HAL Portal UPF (Université de la Polynésie française)
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Sea Water Air Conditioning (SWAC): A Resilient and Sustainable Cooling Solution for hot and humid climates -Energy Performance and Numerical Modeling
No full textInternational audienceSea Water Air Conditioning (SWAC) is a highly efficient alternative to conventional air conditioning that uses deep seawater as a cooling source (Free Cooling). There are three SWAC installations in the world dedicated to cooling production in real-operating conditions, all located in French Polynesia due to its suitable bathymetry for SWAC installations and the high cooling needs of tropical climate. These installations provide cooling for two hotel complexes and a hospital center respectively in Bora Bora, Tetiaroa, and Tahiti. The efficiency of SWAC has been demonstrated through the experimental assessment of the Tetiaroa installation, which showed that its Coefficient of Performance (COP) can range from 20 to 150, depending on the length of the distribution loop. These experimental results can also allow an accurate validation of a numerical model designed to study various operating scenarios to optimize performance, reduce costs, and expand the technology to areas with less favorable bathymetry than French Polynesia. The development of such a design tool model is a necessary step for improving future installations and providing an accurate estimation of the capital costs (CAPEX) and operating costs (OPEX), which would greatly accelerate the development of SWAC technology and its visibility worldwide. This article presents a comprehensive examination of the SWAC technology as a resilient cooling solution for tropical climate. It includes a numerical model created using EnergyPlus and Python plugins, along with its experimental validation using Tetiaroa measurements for an operating period of one month
Individual and collective trajectories of the Free French in the Pacific, 1940 – 1946
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Dossier spécial "(Re)créations du moi dans la littérature francophone du Pacifique contemporain"
No full textLe Bataillon du Pacifique dans la bataille de Bir Hakeim (1940 – 1942)
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Jeux 2 × 2 à Somme Nulle avec Engagements et Observations Bruitées
No full textIn this report, 2 × 2 zero-sum games are studied under the following assumptions: (1) One of the players (the leader) commits to choose its actions by sampling a given probability measure (strategy); (2) The leader announces its action, which is observed by its opponent (the follower) through a binary channel; and (3) the follower chooses its strategy based on the knowledge of the leader’s strategy and the noisy observation of the leader’s action. Under these conditions, the equilibrium is shown to always exist. Interestingly, even subject to noise, observing the actions of the leader is shown to be either beneficial or immaterial for the follower. More specifically, the payoff at the equilibrium of this game is upper bounded by the payoff at the Stackelberg equilibrium (SE) in pure strategies; and lower bounded by the payoff at the Nash equilibrium, which is equivalent to the SE in mixed strategies. Finally, necessary and sufficient conditions for observing the payoff at equilibrium to be equal to its lower bound are presented. Sufficient conditions for the payoff at equilibrium to be equal to its upper bound are also presented.Dans ce rapport, les jeux à somme nulle 2 × 2 sont étudiés sous les hypothèses suivantes : (1) L’un des joueurs (le meneur) s’engage à choisir ses actions en échantillonnant une mesure de probabilité donnée (stratégie) ; (2) Le meneur annonce son action, qui est observée par son adversaire (le suiveur) à travers un canal binaire ; et (3) le suiveur choisit sa stratégie en fonction de la connaissance de la stratégie du meneur et de l’observation bruitée de l’action du meneur. Dans ces conditions, on montre que l’équilibre existe toujours. Fait intéressant, même sujette au bruit, l’observation des actions du leader s’avère soit bénéfique, soit immatérielle pour le suiveur. Plus précisément, la récompense à l’équilibre de ce jeu est majorée par la récompense à l’équilibre de Stackelberg (SE) en stratégies pures, et minorée par la récompense à l’équilibre de Nash, qui équivaut au SE en stratégies mixtes. Enfin, les conditions nécessaires et suffisantes pour observer que la récompense à l’équilibre est égale à sa borne inférieure sont présentées. Les conditions suffisantes pour observer que la récompense à l’équilibre est égale à sa borne supérieure sont aussi présentées
Densité de population de cannes à sucre nobles Saccharum officinarum cultivées dans un contexte d'agriculture biologique certifiée
