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Showing 70,126 through 70,150 of 73,524 results

Uncanny Valley: A Memoir

by Anna Wiener

The prescient, page-turning account of a journey in Silicon Valley: a defining memoir of our digital age <P><P>In her mid-twenties, at the height of tech industry idealism, Anna Wiener—stuck, broke, and looking for meaning in her work, like any good millennial--left a job in book publishing for the promise of the new digital economy. She moved from New York to San Francisco, where she landed at a big-data startup in the heart of the Silicon Valley bubble: a world of surreal extravagance, dubious success, and fresh-faced entrepreneurs hell-bent on domination, glory, and, of course, progress. <P><P>Anna arrived amidst a massive cultural shift, as the tech industry rapidly transformed into a locus of wealth and power rivaling Wall Street. But amid the company ski vacations and in-office speakeasies, boyish camaraderie and ride-or-die corporate fealty, a new Silicon Valley began to emerge: one in far over its head, one that enriched itself at the expense of the idyllic future it claimed to be building. Part coming-of-age-story, part portrait of an already-bygone era, Anna Wiener’s memoir is a rare first-person glimpse into high-flying, reckless startup culture at a time of unchecked ambition, unregulated surveillance, wild fortune, and accelerating political power. With wit, candor, and heart, Anna deftly charts the tech industry’s shift from self-appointed world savior to democracy-endangering liability, alongside a personal narrative of aspiration, ambivalence, and disillusionment. <P><P>Unsparing and incisive, Uncanny Valley is a cautionary tale, and a revelatory interrogation of a world reckoning with consequences its unwitting designers are only beginning to understand.

The Uncanny Valley in Games and Animation

by Angela Tinwell

Advances in technology have enabled animators and video game designers to design increasingly realistic, human-like characters in animation and games. Although it was intended that this increased realism would allow viewers to appreciate the emotional state of characters, research has shown that audiences often have a negative reaction as the human

Uncertain Archives: Critical Keywords for Big Data

by Nanna Bonde Thylstrup Daniela Agostinho Annie Ring Catherine D'Ignazio Kristin Veel

Scholars from a range of disciplines interrogate terms relevant to critical studies of big data, from abuse and aggregate to visualization and vulnerability.This pathbreaking work offers an interdisciplinary perspective on big data, interrogating key terms. Scholars from a range of disciplines interrogate concepts relevant to critical studies of big data--arranged glossary style, from from abuse and aggregate to visualization and vulnerability--both challenging conventional usage of such often-used terms as prediction and objectivity and introducing such unfamiliar ones as overfitting and copynorm. The contributors include both leading researchers, including N. Katherine Hayles, Johanna Drucker and Lisa Gitelman, and such emerging agenda-setting scholars as Safiya Noble, Sarah T. Roberts and Nicole Starosielski.

Uncertain Dynamical Systems: Stability and Motion Control

by A.A. Martynyuk Yu. A. Martynyuk-Chernienko

This self-contained book provides systematic instructive analysis of uncertain systems of the following types: ordinary differential equations, impulsive equations, equations on time scales, singularly perturbed differential equations, and set differential equations. Each chapter contains new conditions of stability of unperturbed motion of the abo

Uncertain Graph and Network Optimization (Springer Uncertainty Research)

by Bo Zhang Jin Peng

This first book focuses on uncertain graph and network optimization. It covers three different main contents: uncertain graph, uncertain programming and uncertain network optimization. It also presents applications of uncertain network optimization in a lot of real problems such as transportation problems, dispatching medical supplies problems and location problems.The book is suitable for researchers, engineers, teachers and students in the field of mathematics, information science, computer science, decision science, management science and engineering, artificial intelligence, industrial engineering, economics and operations research.

Uncertain Information and Linear Systems (Studies in Systems, Decision and Control #254)

by Tofigh Allahviranloo

This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.

