01720nam0 22003973i 450 RAV003740020231121125625.0883860613720160623d1988 ||||0itac50 baitaitz01i xxxe z01n˜Il œsistema operativo Unix System 5.Rachel Morgan, Henry McGiltonMilanoMcGraw-Hill1988702 p.21 cmCollana di istruzione scientifica. Sezione di linguaggi e sistemi operativiTrad. e rev. di Anna Antola e Nello ScarabottoloBibliografia: P. [681]-683.Tit. del dorso.: Unix System VRAV0037405001RAV01322062001 Collana di istruzione scientifica. Sezione di linguaggi e sistemi operativiIntroducing Unix Sistem V. -RAV0037407RAVV02097028090Unix System V. -RAV0037405Sistemi operativi UnixElaboratori elettroniciFIRRMLC414813I005.4321Morgan, RachelRAVV02097007013457McGilton, HenryRAVV02097107013848ITIT-0120160623IT-FR0017 IT-RM1702 Biblioteca umanistica Giorgio ApreaFR0017 Biblioteca Direzione Centrale Prevenzione e Sicurezza Tecnica Vigili del FuocoRM1702 RAV0037400Biblioteca umanistica Giorgio Aprea 52CIS 9/541 52VM 0000627845 VM barcode:00049032. - Inventario:231 FLSVMA 2006082520121204 52 55Introducing Unix Sistem V28090UNICAS03834nam 22007215 450 991051217340332120250505000811.03-030-83640-110.1007/978-3-030-83640-5(CKB)5590000000631161(MiAaPQ)EBC6824949(Au-PeEL)EBL6824949(OCoLC)1290485018(oapen)https://directory.doabooks.org/handle/20.500.12854/74880(PPN)259386650(DE-He213)978-3-030-83640-5(ODN)ODN0010074464(oapen)doab74880(EXLCZ)99559000000063116120211209d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierUncertainty in Engineering Introduction to Methods and Applications /edited by Louis J. M. Aslett, Frank P. A. Coolen, Jasper De Bock1st ed. 2022.2021Cham :Springer International Publishing :Imprint: Springer,2022.1 online resource (148 pages)SpringerBriefs in Statistics,2191-54583-030-83639-8 Introduction to Bayesian statistical inference -- Sampling from complex probability distributions: a Monte Carlo primer for engineers -- Introduction to the theory of imprecise probability -- Imprecise discrete-time Markov chains -- Statistics with imprecise probabilities – a short survey -- Reliability -- Simulation methods for the analysis of complex systems -- Overview of stochastic model updating in aerospace application under uncertainty treatment -- Aerospace flight modeling and experimental testing.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.SpringerBriefs in Statistics,2191-5458StatisticsStatisticsIndustrial engineeringProduction engineeringStatistical Theory and MethodsStatistics in Engineering, Physics, Computer Science, Chemistry and Earth SciencesIndustrial and Production EngineeringBayesian InferenceStatistics.Statistics.Industrial engineering.Production engineering.Statistical Theory and Methods.Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.Industrial and Production Engineering.Bayesian Inference.519.5MAT029000MAT029010TEC032000bisacshAslett Louis J. M1075841Coolen Frank P. A1075842De Bock Jasper1075843MiAaPQMiAaPQMiAaPQBOOK9910512173403321Uncertainty in Engineering2585666UNINA