LEADER 06071oam 2200769 450 001 9910144099003321 005 20200925212234.0 010 $a0-470-77080-5 010 $a1-281-84101-3 010 $a9786611841010 010 $a1-61583-477-X 010 $a0-470-77079-1 010 $a9780470770801$b(electronic bk.) 010 $a9780470770795$b(electronic bk.) 010 $a0470770791$b(electronic bk.) 035 $a(CKB)1000000000551097 035 $a(EBL)366798 035 $a(OCoLC)264714649 035 $a(SSID)ssj0000147488 035 $a(PQKBManifestationID)11910443 035 $a(PQKBTitleCode)TC0000147488 035 $a(PQKBWorkID)10011310 035 $a(PQKB)10160729 035 $a(MiAaPQ)EBC366798 035 $a(PPN)223474088 035 $a(EXLCZ)991000000000551097 100 $a20080414h20082008 uy 0 101 0 $aeng 135 $aur|n||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEngineering design via surrogate modelling $ea practical guide /$fAlexander I.J. Forrester, Andra?s So?bester, and Andy J. Keane, University of Southampton, UK 210 1$aChichester, West Sussex, England :$cWiley,$d2008. 210 4$d©2008 215 $a1 online resource (xviii, 210 pages) $cillustrations (some colour) 311 $a0-470-06068-9 311 08$aOriginal 9780470060681 0470060689 9780470770801 0470770805 9781563479557 1563479559 (DLC) 2008017093 (OCoLC)225090909 320 $aIncludes bibliographical references and index. 327 $aEngineering Design via Surrogate Modelling; Contents; Preface; About the Authors; Foreword; Prologue; Part I Fundamentals; 1 Sampling Plans; 1.1 The 'Curse of Dimensionality' and How to Avoid It; 1.2 Physical versus Computational Experiments; 1.3 Designing Preliminary Experiments (Screening); 1.3.1 Estimating the Distribution of Elementary Effects; 1.4 Designing a Sampling Plan; 1.4.1 Stratification; 1.4.2 Latin Squares and Random Latin Hypercubes; 1.4.3 Space-filling Latin Hypercubes; 1.4.4 Space-filling Subsets; 1.5 A Note on Harmonic Responses; 1.6 Some Pointers for Further Reading 327 $aReferences2 Constructing a Surrogate; 2.1 The Modelling Process; 2.1.1 Stage One: Preparing the Data and Choosing a Modelling Approach; 2.1.2 Stage Two: Parameter Estimation and Training; 2.1.3 Stage Three: Model Testing; 2.2 Polynomial Models; 2.2.1 Example One: Aerofoil Drag; 2.2.2 Example Two: a Multimodal Testcase; 2.2.3 What About the k-variable Case?; 2.3 Radial Basis Function Models; 2.3.1 Fitting Noise-Free Data; 2.3.2 Radial Basis Function Models of Noisy Data; 2.4 Kriging; 2.4.1 Building the Kriging Model; 2.4.2 Kriging Prediction; 2.5 Support Vector Regression 327 $a2.5.1 The Support Vector Predictor2.5.2 The Kernel Trick; 2.5.3 Finding the Support Vectors; 2.5.4 Finding ; 2.5.5 Choosing C and ; 2.5.6 Computing : -SVR; 2.6 The Big(ger) Picture; References; 3 Exploring and Exploiting a Surrogate; 3.1 Searching the Surrogate; 3.2 Infill Criteria; 3.2.1 Prediction Based Exploitation; 3.2.2 Error Based Exploration; 3.2.3 Balanced Exploitation and Exploration; 3.2.4 Conditional Likelihood Approaches; 3.2.5 Other Methods; 3.3 Managing a Surrogate Based Optimization Process; 3.3.1 Which Surrogate for What Use? 327 $a3.3.2 How Many Sample Plan and Infill Points?3.3.3 Convergence Criteria; 3.4 Search of the Vibration Isolator Geometry Feasibility Using Kriging Goal Seeking; References; Part II Advanced Concepts; 4 Visualization; 4.1 Matrices of Contour Plots; 4.2 Nested Dimensions; Reference; 5 Constraints; 5.1 Satisfaction of Constraints by Construction; 5.2 Penalty Functions; 5.3 Example Constrained Problem; 5.3.1 Using a Kriging Model of the Constraint Function; 5.3.2 Using a Kriging Model of the Objective