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Uncanny Valley: A Memoir
by Anna WienerThe 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.
Uncentering the Earth: Copernicus and the Revolutions of the Heavenly Spheres
by William T. VollmanOne of the books in a series called Great Discoveries, which presents good science in the clearest possible way.
Uncertain Climes: Debating Climate Change in Gilded Age America
by Joseph GiacomelliUncertain Climes looks to the late nineteenth century to reveal how climate anxiety was a crucial element in the emergence of American modernity. Even people who still refuse to accept the reality of human-induced climate change would have to agree that the topic has become inescapable in the United States in recent decades. But as Joseph Giacomelli shows in Uncertain Climes, this is actually nothing new: as far back as Gilded Age America, climate uncertainty has infused major debates on economic growth and national development. In this ambitious examination of late-nineteenth-century understandings of climate, Giacomelli draws on the work of scientists, foresters, surveyors, and settlers to demonstrate how central the subject was to the emergence of American modernity. Amid constant concerns about volatile weather patterns and the use of natural resources, nineteenth-century Americans developed a multilayered discourse on climate and what it might mean for the nation’s future. Although climate science was still in its nascent stages during the Gilded Age, fears and hopes about climate change animated the overarching political struggles of the time, including expansion into the American West. Giacomelli makes clear that uncertainty was the common theme linking concerns about human-induced climate change with cultural worries about the sustainability of capitalist expansionism in an era remarkably similar to the United States’ unsettled present.
Uncertain Graph and Network Optimization (Springer Uncertainty Research)
by Bo Zhang Jin PengThis 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 Peril: Genetic Engineering and the Future of Seeds
by Claire Hope CummingsAfter serving as an environmental lawyer for 20 years, four of them with the US Department of Agriculture, Cummings is now a writer and broadcast reporter based in rural northern California. Here she presents a cautionary account of genetic engineering as it is being used in agriculture, though she suggests that many of her findings could apply to its use in medicine, biological warfare, and other areas as well. Her topics include trade secrets, the ownership society, the botany of scarcity, and a conversation with corn. Annotation ©2008 Book News, Inc. , Portland, OR (booknews. com)
Uncertainty: Einstein, Heisenberg, Bohr, and the Struggle for the Soul of Science
by David LindleyThe more precisely the position is determined, the less precisely the momentum is known in this instant, and vice versa. --Werner Heisenberg <P> That God would choose to play dice with the world is something I cannot believe. --Albert Einstein <P> Nothing exists until it is measured. --Neils Bohr <P> The remarkable story of a startling scientific idea that ignited a battle among the greatest minds of the twentieth century and profoundly influenced intellectual inquiry in fields ranging from physics to literary criticism, anthropology and journalism In 1927, the young German physicist Werner Heisenberg challenged centuries of scientific understanding when he introduced what came to be known as "the uncertainty principle. " Building on his own radical innovations in quantum theory, Heisenberg proved that in many physical measurements, you can obtain one bit of information only at the price of losing another. Heisenberg's principle implied that scientific quantities/concepts do not have absolute, independent meaning, but acquire meaning only in terms of the experiments used to measure them. This proposition, undermining the cherished belief that science could reveal the physical world with limitless detail and precision, placed Heisenberg in direct opposition to the revered Albert Einstein. The eminent scientist Niels Bohr, Heisenberg's mentor and Einstein's long-time friend, found himself caught between the two. Uncertaintychronicles the birth and evolution of one of the most significant findings in the history of science, and portrays the clash of ideas and personalities it provoked. Einstein was emotionally as well as intellectually determined to prove the uncertainty principle false. Heisenberg represented a new generation of physicists who believed that quantum theory overthrew the old certainties; confident of his reasoning, Heisenberg dismissed Einstein's objections. Bohr understood that Heisenberg was correct, but he also recognized the vital necessity of gaining Einstein's support as the world faced the shocking implications of Heisenberg's principle.
