Over the last decades, film theories with their focus on the mere audiovisual quality of cinema have been questioned by film scholars with a phenomenological interest. According to these critical approaches, the film experience cannot be understood through a mere involvement of the eye (and the ear). In this context, to disregard the significance of a multisensory attachment to the film results in the consideration of relationship between the film and the viewer to be a dominating one. This dissertation examines this multisensory attachment and aims to define the film experience as an embodied relationship between the film and the viewer by means of a formal analysis of the Turkish director Nuri Bilge Ceylan’s early films. Throughout the dissertation, it is argued that Ceylan encourages his viewer in various forms to have a more sensual and immediate experience of his films rather than to compel them to adhere to symbols and abstractions through a kind of intellectual effort – an intellectual effort that would damage the “sensuous” attachment between the film and the viewer.

This study probes selected stories from Bessie Head's The Collector of Treasures (1977) in order to elicit instances of contiguity and disjuncture between orality and literacy, to establish Head's complex identity configurations which are often manifested in the interactions between aesthetic form and content, authorial consciousness, character delineation, and narrative voice. At the same time, the dissertation explores her portrayal of the proscribed condition of women, the subversive consciousness that undercuts women's subjugation by patriarchy, and her vision for the liberatory possibilities for women from the exigencies of patriarchal domination. I also examine Head's (re-)vision of culture within the framework of hybridity and creolity and determine how some of these perspectives are crystallized in discourses such as When Rain Clouds Gather (1968), Maru (1971) and A Question of Power (1973). I juxtapose my reading of Head with other African writers such as Bâ, Emecheta and Nwapa to draw references in instances where the context permits. The dominant critical approach adopted in this thesis is a contextual approach. I consider this approach useful for my purposes because of its flexibility, the attention it pays to the formal properties of literary texts and, its cognizance of the socio-historical genesis of texts and its demonstration of literature's timeless value. / English Studies / M.A. (English)

A presente dissertação é o resultado de uma pesquisa que avalia as vantagens da utilização de nuvens de texto para apresentar os resultados de um sistema de busca na web. Uma nuvem de texto é uma técnica de visualização de informações textuais e tem como principal objetivo proporcionar um resumo de um ou mais conteúdos em uma única tela. Em uma consulta na web, os resultados aparecem listados em diversas páginas. Através de uma nuvem de texto integrada a um sistema de busca é possível a visualização de uma síntese, de um resumo automático, do conteúdo dos resultados listados em várias páginas sem que elas tenham que ser percorridas e os sites acessados individualmente. A nuvem de texto nesse contexto funciona como uma ferramenta auxiliar para que o usuário possa gerenciar a grande carga de informação que é disponibilizada nos resultados das consultas. Dessa forma os resultados podem ser vistos em contexto e, ainda, as palavras que compõem a nuvem, podem ser utilizadas como palavras-chave adicionais para complementar uma consulta inicial. Essa pesquisa foi desenvolvida em duas fases. A primeira consistiu no desenvolvimento de uma aplicação integrada a um sistema de buscas para mostrar seus resultados em nuvens de texto. A segunda fase foi a avaliação dessa aplicação, focada principalmente em buscas exploratórias, que são aquelas em que os objetivos dos usuários não são bem definidos ou o conhecimento sobre o assunto pesquisado é vago. / This dissertation presents the results of a research that evaluates the advantages of text clouds to the visualization of web search results. A text cloud is a visualization technique for texts and textual data in general. Its main purpose is to enhance comprehension of a large body of text by summarizing it automatically and is generally applied for managing information overload. While continual improvements in search technology have made it possible to quickly find relevant information on the web, few search engines do anything to organize or to summarize the contents of such responses beyond ranking the items in a list. In exploratory searches, users may be forced to scroll through many pages to identify the information they seek and are generally not provided with any way to visualize the totality of the results returned. This research is divided in two parts. Part one describes the development of an application that generates text clouds for the summarization of search results from the standard result list provided by the Yahoo search engine. The second part describes the evaluation of this application. Adapted to this specific context, a text cloud is generated from the text of the first sites returned by the search engine according to its relevance algorithms. The benefit of this application is that it enables users to obtain a visual overview of the main results at once. From this overview the users can obtain keywords to navigate to potential relevant subjects that otherwise would be hidden deep down in the response list. Also, users can realize by visualizing the results in context that his initial query term was not the best choice.