Function; 5.4 Expected Improvement Based Approaches 327 $a5.4.1 Expected Improvement With Simple Penalty Function5.4.2 Constrained Expected Improvement; 5.5 Missing Data; 5.5.1 Imputing Data for Infeasible Designs; 5.6 Design of a Helical Compression Spring Using Constrained Expected Improvement; 5.7 Summary; References; 6 Infill Criteria with Noisy Data; 6.1 Regressing Kriging; 6.2 Searching the Regression Model; 6.2.1 Re-Interpolation; 6.2.2 Re-Interpolation With Conditional Likelihood Approaches; 6.3 A Note on Matrix Ill-Conditioning; 6.4 Summary; References; 7 Exploiting Gradient Information; 7.1 Obtaining Gradients; 7.1.1 Finite Differencing 327 $a7.1.2 Complex Step Approximation 330 $aSurrogate models expedite the search for promising designs by standing in for expensive design evaluations or simulations. They provide a global model of some metric of a design (such as weight, aerodynamic drag, cost, etc.), which can then be optimized efficiently. Engineering Design via Surrogate Modelling is a self-contained guide to surrogate models and their use in engineering design. The fundamentals of building, selecting, validating, searching and refining a surrogate are presented in a manner accessible to novices in the field. Figures are used liberally to explain the key 606 $aEngineering design$xMathematical models 606 $aEngineering design$xStatistical methods 606 $aEngineering design$xStatistical methods$2fast$3(OCoLC)fst00910488 606 $aEngineering design$xMathematical models$2fast$3(OCoLC)fst00910477 615 0$aEngineering design$xMathematical models. 615 0$aEngineering design$xStatistical methods. 615 7$aEngineering design$xStatistical methods. 615 7$aEngineering design$xMathematical models. 676 $a620.0044 676 $a620/.0042015118 700 $aForrester$b Alexander I. J.$0862517 702 $aSo?bester$b Andra?s 702 $aKeane$b A. J. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 801 2$bNhCcYBP 906 $aBOOK 912 $a9910144099003321 996 $aEngineering design via surrogate modelling$91925254 997 $aUNINA LEADER 04381nam 22010335 450 001 9910797323703321 005 20211005214150.0 010 $a0-8232-7234-6 010 $a0-8232-6738-5 010 $a0-8232-6737-7 024 7 $a10.1515/9780823267378 035 $a(CKB)3710000000454542 035 $a(EBL)3430733 035 $a(SSID)ssj0001532790 035 $a(PQKBManifestationID)12619936 035 $a(PQKBTitleCode)TC0001532790 035 $a(PQKBWorkID)11475168 035 $a(PQKB)10291352 035 $a(MiAaPQ)EBC3430733 035 $a(MiAaPQ)EBC5046414 035 $a(StDuBDS)EDZ0001532340 035 $a(OCoLC)915321368 035 $a(MdBmJHUP)muse46344 035 $a(DE-B1597)555358 035 $a(DE-B1597)9780823267378 035 $a(MiAaPQ)EBC4938288 035 $a(Au-PeEL)EBL4938288 035 $a(CaONFJC)MIL818749 035 $a(EXLCZ)993710000000454542 100 $a20200723h20152015 fg 0 101 0 $aeng 135 $aurnn#---|u||u 181 $ctxt 182 $cc 183 $acr 200 10$aThou Shalt Not Kill $eA Political and Theological Dialogue /$fAngelo Scola, Adriana Cavarero 205 $aFirst edition. 210 1$aNew York, NY :$cFordham University Press,$d[2015] 210 4$d©2015 215 $a1 online resource (144 p.) 225 0 $aCommonalities 300 $aIncludes index. 311 0 $a0-8232-6735-0 311 $a0-8232-6734-2 320 $aIncludes bibliographical references and index. 