LEADER 01006nam0-22003371i-450- 001 990005668000403321 005 20101221094407.0 035 $a000566800 035 $aFED01000566800 035 $a(Aleph)000566800FED01 035 $a000566800 100 $a19990604d1971----km-y0itay50------ba 101 1 $aita$cfre 102 $aIT 105 $ay-------001yy 200 1 $aPedagogia sperimentale e sperimentazione$fRobert Dottrens 210 $aRoma$cArmando$d1971 215 $a128 p.$d20 cm 225 1 $a<>problemi della didattica$v52 300 $aTraduzione di F. Scorza Barcellona 454 0$12001$aIntroduction à la pédagogie expérimentale$924561 610 0 $aEducazione$aRicerca 676 $a370.72 700 1$aDottrens,$bRobert$0127561 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990005668000403321 952 $a370.72 DOT 1$bIst.ped. 1008$fFLFBC 959 $aFLFBC 996 $aIntroduction a la pedagogie experimentale$924561 997 $aUNINA LEADER 00976nam0-22003251i-450- 001 990006855110403321 005 20070103103253.0 035 $a000685511 035 $aFED01000685511 035 $a(Aleph)000685511FED01 035 $a000685511 100 $a20010426d1997----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $ay-------001yy 200 1 $a<>segreto del nome$eChora, passioni, salvo il nome$fJacques Derrida$ga cura di Gianfranco Dalmasso e Francesco Garritano 210 $aMilano$cJaca Book$d1997 215 $a184 p.$d23 cm 225 1 $aDi fronte e attraverso$v443 676 $a149.1 700 1$aDerrida,$bJacques$f<1930-2004>$0139765 702 1$aDalmasso,$bGianfranco$f<1943- > 702 1$aGarritano,$bFrancesco 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990006855110403321 952 $aCOLLEZ. 122 (443)$b31331$fFSPBC 959 $aFSPBC 996 $aSegreto del nome$9624704 997 $aUNINA LEADER 00940nam--2200361---450- 001 990002877920203316 005 20070308112325.0 035 $a000287792 035 $aUSA01000287792 035 $a(ALEPH)000287792USA01 035 $a000287792 100 $a20070308d1911----km-y0itay50------ba 101 $afre 102 $aFR 105 $a||||||||001yy 200 1 $a<> Immolé$eroman$fEmile Baumann 205 $a7. ed 210 $aParis$cB. Grasset$d1911 215 $a430 p.$d19 cm 300 $asulla cop. : Ouvrage couronné par l'Académie française 410 0$12001 454 1$12001 461 1$1001-------$12001 676 $a843.9 700 1$aBAUMANN,$bEmile$0390271 801 0$aIT$bsalbc$gISBD 912 $a990002877920203316 951 $aXV.5. 446$b197236 LM$cXV.5. 959 $aBK 969 $aFG 979 $aSENATORE$b90$c20070308$lUSA01$h1123 996 $aImmolé$9990261 997 $aUNISA LEADER 06482nam 22006975 450 001 9910983053903321 005 20250220173434.0 010 $a9783031735004 010 $a3031735005 024 7 $a10.1007/978-3-031-73500-4 035 $a(MiAaPQ)EBC31783873 035 $a(Au-PeEL)EBL31783873 035 $a(CKB)36584266700041 035 $a(DE-He213)978-3-031-73500-4 035 $a(OCoLC)1472989247 035 $a(EXLCZ)9936584266700041 100 $a20241115d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProgress in Artificial Intelligence $e23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3?6, 2024, Proceedings, Part II /$fedited by Manuel Filipe Santos, José Machado, Paulo Novais, Paulo Cortez, Pedro Miguel Moreira 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (0 pages) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v14968 311 08$a9783031734991 311 08$a3031734998 327 $aArtificial Intelligence in Medicine (AIM) -- Synthetic Data for Robust Identification of Typical and Atypical Serotonergic Neurons using Convolutional Neural Networks -- Profiling Atopic Dermatitis Patients Using Decision Tree Classifiers to Anticipate Dupilumab Response -- Modeling Temporal Dynamics in Irregular ICU Data Using MWTA-LSTM -- Evaluating Asthma in Equines with Video Recordings -- Predicting Surgical Site Infections: a Time to Event Approach -- A Study on Automatic Analysis of Handwriting Alterations due to Parkinson?s Disease -- Cervical Cancer Detection in Pap Smear Images -- Automating the Clock Drawing Test with Deep Learning and Saliency Maps -- Acute Pancreatitis Mortality Prediction With Federated Learning -- Predictive Modeling for Medication Administration in Intensive Medicine: A Data-Driven Approach -- Artificial Intelligence in Power and Energy Systems (AIPES) -- A Review of Intelligent Technologies in District Heating Systems -- Intelligent Data Mining on Power Systems: Examples from Case Studies.