Finite mixture modeling is a useful statistical technique for clustering individuals based on patterns of responses. The fundamental idea of the mixture modeling approach is to assume there are latent clusters of individuals in the population which each generate their own distinct distribution of observations (multivariate or univariate) which are then mixed up together in the full population. Hence, the name mixture comes from the fact that what we observe is a mixture of distributions. The goal of this model-based clustering technique is to identify what the mixture of distributions is so that, given a particular response pattern, individuals can be clustered accordingly. Commonly, finite mixture models, as well as the special case of latent class analysis, are used on data that inherently involve repeated measures. The purpose of this dissertation is to extend the finite mixture model to allow for the number of repeated measures to be incorporated and contribute to the clustering of individuals rather than measures. The dimension of the repeated measures or simply the count of responses is assumed to follow a truncated Poisson distribution and this information can be incorporated into what we call a dimension informative finite mixture model (DIMM). The outline of this dissertation is as follows. Paper 1 is entitled, "Dimension Informative Mixture Modeling (DIMM) for questionnaire data with an informative number of repeated measures." This paper describes the type of data structures considered and introduces the dimension informative mixture model (DIMM). A simulation study is performed to examine how well the DIMM fits the known specified truth. In the first scenario, we specify a mixture of three univariate normal distributions with different means and similar variances with different and similar counts of repeated measurements. We found that the DIMM predicts the true underlying class membership better than the traditional finite mixture model using a predicted value metric score. In the second scenario, we specify a mixture of two univariate normal distributions with the same means and variances with different and similar counts of repeated measurements. We found that that the count-informative finite mixture model predicts the truth much better than the non-informative finite mixture model. Paper 2 is entitled, "Patterns of Physical Activity in the Northern Manhattan Study (NOMAS) Using Multivariate Finite Mixture Modeling (MFMM)." This is a study that applies a multivariate finite mixture modeling approach to examining and elucidating underlying latent clusters of different physical activity profiles based on four dimensions: total frequency of activities, average duration per activity, total energy expenditure and the total count of the number of different activities conducted. We found a five cluster solution to describe the complex patterns of physical activity levels, as measured by fifteen different physical activity items, among a US based elderly cohort. Adding in a class of individuals who were not doing any physical activity, the labels of these six clusters are: no exercise, very inactive, somewhat inactive, slightly under guidelines, meet guidelines and above guidelines. This methodology improves upon previous work which utilized only the total metabolic equivalent (a proxy of energy expenditure) to classify individuals into inactive, active and highly active. Paper 3 is entitled, "Complex Drug Use Patterns and Associated HIV Transmission Risk Behaviors in an Internet Sample of US Men Who Have Sex With Men." This is a study that applies the count-informative information into a latent class analysis on nineteen binary drug items of drugs consumed within the past year before a sexual encounter. In addition to the individual drugs used, the mixture model incorporated a count of the total number of drugs used. We found a six class solution: low drug use, some recreational drug use, nitrite inhalants (poppers) with prescription erectile dysfunction (ED) drug use, poppers with prescription/non-prescription ED drug use and high polydrug use. Compared to participants in the low drug use class, participants in the highest drug use class were 5.5 times more likely to report unprotected anal intercourse (UAI) in their last sexual encounter and approximately 4 times more likely to report a new sexually transmitted infection (STI) in the past year. Younger men were also less likely to report UAI than older men but more likely to report an STI.

