De nombreux travaux se sont intéressés aux facteurs sociaux et scolaires du décrochage situés au niveau de l’école élémentaire ou du début du collège (e.g., difficultés scolaires liées à une origine sociale défavorisée). En complément, un besoin de recherche existe pour mieux comprendre le décrochage au lycée et le « processus de stress » qui le sous-tend (Dupéré et al., 2015). Les travaux de cette thèse visent à combler ce besoin en analysant les données administratives et auto-rapportées portant sur des lycéens des filières professionnelles et générales ou technologiques suivis pendant trois ans à partir de la classe de 2nde (N > 1900, dont 17% de décrocheurs). Premièrement, nos analyses multiniveaux montrent que, à caractéristiques comparables en termes d’origine sociale et de parcours scolaire en amont du lycée, le processus de stress au début du lycée augmente le risque de décrochage scolaire en diminuant les perceptions de justice scolaire, de contrôle sur la scolarité et de soutien enseignant (i.e., ressources et besoins protecteurs face au stress), ainsi que l’engagement et les résultats scolaires (i.e., facteurs proximaux du stress). Deuxièmement, quel que soit le parcours de vie de l’élève, le fait d’intégrer une spécialité de formation offrant des perspectives d’emploi plus défavorables facilite le décrochage. De même, intégrer une spécialité moins prestigieuse augmente le risque de décrocher, mais uniquement chez les élèves qui perçoivent peu de contrôle ou de justice au lycée. Troisièmement, des analyses de trajectoires scolaires indiquent l’existence de 4 profils de décrocheurs qui se distinguent aussi bien au niveau de leur parcours de vie que de leur processus de stress. La majorité d’entre eux (60%) présentent des profils d’élèves « dans la norme » au cours du lycée et s’avèrent surreprésentés dans les filières plus défavorisées. Globalement, ces résultats suggèrent que le décrochage au lycée n’est pas réductible aux facteurs de risque précoces mis en avant dans la littérature, mais qu’il tient aussi à l’existence de formations peu porteuses en termes d’emploi et au processus de stress qui résulte, pour certains élèves, de la relégation socio-scolaire. Des implications sont tirées concernant la manière de concevoir et de lutter contre le décrochage dans une approche combinant ces dimensions (i.e., l’orientation scolaire et le développement individuel). / A number of studies have delved into the social or school factors of dropping out rooted in the contexts of elementary or middle school (e.g., school difficulties associated with a low socioeconomic background). As a complement, more research is needed to better understand dropping out during high school and its underlying « stress process » (Dupéré et al., 2015). The present thesis responds to this need by analysing administrative and self-reported data from vocational and academic students followed during three years starting at the first year of high school (N > 1900, including 17% dropouts). Firstly, our multilevel analyses show that, regardless of students’ social and school background before high school, the stress process at the beginning of high school increases the odds of dropping out by diminishing perceptions of school justice and control and teacher support (i.e., resources and needs that protect against stress) as well as school engagement and grades (i.e., proximal factors of stress). Secondly, regardless of students’ background, being admitted into a vocational track that offers poorer employment prospects facilitates dropping out. Likewise, entering a less prestigious track contributes to dropout, but only among students who feel little control or justice in the high school context. Thirdly, analyses of school trajectories point to the existence of 4 dropout profiles that can be differentiated according to their life course and stress process. Most dropouts (60%) show “normative” student profiles during high school and are overrepresented in the most unfavourable tracks. Overall, these results suggest that high school dropout cannot be reduced to the early risk factors that are highlighted in the literature, but that it is also due to the existence of tracks that show little promise for future employment and to the stress process that results, for some students, from school and social relegation. Implications are drawn regarding the way dropping out can be conceived of and tackled from an approach that combines these dimensions (i.e., school tracking and individual development).

本研究使用TFIDF文字探勘技術分析樣本公司年度財務報告裡面的重要非量化資訊，與三項量化財務比率比較，欲探討公司年報在不同市場裡文字敘述與財務表現之一致性。研究結果顯示，根據從2003年至2010年上市半導體公司之年度報告，美國公司的年報較會對財務表現做出誇大的文字敘述，本研究亦發現在文字敘述上，市場較不成熟的中國公司所發布之年報較偏向低估他們的財務表現。 / This study presented a way to extract useful information out of unstructured qualitative textual data with the use of the TFIDF text mining technique, which was used to help us explore for consistencies between financial performance in the form of quantitative financial ratios and qualitative narrative disclosures in the annual report between countries with different levels of market development. The results show that, based on listed semiconductor companies' annual reports between 2003 to 2010, companies in the United States have a high tendency to exaggerate and overstate about their performance in the MD&A, while less developed markets such as China turned out to have the lowest tendency to exaggerate and was more likely to understate about its performance in their Director's Report.