Uncertain Optimal Control (Springer Uncertainty Research Ser.)

by Yuanguo Zhu

This book introduces the theory and applications of uncertain optimal control, and establishes two types of models including expected value uncertain optimal control and optimistic value uncertain optimal control. These models, which have continuous-time forms and discrete-time forms, make use of dynamic programming. The uncertain optimal control theory relates to equations of optimality, uncertain bang-bang optimal control, optimal control with switched uncertain system, and optimal control for uncertain system with time-delay. Uncertain optimal control has applications in portfolio selection, engineering, and games. The book is a useful resource for researchers, engineers, and students in the fields of mathematics, cybernetics, operations research, industrial engineering, artificial intelligence, economics, and management science.

Uncertainties in Peasant Farming: A Colombian Case (LSE Monographs on Social Anthropology)

by Sutti Ortiz

This book examines the life and historical background of the Paez peasants of Colombia and their relationship with the land, including issues of tenure, inheritance and the allocation of resources.

Uncertainty Analysis of Experimental Data with R

by Benjamin Shaw

"This would be an excellent book for undergraduate, graduate and beyond….The style of writing is easy to read and the author does a good job of adding humor in places. The integration of basic programming in R with the data that is collected for any experiment provides a powerful platform for analysis of data…. having the understanding of data analysis that this book offers will really help researchers examine their data and consider its value from multiple perspectives – and this applies to people who have small AND large data sets alike! This book also helps people use a free and basic software system for processing and plotting simple to complex functions." Michelle Pantoya, Texas Tech University Measurements of quantities that vary in a continuous fashion, e.g., the pressure of a gas, cannot be measured exactly and there will always be some uncertainty with these measured values, so it is vital for researchers to be able to quantify this data. Uncertainty Analysis of Experimental Data with R covers methods for evaluation of uncertainties in experimental data, as well as predictions made using these data, with implementation in R. The books discusses both basic and more complex methods including linear regression, nonlinear regression, and kernel smoothing curve fits, as well as Taylor Series, Monte Carlo and Bayesian approaches. Features: 1. Extensive use of modern open source software (R). 2. Many code examples are provided. 3. The uncertainty analyses conform to accepted professional standards (ASME). 4. The book is self-contained and includes all necessary material including chapters on statistics and programming in R. Benjamin D. Shaw is a professor in the Mechanical and Aerospace Engineering Department at the University of California, Davis. His research interests are primarily in experimental and theoretical aspects of combustion. Along with other courses, he has taught undergraduate and graduate courses on engineering experimentation and uncertainty analysis. He has published widely in archival journals and became an ASME Fellow in 2003.

The Uncertainty Analysis of Model Results: A Practical Guide

by Eduard Hofer

This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.

Uncertainty and Artificial Intelligence: Additive Manufacturing, Vibratory Control, Agro-composite, Mechatronics

by Abdelkhalak El Hami

Today's information technology, along with Artificial Intelligence (AI), is moving towards total communication between all computerized systems. AI is a representation of human intelligence based on the creation and application of algorithms in specific computer environments. Its aim is to enable computers to act like human beings. For it to work, this type of technology requires computer systems, data with management systems and advanced algorithms, used by AI. In mechanical engineering, AI can offer many possibilities: in mechanical construction, predictive maintenance, plant monitoring, robotics, additive manufacturing, materials, vibration control and agro composites, among many others. This book is dedicated to Artificial Intelligence uncertainties in mechanical problems. Each chapter clearly sets out used and developed illustrative examples. Aimed at students, Uncertainty and Artificial Intelligence is also a valuable resource for practicing engineers and research lecturers.

Uncertainty and Ground Conditions: A Risk Management Approach

by Martin van Staveren

All civil engineering and construction projects require some sort of solid foundation, but ground conditions bring some degree of uncertainty to every project. Dealing properly with uncertainty over ground conditions can make the difference between the commercial success and failure of a project.With the costs of failing to accurately predict groun

Uncertainty and Imprecision in Decision Making and Decision Support: Selected Papers from BOS-2018, held on September 24-26, 2018, and IWIFSGN-2018, held on September 27-28, 2018 in Warsaw, Poland (Advances in Intelligent Systems and Computing #1081)

by Krassimir T. Atanassov Vassia Atanassova Janusz Kacprzyk Andrzej Kaluszko Maciej Krawczak Jan W. Owsinski Sotir Sotirov Evdokia Sotirova Eulalia Szmidt Slawomir Zadrozny

