Scientific Publications of the University of Toulouse II Le Mirail
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3604 Artificial Intelligence-driven failure prediction on TomoTherapy® systems
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Socio-acoustic co-selection? Vocal encoding of sociability prevails over emotions in sheep bleats
No full textVocalisations of animals are good indicators of their emotions. Temperament is known to influence the regulation and expression of emotions. However, how animal temperament affects their vocalisations and particularly their vocal expressions of emotions remains largely unexplored. Sociability is often measured as the behavioural reactivity to social separation and is a temperament trait intrinsically linked to emotional reactivity. Most social species respond to this challenging situation using contact calls. Here, we investigated whether the acoustic structure of these calls reflect sociability, emotions or both. We used 42 female lambs from two diverging sheep lines selected for high or low sociability. High bleats were recorded both in isolation (social challenge) and before receiving a food treat (non social context) to investigate the link between vocalisations, emotions and heritable sociability. The acoustic features of isolation bleats differed between the lines, but it was not the case for pre-feeding bleats. Surprisingly, the genetic selection index and social behaviour were better predictors of the structure of isolation bleats than the arousal. Last, encoding of individuality in isolation bleats was impaired by the genetic selection. Our findings suggest a socio-acoustic co-selection: selecting for sociable animals affects vocal signatures in calls produced during a social separation
Photographier les effets de la crue de juin 1875 à Toulouse : l'image comme nouveau médium de la catastrophe du millénaire
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Mise en place d'une méthode de reconstruction 3D du sol lunaire à partir de plusieurs images dans un contexte d'atterrissage
No full textInternational audienceMise en place d'une méthode de reconstruction 3D du sol lunaire à partir de plusieurs images dans un contexte d'atterrissag
Photonic Integrated Circuit with System on Chip for Sub-Picometric Displacement Sensor
No full textNational audiencePICSONDE aims to develop an advanced embedded sensing system using optical feedback interferometry (OFI) in a laser diode for predictive maintenance applications. The system integrates a photonicintegrated circuit (PIC) to capture the frequency modulated (FM) channel of the OFI signal, and a system-on-chip (SoC) for data acquisition and processing. The project targets a quantum-limitedperformance of 0.1 pm/√Hz noise power spectrum density (PSD) over a 100 kHz bandwidth, representing the state-of-the-art in OFI systems. To achieve this, PICSONDE must overcome four main technologicalchallenges: (1) acquiring OFI signals with high dynamic range and signal-to-noise ratio, (2) extracting information from non-linear OFI signals, (3) real-time assessment of optical feedback betweenlaser and target, and (4) detecting interferometric fringes in the presence of speckle
Documentation en ligne de l'ANF géomatique sous le logiciel open source Readthedocs (réseau SIST) - édition 2020-2021
No full textCe support web de formation a été réalisé en 2020-2021 dans le cadre d'une Action Nationale de Formation (ANF) portée par le réseau SIST des ingénieurs gestionnaires des données d'observation (https://sist.cnrs.fr) et financée par le CNRS. La formation a eu lieu du 15 au 19 mars 2021 (2 jours de formation théorique en distanciel) et du 7 au 11 juin 2021 (5 jours de formation avec travaux pratiques au centre du Lazaret à Sète).Le logiciel open source utilisé est Readthedocs https://about.readthedocs.com. La documentation en ligne dans sa dernière version est accessible sur https://sist.pages.in2p3.fr/anf20-geomatique/. Le code en lien est hébergé sur le GitLab du CNRS-IN2P3 (https://gitlab.in2p3.fr/sist/anf20-geomatique) avec un archivage dans Software Heritage
Annotation de résumés oraux d'élèves de primaire pour l'analyse automatique des capacités de compréhension de la lecture
No full textInternational audienceThe CHICA-AI project aims to build a computer-assisted learning activity for training the reading comprehension skills of primary school pupils. This activity involves asking students to orally sum- marize a narrative text, in order to identify their comprehension difficulties and provide personalized feedback to the pupil and their teacher. To do this, we’ll be implementing an automatic system for fine-grained analysis of oral summaries, capable of extracting relevant information and combining it to fill out a grid of pedagogical and psycho-cognitive criteria. We present here the challenges of the project, as well as the first tasks carried out : creation of the activity in the Lalilo platform and of the pedagogical content, audio recordings collection, construction of the annotation protocol. Finally, we present the preliminary analyses executed on the first annotations, which will be used to train and evaluate our automatic system.Le projet CHICA-AI vise à construire une activité assistée par ordinateur pour l'entraînement des compétences de compréhension de la lecture des élèves de primaire. Cette activité consiste à demander à l'élève de résumer à l'oral un texte narratif, afin d'identifier ses difficultés de compréhension et fournir un retour personnalisé à l'élève et à son enseignant. Pour cela, nous mettrons en place un système automatique d'analyse fine des résumés oraux, capable d'extraire les informations pertinentes et de les combiner pour remplir une grille de critères pédagogiques et psycho-cognitifs. Nous présentons ici les défis du projet, ainsi que les premiers travaux réalisés : création de l'activité dans la plateforme Lalilo et du contenu pédagogique, collecte d'enregistrements audios, construction du protocole d'annotation. Nous présentons enfin les analyses préliminaires faites sur les premières annotations, qui serviront à l'entraînement et l'évaluation de notre système automatique
Group Multicriteria Decision Making: a case study for safety public policy
No full textInternational audienceEnsuring public safety requires well-structured policies that balance multiple, often conflicting, criteria. This paper proposes a decision-support framework that integrates Group Decision Making (GDM) and Multicriteria Decision Analysis (MCDA) to prioritize safety policies effectively. Using a panel of experts, we apply CoCoFISo and MIRA methods to evaluate policy alternatives based on ten criteria. The approach fosters consensus by aggregating three perspectives while maintaining methodological rigor in prioritization. The results offer valuable insights for decision-makers seeking participatory solutions to enhance public security in Brazil, as well as connecting the area to Smart and Sustainable Cities.</div
Error Bounds for a Kernel-Based Constrained Optimal Smoothing Approximation
No full textThis paper establishes error bounds for the convergence of a piecewise linear approximation of the constrained optimal smoothing problem posed in a reproducing kernel Hilbert space (RKHS). This problem can be reformulated as a Bayesian estimation problem involving a Gaussian process related to the kernel of the RKHS. Consequently, error bounds can be interpreted as a quantification of the maximum a posteriori (MAP) accuracy. To our knowledge, no error bounds have been proposed for this type of problem so far. The convergence results are provided as a function of the grid size, the regularity of the kernel, and the distance from the kernel interpolant of the approximation to the set of constraints. Inspired by the MaxMod algorithm from recent literature, which sequentially allocates knots for the piecewise linear approximation, we conduct our analysis for non-equispaced knots. These knots are even allowed to be non-dense, which impacts the definition of the optimal smoothing solution and our error bound quantifiers. Finally, we illustrate our theorems through several numerical experiments involving constraints such as boundedness and monotonicity