A presente dissertação é o resultado de uma pesquisa que avalia as vantagens da utilização de nuvens de texto para apresentar os resultados de um sistema de busca na web. Uma nuvem de texto é uma técnica de visualização de informações textuais e tem como principal objetivo proporcionar um resumo de um ou mais conteúdos em uma única tela. Em uma consulta na web, os resultados aparecem listados em diversas páginas. Através de uma nuvem de texto integrada a um sistema de busca é possível a visualização de uma síntese, de um resumo automático, do conteúdo dos resultados listados em várias páginas sem que elas tenham que ser percorridas e os sites acessados individualmente. A nuvem de texto nesse contexto funciona como uma ferramenta auxiliar para que o usuário possa gerenciar a grande carga de informação que é disponibilizada nos resultados das consultas. Dessa forma os resultados podem ser vistos em contexto e, ainda, as palavras que compõem a nuvem, podem ser utilizadas como palavras-chave adicionais para complementar uma consulta inicial. Essa pesquisa foi desenvolvida em duas fases. A primeira consistiu no desenvolvimento de uma aplicação integrada a um sistema de buscas para mostrar seus resultados em nuvens de texto. A segunda fase foi a avaliação dessa aplicação, focada principalmente em buscas exploratórias, que são aquelas em que os objetivos dos usuários não são bem definidos ou o conhecimento sobre o assunto pesquisado é vago. / This dissertation presents the results of a research that evaluates the advantages of text clouds to the visualization of web search results. A text cloud is a visualization technique for texts and textual data in general. Its main purpose is to enhance comprehension of a large body of text by summarizing it automatically and is generally applied for managing information overload. While continual improvements in search technology have made it possible to quickly find relevant information on the web, few search engines do anything to organize or to summarize the contents of such responses beyond ranking the items in a list. In exploratory searches, users may be forced to scroll through many pages to identify the information they seek and are generally not provided with any way to visualize the totality of the results returned. This research is divided in two parts. Part one describes the development of an application that generates text clouds for the summarization of search results from the standard result list provided by the Yahoo search engine. The second part describes the evaluation of this application. Adapted to this specific context, a text cloud is generated from the text of the first sites returned by the search engine according to its relevance algorithms. The benefit of this application is that it enables users to obtain a visual overview of the main results at once. From this overview the users can obtain keywords to navigate to potential relevant subjects that otherwise would be hidden deep down in the response list. Also, users can realize by visualizing the results in context that his initial query term was not the best choice.

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No. of bitstreams: 2 Dissertação - Gilberto Antônio Marcon dos Santos - 2016.pdf: 15378242 bytes, checksum: d10f5df08686b55ad63c406e648a2b8e (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-08-12 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Depth sensing methods yield point clouds that represent neighboring surfaces. Interpreting and extracting information from point clouds is an established field, full of yet unsolved challenges. Classic image processing algorithms are not applicable or must be adapted because the organized structure of 2D images is not available. This work presents three contribution to the field of point cloud processing and segmentation. These contributions are the results of investigations carried out at the Laboratory for Education and Innovation in Automation – LEIA, aiming to advance the knowledges related to applying spacial sensing to autonomous robotics. The first contribution consists of a new algorithm, based on evolutionary methods, for