Opportunities From The Integration Of Simulation Science And Data Science
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Opportunities From The Integration Of Simulation Science And Data Science
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2018-07-31
Opportunities From The Integration Of Simulation Science And Data Science written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Computers categories.
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.
Data Science And Simulation In Transportation Research
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Author : Janssens, Davy
language : en
Publisher: IGI Global
Release Date : 2013-12-31
Data Science And Simulation In Transportation Research written by Janssens, Davy and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-31 with Computers categories.
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.
Recoverability As A First Class Security Objective
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2018-10-01
Recoverability As A First Class Security Objective written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-01 with Computers categories.
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.
Simulation For Data Science With R
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Author : Matthias Templ
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-06-30
Simulation For Data Science With R written by Matthias Templ and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-30 with Computers categories.
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.
Big Data Science And Analytics For Smart Sustainable Urbanism
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Author : Simon Elias Bibri
language : en
Publisher: Springer
Release Date : 2019-05-30
Big Data Science And Analytics For Smart Sustainable Urbanism written by Simon Elias Bibri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Political Science categories.
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.
Data Science
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Author : Sebastian Maneth
language : en
Publisher: Springer
Release Date : 2015-06-10
Data Science written by Sebastian Maneth and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-10 with Computers categories.
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.
Modern Data Science With R
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Author : Benjamin S. Baumer
language : en
Publisher: CRC Press
Release Date : 2017-03-16
Modern Data Science With R written by Benjamin S. Baumer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-16 with Mathematics categories.
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.
Emerging Trends In Iot And Integration With Data Science Cloud Computing And Big Data Analytics
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Author : Taser, Pelin Yildirim
language : en
Publisher: IGI Global
Release Date : 2021-11-05
Emerging Trends In Iot And Integration With Data Science Cloud Computing And Big Data Analytics written by Taser, Pelin Yildirim and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-05 with Computers categories.
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.
Clinical Simulations In Nursing Education
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Author : Pamela Jeffries
language : en
Publisher: Lippincott Williams & Wilkins
Release Date : 2022-09-21
Clinical Simulations In Nursing Education written by Pamela Jeffries and has been published by Lippincott Williams & Wilkins this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-21 with Medical categories.
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.
Simulation For Data Science With R
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Author : Matthias Templ
language : en
Publisher: Packt Publishing
Release Date : 2016-06-30
Simulation For Data Science With R written by Matthias Templ and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-30 with Computers categories.