Accelerating Discovery

Author : Scott Spangler
Publisher : CRC Press
Page : 270 pages
File Size : 54,6 Mb
Release : 2015-09-18
Category : Business & Economics
ISBN : 9781482239140

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Accelerating Discovery by Scott Spangler Pdf

Unstructured Mining Approaches to Solve Complex Scientific Problems As the volume of scientific data and literature increases exponentially, scientists need more powerful tools and methods to process and synthesize information and to formulate new hypotheses that are most likely to be both true and important. Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation describes a novel approach to scientific research that uses unstructured data analysis as a generative tool for new hypotheses. The author develops a systematic process for leveraging heterogeneous structured and unstructured data sources, data mining, and computational architectures to make the discovery process faster and more effective. This process accelerates human creativity by allowing scientists and inventors to more readily analyze and comprehend the space of possibilities, compare alternatives, and discover entirely new approaches. Encompassing systematic and practical perspectives, the book provides the necessary motivation and strategies as well as a heterogeneous set of comprehensive, illustrative examples. It reveals the importance of heterogeneous data analytics in aiding scientific discoveries and furthers data science as a discipline.

Author : Anuj Karpatne,Ramakrishnan Kannan,Vipin Kumar
Publisher : CRC Press
Page : 520 pages
File Size : 43,9 Mb
Release : 2022-08-15
Category : Business & Economics
ISBN : 9781000598131

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Knowledge Guided Machine Learning by Anuj Karpatne,Ramakrishnan Kannan,Vipin Kumar Pdf

Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML

Author : Turab Lookman,Francis J. Alexander,Krishna Rajan
Publisher : Springer
Page : 307 pages
File Size : 54,9 Mb
Release : 2015-12-12
Category : Technology & Engineering
ISBN : 9783319238715

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Information Science for Materials Discovery and Design by Turab Lookman,Francis J. Alexander,Krishna Rajan Pdf

This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop for materials design) to involve iteratively learning from experiments and calculations to develop materials with optimum properties. Such a loop requires the elements of incorporating domain materials knowledge, a database of descriptors (the genes), a surrogate or statistical model developed to predict a given property with uncertainties, performing adaptive experimental design to guide the next experiment or calculation and aspects of high throughput calculations as well as experiments. The book is about manufacturing with the aim to halving the time to discover and design new materials. Accelerating discovery relies on using large databases, computation, and mathematics in the material sciences in a manner similar to the way used to in the Human Genome Initiative. Novel approaches are therefore called to explore the enormous phase space presented by complex materials and processes. To achieve the desired performance gains, a predictive capability is needed to guide experiments and computations in the most fruitful directions by reducing not successful trials. Despite advances in computation and experimental techniques, generating vast arrays of data; without a clear way of linkage to models, the full value of data driven discovery cannot be realized. Hence, along with experimental, theoretical and computational materials science, we need to add a “fourth leg’’ to our toolkit to make the “Materials Genome'' a reality, the science of Materials Informatics.

Author : Michael Nielsen
Publisher : Princeton University Press
Page : 272 pages
File Size : 42,6 Mb
Release : 2020-04-07
Category : Science
ISBN : 9780691202846

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Reinventing Discovery by Michael Nielsen Pdf

"Reinventing Discovery argues that we are in the early days of the most dramatic change in how science is done in more than 300 years. This change is being driven by new online tools, which are transforming and radically accelerating scientific discovery"--

Author : Martin Braschler,Thilo Stadelmann,Kurt Stockinger
Publisher : Springer
Page : 465 pages
File Size : 43,9 Mb
Release : 2019-06-13
Category : Computers
ISBN : 9783030118211

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Applied Data Science by Martin Braschler,Thilo Stadelmann,Kurt Stockinger Pdf

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.

Author : Francesco L. Gervasio,Vojtech Spiwok,Raimund Mannhold
Publisher : John Wiley & Sons
Page : 420 pages
File Size : 54,5 Mb
Release : 2018-12-10
Category : Medical
ISBN : 9783527806843

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Biomolecular Simulations in Structure-Based Drug Discovery by Francesco L. Gervasio,Vojtech Spiwok,Raimund Mannhold Pdf

