Neste trabalho, investigamos o controle coerente das bandas de emissão, excitadas via absorção multifotônica, em um cristal de óxido de Zinco (ZnO) através das formatação de pulsos laser ultracurtos (790 nm, 30 fs, 80 MHz e 5 nJ). O ZnO vem se mostrado um possível candidato a dispositivos fotônicos devido a sua grande energia de ligação de éxciton (60 meV).Inicialmente, implementamos a montagem experimental do sistema de formatação de pulsos, bem como de excitação e coleta da fluorescência do ZnO. O controle coerente foi feito através de um programa baseado em um algoritmo genético (GA), também desenvolvido no transcorrer deste trabalho. Através do algoritmo genético, observamos um ganho significativo da emissão do ZnO por meio de fases espectrais impostas ao pulso laser. Monitorando o traço de autocorrelação do pulso, inferimos que este se torna mais longo após a otimização das bandas de emissão via GA. Além disso, verificamos que as funções de fase que otimizam o processo são complexas e oscilatórias. Através da análise das componentes principais (PCA), fizemos uma análise do conjunto de dados providos pelo GA, onde observamos que este método pode ser usado como um filtro para os dados, suavizando as curvas e enfatizando os aspectos mais importantes das máscaras de fase obtidas pelo controle coerente. Por fim investigamos qual a importância das máscaras suavizadas para o entendimento físico do processo. / In this work, we investigate the coherent control of the emission bands, excited via multiphoton absorption, in a zinc oxide crystal (ZnO) by pulse shaping ultrashort laser pulses (790 nm, 30 fs, 5 nJ and 80 MHz). ZnO has been preposed as a potential material for photonic devices due to its strong exciton binding energy(60 meV). Initially, we have implemented the pulse shaper experimental setup, as well as the fluorescence measurements of ZnO. The coherent control was carried out through genetic algorithm (GA) based software, also developed in the course of this work. Using the genetic algorithm, we have observed a significant increase in the ZnO emission when appropriated spectral phase masks are applied to the laser pulse. Autocorrelation measurements were used to infer the pulse duration, which get longer after optimization of the emission band via GA. Additionally, we have found that the phase masks that optimize the process are complex oscillatory functions. Through the Principal Component Analysis, we analyzed the data provided by the GA and observed that it can be used to filter the data, smoothing the curves and highlighting the most important aspects of phase masks obtained by the coherent control. Finally we investigate how important the smoothed masks are for the physical understanding of the process.

Este trabalho análise as ocorrências de 12 classes de substâncias (monoterpenos, sesquiterpenos, lactonas sesquiterpênicas, diterpenos, triterpenos, cumarinas, flavonóides, poliacetilenos, benzofuranos, benzopiranos, acetofenonas e fenilpropanóides) na família Asteraceae e na sua tribo Heliantheae. Pretende-se demonstrar a existência de correlações na produção de metabólitos secundários em níveis taxonômicos baixos (tribos, subtribos e gêneros). Utilizou-se um banco de dados com cerca de 36.000 ocorrências das principais substâncias isoladas em plantas da família. O estudo do equilíbrio químico na produção de metabólitos secundários foi feito utilizando-se Regressão Linear Múltipla. As afinidades entre os grupos com base na sua Química foram pesquisadas por vários métodos tais como: Análise de componentes principais, Análise de Cluster e Análises cladísticas. Observou-se também o grau de oxidação médio de vários metabólitos e sua utilidade como ferramenta em análises