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  • Neuroinformatics
  • 2019-2023
  • Open Access
  • Mémoires en Sciences de l'Information et de la Communication

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: HALIMA, Imen;

    La sécurité des personnes âgées est un enjeu majeur de santé publique. Les travaux de cette Thèse ont porté plus particulièrement un système de détection et de prévention des chutes pouvant être utilisé en Ehpad ou au domicile des personnes autonomes. Pour cela, nous avons utilisé un dispositif à bas coût composé d'une caméra de profondeur et d'une caméra thermique. Ce dispositif fonctionne d'une façon autonome, en temps réel, de jour comme de nuit et permet de préserver l'anonymat de la personne. L'objectif de la thèse était de développer des algorithmes de suivi de la personne et d'identification de son activité afin d'extraire, à court terme, des paramètres pour la détection de la chute et, à long terme, des indices de la fragilité de la personne. Pour cette Thèse, nous avons exploré deux stratégies permettant ce suivi : 1) Une méthode classique de suivi de la personne basée sur du filtrage particulaire. Dans cette approche, les informations acquises par les deux caméras ont été fusionnées afin de suivre la tête de la personne tout au long de la séquence d'images. 2) Une méthode de reconnaissance de l'activité de la personne à partir d’un apprentissage profond sur les séquences d'images thermiques et de profondeurs. Nous avons choisi de détecter quatre postures (assis, debout, allongé sur le lit et allongé par terre) à partir de nos propres bases de données. Nous pensons qu'a terme, l'analyse de la séquence temporelle des postures extraites par nos algorithmes permettra de détecter les signes de fragilité de la personne âgés. The safety of the elderly people is a major public health issue. The work of this Thesis concerned more particularly a fall detection and prevention system that can be used in retirement homes or in the home of autonomous people. For this, we used a low-cost device composed of a depth camera and a thermal camera. This device works autonomously, in real time, day and night and allows to preserve the privacy of the person. The objective of the thesis was to develop algorithms for tracking the person and identifying his activity in order to extract, in the short term, parameters for the detection of the fall and, in the long term, indices of the person's fragility. For this Thesis, we explored two strategies allowing this monitoring: 1) A people tracking method based on particle filtering. In this approach, the information acquired by the two cameras was merged in order to follow the person's head throughout the image sequence. 2) A method of recognizing the person's activity based on deep learning applied on thermal and depth image sequences. We chose to detect four postures (sitting, standing, lying down and fall) from an own acquired dataset. We believe that in the long term, the analysis of the temporal sequence of the postures extracted by our algorithms will allow to detect signs of frailty of the elderly person.

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    Authors: Hebaz, Salah-Eddine; Lambert, Ambroise; Wilkie-Chancellier, Nicolas; Serfaty, Stéphane; +2 Authors

    International audience Les organismes vivants sont des matériaux complexes, capables d’interagir avec leur environnement. Leurs fonctionnalités et leurs structures internes peuvent être modifiées à différentes échelles par stimulations acoustiques. Elles permettent notamment de renforcer certaines propriétés existantes pour leur conférer de nouvelles capacités. Dans ce contexte, la compréhension des interactions cellules – ondes acoustiques peut devenir un enjeu majeur pour des applications de santé et de nombreux domaines connexes. Ce travail présente un dispositif expérimental développé pour la stimulation acoustique et le suivi non- destructif par ondes ultrasonores de matériaux vivants en culture cellulaire. Ces matériaux sont constitués entités structurales vivantes (cellules et éléments de croissance cellulaire) contenus dans un fluide (milieu de culture). Le dispositif utilise un système de génération d’ondes basses fréquences (20 Hz – 20 kHz), collé au support de culture (une boîte de Pétri). Le suivi des changements des propriétés mécaniques de ce fluide complexe est réalisé par impédancemétrie ultrasonore hautes fréquences (100 kHz – qq MHz). Pour comprendre les interactions ondes-cellules, la propagation des ondes est simulée numériquement dans un premier temps en considérant une boite de Pétri, utilisée en cavité résonante, remplie d’un milieu de culture avec et sans cellules. Une analyse préliminaire temps-fréquence est mise en œuvre expérimentalement pour valider les résultats. Une validation applicative est enfin proposée dans le cadre d’une étude de l’influence de séquences sonores spécifiques sur la synthèse protéique à l’échelle de la cellulaire. Ces expériences sont menées sur une lignée de cellules de cancer ovarien (notée SKOV3), transfectées par un plasmide exprimant une protéine d’adhérence cellulaire (intégrine), couplée à une sonde fluorescente. La comparaison avec des images obtenues par microscopie confocale doit permettre d’évaluer l’efficacité de cette approche.

