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Stefano Tarantola Uncertainty in Industrial Practice


Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. Authored by a leading European network of experts representing a cross section of industries, Uncertainty in Industrial Practice aims to provide a reference for the dissemination of uncertainty treatment in any type of industry. It is concerned with the quantification of uncertainties in the presence of data, model(s) and knowledge about the system, and offers a technical contribution to decision-making processes whilst acknowledging industrial constraints. The approach presented can be applied to a range of different business contexts, from research or early design through to certification or in-service processes. The authors aim to foster optimal trade-offs between literature-referenced methodologies and the simplified approaches often inevitable in practice, owing to data, time or budget limitations of technical decision-makers. Uncertainty in Industrial Practice: Features recent uncertainty case studies carried out in the nuclear, air & space, oil, mechanical and civil engineering industries set in a common methodological framework. Presents methods for organizing and treating uncertainties in a generic and prioritized perspective. Illustrates practical difficulties and solutions encountered according to the level of complexity, information available and regulatory and financial constraints. Discusses best practice in uncertainty modeling, propagation and sensitivity analysis through a variety of statistical and numerical methods. Reviews recent standards, references and available software, providing an essential resource for engineers and risk analysts in a wide variety of industries. This book provides a guide to dealing with quantitative uncertainty in engineering and modelling and is aimed at practitioners, including risk-industry regulators and academics wishing to develop industry-realistic methodologies.

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Maurice Lemaire Mechanics and Uncertainty


Science is a quest for certainty, but lack of certainty is the driving force behind all of its endeavors. This book, specifically, examines the uncertainty of technological and industrial science. Uncertainty and Mechanics studies the concepts of mechanical design in an uncertain setting and explains engineering techniques for inventing cost-effective products. Though it references practical applications, this is a book about ideas and potential advances in mechanical science.

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Dennis V. Lindley Understanding Uncertainty


Praise for the First Edition «…a reference for everyone who is interested in knowing and handling uncertainty.» —Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made. Featuring new material, the Revised Edition remains the go-to guide for uncertainty and decision making, providing further applications at an accessible level including: A critical study of transitivity, a basic concept in probability A discussion of how the failure of the financial sector to use the proper approach to uncertainty may have contributed to the recent recession A consideration of betting, showing that a bookmaker's odds are not expressions of probability Applications of the book’s thesis to statistics A demonstration that some techniques currently popular in statistics, like significance tests, may be unsound, even seriously misleading, because they violate the rules of probability Understanding Uncertainty, Revised Edition is ideal for students studying probability or statistics and for anyone interested in one of the most fascinating and vibrant fields of study in contemporary science and mathematics.

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Peter Atkinson M. Uncertainty in Remote Sensing and GIS


Remote sensing and geographical information science (GIS) have advanced considerably in recent years. However, the potential of remote sensing and GIS within the environmental sciences is limited by uncertainty, especially in connection with the data sets and methods used. In many studies, the issue of uncertainty has been incompletely addressed. The situation has arisen in part from a lack of appreciation of uncertainty and the problems it can cause as well as of the techniques that may be used to accommodate it. This book provides general overviews on uncertainty in remote sensing and GIS that illustrate the range of uncertainties that may occur, in addition to describing the means of measuring uncertainty and the impacts of uncertainty on analyses and interpretations made. Uncertainty in Remote Sensing and GIS provides readers with comprehensive coverage of this largely undocumented subject: * Relevant to a broad variety of disciplines including geography, environmental science, electrical engineering and statistics * Covers range of material from base overviews to specific applications * Focuses on issues connected with uncertainty at various points along typical data analysis chains used in remote sensing and GIS Written by an international team of researchers drawn from a variety of disciplines, Uncertainty in Remote Sensing and GIS provides focussed discussions on topics of considerable importance to a broad research and user community. The book is invaluable reading for researchers, advanced students and practitioners who want to understand the nature of uncertainty in remote sensing and GIS, its limitations and methods of accommodating it.

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Professor Caers Jef Modeling Uncertainty in the Earth Sciences


Modeling Uncertainty in the Earth Sciences highlights the various issues, techniques and practical modeling tools available for modeling the uncertainty of complex Earth systems and the impact that it has on practical situations. The aim of the book is to provide an introductory overview which covers a broad range of tried-and-tested tools. Descriptions of concepts, philosophies, challenges, methodologies and workflows give the reader an understanding of the best way to make decisions under uncertainty for Earth Science problems. The book covers key issues such as: Spatial and time aspect; large complexity and dimensionality; computation power; costs of 'engineering' the Earth; uncertainty in the modeling and decision process. Focusing on reliable and practical methods this book provides an invaluable primer for the complex area of decision making with uncertainty in the Earth Sciences.