quimiotaxonômicas. Foi possível mostrar a existência de um equilíbrio na produção das 12 classes de metabólitos em níveis das tribos e subtribos. Mas, no nível dos gêneros um equilíbrio moderado foi encontrado. Também foi possível mostrar a existência de um equilíbrio oxidativo em vários níveis (tribos, subtribos). No nível dos gêneros nenhum equilíbrio foi encontrado utilizando-se o parâmetro passo oxidativo. Foi possível agrupar algumas das subfamílias de Asteraceae segundo Bremer e subtribos da tribo Heliantheae segundo Stuessy usando Análises de componentes principais e Análise de Cluster / This work analyse the occurrence of 12 classes of substances (monoterpenes, sesquiterpenes, sesquiterpene lactones, diterpenes, triterpenes, coumarins, flavonoids, polyacetylenes, Benzofurans, benzopyrans, acetophenones and phenylpropanoids) in the Asteraceae family and its Heliantheae tribe. This study intends to demonstrate the existence of correlations in the production of secondary metabolites in lower taxonomic levels (tribes, subtribes and genera). We used a database of about 36,000 occurrences of the main substances isolated from the plant family. The study of chemical equilibrium in the production of secondary metabolites was done using Multiple Linear Regression. The affinities between the groups based on their chemistry were investigated by various methods such as principal component analysis, Cluster and cladistic analysis. There was also the average degree of oxidation of various metabolites and their usefulness as a tool in chemotaxonomic analysis. It was possible to show the existence of a balance in the production of 12 classes of metabolites in the levels of the tribes and subtribes. But the level of the genus balance was found moderate. It was also possible to show the existence of an oxidative equilibrium in various levels (tribes, subtribes). The level of genus balance was not found using the parameter oxidation step. We could group some of the subfamilies of Asteraceae according to Bremer and the subtribes of Heliantheae according to Stuessy using the principal component analysis and Cluster Analysis

Made available in DSpace on 2014-08-20T13:25:40Z (GMT). No. of bitstreams: 1 Tese_Ana_Paula_Pereira_ Schunemann.pdf: 1246057 bytes, checksum: c60b8be4e7e8bac211613fe410545012 (MD5) Previous issue date: 2009-07-24 / The objective of this study was to evaluate the effect of controlled atmosphere (CA) on the physico-chemical and sensory quality strawberry Camarosa‟ and peach 'Eldorado', produced under conventional (CS) and organic (OS) system during the storage. We applied the statistical technique of principal component analysis (PCA) between the sensory variables in strawberry Camarosa‟ and peach 'Eldorado', to select the variables most representative of the variability of the data and characterize homogeneous groups of samples as storage system under refrigeration or under different conditions of CA and production system SC and SO. The strawberries were stored at a temperature of 1.5 º C RH 90-95%, and made the following treatments: cold storage (CS) - 21% O2 and 0.03% CO2, 4% O2 + 5% CO2 (AC1) 4% O2 + 10% CO2 (AC2). The fruits were kept under storage for a period of 3, 6 and 9 days to 1.5 ° C plus one day of simulated commercialization (SC) at 20 ° C. The peaches were stored at a temperature of 1.5 º C relative humidity of 90-95%, and made the following treatments: control 21% O2 + 0.03% CO2 (AR), 2% O2 + 5% CO2 (AC1), 2% O2 + 10% CO2 (AC2), 2% O2 + 15% CO2 (AC3). The fruits were stored for a period of 15, 30 and 45 days at 1.5 ° C over three days in SC at 20 ° C. A completely randomized design was used for the physic-chemical analyzes, and for the sensory analysis a