Os royalties de petróleo têm ganhado notoriedade nos últimos anos pelo crescimento das atividades petrolíferas no país, as mudanças nas leis, preços do petróleo e transferência e aplicação de recursos nos Municípios para seu desenvolvimento socioeconômico. Esta pesquisa busca identificar mudanças em indicadores socioeconômicos em Municípios do estado do Rio de Janeiro através de análise temporal de variáveis que indiquem uma relação da evolução socioeconômica dos Municípios com os royalties de petróleo. Para testar esta hipótese, foi feita uma análise de agrupamento dos Municípios do estado do Rio de Janeiro utilizando as variáveis IDH (Índice de Desenvolvimento Humano), PIB (Produto Interno Bruto) e população, sendo todas as variáveis apresentando valores do ano 2000. Com a determinação do número de grupos, foram escolhidos dois Municípios de cada grupo sob a condição de maior arrecadador de royalties e não arrecadador de royalties e analisados entre os anos 2003 e 2006 para verificar a possível mudança de indicadores socioeconômicos neste período e possível relação desta mudança com royalties de petróleo. / The oil royalties have gained notoriety in recent years by the growth of oil activities in the country, changes in the legislation, oil prices and the transfer and application of resources in the municipalities for their socioeconomic development. The purpose of this research is to indentify changes in the socioeconomic indicators of municipalities of state of Rio de Janeiro through temporal analysis of variables that indicate a relationship between the socioeconomic development of municipalities and the royalties from oil. To test this hypothesis, we performed a cluster analysis on municipalities of Rio de Janeiro state using variables IHD (Index of Human Development), GDP (Gross Domestic Product) and population, and all the variables are related to the year 2000. Upon determination of the number of groups, the first was the received the largest amount of royalties, and the second did not received royalties at all. They were analyzed from 2003 to 2006 in order to investigate changes in the socioeconomic indicators, and if those changes had to do with oil royalties.

The main goal of this thesis is to test the possibility of forward and backward segmentation on the single-family housing market, to reveal, describe and develop a profile of segments and to suggest marketing recommendations. Data from primary research is encoded in MS Excel and processed in the statistical analysis program SPSS Statistics 19 for Windows. The output of the thesis reveals three forward segments and three backward segments of the market. Based on certain specifics shown by each of the monitored segments, I suggested numerous marketing recommendations.

A leishmaniose visceral é uma zoonose de grande importância para a saúde pública, com ampla distribuição geográfica e epidemiologia complexa. Apesar de diversas estratégias de controle, a doença continua se expandindo, tendo o cão como principal reservatório. Levando em consideração que análises espaciais são úteis para compreender melhor a dinâmica da doença, avaliar fatores de risco e complementar os programas de prevenção e controle, o presente estudo teve como objetivo caracterizar a distribuição da leishmaniose visceral canina e relacionar sua dinâmica com características ou feições espaciais no município de Panorama (SP). A partir de dados secundários coletados em um inquérito sorológico entre agosto de 2012 e janeiro de 2013, 986 cães foram classificados como positivos e negativos de acordo com o protocolo oficial do Ministério da Saúde. Posteriormente uma análise espacial foi conduzida, compreendendo desde a visualização dos dados até a elaboração de um mapa de risco relativo, passando por análises de cluster global (função K) e local (varredura espacial). Para avaliar uma possível relação entre o cluster detectado com a vegetação na área de estudo, calculou-se o Índice de Vegetação por Diferença Normalizada (NDVI). A prevalência da doença encontrada na população de cães estudada foi de 20,3% (200/986). A visualização espacial demonstrou que tanto animais positivos quanto negativos estavam distribuídos por toda a área de estudo. O mapa de intensidade dos animais positivos apontou duas localidades de possíveis clusters, quando comparado ao mapa de intensidade dos animais negativos. As análises de cluster confirmaram a presença de um aglomerado e um cluster foi detectado na região central do município, com um risco relativo de 2,63 (p=0,01). A variação espacial do risco relativo na área de estudo foi mapeada e também identificou a mesma região como área