HAL Portal Cnam (French National Conservatory for Arts and Crafts)
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Anomalous Temperature-Dependent Thermal Transport in Crystalline Polyethylene Driven by Strong Anharmonicity
No full textInternational audienceThermal conductivity typically decreases with increasing temperature along the three principal crystalline directions, primarily due to enhanced phonon anharmonicity. In this work, we conducted a comprehensive first-principles investigation of thermal transport in crystalline polyethylene by solving the Wigner transport equation, assisted with the stochastic self-consistent harmonic approximation. It is found that the thermal conductivity of crystalline polyethylene decreases along the chain direction, but increases nearly linearly in the out-of-chain directions. This anomalous contrasting behavior stems from the dominance of particle-like transport along the chain and wave-like transport in the out-of-chain directions. The strong anharmonicity facilitates phonon tunneling between high- and low-frequency modes in the out-of-plane directions. Therefore, further enhancement of thermal conductivity in those directions could benefit from increased anharmonicity and the introduction of additional disorder. These findings provide fundamental insights into the thermal transport mechanisms of anisotropic crystalline polymers, offering valuable guidance for rationally engineering their thermal properties
Monitoring and Control of Structures subject to Vibration and Damage using the Koopman operator
No full textInternational audienceDue to the effects of fatigue and excessive vibration, structures may present a different health condition than initially observed. The change in system behavior due to damage also causes the system to demand more energy, which can saturate the actuators and make the system unstable. In this context, this work proposes to estimate in real-time the dynamics of a structure and control the undesired effects of vibration and damage. A data-driven model will be developed based on the Koopman operator, analyzing only data from sensors and actuators already installed by the control system. The information obtained by this updated model can be used to monitor changes in structural health and adapt a controller to meet performance specifications, even if the system dynamics vary over time. Changes in the spectral characteristics of the Koopman operator can help identify damage in the structure. In addition, an adaptive model predictive controller can incorporate the possible changes in dynamics in real time, adjusting the optimization problem according to the current estimated model. Therefore, our results have demonstrated the benefits and limitations of this online monitoring and control strategy based on data already measured by the controller. REFERENCES [1] N. Mechbal and E. G. O. Nóbrega, Damage tolerant active control: Concept and state of art. IFAC Proceedings Volumes, vol. 45, no. 20, pp. 63–71, 2012. [2] M. Korda and I. Mezić, Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control. Automatica, vol. 93, pp. 149–160, 2018
IA, numérique et encadrement (table ronde)
No full textInternational audienceÀ mes côtés, les invités de la table ronde étaient Marilyne Pecnard, Cadre de santé au centre hospitalier de Chateaudun, élue dans un syndicat infirmier, Sophie Sebille, Data Scientist au GHU Paris psychiatrie & neurosciences et Jean-François Goglin, Expert digital international HIMSS. La table ronde a été animée par Frédérique HEINTZ, Etienne KIMMEL et Etienne LESECQ
Incidences entre processus de deuil et scolarité chez les jeunes aidants et jeunes adultes aidants. Une étude exploratoire
No full textInternational audienceA “young carer” or “young adult carer” refers to a child, adolescent, or young adult under 25 years old who provides regular and significant support to a relative who is ill or living with a disability. These young people represent 12.3% of middle school students, 14.3% of high school students, and 15.9% of university students in France. While this role affects their health and there are emerging initiatives aimed at supporting young carers in school, no French-language study has yet explored the impact of bereavement on the education of young carers and young adult carers. An analysis of interviews conducted with 16 bereaved young carers and young adult carers reveals that the loss of the person they cared for predominantly has negative consequences on their educational paths and career plans. These young people adopt various behaviors and strategies to cope with this situation at school, such as over-investing in learning or, conversely, distancing themselves from their studies. They express specific needs tied to the uniqueness of their experiences, including increased support from National Education and Higher Education professionals. While bereavement in young carers shares similarities with that of other young people, such as orphans, it appears to be marked by prolonged challenges occurring during the caregiving period and following the death of the relative, requiring long-term adjustment processes. Additionally, these young people face a lack of information and awareness among professionals, leading to insufficient support tailoredto their needs.Un « jeune aidant » ou « jeune adulte aidant » désigne un enfant, adolescent ou jeune adulte de moins de 25 ans apportant un soutien régulier et significatif à un proche malade ou en situation de handicap. Ces jeunes représentent 12,3% des collégiens, 14,3% des lycéens et 15,9% des étudiants en France. Si ce rôle a un impact sur leur santé et si des initiatives émergent pour favoriser l’accompagnement de ces jeunes à l’école, aucune étude francophone n’a exploré les incidences du deuil sur la scolarité des jeunes aidants et jeunes adultes aidants. L’analyse d’entretiens menés auprès de 16 jeunes aidants et jeunes adultes aidants endeuillés révèle que la perte du proche aidé a des répercussions majoritairement négatives sur leur parcours scolaire et leurs projets professionnels. Ces jeunes mettent en place des comportements et stratégies pour s’adapter à cette situation à l’école, notamment en surinvestissant les apprentissages ou au contraire en mettant à distance leur scolarité. Ils expriment des besoins spécifiques liés à la singularité de leurs expériences, dont un soutien accru de la part des professionnels de l’Éducation nationale et de l’enseignement supérieur de la recherche. Si le deuil des jeunes aidants présente des similarités avec celui d’autres jeunes, comme les orphelins, il semble caractérisé par des difficultés prolongées, survenant durant la période d’aidance et après le décès du proche, nécessitant des processus d’ajustement à long terme. Ces jeunes sont par ailleurs confrontés au manque d’information et de sensibilisation des professionnels, entraînant un déficit d’accompagnement adapté à leurs besoins