randomized block design; each judger was considered as a replication. Data were submitted to analysis of variance, and for mean comparison it was applied the Tukey test (P <0.05). AC with 4% O2 and 5% CO2 was effective in preserving the physical, chemical and sensory strawberries Camarosa‟ up to nine days + one day of the SC produced an CS and up to 6 days to the OS. Using cold AR be stored up to this period was lower, without significant losses in firmness, weight loss and significant changes in the attributes of appearance, flavor and texture. The fruits stored in AR In peaches 'Eldorado', in general, the fruit was change the characteristics of flavor, texture and appearance, and the treatments containing 2% O2 and 10% CO2 and 2% O2 and 15% CO2 preserved the physical-chemical and sensory up to 30 days in CS and 15 days in the OS. In AR this period was less than 15 days, without significant losses in sensory quality. Furthermore, the 45 days treatments were altered would not permit evaluation of flavor. The PCA was valid to discriminate the proxy variables and characterize homogeneous groups. / O objetivo do trabalho foi avaliar o efeito de condições de atmosfera controlada (AC) sobre a qualidade físico-química e sensorial de morango Camarosa‟ e pêssego Eldorado‟, produzidos em sistema convencional (SC) e orgânico (SO), durante o período de armazenamento. Aplicou-se a técnica estatística de análise dos componentes principais (ACP), entre as variáveis sensoriais em morango Camarosa‟ e pêssego Eldorado‟, para selecionar as variáveis mais representativas da variabilidade dos dados e caracterizar grupos homogêneos de amostras conforme sistema de armazenamento, sob refrigeração (AR) ou sob diferentes condições de AC e sistema de produção SC e SO. Os morangos foram armazenados a temperatura de 1,5ºC UR de 90-95%, sendo realizados os seguintes tratamentos: armazenamento refrigerado (AR) - 21 % O2 e 0,03 % CO2, 4 % O2 + 5 % CO2 (AC1), 4 % O2 + 10 % CO2 (AC2). As frutas foram armazenadas por um período de 3, 6 e 9 dias a 1,5°C mais um dia de simulação de comercialização (SC) em temperatura de 20°C. Os pêssegos foram armazenados a temperatura de 1,5ºC umidade relativa de 90-95%, sendo realizados os tratamentos: controle 21 % O2 + 0,03 % CO2 (AR), 2 % O2 + 5 % CO2 (AC1), 2 % O2 + 10 % CO2 (AC2), 2 % O2 + 15 % CO2 (AC3). As frutas foram armazenadas por um período de 15, 30 e 45 dias a 1,5°C mais três dias de SC em temperatura de 20°C. O delineamento experimental utilizado para as análises físico-químicas foi inteiramente casualizado e para análise sensorial blocos ao acaso, sendo cada julgador uma repetição. Os dados foram submetidos à análise de variância e para comparação das médias, foi aplicado o teste de Tukey (P<0,05). A AC com 4% de O2 e 5% de CO2 foi eficiente na preservação das características físico-químicas e sensorial de morangos Camarosa‟ em até nove dias + um de comercialização produzidos em SC e até 6 dias para o SO. As frutas armazenadas em AR, este período foi inferior, pois ocorrem perdas significativas na firmeza, perda de massa e alterações significativa nos atributos de aparência, sabor e textura. Em pêssegos Eldorado‟, em geral, as frutas apresentaram alteração nas características de sabor, textura e aparência, sendo que os tratamentos contendo 2% O2 e 10% CO2 e 2% O2 e 15% CO2 preservaram a qualidade físico-química e sensorial até os 30 dias no SC e até 15 dias no SO. Em AR este período foi inferior a 15 dias, pois ocorrem perdas significativas na qualidade sensorial. Além disso, aos 45 dias os tratamentos apresentaram-se alterados impossibilitando a avaliação de sabor. A ACP foi válida para discriminar as variáveis representativas e caracterizar grupos homogêneos.