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Dorota Kurowicka Uncertainty Analysis with High Dimensional Dependence Modelling


Mathematical models are used to simulate complex real-world phenomena in many areas of science and technology. Large complex models typically require inputs whose values are not known with certainty. Uncertainty analysis aims to quantify the overall uncertainty within a model, in order to support problem owners in model-based decision-making. In recent years there has been an explosion of interest in uncertainty analysis. Uncertainty and dependence elicitation, dependence modelling, model inference, efficient sampling, screening and sensitivity analysis, and probabilistic inversion are among the active research areas. This text provides both the mathematical foundations and practical applications in this rapidly expanding area, including: An up-to-date, comprehensive overview of the foundations and applications of uncertainty analysis. All the key topics, including uncertainty elicitation, dependence modelling, sensitivity analysis and probabilistic inversion. Numerous worked examples and applications. Workbook problems, enabling use for teaching. Software support for the examples, using UNICORN – a Windows-based uncertainty modelling package developed by the authors. A website featuring a version of the UNICORN software tailored specifically for the book, as well as computer programs and data sets to support the examples. Uncertainty Analysis with High Dimensional Dependence Modelling offers a comprehensive exploration of a new emerging field. It will prove an invaluable text for researches, practitioners and graduate students in areas ranging from statistics and engineering to reliability and environmetrics.

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Enrico Zio Uncertainty in Risk Assessment


Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.

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George Klir J. Uncertainty and Information


Deal with information and uncertainty properly and efficiently using tools emerging from generalized information theory Uncertainty and Information: Foundations of Generalized Information Theory contains comprehensive and up-to-date coverage of results that have emerged from a research program begun by the author in the early 1990s under the name «generalized information theory» (GIT). This ongoing research program aims to develop a formal mathematical treatment of the interrelated concepts of uncertainty and information in all their varieties. In GIT, as in classical information theory, uncertainty (predictive, retrodictive, diagnostic, prescriptive, and the like) is viewed as a manifestation of information deficiency, while information is viewed as anything capable of reducing the uncertainty. A broad conceptual framework for GIT is obtained by expanding the formalized language of classical set theory to include more expressive formalized languages based on fuzzy sets of various types, and by expanding classical theory of additive measures to include more expressive non-additive measures of various types. This landmark book examines each of several theories for dealing with particular types of uncertainty at the following four levels: * Mathematical formalization of the conceived type of uncertainty * Calculus for manipulating this particular type of uncertainty * Justifiable ways of measuring the amount of uncertainty in any situation formalizable in the theory * Methodological aspects of the theory With extensive use of examples and illustrations to clarify complex material and demonstrate practical applications, generous historical and bibliographical notes, end-of-chapter exercises to test readers' newfound knowledge, glossaries, and an Instructor's Manual, this is an excellent graduate-level textbook, as well as an outstanding reference for researchers and practitioners who deal with the various problems involving uncertainty and information. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

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Stefano Tarantola | EU Science Hub

Stefano Tarantola is a Scientific Officer at the Joint Research Centre of the European Commission. He graduated in Nuclear Engineering in 1992 and received his PhD in Science and Technologies for Engineering at the Polytechnic of Milan in 1996.

Stefano TARANTOLA | European Commission, Brussels | ec ...

Stefano TARANTOLA | Cited by 18,962 | of European Commission, Brussels (ec) | Read 167 publications | Contact Stefano TARANTOLA

Stefano Tarantola Profile | Facebook

Profile von Personen mit dem Namen Stefano Tarantola anzeigen. Tritt Facebook bei, um dich mit Stefano Tarantola und anderen Personen, die du kennen...

Stefano Tarantola in Londra aus Italien | Moneyhouse

Stefano Tarantola in Londra aus Italien hat ein Mandat bei Federazione Svizzera Mixed Martial Arts (FSMMA) (SMMAF) (MMASF)

Stefano Tarantolo : Nebraska Cancer Specialists

Dr. Stefano Tarantolo is a hematologist and oncologist. He received his medical degree from St. George’s University School of Medicine and has been in practice for more than 20 years. He specializes in blood cancers such as multiple myeloma, lymphoma and leukemia.

Stefano Tarantola - Home

Stefano Tarantola. Search for Stefano Tarantola's work. Search Search. Home Stefano Tarantola. Stefano Tarantola. Skip slideshow. Most frequent co-Author ...

Creating Composite Indicators with DEA and Robustness ...

Stefano Tarantola. Joint Research Centre, Italy . Date Written: January 2006. Abstract. Composite indicators are regularly used for benchmarking countries' performance, but equally often stir controversies about the unavoidable subjectivity that is connected with their construction. Data Envelopment Analysis helps to overcome some key limitations, viz., the undesirable dependence of final ...