Made available in DSpace on 2015-05-08T14:53:37Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 3740949 bytes, checksum: 4b4bb1e725e28d0a9a489835e70b4e60 (MD5) Previous issue date: 2014-02-24 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Find emergency public services falls into one of the classic optimization problems where points are available for candidates who are chosen, among them, those that optimize the efficiency criteria established, to find a limited number of facilities. The set of candidate sites have great influence on the final solution generated by a model location . In the research, three strategies were used to elect local candidates to position the cars of police : decision of the Security Manager , p-median model and method of clustering k-means. With the support of Geographical Information Systems (GIS ) it was possible to georeference the occurrences of crimes , to visualize the distribution of selected local candidates and identify the presence of hotspots of crime. Aiming to solve the problem of allocating vehicles adopted two approaches : exact and heuristic . Therefore, two hybrid meta - heuristics were implemented - GRASP combined with VND and GRASP with exact model. They obtained same or very approximate solutions of the optimal solution . It was developed a system of spatial decision support based on the solution of the formulation of the problem of locating facilities with restricted coverage and backup coverage. It is a Web tool built with by WebGIS technology / Localizar serviços públicos emergenciais se enquadra em um dos problemas clássicos de otimização onde pontos candidatos são disponibilizados para que sejam escolhidos, dentre eles, aqueles que otimizem o critério de eficiência estabelecido, visando localizar um número limitado de facilidades. O conjunto de locais candidatos tem grande influência sobre a solução final gerada por um modelo de localização. Na pesquisa, foram definidas três estratégias para eleger os locais candidatos ao posicionamento de viaturas policiais: decisão do gestor de segurança, modelo de Pmedianas e método de clusterização k-means. Com apoio de Sistemas de Informação Geográfica (SIG) foi possível georreferenciar as ocorrências de crimes, visualizar a distribuição dos locais candidatos selecionados e identificar a presença de hotspots de crimes. Visando resolver o problema de alocação de viaturas adotou-se duas abordagens: exata e heurística. Para tanto, duas meta-heurísticas híbridas foram implementadas - GRASP combinado com VND e GRASP com modelo exato, as quais obtiveram soluções iguais ou muito aproximadas da solução ótima. Foi desenvolvido um sistema de apoio a decisão espacial baseado na solução da formulação do problema de localização de facilidades com restrições de cobertura e cobertura backup. Trata-se de uma ferramenta WEB construída com base os padrões usados pela tecnologia WebGIS

Made available in DSpace on 2017-07-10T19:23:44Z (GMT). No. of bitstreams: 1 Kelyn Schenatto.pdf: 4212903 bytes, checksum: 0ba04350cc25aff5e6acb249938e5375 (MD5) Previous issue date: 2014-02-04 / Despite the benefits offered by the technology of precision agriculture (PA), the necessity of dense sampling grids and use of sophisticated equipment for the soil and plant handling make it financially unfeasible in many cases, especially for small producers. With the aimof making viable the PA, the definition of management zones (MZ) consists in dividing the plotin subregions that have similar physicochemical features, where it is possible to work in the conventional manner (without site-specific input application), differing them from the other sub-regions of the field. Thus we use concepts from PA, but adapting some procedures to the reality of the producer, not requiring the replacement of machinery traditionally used.Therefore, yield is usually correlated with physical and chemical properties through statistical and geostatistical methods, and attributes are selected to generate thematic maps, which are then used to define the MZ. In the generation of thematic maps step, are commonly used traditional interpolation methods (Inverse Distance - ID , inverse of the square