This book gathers selected papers from two important conferences held on October 24–28, 2018, in Warsaw, Poland: theFifteenth National Conference of Operational and Systems Research, BOS-2018, one of the leading conferences in the field of operational and systems research not only in Poland but also at the European level; andthe Seventeenth International Workshop on Intuitionistic Fuzzy Sets and General Nets, IWIFSGN-2018, one of thepremiere conferences on fuzzy logic.The papers presented here constitute a fair and comprehensive representation of the topics covered by both BOS-2018 and IWIFSGN-2018, includingextensions of the traditional fuzzy sets, in particular on the intuitionistic fuzzy sets, as well as other topics in uncertainty and imprecision modeling, the Generalized Nets (GNs), a powerful extension of the traditional Petri net paradigm, and InterCriteria Analysis, a new method for feature selection and analyses in multicriteria and multi-attribute decision-making problems. The Workshop was dedicated to the memory of Professor Beloslav Riečan (1936–2018), a regular participant at the IWIFSGN workshops.

Uncertainty and Imprecision in Decision Making and Decision Support: Selected papers from BOS-2020, held on December 14-15, 2020, and IWIFSGN-2020, held on December 10-11, 2020 in Warsaw, Poland (Lecture Notes in Networks and Systems #338)

by Krassimir T. Atanassov Vassia Atanassova Janusz Kacprzyk Andrzej Kałuszko Maciej Krawczak Jan W. Owsiński Sotir S. Sotirov Evdokia Sotirova Eulalia Szmidt Sławomir Zadrożny

This book is composed of selected papers from the Sixteenth National Conference on Operational and Systems Research, BOS-2020, held on December 14-15, 2020, one of premiere conferences in the field of operational and systems research. The second is the Nineteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2020, held on December 10-11, 2020, in Warsaw, Poland, in turn—one of premiere conferences on fuzzy logic, notably on extensions of the traditional fuzzy sets, also comprising a considerable part on the generalized nets (GNs), an important extension of the traditional Petri nets. A joint publication of selected papers from the two conferences follows a long tradition of such a joint organization and—from a substantial point of view—combines systems modeling, systems analysis, broadly perceived operational research, notably optimization, decision making, and decision support, with various aspects of uncertain and imprecise information and their related tools and techniques.

Uncertainty and Imprecision in Decision Making and Decision Support - New Advances, Challenges, and Perspectives: Selected Papers from BOS/SOR-2022, Held on October 13-15, 2022, and IWIFSGN-2022, Held on October 13-14, 2022, in Warsaw, Poland (Lecture Notes in Networks and Systems #793)

by Krassimir T. Atanassov Vassia Atanassova Janusz Kacprzyk Andrzej Kałuszko Maciej Krawczak Jan W. Owsiński Sotir S. Sotirov Evdokia Sotirova Eulalia Szmidt Sławomir Zadrożny

This volume is composed of selected papers from two conferences held in Warsaw, Poland on October 13-15, 2022: the BOS/SOR’2022 - National Conference on Operational and Systems Research, one of premiere conferences in the field of operational and systems research, and the Twentith International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN-2022, one of premiere conferences on fuzzy logic, notably on extensions of the traditional fuzzy sets, also comprising a considerable part on the Generalized Nets (GNs). A joint publication of selected papers from the two conferences follows a long tradition of such a joint organization, and – from a substantial point of view – combines systems modeling, systems analysis, broadly perceived operational research, notably optimization, decision making and decision support, with various aspects of uncertain and imprecise information and their related tools and techniques.