extracting planes from point clouds. Based on the method proposed by Bazargani, Mateus e Loja (2015), this contribution consists of adopting evolutionary strategies in place of genetic algorithms making the process less sensitive to user-defined parameters. The second contribution is a method for segmenting ground and obstacles from point clouds for autonomous navigation, that utilizes the proposed plane extraction algorithm. The use of a quadtree for adaptive area segmentation allows for classifying points with high accuracy efficiently and with a time performance compatible with low cost embedded devices. The third contribution is a variant of the proposed segmentation method that is more noise tolerant and robust by incorporating a neural classifier. The use of a neural classifier in place of simple thresholding makes the process less sensitive to point cloud noise and faults, making it specially interesting for processing point clouds obtained from real time stereo reconstruction methods. A through sensitivity, accuracy, and efficiency analysis is presented for each algorithm. The dihedral angle metric (angle between the detected plane and the reference polygons that share at least one point) proposed by Bazargani, Mateus e Loja (2015) is used to quantify the plane detection method accuracy. The ratio between the correctly classified points and the total number of points is utilized as an accuracy metric for the ground segmentation methods. Additionally, computing costs and execution times are considered and compared to the main state-of-the-art methods. / Métodos de sensoriamento de profundidade produzem nuvens de pontos que representam as superfícies vizinhas. Interpretar e extrair informações de nuvens de pontos é um campo estabelecido e repleto de desafios ainda não superados. Algoritmos de processamento de imagens clássicos não se aplicam ou têm de ser adaptados porque a estrutura organizada que se poderia supor em imagens bidimensionais não se faz presente. Este trabalho apresenta três contribuições ao campo de processamento e segmentação de nuvens de pontos. Tais contribuições são resultados da investigação realizada no Laboratório para Educação e Inovação em Automação – LEIA, com o fim de avançar os conhecimentos relacionados a aplicações de sensoriamento espacial para robótica autônoma. A primeira contribuição consiste de um novo algoritmo para extração de planos de nuvens de pontos, que se baseia em métodos evolutivos. Partindo do método proposto por Bazargani, Mateus e Loja (2015), esta contribuição consiste em utilizar estratégias evolucionárias no lugar de algoritmos genéticos, de forma a tornar o processo menos sensível aos parâmetros definidos pelo usuário. A segunda contribuição é um método para segmentação de piso e obstáculos em nuvens de pontos para navegação autônoma, que utiliza o algoritmo de extração de planos proposto. O uso de uma árvore quaternária para segmentação adaptativa de área permite classificar os pontos com elevada taxa de acerto de forma eficiente e com desempenho compatível com dispositivos embarcados de baixo custo. A terceira contribuição é uma variação do método de segmentação proposto que se faz mais robusta e tolerante a ruído através da agregação de um classificador neural. O uso do classificador neural no lugar da limiarização simples torna o processo menos sensível a ruídos e falhas nas nuvens de pontos, o tornando especialmente interessante para o processamento de nuvens de pontos obtidas por métodos de reconstrução estéreo de tempo real. Uma completa análise de sensibilidade, acurácia e eficiência é apresentada para cada algoritmo. A métrica de ângulo diedral (ângulo entre os planos detectados e os polígonos de referência que compartilham ao menos um ponto em comum) proposta por Bazargani, Mateus e Loja (2015) é utilizada para quantificar a acurácia do método de detecção de planos. A razão entre os pontos corretamente classificados e o número total de pontos é utilizada como métrica de acurácia para os métodos de segmentação de piso. Também são considerados os custos computacionais e o tempo de execução, comparados aos principais métodos estado-da-arte.

