Made available in DSpace on 2014-06-12T15:56:15Z (GMT). No. of bitstreams: 2 arquivo2793_1.pdf: 1387248 bytes, checksum: e99d52780679d746f07f5ff17549301a (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / É crescente a necessidade de controle de acesso a lugares, serviços e informações. É crescente também a busca por soluções mais eficientes na identificação pessoal. Neste contexto, a biometria, que consiste no uso de características biológicas como mecanismo de identificação, tem sido utilizada com resultados bastante promissores. Dentre as informações utilizadas para identificação dos indivíduos podem ser destacadas a íris, a retina, a face, a impressão digital ou até mesmo a geometria da mão. Dentre as biometrias, o reconhecimento de faces destaca-se por ser uma técnica que apresenta ótimos resultados com baixo custo de implantação. Ela pode ser utilizada nos mais diversos tipos de dispositivos e, em sua forma mais simples, não exige hardware dedicado. A técnica destaca-se ainda por não necessitar da interação do usuário ou qualquer tipo de contato físico para captura e classificação das faces. O presente trabalho é focado no reconhecimento de faces baseado em imagens (2D). Mais precisamente o trabalho visa reduzir ou eliminar os efeitos de variações no ambiente ou na própria face que prejudiquem a sua classificação final. As técnicas examinadas e propostas fazem uso da análise de componentes principais (PCA) para extração de características das imagens de faces frontais. Elas baseiam-se em estudos recentes com o objetivo de melhorar as taxas de classificação mesmo sob condições adversas de aquisição de imagens ou oclusão parcial das faces. Os resultados obtidos mostraram uma superioridade nas taxas de acerto das abordagens propostas em relação às suas técnicas-base quando executadas sobre imagens com algum tipo de variação local. Foi constatado também um grande ganho no tempo de processamento das imagens, o que contribui para aplicar as técnicas propostas em dispositivos com menor capacidade computacional

O objetivo deste trabalho é investigar a relação entre a Temperatura da Superfície do Mar (TSM) no Oceano Atlântico Sul (OAS) e a precipitação no estado de São Paulo. Para tanto, adotaram-se as escalas mensal e sazonal. A técnica estatística multivariada, chamada Análise de Componentes Principais (ACP, ou EOF em inglês) foi aplicada para definir as áreas homogêneas do oceano (de \'A\' a \'L\') e as subregiões do continente (de 1 a 7). Além da definição das áreas e sub-regiões, a ACP identificou muito bem os padrões espaciais da precipitação e da TSM em todas as escalas adotadas: mensal contínua, mensal descontínua e sazonal. Na ACP da série temporal sazonal de verão, o primeiro e o segundo modos da precipitação evidenciam a distribuição espacial típica de verão (zonal) para o estado de São Paulo, e a variância explicada por esses dois modos juntos é de 59,79% do total. Esta distribuição espacial já havia sido observada nas análises iniciais a partir das médias sazonais da precipitação, padrão que se explica pelos fluxos de umidade que, nesta estação, devido ao sistema de monções da América do Sul, movem-se mais intensamente em direção ao continente. Já na ACP da série temporal sazonal de inverno, o primeiro e segundo modos da precipitação evidenciam a distribuição meridional, com variância explicada de 39,15 e 17,77%, respectivamente. Os sistemas frontais no inverno agem como responsáveis por uma parcela considerável do total precipitado, o que explica o padrão meridional da chuva. Os coeficientes de correlação linear significativos entre as áreas oceânicas e sub-regiões continentais homogêneas demonstraram que a variabilidade sazonal da precipitação está associada à TSM, sobretudo na porção central da área estudada (próximo ao litoral sul e sudeste do Brasil), nas estações seca (abril a setembro) e chuvosa (outubro a março). Além das variáveis principais (precipitação e TSM), os campos de Radiação de Onda Longa Emergente (ROLE), Pressão no nível do Mar (PNM), e Divergência do ar em 250 e 850hPa auxiliaram na identificação dos padrões atmosféricos e na análise dos eventos extremos. As estações consideradas atípicas, ou seja, as que apresentaram média muito acima ou muito abaixo do desvio padrão, foram separadas em quatro classes: verão chuvoso, verão seco, inverno chuvoso e inverno seco. A partir da análise desses eventos, conclui-se então que a TSM do OAS pode alterar consideravelmente o padrão sazonal de precipitação no estado de São Paulo, principalmente se estiver atrelada a padrões atmosféricos. No inverno, anomalias negativas (positivas) de TSM estão associadas com a precipitação acima (abaixo) da média climatológica nesse estado. Devido a bloqueios atmosféricos no OAS no verão, a diminuição da passagem de sistemas frontais pode intensificar anomalias positivas no oceano, as quais estão associadas aos períodos chuvosos no sul do país e de seca no estado de São Paulo. / The purpose of this paper is to study the relationship between the Sea Surface Temperature (SST) in the South Atlantic Ocean (SAO) and the precipitation in São Paulo state. So, the monthly and seasonal scales were adopted. The Principal Component Analysis multivariate statistic