Uncertainty and Optimization in Structural Mechanics (Focus Ser.)

by Abdelkhalak El Hami Bouchaib Radi

Optimization is generally a reduction operation of a definite quantity. This process naturally takes place in our environment and through our activities. For example, many natural systems evolve, in order to minimize their potential energy. Modeling these phenomena then largely relies on our capacity to artificially reproduce these processes. In parallel, optimization problems have quickly emerged from human activities, notably from economic concerns. This book includes the most recent ideas coming from research and industry in the field of optimization, reliability and the recognition of accompanying uncertainties. It is made up of eight chapters which look at the reviewing of uncertainty tools, system reliability, optimal design of structures and their optimization (of sizing, form, topology and multi-objectives) – along with their robustness and issues on optimal safety factors. Optimization reliability coupling will also be tackled in order to take into account the uncertainties in the modeling and resolution of the problems encountered. The book is aimed at students, lecturers, engineers, PhD students and researchers. Contents 1. Uncertainty. 2. Reliability in Mechanical Systems. 3. Optimal Structural Design. 4. Multi-object Optimization with Uncertainty. 5. Robust Optimization. 6. Reliability Optimization. 7. Optimal Security Factors Approach. 8. Reliability-based Topology Optimization. About the Authors Abdelkhalak El Hami is Professor at the Institut National des Sciences Appliquées, Rouen, France. He is the author of many articles and books on optimization and uncertainty. Bouchaib Radi is Professor in the Faculty of Sciences and Technology at the University of Hassan Premier, Settat, Morocco. His research interests are in such areas as structural optimization, parallel computation, contact problem and metal forming. He is the author of many scientific articles and books.

Uncertainty-aware Integration of Control with Process Operations and Multi-parametric Programming Under Global Uncertainty (Springer Theses)

by Vassilis M. Charitopoulos

This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations. The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods. Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.

Uncertainty-Based Ship Design Optimization: Theory and Method

by Xiao Wei Zuyuan Liu Baiwei Feng Haichao Chang

The book focused on the basic bottleneck issues in the ship uncertainty-based design optimization. Based on the concepts of robustness and reliability design, uncertainty classification, uncertainty modeling, uncertainty analysis and propagation methods were systematically explained, revealing the influence mechanism and rules of multi-source aleatory and epistemic uncertainty on ship design. Finally, a hull form design optimization method with mixed uncertainty was established. The theory of uncertainty design optimization is not yet mature, and this book gives a detailed introduction. The illustrations and tables in this book compared the differences between uncertainty-based optimization and traditional deterministic optimization, reflecting the advantages of uncertainty optimization. This book will be a useful reference for researchers and engineers in the field of ship design.

Uncertainty by Design: Preparing for the Future with Scenario Technology (Expertise: Cultures and Technologies of Knowledge)

by Limor Samimian-Darash

In Uncertainty by Design Limor Samimian-Darash presents cases of the use of scenario technology in the fields of security and emergency preparedness, energy, and health by analyzing scenario narratives and practices at the National Emergency Management Authority in Israel, the World Health Organization's Regional Office for Europe, and the World Energy Council. Humankind has long struggled with the uncertainty of the future, with how to foresee the future, imagine alternatives, or prepare for and guard against undesirable eventualities. Scenario—or scenario planning—emerged in recent decades to become a widespread means through which states, large corporations, and local organizations imagine and prepare for the future. The scenario technology cases examined in Uncertainty by Design provide a useful lens through which to view contemporary efforts to engage in an overall journey of discovering the future, along with the modality of governing involved in these endeavors to face future uncertainties. Collectively, they enable us to understand in depth how scenarios express a new governing modality.

Uncertainty, Constraints, and Decision Making (Studies in Systems, Decision and Control #484)

by Martine Ceberio Vladik Kreinovich

In the first approximation, decision making is nothing else but an optimization problem: We want to select the best alternative. This description, however, is not fully accurate: it implicitly assumes that we know the exact consequences of each decision, and that, once we have selected a decision, no constraints prevent us from implementing it. In reality, we usually know the consequences with some uncertainty, and there are also numerous constraints that needs to be taken into account. The presence of uncertainty and constraints makes decision making challenging. To resolve these challenges, we need to go beyond simple optimization, we also need to get a good understanding of how the corresponding systems and objects operate, a good understanding of why we observe what we observe – this will help us better predict what will be the consequences of different decisions. All these problems – in relation to different application areas – are the main focus of this book.

