LEADER 02714nam 22006134a 450 001 9910782119403321 005 20230617040721.0 010 $a1-281-93439-9 010 $a9786611934392 010 $a981-279-422-0 035 $a(CKB)1000000000537803 035 $a(StDuBDS)AH24685101 035 $a(SSID)ssj0000211961 035 $a(PQKBManifestationID)11169167 035 $a(PQKBTitleCode)TC0000211961 035 $a(PQKBWorkID)10136045 035 $a(PQKB)11055695 035 $a(MiAaPQ)EBC1681228 035 $a(WSP)00005452 035 $a(Au-PeEL)EBL1681228 035 $a(CaPaEBR)ebr10255532 035 $a(CaONFJC)MIL193439 035 $a(OCoLC)815752313 035 $a(EXLCZ)991000000000537803 100 $a20040617d2004 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aNonlinear theory of elasticity$b[electronic resource] $eapplications in biomechanics /$fLarry A. Taber 210 $aRiver Edge, NJ $cWorld Scientific$dc2004 215 $a1 online resource (xvi, 399 p. ) $cill 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a981-238-735-8 320 $aIncludes bibliographical references (p. 389-394) and index. 327 $aVectors, Dyadics, and Tensors; Analysis of Deformation; Analysis of Stress; Constitutive Relations; Biomechanics Applications. 330 $aSoft biological tissues often undergo large elastic (or nearly elastic) deformations that can be analyzed using the nonlinear theory of elasticity. Because of the varied approaches to nonlinear elasticity in the literature, some aspects of the subject may be difficult to appreciate. 330 $bSoft biological tissues often undergo large elastic (or nearly elastic) deformations that can be analyzed using the nonlinear theory of elasticity. Because of the varied approaches to nonlinear elasticity in the literature, some aspects of the subject may be difficult to appreciate. This book attempts to clarify and unify those treatments, illustrating the advantages and disadvantages of each through various examples in the mechanics of soft tissues. Applications include muscle, arteries, the heart, embryonic tissues, and biological membranes. 606 $aElasticity 606 $aBiomechanics 606 $aNonlinear mechanics 615 0$aElasticity. 615 0$aBiomechanics. 615 0$aNonlinear mechanics. 676 $a571.4/3 700 $aTaber$b Larry Alan$0472546 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910782119403321 996 $aNonlinear theory of elasticity$9225592 997 $aUNINA LEADER 04028oam 2200481 450 001 9910299038703321 005 20190911112727.0 010 $a94-007-7284-X 024 7 $a10.1007/978-94-007-7284-7 035 $a(OCoLC)865654312 035 $a(MiFhGG)GVRL6XDE 035 $a(EXLCZ)992670000000429195 100 $a20140415d2014 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 00$aComputing meaning$hVolume 4 /$fHarry Bunt, Johan Bos, Stephen Pulman, editors 205 $a1st ed. 2014. 210 1$aDordrecht, Netherlands :$cSpringer,$d2014. 215 $a1 online resource (viii, 260 pages) $cillustrations 225 1 $aText, Speech and Language Technology,$x1386-291X ;$v47 300 $a"ISSN: 1386-291X." 311 $a94-007-7283-1 320 $aIncludes bibliographical references and index. 327 $aComputing Meaning: Annotation, Representation, and Inference by Harry Bunt, Johan Bos, and Stephen Pulman -- Part I Semantic Representation and Compositionality . Deterministic Statistical Mapping of Sentences to Underspecified Semantics by Hiyan Alshawi, Pi-Chuan Chang, and Michael Ringgaard -- A formal approach to linking logical form and vector-space lexical semantics by Dan Garrette, Katrin Erk, and Raymond Mooney -- Annotations that effectively contribute to semantic interpretation by Harry Bunt -- Concrete Sentence Spaces for Compositional Distributional Models of Meaning by Edward Grefenstette, Mehmoosh Sadrzadeh, Stephen Clark, Bob Coecke, and Stephen Pulman --  Part II Inference and Understanding . Recognizing Textual Entailment and Computational Semantics by Johan Bos -- Abductive Reasoning with a Large Knowledge Base for Discourse Processing by Ekaterina Ovchinnikova, Niloofar Montazeri, Theodore Alexandrov, Jerry R. Hobbs, Michael C. McCord, and Rutu Mulkar-Mehta -- Natural logic and natural language inference by Bill MacCartney and Christopher D. Manning -- Designing Efficient Controlled Languages for Ontologies by Camilo Thorne, Raffaella Bernardi, and Diego Calvanese -- Part III Semantic Resources and Annotation . A Context-Change Semantics for Dialogue Acts by Harry Bunt -- VerbNet Class Assignment as a WSD Task by Susan Windisch Brown, Dmitriy Dligach and Martha Palmer -- Annotation of Compositional Operations with GLML by Pustejovsky, Rumshisky, Batiukova, and Moszkowicz -- Incremental Recognition and Prediction of Dialogue Acts by Volha Petukhova and Harry Bunt -- Index . 330 $aThis book is a collection of papers by leading researchers in computational semantics. It presents a state-of-the-art overview of recent and current research in computational semantics, including descriptions of new methods for constructing and improving resources for semantic computation, such as WordNet, VerbNet, and semantically annotated corpora. It also presents new statistical methods in semantic computation, such as the application of distributional semantics in the compositional calculation of sentence meanings. Computing the meaning of sentences, texts, and spoken or texted dialogue is the ultimate challenge in natural language processing, and the key to a wide range of exciting applications. The breadth and depth of coverage of this book makes it suitable as a reference and overview of the state of the field for researchers in Computational Linguistics, Semantics, Computer Science, Cognitive Science, and Artificial Intelligence. 410 0$aText, speech, and language technology ;$vvolume 47. 606 $aSemantics$xData processing 606 $aFormal languages$xSemantics 615 0$aSemantics$xData processing. 615 0$aFormal languages$xSemantics. 676 $a401.430285 702 $aBunt$b Harry C. 702 $aBos$b Johannes 702 $aPulman$b S. G.$f1949- 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910299038703321 996 $aComputing Meaning$92124956 997 $aUNINA