Este trabalho apresenta os resultados obtidos com o desenvolvimento de um sistema robusto como uma alternativa de reconhecimento da qualidade de vapor de álcool combustível e do poder calorífico do gás combustível GLP em um nariz eletrônico. Foram implementadas duas metodologias experimentais para a extração de atributos dos padrões de vapor de álcool combustível e de gás GLP. Na primeira abordagem de tratamento dos dados, foram usados um Sistema de Inferência Fuzzy (FIS), e dois algoritmos de treinamento de Redes Neurais Artificiais (RNA) para reconhecer padrões de vapor de álcool combustível: a Backpropagation e Learning Vector Quantization. A segunda abordagem para o tratamento dos dados foi desenvolver um sistema reconhecedor do poder calorífico do gás GLP robusto à perda aleatória de um dos sensores. Foram usados três sistemas. No primeiro foi implementada uma RNA para reconhecer todos os dados que simulavam a falha de um sensor aleatório. O resultado desse sistema foi de 97% de acertos. O segundo implementou sete RNA’s treinadas com subconjuntos dos dados de entrada, tais que seis RNA’s foram treinadas com um sensor diferente com falha; e a sétima RNA foi treinada com dados dos sensores sem falhas. O resultado desse sistema foi de 99% de acertos. O terceiro implementou uma Máquina de Comitê Estática Ensemble constituída de dez RNA’s em paralelo para resolver o problema. O resultado foi de 97% de acertos. As RNA’s tiveram melhores respostas que os FIS. Foram sugeridas algumas formas de implementação em hardware do sistema reconhecedor em sistemas pré-fabricados com DSP’s e micro-controladores. / This work shows the results of a robust system development as an alternative to recognize the quality of an alcohol fuel vapor sample and Liquid Petrol Gas (LPG) heat power in an electric nose. Two experimental methodologies were implemented to extract the features of alcohol fuel vapor and LPG gas patterns. The first approach to process the data used an Fuzzy Inference System (FIS) and two training algorithms of Artificial Neural Networks (ANN) to recognize alcohol fuel vapor patterns: Backpropagation and Learning Vector Quantization. The second approach consists of process data to develop an LPG heat power recognizing system robust to one-random-sensor-loss. Three systems were used. The first implemented an ANN to recognize all data that simulated the failure of a random sensor. This system had 97% of right responses. The second implemented seven ANN’s trained with input data subsets, such that six ANN’s were trained with a different failure sensor, and the seventh ANN was trained with data of all sensors without failure. This system had 99% of right responses. The third implemented an Ensemble Static Learning Machine containing ten parallel RNA’s to solve the problem. The result were 97% of right responses. RNA’s had better results than FIS. Some ways of hardware implementation of the recognizing system were suggested in DSP and micro-controllers pre-built systems.

Accurate information about tree volume in tropical vegetation formations is critical for the identification of potential areas for sustainable timber production, carbon estimation and biodiversity conservation. Difficult access and the cost of obtaining a large number of samples needed for accurate wood volume and biomass determination are often barriers for carrying out inventories and studies in natural forests in Brazil. Therefore, the development of more efficient techniques of mensuration in tropical forests is an important mechanism for conservation, management and production advancement. The main purposes of this thesis are: introducing a new method for quantifying vertical and horizontal structures by using principal component analysis (PCA); developing two different approaches of volume modeling, one based on DBH and another based on crown area; proposing a new taper equation for native vegetation in three different formations; and estimating upper section diameters to become the geometric form method useful in natural vegetation in Brazil and reducing dependence on destructive measurements. / Informações corretas sobre o volume de árvores em formações de vegetação natural são fundamentais para a identificação de áreas potenciais para produção madeireira sustentável, estimativa de carbono e conservação da biodiversidade. Dificuldade de acesso e altos custos na obtenção de amostras necessárias para estimativas precisas de volume e biomassa são barreiras frequentes na condução de inventários e estudos florestais no Brasil. Dessa forma, o desenvolvimento de técnicas mais eficientes de mensuração em florestas tropicais é um importante mecanismo para o avanço da conservação, manejo e produção. Os principais objetivos deste trabalho foram: introduzir um novo método de quantificação das estruturas vertical e horizontal por meio do uso de análise de componentes principais (ACP); desenvolver modelos volumétricos baseados em DAP e modelos baseados em área de copa; propor uma nova função de afilamento aplicada a três diferentes formações vegetais; e estimar alturas em que deverão ter diâmetros medidos ao longo da árvore para tornar o método geométrico útil em formações naturais no Brasil, e reduzindo a necessidade de mensurações que requerem o abatimento das árvores.

