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Climatic a priori information for the GEV distribution’s shape parameter of annual maximum flow series
No full textInternational audienc
Le Carnaval guyanais et son évolution de 1743 à nos jours
No full textInternational audienceFrom private balls to masked balls, traditional costumes to glittering finery, the Guyanese carnival has constantly reinvented itself since its emergence in the 18th century. A blend of tradition and modernity, it remains a pillar of Guyanese culture and reflects the social changes taking place in the territory.Des bals privés au bals paré-masqués, des costumes traditionnels aux parures scintillantes, le carnaval guyanais n'a pas cessé de se réinventer depuis son apparition au XVIIIe siècle jusqu'à aujourd'hui. Mélange de traditions et de modernité, il demeure un pilier de la culture guyanaise et reflète mutations sociales du territoire
Variation of vegetation cover and the relationship with land surface temperature across Thailand (2007 to 2022)
No full textInternational audienceUnderstanding vegetation-climate interactions is essential amid escalating global climate change. This study investigates spatial-temporal and seasonal variations in Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) across six regions of Thailand (2007-2022). Results reveal distinct regional and seasonal characteristics, with significant negative correlations between LST and NDVI (R = 0.61 dry; 0.39 rainy; 0.72 winter). The strongest negative correlation occurred during the rainy season in 2017, highlighting complex interannual variations. Seasonal LST fluctuations (winter-summer: 1.24, winter-rainy: -1.54, summer-rainy: -2.78, p < 0.001) and NDVI variations (winter-summer: 0.09, winter-rainy: 0.07, summer-rainy: -0.03, p < 0.001) were statistically significant. These findings emphasize monitoring LST and NDVI as vital for understanding ecological impacts of climate change and urbanization. The study specifically explores whether increased vegetation consistently is associated with lower temperatures, underscoring the importance of strategies to mitigate heat and enhance climate resilience, particularly in rapidly urbanizing regions
A multi-species population harvesting model with time and size competition dependence function
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FUTURISKS à Mayotte : comprendre les risques côtiers pour mieux s’y préparer: Anticiper l’impact des vagues et du climat sur la barrière de récif de Mayotte
No full textPoster aux journées portes ouvertes de l'université de MayotteFUTURISKS en bref : Un programme national sur l’ensemble des territoires d’outremer français (Antilles, Mayotte, la Réunion, la Nouvelle Calédonie, la Polynésie française).Observer & modéliser : mesures terrain + modélisations numériquesComprendre les risques, anticiper la submersion et l’érosionUn projet collectif : Chercheurs + acteurs locaux = stratégies d’adaptation durables pour les îles tropicales
Les ambivalences de la reconnaissance du droit à l’autodétermination des peuples autochtones en droit international
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R&R: Metric-guided Adversarial Sentence Generation
No full textAdversarial examples are helpful for analyzing and improving the robustness of text classifiers. Generating high-quality adversarial examples is a challenging task as it requires generating fluent adversarial sentences that are semantically similar to the original sentences and preserve the original labels, while causing the classifier to misclassify them. Existing methods prioritize misclassification by maximizing each perturbation's effectiveness at misleading a text classifier; thus, the generated adversarial examples fall short in terms of fluency and similarity. In this paper, we propose a rewrite and rollback (R&R) framework for adversarial attack. It improves the quality of adversarial examples by optimizing a critique score which combines the fluency, similarity, and misclassification metrics. R&R generates high-quality adversarial examples by allowing exploration of perturbations that do not have immediate impact on the misclassification metric but can improve fluency and similarity metrics. We evaluate our method on 5 representative datasets and 3 classifier architectures. Our method outperforms current state-of-the-art in attack success rate by +16.2%, +12.8%, and +14.0% on the classifiers respectively. Code is available at https: //github.com/DAI-Lab/fibbe
Critical review of hybrid modular multilevel converters for HVDC transmission in offshore wind energy
No full textInternational audienceFor the integration of wind energy into the transmission system, High Voltage DC (HVDC) is the most efficient and cost-effective option. Modular multilevel converters have emerged as the most suitable converters for the required AC/DC conversions. To maintain power availability, stability, and reliability in the HVDC transmission, the converters' ability to offer fault ride-through (FRT) and work as static compensators (STATCOM) during DC faults have become important requirements. The conventional half bridge-based MMC is the most cost-effective, efficient, and widely used topology, but it cannot meet these requirements. Though full-bridge MMC has this ability, it doubles the converter cost, device count, and losses. In the present MMC topology, the capacitors occupy 50 % of the volume and 80 % weight of the converter. Reducing energy storage requirements is needed for their efficient use in offshore wind energy substations. Many Hybrid MMC (HMMC) topologies have been introduced in the last few years to offer a solution to meet these requirements, but no topology has been found yet that can fulfill all the required criteria. A comprehensive review of the existing topologies, their features, strengths, and drawbacks are needed to identify research gaps and guide future works. This paper provides a thorough and systematic review of the topology, fault handling, and STATCOM mode of all hybrid MMCs (HMMCs) for HVDC offshore wind energy transmission found in the literature. It compares these topologies' structure, losses, and functionality to guide future research. A case study calculates these topologies' losses and energy requirements by using time-domain analysis of a switching-based model in MATLAB of these converters, with a rating of 1500MVA with 1050KV DC voltage. The results present a quantitative comparison of losses and energy storage requirements across these topologies which would be useful to give directions to future works