significativa de alto risco (p<0,05). Não foram observadas diferenças no padrão de vegetação comparando as áreas interna e externa ao cluster. Sendo assim, novos estudos devem ser realizados com o intuito de compreender outros fatores de risco que possam ter levado à ocorrência do cluster descrito. A prevalência, a localização do cluster espacial e o mapa de risco relativo fornecem subsídios para direcionamento de esforços do Setor de Vigilância Epidemiológica de Panorama para áreas de alto risco, o que pode poupar recursos e aperfeiçoar o controle da leishmaniose visceral no município. / Visceral leishmaniasis is a zoonosis of great importance for public health, having worldwide distribution and complex epidemiology. Despite several control strategies, the disease continues to expand, being dogs its main reservoir. Considering that spatial analysis is useful to better understand the disease dynamics, to evaluate risk factors and to complement prevention and control programs, this study aimed to characterize the distribution of canine visceral leishmaniasis and relate it to spatial features in Panorama, an endemic city of São Paulo State, Brazil. Using secondary data collected in a serological survey between August 2012 and January 2013, 986 dogs were classified as positive and negative for leishmaniasis. Later, a spatial analysis was conducted comprising from data visualization to the elaboration of a relative risk map, undergoing global (K function) and local cluster analysis (spatial scan). To evaluate a possible relation between the detected cluster and vegetation in the study area, the Normalized Difference Vegetation Index (NDVI) was calculated. The prevalence in the studied dog population was 20.3% (200/986). Spatial visualization showed that both positive and negative animals were distributed throughout the study area. Intensity map of positive animals showed two sites of possible clusters compared to the intensity map of negative animals. A cluster was detected in a central region of the city, with a relative risk of 2.63 (p=0,01). The spatial variation of the relative risk in the study area was mapped and the same region was identified as a significant high risk area (p<0.05). No differences were observed in the vegetation pattern comparing the cluster internal and external areas. Therefore, further studies should be conducted in order to understand other risk factors that may have led to the occurrence of the described cluster. The prevalence data, the cluster location and the relative risk map provide subsidies for the efforts of the city epidemiological surveillance department towards high risk areas. This can save resources and improve control of visceral leishmaniasis in the study area.

O efeito das variáveis meteorológicas na maturação da cana-de-açúcar é um processo ainda pouco conhecido, apesar de apresentar inúmeros impactos à qualidade da matéria-prima para a indústria sucro-energética brasileira. O objetivo do presente trabalho foi avaliar os efeitos das variáveis meteorológicas no processo de maturação de cultivares de cana-de-açúcar e gerar modelos capazes de descrevê-lo. O experimento foi realizado em área pertencente ao Grupo Raízen (ex-Cosan), em Piracicaba, SP, no período de março de 2002 a outubro de 2003. Foram avaliadas oito cultivares de cana-de-açúcar em 32 amostragens realizadas de março a outubro de 2003. Variáveis relacionadas à qualidade de matéria-prima da cana-de-açúcar (ATR, AR, ART, Pureza, Brix, Pol%cana, fibra e umidade) e variáveis meteorológicas (temperatura do ar, precipitação, radiação solar, entre outras) foram submetidas à análise estatística descritiva e multivariada, visando melhorar a compreensão do processo de maturação e suas relações com as condições ambientais. As variáveis meteorológicas de melhor correlação com as variáveis de qualidade da cana-de-açúcar foram utilizadas na elaboração de modelos descritivos do processo de maturação, os quais foram agrupados em precoces, médios e tardios, de acordo com o padrão de maturação das cultivares estudadas. A avaliação dos modelos foi realizada pela análise dos resíduos (presença de outliers, homogeneidade das variâncias e normalidade dos resíduos) e pela comparação com dados independentes (erros médios, R2, índice de concordância de Willmott e índice de confiança de Camargo). Independente do padrão de maturação (precoce, médias e tardias), os modelos de melhor desempenho foram aqueles que descreveram as variáveis ATR, Brix, Pol%cana e umidade, com valores de R2 ajustado acima de 0,9 (p significativo a 1%) e ótimo desempenho segundo índice C de Camargo (acima de 0,85), quando testados com dados independentes. O