Data Analytics And What It Means To The Materials Community

Author : National Academies of Sciences Engineering and Medicine,Division on Engineering and Physical Sciences,National Materials and Manufacturing Board
Publisher : Unknown
Page : 128 pages
File Size : 52,5 Mb
Release : 2021-09-12
Category : Electronic
ISBN : 030966408X

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Data Analytics and What It Means to the Materials Community by National Academies of Sciences Engineering and Medicine,Division on Engineering and Physical Sciences,National Materials and Manufacturing Board Pdf

Emerging techniques in data analytics, including machine learning and artificial intelligence, offer exciting opportunities for advancing scientific discovery and innovation in materials science. Vast repositories of experimental data and sophisticated simulations are being utilized to predict material properties, design and test new compositions, and accelerate nearly every facet of traditional materials science. How can the materials science community take advantage of these opportunities while avoiding potential pitfalls? What roadblocks may impede progress in the coming years, and how might they be addressed? To explore these issues, the Workshop on Data Analytics and What It Means to the Materials Community was organized as part of a workshop series on Defense Materials, Manufacturing, and Its Infrastructure. Hosted by the National Academies of Sciences, Engineering, and Medicine, the 2-day workshop was organized around three main topics: materials design, data curation, and emerging applications. Speakers identified promising data analytics tools and their achievements to date, as well as key challenges related to dealing with sparse data and filling data gaps; decisions around data storage, retention, and sharing; and the need to access, combine, and use data from disparate sources. Participants discussed the complementary roles of simulation and experimentation and explored the many opportunities for data informatics to increase the efficiency of materials discovery, design, and testing by reducing the amount of experimentation required. With an eye toward the ultimate goal of enabling applications, attendees considered how to ensure that the benefits of data analytics tools carry through the entire materials development process, from exploration to validation, manufacturing, and use. This publication summarizes the presentations and discussion of the workshop.

Author : Anonim
Publisher : Unknown
Page : 83 pages
File Size : 47,5 Mb
Release : 2021
Category : Defense industries
ISBN : 0309664098

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Data Analytics and What It Means to the Materials Community by Anonim Pdf

Author : Jeffrey P. Simmons,Lawrence F. Drummy,Charles A. Bouman,Marc De Graef
Publisher : CRC Press
Page : 537 pages
File Size : 53,9 Mb
Release : 2019-02-13
Category : Science
ISBN : 9781498738217

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Statistical Methods for Materials Science by Jeffrey P. Simmons,Lawrence F. Drummy,Charles A. Bouman,Marc De Graef Pdf

Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.

Author : B. Lynn Ferguson, Robert Goldstein, Scott MacKenzie, and Rozalia Papp
Publisher : ASM International
Page : 342 pages
File Size : 51,7 Mb
Release : 2014-06-01
Category : Electronic books
ISBN : 9781627080682

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Thermal Process Modeling 2014: by B. Lynn Ferguson, Robert Goldstein, Scott MacKenzie, and Rozalia Papp Pdf

Thermal processes are key manufacturing steps in producing durable and useful products, with solidification, welding, heat treating, and surface engineering being primary steps. These papers represent the latest state-of-the-art in thermal process modeling. The breadth of topics covers the depth of the industry.

Author : Sathiyamoorthi, V.,Elci, Atilla
Publisher : IGI Global
Page : 324 pages
File Size : 41,7 Mb
Release : 2020-12-04
Category : Computers
ISBN : 9781799825685

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Challenges and Applications of Data Analytics in Social Perspectives by Sathiyamoorthi, V.,Elci, Atilla Pdf

With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.

Author : Dongwon Shin,James Saal
Publisher : Springer
Page : 233 pages
File Size : 55,7 Mb
Release : 2017-11-10
Category : Technology & Engineering
ISBN : 9783319682808

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Computational Materials System Design by Dongwon Shin,James Saal Pdf

This book provides state-of-the-art computational approaches for accelerating materials discovery, synthesis, and processing using thermodynamics and kinetics. The authors deliver an overview of current practical computational tools for materials design in the field. They describe ways to integrate thermodynamics and kinetics and how the two can supplement each other.