distance - ISD, and kriging - KRI), and it is important to assess if the quality of thematic maps generated influences in the MZ drafting process and can not justify the interpolation data using robust methods such as KRI. Thus, the present study aimed to evaluate three interpolation methods (ID , ISD and KRI ) for generation of thematic maps used in the generation of MZ by clustering methods K-Means and Fuzzy C-Meas, in two experimental areas (9.9 ha and 15.5 ha), and been used data from four seasons (three crops of soybeans and one of corn). The KRI interpolation and ID showed similar UM. The agreement between the maps decreased when an increase in the number of classes, but with greater intensity with the Fuzzy C-Means method. Clustering algorithms K-Means and Fuzzy C-Means performed similar division on two UM. The best interpolation method was KRI following the ID, what justifies the choice of a more robust interpolation (KRI) to generate UM / Apesar dos benefícios proporcionados pela tecnologia de agricultura de precisão (AP), a necessidade de grades amostrais densas e uso de equipamentos sofisticados para o manejo do solo e da planta tornam o seu cultivo em muitos casos inviável financeiramente, principalmente para pequenos produtores. Com a finalidade de viabilizar a AP, a definição de unidades de manejo (UM) consiste em dividir o talhão em sub-regiões que possuam características físico-químicas semelhantes, onde se pode trabalhar de forma convencional (sem aplicação localizada de insumos), diferenciando-se das outras sub-regiões do talhão. Dessa forma, utilizam-se conceitos de AP, mas adaptam-se alguns procedimentos para a realidade do produtor, não havendo necessidade da substituição de máquinas tradicionalmente utilizadas. Para isso, são geralmente correlacionados atributos físicos e químicos com a produtividade das culturas e, por meio de métodos estatísticos e geoestatísticos, selecionam-se atributos que darão origem a mapas temáticos posteriormente utilizados para definição das UM. Na etapa de geração dos mapas temáticos, são normalmente utilizados métodos tradicionais de interpolação (inverso da distância ID, inverso da distância ao quadrado IDQ e krigagem KRI) e é importante avaliar se a qualidade dos mapas temáticos gerados influencia no processo de definição das UM, podendo desta forma não se justificar a interpolação de dados a partir do uso de métodos robustos como a KRI. O presente trabalho teve como objetivo a avaliação de três métodos de interpolação (ID, IQD e KRI) para definição dos mapas temáticos utilizados na confecção de UM pelos métodos de agrupamento K-Means e Fuzzy C-Means, em duas áreas experimentais (de 9,9 ha e 15,5 ha), sendo utilizados dados de quatro safras (três safras de soja e uma de milho). Os interpoladores ID e KRI apresentaram UM similares. A concordância entre os mapas diminuiu quando houve aumento do número de classes, mas teve maior intensidade com o método Fuzzy C-Means. Os algoritmos de agrupamento K-Means e Fuzzy C-Means se apresentaram similares na divisão em duas UM. O melhor método de interpolação foi a KRI, seguida do ID, o que justifica a escolha do interpolador mais robusto (KRI) na geração de UM

Clustering -- automatically sorting -- web search results has been the focus of much attention but is by no means a solved problem, and there is little previous work in Swedish. This thesis studies the performance of three clustering algorithms -- k-means, agglomerative hierarchical clustering, and bisecting k-means -- on a total of 32 corpora, as well as whether clustering web search previews, called snippets, instead of full texts can achieve reasonably decent results. Four internal evaluation metrics are used to assess the data. Results indicate that k-means performs worse than the other two algorithms, and that snippets may be good enough to use in an actual product, although there is ample opportunity for further research on both issues; however, results are inconclusive regarding bisecting k-means vis-à-vis agglomerative hierarchical clustering. Stop word and stemmer usage results are not significant, and appear to not affect the clustering by any considerable magnitude.