La modélisation de scènes réelles à travers la capture de données numériques 3D a été prouvée à la fois utile et applicable dans une variété d’applications. Des scènes entières sont généralement numérisées par des scanners laser et représentées par des grands nuages de points non organisés souvent accompagnés de données photogrammétriques. Un problème typique dans le traitement de ces nuages et données réside dans la détection et la classification des objets présents dans la scène. Ces tâches sont souvent entravées par la variabilité des conditions de capture des données, la présence de bruit, les occlusions ainsi que les données manquantes. Compte tenu de la complexité des problèmes sous-jacents, les approches de traitement récentes tentent d’exploiter les connaissances sémantiques pour identifier et classer les objets. Dans cette thèse, nous proposons une nouvelle approche qui fait appel à des stratégies intelligentes de gestion des connaissances pour le traitement des nuages de points 3D ainsi que l’identification et la classification des objets dans les scènes numérisées. Notre approche étend l’utilisation des connaissances sémantiques à toutes les étapes du traitement, y compris le choix et le guidage des algorithmes de traitement axées sur les données individuelles. Notre solution constitue un concept multi-étape itératif sur la base de trois facteurs : la connaissance modélisée, un ensemble d’algorithmes de traitement, et un moteur de classification. L’objectif de ce travail est de sélectionner et d’orienter les algorithmes de manière adaptative et intelligente pour détecter des objets dans les nuages de points. Des expériences avec deux études de cas démontrent l’applicabilité de notre approche. Les études ont été réalisées sur des analyses de la salle d’attente d’un aéroport et le long des voies de chemin de fer. Dans les deux cas, l’objectif était de détecter et d’identifier des objets dans une zone définie. Les résultats montrent que notre approche a réussi à identifier les objets d’intérêt tout en utilisant différents types de données / The modeling of real-world scenes through capturing 3D digital data has proven to be both useful andapplicable in a variety of industrial and surveying applications. Entire scenes are generally capturedby laser scanners and represented by large unorganized point clouds possibly along with additionalphotogrammetric data. A typical challenge in processing such point clouds and data lies in detectingand classifying objects that are present in the scene. In addition to the presence of noise, occlusionsand missing data, such tasks are often hindered by the irregularity of the capturing conditions bothwithin the same dataset and from one data set to another. Given the complexity of the underlyingproblems, recent processing approaches attempt to exploit semantic knowledge for identifying andclassifying objects. In the present thesis, we propose a novel approach that makes use of intelligentknowledge management strategies for processing of 3D point clouds as well as identifying andclassifying objects in digitized scenes. Our approach extends the use of semantic knowledge to allstages of the processing, including the guidance of the individual data-driven processing algorithms.The complete solution consists in a multi-stage iterative concept based on three factors: the modeledknowledge, the package of algorithms, and a classification engine. The goal of the present work isto select and guide algorithms following an adaptive and intelligent strategy for detecting objects inpoint clouds. Experiments with two case studies demonstrate the applicability of our approach. Thestudies were carried out on scans of the waiting area of an airport and along the tracks of a railway.In both cases the goal was to detect and identify objects within a defined area. Results show that ourapproach succeeded in identifying the objects of interest while using various data types

Aerosol properties are highly variable in space and time which makes the aerosol study more complex. The sources and production mechanism of aerosols decide the properties of the aerosols. Aerosol radiative forcing is defined as the perturbation to the radiative fluxes of the earth atmosphere system caused by the aerosols. High uncertainty in the aerosol radiative forcing values exists today due to the lack of the exact chemical composition data of the aerosols everywhere. There are previous studies which have introduced methods to estimate ‘optical equivalent’ composition of aerosols using spectral aerosol optical depth measurements at the surface. The impact of aerosols on the solar radiative flux depends on its size distribution and composition. Hence, measurements of downward solar spectral fluxes at the surface can be used to infer ‘optically equivalent’ composition of aerosols. Measurements of downward solar spectral flux at Bangalore were made on clear days using a spectroradiometer. This data has been used to infer the aerosol composition following an iterative method with the help of the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). Aerosols have been classified as water soluble, black carbon and three types of dust. Influence of the different aerosol types on spectral down welling irradiance at the surface have been simulated using Optical Properties of Aerosols and Clouds (OPAC) and SBDART models. The strong spectral dependence influence of water soluble aerosols and the dust aerosols on the spectral irradiance is shown. Aerosol composition was inferred following least square error minimization principle. This method can be used to estimate near-surface aerosol concentration if the vertical profile of aerosols is known a priori. This method also enables derivation of spectral single scattering albedo. The aerosol spectral radiative forcing has been estimated using downward spectral flux at the surface and compared with modeled fluxes. The contribution to the total forcing by the wavelength band 360 – 528 nm is around 60% of the total forcing. The wavelength band of 453-518 nm contributes maximum to the total forcing and it is seen that the shape of the spectral forcing is a major function of shape of the incoming solar spectrum. Aerosol spectral radiative forcing from observations of radiative fluxes agreed with modeled values when derived aerosol chemical composition was used as input. This study demonstrates that spectral flux measurements at the surface are useful to infer aerosol composition (which is optically equivalent) when and where the conventional chemical analysis is unavailable.

