LEADER 04874nam 2200649Ia 450 001 9910452216203321 005 20200520144314.0 010 $a1-61122-922-7 035 $a(CKB)2550000001041187 035 $a(EBL)3018197 035 $a(SSID)ssj0000834813 035 $a(PQKBManifestationID)11526159 035 $a(PQKBTitleCode)TC0000834813 035 $a(PQKBWorkID)10989720 035 $a(PQKB)10109463 035 $a(MiAaPQ)EBC3018197 035 $a(Au-PeEL)EBL3018197 035 $a(CaPaEBR)ebr10659119 035 $a(OCoLC)923657387 035 $a(EXLCZ)992550000001041187 100 $a20091210d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$a3D imaging$b[electronic resource] $etheory, technology and applications /$fEmerson H. Duke and Stephen R. Aguirre, editors 210 $aNew York $cNova Science Publishers$dc2009 215 $a1 online resource (343 p.) 225 1 $aComputer Science, Technology and Applications 300 $aDescription based upon print version of record. 311 $a1-60876-885-6 320 $aIncludes bibliographical references and index. 327 $a""3D IMAGING: THEORY, TECHNOLOGY AND APPLICATIONS ""; ""3D IMAGING: THEORY, TECHNOLOGY AND APPLICATIONS ""; ""CONTENTS""; ""PREFACE""; ""3D IMAGING OF ABDOMINAL AORTIC ANEURYSMS: TECHNIQUES AND APPLICATIONS ""; ""ABSTRACT""; "" Background""; ""Methods""; ""Results""; ""Conclusion""; ""1. INTRODUCTION ""; ""1.1 Incidence and Current Opinions ""; ""1.2 Medical Imaging""; ""2. 3D RECONSTRUCTION FROM CT SCANS ""; ""3. APPLICATIONS OF AAA 3D RECONSTRUCTIONS ""; ""4. NUMERICAL INVESTIGATIONS ""; ""4.1 Pre-Operative Planning for EVAR""; ""4.2 Stent-Graft Design"" 327 $a""4.3 Optimum Smoothing of 3D Models """"4.4 Determining AAA Asymmetry""; ""4.5 Improving Rupture Predictions""; ""4.6 Pre and Post-Operative Biomechanics""; ""4.7 Computer-Aided Design and Computer-Aided Manufacture ""; ""5. EXPERIMENTAL INVESTIGATIONS ""; ""5.1 In-Vitro Models ""; ""5.2 The Photoelastic Method ""; ""5.3 Improving Experimental Materials""; ""5.3.1 Material Selection, Development and Testing ""; ""5.3.2 Application to 3D Geometries ""; ""5.4 Experimental Rupture Testing""; ""6. CONCLUSION ""; ""ACKNOWLEDGMENTS ""; ""REFERENCES "" 327 $a""3D IMAGING OF PHASE MICROSCOPIC OBJECTS BY DIGITAL HOLOGRAPHIC METHOD""""ABSTRACT ""; ""INTRODUCTION ""; ""1. CLASSICAL AND HOLOGRAPHIC METHODS OF PHASE MICROOBJECTS VISUALIZATION ""; ""1.1 Classical Methods of Phase Microscopic Objects Visualization ""; ""1.1.1 Zernike phase-contrast method""; ""1.1.2 The method of interference contrast ""; ""1.2 Holography as the Method of Recoding and Reconstruction of Waves ""; ""1.3 Holographic Methods of Phase Microscopic Objects Visualization ""; ""1.3.1 History of holographic microscopy "" 327 $a""1.3.2 Holographic phase-contrast method (the method of holographic addition and subtraction in an interference fringe) """"1.3.3 The method of holographic interferometry in fringes of finite width ""; ""1.3.4 Comparison of the possibilities of the holographic methods for solution the problem of obtaining 3D images of phase microobjects ""; ""1.4 Digital Holographic Interference Microscope ""; ""2. APPLICATION OF THE DIGITAL HOLOGRAPHIC MICROSCOPY FOR PHASE MICROOBJECTS STUDY""; ""2.1 DHIM Study of The 3D Morphology of Blood Erythrocytes""; ""2.2 DHIM Study of Thin Transparent Films "" 327 $a""CONCLUSION""""REFERENCES ""; ""ELECTRON MICROSCOPE TOMOGRAPHY IN STRUCTURAL BIOLOGY ""; ""ABSTRACT ""; ""INTRODUCTION""; ""DATA ACQUISITION""; ""PRE-PROCESSING: ALIGNMENT AND RESTORATION ""; ""TOMOGRAPHIC RECONSTRUCTION""; ""POST-PROCESSING AND INTERPRETATION OF TOMOGRAMS ""; ""AN ILLUSTRATIVE EXAMPLE: EMT OF VACCINIA VIRUS ""; ""HIGH PERFORMANCE COMPUTING IN EMT ""; ""SOFTWARE TOOLS FOR EMT ""; ""CONCLUSION ""; ""ACKNOWLEDGMENTS""; ""REFERENCES""; ""THREE-DIMENSIONAL IMAGING AND PROCESSING""; ""ABSTRACT ""; ""1. INTRODUCTION ""; ""2. CURRENT STATUS AND PROBLEM "" 327 $a""3. 3D RECONSTRUCTION ALGORITHM "" 410 0$aComputer Science, Technology and Applications 606 $aThree-dimensional imaging$xIndustrial applications 606 $aThree-dimensional imaging in medicine 606 $aThree-dimensional imaging in biology 608 $aElectronic books. 615 0$aThree-dimensional imaging$xIndustrial applications. 615 0$aThree-dimensional imaging in medicine. 615 0$aThree-dimensional imaging in biology. 