Depuis environ une dizaine d’années, les images hyperspectrales produites par les systèmes de télédétection, “Remote Sensing”, ont permis d’obtenir des informations très fiables quant aux caractéristiques spectrales de matériaux présents dans une scène donnée. Nous nous intéressons dans ce travail au problème de la segmentation non supervisée d’images hyperspectrales suivant trois approches bien distinctes. La première, de type Graph Embedding, nécessite deux étapes : une première étape d’appariement des pixels de patchs de l’image initiale grâce à une mesure de similarité spectrale entre pixels et une seconde étape d’appariement d’objets issus des segmentations locales grâce à une mesure de similarité entre objets. La deuxième, de type Spectral Hashing ou Semantic Hashing, repose sur un codage binaire des variations des profils spectraux. On procède à des segmentations par clustering à l’aide d’un algorithme de k-modes adapté au caractère binaire des données à traiter et à l’aide d’une version généralisée de la distance classique de Hamming. La troisième utilise les informations riemanniennes des variétés issues des différentes façons de représenter géométriquement une image hyperspectrale. Les segmentations se font une nouvelle fois par clustering à l’aide d’un algorithme de k-means. Nous exploitons pour cela les propriétés géométriques de l’espace des matrices symétriques définies positives, induites par la métrique de Fisher Rao. / Hyperspectral images provided by modern spectrometers are composed of reflectance values at hundreds of narrow spectral bands covering a wide range of the electromagnetic spectrum. Since spectral reflectance differs for most of the materials or objects present in a given scene, hyperspectral image processing and analysis find many real-life applications. We address in this work the problem of unsupervised hyperspectral image segmentation following three distinct approaches. The first one is of Graph Embedding type and necessitates two steps : first, pixels of the original image patchs are compared using a spectral similarity measure and then objects obtained by local segmentations are fusioned by means of a similarity measure between objects. The second one is of Spectral Hashing or Semantic Hashing type. We first define a binary encoding of spectral variations and then propose a clustering segmentation relying on a k- mode classification algorithm adapted to the categorical nature of the data, the chosen distance being a generalized version of the classical Hamming distance. In the third one, we take advantage of the geometric information given by the manifolds associated to the images. Using the metric properties of the space of Riemannian metrics, that is the space of symmetric positive definite matrices, endowed with the so-called Fisher Rao metric, we propose a k-means algorithm to obtain a cluster partitioning of the image.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / This study aimed to analyze the spatial distribution and use of orbital images for the identification of white grub damage. Will be presented in two chapters, the chapter one, presents the geostatistical characterization of white grub spatial distribution and chapter two describes the use of orbital images for the identification of white grub damage. Surveys were made during 2009 in São Francisco de Assis, Cruz Alta, Ijuí, Lagoa Vermelha, Vacaria and Tapejara, RS. The perimeters of the areas were marked with GPS navigation, with interface for computer-to-hand, used the CR-Campeiro software to create grids of sampling. The population density was estimated from soil trenches, the analysis of spatial variability was made with semivariograms, maps were generated with the ArcGIS 9.3 software, and spatial dependence estimated by classification of Cambardella et al. (1994). The satellite image is from the ALOS satellite, a scene was selected from the PRISM sensor with spatial resolution of 2.5 m, which has a dimension of 35 x 70 km. The classification of the orbital image and white grub spatial distribution map was performed in ENVI software, for this we used the unsupervised classification, the K-means algorithm to evaluate the classification accuracy; this was related to the true field (larvae m-²). The models are adjusted for different species and areas, and the species of white grubs present spatial dependence in all areas, the semivariograms indicate that the species of white grubs have different behavior spatial variability, the sampling grids and sampling can be used to characterize the spatial distribution of white grubs, the map of the spatial distribution of white grubs pests showed the aggregate behavior of these species, white grubs influence the spectral response of culture, Kappa coefficient is considered good, the ALOS image to identify white grubs damage. / Este trabalho teve por objetivo analisar a distribuição espacial e a utilização de imagens orbitais na identificação de danos de corós. Será apresentado em dois capítulos; no capítulo um, apresenta-se a caracterização geoestatística da distribuição espacial de larvas de melolontídeos e o capítulo dois descreve o uso de imagens orbitais na identificação dos danos de larvas de melolontídeos. Para isso foram feitos estudos no ano de 2009, em São Francisco de Assis, Cruz Alta, Ijuí, Lagoa Vermelha, Vacaria e Tapejara, RS. O perímetro das áreas foram demarcados com GPS de navegação, com interface para computador-de-mão, utilizou-se o programa computacional CR-Campeiro para confeccionar os grides de amostragem, a partir da abertura de uma trincheira por ponto do gride e com a contagem das larvas encontradas, foi estimada a densidade populacional, a análise da variabilidade espacial foi feita com semivariogramas, os mapas foram gerados com o programa computacional ArcGis 9.3, e a dependência espacial estimada pela classificação de Cambardella et al. (1994). A imagem de satélite é oriunda do satélite ALOS, do qual selecionou-se uma cena do sensor PRISM, com resolução espacial de 2,5 m, esta possui dimensão de 35 x 70 km, a classificação da imagem orbital e do mapa da distribuição espacial de corós foi efetuada no programa computacional ENVI; para tal foi utilizada a classificação não supervisionada, pelo algoritmo K-means, para avaliar a exatidão da classificação, esta foi relacionada com a verdade de campo (larvas m-²). Os modelos ajustados são diferentes para as espécies e áreas; a distribuição espacial das larvas de melolontídeos apresenta dependência espacial em todas as áreas; os semivariogramas indicam que as espécies de corós apresentam comportamento de variabilidade espacial diferenciado; os grides amostrais e a técnica de amostragem podem ser utilizados para caracterizar a distribuição espacial de corós; o mapa da distribuição espacial de larvas de melolontídeos demonstrou o comportamento agregado dessas espécies; as larvas de melolontídeos influenciaram na resposta espectral da cultura; o coeficiente Kappa é considerado bom; a imagem ALOS permite identificar os danos de larvas de melolontídeos.

