LEADER 01168nam0 22003253i 450 001 UFI0426828 005 20231121125909.0 010 $a9042010657 100 $a20160401d2003 ||||0itac50 ba 101 | $aeng 102 $anl 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $a˜The œAvestan vowels$fMichiel de Vaan 210 $aAmsterdam$aNew York$cRodopi$d2003 215 $aXXXV, 710 p.$d24 cm. 225 | $aLeiden studies in Indo-European$v12 410 0$1001UFI0132058$12001 $aLeiden studies in Indo-European$v12 606 $aLingue indoeuropee$x[Lingua avestana]$xGrammatica$2FIR$3RMLC423535$9I 606 $aLingua avestica$xVocali$2FIR$3UFIC101748$9I 676 $a491.525$9$v21 700 1$aVaan$b, Michiel Arnoud Cor : de$3UFIV153121$4070$01448230 801 3$aIT$bIT-01$c20160401 850 $aIT-FR0017 899 $aBiblioteca umanistica Giorgio Aprea$bFR0017 $eN 912 $aUFI0426828 950 0$aBiblioteca umanistica Giorgio Aprea$d 52MAG 4/633$e 52DSU0000000305 VMN RS $fA $h20190926$i20190926 977 $a 52 996 $aAvestan vowels$93641939 997 $aUNICAS LEADER 02221nas 2200577-c 450 001 996480963603316 005 20231228213020.0 011 $a2013-2298 035 $a(DE-599)ZDB2642638-9 035 $a(OCoLC)786448915 035 $a(CKB)2670000000120811 035 $a(CONSER)--2012254119 035 $a(EXLCZ)992670000000120811 100 $a20120227a20099999 --- b 101 0 $acat 135 $aurmnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aRevista d'innovació docent universitària 210 1$aBarcelona$cUniversitat de Barcelona, Facultat d'Economia i Empresa, Departament de Matemàtica Econòmica, Financera i Actuarial$d2009- 215 $a1 online resource 311 $a2014-1319 517 1 $aRIDU 531 0 $aRev. innov. docent univ. 606 $aEducational innovations$vPeriodicals 606 $aEducation, Higher$xStudy and teaching$vPeriodicals 606 $aEducation$xStudy and teaching (Higher)$vPeriodicals 606 $aEnseignement$xInnovations$vPériodiques 606 $aEnseignement supérieur$xÉtude et enseignement$vPériodiques 606 $aInnovaciones educativas$vPublicaciones periódicas$2embne 606 $aEnseñanza superior$vPublicaciones periódicas$2embne 606 $aEducation, Higher$xStudy and teaching$2fast 606 $aEducation$xStudy and teaching (Higher)$2fast 606 $aEducational innovations$2fast 608 $aPeriodicals$2fast 615 0$aEducational innovations 615 0$aEducation, Higher$xStudy and teaching 615 0$aEducation$xStudy and teaching (Higher) 615 6$aEnseignement$xInnovations 615 6$aEnseignement supérieur$xÉtude et enseignement 615 7$aInnovaciones educativas 615 7$aEnseñanza superior 615 7$aEducation, Higher$xStudy and teaching 615 7$aEducation$xStudy and teaching (Higher) 615 7$aEducational innovations 712 02$aUniversitat de Barcelona.$bDepartament de Matemàtica Econòmica, Financera i Actuarial, 906 $aJOURNAL 912 $a996480963603316 996 $aRevista d'innovació docent universitària$92219709 997 $aUNISA LEADER 03129nam 22005895 450 001 9910367238003321 005 20250220112244.0 010 $a9789811518607 010 $a9811518602 024 7 $a10.1007/978-981-15-1860-7 035 $a(CKB)5280000000190054 035 $a(MiAaPQ)EBC5997309 035 $a(DE-He213)978-981-15-1860-7 035 $a(PPN)242817947 035 $a(EXLCZ)995280000000190054 100 $a20191212d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNon-intrusive Load Monitoring $eTheory, Technologies and Applications /$fby Hui Liu 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (288 pages) 311 08$a9789811518591 311 08$a9811518599 327 $aIntroduction -- Detection of Transient Events in Time Series -- Appliance Signature Extraction -- Appliance Identification Based on Template Matching -- Steady State Current Decomposition Based Appliance Identification -- Machine Learning Based Appliance Identification -- Hidden Markov Models Based Appliance Identification -- Deep Learning Based Appliance Identification -- Deterministic Prediction of Electric Load Time Series -- Interval Prediction of Electric Load Time Series. 330 $aFocusing on non-intrusive load monitoring techniques in the area of smart grids and smart buildings, this book presents a thorough introduction to related basic principles, while also proposing improvements. As the basis of demand-side energy management, the non-intrusive load monitoring techniques are highly promising in terms of their energy-saving and carbon emission reduction potential. The book is structured clearly and written concisely. It introduces each aspect of these techniques with a number of examples, helping readers to understand and use the corresponding results. It provides latest strengths on the non-intrusive load monitoring techniques for engineers and managers of relevant departments. It also offers extensive information and a source of inspiration for researchers and students, while outlining future research directions. 606 $aEnergy policy 606 $aEnergy policy 606 $aArtificial intelligence 606 $aElectric power production 606 $aEnergy Policy, Economics and Management 606 $aArtificial Intelligence 606 $aElectrical Power Engineering 615 0$aEnergy policy. 615 0$aEnergy policy. 615 0$aArtificial intelligence. 615 0$aElectric power production. 615 14$aEnergy Policy, Economics and Management. 615 24$aArtificial Intelligence. 615 24$aElectrical Power Engineering. 676 $a621.317 700 $aLiu$b Hui$4aut$4http://id.loc.gov/vocabulary/relators/aut$0274539 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910367238003321 996 $aNon-intrusive Load Monitoring$92184209 997 $aUNINA