A guide to applying the power of modern simulation tools to better drug design Biomolecular Simulations in Structure-based Drug Discovery offers an up-to-date and comprehensive review of modern simulation tools and their applications in real-life drug discovery, for better and quicker results in structure-based drug design. The authors describe common tools used in the biomolecular simulation of drugs and their targets and offer an analysis of the accuracy of the predictions. They also show how to integrate modeling with other experimental data. Filled with numerous case studies from different therapeutic fields, the book helps professionals to quickly adopt these new methods for their current projects. Experts from the pharmaceutical industry and academic institutions present real-life examples for important target classes such as GPCRs, ion channels and amyloids as well as for common challenges in structure-based drug discovery. Biomolecular Simulations in Structure-based Drug Discovery is an important resource that: -Contains a review of the current generation of biomolecular simulation tools that have the robustness and speed that allows them to be used as routine tools by non-specialists -Includes information on the novel methods and strategies for the modeling of drug-target interactions within the framework of real-life drug discovery and development -Offers numerous illustrative case studies from a wide-range of therapeutic fields -Presents an application-oriented reference that is ideal for those working in the various fields Written for medicinal chemists, professionals in the pharmaceutical industry, and pharmaceutical chemists, Biomolecular Simulations in Structure-based Drug Discovery is a comprehensive resource to modern simulation tools that complement and have the potential to complement or replace laboratory assays for better results in drug design.

Author : Margherita Pagani,Renaud Champion
Publisher : Taylor & Francis
Page : 142 pages
File Size : 52,5 Mb
Release : 2023-07-05
Category : Business & Economics
ISBN : 9781000953930

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Artificial Intelligence for Business Creativity by Margherita Pagani,Renaud Champion Pdf

Artificial Intelligence for Business Creativity provides an in-depth examination of the integration of Artificial Intelligence (AI) into the business sector to foster creativity. The book explores the interplay between micro-level individual creativity and macro-level organizational innovation through the lens of AI. It delves into three crucial areas where AI can stimulate business creativity: product and service design, optimized processes, and enhanced organizational collaboration. The authors also highlight the versatility and capability of generative AI systems in promoting creativity and innovation. Intended for business leaders, managers, entrepreneurs, and those interested in AI and creativity, the book offers practical guidance and insightful recommendations on how organizations can effectively utilize AI to enhance their creative process. By offering a comprehensive understanding of the role of AI in fostering creativity, the book equips its readers with the tools to stay ahead in the rapidly changing landscape of AI and creativity. This book is a valuable resource for anyone seeking to understand the impact of AI on business creativity and how to effectively leverage it to foster creativity and innovation in their organization. It is a must-read for anyone looking to increase their knowledge and understanding of AI and its impact on business creativity.

Author : United States. Congress. House. Committee on Appropriations. Subcommittee on the Departments of Labor, Health and Human Services, Education, and Related Agencies
Publisher : Unknown
Page : 1834 pages
File Size : 49,8 Mb
Release : 2012
Category : Administrative agencies
ISBN : MINN:31951D035772423

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Departments of Labor, Health and Human Services, Education, and Related Agencies Appropriations for 2013 by United States. Congress. House. Committee on Appropriations. Subcommittee on the Departments of Labor, Health and Human Services, Education, and Related Agencies Pdf

Author : Anonim
Publisher : Unknown
Page : 132 pages
File Size : 48,7 Mb
Release : 2006
Category : Cancer
ISBN : UCBK:C086898400

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Accelerating Successes Against Cancer by Anonim Pdf

Author : Edward O. Pyzer-Knapp,Matthew Benatan
Publisher : John Wiley & Sons
Page : 213 pages
File Size : 53,8 Mb
Release : 2021-09-21
Category : Science
ISBN : 9781119408352

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Deep Learning for Physical Scientists by Edward O. Pyzer-Knapp,Matthew Benatan Pdf

Discover the power of machine learning in the physical sciences with this one-stop resource from a leading voice in the field Deep Learning for Physical Scientists: Accelerating Research with Machine Learning delivers an insightful analysis of the transformative techniques being used in deep learning within the physical sciences. The book offers readers the ability to understand, select, and apply the best deep learning techniques for their individual research problem and interpret the outcome. Designed to teach researchers to think in useful new ways about how to achieve results in their research, the book provides scientists with new avenues to attack problems and avoid common pitfalls and problems. Practical case studies and problems are presented, giving readers an opportunity to put what they have learned into practice, with exemplar coding approaches provided to assist the reader. From modelling basics to feed-forward networks, the book offers a broad cross-section of machine learning techniques to improve physical science research. Readers will also enjoy: A thorough introduction to the basic classification and regression with perceptrons An exploration of training algorithms, including back propagation and stochastic gradient descent and the parallelization of training An examination of multi-layer perceptrons for learning from descriptors and de-noising data Discussions of recurrent neural networks for learning from sequences and convolutional neural networks for learning from images A treatment of Bayesian optimization for tuning deep learning architectures Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access.