modelo de fibra apresentou os menores valores de R2 ajustado (em torno de 0,65) e não normalidade dos resíduos. Contudo, sua avaliação com dados independentes levou à obtenção de valores de índice C acima de 0,8. Os modelos gerados mostram que a precipitação pode ser utilizada como a principal variável na previsão da qualidade da matéria-prima da cana-de-açúcar e que seu uso pode ser estendido a outras áreas além daquela para onde foi inicialmente gerado. / The effect of meteorological variables on sugarcane ripening is a not very well known process in spite of the several impacts of that on the quality of the raw material for the sugarcane industry. The objective of this study was to evaluate the effects of meteorological variables on sugarcane ripening and based on that to establish models able to describe this process. The study was conducted in an area of the Raízen Group (former Cosan), in Piracicaba, state of São Paulo, Brazil, from March 2002 (planting) to October 2003. Eight sugarcane cultivars were evaluated by analyzing 32 samples collected from March to October 2003. Variables related to the quality of the raw material (ATR, AR, ART, Purity, Brix, Pol%cane, fiber and moisture) and weather (air temperature, rainfall, solar radiation, among others) were submitted to descriptive and multivariate statistical analysis in order to better understand the sugarcane ripening process and the relationship between this process and environmental conditions. The meteorological variables of best fit were used for elaborating the models to describe the ripening process, which were grouped into early, middle and late, according to the maturity pattern of the studied cultivars. The evaluation of the models was based on the analysis of residuals (presence of outliers, homogeneity of variances and normality of residuals) and on the comparison between estimated and independent data (mean errors, R2, agreement index of Willmott and confidence index of Camargo). Regardless of the pattern of sugarcane maturation (early, middle and late), the models that presented the best performance were for ATR, Brix, Pol% cane and humidity variables, with adjusted R2 values above 0.9 (p significant at 1%) and excellent performance, with C index above 0.85, when evaluated with independent data. The fiber model had the lowest adjusted R2 values (around 0.65) and problems in the distribution of its residuals (non-normality); however, when it was tested with independent data an acceptable performance was found, with C index above 0.8. The generated models showed that precipitation can be used as the main variable for predicting sugarcane quality and that its use can be extended to other areas than the one where it was originally generated.

Coagrupamento é uma estratégia para análise de dados capaz de encontrar grupos de dados, então denominados cogrupos, que são formados considerando subconjuntos diferentes das características descritivas dos dados. Contextos de aplicação caracterizados por apresentar subjetividade, como mineração de texto, são candidatos a serem submetidos à estratégia de coagrupamento; a flexibilidade em associar textos de acordo com características parciais representa um tratamento adequado a tal subjetividade. Um método para implementação de coagrupamento capaz de lidar com esse tipo de dados é a fatoração de matrizes. Nesta dissertação de mestrado são propostas duas estratégias para coagrupamento baseadas em fatoração de matrizes não-negativas, capazes de encontrar cogrupos organizados com sobreposição de colunas em uma matriz de valores reais positivos. As estratégias são apresentadas em termos de suas definições formais e seus algoritmos para implementação. Resultados experimentais quantitativos e qualitativos são fornecidos a partir de problemas baseados em conjuntos de dados sintéticos e em conjuntos de dados reais, sendo esses últimos contextualizados na área de mineração de texto. Os resultados são analisados em termos de quantização do espaço e capacidade de reconstrução, capacidade de agrupamento utilizando as métricas índice de Rand e informação mútua normalizada e geração de informação (interpretabilidade dos modelos). Os resultados confirmam a hipótese de que as estratégias propostas são capazes de descobrir cogrupos com sobreposição de forma natural, e que tal organização de cogrupos fornece informação detalhada, e portanto de valor diferenciado, para as áreas de análise de agrupamento e mineração de texto / Coclustering is a data analysis strategy which is able to discover data clusters, known as coclusters. This technique allows data to be clustered based on different subsets defined