Search results for "apprentissage."

showing 10 items of 188 documents

Le manuel de conversation sur Palerme et la Sicile de Giuseppina Catalano

2018

Le livre de Giuseppina Catalano, Palerme et la Sicile, Causeries familiaires (sic) servant à la conversation française par Mme Joséphine Catalano, édité à Palerme en 1907, s’insère dans une longue tradition de manuels de conversation à l’usage de l’enseignement de la langue française dans les écoles ou simplement en tant que support dans l’autoapprentissage.

Settore L-LIN/04 - Lingua E Traduzione - Lingua FranceseEnseignement de la langue française Causeries Giuseppina Catalano manuels de conversation autoapprentissage.
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Contribution of Multi-Agent Systems and Fuzzy logic to support tutors in Learning Communities

2016

The growing importance of online training has put emphasis on the role of remote tutoring. A whole new area of research, dedicated to environment for human learning (EHL), is emerging. We are concerned with this field. More specifically, we will focus on the monitoring of learners.The instrumentation and observation of learners activities by exploiting interaction traces in the EHL and the development of indicators can help tutors to monitor activities of learners and support them in their collaborative learning process. Indeed, in a learning situation, the teacher needs to observe the behavior of learners in order to build an idea about their involvement, preferences and learning styles so…

Social ProfilesPédagogie de projetLogique floueMulti-Agent SystemApprentissage collectifCollaborative LearningAnalyse de texteNaïve bayésienneNaïve BayesFuzzy LogicCSCLProfils sociaux[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]Système Multi-Agents[INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC]Acte langageConversation Analysis
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L’influence des facteurs stratégiques et organisationnels sur les relations entre contrôle de gestion environnemental et apprentissage organisationne…

2020

Cet article étudie les relations entre contrôle de gestion environnemental (CGE) et apprentissage organisationnel (AO) en inscrivant le modèle de Simons (1995) dans une perspective contingente. Par des facteurs stratégiques et organisationnels, ce modèle enrichi explique les liens entre les modes de contrôle (diagnostique et interactif) de Simons et les niveaux d’apprentissage (en simple et double boucle) d’Argyris et Schön (1978). S’appuyant sur le « cas révélateur » d’une éco-PME missionnaire, l’étude montre l’influence de trois facteurs (valeurs fortes, stratégie proactive, cycle de vie des activités) sur les quatre configurations relationnelles CGE-AO et ouvre de nouvelles perspectives …

Social Sciences and HumanitiesFactores de Contingencia05 social sciencesInteractive ControlAprendizaje Organizacional (OA)Diagnostic ControlGeneral MedicineEnvironmental Management Control (EMC)Organizational Learning (OL)Facteurs de contingenceContrôle diagnostiqueContrôle interactif0502 economics and businessContrôle de gestion environnemental (CGE)Apprentissage organisationnel (AO)050211 marketingSciences Humaines et SocialesControl de Gestión Ambiental (CGE)Control de Diagnóstico050203 business & managementContingency FactorsControl Interactivo
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Production of written French skills by first generation immigrants in working age

2013

This paper aims to identify factors explaining the level of proficiency in written French by immigrants in working age, knowing that few research has been conducted in France on this issue. The originality of this paper is the stochastic production frontier model to explain the scores in written French and the productive performance of immigrants (considered as producers of their own skills). The main results show that mother tongue, age at immigration, social life and mother's diploma are elements which influence the effectiveness of this production. They play a crucial role in the ability of immigrants to use effectively their duration of stay in France and their length of education, cons…

Social factorLearning foreign languages[SHS.EDU]Humanities and Social Sciences/EducationSkillsFacteur social[SHS.EDU] Humanities and Social Sciences/EducationForeign languages[ SHS.EDU ] Humanities and Social Sciences/EducationLangues étrangèresFrench foreign languageNiveau de compétencesModèle économiqueFrançais langue étrangèreEfficacité de l'enseignementTeaching effectivenessEvaluation des performancesApprentissage des langues étrangèresPerformance evaluationÉcritEconomic modelProduction frontierFrontière de productionAcquisition de compétencesskill levelimmigration
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Comment utiliser un diaporama pour favoriser les apprentissages des étudiants ?

2013

Madame N enseigne dans l'enseignement supérieur depuis de nombreuses années. Elle dirige un laboratoire de recherche dans le domaine de la santé et communique beaucoup lors de colloques. Ses enseignements en master sont directement liés à ses travaux de recherche, aussi elle utilise le plus souvent les mêmes diaporamas pour l'enseignement et pour les communications scientifiques. En prenant connaissance des résultats d'évaluation des enseignements, elle est interloquée par les commentaires des étudiants à propos de ses diaporamas : ils les trouvent brouillons, illisibles et certains demandent même à les supprimer. Cependant Madame N ne voit pas comment elle pourrait présenter ses données sc…

