Portail HAL des publications du LIRMM
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Genomic tracking of the spread of piscine myocarditis virus (PMCV) in farmed salmon
No full textInternational audienc
Virtually Free Randomisations of NTT in RLWE Cryptosystem to Counteract Side Channel Attack based on Belief Propagation
No full textInternational audienceAt CHES 2017, Primas, Pessl and Mangard presented an attack on RLWE cryptosystem based on Belief Propagation. The attack applies on the Number Theoretic Transform (NTT) used to decipher a message. It gathers power consumption leakage of the multiplication by roots of unity in the NTT and then applies Belief Propagation to circulate the information of all leakage nodes, until the combined leakage reveal most of the output coefficients of the NTT. In this paper we present some randomisations which either induce in NTT some random mask on values or randomly rearrange the sequence of operations. We evaluate the level of randomisation provided by the proposed countermeasures and also the effect on the processed values in the NTT. We apply Belief Propagation on the proposed randomised NTT and we study how these randomisations affect the attack. Finally we point out that a set of three combined strategies provide a high level of randomisation and a good protection against Belief Propagation attack of Primas et al
PRIAM
No full textPRIAM is an innovative solution specifically designed to help organizations ensure their applications comply with the stringent requirements of the General Data Protection Regulation (GDPR). As privacy and data protection become increasingly critical, businesses need a reliable framework to address the complexities of GDPR compliance, and PRIAM provides just that.\n\nIn this project, we focus primarily on consent management, which is a key aspect of GDPR compliance. Consent management ensures that organizations properly handle and record user consent for the processing of personal data. This feature is crucial for complying with GDPR's requirements on transparency and user control over their data
Débats en ligne : l’analyse formelle de concepts comme outil d’extraction de connaissances
No full textInternational audienceNous présentons un processus automatisé d’assistance aux débats qui cible l’extraction d’associations entre les termes à partir des listes de termes-clés issues des arguments. Ces listes sont co-élaborées par les utilisateurs et notre système d’indexation. Notre approche cherche à inciter les utilisateurs à proposer des termes-clés, stimulant ainsi leur participation et favorisant l’intelligibilité de leur propos. L’indexation sert de levier pour amener les utilisateurs à améliorer et à enrichir les listes de termes-clés, agissant comme un moteur pour la création de propos structurés. L’algorithme sous-jacent repose sur une analyse formelle de concepts et exploite une base de connaissances, le réseau lexico-sémantique JeuxDeMots (JDM). La procédure implique plusieurs modules, aboutissant à une étape d’extraction de connaissances sous forme d’implications destinées à être intégrées dans JDM. Cette approche collaborative permet à la base de connaissances de s’enrichir au fur et à mesure de l’analyse des débats, améliorant ainsi les termes-clés suggérés par la plate-forme
RDF graph pair profile dataset for the data linking community
No full textInternational audienceAs the number of RDF datasets published on the Web grows, it becomes increasingly important to link similar entities across these datasets. We present the "RDF graph pair profiles dataset", designed to help the data linking community develop tools and carry out evaluation work. This dataset includes profiles of 30 RDF graph pairs, classified according to ontology matching (OM), instance matching (IM) or both (OM + IM). Each profile includes statistical measures and lists of qualitative and quantitative information and descriptive models generated using automated tools. These profiles help in understanding dataset characteristics, facilitating the development, selection and validation of data linking tools. They are particularly useful in machine learning applications where the profiles can serve as input parameters. The dataset includes both the quasi-original RDF graphs and their profiles represented in a specific described format offering a comprehensive resource for researchers and practitioners. The methodology applied to obtain the profiles is also briefly presented
Tight Fine-Grained Bounds for Direct Access on Join Queries
No full textInternational audienceWe consider the task of lexicographic direct access to query answers. That is, we want to simulate an array containing the answers of a join query sorted in a lexicographic order chosen by the user. A recent dichotomy showed for which queries and orders this task can be done in polylogarithmic access time after quasilinear preprocessing, but this dichotomy does not tell us how much time is required in the cases classified as hard. We determine the preprocessing time needed to achieve polylogarithmic access time for all join queries and all lexicographical orders. To this end, we propose a decomposition-based general algorithm for direct access on join queries. We then explore its optimality by proving lower bounds for the preprocessing time based on the hardness of a certain online Set-Disjointness problem, which shows that our algorithm's bounds are tight for all lexicographic orders on join queries. Then, we prove the hardness of Set-Disjointness based on the Zero-Clique Conjecture which is an established conjecture from fine-grained complexity theory. Interestingly, while proving our lower bound, we show that self-joins do not affect the complexity of direct access (up to logarithmic factors). Our algorithm can also be used to solve queries with projections and relaxed order requirements, though in these cases, its running time is not necessarily optimal. We also show that similar techniques to those used in our lower bounds can be used to prove that, for enumerating answers to Loomis-Whitney joins, it is not possible to significantly improve upon trivially computing all answers at preprocessing. This, in turn, gives further evidence (based on the Zero-Clique Conjecture) to the enumeration hardness of self-join-free cyclic joins with respect to linear preprocessing and constant delay
Luxation traumatique du globe dans le sinus maxillaire avec récupération précoce de l’acuité visuelle : cas clinique et revue de la littérature