676 $a621.36/7 701 $aDuke$b Emerson H$0950558 701 $aAguirre$b Stephen R$0950559 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910452216203321 996 $a3D imaging$92149211 997 $aUNINA LEADER 05324nam 22007815 450 001 9910483236403321 005 20250624084713.0 010 $a3-642-41550-4 024 7 $a10.1007/978-3-642-41550-0 035 $a(CKB)3710000000031292 035 $a(DE-He213)978-3-642-41550-0 035 $a(SSID)ssj0001067703 035 $a(PQKBManifestationID)11600966 035 $a(PQKBTitleCode)TC0001067703 035 $a(PQKBWorkID)11094371 035 $a(PQKB)10731971 035 $a(MiAaPQ)EBC3093203 035 $a(PPN)176116567 035 $a(EXLCZ)993710000000031292 100 $a20131114d2013 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModeling Decisions for Artificial Intelligence $e10th International Conference, MDAI 2013, Barcelona, Spain, November 20-22, 2013, Proceedings /$fedited by Vincenc Torra, Yasuo Narukawa, Guillermo Navarro-Arribas, David Megías 205 $a1st ed. 2013. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013. 215 $a1 online resource (XXII, 309 p. 88 illus.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v8234 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-642-41549-0 327 $aTheory and Applications of Non-additive Measures and Corresponding Integrals -- Some New Domain Restrictions in Social Choice, and Their Consequences -- Weighted Quasi-Arithmetic Means: Utility Functions and Weighting Functions -- Toward a General Framework for Information Fusion -- Facility Location and Social Choice via Microaggregation -- Ordering Pareto Sets with Fuzzy Inference Systems -- A Comparison of Two Approaches for Situation Detection in an Air-to-Air Combat Scenario -- Web 2.0 Tools to Support Decision Making in Enterprise Contexts -- Using the Logarithmic Generator Function in the Spoken Term Detection Task -- Emotion Detection Using Hybrid Structural and Appearance Descriptors -- A Lazy Learning Approach for Self-training -- Combining Recommender and Reputation Systems to Produce Better Online Advice -- Pushing Constraints into a Pattern-Tree -- Generalization of Quadratic Regularized and Standard Fuzzy c-Means Clustering with Respect to Regularization of Hard c-Means -- Semi-supervised Sequential Kernel Regression Models with Pairwise Constraints -- Query Optimization Strategies in Similarity-Based Databases -- Variables for Controlling Cluster Sizes on Fuzzy c-means -- On Sequential Cluster Extraction Based on L1-Regularized Possibilistic Non-metric Model -- Fast Implementations of Markov Clustering for Protein Sequence Grouping -- The Property of ?2 01-Concordance for Bayesian Confirmation Measures -- Permutability of Fuzzy Consequence Operators Induced by Fuzzy Relations -- Fuzzy Multisets in Granular Hierarchical Structures Generated from Free Monoids -- Landmark Selection for Isometric Feature Mapping Based on Mixed-Integer Optimization -- Rough c-Regression Based on Optimization of Objective Function -- Improving Automatic Edge Selection for Relational Classification -- Analyzing the Impact of Edge Modifications on Networks. 330 $aThis book constitutes the proceedings of the 10th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2013, held in Barcelona, Spain, in November 2013. The 24 papers presented in this volume were carefully reviewed and selected from 40 submissions. They deal with the theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v8234 606 $aArtificial intelligence 606 $aPattern recognition systems 606 $aData mining 606 $aApplication software 606 $aInformation storage and retrieval systems 606 $aNumerical analysis 606 $aArtificial Intelligence 606 $aAutomated Pattern Recognition 606 $aData Mining and Knowledge Discovery 606 $aComputer and Information Systems Applications 606 $aInformation Storage and Retrieval 606 $aNumerical Analysis 615 0$aArtificial intelligence. 615 0$aPattern recognition systems. 615 0$aData mining. 615 0$aApplication software. 615 0$aInformation storage and retrieval systems. 615 0$aNumerical analysis. 615 14$aArtificial Intelligence. 615 24$aAutomated Pattern Recognition. 615 24$aData Mining and Knowledge Discovery. 615 24$aComputer and Information Systems Applications. 615 24$aInformation Storage and Retrieval. 615 24$aNumerical Analysis. 676 $a006.3 702 $aTorra$b Vincenc$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aNarukawa$b Yasuo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aNavarro-Arribas$b Guillermo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMegías$b David$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910483236403321 996 $aModeling Decisions for Artificial Intelligence$9772296 997 $aUNINA