Submitted by Neusa Fagundes (neusa.fagundes@unioeste.br) on 2017-09-18T14:32:46Z No. of bitstreams: 1 Alan_Gavioli2017.pdf: 4935513 bytes, checksum: 58816f2871fee27474b2fd5e511826af (MD5) / Made available in DSpace on 2017-09-18T14:32:46Z (GMT). No. of bitstreams: 1 Alan_Gavioli2017.pdf: 4935513 bytes, checksum: 58816f2871fee27474b2fd5e511826af (MD5) Previous issue date: 2017-02-17 / Two basic activities for the definition of quality management zones (MZs) are the variable selection task and the cluster analysis task. There are several methods proposed to execute them, but due to their complexity, they need to be made available by computer systems. In this study, 5 methods based on spatial correlation analysis, principal component analysis (PCA) and multivariate spatial analysis based on Moran’s index and PCA (MULTISPATI-PCA) were evaluated. A new variable selection algorithm, named MPCA-SC, based on the combined use of spatial correlation analysis and MULTISPATI-PCA, was proposed. The potential use of 20 clustering algorithms for the generation of MZs was evaluated: average linkage, bagged clustering, centroid linkage, clustering large applications, complete linkage, divisive analysis, fuzzy analysis clustering (fanny), fuzzy c-means, fuzzy c-shells, hard competitive learning, hybrid hierarchical clustering, k-means, McQuitty’s method (mcquitty), median linkage, neural gas, partitioning around medoids, single linkage, spherical k-means, unsupervised fuzzy competitive learning, and Ward’s method. Two computational modules developed to provide the variable selection and data clustering methods for definition of MZs were also presented. The evaluations were conducted with data obtained between 2010 and 2015 in three commercial agricultural areas, cultivated with soybean and corn, in the state of Paraná, Brazil. The experiments performed to evaluate the 5 variable selection algorithms showed that the new method MPCA-SC can improve the quality of MZs in several aspects, even obtaining satisfactory results with the other 4 algorithms. The evaluation experiments of the 20 clustering methods showed that 17 of them were suitable for the delineation of MZs, especially fanny and mcquitty. Finally, it was concluded that the two computational modules developed made it possible to obtain quality MZs. Furthermore, these modules constitute a more complete computer system than other free-to-use software such as FuzME, MZA, and SDUM, in terms of the diversity of variable selection and data clustering algorithms. / A seleção de variáveis e a análise de agrupamento de dados são atividades fundamentais para a definição de zonas de manejo (ZMs) de qualidade. Para executar essas duas atividades, existem diversos métodos propostos, que devido à sua complexidade precisam ser executados por meio da utilização de sistemas computacionais. Neste trabalho, avaliaramse 5 métodos de seleção de variáveis baseados em análise de correlação espacial, análise de componentes principais (ACP) e análise espacial multivariada baseada no índice de Moran e em ACP (MULTISPATI-PCA). Propôs-se um novo algoritmo de seleção de variáveis, denominado MPCA-SC, desenvolvido a partir da aplicação conjunta da análise de correlação espacial e de MULTISPATI-PCA. Avaliou-se a viabilidade de aplicação de 20 algoritmos de agrupamento de dados para a geração de ZMs: average linkage, bagged clustering, centroid linkage, clustering large applications, complete linkage, divisive analysis, fuzzy analysis clustering (fanny), fuzzy c-means, fuzzy c-shells, hard competitive learning, hybrid hierarchical clustering, k-means, median linkage, método de McQuitty (mcquitty), método de Ward, neural gas, partitioning around medoids, single linkage, spherical k-means e unsupervised fuzzy competitive learning. Apresentaram-se ainda dois módulos computacionais desenvolvidos para disponibilizar os métodos de seleção de variáveis e de agrupamento de dados para a definição de ZMs. As avaliações foram realizadas com dados obtidos entre os anos de 2010 e 2015 de três áreas agrícolas comerciais, localizadas no estado do Paraná, nas quais cultivaram-se milho e soja. Os experimentos efetuados para avaliar os 5 algoritmos de seleção de variáveis mostraram que o novo método MPCA-SC pode melhorar a qualidade de ZMs em diversos aspectos, mesmo obtendo-se resultados satisfatórios com os outros 4 algoritmos. Os experimentos de avaliação dos 20 métodos de agrupamento citados mostraram que 17 deles foram adequados para o delineamento de ZMs, com destaque para fanny e mcquitty. Por fim, concluiu-se que os dois módulos computacionais desenvolvidos possibilitaram a obtenção de ZMs de qualidade. Além disso, esses módulos constituem uma ferramenta computacional mais abrangente que outros softwares de uso gratuito, como FuzME, MZA e SDUM, em relação à diversidade de algoritmos disponibilizados para selecionar variáveis e agrupar dados.

