LEADER 06198nam 2200649 450 001 9910140497903321 005 20200520144314.0 010 $a1-118-66293-8 010 $a1-118-66295-4 010 $a1-118-66294-6 035 $a(CKB)2670000000571218 035 $a(EBL)1813088 035 $a(MiAaPQ)EBC1813088 035 $a(DLC) 2014036103 035 $a(Au-PeEL)EBL1813088 035 $a(CaPaEBR)ebr10952039 035 $a(CaONFJC)MIL651317 035 $a(OCoLC)893332547 035 $a(PPN)201682850 035 $a(EXLCZ)992670000000571218 100 $a20141018h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aMultiple-point geostatistics $estochastic modeling with training images /$fGregoire Mariethoz and Jef Caers 210 1$aChichester, England ;$aOxford, England ;$aHoboken, New Jersey :$cWiley Blackwell,$d2015. 210 4$dİ2015 215 $a1 online resource (379 p.) 300 $a"with website"--Cover. 311 $a1-118-66275-X 311 $a1-322-20037-8 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aMultiple-point geostatistics; Contents; Preface; Acknowledgments; Part I Concepts; 1 Hiking in the Sierra Nevada; 1.1 An imaginary outdoor adventure company: Buena Sierra; 1.2 What lies ahead; 2 Spatial estimation based on random function theory; 2.1 Assumptions of stationarity; 2.2 Assumption of stationarity in spatial problems; 2.3 The kriging solution; 2.3.1 Unbiasedness condition; 2.3.2 Minimizing squared loss; 2.4 Estimating covariances; 2.5 Semivariogram modeling; 2.6 Using a limited neighborhood; 2.7 Universal kriging; 2.8 Semivariogram modeling for universal kriging 327 $a2.9 Simple trend example case2.10 Nonstationary covariances; 2.11 Assessment; References; 3 Universal kriging with training images; 3.1 Choosing for random function theory or not?; 3.2 Formulation of universal kriging with training images; 3.2.1 Zero error-sum condition; 3.2.2 Minimum sum of square error condition; 3.3 Positive definiteness of the sop matrix; 3.4 Simple kriging with training images; 3.5 Creating a map of estimates; 3.6 Effect of the size of the training image; 3.7 Effect of the nature of the training image; 3.8 Training images for nonstationary modeling 327 $a3.9 Spatial estimation with nonstationary training images3.10 Summary of methodological differences; References; 4 Stochastic simulations based on random function theory; 4.1 The goal of stochastic simulations; 4.2 Stochastic simulation: Gaussian theory; 4.3 The sequential Gaussian simulation algorithm; 4.4 Properties of multi-Gaussian realizations; 4.5 Beyond Gaussian or beyond covariance?; References; 5 Stochastic simulation without random function theory; 5.1 Direct sampling; 5.1.1 Relying on information theory; 5.1.2 Application of direct sampling to Walker Lake 327 $a5.2 The extended normal equation5.2.1 Formulation; 5.2.2 The RAM solution; 5.2.3 Single normal equations simulation for Walker Lake; 5.2.4 The problem of conditioning; 5.3 Simulation by texture synthesis; 5.3.1 Computer graphics; 5.3.2 Image quilting; References; 6 Returning to the Sierra Nevada; Reference; Part II Methods; 1 Introduction; 2 The algorithmic building blocks; 2.1 Grid and pointset representations; 2.2 Multivariate grids; 2.3 Neighborhoods; 2.4 Storage and restitution of data events; 2.4.1 Raw storage of training image; 2.4.2 Cross-correlation based convolution 327 $a2.4.3 Partial convolution2.4.4 Tree storage; 2.4.5 List storage; 2.4.6 Clustering of patterns; 2.4.7 Parametric representation of patterns; 2.5 Computing distances; 2.5.1 Norms; 2.5.2 Hausdorff distance; 2.5.3 Invariant distances; 2.5.4 Change of variable; 2.5.5 Distances between distributions; 2.6 Sequential simulation; 2.6.1 Random path; 2.6.2 Unilateral path; 2.6.3 Patch-based methods; 2.6.4 Patch carving; 2.7 Multiple grids; 2.8 Conditioning; 2.8.1 The different types of data; 2.8.2 Different types of data: an example; 2.8.3 Steering proportions; References 327 $a3 Multiple-point geostatistics algorithms 330 $a"This book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable reference for students, researchers and practitioners of all areas of the Earth Sciences where forecasting based on spatio-temporal data is performed"--$cProvided by publisher. 330 $a"The topic of this book concerns an area of geostatistics that has commonly been known as multiple-point geostatistics because it uses more than two-point statistics (correlation), traditionally represented by the variogram, to model spatial phenomena"--$cProvided by publisher. 606 $aGeology$xStatistical methods 606 $aGeological modeling 615 0$aGeology$xStatistical methods. 615 0$aGeological modeling. 