Learn how Artificial Intelligence (AI) is being applied in the fashion industry. With an application focused approach, this book provides real-world examples, breaks down technical jargon for non-technical readers, and provides an educational resource for fashion professionals. The book investigates the ways in which AI is impacting every part of the fashion value chain starting with product discovery and working backwards to manufacturing.
Artificial Intelligence for Fashion walks you through concepts, such as connected retail, data mining, and artificially intelligent robotics. Each chapter contains an example of how AI is being applied in the fashion industry illustrated by one major technological theme. There are no equations, algorithms, or code. The technological explanations are cumulative so you'll discover more information about the inner workings of artificial intelligence in practical stages as the book progresses.
What You'll Learn
Gain a basic understanding of AI and how it is used in fashion
Understand key terminology and concepts in AI
Review the new competitive landscape of the fashion industry
Conceptualize and develop new ways to apply AI within the workplace
Who This Book Is For Fashion industry professionals from designers, managers, department heads, and executives can use this book to learn about how AI is impacting roles in every department and profession.
Автор: Linghe Kong; Bowen Wang; Guihai Chen Название: When Compressive Sensing Meets Mobile Crowdsensing ISBN: 9811377758 ISBN-13(EAN): 9789811377754 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data.Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don’t wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. To address these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.
Описание: The purpose of this book is to examine the geospatial and temporal linkage between offshore supply vessels and oil and gas activity in the Outer Continental Shelf Gulf of Mexico, and to model OSV activity expected to result from future lease sales.
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: Gang Yu Название: Operations Research in the Airline Industry ISBN: 1461375134 ISBN-13(EAN): 9781461375135 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of this book is to examine the geospatial and temporal linkage between offshore supply vessels and oil and gas activity in the Outer Continental Shelf Gulf of Mexico, and to model OSV activity expected to result from future lease sales.
Автор: Ram, Mangey Название: Advances In Mathematics For Industry 4.0 ISBN: 0128189061 ISBN-13(EAN): 9780128189061 Издательство: Elsevier Science Рейтинг: Цена: 33013.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Advances in Mathematics for Industry 4.0 examines key tools, techniques, strategies, and methods in engineering applications. By covering the latest knowledge in technology for engineering design and manufacture, chapters provide systematic and comprehensive coverage of key drivers in rapid economic development. Written by leading industry experts, chapter authors explore managing big data in processing information and helping in decision-making, including mathematical and optimization techniques for dealing with large amounts of data in short periods.
Описание: The Fifth European Conference on Industrial Mathematics (ECMI 90) took place at Lahti, Finland on June 6-9, 1990. The conference was organised by the Rolf Nevanlinna Institute together with the Lahti Research and Training Centre of the University of Helsinki. Like its predecessors the Lahti meeting was devoted to the exchange of experience, ideas and methods from various fields of industrial mathematics. The series of ECMI conferences have clearly established an important forum of interaction between the advancing front of technology and one of its crucial development resources, modern applications-oriented mathematics. The precise title of the conferences has been the subject of some discussion and it has been argued that there is no such area which can be labelled as "industrial mathematics." This is certainly true if one thinks only in terms of the range of ideas, theorems, methods and algorithms constituting mathematics all of which may be applied. However with another viewpoint industrial mathematics is not a collection of topics but refers to the interactive process in which mathematics, the science, meets the real world of applications. Ideally this interaction involves both good mathematics and technological advance. The computer revolution has created a new era in technology with the increased computational capability to simulate complex industrial processes, devices, and other technolog- making it possible ical systems. This simulation depends on mathematical modelling and analysis and these techniques, sometimes ingenious but often quite routine, have provided a powerful tool for industrial scientists and creative research management.
Автор: Michiel Hazewinkel; R.M.M. Mattheij; E. van Groese Название: Proceedings of the First European Symposium on Mathematics in Industry ISBN: 9027727309 ISBN-13(EAN): 9789027727305 Издательство: Springer Рейтинг: Цена: 22354.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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