327 $tFront matter --$tCONTENTS --$tTRANSLATORS? NOTE --$tPART I: The Irrepressible Face of the Other --$tPoint of Departure --$tCommandments and Covenant --$tChristianity and Rational, Universal Morals --$tYou Shall Not Kill --$tResponsibilities and Challenges: Burning Issues --$tPart II: The Archaeology of Homicide --$tA Special Law --$tBrief Philological Note --$tCrime and Punishment --$tWhen Killing Is Lawful and Just --$tTo Cut Life Short --$tA Weak Commandment --$tIn the Beginning --$tHomo Necans --$tYou Shall Never Kill --$tThe Sex of Cain --$tNotes --$tIndex 330 $aIn this fascinating and rare little book, a leading Italian feminist philosopher and the Archbishop of Milan face off over the contemporary meaning of the biblical commandment not to kill. The result is a series of erudite and wide-ranging arguments that move from murder and suicide to just war and drone strikes, from bioethics and biopolitics to hermeneutics and philology, from Theodor Adorno and Max Horkheimer to Hannah Arendt and Michel Foucault, from Torah and Scripture to art and literature, from the essence of human dignity and the paradoxes of fratricide to engagements with Levinasian ethics. Less a direct debate than a disputation in the classical sense, Thou Shalt Not Kill proves to be a searching meditation on one of the unstated moral premises shared by otherwise bitterly opposed political factions. It will stimulate the mind of the novice while also reminding more advanced readers of the necessity and desirability of thinking in the present. 410 0$aCommonalities. 606 $aBioethics 606 $aBiopolitics 606 $aEmmanuel Levinas 606 $aHannah Arendt 606 $aHomicide 606 $aHomo Necans 606 $aJust War 606 $aMurder 606 $aTen Commandments 606 $aTorah 610 $aBioethics. 610 $aBiopolitics. 610 $aEmmanuel Levinas. 610 $aHannah Arendt. 610 $aHomicide. 610 $aHomo Necans. 610 $aJust War. 610 $aMurder. 610 $aTen Commandments. 610 $aTorah. 615 0$aBioethics. 615 0$aBiopolitics. 615 0$aEmmanuel Levinas. 615 0$aHannah Arendt. 615 0$aHomicide. 615 0$aHomo Necans. 615 0$aJust War 615 0$aMurder. 615 0$aTen Commandments. 615 0$aTorah. 676 $a179.7 700 $aCavarero$b Adriana$4aut$4http://id.loc.gov/vocabulary/relators/aut$0145354 701 $aGroesbeck$b Margaret Adams$01544327 701 $aSitze$b Adam$01475917 702 $aScola$b Angelo$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bDE-B1597 801 1$bDE-B1597 906 $aBOOK 912 $a9910797323703321 996 $aThou Shalt Not Kill$93798464 997 $aUNINA LEADER 01823nas 2200661-a 450 001 996202236403316 005 20230801213017.0 011 $a1179-1926 035 $a(DE-599)ZDB2043781-X 035 $a(OCoLC)37663879 035 $a(CKB)954925516554 035 $a(CONSER)--2007233700 035 $a(EXLCZ)99954925516554 100 $a19970922a19769999 s-- - 101 0 $aeng 135 $aurmnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aClinical pharmacokinetics 210 $a[Langhorne, PA] $cAdis International 215 $a1 online resource (volumes) 300 $aRefereed/Peer-reviewed 311 $a0312-5963 531 $aCLIN PHARMACOKINET 531 $aCLIN PHARMA 531 $aCLIN. PHARMACOKINET 606 $aPharmacology$vPeriodicals 606 $aPharmacology 606 $aPharmacokinetics$vPeriodicals 606 $aKinetics 606 $aPharmacology 606 $aPharmacocinétique$vPériodiques 606 $aPharmacologie$vPériodiques 606 $aPharmacologie 606 $apharmacology$2aat 606 $aPharmacokinetics$2fast$3(OCoLC)fst01060250 606 $aPharmacology$2fast$3(OCoLC)fst01060259 608 $aPeriodical 608 $aPeriodicals.$2fast 610 $aPharmacology 610 $aPharmacy 615 0$aPharmacology 615 0$aPharmacology. 615 0$aPharmacokinetics 615 2$aKinetics 615 2$aPharmacology 615 6$aPharmacocinétique 615 6$aPharmacologie 615 6$aPharmacologie. 615 7$apharmacology. 615 7$aPharmacokinetics. 615 7$aPharmacology. 676 $a615 906 $aJOURNAL 912 $a996202236403316 996 $aClinical pharmacokinetics$9797114 997 $aUNISA