by data descriptive features. Application contexts characterized by subjectivity, such as text mining, are candidates for applying coclustering strategy due to the flexibility to associate documents according to partial features. The coclustering method can be implemented by means of matrix factorization, which is suitable to handle this type of data. In this thesis two strategies are proposed in non-negative matrix factorization for coclustering. These strategies are able to find column overlapping coclusters in a given dataset of positive data and are presented in terms of their formal definitions as well as their algorithms\' implementation. Quantitative and qualitative experimental results are presented through applying synthetic datasets and real datasets contextualized in text mining. This is accomplished by analyzing them in terms of space quantization, clustering capabilities and generated information (interpretability of models). The well known external metrics Rand index and normalized mutual information are used to achieve the analysis of clustering capabilities. Results confirm the hypothesis that the proposed strategies are able to discover overlapping coclusters naturally. Moreover, these coclusters produced by the new algorithms provide detailed information and are thus valuable for future research in cluster analysis and text mining

Submitted by Jorge Silva (jorgelmsilva@ufrrj.br) on 2016-10-26T17:13:33Z No. of bitstreams: 1 2016 - Raquel Rodrigues Costa Mello.pdf: 1199112 bytes, checksum: bcda4e1218e0674de384583a345b56eb (MD5) / Made available in DSpace on 2016-10-26T17:13:33Z (GMT). No. of bitstreams: 1 2016 - Raquel Rodrigues Costa Mello.pdf: 1199112 bytes, checksum: bcda4e1218e0674de384583a345b56eb (MD5) Previous issue date: 2016-01-29 / CAPES / The aim of this study was to investigate the possibility to generate different productive groups in Sindhi breed through multivariate techniques, in order to give directions to genetic improvement programs in this breed. For this goal, performance data provided by the Brazilian Association of Zebu Breeders related to 560 Sindhi breed females from 28 different herds in Brazil, born in the period from 1987 to 2011, were used. The traits age at first calving, calving interval, reproductive efficiency, total milk yield and lactation period were analyzed, being submitted to the principal components and cluster analysis, with the aid of GENES? statistical program. By the principal components analysis, these five components were estimated, and the first three explained 90.79% of the data?s total variation. The traits considered most relevant to the discrimination of the data set, in decreasing order of importance, were: calving interval, lactation period, age at first calving, total milk yield, and reproductive efficiency. By cluster analysis, twelve different groups were generated from the pool of Sindhi herds analyzed, with a great homogeneity among females for the traits evaluated, and only few females generating separate groups. Four hundred and twenty-nine females were clustered in one group, representing 76.60% of the genotypes. This indicates that, although there are genotypes with large genetic diversity, more than two thirds of the animals are similar to the traits evaluated, showing a high degree of relationship between them. The traits for total milk yield showed 71.92% of the total variation, and age at first calving contributed with 23.06% of the variation, being the two most important traits for the variability of the data. Thus, there is evidence of divergence between the groups regarding total milk yield, indicating that this trait stands out in the differentiation of groups, and these groups could be benchmarks for the use of genetic improvement programs whose focus is the increase in milk yield. In conclusion, the multivariate procedures were effective to summarize the evaluated information and to discriminate the most important traits, providing better identification of the most appropriate females to certain herds or milk production systems. The analysis of the relative contribution was effective in identifying total milk yield and age at first calving as the most relevant traits for the differentiation of groups, and they can be useful targets for genetic improvement programs that focus on milk yield and reproductive precocity. / O objetivo deste trabalho foi verificar a possibilidade de forma??o de diferentes grupos produtivos na ra?a Sindi por meio de t?cnicas multivariadas, a fim de se direcionar as a??es nos programas de melhoramento gen?tico nesta ra?a. Para tanto, foram utilizados dados de desempenho fornecidos pela