Uncertainty Analyses in Environmental Sciences and Hydrogeology: Methods and Applications to Subsurface Contamination (SpringerBriefs in Applied Sciences and Technology)
by Rachid Ababou Juliette Chastanet Jean-Marie Côme Manuel Marcoux Michel QuintardThis book highlights several methods and quantitative implementations of both probabilistic and fuzzy-based approaches to uncertainty quantification and uncertainty propagation through environmental subsurface pollution models with uncertain input parameters. The book focuses on methods as well as applications in hydrogeology, soil hydrology, groundwater contamination, and related areas (e.g., corrosion of nuclear waste canisters). The methods are illustrated for a broad spectrum of models, from non-differential I/O models to complex PDE solvers, including a novel 3D quasi-analytical model of contaminant transport, and a site-specific computer model of dissolved contaminant migration from a DNAPL (Dense Non Aqueous Phase Liquid) pollution source.
The Uncertainty Analysis of Model Results: A Practical Guide
by Eduard HoferThis 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-aware Integration of Control with Process Operations and Multi-parametric Programming Under Global Uncertainty (Springer Theses)
by Vassilis M. CharitopoulosThis 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.
The Uncertainty Business: Risks and Opportunities in Weather and Climate
by W. J. MaunderOriginally published in 1986, this book discusses the value of weather and climate information in government and business decision-making. It issues a strong manifesto for the development of new areas of research requiring the skills of weather scientists, geographers, economists, planners and political scientists. It offers a coherent and non-technical presentation of this climatology, supported with practical guidance on assessing the impacts of weather and climate on human affairs.
Uncertainty, Calibration and Probability: The Statistics of Scientific and Industrial Measurement
by C.F DietrichAll measurements are subject to error because no quantity can be known exactly; hence, any measurement has a probability of lying within a certain range. The more precise the measurement, the smaller the range of uncertainty. Uncertainty, Calibration and Probability is a comprehensive treatment of the statistics and methods of estimating these calibration uncertainties. The book features the general theory of uncertainty involving the combination (convolution) of non-Gaussian, student t, and Gaussian distributions; the use of rectangular distributions to represent systematic uncertainties; and measurable and nonmeasurable uncertainties that require estimation. The author also discusses sources of measurement errors and curve fitting with numerous examples of uncertainty case studies. Many useful tables and computational formulae are included as well. All formulations are discussed and demonstrated with the minimum of mathematical knowledge assumed. This second edition offers additional examples in each chapter, and detailed additions and alterations made to the text. New chapters consist of the general theory of uncertainty and applications to industry and a new section discusses the use of orthogonal polynomials in curve fitting. Focusing on practical problems of measurement, Uncertainty, Calibration and Probability is an invaluable reference tool for R&D laboratories in the engineering/manufacturing industries and for undergraduate and graduate students in physics, engineering, and metrology.
Uncertainty in Biology
by Liesbet Geris David Gomez-CabreroComputational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process. This book wants to address four main issues related to the building and validation of computational models of biomedical processes: 1. Modeling establishment under uncertainty 2. Model selection and parameter fitting 3. Sensitivity analysis and model adaptation 4. Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples. This book is intended for graduate students and researchers active in the field of computational modeling of biomedical processes who seek to acquaint themselves with the different ways in which to study the parameter space of their model as well as its overall behavior.
Uncertainty in Complex Networked Systems: In Honor of Roberto Tempo (Systems & Control: Foundations & Applications)
by Tamer BaşarThe 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 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 GrocheThis 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-PratsThis 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.
Uncertainty Quantification
by Christian SoizeAdvanced Computational Vibroacoustics presents an advanced computational method for the prediction of sound and structural vibrations, in low- and medium-frequency ranges - complex structural acoustics and fluid-structure interaction systems encountered in aerospace, automotive, railway, naval, and energy-production industries. The formulations are presented within a unified computational strategy and are adapted for the present and future generation of massively parallel computers. A reduced-order computational model is constructed using the finite element method for the damped structure and the dissipative internal acoustic fluid (gas or liquid with or without free surface) and using an appropriate symmetric boundary-element method for the external acoustic fluid (gas or liquid). This book allows direct access to computational methods that have been adapted for the future evolution of general commercial software. Written for the global market, it is an invaluable resource for academic researchers, graduate students, and practising engineers.
Uncertainty Quantification in Computational Fluid Dynamics
by Hester Bijl Didier Lucor Siddhartha Mishra Christoph SchwabFluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.
Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines (SpringerBriefs in Applied Sciences and Technology)
by Francesco MontomoliThis book introduces design techniques developed to increase the safety of aircraft engines, and demonstrates how the application of stochastic methods can overcome problems in the accurate prediction of engine lift caused by manufacturing error. This in turn addresses the issue of achieving required safety margins when hampered by limits in current design and manufacturing methods. The authors show that avoiding the potential catastrophe generated by the failure of an aircraft engine relies on the prediction of the correct behaviour of microscopic imperfections. This book shows how to quantify the possibility of such failure, and that it is possible to design components that are inherently less risky and more reliable.This new, updated and significantly expanded edition gives an introduction to engine reliability and safety to contextualise this important issue, evaluates newly-proposed methods for uncertainty quantification as applied to jet engines.Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines will be of use to gas turbine manufacturers and designers as well as CFD practitioners, specialists and researchers. Graduate and final year undergraduate students in aerospace or mathematical engineering may also find it of interest.
Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines
by Francesco Montomoli Mauro Carnevale Antonio D'Ammaro Michela Massini Simone SalvadoriThis book introduces novel design techniques developed to increase the safety of aircraft engines. The authors demonstrate how the application of uncertainty methods can overcome problems in the accurate prediction of engine lift, caused by manufacturing error. This in turn ameliorates the difficulty of achieving required safety margins imposed by limits in current design and manufacturing methods. This text shows that even state-of-the-art computational fluid dynamics (CFD) are not able to predict the same performance measured in experiments; CFD methods assume idealised geometries but ideal geometries do not exist, cannot be manufactured and their performance differs from real-world ones. By applying geometrical variations of a few microns, the agreement with experiments improves dramatically, but unfortunately the manufacturing errors in engines or in experiments are unknown. In order to overcome this limitation, uncertainty quantification considers the probability density functions of manufacturing errors. It is then possible to predict the overall variation of the jet engine performance using stochastic techniques. Uncertainty Quantification in Computational Fluid Dynamics and Aircraft Engines demonstrates that some geometries are not affected by manufacturing errors, meaning that it is possible to design safer engines. Instead of trying to improve the manufacturing accuracy, uncertainty quantification when applied to CFD is able to indicate an improved design direction. This book will be of interest to gas turbine manufacturers and designers as well as CFD practitioners, specialists and researchers. Graduate and final year undergraduate students may also find it of use.
Uncertainty Quantification in Laminated Composites: A Meta-model Based Approach
by Sudip Dey Tanmoy Mukhopadhyay Sondipon AdhikariOver the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.
Uncertainty Quantification of Stochastic Defects in Materials (Emerging Materials and Technologies)
by Liu ChuUncertainty Quantification of Stochastic Defects in Materials investigates the uncertainty quantification methods for stochastic defects in material microstructures. It provides effective supplementary approaches for conventional experimental observation with the consideration of stochastic factors and uncertainty propagation. Pursuing a comprehensive numerical analytical system, this book establishes a fundamental framework for this topic, while emphasizing the importance of stochastic and uncertainty quantification analysis and the significant influence of microstructure defects on the material macro properties. Key Features Consists of two parts: one exploring methods and theories and the other detailing related examples Defines stochastic defects in materials and presents the uncertainty quantification for defect location, size, geometrical configuration, and instability Introduces general Monte Carlo methods, polynomial chaos expansion, stochastic finite element methods, and machine learning methods Provides a variety of examples to support the introduced methods and theories Applicable to MATLAB and ANSYS software This book is intended for advanced students interested in material defect quantification methods and material reliability assessment, researchers investigating artificial material microstructure optimization, and engineers working on defect influence analysis and nondestructive defect testing.
Uncharted
by Erez AidenBreaking open Big Data, two Harvard scientists reveal a ground-breaking way of looking at history and culture. One of the greatest untapped resources of today isn’t offshore oil or natural gas-it’s data. Gigabytes, exabytes (that’s one quintillion bytes) of data are sitting on servers across the world. So how can we start to access this explosion of information, this "big data,” and what can it tell us? Erez Aiden and Jean-Baptiste Michel are two young scientists at Harvard who started to ask those questions. They teamed up with Google to create the Ngram Viewer, a Web-based tool that can chart words throughout the massive Google Books archive, sifting through billions of words to find fascinating cultural trends. On the day that the Ngram Viewer debuted in 2010, more than one million queries were run through it. On the front lines of Big Data, Aiden and Michel realized that this big dataset-the Google Books archive that contains remarkable information on the human experience-had huge implications for looking at our shared human history. The tool they developed to delve into the data has enabled researchers to track how our language has evolved over time, how art has been censored, how fame can grow and fade, how nations trend toward war. How we remember and how we forget. And ultimately, how Big Data is changing the game for the sciences, humanities, politics, business, and our culture. .