technic (PCA, and also called EOF) was applied to define the oceans homogeneous areas (from A to L) and the continents sub-regions (from 1 to 7). Besides defining the areas and sub-regions, the PCA has identified very well the spatial patterns of the precipitation and SST in all the adopted scales: continuous monthly, discontinuous monthly and seasonal. In the PCA of the summer seasonal temporal series, the first and the second precipitations mode evidence the summer-typical spatial distribution (zonal) for São Paulo state, and the variance explained by these two modes together is 59,79% of the total. This spatial distribution was already noted in the first analysis from the seasonal precipitation averages, and such a pattern is explained by the flow of humidity, which in the summer, owing to the South America monsoon systems, move more intensely toward the continent. On the other hand, in the PCA of the winter seasonal temporal series, the first and the second precipitations modes evidence the meridional distribution, with a variance explained from 39,15 to 17,77%, respectively. The frontal systems in the winter act as responsibles for a substantial portion of the total of precipitation, which explains the rains meridional pattern. The significative linear correlation coefficients between the oceanic areas and the homogeneous continental sub-regions demonstrate that the precipitations seasonal variability is associated to the SST, mostly in the central portion of the studied area (next to the southern and southeastern Brazilian coast), in the drought season (from April to September) and rainy season (from October to March). Besides the principal variables (precipitation and SST), the fields of Outgoing Long wave Radiation (OLR), Sea-level Pressure (SLP) and air Divergence in 250 and 850hPa has helped to identify the atmospheric patterns and to analyze the extreme events. The atypical seasons, in other words, those which presented an average too high or too low compared to the standard deviation, were divided in four categories: rainy summer, drought summer, rainy winter and drought winter. With the analysis of these events, it is possible to conclude that the SST of the SAO can change substantially the precipitation seasonal pattern in São Paulo state, mainly if it is linked to atmospheric patterns. In the winter, SSTs negative (positive) anomalies are associated to the overage (underage) climatologic precipitation in this state. Owing to atmospheric blockades on the SAO in the summer, the decreasing transit of frontal systems can intensify positive anomalies in the ocean, which are associated to the rainy periods in the Brazilian South and drought periods in the São Paulo state.

Made available in DSpace on 2017-07-10T17:48:26Z (GMT). No. of bitstreams: 1 Leslie_Defante.pdf: 812707 bytes, checksum: d92d4165f390781200d13f9907af6b34 (MD5) Previous issue date: 2011-07-29 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / In order to characterize the farms, by identifying characteristics of production, milk composition and influence of the management systems of hygiene and sanitary production of milk - SPL of the western region of Paraná State. A study was conducted in 23 SPL, with the collection of data from a semi-structured questionnaire guide and collection of samples of raw milk and cooled water reservoirs.. analyses were performed using physical-chemical (fat, protein, lactose, total solids) of somatic cell counting (SCC) and total bacterial counting (TBC). For microbiological tests were performed to determine the most probable number of total coliform and thermotolerant coliform by multiple tube method. We evaluated the differences found in production systems by means of multivariate statistical techniques, namely: multiple correspondence analysis (MCA), principal component analysis (PCA) and cluster analysis, the milk production and herd feeding management, milking management, reproductive management, disease control, and finally the marketing of milk. The variables that best explained the diversity of the systems were: the amount of milk produced, lactating cows, repetition of estrus, based on feed and milking practices, hygiene and mastitis test ceilings. While the high counts of CBT, CCS and the presence of total coliforms and thermotolerant in some dairy production systems have proved to be indicative of deficiencies in hygiene procedures for milking, cleaning and sanitizing of milking equipment, associated with inadequate cooling of milk. Delivering the decreased concentrations of the components fat, protein and total solids, causing changes in the quality of milk and dairy products. The typology of production systems allowed to portray the diversity in the organization and manner of production, enabling the simplification of the universe of producers, allowing us to tailor production strategies, managing and improving the quality of milk for each system / Objetivou-se avaliar as características de 23 sistemas de produção de leite (SPL) na região Oeste do Estado do Paraná. O levantamento das características de produção, composição e qualidade do leite e do manejo higiênico-sanitário foi obtido pela coleta de dados a partir de um questionário guia