William Castaings, Stefano Tarantola

William Castaings*, Stefano Tarantola*, Abstract: This report is a methodological analysis on the composite index of the information and communication technology (ICT) adoption and use by enterprises in Europe. Efficient adoption and use of ICT is a key factor to help European enterprises to raise their productivity and competitiveness. The 2007 European E-Business Readiness Index, evaluated ...

Sensitivity analysis: An introduction

[email protected] Simulation (or computer) models are used in many disciplinesto understand complex phenomena (natural or social) and consequently astools to support decisions and policy.

Guidelines for inspections of offshore installations

Stefano Tarantola (European Commission, Joint Research Centre) 4 1 Introduction The blowout on the Deepwater Horizon drilling rig on April 20th 2010, whilst drilling the Macondo well in the Gulf of Mexico, significantly raised worldwide awareness of the risks involved in offshore oil & gas operations. In addition to the tragic loss of eleven lives, the blowout released nearly five million ...

‪Stefano Tarantola‬ - ‪Google Scholar‬

‪Joint Research Centre, European Commission‬ - ‪Cited by 30,310‬

Stefano Tarantola, William Castaings

Stefano Tarantola and William Castaings Abstract: This report shows the scores of the 2008 e-business readiness index for European enterprises. The 2008 e-business readiness index, evaluated using data from the 2007 ICT enterprise survey carried out by Eurostat, is a useful mechanism for comparing e-business adoption and use by firms in the various European countries. The e-business readiness ...

Stefano Tarantola - AI Profile

Stefano Tarantola, Joint Research Centre of the European Commission|Institute for the Protection, undefined... Home Research-feed Channel Rankings GCT THU AI TR Open Data Must Reading. Research Feed. Log in AMiner. Academic Profile User Profile. Research Feed My following Paper Collections. views: 19. Update Photo . Stefano Tarantola. Follow. Sign in to view more. Show Academic Trajectory. Ego ...

Stefano Tarantola, 47 - Howard Beach, NY Has Court or ...

Summary: Stefano Tarantola is 47 years old and was born on 07/06/1973. Previous to Stefano's current city of Howard Beach, NY, Stefano Tarantola lived in Middle Village NY. Steven Tarantola and Steve Tarantola are some of the alias or nicknames that Stefano has used.

Stefano Tarantola (Author of Sensitivity Analysis in Practice)

Stefano Tarantola is the author of Global Sensitivity Analysis (4.60 avg rating, 5 ratings, 0 reviews, published 2008), Uncertainty in Industrial Practic...

Stefano Tarantola - dblp.uni-trier.de

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Stefano Tarantola | Facebook

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Stefano Tarantola - Researcher - European Commission ...

Stefano Tarantola is a Scientific Officer at the Joint Research Centre of the European Commission. He graduated in Nuclear Engineering in 1992 and received his PhD in Science and Technologies for Engineering at the Polytechnic of Milan in 1996. He works at the Directorate for Energy, Transport and Climate conducting methodological work and pre-normative research in the field interoperability ...

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Dr. Stefano Tarantolo Hematology. Omaha NE

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Tarantola, Stefano [WorldCat Identities]

Most widely held works by Stefano Tarantola Uncertainty in industrial practice : a guide to quantitative uncertainty management ( ) 8 editions published in ...

Stefano Tarantola - researchr alias

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Stefano Tarantola in Londra - Auskünfte | Moneyhouse

Stefano Tarantola in Londra aus Italien Verbunden mit 1 Firma keine Beteiligungen Federazione Svizzera Mixed Martial Arts (FSMMA) (SMMAF) (MMASF)

Stefano Tarantola, 64 - Independence, MO Has Court or ...

Summary: Stefano Tarantola was born on 06/28/1956 and is 64 years old. Currently, Stefano lives in Independence, MO. Other family members and associates include Janene Nalivaiko, Rose Vernon, Saveria Tarantola, Rosario Tarantola and Sal Tarantola. Read Full Summary

Stefano Tarantola | ENDU

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5 "Stefano Tarantola" profiles | LinkedIn

View the profiles of professionals named "Stefano Tarantola" on LinkedIn. There are 5 professionals named "Stefano Tarantola", who use LinkedIn to exchange information, ideas, and opportunities.

Sensitivity Analysis in Practice: A Guide to Assessing ...

Andrea Saltelli, Stefano Tarantola, Francesca Campolongo, Marco Ratto. John Wiley & Sons, Jul 16, 2004 - Mathematics - 232 pages. 1 Review. Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of ...

Sensitivity Analysis in Practice: A Guide to Assessing ...

Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models | Saltelli, Andrea, Tarantola, Stefano, Campolongo, Francesca, Ratto, Marco | ISBN ...

Global Sensitivity Analysis: The Primer - Andrea Saltelli ...