Associa??o Brasileira dos Criadores de Zebu (ABCZ) referentes a 560 f?meas da ra?a Sindi procedentes de 28 rebanhos dos diferentes estados do Brasil, nascidas entre 1987 a 2011. Desse modo, foram analisadas as caracter?sticas idade ao primeiro parto, intervalo de partos, efici?ncia reprodutiva, produ??o de leite e dura??o da lacta??o, sendo submetidas ?s an?lises dos componentes principais e de agrupamento com o aux?lio do programa estat?stico GENES?. Pela an?lise dos componentes principais, foram estimados cinco componentes, dos quais os tr?s primeiros explicaram 90,79% da varia??o total dos dados. O primeiro componente explicou 37,18%, o segundo 33,63% e o terceiro 19,97% da vari?ncia total, sendo que esta an?lise possibilitou a discrimina??o das caracter?sticas mais importantes e menos importantes para a varia??o total no conjunto dos dados. As caracter?sticas consideradas mais relevantes para a caracteriza??o do conjunto de dados, em ordem decrescente de import?ncia, foram intervalo de partos, dura??o da lacta??o, idade ao primeiro parto, produ??o total de leite e efici?ncia reprodutiva. Pela an?lise de agrupamentos, observou-se a forma??o de doze diferentes grupos no rebanho Sindi estudado, com uma grande homogeneidade entre os animais para as caracter?sticas avaliadas, com alguns poucos animais formando grupos distintos. Houve a forma??o de um grupo com 429 f?meas, ou seja, 76,60% dos gen?tipos, o que indica que, embora haja gen?tipos com grande diverg?ncia gen?tica entre si, mais da metade ? similar para as caracter?sticas avaliadas, evidenciando um grau estreito de rela??o entre elas. Al?m disso, foi poss?vel observar as caracter?sticas produ??o total de leite, com 71,92% da varia??o total, e idade ao primeiro parto, com 23,06% da varia??o total, como as mais importantes para a variabilidade dos dados. As caracter?sticas com menor variabilidade e, portanto, consideradas menos importantes foram intervalo de partos, dura??o da lacta??o e efici?ncia reprodutiva, com 4,37; 0,61 e 0,02% da varia??o total, respectivamente. Assim, evidenciou-se o distanciamento entre os grupos para as diferentes m?dias de produ??o total de leite, indicando que tal caracter?stica se destaca na diferencia??o dos grupos e que tais grupos poderiam ser referenciais para utiliza??o em programas de melhoramento gen?tico, cujo enfoque seja a obten??o de maiores produ??es de leite. Portanto, conclui-se que os procedimentos multivariados foram eficientes para resumir as informa??es avaliadas e discriminar as caracter?sticas mais importantes, promovendo maior facilidade na identifica??o das f?meas mais adequadas para determinados rebanhos ou sistemas de produ??o de leite. A an?lise da contribui??o relativa das vari?veis foi efetiva na identifica??o das caracter?sticas produ??o total de leite e idade ao primeiro parto como mais relevantes para a diferencia??o dos grupos formados, sendo ?teis para o direcionamento em programas de melhoramento gen?tico cujo enfoque seja maior produ??o de leite e precocidade sexual.

INTRODUÇÃO: O Acidente Vascular Cerebral (AVC) é a segunda causa de mortalidade e a principal causa de incapacidade no mundo. Muitos fatores de riscos estão associados ao AVC, sendo o principal a hipertensão arterial. Vários estudos também mostraram a associação de um baixo status socioeconômico com altas taxas de mortalidade pelo AVC. O presente estudo teve como objetivo analisar a distribuição espacial da mortalidade por AVC na cidade de São Paulo de acordo com os fatores socioeconômicos. MÉTODOS: Estudo realizado nos 96 distritos da cidade de São Paulo no período de 2006 a 2008. Foram analisadas taxas de mortalidade por AVC em ambos os sexos. Os fatores analisados foram % de indivíduos com escolaridade nível superior, % domicílios com três pessoas ou mais morando na residência e % de indivíduos das classes D e E em cada distrito. Aplicou-se a metodologia de agrupamento K-means para análise da distribuição da mortalidade por AVC de acordo com os fatores socioeconômicos e uma regressão linear com heterocedasticidade corrigida para avaliar a relevância de cada fator. RESULTADOS: As médias das taxas de mortalidade por AVC foram mais elevadas nos homens xx (72,7/100.000 habitantes) comparados às mulheres (48,9/100.000 habitantes). O agrupamento A possui os distritos com melhores condições socioeconômicas (51,3% possuem escolaridade superior, 47,3% moram com três pessoas ou mais, 3,23% pertencem a classe D e E) enquanto que os grupos D e E incluem distritos com piores condições socioeconômicas localizados nas áreas mais periféricas. As taxas de mortalidade por AVC foram mais elevadas no grupo E, tanto no sexo masculino (82,7/100.000 habitantes) quanto no feminino (60,2/100.000 habitantes). A regressão linear em ambos os sexos mostrou que o modelo aplicado foi adequado com r² ajustado de 0,64 para homens e 0,70 para mulheres, sendo que a escolaridade superior e três pessoas ou mais habitantes na mesma residência foram significativos (p<0,001, para ambos). CONCLUSÃO: A mortalidade por AVC apresentou uma distribuição diferenciada na cidade de São Paulo com maior mortalidade nas regiões mais pobres e periféricas mostrando uma relação inversa com o status socioeconômico / BACKGROUND: Stroke is the second cause of mortality and the main cause of disabilities in the world. Several risk factors are associated to stroke and the most important is the high blood pressure. Several studies have also showed an association between low socioeconomic status and high stroke mortality rates. The objective of this study is to analyze the spatial distribution of stroke mortality according to socioeconomic status in the city of Sao Paulo, Brazil. METHOD: The study included all the 96 districts of the city from 2006 to 2008. We analyzed stroke mortality rates in both genders. Socioeconomic factors included in the analysis are: % of people with at least college education, % of houses with at least three people living together, and % of people from classes D and E (most deprived people) in the district. We used cluster analysis K-means for evaluation of the distribution of socioeconomic factors and stroke mortality rates and a linear regression with heteroskedasticity corrected to evaluate contribution of each factor on stroke mortality. RESULTS: Mean stroke mortality rate was higher in men (72.7/100,000 inhabitants) compared to women (48.9/100,000 inhabitants). Group A has the districts with better socioeconomic status (51.3% of xxii individuals with at least college, 47.3% of individuals living in a house with at least 3 people, and only 3.2% of individuals of the Classes D and E most deprived people) while groups D and E have the worst economic status living in the most peripheric areas. Stroke mortality rates were higher in group E for men (82.6/100,000 inhabitants) and women (60.2/100,000 inhabitants). For both sexes, a linear regression showed that the applied model was adequate with a adjusted r2 of 0.64 for men and of 0.70 of women with a significant difference for % of individuals with at least college education and % of houses with at least three individuals living together (p<0,001, for both). CONCLUSION: Stroke mortality presented a different spatial distribution in the city with a higher mortality in the most deprived and peripheric areas showing an inverse relationship with socioeconomic status

La lombalgie (LBP) touche 80% de la population mondiale adulte et devient chronique dans 10 à 15% des cas. Pour la grande majorité des cas adultes (85%), aucune cause ne peut être clairement identifiée pour expliquer ces douleurs et l’on parle alors de lombalgie chronique « non-spécifique » (NSCLBP). Chez l’enfant et l’adolescent, la prévalence de la NSCLBP est semblable à celle de l’adulte. Malgré la faible incidence de pathologies graves associées, la lombalgie de l’enfant et de l’adolescent implique, souvent dans sa prise en charge diagnostique, une exposition augmentée aux radiations et un stress parental important. Cependant, la présence d’anomalies radiologiques est aussi fréquente dans la population asymptomatique que dans la population avec NSCLBP. Ceci remet en question l’intérêt clinique de la radiologie pour dépister une cause possible de NSCLBP. Dans ce contexte, il est nécessaire d’identifier de nouveaux outils, si possible non-irradiants et peu coûteux, pour identifier des caractéristiques spécifiques aux enfants et adolescents souffrant de NSCLBP et ainsi améliorer la compréhension de cette pathologie.L’analyse électromyographique (EMG) de l’activité des muscles paravertébraux lombaires s’est avérée cliniquement pertinente dans la population adulte pour discriminer les patients souffrant de NSCLBP des participants asymptomatiques. Plusieurs paramètres EMG enregistrés lors de différentes tâches ont été identifiés chez l’adulte pour caractériser les participants NSCLBP. Les paramètres EMG des muscles lombaires les plus couramment rapportés dans la littérature sont : un temps de maintien réduit ainsi qu’une fatigue musculaire accélérée pendant le test d’endurance des muscles extenseurs du tronc, la réduction ou l’absence du phénomène de flexion-relaxation (FRP) pendant la tâche de flexion maximale du tronc ainsi qu’un pattern atypique supportant l’hypothèse de précaution pendant la marche à différentes vitesses. Si