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    Authors: Gascuel, Chantal; Patrick, Bertuzzi; Allard, Denis; Raynal, Helene, H.;
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    Authors: Abdelghani Laifa; Laurent Gautier; Christophe Cruz;

    International audience; The present work aims to develop a text summarisation system for financial texts with a focus on the fluidity of the target language. Linguistic analysis shows that the process of writing summaries should take into account not only terminological and collocational extraction, but also a range of linguistic material referred to here as the "support lexicon", that plays an important role in the cognitive organisation of the field. On this basis, this paper highlights the relevance of pre-training the CamemBERT model on a French financial dataset to extend its domainspecific vocabulary and fine-tuning it on extractive summarisation. We then evaluate the impact of textual data augmentation, improving the performance of our extractive text summarisation model by up to 6%-11%.

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    https://doi.org/10.1007/978-3-...
    Part of book or chapter of book . 2021 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      https://doi.org/10.1007/978-3-...
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    Authors: Yosra Ben Slimen; Joanna Balcerzak; Albert Pages; Fernando Agraz; +6 Authors

    In order to compete for a prominent market share, network operators and service providers should retain and increase the verticals’ subscription, catering to their needs in order to differentiate themselves from competitors. In this scenario, verticals’ satisfaction arises of paramount importance. As such, user experience is becoming a reliable indicator for service providers and telecommunication operators to convey overall end-to-end system functioning. To properly estimate end user satisfaction, operators and service providers require efficient means for quality monitoring and estimation at all layers, in conjunction with mechanisms able to maintain said quality at optimum levels. Given these factors, this paper proposes a mechanism for Quality of Perception (QoP) estimation in e-Health services, enabling the QoP-aware management of network slices fulfilling the requirements of supported services. To this end, the paper proposes a cognitive-based architecture which allows for the collection and monitoring of verticals’ data to estimate QoP and provides mechanisms to re-configure the underlying network slices according to the monitored quality levels. A machine learning (ML) model is introduced that aims to forecast any future degradation in the quality perceived by vertical users. In case of a predicted degradation, the proposed architecture reacts and triggers the necessary remedial actions, referred as actuations. In order to evaluate the developed ML model and to showcase the interaction between the different components of the proposed architecture, an experimental study is presented with real data extracted from a roaming ambulance. In addition, a Proof of Concept of the actuation mechanism is demonstrated through an experimental testbed emulating e-Health services. This work has been funded in part through the European Union’s H2020 program, under grant agreement No 761913: project SliceNet. The authors would like to thank all SliceNet partners for their support in this work. Peer Reviewed

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    Authors: Kalali, Faouzia;