676 $a551.01/5195 686 $aSCI031000$2bisacsh 700 $aMariethoz$b Gregoire$0481277 702 $aCaers$b Jef 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910140497903321 996 $aMultiple-point geostatistics$92147967 997 $aUNINA LEADER 02898nam 2200577 a 450 001 9910786109203321 005 20230803025726.0 010 $a3-527-67503-5 035 $a(CKB)2670000000342930 035 $a(EBL)1161984 035 $a(OCoLC)836403150 035 $a(SSID)ssj0001192835 035 $a(PQKBManifestationID)11684653 035 $a(PQKBTitleCode)TC0001192835 035 $a(PQKBWorkID)11227475 035 $a(PQKB)10371421 035 $a(MiAaPQ)EBC481344 035 $a(Au-PeEL)EBL481344 035 $a(CaPaEBR)ebr10682369 035 $a(CaONFJC)MIL194693 035 $a(OCoLC)264717029 035 $a(EXLCZ)992670000000342930 100 $a20130410d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aReliability of MEMS$b[electronic resource] $etesting of materials and devices /$fedited by Osamu Tabata, Toshiyuki Tsuchiya 205 $a2nd ed. 210 $aWeinheim $cWiley-VCH$d2013 215 $a1 online resource (325 p.) 225 1 $aAdvanced micro & nanosystems 300 $aFirst edition 2007. 311 $a3-527-33501-3 320 $aIncludes bibliographical references and index. 327 $aTitle Page; Preface; Foreword; Contents; List of Contributors; Overview; 1 Evaluation of Mechanical Properties of MEMS Materials and Their Standardization; 2 Elastoplastic Indentation Contact Mechanics of Homogeneous Materials and Coating - Substrate Systems; 3 Thin film Characterization Using the Bulge Test; 4 Uniaxial Tensile Test for MEMS Materials; 5 On chip Testing of MEMS; 6 Reliability of a Capacitive Pressure Sensor; 7 Inertial Sensors; 8 High accuracy, High reliability MEMS Accelerometer; 9 Reliability of MEMS Variable Optical Attenuator; 10 Eco Scan MEMS Resonant Mirror; Index 330 $aNow available in softcover, this book closely examines the enabling technologies for the fabrication of micro- and nanodevices. Divided into two clearly structured sections, the first begins with an insider's view of industrial MEMS commercialization, followed by chapters on capacitive interfaces for MEMS, packaging issues of micro- and nanosystems, MEMS contributions to high frequency integrated resonators and filters, as well as the uses of MEMS in mass data storage and electrochemical imaging by means of scanning micro- and nanoprobes. The second section on nanodevices first tackles the 410 0$aAdvanced micro & nanosystems. 606 $aMicroelectromechanical systems$xReliability 615 0$aMicroelectromechanical systems$xReliability. 676 $a539.60113 701 $aTabata$b Osamu$0892953 701 $aTsuchiya$b Toshiyuki$0917771 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910786109203321 996 $aReliability of MEMS$92057813 997 $aUNINA LEADER 02453nam 2200745Ia 450 001 9910780762103321 005 20230617001949.0 010 $a0-674-03022-2 024 7 $a10.4159/9780674030220 035 $a(CKB)2440000000013097 035 $a(OCoLC)442778432 035 $a(CaPaEBR)ebrary10314213 035 $a(SSID)ssj0000262731 035 $a(PQKBManifestationID)12041807 035 $a(PQKBTitleCode)TC0000262731 035 $a(PQKBWorkID)10271445 035 $a(PQKB)10023124 035 $a(SSID)ssj0000488078 035 $a(PQKBManifestationID)11318227 035 $a(PQKBTitleCode)TC0000488078 035 $a(PQKBWorkID)10446491 035 $a(PQKB)10462243 035 $a(MiAaPQ)EBC3300206 035 $a(DE-B1597)457590 035 $a(OCoLC)1013948308 035 $a(OCoLC)1029816985 035 $a(OCoLC)1032690803 035 $a(OCoLC)1037981714 035 $a(OCoLC)1041992773 035 $a(OCoLC)1046604267 035 $a(OCoLC)1046997875 035 $a(OCoLC)979575337 035 $a(DE-B1597)9780674030220 035 $a(Au-PeEL)EBL3300206 035 $a(CaPaEBR)ebr10314213 035 $a(OCoLC)842973071 035 $a(EXLCZ)992440000000013097 100 $a20040824d2005 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aTruth and predication$b[electronic resource] /$fDonald Davidson 210 $aCambridge, MA $cHarvard University Press$d2005 215 $a1 online resource (193 p.) 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a0-674-01525-8 311 $a0-674-03040-0 320 $aIncludes bibliographical references (p. 165-172) and index. 327 $tFrontmatter --$tContents --$tForeword --$tPreface --$tIntroduction --$t1. Theories of Truth --$t2. What More Is There to Truth? --$t3. The Content of the Concept of Truth --$t4. The Problem of Predication --$t5. Failed Attempts --$t6. Truth and Predication --$t7. A Solution --$tBibliography --$tIndex 606 $aTruth 606 $aPredicate (Logic) 615 0$aTruth. 615 0$aPredicate (Logic) 676 $a121 686 $aCI 6398$2rvk 700 $aDavidson$b Donald$f1917-2003.$046094 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910780762103321 996 $aTruth and predication$93818448 997 $aUNINA