semi-estruturado e pela coleta de amostras de leite de tanque e água de reservatórios. As amostras de leite foram analisadas quanto às características físico-químicas (gordura, proteína, lactose, sólidos totais), contagem de células somáticas, contagem bacteriana total e microbiológicas no leite. Para as análises microbiológicas foram realizadas a determinação do número mais provável de coliformes totais e coliformes termotolerantes pelo método de tubos múltiplos. Posteriormente, as diversidades encontradas nos SPL foram analisadas por meio de técnicas estatísticas multivariadas: análise de correspondências múltiplas (ACM), análise de componentes principais (ACP) e análise de cluster; quanto a produtividade do rebanho, manejo alimentar, manejo de ordenha, manejo reprodutivo, controle sanitário, e por último a comercialização do leite. As variáveis que melhor explicaram as diversidades dos SPL foram: a quantidade de leite produzido, o número de vacas lactantes, repetição de cio, base forrageira e as práticas de ordenha (teste de mastite e higienização dos tetos). Enquanto que elevados valores de CBT, CCS e presença de coliformes totais e termotolerantes em alguns SPL demonstraram ser um indicativo de deficiência nos procedimentos de higiene na ordenha, na limpeza e sanitização dos equipamentos de ordenha. Isso proporcionou uma a diminuição das concentrações dos componentes gordura, proteína e sólidos totais, ocasionando alterações na qualidade do leite. A tipologia dos sistemas de produção permitiu retratar a diversidade existente na organização e na forma de produção, possibilitando a simplificação do universo dos produtores, e a adequação de estratégias de produção, gestão e melhoria da qualidade do leite para cada sistema

Made available in DSpace on 2017-07-10T17:48:30Z (GMT). No. of bitstreams: 1 Ilton_Isandro_Eckstein.PDF: 1269135 bytes, checksum: 52bc33a50ce148953b29202d47265022 (MD5) Previous issue date: 2012-03-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Knowing the factors that affect the composition and quality of milk in Dairy Production Systems (SPL) is of utmost importance to the producer. The objective was to evaluate the characteristics of 32 SPL in the city of Toledo, together in partnership with a dairy. We performed the data collection of properties, with the aid of a semi-structured questionnaire, which collected information on the production traits, milk composition and quality, besides the technical and management practices carried out, mainly related to hygiene and management health of milking. Milk samples were analyzed for their composition (fat, protein, lactose and total solids), Somatic Cell Count (SCC), Total Bacterial Count (TBC), and also to the presence of total coliforms and fecal coliforms. Subsequently, data collection, the variables were selected and analyzed using multivariate techniques, using the principal component analysis (PCA) and analysis of Ascendant Hierarchical Classification (AHC). We analyzed variables related to production and milk quality, techniques and practices used at the time of milking, feeding management, milking system and socio-cultural variables related to the producer. The variables that best explained the differences in the PCA were related to the hygienic and sanitary practices (pre and post-dipping, use of detergents in alkaline and acid cleaning, testing for mastitis) held for milking, with the composition of milk and linked to the producer (age, education, length of service). It was found that the use of these practices can help to improve production and milk quality, ensuring a raw material with high commercial value. The grouping of production systems has shown that there is great diversity among the forms of production, allowing identifying the factors that can influence it, in order to form strategies that may result from gains in production and milk quality / Conhecer os fatores que afetam a composição e qualidade do leite em Sistemas de Produção Leiteiros (SPL) é de extrema importância ao produtor. Objetivou-se avaliar as características de 32 SPL, na cidade de Toledo, juntamente em parceria com um laticínio. Foi realizada a coleta de dados das propriedades, com o auxílio de um questionário semi-estruturado, onde se colheu informações acerca das características de produção, composição e qualidade do leite, além das técnicas e práticas de manejo realizadas, principalmente relacionadas ao manejo higiênico-sanitário de ordenha. As amostras de leite foram analisadas em relação a sua composição (gordura, proteína, lactose e sólidos totais), Contagem de Células Somáticas (CCS), Contagem Bacteriana Total (CBT), e também para presença de coliformes totais e coliformes termotolerantes. Posteriormente, a coleta de dados, as variáveis foram selecionadas e analisadas por meio de técnicas multivariadas, sendo utilizada a análise de Componentes Principais (ACP) e a análise de Classificação Hierárquica Ascendente (CHA). Foram analisadas variáveis relacionadas à produção e qualidade do leite, técnicas e práticas utilizadas no momento da ordenha, manejo alimentar, sistema de ordenha e variáveis sócio-culturais relacionadas ao produtor. As variáveis que melhor explicaram as diversidades das ACP foram as relacionadas com as práticas higiênico-sanitária (pré e pós-dipping, utilização dos detergentes alcalino e ácido na higienização, testes para detecção de mastite) realizadas na ordenha, com a composição de leite e vinculadas ao produtor (idade, escolaridade, tempo na atividade). Foi verificado que o uso destas práticas podem auxiliar para melhorar a produção e qualidade do leite, assegurando uma matéria-prima com maior valor comercial. O agrupamento dos sistemas de produção permitiu verificar a existência de grande diversidade entre as formas de produção, possibilitando identificar os fatores que podem influenciá-lo, a fim de formar estratégias que possam resultar ganhos em produção e qualidade do leite