The plumage colour and patterns of birds have interested biologists for a long time.Why are some bird species all black while others have a multitude of colours? Does ithave anything to do with sexual selection, predator avoidance or social signalling?Many questions such as these have been asked and as many hypotheses about thefunctional role of the plumage have been formed. The problem, however, has been toprove any of these. To test these hypotheses you need to analyse the bird plumagesand today such analyses are still rather subjective. Meaning the results could varydepending on the individual performing the analysis. Another problem that stemsfrom this subjectiveness is that it is difficult to make quantitative measurements of theplumage colours. Quantitative measurements would be very useful since they couldbe related to other statistical data like speciation rates, sexual selection and ecologicaldata. This thesis aims to assist biologists with the analysis and measurement of birdplumages by developing a MATLAB toolbox for this purpose. The result is a wellstructured and user friendly toolbox that contains functions for segmenting, resizing,filtering and warping, all used to prepare the images for analysis. It also containsfunctions for the actual analysis such as basic statistical measurements, principalcomponent analysis and eigenvector projection.

Les modèles humains numériques sont devenus des outils indispensables à l’étude de la posture est du mouvement dans de nombreux domaines de la biomécanique visant des applications en ergonomie ou pour la clinique. Ces modèles intègrent une représentation géométrique de la surface du corps et un squelette filaire interne composé de segments rigides et d’articulations assurant leur mise en mouvement. La personnalisation des mannequins s'effectue d’abord sur les dimensions anthropométriques externes, servant ensuite de données d’entrée à l’ajustement des longueurs des segments du squelette en interne. Si les données externes sont de plus en plus facilement mesurables à l’aide des outils de scanning 3D actuels, l’enjeu scientifique est de pouvoir prédire des points caractéristiques du squelette en interne à partir de données uniquement externes. L’Institut de Biomécanique Humaine Georges Charpak (Arts et Métiers ParisTech) a développé des méthodes de reconstruction des os et de l’enveloppe externe à partir de radiographies biplanes obtenues avec le système basse dose EOS. En s’appuyant sur cette technologie, ces travaux ont permis de proposer de nouvelles relations statistiques externes-internes pour prédire des points du squelette longitudinal, en particulier l’ensemble des centres articulaires du rachis, à partir d’une base de données de 80 sujets. L'application de ce travail pourrait permettre d’améliorer le réalisme des modèles numériques actuels en vue de mener des analyses biomécaniques, principalement en ergonomie, nécessitant des informations dépendant de la position des articulations comme les mesures d’amplitude de mouvement et de charges articulaires / Digital human models have become instrumental tools in the analysis of posture and motion in many areas of biomechanics, including ergonomics and clinical settings. These models include a geometric representation of the body surface and an internal linkage composed of rigid segments and joints allowing simulation of human movement. The customization of human models first starts with the adjustment of external anthropometric dimensions, which are then used as input data to the adjustment of internal skeletal segments lengths. While the external data points are more readily measurable using current 3D scanning tools, the scientific challenge is to predict the characteristic points of the internal skeleton from external data only. The Institut de Biomécanique Humaine Georges Charpak (Arts et Métiers ParisTech) has developed 3D reconstruction methods of bone and external envelope from biplanar radiographs obtained from the EOS system (EOS Imaging, Paris), a low radiation dose technology. Using this technology, this work allowed proposing new external-internal statistical relationships to predict points of the longitudinal skeleton, particularly the complete set of spine joint centers, from a database of 80 subjects. The implementation of this work could improve the realism of current digital human models used for biomechanical analysis requiring information of joint center location, such as the estimation of range of motion and joint loading

