, incorporation of important constructs such as the social determinants of health, and the use of simulations in nursing education and competency-based testing, this engaging resource continues to provide intermediate and advanced simulation users and advocates with critical considerations for advancing simulation in nursing education. The comprehensive updated second edition focuses on the latest trends and concepts in simulation pedagogy to help nurse educators confidently prepare for their role in developing, planning, implementing, evaluating, and conducting research for effective simulation programs.

Download or read book Roundtable on Data Science Postsecondary Education written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-09-02 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting.

Download or read book Sustained Simulation Performance 2022 written by Michael M. Resch and published by Springer Nature. This book was released on 2024 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zusammenfassung: This book presents the state of the art in High-Performance Computing on modern supercomputer architectures. It addresses trends in hardware and software development in general. The contributions cover a broad range of topics, from performance evaluations in context with power efficiency to Computational Fluid Dynamics and High-Performance Data Analytics. In addition, they explore new topics like the use of High-Performance Computers in the field of Artificial Intelligence and Machine Learning. All contributions are based on selected papers presented in 2022 at the 33rd Workshop on Sustained Simulation Performance, WSSP33, held at HLRS in Stuttgart, Germany, and WSSP34, held at Tohoku University in Sendai, Japan

Download or read book Integrative Omics written by Manish Kumar Gupta and published by Elsevier. This book was released on 2024-05-10 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrative Omics: Concepts, Methodology and Applications provides a holistic and integrated view of defining and applying network approaches, integrative tools, and methods to solve problems for the rationalization of genotype to phenotype relationships. The reference includes a range of chapters in a systemic ‘step by step’ manner, which begins with the basic concepts from Omic to Multi Integrative Omics approaches, followed by their full range of approaches, applications, emerging trends, and future trends. All key areas of Omics are covered including biological databases, sequence alignment, pharmacogenomics, nutrigenomics and microbial omics, integrated omics for Food Science and Identification of genes associated with disease, clinical data integration and data warehousing, translational omics as well as omics technology policy and society research. Integrative Omics: Concepts, Methodology and Applications highlights the recent concepts, methodologies, advancements in technologies and is also well-suited for researchers from both academic and industry background, undergraduate and graduate students who are mainly working in the area of computational systems biology, integrative omics and translational science. The book bridges the gap between biological sciences, physical sciences, computer science, statistics, data science, information technology and mathematics by presenting content specifically dedicated to mathematical models of biological systems. Provides a holistic, integrated view of a defining and applying network approach, integrative tools, and methods to solve problems for rationalization of genotype to phenotype relationships Offers an interdisciplinary approach to Databases, data analytics techniques, biological tools, network construction, analysis, modeling, prediction and simulation of biological systems leading to ‘translational research’, i.e., drug discovery, drug target prediction, and precision medicine Covers worldwide methods, concepts, databases, and tools used in the construction of integrated pathways