Support de coursPédagogie universitaire[SHS.EDU]Humanities and Social Sciences/Education[SHS.EDU] Humanities and Social Sciences/EducationAméliorationÉtudiant[ SHS.EDU ] Humanities and Social Sciences/EducationDiaporamaProcessus d'apprentissageEnseignement supérieur
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A metabolomic study of yeast/bacteria interactions

2015

As a complex microbial ecosystem, wine is a particularly interesting model for studying interactions between microorganisms. Contact-independent interactions (indirect interactions) between the yeast Saccharomyces cerevisae and the lactic acid bacterium Oenococcus oeni have a direct effect on malolactic fermentation (MLF), induction and completion, which is an important factor in wine quality. Yeast strains could be classified as MLF+ phenotype if it usually stimulates the bacterial growth or MLF- in the opposite case. The known metabolites that stimulate or inhibit the MLF cannot always explain the phenotypic distinction. In this work, a multidisciplinary workflow combining non-targeted me…

UPLC-Q-TOF-MSWineBactérie lactiqueApprentissage automatique[SDV.IDA] Life Sciences [q-bio]/Food engineeringYeastMicrobial interactionInteraction microbienne[SDV.AEN] Life Sciences [q-bio]/Food and NutritionMachine learningVinLactic acid bacteriaMetabolomicsLevurePeptidesFT-ICR-MSMétabolomique
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Classification par méthodes d’apprentissage supervisé et faiblement superviséd’images multimodales pour l’aide au diagnostic du lentigo malin en derm…

2021

Carried out in collaboration with the Saint-Étienne University Hospital, this work provides additional information to help the skin diagnosis by providing new decision methods on Lentigo Maligna and Lentigo Maligna Melanoma pathologies. To this end, the modalities regularly used in clinical conditions are made available to this work and are orchestrated within a multimodal process. Among image modalities, may be mentioned the clinical photography, the dermatoscopy, and the confocal reflectance microscopy. Initially, the first steps of this manuscript focus on reflectance confocal microscopy as the work in computer diagnostic assistance is relatively underdeveloped, in particular on the dete…

Upervised learning[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Apprentissage profond[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingLentigo Maligna MelanomaImage classification[INFO.INFO-IM] Computer Science [cs]/Medical ImagingDermatoscopieDermatologyMultimodalité[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Dermatoscopy[INFO.INFO-IM]Computer Science [cs]/Medical ImagingApprentissage faiblement superviséMultimodalityDermatologieFusion de donnéesWeakly supervised learningLentigo MalignaDeep learningApprentissage superviséData fusionMicroscopie confocale par réflectanceClassification d'images[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Confocal reflectance microscopySupervised learning
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Olores, aprendizaje y periodos sensibles durante el desarrollo

2010

traduction simultanée du titre; absent

[ SDV.NEU.PC ] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior[SDV.AEN] Life Sciences [q-bio]/Food and Nutrition[SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior[ SDV.AEN ] Life Sciences [q-bio]/Food and Nutrition[SDV.NEU.PC] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behaviorodeur[SDV.AEN]Life Sciences [q-bio]/Food and Nutritionapprentissagedéveloppement
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Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks

2023

Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning-based solutions have been designed to accurately detect security attacks. Specifically, supervised learning techniques have been widely applied to train attack detection models. However, the main limitation of such solutions is their inability to detect attacks different from those seen during the training phase, or new attacks, also called zero-day attacks. Moreover, training the detection model requires significant data collection and labeling, which increases th…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]5GBIoV[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI]Zero-day attacksSécurité5G V2X IoV Sécurité Attaques Détection Apprentissage Fédéré[INFO] Computer Science [cs]Intrusion DetectionDétectionAttaquesSecurityV2XApprentissage FédéréFederated Learning5GConnected and Automated Vehicles[INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]
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Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

2020

L'analyse prédictive permet d'estimer les tendances des évènements futurs. De nos jours, les algorithmes Deep Learning permettent de faire de bonnes prédictions. Cependant, pour chaque type de problème donné, il est nécessaire de choisir l'architecture optimale. Dans cet article, les modèles Stack-LSTM, CNN-LSTM et ConvLSTM sont appliqués à une série temporelle d'images radar sentinel-1, le but étant de prédire la prochaine occurrence dans une séquence. Les résultats expérimentaux évalués à l'aide des indicateurs de performance tels que le RMSE et le MAE, le temps de traitement et l'index de similarité SSIM, montrent que chacune des trois architectures peut produire de bons résultats en fon…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciencesApprentissage profondComputer Science - Machine LearningImage and Video Processing (eess.IV)[INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]PrévisionComputer Science - Neural and Evolutionary ComputingDeep Learning AlgorithmsPrédiction[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]Electrical Engineering and Systems Science - Image and Video ProcessingLand cover change[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Machine Learning (cs.LG)SARIMA[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]FOS: Electrical engineering electronic engineering information engineeringSatellite imagesNeural and Evolutionary Computing (cs.NE)LSTMPredictionForecastingImages satellitaires
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