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Composition-based statistical model for predicting CO2 solubility in modified atmosphere packaging application
No full textInternational audienceCarbon dioxide (CO2) is an important gas used in modified atmosphere packaging of nonrespiring foods where it solubilizes into the aqueous and lipid phases of food and exerts an antimicrobial effect. Prediction of CO2 solubility within food is thus of paramount importance to anticipate its benefit on food preservation. In the present study, machine learning algorithms were applied on a set of 362 values of CO2 solubilities collected from the scientific literature to tentatively predict the solubility as a function of food composition (water, protein, fat and salt content) and temperature. The best option kept was a random forest algorithm that was used to predict CO2 solubility in four food case studies (ham, salmon, cheese and pâté) that were further 1 Corresponding author 2 used as input parameters in the MAP' OPT tool, predicting the evolution of headspace gas composition. Predicted CO2 solubilities used as input parameters succeeded in representing the CO2 headspace dynamic as a function of time in the four case studies
Compte rendu du livre d'Henri Scepi, Baudelaire et le nuage, Genève, La Baconnière, 2022, 128 p.
No full textInternational audienc
Construction et perpétuation post mortem d’un lieu de mémoire et d’une figure controversée de l’histoire de l’esclavage à La Réunion : le musée de Villèle et Mme Desbassyns (1755-1846)
No full textInternational audienc
A non-convex economic load dispatch problem using chameleon swarm algorithm with roulette wheel and Levy flight methods
No full textInternational audienceAn Enhanced Chameleon Swarm Algorithm (ECSA) by integrating roulette wheel selection and Lé vy flight methods is presented to solve non-convex Economic Load Dispatch (ELD) problems. CSA has diverse strategies to move towards the optimal solution. Even so, this algorithm’s performance faces some hurdles, such as early convergence and slumping into local optimum. In this paper, several enhancements were made to this algorithm. First, it’s position updating process was slightly tweaked and took advantage of the chameleons’ randomization as well as adopting several time-varying functions. Second, the Lévy flight operator is integrated with roulette wheel selection method and both are combined with ECSA to augment the exploration behavior and lessen its bias towards exploitation. Finally, an add-on position updating strategy is proposed to develop a further balance between exploration and exploitation conducts. The optimization performance of ECSA is shown by testing it on five various real ELD cases with a generator having 3, 13, 40, 80 and 140 units, each with different constraints. The results of the ELD systems’ analysis depict that ECSA is better than the parent CSA and other state-of-the art methods. Further, the efficacy of ECSA was experimented on several benchmark test functions, and its performance was compared to other well-known optimization methods. Experimental results show that ECSA surpasses other methods on complex benchmark functions with modest computational burdens. The superiority and practicality of ECSA is demonstrated by getting new best solutions for large-scale ELD cases such as 40-unit and 140-unit test systems
Markisa/Passion Fruit Image Classification Based Improved Deep Learning Approach Using Transfer Learning
No full textInternational audienceFruit recognition becomes more and more important in the agricultural industry. Traditionally, we need to manually identify and label all the fruits in the production line, which is labor intensive, error-prone, and ineffective. Therefore, a lot of fruit recognition systems are created to automate the process, but fruit recognition system for Malaysia local fruit is limited. Thus, this project will focus on classifying one of the Malaysia local fruits which is markisa/passion fruit. We proposed two CNN models for markisa classification. The performances of the proposed models are evaluated on our own dataset collection and produces an accuracy of 97% and 65% respectively. The results indicated that the architecture of CNN model is very important because different architecture can produce different results. Therefore, first CNN model is selected because it can classify 4 types of markisa with a higher accuracy. In the proposed work, we also inspected two transfer learning methods in the classification of markisa which are VGG-16 and InceptionV3. The results showed that the performance of the first proposed CNN model outperforms VGG-16 (95% accuracy) and InceptionV3 (65% accuracy)
Pourquoi tant de violence(s) ? Analyse historique et anthropologique des rapports familiaux chez les Aborigènes d’Australie
No full textInternational audienceCet article cherchera à comprendre comment les sociétés aborigènes, décrites comme libres et traditionnellement à la fois ‘égalitaires’ et non-violentes par les anthropologues, sont progressivement devenues des sociétés subordonnées empreintes de patriarcat et de violences après la colonisation du continent en 1788. Pour ce faire, il tâchera de rendre compte des rapports hommes / femmes, et des rapports pères / mères, depuis l’époque précoloniale jusqu’à nos jours, en prenant en compte les rapports croisées du sexisme, du racisme et du colonialisme. Au final, l’idée sera de comprendre les nouvelles dynamiques à l’œuvre dans les communautés pour désamorcer les jugements hâtifs et permettre un meilleur accompagnement des efforts qui sont faits dans le sens d’une parenté et d’une parentalité qui enfin ne seraient plus contrariées
Commentaire des articles 47, 48 de la Convention européenne des droits de l’homme
No full text13 pagesInternational audienc
Commentaire de l’article 45 de la Convention européenne des droits de l’homme
No full text28 pagesInternational audienc
Être un individu vivant dans un environnement organisé : trois études dans le contexte du management d’animaux
No full textAt the intersection of research in strategy, organizational theory and environmental humanities, this thesis aims to flesh out our understanding of contemporary management. First, the thesis introduces the notion of "animals’ management" to account for a pervasive management phenomenon that contributes to the disruption of the Earth system. The idea of animals’ management makes it possible to grasp that at the scale of the European Union, at any given moment, for each human individual, approximately 15 animal individuals are inserted into our economies of organizations and markets. Secondly, the thesis reports on three observations of animal management. A first essay theorizes the organization of our knowledge about our environments in our complex societies by studying the controversies about the living conditions of farm animals. A second essay formulates four archetypes organizing collective action and explores how 85 animal welfare management initiatives mobilize them in practice. A third essay introduces the concept of "unaware membership" to describe configurations in which individuals are registered as mere members of organizations, and participates in the organization’s purpose without being precisely aware of it. We contend that unaware membership is ubiquitous in the context of animals’ management and in our current social lives. By uncovering a singular field of management, this work formulates thought tables that can support practitioners in understanding their strategic environment and in modeling collective actions.A l’intersection des recherches en stratégie, en théories des organisations et en humanités environnementales, cette thèse vise à éclairer sous un nouveau jour les ressorts du management contemporain. En premier lieu, la thèse introduit la notion de « management d’animaux » pour rendre compte d’un phénomène gestionnaire omniprésent qui contribue aux dérèglements du système Terre. L’idée de management d’animaux permet de saisir qu’à l’échelle de l’Union Européenne, à chaque instant, pour chaque individu humain, environ 15 individus animaux sont insérés dans nos économies d’organisations et de marchés. En second lieu, la thèse rend compte de trois observations de management d’animaux. Un premier essai théorise l’organisation de nos connaissances sur nos environnements dans nos sociétés complexes en étudiant les controverses à propos des conditions de vie des animaux d’élevage. Un deuxième essai formule 4 idéaux-type organisant l’action collective pour explorer comment 85 initiatives ayant trait au management du bien-être animal les mobilisent en pratique. Un troisième essai propose le concept d’« unaware membership » pour analyser des configurations dans lesquelles des individus vivants sont affiliés à leur insu à des organisations, un phénomène ubiquitaire dans le contexte du management d’animaux et dans nos sociétés contemporaines. En mettant à jour un domaine singulier du management, ce travail formule des tableaux de pensée pouvant appuyer les praticiens dans la compréhension de leur environnement stratégique et dans la modélisation d’actions collectives