Au cours des dernières années, la cartographie urbaine 3D a suscité un intérêt croissant pour répondre à la demande d’applications d’analyse des scènes urbaines tournées vers un large public. Conjointement les techniques d’acquisition de données 3D progressaient. Les travaux concernant la modélisation et la visualisation 3D des villes se sont donc intensifiés. Des applications fournissent au plus grand nombre des visualisations efficaces de modèles urbains à grande échelle sur la base des imageries aérienne et satellitaire. Naturellement, la demande s’est portée vers des représentations avec un point de vue terrestre pour offrir une visualisation 3D plus détaillée et plus réaliste. Intégrées dans plusieurs navigateurs géographiques comme Google Street View, Microsoft Visual Earth ou Géoportail, ces modélisations sont désormais accessibles et offrent une représentation réaliste du terrain, créée à partir des numérisateurs mobiles terrestres. Dans des environnements urbains, la qualité des données obtenues à partir de ces véhicules terrestres hybrides est largement entravée par la présence d’objets temporairement statiques ou dynamiques (piétons, voitures, etc.) dans la scène. La mise à jour de la cartographie urbaine via la détection des modifications et le traitement des données bruitées dans les environnements urbains complexes, l’appariement des nuages de points au cours de passages successifs, voire la gestion des grandes variations d’aspect de la scène dues aux conditions environnementales constituent d’autres problèmes délicats associés à cette thématique. Plus récemment, les tâches de perception s’efforcent également de mener une analyse sémantique de l’environnement urbain pour renforcer les applications intégrant des cartes urbaines 3D. Dans cette thèse, nous présentons un travail supportant le passage à l’échelle pour la cartographie 3D urbaine automatique incorporant la reconnaissance et l’intégration temporelle. Nous présentons en détail les pratiques actuelles du domaine ainsi que les différentes méthodes, les applications, les technologies récentes d’acquisition des données et de cartographie, ainsi que les différents problèmes et les défis qui leur sont associés. Le travail présenté se confronte à ces nombreux défis mais principalement à la classification des zones urbaines l’environnement, à la détection automatique des changements, à la mise à jour efficace de la carte et l’analyse sémantique de l’environnement urbain. Dans la méthode proposée, nous effectuons d’abord la classification de l’environnement urbain en éléments permanents et temporaires. Les objets classés comme temporaire sont ensuite retirés du nuage de points 3D laissant une zone perforée dans le nuage de points 3D. Ces zones perforées ainsi que d’autres imperfections sont ensuite analysées et progressivement éliminées par une mise à jour incrémentale exploitant le concept de multiples passages. Nous montrons que la méthode d’intégration temporelle proposée permet également d’améliorer l’analyse sémantique de l’environnement urbain, notamment les façades des bâtiments. Les résultats, évalués sur des données réelles en utilisant différentes métriques, démontrent non seulement que la cartographie 3D résultante est précise et bien mise à jour, qu’elle ne contient que les caractéristiques permanentes exactes et sans imperfections, mais aussi que la méthode est également adaptée pour opérer sur des scènes urbaines de grande taille. La méthode est adaptée pour des applications liées à la modélisation et la cartographie du paysage urbain nécessitant une mise à jour fréquente de la base de données. / Over the years, 3D urban cartography has gained widespread interest and importance in the scientific community due to an ever increasing demand for urban landscape analysis for different popular applications, coupled with advances in 3D data acquisition technology. As a result, in the last few years, work on the 3D modeling and visualization of cities has intensified. Lately, applications have been very successful in delivering effective visualizations of large scale models based on aerial and satellite imagery to a broad audience. This has created a demand for ground based models as the next logical step to offer 3D visualizations of cities. Integrated in several geographical navigators, like Google Street View, Microsoft Visual Earth or Geoportail, several such models are accessible to large public who enthusiastically view the real-like representation of the terrain, created by mobile terrestrial image acquisition techniques. However, in urban environments, the quality of data acquired by these hybrid terrestrial vehicles is widely hampered by the presence of temporary stationary and dynamic objects (pedestrians, cars, etc.) in the scene. Other associated problems include efficient update of the urban cartography, effective change detection in the urban environment and issues like processing noisy data in the