No full textSource Agritrop Cirad (https://agritrop.cirad.fr/604199/)International audienceSaccharum officinarum noble sugarcanes are used for organic rum production and have specific agronomic characteristics. Their height and tillering do not allow good yields with standard cultivation practices. As they produce fewer stalks within the same plant than modern cultivars, population densities are lower than plantation standards. The leaf area index (LAI) was measured to determine their capacity to achieve canopy closure and, hence, prevent weed development. There were significant differences (p=0.5) between modern cultivars (LAI=5.18) and noble sugarcanes (LAI=2.69-3.34). Cultivar “To Re'are'a” S. officinarum was then used as a noble variety to compare two densities of planting within a plot of 4 000 m2. The double-density plots showed better LAI (4.52 compared to 2.25) and biomass yields also were higher (108.0 compared to 47.5 t/ha) than in the normal density. Doubling the density of “To re'are'a” could be a good agronomic practice for organic agriculture. A special focus will be put on an intergeneric hybrid of S. officinarum x Miscanthus floridulus called To 'a'eho to investigate the management of weeds within the row. Its LAI is about 6.65, higher than modern varieties and it produces good cane yields.Les cannes à sucre nobles Saccharum officinarum sont utilisées pour la production de rhum biologique et ont des caractéristiques agronomiques spécifiques. Leur hauteur et leur tallage ne permettent pas de bons rendements avec les pratiques culturales standard. Comme ils produisent moins de tiges par pied que les cultivars modernes, les densités de population sont inférieures aux normes de plantation. L'indice de surface foliaire (LAI) a été mesuré pour déterminer leur capacité à fermer le rang et, par conséquent, à empêcher le développement des adventices. Il y a des différences significatives (p = 0,5) entre les cultivars modernes (LAI = 5,18) et les cannes à sucre nobles (LAI = 2,69-3,34). Le cultivar " To Re'are'a " S. officinarum a ensuite été utilisé (variété noble) pour comparer deux densités de plantation au sein d'une parcelle de 4 000 m2. Les parcelles à double densité ont montré un meilleur LAI (4,52 contre 2,25) et les rendements en biomasse étaient également plus élevés (108,0 contre 47,5 t/ha) que dans la densité normale. Doubler la densité de " To re'are'a " pourrait être une bonne pratique agronomique pour l'agriculture biologique. Un accent particulier sera mis sur un hybride inter-générique de S. officinarum x Miscanthus floridulus appelé To 'a'eho pour étudier la gestion des adventices dans le rang. Son LAI est d'environ 6,65, plus élevé que les variétés modernes et il produit de bons rendements de canne
Marine Flora of French Polynesia: An Updated List Using DNA Barcoding and Traditional Approaches
No full textInternational audienceLocated in the heart of the South Pacific Ocean, the French Polynesian islands represent a remarkable setting for biological colonization and diversification, because of their isolation. Our knowledge of this region’s biodiversity is nevertheless still incomplete for many groups of organisms. In the late 1990s and 2000s, a series of publications provided the first checklists of French Polynesian marine algae, including the Chlorophyta, Rhodophyta, Ochrophyta, and Cyanobacteria, established mostly on traditional morphology-based taxonomy. We initiated a project to systematically DNA barcode the marine flora of French Polynesia. Based on a large collection of ~2452 specimens, made between 2014 and 2023, across the five French Polynesian archipelagos, we re-assessed the marine floral species diversity (Alismatales, Cyanobacteria, Rhodophyta, Ochrophyta, Chlorophyta) using DNA barcoding in concert with morphology-based classification. We provide here a major revision of French Polynesian marine flora, with an updated listing of 702 species including 119 Chlorophyta, 169 Cyanobacteria, 92 Ochrophyta, 320 Rhodophyta, and 2 seagrass species—nearly a two-fold increase from previous estimates. This study significantly improves our knowledge of French Polynesian marine diversity and provides a valuable DNA barcode reference library for identification purposes and future taxonomic and conservation studies. A significant part of the diversity uncovered from French Polynesia corresponds to unidentified lineages, which will require careful future taxonomic investigation
L’industrie minière calédonienne face aux crises (de 1880 à nos jours)
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A Comprehensive Review on Non-Neural Networks Collaborative Filtering Recommendation Systems
No full textInternational audienceOver the past two decades, recommendation systems have attracted a lot of interest due to the massive rise of online applications. A particular attention has been paid to collaborative filtering, which is the most widely used in applications that involve information recommendations. Collaborative Filtering (CF) uses the known preference of a group of users to make predictions and recommendations about the unknown preferences of other users (recommendations are made based on the past behavior of users). First introduced in the 1990s, a wide variety of increasingly successful models have been proposed. Due to the success of machine learning techniques in many areas, there has been a growing emphasis on the application of such algorithms in recommendation systems. In this article, we present an overview of the CF approaches for recommendation systems, their two main categories, and their evaluation metrics. We focus on the application of classical Machine Learning algorithms to CF recommendation systems by presenting their evolution from their first use-cases to advanced Machine Learning models. We attempt to provide a comprehensive and comparative overview of CF systems (with python implementations) that can serve as a guideline for research and practice in this area