    International audience; Table des matièresIntroductionChapitre premier : Aux fondements des deux notions1. Entre dualité de la motivation1.1. Au plan étymologique1.2. Au plan des usages pédagogiques2. … et dialectique du rapport au savoirChapitre deuxième : Les travaux sur la motivation scolaire1. Motivation scolaire : un nouvel objet de recherche ?2. Les travaux sur l’attribution : à l’origine, la pensée de Heider2.1. Les attributions sociales1.2. Les attributions scolaires3. Les travaux en psychologie sociocognitive3.1. Aux origines du courant cognitiviste : la pensée de Lewin3.2. La perception de sa compétence ou la self efficacy de Bandura3.3. La résignation acquise de Seligman3.4. La perspective future de Nuttin4. Que peut-on dire de ce champ de recherches ?Chapitre troisième : Du rapport au savoir1. Une problématique sociologique : « Du social comme position, au social comme position, histoire et activité »1.1. Singularité, sens, savoir : champ problématique du rapport au savoir-Recherche collective de 19921.2. De l’apprendre ou du savoir à des conceptions différentes du sujet ?2. Problématique psychanalytique2.1. Rapport au savoir en tant que processus créateur de savoir2.2. La part du psychisme et du social2.3. Vers une compréhension clinique des phénomènes d’éducation et de formation3. Bilan des travaux d’ESCOL et du CREF - Logique de formation du sujet par un « retrait de sociabilité » - Logique de formation du sujet par un « progrès de sociabilité » - Quelques réflexions sur la responsabilité du chercheur - Le côté diurne - Le coté nocturneChapitre quatrième : Rapports aux savoirs : les recherches en didactique1. Aux origines du questionnement du rapport aux savoirs en didactique1.1. Théories anthropologique du Didactique, conformité des rapports personnels etinstitutionnels - Rapport personnel, rapport institutionnel - Sur un exemple - Analyse des institutions et conditions de possibilité du didactique1.2. Problématique du rapport au savoir en didactique des sciences expérimentales - Appropriation des concepts en biologie - Rapport aux savoirs en didactique des sciences : la physiqueConclusionBibliographieListes des publications et communications scientifiques.

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    Authors: Fahes, Mohammad; Kervazo, Christophe; Bobin, Jérôme; Tupin, Florence;

    Sparse Blind Source Separation (BSS) has become a well established tool for a wide range of applications - for instance, in astrophysics and remote sensing. Classical sparse BSS methods, such as the Proximal Alternating Linearized Minimization (PALM) algorithm, nevertheless often suffer from a difficult hyperparameter choice, which undermines their results. To bypass this pitfall, we propose in this work to build on the thriving field of algorithm unfolding/unrolling. Unrolling PALM enables to leverage the data-driven knowledge stemming from realistic simulations or ground-truth data by learning both PALM hyperparameters and variables. In contrast to most existing unrolled algorithms, which assume a fixed known dictionary during the training and testing phases, this article further emphasizes on the ability to deal with variable mixing matrices (a.k.a. dictionaries). The proposed Learned PALM (LPALM) algorithm thus enables to perform semi-blind source separation, which is key to increase the generalization of the learnt model in real-world applications. We illustrate the relevance of LPALM in astrophysical multispectral imaging: the algorithm not only needs up to $10^4-10^5$ times fewer iterations than PALM, but also improves the separation quality, while avoiding the cumbersome hyperparameter and initialization choice of PALM. We further show that LPALM outperforms other unrolled source separation methods in the semi-blind setting. Comment: 10th International Conference on Learning Representations, ICLR 2022. 21 pages

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    https://doi.org/10.48550/arxiv...
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      https://doi.org/10.48550/arxiv...
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    Authors: Mariam, Houssein; Poulichet, Patrick; Takhedmit, Hakim; Lionel, Rousseau; +4 Authors

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    Authors: F. Lott; R. Rani; A. Podglajen; F. Codron; +3 Authors

    AbstractThe parameterization scheme that represents gravity waves due to convection in LMDz‐6A, the atmospheric components of the IPSL coupled climate model (IPSLCM6), is directly compared to Strateole‐2 balloon observations made in the lower tropical stratosphere from November 2019 to February 2020. The input meteorological fields necessary to run the parameterization offline are extracted from the ERA5 reanalysis and correspond to the instantaneous meteorological conditions found underneath the balloons. In general, we find a fair agreement between measurements of the momentum fluxes due to waves with periods less than 1 hr and the parameterization. The correlation of the daily values between the observations and the results of the parameterization is around 0.4, which is statistically elevated considering that we analyze around 600 days of data and surprisingly good considering that the parameterization has not been tuned: the scheme is just the standard one that helps producing a quasi‐biennial oscillation (QBO) in the IPSLCM6 model. Online simulations also show that the measured values of momentum fluxes are well representative of the zonally and averaged values of momentum fluxes needed in LMDz‐6A to simulate a QBO. The observations also show that longer waves with periods smaller than a day carry about twice as much flux as waves with periods smaller than an hour, which is a challenge since the low period waves that make the difference are potentially in the “gray zone” of most climate models.

