LEADER 01716nam 2200493 450 001 9910702354303321 005 20130115151421.0 035 $a(CKB)5470000002426615 035 $a(OCoLC)824456197 035 $a(EXLCZ)995470000002426615 100 $a20130115d2012 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aReliability of COPVs accounting for margin of safety on design burst /$fPappu L. N. Murthy 210 1$aCleveland, Ohio :$cNational Aeronautics and Space Administration, Glenn Research Center,$d[2012] 215 $a1 online resource (11 pages) $cillustrations 225 1 $a[NASA technical memorandum] ;$vNASA/TM-2012-217638 300 $aTitle from title screen (viewed Jan. 15, 2013). 300 $a"August 2012." 320 $aIncludes bibliographical references (page 11). 606 $aComposite wrapping$2nasat 606 $aPressure vessels$2nasat 606 $aFiber strength$2nasat 606 $aPressure distribution$2nasat 606 $aBurst tests$2nasat 606 $aPressure effects$2nasat 615 7$aComposite wrapping. 615 7$aPressure vessels. 615 7$aFiber strength. 615 7$aPressure distribution. 615 7$aBurst tests. 615 7$aPressure effects. 700 $aMurthy$b P. L. N.$01386975 712 02$aNASA Glenn Research Center, 712 02$aUnited States.$bNational Aeronautics and Space Administration, 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910702354303321 996 $aReliability of COPVs accounting for margin of safety on design burst$93459028 997 $aUNINA LEADER 04022nam 22007215 450 001 9910409836103321 005 20251113185739.0 010 $a981-15-5573-7 024 7 $a10.1007/978-981-15-5573-2 035 $a(CKB)4100000011325766 035 $a(DE-He213)978-981-15-5573-2 035 $a(MiAaPQ)EBC6420083 035 $a(Au-PeEL)EBL6420083 035 $a(OCoLC)1176494182 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/35038 035 $a(MiAaPQ)EBC30592734 035 $a(Au-PeEL)EBL30592734 035 $a(PPN)260301140 035 $a(ODN)ODN0010073103 035 $a(EXLCZ)994100000011325766 100 $a20200703d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRepresentation Learning for Natural Language Processing /$fby Zhiyuan Liu, Yankai Lin, Maosong Sun 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (XXIV, 334 p. 131 illus., 99 illus. in color.) 225 1 $aComputer Science Series 311 08$a981-15-5572-9 327 $a1. Representation Learning and NLP -- 2. Word Representation -- 3. Compositional Semantics -- 4. Sentence Representation -- 5. Document Representation -- 6. Sememe Knowledge Representation -- 7. World Knowledge Representation -- 8. Network Representation -- 9. Cross-Modal Representation -- 10. Resources -- 11. Outlook. 330 $aThis open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing. 410 0$aComputer Science Series 606 $aNatural language processing (Computer science) 606 $aComputational linguistics 606 $aArtificial intelligence 606 $aData mining 606 $aNatural Language Processing (NLP) 606 $aComputational Linguistics 606 $aArtificial Intelligence 606 $aData Mining and Knowledge Discovery 615 0$aNatural language processing (Computer science). 615 0$aComputational linguistics. 615 0$aArtificial intelligence. 615 0$aData mining. 615 14$aNatural Language Processing (NLP). 615 24$aComputational Linguistics. 615 24$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 676 $a006.35 686 $aCOM004000$aCOM021030$aCOM073000$aLAN009000$2bisacsh 700 $aLiu$b Zhiyuan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0851460 702 $aLin$b Yankai$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSun$b Maosong$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910409836103321 996 $aRepresentation Learning for Natural Language Processing$91900993 997 $aUNINA