ces caractéristiques EMG spécifiques aux patients souffrant de NSCLBP ont été bien établies chez l’adulte, la question est désormais de savoir ce qu’il en est chez l’enfant et l’adolescent souffrant de NSCLBP.Dans ce contexte clinique, l’objectif de ce travail doctoral était d’évaluer les caractéristiques EMG décrites ci-dessus dans une cohorte d’enfants et d’adolescents souffrant de NSCLBP en comparaison à des participants asymptomatiques (CTRL). Pour y répondre, plusieurs études complémentaires ont été effectuées.Dans leur ensemble, les travaux de cette thèse de doctorat ont montré que les phénomènes EMG reportés dans une population adulte avec NSCLBP ne sont pas retrouvés dans une population pédiatrique avec NSCLBP. Ces résultats remettent en question le diagnostic et la prise en charge actuelle des enfants et adolescents souffrant de NSCLBP, qui est, à ce jour, calquée sur le modèle adulte. Des études supplémentaires sont cependant nécessaires pour confirmer ces résultats sur une cohorte plus importante. Il serait aussi intéressant d’évaluer une même cohorte à partir de l’enfance jusqu’à l’âge adulte afin d’évaluer quels facteurs pourraient prédire l’apparition des phénomènes rapportés dans la littérature adulte. / The majority of the worldwide population (80%) suffers from low back pain (LBP) over life. LBP becomes chronic (CLBP) in 10 to 15% of (all) adult cases yielding important functional and socio-economic adverse repercussions. The majority of LBP (85%) is classified as “non-specific” (NSCLBP), i.e. with an absence of any identified cause. LBP prevalence on children and adolescents is comparable to adults. Despite the low incidence of serious associated diseases, the fear of missing them increased patient’s exposure to radiation. However, an absence of significant correlation between radiology changes in the lower spine and low back pain was reported for school children. In this context, it is necessary to identify new tools, if possible non-irradiating and inexpensive, to identify specific characteristics of children and adolescents suffering from NSCLBP and thus improve the understanding of this pathology.An interesting tool, highlighted in adult population, is to evaluate surface electromyography (EMG) of low back muscles. Existing EMG phenomena were reported to discriminate adults with and without NSCLBP: reduced trunk muscle endurance, absence of flexion-relaxation phenomenon and guarding hypothesis during gait at different velocities. These EMG characteristics have not yet been confirmed for children and adolescents suffering of NSCLBP.This clinical context justifies the present doctoral work. The aim was to evaluate EMG characteristics in children and adolescents with NSCLBP in comparison with control participants. To achieve these objectives, several complementary studies were successively conducted.Taken together, the results of this doctoral work showed that the EMG characteristics frequently reported for NSCLBP in adults were absent or reduced in children and adolescent suffering from NSCLBP. These findings are inconsistent with the existing literature on adults and might affect the future therapeutic management of children and adolescents with NSCLBP, which is, to date, an imitation of the adult model. It would be interesting to confirm these results on the basis of a larger cohort and to reassess the same children and adolescents in adulthood to identify whether the EMG phenomenon, as known in NSCLBP adults, appears over time.

Vast amounts of data are produced all the time. Yet this data does not easily equate to useful information: extracting information from large amounts of high dimensional data is nontrivial. People are simply drowning in data. A recent and growing source of high-dimensional data is hyperspectral imaging. Hyperspectral images allow for massive amounts of spectral information to be contained in a single image. In this thesis, a robust supervised machine learning algorithm is developed to efficiently perform binary object classification on hyperspectral image data by making use of the geometry of Grassmann manifolds. This algorithm can consistently distinguish between a large range of even very similar materials, returning very accurate classification results with very little training data. When distinguishing between dissimilar locations like crop fields and forests, this algorithm consistently classifies more than 95 percent of points correctly. On more similar materials, more than 80 percent of points are classified correctly. This algorithm will allow for very accurate information to be extracted from these large and complicated hyperspectral images.