Quantifying Environmental Impact Assessments Using Fuzzy Logic, Richard B. Shepard
Автор: Caers Название: Quantifying Uncertainty in Subsurface Systems ISBN: 1119325838 ISBN-13(EAN): 9781119325833 Издательство: Wiley Рейтинг: Цена: 25019.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Under the Earth's surface is a rich array of geological resources, many with potential use to humankind. However, extracting and harnessing them comes with enormous uncertainties, high costs, and considerable risks. The valuation of subsurface resources involves assessing discordant factors to produce a decision model that is functional and sustainable. This volume provides real-world examples relating to oilfields, geothermal systems, contaminated sites, and aquifer recharge.
Volume highlights include:
A multi-disciplinary treatment of uncertainty quantification
Case studies with actual data that will appeal to methodology developers
A Bayesian evidential learning framework that reduces computation and modeling time
Quantifying Uncertainty in Subsurface Systems is a multidisciplinary volume that brings together five major fields: information science, decision science, geosciences, data science and computer science. It will appeal to both students and practitioners, and be a valuable resource for geoscientists, engineers and applied mathematicians.
Read the Editors' Vox: https: //eos.org/editors-vox/quantifying-uncertainty-about-earths-resources
Reviews, The Leading Edge, SEG, May 2020
The subsurface medium created by geologic processes is not always well understood. The data we collect in an attempt to characterize the subsurface can be incomplete and inaccurate. However, if we understand the uncertainty of our data and the models we generate from them, we can make better decisions regarding the management of subsurface resources. Modeling and managing subsurface resources, and properly characterizing and understanding the uncertainties, requires the integration of a variety of scientific and engineering disciplines.
Five case studies are outlined in the introductory chapter, which are used to demonstrate various methods throughout the book. The second chapter introduces the basic notions in decision analysis. Uncertainty quantification is only relevant within the decision framework used. Models alone do not quantify uncertainty, but do allow the determination of key variables that influence models and decisions. Next, an overview of the various data science methods relevant to uncertainty quantification in the subsurface is provided. Sensitivity analysis is then covered, specifically Monte Carlo-based sensitivity analysis. The next three chapters develop the Bayesian approach to uncertainty quantification, and this is the focus of the book.
All of this is brought together in Chapter 8, which describes a solution regarding quantifying the uncertainties for each of the problems presented in the first chapter. The authors admit that it is not the only solution. No single solution fits all problems of uncertainty quantification. The results in this chapter allow the reader to see the previously described methods applied and how choices influence models and decisions. The final two chapters discuss various software components necessary to implement the strategies presented in the book and challenges faced in the future of uncertainty quantification.
The book uses a number of relevant subsurface problems to explore the various aspects of uncertainty quantification. Understanding uncertainty, and how it affects modeling and decision outcomes, is not always straightforward. However, it is necessary in order to make good, consistent decisions. The book is not an easy read. Some portions require good mathematical understanding of the underlying principles. However, the book is well documented and organized. I would say that is not a good book for a beginner, but it is a good resource for someone to get a grounding to go further into the subject. I appreciate the authors putting together this book on a complex problem that is important to our industry.
-- Da
Автор: Sauro, Jeff Название: Quantifying the User Experience ISBN: 0128023082 ISBN-13(EAN): 9780128023082 Издательство: Elsevier Science Рейтинг: Цена: 7241.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "
Quantifying the User Experience: Practical Statistics for User Research, Second Edition, " provides practitioners and researchers with the information they need to confidently quantify, qualify, and justify their data. The book presents a practical guide on how to use statistics to solve common quantitative problems that arise in user research. It addresses questions users face every day, including, Is the current product more usable than our competition? Can we be sure at least 70% of users can complete the task on their first attempt? How long will it take users to purchase products on the website?
This book provides a foundation for statistical theories and the best practices needed to apply them. The authors draw on decades of statistical literature from human factors, industrial engineering, and psychology, as well as their own published research, providing both concrete solutions (Excel formulas and links to their own web-calculators), along with an engaging discussion on the statistical reasons why tests work and how to effectively communicate results. Throughout this new edition, users will find updates on standardized usability questionnaires, a new chapter on general linear modeling (correlation, regression, and analysis of variance), with updated examples and case studies throughout. Completely updated to provide practical guidance on solving usability testing problems with statistics for any project, including those using Six Sigma practicesIncludes new and revised information on standardized usability questionnaires, as well as general linear modeling (correlation, regression, and analysis of variance)Shows practitioners which test to use, why they work, and best practices for application, along with easy-to-use Excel formulas and web-calculators for analyzing dataRecommends ways for researchers and practitioners to communicate results to stakeholders in plain English
Описание: This thesis demonstrates the adaptation of existing techniques and principles towards enabling clean and precise measurements of biomolecules interacting with inorganic surfaces. In particular, it includes real-time measurement of serum proteins interacting with engineered nanomaterial. Making meaningful and unambiguous measurements has been an evolving problem in the field of biology and its various allied domains, primarily due to the complex nature of experiments and the large number of possible interferants. The subsequent quantification of interactions between biomolecules and inorganic surfaces solves pressing problems in the rapidly developing fields of lipidomics and nanomedicine.
Автор: Bowman, Alan; Wilson, Andrew Название: Quantifying the Roman Economy ISBN: 0199679290 ISBN-13(EAN): 9780199679294 Издательство: Oxford Academ Рейтинг: Цена: 6414.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The first volume in a new series, Oxford Studies on the Roman Economy: a collection of essays, edited by the series editors, focusing on the economic performance of the Roman empire, and suggesting how we can derive a quantified account of economic growth and contraction in the period of the empire`s greatest extent and prosperity.
Описание: In this thesis, the author makes several contributions to thestudy of design of graphical materials. The thesis begins with a review of therelationship between design and aesthetics, and the use of mathematical modelsto capture this relationship. Then, a novel method for linking linguistic concepts to colorsusing the Latent Dirichlet Allocation Dual Topic Model is proposed. Next, the thesis studies the relationship between aesthetics and spatial layout by formalizing the notion of visual balance. Applying principles of salience and Gaussian mixture models over a body of about 120,000 aesthetically rated professional photographs, the author provides confirmation of Arnhem's theory about spatial layout. The thesis concludes with a description oftools to support automatically generating personalized design.
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