LEADER 04882nam 22006615 450 001 996418253503316 005 20200719185423.0 010 $a3-030-46939-5 024 7 $a10.1007/978-3-030-46939-9 035 $a(CKB)4100000011354651 035 $a(DE-He213)978-3-030-46939-9 035 $a(MiAaPQ)EBC6273611 035 $a(PPN)258875399 035 $a(EXLCZ)994100000011354651 100 $a20200719d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Computational and Bio-Engineering$b[electronic resource] $eProceeding of the International Conference on Computational and Bio Engineering, 2019, Volume 1 /$fedited by S. Jyothi, D. M. Mamatha, Suresh Chandra Satapathy, K. Srujan Raju, Margarita N. Favorskaya 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (X, 667 p. 273 illus., 194 illus. in color.) 225 1 $aLearning and Analytics in Intelligent Systems,$x2662-3447 ;$v15 311 $a3-030-46938-7 327 $aChapter 1: Sequential Pattern Mining for U.S. presidential elections using Google Cloud Platform (GCP) -- Chapter 2: An evolutionary optimization methodology for analysing breast canr gene sequens using MSAPSO and MSADE -- Chapter 3: Performing Image Compression and Decompression Using Matrix Substitution Technique -- Chapter 4: Classification of Cotton Crop Pests using Big Data Analytics -- Chapter 5: Effect Of Formulation Variables on Optimization of Gastroretentive in Situ Rafts of Bosentan Monohydrate HCL by 32 Factorial Design -- Chapter 6: Performan Analysis of Apache Spark ML lib Clustering on Batch Data Stored in Cassandra -- Chapter 7: A study on Opinion of B.Sc Nursing studentson Health Informatics and EMR to included in Nursing Education -- Chapter 8: A Comprehensive Hybrid Ensemble Method with Feature Selection Techniques -- Chapter 9: DNA based Quick Response (QR) code for Screening of Potential Parents for Evolving new Silkworm Ras of high Productivity -- Chapter 10: Big Data Analysis for Land Use Classification Using Machine Learning Algorithms. 330 $aThis book gathers state-of-the-art research in computational engineering and bioengineering to facilitate knowledge exchange between various scientific communities. Computational engineering (CE) is a relatively new discipline that addresses the development and application of computational models and simulations often coupled with high-performance computing to solve complex physical problems arising in engineering analysis and design in the context of natural phenomena. Bioengineering (BE) is an important aspect of computational biology, which aims to develop and use efficient algorithms, data structures, and visualization and communication tools to model biological systems. Today, engineering approaches are essential for biologists, enabling them to analyse complex physiological processes, as well as for the pharmaceutical industry to support drug discovery and development programmes. 410 0$aLearning and Analytics in Intelligent Systems,$x2662-3447 ;$v15 606 $aBiomathematics 606 $aComputational intelligence 606 $aBiomedical engineering 606 $aEngineering mathematics 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 606 $aEngineering Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/T11030 615 0$aBiomathematics. 615 0$aComputational intelligence. 615 0$aBiomedical engineering. 615 0$aEngineering mathematics. 615 14$aMathematical and Computational Biology. 615 24$aComputational Intelligence. 615 24$aBiomedical Engineering and Bioengineering. 615 24$aEngineering Mathematics. 