No full textInternational audienceTraumatic orbital fracture with prolapse of the globe into the paranasal sinuses is very rare. The visual prognosis is poor, and the medical and surgical management is still a topic of debate. We herein describe an extremely rare case of globe dislocation into the left maxillary sinus with complete recovery of visual acuity. A 67-year-old man presented with an isolated left-sided orbital floor fracture with dislocation of the globe into the maxillary sinus. The visual acuity was no light perception in his left eye. He was immediately taken to the operating room for globe repositioning and orbital floor reconstruction. The spectacular visual recovery allowed a return to normal visual acuity. We summarize the clinical outcomes of traumatic globe dislocations between 1971 and 2023 and suggest treatment guidelines. Among the 31 cases reported in the literature, 26 (83.9%) were into the maxillary sinus (vs. ethmoid), of which only 3 (11.5%) had a complete recovery of visual acuity.La luxation du globe dans un sinus paranasal à la suite d’une fracture orbitaire est une affection très rare. Le pronostic visuel est mauvais et la prise en charge médicale et chirurgicale de celle-ci fait actuellement débat. Nous décrivons ici un cas extrêmement rare de luxation du globe dans le sinus maxillaire avec récupération précoce et complète de l’acuité visuelle. Un homme de 67 ans s’est présenté avec une fracture du plancher orbitaire gauche et une luxation complète du globe dans le sinus maxillaire sous-jacent. L’acuité visuelle de l’œil gauche était nulle (perception lumineuse négative). Le patient a été immédiatement pris en charge au bloc opératoire pour repositionnement du globe et reconstruction du plancher orbitaire. La récupération visuelle spectaculaire a permis un retour à l’iso-acuité. Nous avons résumé les résultats cliniques des luxations traumatiques du globe entre 1971 et 2023 et proposé des lignes directrices de traitement. Parmi les 31 cas rapportés dans la littérature, 26 (83,9 %) se trouvaient dans le sinus maxillaire (les autres dans le sinus ethmoïdal) et seuls 3 (11,5 %) ont récupéré complètement leur acuité visuelle
Managing linguistic obstacles in multidisciplinary, multinational, and multilingual research projects
No full textInternational audienceEnvironmental challenges are rarely confined to national, disciplinary, or linguistic domains. Convergent solutions require international collaboration and equitable access to new technologies and practices. The ability of international, multidisciplinary and multilingual research teams to work effectively can be challenging. A major impediment to innovation in diverse teams often stems from different understandings of the terminology used. These can vary greatly according to the cultural and disciplinary backgrounds of the team members. In this paper we take an empirical approach to examine sources of terminological confusion and their effect in a technically innovative, multidisciplinary, multinational, and multilingual research project, adhering to Open Science principles. We use guided reflection of participant experience in two contrasting teams-one applying Deep Learning (Artificial Intelligence) techniques, the other developing guidance for Open Science practices-to identify and classify the terminological obstacles encountered and reflect on their impact. Several types of terminological incongruities were identified, including fuzziness in language, disciplinary differences and multiple terms for a single meaning. A novel or technical term did not always exist in all domains, or if known, was not fully understood or adopted. Practical matters of international data collection and comparison included an unanticipated need to incorporate different types of data labels from country to country, authority to authority. Sometimes these incongruities could be solved quickly, sometimes they stopped the workflow. Active collaboration and mutual trust across the team enhanced workflows, as incompatibilities were resolved more speedily than otherwise. Based on the research experience described in this paper, we make six recommendations accompanied by suggestions for their implementation to improve the success of similar multinational, multilingual and multidisciplinary projects. These recommendations are conceptual drawing on a singular experience and remain to be sources for discussion and testing by others embarking on their research journey
Beyond supervision: Harnessing self-supervised learning in unseen plant disease recognition
No full textInternational audienceDeep learning models have demonstrated great promise in plant disease identification. However, existing approaches often face challenges when dealing with unseen crop-disease pairs, limiting their practicality in real-world settings. This research addresses the gap between known and unknown (unseen) plant disease identification. Our study pioneers the exploration of the zero-shot setting within this domain, offering a new perspective to conceptualizing plant disease identification. Specifically, we introduce the novel Cross Learning Vision Transformer (CL-ViT) model, incorporating self-supervised learning, in contrast to the previous state-of-the-art, FF-ViT, which emphasizes conceptual feature disentanglement with a synthetic feature generation framework. Through comprehensive analyses, we demonstrate that our novel model outperforms state-of-the-art models in both accuracy performance and visualization analysis. This study establishes a new benchmark and marks a significant advancement in the field of plant disease identification, paving the way for more robust and efficient plant disease identification systems. The code is available at https://github.com/abelchai/Cross-Learning-Vision-Transformer-CL-ViT
Cite-worthiness Detection on Social Media: A Preliminary Study
No full textInternational audienceDetecting cite-worthiness in text is seen as the problem of flagging a missing reference to a scientific result (an article or a dataset) that should come to support a claim formulated in the text. Previous work has taken interest in this problem in the context of scientific literature, motivated by the need to allow for reference recommendation for researchers and flag missing citations in scientific work. In this preliminary study, we extend this idea towards the context of social media. As scientific claims are often made to support various arguments in societal debates on the Web, it is crucial to flag non-referenced or unsupported claims that relate to science, as this promises to contribute to improving the quality of the debates online. We experiment with baseline models, initially tested on scientific literature, by applying them on the SciTweets dataset which gathers science-related claims from X. We show that models trained on scientific papers struggle to detect cite-worthy text from X, we discuss implications of such results and argue for the necessity to train models on social media corpora for satisfactory flagging of missing references on social media. We make our data publicly available to encourage further research on cite-worthiness detection on social media