cluttered urban environment, matching / registration of point clouds in successive passages, and wide variations in environmental conditions, etc. Another aspect that has attracted a lot of attention recently is the semantic analysis of the urban environment to enrich semantically 3D mapping of urban cities, necessary for various perception tasks and modern applications. In this thesis, we present a scalable framework for automatic 3D urban cartography which incorporates recognition and temporal integration. We present in details the current practices in the domain along with the different methods, applications, recent data acquisition and mapping technologies as well as the different problems and challenges associated with them. The work presented addresses many of these challenges mainly pertaining to classification of urban environment, automatic change detection, efficient updating of 3D urban cartography and semantic analysis of the urban environment. In the proposed method, we first classify the urban environment into permanent and temporary classes. The objects classified as temporary are then removed from the 3D point cloud leaving behind a perforated 3D point cloud of the urban environment. These perforations along with other imperfections are then analyzed and progressively removed by incremental updating exploiting the concept of multiple passages. We also show that the proposed method of temporal integration also helps in improved semantic analysis of the urban environment, specially building façades. The proposed methods ensure that the resulting 3D cartography contains only the exact, accurate and well updated permanent features of the urban environment. These methods are validated on real data obtained from different sources in different environments. The results not only demonstrate the efficiency, scalability and technical strength of the method but also that it is ideally suited for applications pertaining to urban landscape modeling and cartography requiring frequent database updating.

Les nuages jouent un rôle important dans le cycle de l'eau et de l'énergie au sein de l'atmosphère. De plus, ils représentent l'une des principales sources d'incertitudes dans les projections des modèles de climat en raison notamment de la difficulté à paramétrer les processus qui leurs sont associés ainsi que leurs interactions avec l'environnement. Dans cette thèse nous étudions les nuages de mi-niveau qui ont été beaucoup moins étudiés que les nuages bas et les nuages hauts, en se focalisant sur l’Afrique de l'Ouest. L'Afrique de l'Ouest se caractérise par une forte saisonnalité des précipitations survenant au Sahel de juin à septembre durant la période dite de mousson. Cette période coïncide également avec le maximum annuel de la couverture nuageuse. Au travers du déploiement de la station mobile ARM (Atmospheric Radiation Measurement) durant une année en 2006 à Niamey (Niger), Bouniol et al. (2012) ont documenté les différents types de nuages observés pendant la mousson et ont montré la présence récurrente de nuages vers 6 km d'altitude dont l’impact radiatif est important dans les domaines du visible et de l'infrarouge. Dans le prolongement de cette étude, l'objectif de cette thèse est donc d'analyser plus en détails ces nuages de mi-niveau en documentant leur occurrence, leur cycle diurne et leurs caractéristiques macro- et microphysiques. Nous analysons également l'environnement thermodynamique dans lequel ces nuages sont observés ainsi que leurs effets radiatifs. D’autre part, en analysant les simulations effectuées dans le cadre du projet CMIP5, Roehrig et al. (2013) ont montré une sous-estimation de ce type de nuages dans les modèles de climat. Nous documentons plus précisément ici comment les modèles de climat et les modèles à aire limitée simulent ces nuages de mi-niveau. Afin de documenter ces nuages, des observations obtenues à partir d'instruments de télédétection active déployés sur deux sites sols : Niamey au Sahel et Bordj Badji Mokhtar au Sahara ont été combinées avec les données satellites de CloudSat et CALIPSO. Ces observations ont révélé une occurrence de ces nuages tout au long de l'année avec une prédominance durant la période de mousson. Ces nuages sont majoritairement observés dans le Sud et l'Ouest de l'Afrique de l'Ouest mais s’étendent jusqu’au cœur du Sahara. Leur présence dans cette zone désertique pourrait s’expliquer par la dynamique de la dépression thermique saharienne (Saharan Heat Low). Ces nuages sont généralement fins (la plupart ont une épaisseur inférieure à 1000 m) et sont principalement composés d'eau liquide. Une méthode de clustering appliquée à ces données nous a permis d'identifier trois types de nuages : le premier avec des bases plus basses, le deuxième avec des bases plus hautes et le dernier avec de plus fortes épaisseurs. Les radiosondages et les mesures de rayonnement nous ont permis de déterminer la stratification thermodynamique