Author : Juan J. Cuadrado-Gallego,Yuri Demchenko
Publisher : Springer Nature
Page : 486 pages
File Size : 44,5 Mb
Release : 2023-11-30
Category : Computers
ISBN : 9783031391293

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Data Analytics by Juan J. Cuadrado-Gallego,Yuri Demchenko Pdf

Building upon the knowledge introduced in The Data Science Framework, this book provides a comprehensive and detailed examination of each aspect of Data Analytics, both from a theoretical and practical standpoint. The book explains representative algorithms associated with different techniques, from their theoretical foundations to their implementation and use with software tools. Designed as a textbook for a Data Analytics Fundamentals course, it is divided into seven chapters to correspond with 16 weeks of lessons, including both theoretical and practical exercises. Each chapter is dedicated to a lesson, allowing readers to dive deep into each topic with detailed explanations and examples. Readers will learn the theoretical concepts and then immediately apply them to practical exercises to reinforce their knowledge. And in the lab sessions, readers will learn the ins and outs of the R environment and data science methodology to solve exercises with the R language. With detailed solutions provided for all examples and exercises, readers can use this book to study and master data analytics on their own. Whether you're a student, professional, or simply curious about data analytics, this book is a must-have for anyone looking to expand their knowledge in this exciting field.

Author : Taha Chaiechi,Jacob Wood
Publisher : Springer Nature
Page : 699 pages
File Size : 47,9 Mb
Release : 2022-01-12
Category : Political Science
ISBN : 9789811652608

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Community Empowerment, Sustainable Cities, and Transformative Economies by Taha Chaiechi,Jacob Wood Pdf

This edited volume presents the conference papers from the 1st International Conference on Business, Economics, Management, and Sustainability (BEMAS), organized by the Centre for International Trade and Business in Asia (CITBA) at James Cook University. This book argues that the orthodox methods of external risks, climate change adaptation plans, and sustainable economic growth in cities are no longer adequate. These methods, so far, have not only ignored the ongoing structural changes associated with economic development but also failed to account for evolving industries’ composition and the emergence of new comparative advantages and skills. Specifically, this book looks at the vulnerable communities and exposed areas, particularly in urban areas, that tend to experience higher susceptibility to external risks (such as climate change, natural disasters, and public health emergencies) have been largely ignored in incremental adaptation plans. Vulnerable communities and areas not only require different adaptive responses to climate risk but also possess unlocked adaptive capacity that can motivate different patterns of sustainable development to achieve the goals of the 2030 Agenda. It is essential, therefore, to view transformative growth and fundamental reorientation of economic resources as integral parts of the solution. Social disorganisation and vulnerability are other undesired outcomes of the unpredictable and widespread external economic shocks. This is due to a sudden and tough competition between members of society to acquire precious resources, most of which may be depleted during unprecedented events such as natural disasters or pandemics resulting in an even more chaotic and disorganised conditions.

Author : Surya R. Kalidindi
Publisher : Elsevier
Page : 230 pages
File Size : 40,7 Mb
Release : 2015-08-06
Category : Technology & Engineering
ISBN : 9780124104556

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Hierarchical Materials Informatics by Surya R. Kalidindi Pdf

Custom design, manufacture, and deployment of new high performance materials for advanced technologies is critically dependent on the availability of invertible, high fidelity, structure-property-processing (SPP) linkages. Establishing these linkages presents a major challenge because of the need to cover unimaginably large dimensional spaces. Hierarchical Materials Informatics addresses objective, computationally efficient, mining of large ensembles of experimental and modeling datasets to extract this core materials knowledge. Furthermore, it aims to organize and present this high value knowledge in highly accessible forms to end users engaged in product design and design for manufacturing efforts. As such, this emerging field has a pivotal role in realizing the goals outlined in current strategic national initiatives such as the Materials Genome Initiative (MGI) and the Advanced Manufacturing Partnership (AMP). This book presents the foundational elements of this new discipline as it relates to the design, development, and deployment of hierarchical materials critical to advanced technologies. Addresses a critical gap in new materials research and development by presenting a rigorous statistical framework for the quantification of microstructure Contains several case studies illustrating the use of modern data analytic tools on microstructure datasets (both experimental and modeling)