Les développements continus en micro-spectroscopie vibrationnelle IR et en analyse numérique de données multidimensionnelles ont permis récemment l'émergence de l'histologie spectrale. A l'échelle tissulaire et sur une base biomoléculaire, cette nouvelle approche représente un outil prometteur pour une meilleure analyse et caractérisation de différents états physiopathologiques, et potentiellement une aide au diagnostic clinique. Dans ce travail, en utilisant un modèle tissulaire de côlon normal chez la Souris et chez l’Homme, nous avons apporté des améliorations à la chaîne de traitements des données afin d'automatiser et d'optimiser cette histologie spectrale.En effet, dans un premier temps, le développement d’une double application hiérarchique d'indices de validité a permis de déterminer le nombre optimal de classes nécessaire à une caractérisation complète des structures histologiques. Dans un second temps, cette méthode a été généralisée à l'échelle interindividuelle par couplage d'un prétraitement par EMSC (Extended Multiplicative Signal Correction) et d'une classification non-supervisée k-Means; ce couplage étant appliqué conjointement à toutes les images spectrales IR. Enfin, compte tenu de l'essor des métaheuristiques et de leur capacité à résoudre des problèmes complexes d'optimisation numérique, nous avons transposé un algorithme mémétique aux données spectrales IR. Ce nouvel algorithme se compose d'un algorithme génétique et d'un raffinement par classification non-supervisée k-Means. Comparé aux méthodes classiques de clustering, cet algorithme mémétique appliqué aux images spectrales IR, a permis de réaliser une classification non-supervisée optimale et indépendante de l'initialisation. / Recent developments in IR vibrational microspectroscopy and numerical multidimensional analysis have led to the emergence of spectral histology. At the tissue level, this new approach represents an attractive tool for a better analysis and characterization of pathophysiological states and for diagnostic challenges. Here, using normal murine and human colon tissues, data processing steps have been improved for automating and optimizing this spectral histology. First, the development of a hierarchical double application of validity indices permitted to determine the optimal number of clusters that correctly identified the different colon histological components. Second, this method has been improved to perform spectral histology at the inter-individual level. For this, EMSC (Extended Multiplicative Signal Correction) preprocessing has been successfully combined to k-Means clustering. Finally, given the ability of metaheuristics to solve complex optimization problems, a memetic algorithm has been developed for IR spectral data clustering. This algorithm is composed of a genetic algorithm and a k-Means clustering refinement. Compared with conventional clustering methods, our memetic algorithm allowed to generate an optimal and initialization-independent clustering.

This master thesis deals with cluster analysis, more specifically with clustering methods that use fuzzy sets. Basic clustering algorithms and necessary multivariate transformations are described in the first chapter. In the practical part, which is in the third chapter we apply fuzzy c-means clustering and k-means clustering on real data. Data used for clustering are the inputs of chemical transport model CMAQ. Model CMAQ is used to approximate concentration of air pollutants in the atmosphere. To the data we will apply two different clustering methods. We have used two different methods to select optimal weighting exponent to find data structure in our data. We have compared all 3 created data structures. The structures resembled each other but with fuzzy c-means clustering, one of the clusters did not resemble any of the clustering inputs. The end of the third chapter is dedicated to an attempt to find a regression model that finds the relationship between inputs and outputs of model CMAQ.

The programme for the segmentation of a speech into fonems was created as a part of the master´s thesis. This programme was made in the programme Matlab and consists of several scripts. The programme serves for automatic segmentation. Speech segmentation is the process of identifying the boundaries between phonemes in spoken natural languages. Automatic segmentation is based on vector quantization. In the first step of algorithm, feature extraction is realized. Then speech segments are assigned to calculated centroids. Position where centroid is changed is marked as a boundary of phoneme. The audiorecords were elaborated by the programme and a operation of the automatic segmentation was analysed. A detailed manual was created to the programme too. Individual used methods of the elaboration of a speech were in the master´s thesis briefly descripted, its implementations in the programme and reasons of set of its parameters.