59 research outputs found

    Sur la vérification du locuteur à partir de traces d’exécution de modèles acoustiques personnalisés

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    National audienceSpeaker personalized acoustic models are obtained from a global model by updating its parameters using speaker's data. An important question is whether access to these personalized models allows to easily build an attack to identify the associated speaker. This problem is especially important in the context of federated learning of speech recognition acoustic models where a global model is learnt on the server using the updates received from multiple clients. We propose an approach to analyze information in neural network acoustic models based on a neural network footprint on the so-called indicator dataset. Using this method, we develop two very effective attack models that allow to infer speaker identity from the updated personalized models without access to the users’ speech data.Les modèles acoustiques personnalisés sont construits par entraînement à partir de données provenant d’un locuteur unique en raffinant un modèle générique. Une question importante est de savoir si l’accès à ces modèles personnalisés permet facilement de construire une attaque permettant d’identifier le locuteur associé. Ce problème est important dans le contexte de l’apprentissage fédéré de modèles pour la reconnaissance de la parole où un modèle global est appris sur un serveur à partir des modifications des paramètres des modèles reçues de plusieurs clients. Nous proposons une méthode qui consiste à construire des empreintes de ces modèles à partir des traces de leur application sur un jeu de données fixe et indépendant que nous appelons indicateur. Grâce à ces empreintes, nous développons deux modèles d’attaques très efficaces qui visent à inférer l’identité du locuteur

    Hereditary breast cancer in Middle Eastern and North African (MENA) populations: identification of novel, recurrent and founder BRCA1 mutations in the Tunisian population

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    Germ-line mutations in BRCA1 breast cancer susceptibility gene account for a large proportion of hereditary breast cancer families and show considerable ethnic and geographical variations. The contribution of BRCA1 mutations to hereditary breast cancer has not yet been thoroughly investigated in Middle Eastern and North African populations. In this study, 16 Tunisian high-risk breast cancer families were screened for germline mutations in the entire BRCA1 coding region and exon–intron boundaries using direct sequencing. Six families were found to carry BRCA1 mutations with a prevalence of 37.5%. Four different deleterious mutations were detected. Three truncating mutations were previously described: c.798_799delTT (916 delTT), c.3331_3334delCAAG (3450 delCAAG), c.5266dupC (5382 insC) and one splice site mutation which seems to be specific to the Tunisian population: c.212 + 2insG (IVS5 + 2insG). We also identified 15 variants of unknown clinical significance. The c.798_799delTT mutation occurred at an 18% frequency and was shared by three apparently unrelated families. Analyzing five microsatellite markers in and flanking the BRCA1 locus showed a common haplotype associated with this mutation. This suggests that the c.798_799delTT mutation is a Tunisian founder mutation. Our findings indicate that the Tunisian population has a spectrum of prevalent BRCA1 mutations, some of which appear as recurrent and founding mutations

    The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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    The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

    Depletion Perturbation Theory in decay heat calculation context

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    International audienceThis article describes an implementation of Depletion Perturbation Theory (DPT) using deterministic neutronics code APOLLO3® alongside depletion code MENDEL. We use DPT to calculate the sensitivity coefficients of decay heat (DH) to various nuclear data such as reaction cross-sections, fissions yields, and reaction energy.DPT allows for the coupling of the Bateman, Boltzmann, and normalization equations, and has the advantage of needing only one calculation per cooling time to compute the sensitivity coefficient to all input parameters, as opposed to usual finite differences schemes which need as many calculation as there are input parameters.The calculation of sensitivity coefficients is done using both the DPT methodology and a finite differencesscheme as a mean of numerical verification. Both methods showed good agreement, although we found that DPT should be used with care when studying short cooling times. Sensitivity coefficients were then used to perform deterministic uncertainty propagation, the resulting uncertainty calculation were used to compare the effect of various coupling configurations
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