Uncharted: How Scientists Navigate Their Own Health, Research, and Experiences of Bias
by Skylar Bayer Gabriela Serrato MarksPeople with disabilities are underrepresented in STEM fields, and all too often, they face isolation and ableism in academia. Uncharted is a collection of powerful first-person stories by current and former scientists with disabilities or chronic conditions who have faced changes in their careers, including both successes and challenges, because of their health. It gives voice to common experiences that are frequently overlooked or left unspoken. These deeply personal accounts describe not only health challenges but also the joys, sorrows, humor, and wonder of science and scientists.With a breadth of perspectives on being disabled or chronically ill, these stories highlight the intersectionality of minoritized identities with the disability community. Uncharted features essays by contributors who are d/Deaf, blind, neurodivergent, wheelchair users, have experienced traumatic brain injuries, have blood sugar disorders, have rare medical diagnoses, or have received psychiatric diagnoses, among many others. In many cases, the scientific field is not fully accessible to them, and they frankly describe struggling as well as thriving alongside their conditions.This book serves as representation for scientists who have never felt comfortable disclosing their disability or who have never felt fully understood. The stories shared in this book seek to normalize medical conditions and disabilities in scientific culture, offering recommendations for how and why to improve access. Uncharted is vital and compelling reading for current and aspiring scientists who want to make their fields more inclusive and supportive for everyone.
Uncle Tungsten: Memories of a Chemical Boyhood
by Oliver SacksLong before Oliver Sacks became a distinguished neurologist and bestselling writer, he was a small English boy fascinated by metals–also by chemical reactions (the louder and smellier the better), photography, squids and cuttlefish, H.G. Wells, and the periodic table. In this endlessly charming and eloquent memoir, the author of The Man Who Mistook His Wife for a Hat and Awakenings chronicles his love affair with science and the magnificently odd and sometimes harrowing childhood in which that love affair unfolded.In Uncle Tungsten we meet Sacks’ extraordinary family, from his surgeon mother (who introduces the fourteen-year-old Oliver to the art of human dissection) and his father, a family doctor who imbues in his son an early enthusiasm for housecalls, to his “Uncle Tungsten,” whose factory produces tungsten-filament lightbulbs. We follow the young Oliver as he is exiled at the age of six to a grim, sadistic boarding school to escape the London Blitz, and later watch as he sets about passionately reliving the exploits of his chemical heroes–in his own home laboratory. Uncle Tungsten is a crystalline view of a brilliant young mind springing to life, a story of growing up which is by turns elegiac, comic, and wistful, full of the electrifying joy of discovery.
Uncommon Dissent: Intellectuals Who Find Darwinism Unconvincing
by William DembskiRecent years have seen the rise to prominence of ever more sophisticated philosophical and scientific critiques of the ideas marketed under the name of Darwinism. In Uncommon Dissent, mathematician and philosopher William A. Dembski brings together essays by leading intellectuals who find one or more aspects of Darwinism unpersuasive. As Dembski explains, Darwinism has gathered around itself an aura of invincibility that is inhospitable to rational discussion--to say the least: "Darwinism, its proponents assure us, has been overwhelmingly vindicated. Any resistance to it is futile and indicates bad faith or worse." Indeed, those who question the Darwinian synthesis are supposed, in the famous formulation of Richard Dawkins, to be ignorant, stupid, insane, or wicked.The hostility of dogmatic Darwinians like Dawkins has not, however, prevented the advent of a growing cadre of scholarly critics of metaphysical Darwinism. The measured, thought-provoking essays in Uncommon Dissent make it increasingly obvious that these critics are not the brainwashed fundamentalist buffoons that Darwinism's defenders suggest they are, but rather serious, skeptical, open-minded inquirers whose challenges pose serious questions about the viability of Darwinist ideology. The intellectual power of their contributions to Uncommon Dissent is bracing.