LEADER 01735oam 2200493 450 001 9910704919703321 005 20131219122603.0 035 $a(CKB)5470000002446552 035 $a(OCoLC)865579873 035 $a(EXLCZ)995470000002446552 100 $a20131219d1988 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAccretion shock geometries in the magnetic variables /$fby H.S. Stockman 210 1$aBaltimore, Maryland :$cSpace Telescope Science Institute;$a[Washington, DC] :$c[National Aeronautics and Space Administration],$d[1988] 215 $a1 online resource (22 pages) $cillustrations 225 1 $aNASA-CR ;$v186290 225 1 $aSpace Telescope Science Institute preprint series ;$vno. 293 300 $aTitle from title screen (viewed on Dec. 19, 2013). 300 $a"July 1988." 320 $aIncludes bibliographical references (pages 13-14). 606 $aCanonical forms$2nasat 606 $aMagnetic stars$2nasat 606 $aShock waves$2nasat 606 $aStellar mass accretion$2nasat 606 $aStellar models$2nasat 615 7$aCanonical forms. 615 7$aMagnetic stars. 615 7$aShock waves. 615 7$aStellar mass accretion. 615 7$aStellar models. 700 $aStockman$b H. S$g(H. S. Peter),$0322369 712 02$aSpace Telescope Science Institute (U.S.), 712 02$aUnited States.$bNational Aeronautics and Space Administration, 801 0$bGPO 801 1$bGPO 801 2$bGPO 906 $aBOOK 912 $a9910704919703321 996 $aAccretion shock geometries in the magnetic variables$93493856 997 $aUNINA LEADER 06698nam 22008295 450 001 9910865239103321 005 20250626164135.0 010 $a9783031627996$b(electronic bk.) 010 $z9783031627989 024 7 $a10.1007/978-3-031-62799-6 035 $a(MiAaPQ)EBC31471656 035 $a(Au-PeEL)EBL31471656 035 $a(CKB)32273978300041 035 $a(DE-He213)978-3-031-62799-6 035 $a(OCoLC)1439597655 035 $a(EXLCZ)9932273978300041 100 $a20240612d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Artificial Intelligence $e20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, A Coruña, Spain, June 19?21, 2024, Proceedings /$fedited by Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas, Verónica Bolón-Canedo, Elena Hernández-Pereira, Oscar Fontenla-Romero, David Camacho, Juan Ramón Rabuñal, Manuel Ojeda-Aciego, Jesús Medina, José C. Riquelme, Alicia Troncoso 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (293 pages) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v14640 311 08$aPrint version: Alonso-Betanzos, Amparo Advances in Artificial Intelligence Cham : Springer International Publishing AG,c2024 9783031627989 327 $a -- Taking Advantage of Depth Information for Semantic Segmentation in Field-Measured Vineyards. -- Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains. -- Deep Variational Auto-Encoder for Model-based Water Quality Patrolling with Intelligent Surface Vehicles. -- An Architecture Towards Building a Reliable Suicide Information Chatbot. -- Age estimation using soft labelling ordinal classification approaches. -- O-Hydra: a hybrid convolutional and dictionary-based approach to Time Series Ordinal Classification. -- Predicting Parkinson?s Disease Progression: Analyzing Prodromal Stages through Machine Learning. -- Ground-Level Ozone Forecasting using Explainable Machine Learning. -- Multi-Objective Lagged Feature Selection based on Dependence Coefficient for Time-Series Forecasting. -- FuSDG: A proposal for a fuzzy assessment of Sustainable Development goals achievement. -- A surrogate assisted approach for fitness computation in robust optimization over time. -- A Path Relinking-based approach for the Bi-Objective Double Floor Corridor Allocation Problem. -- An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines. -- Preserving the Essential Features in CNNs: Pruning and Analysis. -- Iterated Local Search for the Facility Location problem with Limited Choice rule. -- Driven PCTBagging: Seeking greater discriminating capacity for the same level of interpretability. -- Semi-supervised learning methods for Semantic Segmentation of Polyps. -- Community-Based Topic Modeling with Contextual Outlier Handling. -- Toward Explaining Competitive Success in League of Legends: A Machine Learning Analysis. -- Reconstruction-based Anomaly Detection in Wind Turbine Operation Time Series using Generative Models. -- Multi-class and Multi-label Classification of an Assembly Task in Manufacturing. -- Image Processing and Deep Learning Methods for the Semantic Segmentation of Blastocyst Structures. -- Multivariate-Autoencoder flow-analogue method for heat waves reconstruction. -- HEX-GNN: Hierarchical EXpanders for Node Classification. -- The notion of bond in the multi-adjoint concept lattice framework. -- Exploring the use of LLMs for teaching AI and Robotics concepts at a Master's Degree. -- Exploring the Capabilities and Limitations of Neural Methods in the Maximum Cut. 330 $aThis book constitutes the refereed proceedings of the 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, held in A Coruña, Spain, during June 19?21, 2024. The 27 full papers presented in this book were carefully reviewed and selected from 38 submissions. CAEPIA is a forum open to researchers from all over the world to present and discuss their latest scientific and technological advances in Artificial Intelligence (AI). The papers cover such themes as: machine learning, search and optimization, creativity and AI, ontologies and knowledge graphs, education and AI, foundation, models and applications of AI, uncertainty in AI, ambient intelligence and smart environments, explainable and responsible AI, fuzzy logic, natural language processing, knowledge representation, reasoning and logic, constraints, search and planning, multi-agent systems, computer vision and robotics, and intelligent web and information retrieval. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v14640 606 $aArtificial intelligence 606 $aComputer networks 606 $aSocial sciences$xData processing 606 $aEducation$xData processing 606 $aComputer vision 606 $aApplication software 606 $aArtificial Intelligence 606 $aComputer Communication Networks 606 $aComputer Application in Social and Behavioral Sciences 606 $aComputers and Education 606 $aComputer Vision 606 $aComputer and Information Systems Applications 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 0$aSocial sciences$xData processing. 615 0$aEducation$xData processing. 615 0$aComputer vision. 615 0$aApplication software. 615 14$aArtificial Intelligence. 615 24$aComputer Communication Networks. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aComputers and Education. 615 24$aComputer Vision. 615 24$aComputer and Information Systems Applications. 676 $a006.3 700 $aAlonso-Betanzos$b Amparo$01742682 701 $aGuijarro-Berdiñas$b Bertha$01742683 701 $aBolo?n-Canedo$b Vero?nica$00 701 $aHernández-Pereira$b Elena$01742684 701 $aFontenla-Romero$b Oscar$01742685 701 $aCamacho$b David$0995300 701 $aRabuñal$b Juan Ramón$01742686 701 $aOjeda-Aciego$b Manuel$01423741 701 $aMedina$b Jesu?s$00 701 $aRiquelme$b José C$01742687 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910865239103321 996 $aAdvances in Artificial Intelligence$94169394 997 $aUNINA