Spectral methods have become increasingly popular in designing fast algorithms for modern highdimensional datasets. This thesis looks at several problems in which spectral methods play a central role. In some cases, we also show that such procedures have essentially the best performance among all randomised polynomial time algorithms by exhibiting statistical and computational trade-offs in those problems. In the first chapter, we prove a useful variant of the well-known Davis{Kahan theorem, which is a spectral perturbation result that allows us to bound of the distance between population eigenspaces and their sample versions. We then propose a semi-definite programming algorithm for the sparse principal component analysis (PCA) problem, and analyse its theoretical performance using the perturbation bounds we derived earlier. It turns out that the parameter regime in which our estimator is consistent is strictly smaller than the consistency regime of a minimax optimal (yet computationally intractable) estimator. We show through reduction from a well-known hard problem in computational complexity theory that the difference in consistency regimes is unavoidable for any randomised polynomial time estimator, hence revealing subtle statistical and computational trade-offs in this problem. Such computational trade-offs also exist in the problem of restricted isometry certification. Certifiers for restricted isometry properties can be used to construct design matrices for sparse linear regression problems. Similar to the sparse PCA problem, we show that there is also an intrinsic gap between the class of matrices certifiable using unrestricted algorithms and using polynomial time algorithms. Finally, we consider the problem of high-dimensional changepoint estimation, where we estimate the time of change in the mean of a high-dimensional time series with piecewise constant mean structure. Motivated by real world applications, we assume that changes only occur in a sparse subset of all coordinates. We apply a variant of the semi-definite programming algorithm in sparse PCA to aggregate the signals across different coordinates in a near optimal way so as to estimate the changepoint location as accurately as possible. Our statistical procedure shows superior performance compared to existing methods in this problem.

La préservation de la richesse aquatique est devenue un souci majeur d'ordre mondial suite au risque de pénurie en eau. Au Liban, les rejets anthropiques incontrôlés et incontrôlables au bord des rivières menacent la qualité de ses eaux de surface. Pour cela, quatre cours d'eau libanais ont été choisis comme cadre d'étude : la rivière Damour, la rivière Kadisha-Abou Ali, la rivière Ibrahim et la rivière Oronte.Les différents paramètres physico-chimiques et microbiologiques étudiés ont permis dans un premier temps la construction d'une base de données de chacune de ces rivières. Une seule analyse spatio-temporelle des paramètres séparément n'aide pas à définir l'état trophique des rivières. Partant de l'idée des corrélations que peuvent exister entre certains paramètres, l'Analyse en Composante Principale (ACP) retenant la totalité de l'information sera utilisée en dépit des méthodes classiques. Cet outil statistique a permis de classer les rivières par niveau de pollution. Il a aussi aidé à observer l'impact des apports des polluants sur les différentes stations de rivières étudiées.Pour suivre le devenir des coliformes fécaux dans les eaux, l'ACP des variables microbiologiques a montré la persistance des colonies bactériennes dans les eaux malgré les conditions climatiques diverses et le régime méditerranéen torrentiel des rivières. En effet, les sédiments constituent des réservoirs potentiels de microorganismes pathogènes. Le décrochage bactérien des agrégats sédimentaires et la remise en suspension dans l'eau pose un problème alarmant de santé publique. / Preservation of aquatic wealth has worldwide become a major concern due to the risk of water shortage. In Lebanon, uncontrolled and uncontrollable anthropogenic rejections along rivers threaten the quality of its surface waters. Four Lebanese rivers were selected as study framework: The Damour river, Kadisha-Abu Ali river, Ibrahim river and Orontes river. The physico-chemical and microbiological parameters analyzed has formed a large database of these rivers. The spatio-temporal analysis of separate parameters did not help defining the trophic status of rivers. The assumption that correlations exist between certain parameters, guides us to use the Principal Component Analysis (PCA) in spite of conventional methods. This statistical tool was used to define the pollution levels in rivers. It also leads to observe the impact of pollutants inflows on different sites studied. To follow the fate of fecal coliform in water, the ACP of microbiological variables showed the persistence of bacterial colonies in water despite the various climatic conditions and the Mediterranean flow rate. Indeed, sediments are potential reservoirs of pathogenic microorganisms. The bacteria aggregated to the sediment can be present again in water column causing an alarming public health problem.