676 $a004 702 $aJyothi$b S$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMamatha$b D. M$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSatapathy$b Suresh Chandra$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRaju$b K. Srujan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFavorskaya$b Margarita N$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996418253503316 996 $aAdvances in Computational and Bio-Engineering$92084628 997 $aUNISA LEADER 01183nam a2200265 i 4500 001 991001773949707536 008 120702s1985 enk 000 0 eng d 035 $ab14068321-39ule_inst 040 $aDip.to Filologia Class. e Scienze Filosofiche$bita 082 00$a882.01 100 1 $aCropp, Martin$0326416 245 10$aResolutions and chronology in Euripides :$bthe fragmentary tragedies /$cby Martin Cropp and Gordon Fick 260 $aLondon :$bInstitute of Classical Studies, University of London,$c1985 300 $aXI, 92 p. :$bill. ;$c28 cm 440 0$aBulletin supplement (University of London. Institute of Classical Studies) ;$v43 490 1 $aBulletin supplement ;$v43 504 $aBibliografia: p. XI 600 04$aEuripides$xStile 700 1 $aFick, Gordon$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0732088 907 $a.b14068321$b02-07-12$c02-07-12 912 $a991001773949707536 945 $aLE007 880.1 Euripides 1985-02$g1$i2007000231432$lle007$og$pE15.00$q-$rl$s- $t0$u1$v0$w1$x0$y.i15429829$z02-07-12 996 $aResolutions and chronology in Euripides$91442378 997 $aUNISALENTO 998 $ale007$b02-07-12$cm$da $e-$feng$genk$h0$i0 LEADER 02909oam 2200565 c 450 001 9910563009303321 005 20250513224735.0 024 7 $a10.3726/b13541 035 $a(CKB)5450000000173876 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/34930 035 $a(PH02)9783631749746 035 $a(oapen)doab34930 035 $a(EXLCZ)995450000000173876 100 $a20240525h20182009 uy 0 101 0 $ager 135 $aurnnunnnannuu 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 04$aDie Ausweitung des Versichertenkreises der Gesetzlichen Rentenversicherung$eBestimmungsgründe und Verteilungswirkungen$fBert Rürup, Bert Rürup, Anabell Kohlmeier 205 $a1st, New ed. 210 $aFrankfurt a.M$cPH02$d2018 210 $d2018, c2009 215 $a1 online resource (229 p.)$c, EPDF 225 0 $aSozialo?konomische Schriften$v36 300 $aPeter Lang GmbH, Internationaler Verlag der Wissenschaften 311 08$a3-631-74974-0 327 $aAus dem Inhalt: Alterssicherung in Deutschland - Interne Rendite und implizite Steuer - Ausweitungsoptionen des Versichertenkreises der Gesetzlichen Rentenversicherung - Altersarmut und Schutzbedu?rftigkeit - Effekte der Ausweitung auf die implizite Besteuerung - Politische Handlungsempfehlung. 330 $aSeit einigen Jahren werden verschiedene Optionen der Ausweitung des Versichertenkreises der Gesetzlichen Rentenversicherung diskutiert, in der zurzeit die abha?ngig Bescha?ftigten und lediglich einige Selbsta?ndige versichert sind. Prima?res Ziel dieser Ausweitungsoptionen ist es, potentiell zu erwartende Altersarmut zu verhindern. Allerdings ist unklar, inwieweit die jeweils zu integrierenden Gruppen tatsa?chlich von Altersarmut bedroht sind, bzw. ob eine Pflichtversicherung in der Gesetzlichen Rentenversicherung diese verhindern kann. Ziel der Arbeit ist es, Antworten auf diese Fragen zu finden und die verschiedenen Ausweitungsoptionen im Hinblick auf die implizite Besteuerung in der Gesetzlichen Rentenversicherung zu analysieren sowie eine politische Handlungsempfehlung abzugeben. 606 $aWelfare economics$2bicssc 610 $aAltersarmut 610 $aAlterssicherung in Deutschland 610 $aAusweitung 610 $aBestimmungsgründe 610 $aGesetzlichen 610 $aImplizite Besteuerung 610 $aKohlmeier 610 $aRentenversicherung 610 $aVersichertenkreises 610 $aVerteilungswirkungen 615 7$aWelfare economics 700 $aKohlmeier$b Anabell$4auth$01282235 702 $aRu?rup$b Bert$4edt 702 $aKohlmeier$b Anabell$4aut 801 0$bPH02 801 1$bPH02 906 $aBOOK 912 $a9910563009303321 996 $aDie Ausweitung des Versichertenkreises der Gesetzlichen Rentenversicherung$93018744 997 $aUNINA