Author : National Research Council,Division on Engineering and Physical Sciences,National Materials and Manufacturing Board,Defense Materials Manufacturing and Infrastructure Standing Committee
Publisher : National Academies Press
Page : 78 pages
File Size : 48,7 Mb
Release : 2014-10-22
Category : Technology & Engineering
ISBN : 9780309303828

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Big Data in Materials Research and Development by National Research Council,Division on Engineering and Physical Sciences,National Materials and Manufacturing Board,Defense Materials Manufacturing and Infrastructure Standing Committee Pdf

Big Data in Materials Research and Development is the summary of a workshop convened by the National Research Council Standing Committee on Defense Materials Manufacturing and Infrastructure in February 2014 to discuss the impact of big data on materials and manufacturing. The materials science community would benefit from appropriate access to data and metadata for materials development, processing, application development, and application life cycles. Currently, that access does not appear to be sufficiently widespread, and many workshop participants captured the constraints and identified potential improvements to enable broader access to materials and manufacturing data and metadata. This report discusses issues in defense materials, manufacturing and infrastructure, including data ownership and access; collaboration and exploitation of big data's capabilities; and maintenance of data.

Author : Gabriela Castillo Areco
Publisher : Packt Publishing Ltd
Page : 344 pages
File Size : 41,7 Mb
Release : 2023-12-29
Category : Computers
ISBN : 9781837635580

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Data Science for Web3 by Gabriela Castillo Areco Pdf

Be part of the future of Web3, decoding blockchain data to build trust in the next-generation internet Key Features Build a deep understanding of the fundamentals of blockchain analytics Extract actionable business insights by modeling blockchain data Showcase your work and gain valuable experience to seize opportunities in the Web3 ecosystem Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData is the new oil and Web3 is generating it at an unprecedented rate. Complete with practical examples, detailed explanations, and ideas for portfolio development, this comprehensive book serves as a step-by-step guide covering the industry best practices, tools, and resources needed to easily navigate the world of data in Web3. You’ll begin by acquiring a solid understanding of key blockchain concepts and the fundamental data science tools essential for Web3 projects. The subsequent chapters will help you explore the main data sources that can help address industry challenges, decode smart contracts, and build DeFi- and NFT-specific datasets. You’ll then tackle the complexities of feature engineering specific to blockchain data and familiarize yourself with diverse machine learning use cases that leverage Web3 data. The book includes interviews with industry leaders providing insights into their professional journeys to drive innovation in the Web 3 environment. Equipped with experience in handling crypto data, you’ll be able to demonstrate your skills in job interviews, academic pursuits, or when engaging potential clients. By the end of this book, you’ll have the essential tools to undertake end-to-end data science projects utilizing blockchain data, empowering you to help shape the next-generation internet.What you will learn Understand the core components of blockchain transactions and blocks Identify reliable sources of on-chain and off-chain data to build robust datasets Understand key Web3 business questions and how data science can offer solutions Build your skills to create and query NFT- and DeFi-specific datasets Implement a machine learning toolbox with real-world use cases in the Web3 space Who this book is for This book is designed for data professionals—data analysts, data scientists, or data engineers— and business professionals, aiming to acquire the skills for extracting data from the Web3 ecosystem, as it demonstrates how to effectively leverage data tools for in-depth analysis of blockchain transactional data. If you seek hands-on experience, you'll find value in the shared repository, enabling you to experiment with the provided solutions. While not mandatory, a basic understanding of statistics, machine learning, and Python will enhance your learning experience.

Author : Ghanshyam Pilania,Prasanna V. Balachandran,James E. Gubernatis,Turab Lookman
Publisher : Springer Nature
Page : 172 pages
File Size : 41,7 Mb
Release : 2022-05-31
Category : Science
ISBN : 9783031023835

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Data-Based Methods for Materials Design and Discovery by Ghanshyam Pilania,Prasanna V. Balachandran,James E. Gubernatis,Turab Lookman Pdf

Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions. The authors, who have extensive experience in this interdisciplinary field, discuss generalizations where more than one competing material property is involved or data with differing degrees of precision/costs or fidelity/expense needs to be considered.

