LEADER 01735nam a2200325 i 4500 001 991000807069707536 008 100723m20009999au abef b 000 0 eng d 020 $a3700128150 (pt. 1) 035 $ab13914765-39ule_inst 040 $aBiblioteca Interfacoltà$bita 245 00$aTell el-Dab?a X :$bthe palace district of Avaris : the pottery of the Hyksos period and the kingdom (areas H/III and H/VI) /$cPerla Fuscaldo 246 30$aPalace district of Avaris 246 30$aPottery of the Hyksos period and the new kingdom (areas H/III and H/VI) 260 $aWien :$bVerlag der Österreichischen Akademie der Wissenschaften,$c2000- 300 $a v. :$bill., mappe ;$c31 cm. $e+ 7 c. di tav. ripieg. in cartella 440 0$aDenkschriften der Gesamtakademie ;$vBd. 17 440 0$aUntersuchungen der Zweigstelle Kairo des Österreichischen Archäologischen Institutes ;$vBd. 16 500 $aIn testa al front.: Österreichische Akademie der Wissenschaften 500 $aPt. 1 has accompanying portfolio with four folded plates. 504 $aIncludes bibliographical references. 505 0 $gpt. 1.$tLocus 66 /$rgraphic design, Elisabeth Majerus, Nicola Math and Marian Negrete Martínez. - 135 p., [3] c. di tav. : ill. 650 4$aScavi archeologici$zEgitto 651 4$aEgitto$zTell el-Dab?a 700 1 $aFuscaldo, Perla$eauthor$4http://id.loc.gov/vocabulary/relators/aut$0466775 907 $a.b13914765$b02-04-14$c23-07-10 912 $a991000807069707536 945 $aLE002 Museo papirologico BELT 930.1 FUS$g1$i2002000614780$lle002$og$pE87.00$q-$rn$so $t0$u0$v0$w0$x0$y.i15156175$z23-07-10 996 $aTell el-Dab?a X$91440996 997 $aUNISALENTO 998 $ale002$b23-07-10$cm$da $e-$feng$gau $h0$i0 LEADER 04810nam 22005775 450 001 9910483676703321 005 20251116220948.0 010 $a3-030-15628-1 024 7 $a10.1007/978-3-030-15628-2 035 $a(CKB)4100000008618263 035 $a(MiAaPQ)EBC5811798 035 $a(DE-He213)978-3-030-15628-2 035 $a(PPN)243771584 035 $a(EXLCZ)994100000008618263 100 $a20190706d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning Paradigms $eApplications of Learning and Analytics in Intelligent Systems /$fedited by George A. Tsihrintzis, Maria Virvou, Evangelos Sakkopoulos, Lakhmi C. Jain 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (552 pages) 225 1 $aLearning and Analytics in Intelligent Systems,$x2662-3447 ;$v1 311 08$a3-030-15627-3 327 $aChapter 1: Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems -- Chapter 2: A Comparison of Machine Learning Techniques to Predict the Risk of Heart Failure -- Chapter 3: Differential gene Expression Analysis of RNA-seq Data Using Machine Learning for Cancer Research -- Chapter 4: Machine Learning Approaches for Pap-Smear Diagnosis: An Overview -- Chapter 5: Multi-Kernel Analysis Paradigm Implementing the Learning from Loads Approach for Smart Power Systems -- Chapter 6: Conceptualizing and Measuring Energy Security: Geopolitical Dimensions, Data Availability, Quantitative and Qualitative Methods -- Chapter 7: Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learning -- Chapter 8: Airport Data Analysis Using Common Statistical Methods and Knowledge-Based Techniques -- Chapter 9: A Taxonomy and Review of the Network Data Envelopment Analysis Literature -- Chapter 10: Applying Advanced Data Analytics and Machine Learning to Enhance the Safety Control of Dams -- Chapter 11: Analytics and Evolving Landscape of Machine Learning for Emergency Response -- Chapter 12: Social Media Analytics, Types and Methodology -- Chapter 13: Machine Learning Methods for Opinion Mining in Text: The Past and the Future -- Chapter 14: Ship Detection Using Machine Learning and Optical Imagery in the Maritime Environment -- Chapter 15: Video Analytics for Visual Surveillance and Applications: An Overview and Survey -- Chapter 16: Machine Learning in Alternate Testing of Integrated Circuits. 330 $aThis book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intelligent systems and related technologies. These disciplines are strongly related and mutually complementary; accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation. To maximize the dissemination of research findings, the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most. 410 0$aLearning and Analytics in Intelligent Systems,$x2662-3447 ;$v1 606 $aComputational intelligence 606 $aEngineering?Data processing 606 $aMachine learning 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aData Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11040 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 615 0$aComputational intelligence. 615 0$aEngineering?Data processing. 615 0$aMachine learning. 615 14$aComputational Intelligence. 615 24$aData Engineering. 615 24$aMachine Learning. 676 $a006.31 676 $a006.31 702 $aTsihrintzis$b George A.$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVirvou$b Maria$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSakkopoulos$b Evangelos$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJain$b L. C.$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910483676703321 996 $aMachine Learning Paradigms$91995437 997 $aUNINA