Thermal field estimation in CFRTP composites using an attention-enhanced U-Net
No full textInternational audienceThis study presents a surrogate model based on the convolutional U-Net architecture to predict the thermal field in a carbon fibre-reinforced thermoplastic tape at the microscale during brief and localized heating. Leveraging microstructure data within a machine learning framework, the proposed model aims to enhance the accuracy of temperature field predictions at a low computational cost. The incorporation of a co-attention mechanism to handle image channels of different nature significantly improves precision, resulting in a strong correlation between the model’s predictions and the ground truth obtained from the numerical solution of the heat equation. This capability enables rapid assessment of diverse microstructures, facilitating optimization and real-time applications in manufacturing settings
Interval Estimation for Continuous-Time Linear Systems With Discrete Measurements
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Optimisation des ressources et des forces morales des militaires par les psychological skills training.
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Optimal Margins in Demands–Resources Fit and Student Engagement
No full textInternational audienceA long-standing view in stress and motivation research is that strong resources can offset the strain of high demands—a “buffering” process thought to sustain engagement (students’ dedication, absorption, and vigor in learning) under pressure. Yet this account rarely considers how engagement varies across the full set of demand–resource combinations, whether balanced or imbalanced, and whether both are at high or low levels. Drawing on person–environment fit perspectives, we analyzed three independent datasets spanning middle school to higher education (N = 423, 587, 734) using cubic response surface analysis to examine how a key demand (study workload) and key resources (teacher, peer, and parental support; self-efficacy) jointly shape engagement. Across contexts, engagement was highest when resources outweighed demands, consistent with protective effects. However, when demands and resources were in balance, engagement often peaked at moderate to moderately high intensity, then declined once both were high. This decline is consistent with protective inhibition, a self-regulatory process in which the behavioral system reduces sustained effort to prevent overstrain, even when resources are still available. This pattern affected up to one-fifth of students, challenging the notion that high levels of resources indefinitely counteract high demands. These findings identify intensity thresholds in demand–resource alignment that can limit or boost engagement, highlighting the value of calibrating, not simply increasing, resources in high-demand settings
A preconditioned Hessian-like proximal gradient algorithm for sparse ML-DOA estimation
No full textInternational audienceMaximum Likelihood (ML) Direction-of-Arrival (DoA) estimation under the Vectorized Covariance Matrix Model (VCMM) offers improved performance but remains computationally intensive. To alleviate this issue, sparse formulations have been adopted and shown to be asymptotically equivalent to the ML using a proper regularization parameter choice. Yet, the resulting sparse criterion remains intricate and is typically minimized using slow first-order methods such as the Proximal Gradient Algorithm (PGA). To improve convergence speed, an Hessian-like preconditioned PGA is introduced. As the associated proximal operator lacks a closed-form expression, an IRL1 scheme, known to converge to a critical point of the 0-regularized criterion is employed, enabling its numerical evaluation via the Chambolle-Pock (CP) algorithm. This approach yields faster convergence and enhanced performance in low-SNR scenarios by exploiting the local geometry encoded in the Hessian
Pitch Spelling Jazz Lead Sheets and Solo Transcriptions
No full textInternational audienceWe present an algorithm for pitch spelling tailored for written jazz music. Receiving some input in a MIDI-like format, including information about note heights (expressed in semitones from a reference lowest note) and boundaries of bars (measures), it estimates appropriate note names, one global key signature, and one local scale for each bar. These related pieces of information are jointly assessed in two optimisation steps. In a first "modal" step, one likely scale is guessed for each bar, by minimising the number of accidentals that shall be printed in the engraved score, in a best-path search. Then, in a second "tonal" step, these local scales are used for estimating the key signature that would give the best note spelling on the whole piece. We report successful experiments on a set of lead sheets from the Real Book as well as transcriptions of Jazz solo recordings and basslines. Our procedure is originally designed for an application to music transcription, in particular the construction of digital collections of written jazz soli from audio recordings, in the context of musical analysis, teaching and cultural heritage preservation. Moreover, we have defined for its purpose new distances between various common jazz scales, which might be of some interest in musicological studies