LEADER 01542nam a22002771i 4500 001 991002685699707536 005 20040301191000.0 008 040624m19621963uik|||||||||||||||||mul 035 $ab12962132-39ule_inst 035 $aARCHE-091981$9ExL 040 $aDip.to Beni Culturali$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 041 0 $alateng 082 04$a878.01 100 1 $aFronto, Marcus Cornelius$0330713 245 14$aThe correspondence of Marcus Cornelius Fronto :$bwith Marcus Aurelius Antoninus, Lucius Verus, Antoninus Pius, and various friends /$cedited and for the first time translated into english by C. R. Haines 260 $aCambridge :$bHarvard University press ;$aLondon :$bW. Heinemann,$c1962-1963 300 $a2 v. ;$c17 cm 440 4$aThe Loeb classical library 700 1 $aHaines, Charles Reginald 907 $a.b12962132$b02-04-14$c12-07-04 912 $a991002685699707536 945 $aLE001 LAT F3 I$g1$i2001000089208$lle001$nV. 1. - C. 1 PATRIMONIO DELLA BIBLIOTECA INTERFACOLTA. IN CONSULTAZIONE PRESSO LA BIBLIOTECA DEL DIPARTIMENTO DI BENI CULTURALI$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i1356349x$z12-07-04 945 $aLE001 LAT I3 II$g1$i2001000089192$lle001$nV. 2. - C. 1 PATRIMONIO DELLA BIBLIOTECA INTERFACOLTA. IN CONSULTAZIONE PRESSO LA BIBLIOTECA DEL DIPARTIMENTO DI BENI CULTURALI$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i13563506$z12-07-04 996 $aCorrespondence of Marcus Cornelius Fronto$9280399 997 $aUNISALENTO 998 $ale001$b12-07-04$cm$da $e-$fmul$guik$h4$i2 LEADER 06961nam 2200505 450 001 996546841203316 005 20230801215410.0 010 $a981-9916-39-9 024 7 $a10.1007/978-981-99-1639-9 035 $a(CKB)5710000000117068 035 $a(DE-He213)978-981-99-1639-9 035 $a(MiAaPQ)EBC7238830 035 $a(Au-PeEL)EBL7238830 035 $a(PPN)269656332 035 $a(EXLCZ)995710000000117068 100 $a20230801d2023 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aNeural information processing $e29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022, proceedings, part IV /$fedited by Mohammad Tanveer [and four others] 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer,$d[2023] 210 4$d©2023 215 $a1 online resource (XXXV, 707 p. 203 illus., 176 illus. in color.) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1791 311 $a981-9916-38-0 320 $aIncludes bibliographical references and index. 327 $aTheory and Algorithms -- Knowledge Transfer from Situation Evaluation to Multi-agent Reinforcement Learning -- Sequential three-way rules class-overlap under-sampling based on fuzzy hierarchical subspace for imbalanced data -- Two-stage Multilayer Perceptron Hawkes Process -- The Context Hierarchical Contrastive Learning for Time Series in Frequency Domain -- Hawkes Process via Graph Contrastive Discriminant representation Learning and Transformer capturing long-term dependencies -- A Temporal Consistency Enhancement Algorithm Based On Pixel Flicker Correction -- Data representation and clustering with double low-rank constraints -- RoMA: a Method for Neural Network Robustness Measurement and Assessment -- Independent Relationship Detection for Real-Time Scene Graph Generation -- A multi-label feature selection method based on feature graph with ridge regression and eigenvector centrality -- O3GPT: A Guidance-Oriented Periodic Testing Framework with Online Learning, Online Testing, and Online Feedback -- AFFSRN: Attention-Based Feature Fusion Super-Resolution Network -- Temporal-Sequential Learning with Columnar-Structured Spiking Neural Networks -- Graph Attention Transformer Network for Robust Visual Tracking -- GCL-KGE:Graph Contrastive Learning for Knowledge Graph Embedding -- Towards a Unified Benchmark for Reinforcement Learning in Sparse Reward Environments -- Effect of Logistic Activation Function and Multiplicative Input Noise on DNN-kWTA model -- A High-Speed SSVEP-Based Speller Using Continuous Spelling Method -- AAT: Non-Local Networks for Sim-to-Real Adversarial Augmentation Transfer -- Aggregating Intra-class and Inter-class information for Multi-label Text Classification -- Fast estimation of multidimensional regression functions by the Parzen kernel-based method -- ReGAE: Graph autoencoder based on recursive neural networks -- Efficient Uncertainty Quantification for Under-constraint Prediction following Learning using MCMC -- SMART: A Robustness Evaluation Framework for Neural Networks -- Time-aware Quaternion Convolutional Network for Temporal Knowledge Graph Reasoning -- SumBART - An improved BART model for abstractive text summarization -- Saliency-Guided Learned Image Compression for Object Detection -- Multi-Label Learning with Data Self-Augmentation -- MnRec: A News Recommendation Fusion Model Combining Multi-granularity Information -- Infinite Label Selection Method for Mutil-label Classification -- Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning -- Searching for Textual Adversarial Examples with Learned Strategy -- Multivariate Time Series Retrieval with Binary Coding from Transformer. -Learning TSP Combinatorial Search and Optimization with Heuristic Search -- A Joint Learning Model for Open Set Recognition with Post-processing -- Cross-Layer Fusion for Feature Distillation -- MCHPT: A Weakly Supervise Based Merchant Pre-trained Model -- Progressive Latent Replay for efficient Generative Rehearsal -- Generalization Bounds for Set-to-Set Matching with Negative Sampling -- ADA: An Attention-Based Data Augmentation Approach to Handle Imbalanced Textual Datasets -- Countering the Anti-detection Adversarial Attacks -- Evolving Temporal Knowledge Graphs by Iterative Spatio-Temporal Walks -- Improving Knowledge Graph Embedding Using Dynamic Aggregation of Neighbor Information -- Generative Generalized Zero-Shot Learning based on Auxiliary-Features -- Learning Stable Representations with Progressive Autoencoder (PAE) -- Effect of Image Down-sampling on Detection of Adversarial Examples -- Boosting the Robustness of Neural Networks with M-PGD -- StatMix: Data augmentation method that relies on image statistics in federated learning -- Classification by Components Including Chow's Reject Option. -Community discovery algorithm based on improved deep sparse autoencoder -- Fairly Constricted Multi-Objective Particle Swarm Optimization -- Argument Classification with BERT plus Contextual, Structural and Syntactic Features as Text -- Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient -- Optimizing Knowledge Distillation Via Shallow Texture Knowledge Transfer -- Unsupervised Domain Adaptation Supplemented with Generated Images -- MAR2MIX: A Novel Model for Dynamic Problem in Multi-Agent Reinforcement Learning -- Adversarial Training with Knowledge Distillation Considering Intermediate Representations in CNNs -- Deep Contrastive Multi-view Subspace Clustering. 330 $aThe four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22?26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v1791 606 $aNeural computers$vCongresses 606 $aNeural networks (Computer science)$vCongresses 615 0$aNeural computers 615 0$aNeural networks (Computer science) 676 $a745.05 702 $aTanveer$b Mohammad 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996546841203316 996 $aNeural Information Processing$92554499 997 $aUNISA LEADER 02718nam 2200565Ia 450 001 9910830076303321 005 20230721031303.0 010 $a1-280-93262-7 010 $a9786610932627 010 $a0-470-75090-1 010 $a1-4051-8130-3 035 $a(CKB)1000000000412949 035 $a(EBL)306566 035 $a(OCoLC)173616922 035 $a(SSID)ssj0000152964 035 $a(PQKBManifestationID)11178318 035 $a(PQKBTitleCode)TC0000152964 035 $a(PQKBWorkID)10393035 035 $a(PQKB)11654887 035 $a(MiAaPQ)EBC306566 035 $a(EXLCZ)991000000000412949 100 $a20060810d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe fainting phenomenon$b[electronic resource] $eunderstanding why people faint and what to do about it /$fBlair P. Grubb 205 $a2nd ed. 210 $aMalden, MA $cBlackwell Pub.$d2007 215 $a1 online resource (146 p.) 300 $aDescription based upon print version of record. 311 $a1-4051-4841-1 320 $aIncludes bibliographical references and index. 327 $aThe Fainting Phenomenon; Contents; About the author; 1 Introduction; 2 The fainting phenomenon; 3 The normal nervous system; 4 The normal cardiovascular system; 5 Orthostatic intolerance and orthostatic (postural) hypotension; 6 Neurocardiogenic syncope; 7 Postural tachycardia syndrome and chronic fatigue syndrome; 8 Other possible causes of fainting; 9 Fainting in children and adolescents and in older people; 10 Diagnosing the underlying causes of fainting; 11 Treating fainting; 12 Wrapping up; Glossary of useful terms; Index 330 $aFainting, the sudden and often unpredictable loss of consciousness, can be a frightening experience. While often benign, fainting can sometimes be the sign of serious illness. Recurrent fainting can significantly disrupt a person's life, and make them prone to injury and, on occasion, death. The Fainting Phenomenon, Second Edition is a valuable information resource for anyone whose life is affected by fainting. Written for the layperson, this book will help you:Understand the different reasons why people faint and their significance Seek proper medical a 606 $aSyncope (Pathology)$vPopular works 606 $aLoss of consciousness 615 0$aSyncope (Pathology) 615 0$aLoss of consciousness. 676 $a616.12 676 $a616/.047 700 $aGrubb$b Blair P$0941654 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830076303321 996 $aThe fainting phenomenon$93066940 997 $aUNINA