LEADER 02705nam 2200649 a 450 001 9910785812703321 005 20230207214548.0 010 $a3-11-088566-2 024 7 $a10.1515/9783110885668 035 $a(CKB)2670000000251155 035 $a(EBL)936552 035 $a(OCoLC)843205604 035 $a(SSID)ssj0000594791 035 $a(PQKBManifestationID)11414699 035 $a(PQKBTitleCode)TC0000594791 035 $a(PQKBWorkID)10549745 035 $a(PQKB)11166596 035 $a(MiAaPQ)EBC936552 035 $a(WaSeSS)Ind00009446 035 $a(DE-B1597)55479 035 $a(OCoLC)979764444 035 $a(DE-B1597)9783110885668 035 $a(Au-PeEL)EBL936552 035 $a(CaPaEBR)ebr10598088 035 $a(EXLCZ)992670000000251155 100 $a19930513d1993 uy 0 101 0 $ager 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBetteln und Spenden$b[electronic resource] $eeine soziologische Studie u?ber Rituale freiwilliger Armenunterstu?tzung, ihre historischen und aktuellen Formen sowie ihre sozialen Leistungen /$fAndreas Voss 205 $aReprint 2010 210 $aBerlin ;$aNew York $cW. de Gruyter$d1993 215 $a1 online resource (224 p.) 225 0 $aMateriale Soziologie / TB ;$v2 225 0$aMateriale Soziologie.$pTB ;$v2 300 $aDescription based upon print version of record. 311 $a3-11-013578-7 320 $aIncludes bibliographical references (p. [169]-174). 327 $t Frontmatter -- $tEinleitung -- $t1 Marksteine und Wendepunkte in der historischen Entwicklung der Armenfürsorge -- $t2 Die Grundmerkmale und Grundformen formal freiwilliger Armenunterstützung und die Definition des Forschungsgegenstandes -- $t3 Die Entfaltung des Forschungsinteresses, der Fragestellung sowie Angaben zur Methode -- $t4 Direktes Betteln und Spenden -- $t5 Vermitteltes Betteln und Spenden -- $t6 Die Deutung -- $tLiteratur -- $tBildteil -- $tAbbildungsnachweis 330 $aBetteln Und Spenden: Eine Soziologische Studie Ber Rituale Freiwilliger Armenunterst Tzung, Ihre Historischen Und Aktuellen Formen Sowie Ihre Sozialen Leistungen 410 0$aMateriale Soziologie / TB 606 $aCharities$zGermany$xSocieties, etc 606 $aVolunteer workers in social service$zGermany 615 0$aCharities$xSocieties, etc. 615 0$aVolunteer workers in social service 676 $a330 686 $aMS 6440$2rvk 700 $aVoss$b Andreas$01551031 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910785812703321 996 $aBetteln und Spenden$93810315 997 $aUNINA LEADER 04513nam 22006855 450 001 9910580150803321 005 20251113190759.0 010 $a981-19-0840-0 024 7 $a10.1007/978-981-19-0840-8 035 $a(MiAaPQ)EBC7022391 035 $a(Au-PeEL)EBL7022391 035 $a(CKB)24088213000041 035 $aEBL7022391 035 $a(AU-PeEL)EBL7022391 035 $a(PPN)26781366X 035 $a(OCoLC)1333704668 035 $a(DE-He213)978-981-19-0840-8 035 $a(EXLCZ)9924088213000041 100 $a20220625d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Machine Intelligence and Signal Processing /$fedited by Deepak Gupta, Koj Sambyo, Mukesh Prasad, Sonali Agarwal 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (859 pages) 225 1 $aLecture Notes in Electrical Engineering,$x1876-1119 ;$v858 300 $aDescription based upon print version of record. 311 08$aPrint version: Gupta, Deepak Advanced Machine Intelligence and Signal Processing Singapore : Springer,c2022 9789811908392 320 $aIncludes bibliographical references. 327 $aLeukocyte Subtyping using Convolutional Neural Networks for Enhanced Disease Prediction -- Comparative analysis of novel approaches to automated COVID-19 detection using radiography images -- OXGBoost: An Optimized eXtreme Gradient Boosting Algorithm for Classification of Breast Cancer -- An Empirical Study on Graph-based Clustering Algorithms using Schizophrenia Genes -- Traffic Rule Violation Detection System: Deep Learning Approach -- A Web Application for Early Prediction of Diabetes Using Artificial Neural Network -- Web based disease prediction system via machine learning approach. 330 $aThis book covers the latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing, and their applications in real world. The topics covered in machine learning involve feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modeling from video, 3D object recognition, localization and tracking, medical image analysis, and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multitask, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), and electromyogram (EMG). 410 0$aLecture Notes in Electrical Engineering,$x1876-1119 ;$v858 606 $aComputational intelligence 606 $aMachine learning 606 $aTelecommunication 606 $aSignal processing 606 $aComputational Intelligence 606 $aMachine Learning 606 $aCommunications Engineering, Networks 606 $aSignal, Speech and Image Processing 615 0$aComputational intelligence. 615 0$aMachine learning. 615 0$aTelecommunication. 615 0$aSignal processing. 615 14$aComputational Intelligence. 615 24$aMachine Learning. 615 24$aCommunications Engineering, Networks. 615 24$aSignal, Speech and Image Processing. 676 $a006.31 702 $aGupta$b Deepak 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910580150803321 996 $aAdvanced machine intelligence and signal processing$92998390 997 $aUNINA