-Application of a Genetic Algorithm for Optimising the Location of Electric Vehicle Charging Stations -- Retrieval-augmented Generation based Assistant: A Smart Home Case Study -- Dynamic Online Parameter Configuration of Genetic Algorithms using Reinforcement Learning -- Assessing Advanced Computer Vision Techniques in Aerial Imagery: A Case Study on Transmission Tower Identification -- Generative Adversarial Networks for Synthetic Meteorological Data Generation -- Artificial Intelligence in Transportation Systems (AITS) -- Fuel Efficiency Analysis of the Public Transportation System Based on the Gaussian Mixture Model Clustering -- Multi-Agent Based Simulation for Decentralized Electric Vehicle Charging Strategies and their Impacts -- Bi-LSTM Neural Networks for Traffic Flow Prediction: A Comprehensive Analysis -- Imbalance Management on Free-floating VSS: A Multi-agent Model Approach -- Ethics and Responsibility in AI (ERAI) -- GASTeNv2: Generative Adversarial Stress Testing Networks with Gaussian Loss -- A Multidimensional Taxonomy for Recent Trends in Explainable Artificial Intelligence -- Explainability of fMRI Decoding Models can Unveil Insights into Neural Mechanisms Related to Emotions -- Dynamics of Fisheries in the Azores Islands: A Network Analysis Approach -- General AI (GAI) -- Detection and Classification of Spam in Social Media Comments using Artificial Intelligence ? a Case Study -- A Comparative Study of Continual Backprop -- Time Series Data Augmentation as an Imbalanced Learning Problem -- Domain Reductions after Preprocessing: Effects on Dynamic Variable Ordering in Constraint Satisfaction Search -- Efficient Image Search and Retrieval System in Cloud Platforms -- Unveiling Cetacean Voices: Entropy-Powered Spectrogram Denoising for Deep Learning Applications. 330 $aThe 3-volume set LNAI 14967, 14968, and 14969 constitutes the proceedings of the 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, held in Viana do Castelo, Portugal, during September 3?6, 2024. The 94 full papers presented in these proceedings were carefully reviewed and selected from 187 submissions. The papers are organized in the following topical sections: Volume I: AI and Creativity (AIC); Ambient Intelligence and Affective Environments (AmIA); Artificial Intelligence and IoT in Agriculture (AIoTA); Artificial Intelligence and Law (AIL); and Artificial Intelligence for Industry and Societies (AI4IS). Volume II: Artificial Intelligence in Medicine (AIM); Artificial Intelligence in Power and Energy Systems (AIPES); Artificial Intelligence in Transportation Systems (AITS); Ethics and Responsibility in AI (ERAI); and General AI (GAI). Volume III: Generative AI ? Foundations and Applications (GenAI); Intelligent Robotics (IROBOT); Knowledge Discovery and Business Intelligence (KDBI); Natural Language Processing, Text Mining and Applications (TeMA); and Data-Centric AI ? Solutions and Emerging Technologies (DCenAI). 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v14968 606 $aArtificial intelligence 606 $aComputer networks 606 $aApplication software 606 $aNatural language processing (Computer science) 606 $aArtificial Intelligence 606 $aComputer Communication Networks 606 $aComputer and Information Systems Applications 606 $aNatural Language Processing (NLP) 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 0$aApplication software. 615 0$aNatural language processing (Computer science) 615 14$aArtificial Intelligence. 615 24$aComputer Communication Networks. 615 24$aComputer and Information Systems Applications. 615 24$aNatural Language Processing (NLP). 676 $a006.3 700 $aSantos$b Manuel Filipe$01782737 701 $aMachado$b Jose?$00 701 $aNovais$b Paulo$0762363 701 $aCortez$b Paulo$0524960 701 $aMoreira$b Pedro Miguel$01782738 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983053903321 996 $aProgress in Artificial Intelligence$94309241 997 $aUNINA