No abstract

We propose a probabilistic approach to modelling the propagation of the coronavirus disease 2019 in Madagascar, with all its specificities. With the strategy of the Malagasy state, which consists of isolating all suspected cases and hospitalized confirmed case, we get an epidemic model with seven compartments: susceptible (S), Exposed (E), Infected (I), Asymptomatic (A), Hospitalized (H), Cured (C) and Death (D). In addition to the classical deterministic models used in epidemiology, the stochastic model offers a natural representation of the evolution of the COVID-19 epidemic. We inferred the models with the official data provided by the COVID-19 Command Center (CCO) of Madagascar, between March and August 2020. The basic reproduction number R 0 and the other parameters were estimated with a Bayesian approach. We developed an algorithm that allows having a temporal estimate of this number with confidence intervals. The estimated values are slightly lower than the international references. Generally, we were able to obtain a simple but effective model to describe the spread of the disease.

In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.

Les marais potentiellement aménageables en rizières constituent des zones de future défriche en zones forestières tropi\-cales. Une chaîne de traitement d'images satellitaires multirésolutions et multisources, utilisant Orfeo ToolBox, est mise à l'épreuve pour discriminer les zones humides : eaux, marais et rizières. Cette méthodologie combine des indices radiométriques extraits d'images qui disposent d'un plus grand nombre de bandes spectrales et des indices texturaux issus d'images à résolution spatiale élevée. Ainsi l'information spectrale d'une image du satellite Landsat~7 ETM+ est valorisée pour identifier les zones humides avec une résolution de 30$\:$m et en dresser la cartographie régionale. L'information texturale d'images du satellite SPOT~5 de 10 m et de 2,5$\:$m de résolution est utilisée pour discriminer des types de zones humides et les cartographier à l'échelle locale. En combinant les données des deux satellites, les surfaces en eaux, marais et rizières ont été évaluées avec un indice de Kappa égal à 0,8, dans deux communes du corridor forestier de Fianarantsoa (Madagascar).

Natural user interfaces are increasingly popular these days. One of the most common of these user interfaces today are voice-activated interfaces, in particular intelligent voice assistants such as Google Assistant, Alexa, Cortana and Siri. However, the results show that although there are many services available, there is still a lot to be done to improve the usability of these systems. Speech recognition, contextual understanding and human interaction are the issues that are not yet solved in this field. In this context, this research paper focuses on the state of the art and knowledge of work on intelligent voice interfaces, challenges and issues related to this field, in particular on interaction quality, usability, security and usability. As such, the study also examines voice assistant architecture components following the expansion of the use of technologies such as wearable computing in order to improve the user experience. Moreover, the presentation of new emerging technologies in this field will be the subject of a section in this work. The main contributions of this paper are therefore: (1) overview of existing research, (2) analysis and exploration of the field of intelligent voice assistant systems, with details at the component level, (3) identification of areas that require further research and development, with the aim of increasing its use, (4) various proposals for research directions and orientations for future work, and finally, (5) study of the feasibility of designing a new type of voice assistant and general presentation of the latter, whose realisation will be the subject of a thesis.