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    Journal of Geophysical Research Atmospheres
    Article . 2023 . Peer-reviewed
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      Journal of Geophysical Research Atmospheres
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    Authors: Morel, Jean-Paul; Villedieu, Françoise;

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    Authors: HALIMA, Imen;

    La sécurité des personnes âgées est un enjeu majeur de santé publique. Les travaux de cette Thèse ont porté plus particulièrement un système de détection et de prévention des chutes pouvant être utilisé en Ehpad ou au domicile des personnes autonomes. Pour cela, nous avons utilisé un dispositif à bas coût composé d'une caméra de profondeur et d'une caméra thermique. Ce dispositif fonctionne d'une façon autonome, en temps réel, de jour comme de nuit et permet de préserver l'anonymat de la personne. L'objectif de la thèse était de développer des algorithmes de suivi de la personne et d'identification de son activité afin d'extraire, à court terme, des paramètres pour la détection de la chute et, à long terme, des indices de la fragilité de la personne. Pour cette Thèse, nous avons exploré deux stratégies permettant ce suivi : 1) Une méthode classique de suivi de la personne basée sur du filtrage particulaire. Dans cette approche, les informations acquises par les deux caméras ont été fusionnées afin de suivre la tête de la personne tout au long de la séquence d'images. 2) Une méthode de reconnaissance de l'activité de la personne à partir d’un apprentissage profond sur les séquences d'images thermiques et de profondeurs. Nous avons choisi de détecter quatre postures (assis, debout, allongé sur le lit et allongé par terre) à partir de nos propres bases de données. Nous pensons qu'a terme, l'analyse de la séquence temporelle des postures extraites par nos algorithmes permettra de détecter les signes de fragilité de la personne âgés. The safety of the elderly people is a major public health issue. The work of this Thesis concerned more particularly a fall detection and prevention system that can be used in retirement homes or in the home of autonomous people. For this, we used a low-cost device composed of a depth camera and a thermal camera. This device works autonomously, in real time, day and night and allows to preserve the privacy of the person. The objective of the thesis was to develop algorithms for tracking the person and identifying his activity in order to extract, in the short term, parameters for the detection of the fall and, in the long term, indices of the person's fragility. For this Thesis, we explored two strategies allowing this monitoring: 1) A people tracking method based on particle filtering. In this approach, the information acquired by the two cameras was merged in order to follow the person's head throughout the image sequence. 2) A method of recognizing the person's activity based on deep learning applied on thermal and depth image sequences. We chose to detect four postures (sitting, standing, lying down and fall) from an own acquired dataset. We believe that in the long term, the analysis of the temporal sequence of the postures extracted by our algorithms will allow to detect signs of frailty of the elderly person.

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    Authors: Hebaz, Salah-Eddine; Lambert, Ambroise; Wilkie-Chancellier, Nicolas; Serfaty, Stéphane; +2 Authors