Uncertainty in Acoustics: Measurement, Prediction and Assessment

by Robert Peters

This guide to estimating uncertainties in the measurement, prediction and assessment of noise and vibration applies across environmental noise and vibration, occupational noise and vibration exposure, and building and architectural acoustics. The book collates information from the various Standards and from research, with explanation, examples and case studies. It enables estimation of uncertainty in the measurement and prediction of acoustic quantities, suitable for use in environmental impact and occupational exposure assessments. It is for acoustic consultants, mechanical and building service engineers, architect and building professionals and environmental health officers. Bob Peters worked for more than forty years in acoustics and noise control – teaching, research, consultancy. He was a principal acoustic consultant with Applied Acoustic Design, a senior research fellow at London South Bank University, and a tutor on Institute of Acoustics distance learning courses.

Uncertainty in Complex Networked Systems: In Honor of Roberto Tempo (Systems & Control: Foundations & Applications)

by Tamer Başar

The chapters in this volume, and the volume itself, celebrate the life and research of Roberto Tempo, a leader in the study of complex networked systems, their analysis and control under uncertainty, and robust designs. Contributors include authorities on uncertainty in systems, robustness, networked and network systems, social networks, distributed and randomized algorithms, and multi-agent systems—all fields that Roberto Tempo made vital contributions to. Additionally, at least one author of each chapter was a research collaborator of Roberto Tempo’s.This volume is structured in three parts. The first covers robustness and includes topics like time-invariant uncertainties, robust static output feedback design, and the uncertainty quartet. The second part is focused on randomization and probabilistic methods, which covers topics such as compressive sensing, and stochastic optimization. Finally, the third part deals with distributed systems and algorithms, and explores matters involving mathematical sociology, fault diagnoses, and PageRank computation.Each chapter presents exposition, provides new results, and identifies fruitful future directions in research. This book will serve as a valuable reference volume to researchers interested in uncertainty, complexity, robustness, optimization, algorithms, and networked systems.

Uncertainty in Engineering: Introduction to Methods and Applications (SpringerBriefs in Statistics)

by Louis J. M. Aslett Frank P. A. Coolen Jasper De Bock

This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners.

Uncertainty in Mechanical Engineering: Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), June 7–8, 2021 (Lecture Notes in Mechanical Engineering)

by Peter F. Pelz Peter Groche

This open access book reports on methods and technologies to describe, evaluate and control uncertainty in mechanical engineering applications. It brings together contributions by engineers, mathematicians and legal experts, offering a multidisciplinary perspective on the main issues affecting uncertainty throughout the complete system lifetime, which includes process and product planning, development, production and usage. The book is based on the proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering (ICUME 2021), organized by the Collaborative Research Center (CRC) 805 of the TU Darmstadt, and held online on June 7–8, 2021. All in all, it offers a timely resource for researchers, graduate students and practitioners in the field of mechanical engineering, production engineering and engineering optimization.

Uncertainty Management for Robust Industrial Design in Aeronautics: Findings and Best Practice Collected During UMRIDA, a Collaborative Research Project (2013–2016) Funded by the European Union (Notes on Numerical Fluid Mechanics and Multidisciplinary Design #140)

by Charles Hirsch Dirk Wunsch Jacek Szumbarski Łukasz Łaniewski-Wołłk Jordi Pons-Prats

This book covers cutting-edge findings related to uncertainty quantification and optimization under uncertainties (i.e. robust and reliable optimization), with a special emphasis on aeronautics and turbomachinery, although not limited to these fields. It describes new methods for uncertainty quantification, such as non-intrusive polynomial chaos, collocation methods, perturbation methods, as well as adjoint based and multi-level Monte Carlo methods. It includes methods for characterization of most influential uncertainties, as well as formulations for robust and reliable design optimization. A distinctive element of the book is the unique collection of test cases with prescribed uncertainties, which are representative of the current engineering practice of the industrial consortium partners involved in UMRIDA, a level 1 collaborative project within the European Commission's Seventh Framework Programme (FP7). All developed methods are benchmarked against these industrial challenges. Moreover, the book includes a section dedicated to Best Practice Guidelines for uncertainty quantification and robust design optimization, summarizing the findings obtained by the consortium members within the UMRIDA project. All in all, the book offers a authoritative guide to cutting-edge methodologies for uncertainty management in engineering design, covers a wide range of applications and discusses new ideas for future research and interdisciplinary collaborations.

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