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 444 pages
File Size : 40,7 Mb
Release : 2022-01-28
Category : Social Science
ISBN : 9781668445167

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Research Anthology on Fandoms, Online Social Communities, and Pop Culture by Management Association, Information Resources Pdf

The internet has grown to become one of the largest communication hubs in history. With its ability to share content and create community bonds, it has seen many fandoms and online social communities develop within the past decades. While there are some detriments to these communities, there are also many benefits and potential uses for the betterment of society. The Research Anthology on Fandoms, Online Social Communities, and Pop Culture explores the ways in which the internet has presented itself as a platform for communities to gather. This essential reference source discusses the engagement of these communities, social media use, and the uses of these communities for education. Covering topics such as digital communities, transmedia language learning, and digital humanities, this book is a vital tool for educators of K-12 and higher education, digital folklorists, sociologists, communications researchers, online administrators, community leaders, and academicians.

Author : Sidney Yip
Publisher : Springer Science & Business Media
Page : 2903 pages
File Size : 44,8 Mb
Release : 2007-11-17
Category : Science
ISBN : 9781402032868

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Handbook of Materials Modeling by Sidney Yip Pdf

The first reference of its kind in the rapidly emerging field of computational approachs to materials research, this is a compendium of perspective-providing and topical articles written to inform students and non-specialists of the current status and capabilities of modelling and simulation. From the standpoint of methodology, the development follows a multiscale approach with emphasis on electronic-structure, atomistic, and mesoscale methods, as well as mathematical analysis and rate processes. Basic models are treated across traditional disciplines, not only in the discussion of methods but also in chapters on crystal defects, microstructure, fluids, polymers and soft matter. Written by authors who are actively participating in the current development, this collection of 150 articles has the breadth and depth to be a major contributor toward defining the field of computational materials. In addition, there are 40 commentaries by highly respected researchers, presenting various views that should interest the future generations of the community. Subject Editors: Martin Bazant, MIT; Bruce Boghosian, Tufts University; Richard Catlow, Royal Institution; Long-Qing Chen, Pennsylvania State University; William Curtin, Brown University; Tomas Diaz de la Rubia, Lawrence Livermore National Laboratory; Nicolas Hadjiconstantinou, MIT; Mark F. Horstemeyer, Mississippi State University; Efthimios Kaxiras, Harvard University; L. Mahadevan, Harvard University; Dimitrios Maroudas, University of Massachusetts; Nicola Marzari, MIT; Horia Metiu, University of California Santa Barbara; Gregory C. Rutledge, MIT; David J. Srolovitz, Princeton University; Bernhardt L. Trout, MIT; Dieter Wolf, Argonne National Laboratory.

Author : Anonim
Publisher : Elsevier
Page : 390 pages
File Size : 41,9 Mb
Release : 2015-08-04
Category : Mathematics
ISBN : 9780444634979

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Big Data Analytics by Anonim Pdf

While the term Big Data is open to varying interpretation, it is quite clear that the Volume, Velocity, and Variety (3Vs) of data have impacted every aspect of computational science and its applications. The volume of data is increasing at a phenomenal rate and a majority of it is unstructured. With big data, the volume is so large that processing it using traditional database and software techniques is difficult, if not impossible. The drivers are the ubiquitous sensors, devices, social networks and the all-pervasive web. Scientists are increasingly looking to derive insights from the massive quantity of data to create new knowledge. In common usage, Big Data has come to refer simply to the use of predictive analytics or other certain advanced methods to extract value from data, without any required magnitude thereon. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. While there are challenges, there are huge opportunities emerging in the fields of Machine Learning, Data Mining, Statistics, Human-Computer Interfaces and Distributed Systems to address ways to analyze and reason with this data. The edited volume focuses on the challenges and opportunities posed by "Big Data" in a variety of domains and how statistical techniques and innovative algorithms can help glean insights and accelerate discovery. Big data has the potential to help companies improve operations and make faster, more intelligent decisions. Review of big data research challenges from diverse areas of scientific endeavor Rich perspective on a range of data science issues from leading researchers Insight into the mathematical and statistical theory underlying the computational methods used to address big data analytics problems in a variety of domains