dans laquelle ces nuages sont observés ainsi que d’estimer leur impact radiatif. On observe généralement des inversions de température potentielle au sommet des nuages des deux premières familles. Dans les modèles de climat, nous avons mis en évidence une forte dispersion des occurrences des nuages de mi-niveau en termes de fréquence, de position et d’extension sur la verticale et de cycle saisonnier. L'analyse des simulations régionales indique aussi une influence de la résolution spatiale et de la paramétrisation de la convection sur la modélisation des nuages de mi-niveau simulés au Sahel et sur le Sahara. / Clouds have an important impact on the water and energy fluxes within the atmosphere. They also represent one of the main sources of uncertainties of climate models projections as a consequence of the difficulty to parametrize their associated processes as well as their interactions with their environment. In this thesis mid-level clouds are studied. Such clouds have been much less studied than low clouds and high clouds and the focus is on the West Africa. West Africa is characterized by a strong seasonality in precipitation that occur in the Sahel from June to September named the monsoon season. This period also coincides with the annual maximum of the cloud cover. Taking advantage of the one-year ARM Mobile Facility (AMF) deployment in 2006 in Niamey (Niger), Bouniol et al. (2012) documented the distinct cloud types observed during the monsoon and showed a frequent occurrence of clouds around 6 km height with an important radiative impact in the surface short-wave and long-wave domains. In the continuity of this study, the aim of this thesis is therefore to analyse in more details these mid-level clouds by documenting their occurrence, their diurnal cycle as well as their macro- and microphysical characteristics. We also analyse the thermodynamical environment in which these clouds are observed and their radiative effects. In a process-oriented evaluation of CMIP5 climate models, Roehrig et al. (2013) showed an underestimation of mid-level clouds. We document more precisely here how climate models and limited-area models simulate these mid-level clouds. To document those clouds, we combine observational data from active remote sensing instruments deployed at the two groundbased sites : Niamey in the Sahel and Bordj Badji Mokhtar in the Sahara, with merged CloudSatCALIPSO satellite. These observations reveal an occurrence of those clouds throughout the year with a predominance around the monsoon season. These clouds are preferentially observed in the Southern and Western part of West Africa but extend to the heart of the Sahara. Their presence in this desert zone may be explained by the dynamics of the Saharan Heat Low. Those clouds are usually quite thin (most of them are less than 1000 m deep) and mainly composed of liquid water. A clustering method applied to this data allows us to identify three different types of clouds : one with lower bases, one with higher bases and another with larger thicknesses. Radiosondes and radiation measurements allowed us to determine the thermodynamical stratification in which these clouds are observed as well as to estimate their radiative impact. Potential temperature inversions are generally observed at the top of the clouds of the first two families. In the climate models, we showed a strong dispersion of the occurrences of mid-level clouds in terms of frequency, location and vertical extension and seasonal cycle. Analysis of regional simulations also indicates an influence of spatial resolution and of the convection parametrization on the model ability in simulating mid-level clouds in the Sahel and in the Sahara.

The main point of this thesis is the extension of the complex solar radiation simulator, the creation of new functionalities, and the cooperation of this complex simulator with the PV power plant. This work builds on the work done in the area of solar radiation modeling. The thesis deals with the continuation, or improvement of some shortcomings, removing shortcomings, such as fixing the beginnings and ends of the simulation, correcting the calculation of sunrise and sunset, but also adding different types of clouds, combinations of different preset cloud situations, or data input, and more. These deficiencies are found in the bachelor's thesis "Complex Simulator of the solar irradiance", and PSCAD is the main tool in this work. Another important point of this work is the realization of the simulation where an improved solar radiation simulator works in cooperation with a model of a photovoltaic panel or a PV power plant, respectively. It has different operating states created in PSCAD. These include, for example, cloud crossings, both over the entire power plant and only partial. In addition, there are experiments that prove the fact that the direction of the incoming cloud plays a role in the power of the PV power plant.