LEADER 00971nam a2200241 i 4500 001 991003331199707536 008 031107s2000 it 000 0 ita d 020 $a883481360X 035 $ab12411802-39ule_inst 040 $aDip.to Studi Giuridici$bita 082 0 $a349.20 100 1 $aBianchi, Paolo$0252084 245 13$aLa creazione giurisprudenziale delle tecniche di selezione dei casi /$cPaolo Bianchi 260 $aTorino :$bG. Giappichelli,$cc2000 300 $a363 p. ;$c24 cm 440 0$aQuaderni del Dipartimento di diritto pubblico, Università di Pisa ;$v19 650 4$aGiustizia costituzionale 907 $a.b12411802$b02-04-14$c07-11-03 912 $a991003331199707536 945 $aLE027 349.20 BIA01.01$g1$iLE027-12570$lle027$o-$pE30.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i13044436$z16-12-03 996 $aCreazione giurisprudenziale delle tecniche di selezione dei casi$9167132 997 $aUNISALENTO 998 $ale027$b06-11-03$cm$da $e-$fita$git $h3$i0 LEADER 01072nam0 22002891i 450 001 UON00329418 005 20231205104214.361 010 $a34-12-11375-1 100 $a20090831d1975 |0itac50 ba 101 $ager 102 $aDE 105 $a|||| ||||| 200 1 $aPalatium und Civitas$eStudien zur Profanotopographie spatantiker Civitas vom 3. bis bis zum 13. Jahrhundert$fCarlrichard Bruhl 205 $aKoln$gWien : Bohlau 210 $a VIII$d275 p.$cc. di tav., cart. ; 29 cm 215 $aVol. I$cGallien. 606 $aCittà$3UONC058232$2FI 620 $aAT$dWien$3UONL003140 620 $aDE$dKöln$3UONL005641 700 1$aBRUHL$bCarlrichard$3UONV059686$0445657 712 $aBöhlau$3UONV246149$4650 801 $aIT$bSOL$c20251107$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00329418 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI EUR B 0414 $eSI SPS150 5 0414 996 $aPalatium und civitas$91286657 997 $aUNIOR LEADER 04741nam 22007215 450 001 9910523725603321 005 20251229082705.0 010 $a3-030-89508-4 024 7 $a10.1007/978-3-030-89508-2 035 $a(CKB)5490000000111326 035 $a(MiAaPQ)EBC6794562 035 $a(Au-PeEL)EBL6794562 035 $a(OCoLC)1285168021 035 $a(DE-He213)978-3-030-89508-2 035 $a(PPN)258299908 035 $a(EXLCZ)995490000000111326 100 $a20211027d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy $eSPIoT-2021 Volume 1 /$fedited by John Macintyre, Jinghua Zhao, Xiaomeng Ma 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (1169 pages) 225 1 $aLecture Notes on Data Engineering and Communications Technologies,$x2367-4520 ;$v97 300 $aIncludes index. 311 08$a3-030-89507-6 327 $aApplication of Artificial Intelligence in Arrangement Creation -- Automatic Segmentation for Retinal Vessel Using Concatenate UNet++ -- Experimental Analysis of Mandarin Tone Pronunciation of Tibetan College Students for Artificial Intelligence Speech Recognition -- Exploration of Paths for Artificial Intelligence Technology to Promote Economic Development -- Influence of RPA Financial Robot on Financial Accounting and its Countermeasures -- Application of Artificial Intelligence Technology in English Online Learning Platform -- Spectral Identification Model of NIR Origin Based on Deep Extreme Learning Machine -- Frontier Application and Development Trend of Artificial Intelligence in New Media in the AI Era -- Analysis on the Application of Machine Learning Stock Selection Algorithm in the Financial Field -- Default Risk Prediction Based on Machine Learning under Big Data Analysis Technology -- Application of Intelligent Detection Technology and Machine Learning Algorithm in Music Intelligent System -- Application of 3D Computer Aided System in Dance Creation and Learning -- Data Selection and Machine Learning Algorithm Application under the Background of Big Data. . 330 $aThis book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field. 410 0$aLecture Notes on Data Engineering and Communications Technologies,$x2367-4520 ;$v97 606 $aEngineering$xData processing 606 $aCooperating objects (Computer systems) 606 $aComputational intelligence 606 $aBig data 606 $aArtificial intelligence 606 $aData Engineering 606 $aCyber-Physical Systems 606 $aComputational Intelligence 606 $aBig Data 606 $aArtificial Intelligence 615 0$aEngineering$xData processing. 615 0$aCooperating objects (Computer systems). 615 0$aComputational intelligence. 615 0$aBig data. 615 0$aArtificial intelligence. 615 14$aData Engineering. 615 24$aCyber-Physical Systems. 615 24$aComputational Intelligence. 615 24$aBig Data. 615 24$aArtificial Intelligence. 676 $a006.31 702 $aMacintyre$b John 702 $aZhao$b Jinghua 702 $aMa$b Xiaomeng 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910523725603321 996 $aThe 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy$92901582 997 $aUNINA