    International audience Les organismes vivants sont des matériaux complexes, capables d’interagir avec leur environnement. Leurs fonctionnalités et leurs structures internes peuvent être modifiées à différentes échelles par stimulations acoustiques. Elles permettent notamment de renforcer certaines propriétés existantes pour leur conférer de nouvelles capacités. Dans ce contexte, la compréhension des interactions cellules – ondes acoustiques peut devenir un enjeu majeur pour des applications de santé et de nombreux domaines connexes. Ce travail présente un dispositif expérimental développé pour la stimulation acoustique et le suivi non- destructif par ondes ultrasonores de matériaux vivants en culture cellulaire. Ces matériaux sont constitués entités structurales vivantes (cellules et éléments de croissance cellulaire) contenus dans un fluide (milieu de culture). Le dispositif utilise un système de génération d’ondes basses fréquences (20 Hz – 20 kHz), collé au support de culture (une boîte de Pétri). Le suivi des changements des propriétés mécaniques de ce fluide complexe est réalisé par impédancemétrie ultrasonore hautes fréquences (100 kHz – qq MHz). Pour comprendre les interactions ondes-cellules, la propagation des ondes est simulée numériquement dans un premier temps en considérant une boite de Pétri, utilisée en cavité résonante, remplie d’un milieu de culture avec et sans cellules. Une analyse préliminaire temps-fréquence est mise en œuvre expérimentalement pour valider les résultats. Une validation applicative est enfin proposée dans le cadre d’une étude de l’influence de séquences sonores spécifiques sur la synthèse protéique à l’échelle de la cellulaire. Ces expériences sont menées sur une lignée de cellules de cancer ovarien (notée SKOV3), transfectées par un plasmide exprimant une protéine d’adhérence cellulaire (intégrine), couplée à une sonde fluorescente. La comparaison avec des images obtenues par microscopie confocale doit permettre d’évaluer l’efficacité de cette approche.

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    Authors: Gascuel, Chantal; Patrick, Bertuzzi; Allard, Denis; Raynal, Helene, H.;
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    Authors: Abdelghani Laifa; Laurent Gautier; Christophe Cruz;

    International audience; The present work aims to develop a text summarisation system for financial texts with a focus on the fluidity of the target language. Linguistic analysis shows that the process of writing summaries should take into account not only terminological and collocational extraction, but also a range of linguistic material referred to here as the "support lexicon", that plays an important role in the cognitive organisation of the field. On this basis, this paper highlights the relevance of pre-training the CamemBERT model on a French financial dataset to extend its domainspecific vocabulary and fine-tuning it on extractive summarisation. We then evaluate the impact of textual data augmentation, improving the performance of our extractive text summarisation model by up to 6%-11%.

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    https://hal.archives-ouvertes....
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    https://doi.org/10.1007/978-3-...
    Part of book or chapter of book . 2021 . Peer-reviewed
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      https://doi.org/10.1007/978-3-...
      Part of book or chapter of book . 2021 . Peer-reviewed
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    Authors: Yosra Ben Slimen; Joanna Balcerzak; Albert Pages; Fernando Agraz; +6 Authors

    In order to compete for a prominent market share, network operators and service providers should retain and increase the verticals’ subscription, catering to their needs in order to differentiate themselves from competitors. In this scenario, verticals’ satisfaction arises of paramount importance. As such, user experience is becoming a reliable indicator for service providers and telecommunication operators to convey overall end-to-end system functioning. To properly estimate end user satisfaction, operators and service providers require efficient means for quality monitoring and estimation at all layers, in conjunction with mechanisms able to maintain said quality at optimum levels. Given these factors, this paper proposes a mechanism for Quality of Perception (QoP) estimation in e-Health services, enabling the QoP-aware management of network slices fulfilling the requirements of supported services. To this end, the paper proposes a cognitive-based architecture which allows for the collection and monitoring of verticals’ data to estimate QoP and provides mechanisms to re-configure the underlying network slices according to the monitored quality levels. A machine learning (ML) model is introduced that aims to forecast any future degradation in the quality perceived by vertical users. In case of a predicted degradation, the proposed architecture reacts and triggers the necessary remedial actions, referred as actuations. In order to evaluate the developed ML model and to showcase the interaction between the different components of the proposed architecture, an experimental study is presented with real data extracted from a roaming ambulance. In addition, a Proof of Concept of the actuation mechanism is demonstrated through an experimental testbed emulating e-Health services. This work has been funded in part through the European Union’s H2020 program, under grant agreement No 761913: project SliceNet. The authors would like to thank all SliceNet partners for their support in this work. Peer Reviewed

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