Andrea Saltelli, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Fulvia Pennoni, Marco Ratto, Michaela Saisana, Stefano Tarantola – Joint Research Centre of the European Commission, Ispra, Unit of Applied Statistics and Econometrics. Presently leading the Econometric and Applied Statistics Unit of the Joint Research Centre, lead author Professor Saltelli has published many articles ...

Stefano Tarantola eBooks - eBooks.com

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Global Sensitivity Analysis: The Primer - Andrea Saltelli ...

Andrea Saltelli, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Fulvia Pennoni, Marco Ratto, Michaela Saisana, Stefano Tarantola – Joint Research Centre of the European Commission, Ispra, Unit of Applied Statistics and Econometrics. Presently leading the Econometric and Applied Statistics Unit of the Joint Research Centre, lead author Professor Saltelli has published many articles ...

Stefano Tarantola | ENDU

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STD.DOC 2005 3-1 - OECD

Saisana, Andrea Saltelli and Stefano Tarantola. Primary authors from the OECD are Anders Hoffmann and Enrico Giovannini. Editorial assistance was provided by Candice Stevens, Gunseli Baygan and Karsten Olsen. The research is partly funded by the European Commission, Research Directorate, under the project KEI (Knowledge Economy Indicators), Contract FP6 No. 502529. In the OECD context, the ...

Dr. Stefano Tarantolo, MD | Omaha, NE | Healthgrades

Dr. Stefano Tarantolo, MD is a Hematology Specialist in Omaha, NE and has over 36 years of experience in the medical field. He graduated from St George's University medical school in 1985. He is affiliated with medical facilities such as CHI Health Creighton University Medical Center - Bergan Mercy and Chi Health Lakeside. He is accepting new patients and has indicated that he accepts ...

Auflistung Informatik in den Lebenswissenschaften (ILW ...

Sensitivity analysis techniques for calibration and reduction of environmental models . Ratto, Marco; Tarantola, Stefano

Global Sensitivity Analysis (eBook, PDF) von Andrea ...

Complex mathematical and computational models are used in all areasof society and technology and yet model based science isincreasingly contested or refuted, especially when models areapplied to controversial themes in domains such as health, theenvironment or the economy.

Markus Tullius – Technischer Leiter – Jung und Partner ...

Stefano Tarantola. Stefano Tarantola Scientific officer at the Joint Research Centre of the European Commission - Living Labs, smart grids, smart cities Provincia di Varese. Jochen Meyer. Jochen Meyer Technischer Leiter Conmar Shipping GmbH & Co KG Deutschland. Frank Woryna ...

Verfasser Suchresultate

Tarantola, A; Treffer 1 - 20 von 236. Treffer pro Seite. Sortieren. 1 . Online-Ressource. Unforgotten Biafra 50 Years Later . von Tarantola, Daniel Veröffentlicht in American Journal of Public Health (2018 ...

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W. Steele Glenn Experimentation, Validation, and Uncertainty Analysis for Engineers


Helps engineers and scientists assess and manage uncertainty at all stages of experimentation and validation of simulations Fully updated from its previous edition, Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes expanded coverage and new examples of applying the Monte Carlo Method (MCM) in performing uncertainty analyses. Presenting the current, internationally accepted methodology from ISO, ANSI, and ASME standards for propagating uncertainties using both the MCM and the Taylor Series Method (TSM), it provides a logical approach to experimentation and validation through the application of uncertainty analysis in the planning, design, construction, debugging, execution, data analysis, and reporting phases of experimental and validation programs. It also illustrates how to use a spreadsheet approach to apply the MCM and the TSM, based on the authors’ experience in applying uncertainty analysis in complex, large-scale testing of real engineering systems. Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes examples throughout, contains end of chapter problems, and is accompanied by the authors’ website www.uncertainty-analysis.com. Guides readers through all aspects of experimentation, validation, and uncertainty analysis Emphasizes the use of the Monte Carlo Method in performing uncertainty analysis Includes complete new examples throughout Features workable problems at the end of chapters Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition is an ideal text and guide for researchers, engineers, and graduate and senior undergraduate students in engineering and science disciplines. Knowledge of the material in this Fourth Edition is a must for those involved in executing or managing experimental programs or validating models and simulations.

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Philippe Weber Data Uncertainty and Important Measures


The first part of the book defines the concept of uncertainties and the mathematical frameworks that will be used for uncertainty modeling. The application to system reliability assessment illustrates the concept. In the second part, evidential networks as a new tool to model uncertainty in reliability and risk analysis is proposed and described. Then it is applied on SIS performance assessment and in risk analysis of a heat sink. In the third part, Bayesian and evidential networks are used to deal with important measures evaluation in the context of uncertainties.

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