Author : United States,United States. Office of Management and Budget
Publisher : Unknown
Page : 356 pages
File Size : 43,8 Mb
Release : 2006
Category : Budget
ISBN : UIUC:30112065986058

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The Budget of the United States Government by United States,United States. Office of Management and Budget Pdf

Author : Nirav Joshi,Vinod Kushvaha,Priyanka Madhushri
Publisher : Springer Nature
Page : 306 pages
File Size : 48,9 Mb
Release : 2023-05-22
Category : Science
ISBN : 9789819903931

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Machine Learning for Advanced Functional Materials by Nirav Joshi,Vinod Kushvaha,Priyanka Madhushri Pdf

This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material’s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.

Author : Frank Kessel,Patricia Rosenfield Carnegie Corporation of New York,Norman Anderson American Psychological Association
Publisher : Oxford University Press, USA
Page : 510 pages
File Size : 44,7 Mb
Release : 2008-03-11
Category : Psychology
ISBN : 9780198043546

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Interdisciplinary Research : Case Studies from Health and Social Science by Frank Kessel,Patricia Rosenfield Carnegie Corporation of New York,Norman Anderson American Psychological Association Pdf

Interdisciplinary research now receives a great deal of attention because of the rich, creative contributions it often generates. But a host of factors--institutional, interpersonal and intellectual--also make a daunting challenge of conducting research outside one's usual domain. This newly updated and revised edition of Interdisciplinary Research is a substantive and practical guide to the most effective avenues for collaborative and integrative research in the social, behavioral, and bio-medical sciences. It provides answers to questions such as what is the best way to conduct interdisciplinary research on topics related to human health, behavior, and development? Which are the most successful interdisciplinary research programs in these areas? How do you identify appropriate collaborators? How do you find dedicated funding streams? How do you overcome peer-review and publishing challenges? This is the only book that provides answers directly from researchers who have carried out successful interdisciplinary programs. The editors give a concise of account of the lessons that can be taken from the book, and then present a series of case studies that reveal the most successful interdisciplinary research programs. These programs provide a variety of models of how best to undertake interdisciplinary research. Each of the chapter authors has carried out innovative, collaborative programs, and all give compelling accounts of the benefits of interdisciplinary research and the central strategies required to achieve them.

Author : NITA
Publisher : Aspen Publishing
Page : 356 pages
File Size : 45,5 Mb
Release : 2021-08-25
Category : Law
ISBN : 9781601567697

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Pretrial Advocacy by NITA Pdf

Ninety percent of all civil cases never make it the jury; they are resolved through a pretrial process that is today the unsung forum for dispute resolution. Rather than teaching lawyers to abandon evidence and trial skills, Pretrial Advocacy does the opposite; it teaches lawyers that modern litigation is “front loaded” and cases must be prepared with the assumption that they will be tried. As the authors note, it is the rigor of the pretrial process that drives resolution. From the first client interview through motions practice, you will learn to effectively evaluate cases, draft complaints, conduct informal and formal discovery, prepare and respond to motions, negotiate with opposing counsel, and, if necessary, be ready for trial. Pretrial Advocacy is the ideal textbook for law school clinics, law school pretrial litigation courses, and practicing lawyers. Both practical and theoretical, it teaches litigation as a process informed by rules and cases, but also by strategic considerations. Its hands-on and accessible text makes it a perfect reference for learning skills and a continuing reference. Professors and students will benefit from: Practical guidance for each step of representation, backed up by citations and references for deeper understanding of each topic An accessible writing style that puts the needed information right at the reader’s fingertips Tips to foster the attorney’s relationships with clients, opposing counsel, and the court

Author : Wei-tou Ni
Publisher : World Scientific
Page : 636 pages
File Size : 46,5 Mb
Release : 2017-05-26
Category : Science
ISBN : 9789814678513

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One Hundred Years Of General Relativity: From Genesis And Empirical Foundations To Gravitational Waves, Cosmology And Quantum Gravity - Volume 2 by Wei-tou Ni Pdf

The aim of this two-volume title is to give a comprehensive review of one hundred years of development of general relativity and its scientific influences. This unique title provides a broad introduction and review to the fascinating and profound subject of general relativity, its historical development, its important theoretical consequences, gravitational wave detection and applications to astrophysics and cosmology. The series focuses on five aspects of the theory: The first three topics are covered in Volume 1 and the remaining two are covered in Volume 2. While this is a two-volume title, it is designed so that each volume can be a standalone reference volume for the related topic.