With the evolution in the game industry and other virtual environments, demands on what comes with an application is higher than ever before. This leads to many companies trying to to procedurally generate content in order to save up on storage space and get a wider variety of content. It has become essential to infuse immersion in such application and some companies has even gone as far as to let the player recreate him- or herself to be the hero or heroine of the game. Even so, many AAA companies refrain from using face segmentation software as it gives the power of adding game content by the end users, and that may lead to an increased risk of offensive content, that goes against company standards and policy, to enter their application. By taking the concept of procedural generation and applying this together with face segmentation, placing a Principal Component Analysis (PCA) based texturization model, we allow for a controlled yet functioning face texturization in a run-time virtual environment. In this project we use MatLab to create a controlled Eigen space, infuses this into an application built in Unity 3D using UMA, and lets smaller recreation vectors, that spans a few kilobytes as most, to create textures in run-time. In doing so, we can project faces onto the Eigen space and get fully functioning and texturized characters, able to use ready animations and controllers of the developer’s choice. These Eigen spaces may cost more storage space and loading times up to a limit, but can in turn generate a seemingly endless variation of textural content dynamically. In order to see what potential users prioritize when it comes to applications like these, we conducted a survey where the responders saw variations of this technique and were able to express their view on attributes expected from a “good” (from their point of view) application. In the end we have a UMA ready set of scripts, and a one-time use system to create Eigen spaces for the applications to use it. We worked in close relation with Högström’s Selfie to Avatar face segmentation software and proved the concept in Unity 3D applications.

This thesis investigates the possibility of improving black box fault diagnosis by a process called manifold learning, which simply stated is a way of finding patterns in recorded sensor data. The idea is that there is more information in the data than is exploited when using simple classification algorithms such as k-Nearest Neighbor and Support Vector Machines, and that this additional information can be found by using manifold learning methods. To test the idea of using manifold learning, data from two different fault diagnosis scenarios is used: A Scania truck engine and an electrical system called Adapt. Two linear and one non-linear manifold learning methods are used: Principal Component Analysis and Linear Discriminant Analysis (linear) and Laplacian Eigenmaps (non-linear).Some improvements are achieved given certain conditions on the diagnosis scenarios. The improvements for different methods correspond to the systems in which they are achieved in terms of linearity. The positive results for the relatively linear electrical system are achieved mainly by the linear methods Principal Component Analysis and Linear Discriminant Analysis and the positive results for the non-linear Scania system are achieved by the non-linear method Laplacian Eigenmaps.The results for scenarios without these special conditions are not improved however, and it is uncertain wether the improvements in special condition scenarios are due to gained information or to the nature of the cases themselves.

In modern biological research, OMICs techniques, such as genomics, proteomics or metabolomics, are often employed to gain deep insights into metabolic regulations and biochemical perturbations in response to a specific research question. To gain complementary biologically relevant information, multiOMICs, i.e., several different OMICs measurements on the same specimen, is becoming increasingly frequent. To be able to take full advantage of this complementarity, joint analysis of such multiOMICs data is necessary, but this is yet an underdeveloped area. In this thesis, a theoretical background is given on general component-based methods for dimensionality reduction such as PCA, PLS for single block analysis, and multiblock PLS for co-analysis of OMICs data. This is followed by a rotation of an unsupervised analysis method. The aim of this method is to divide dimensionality-reduced data in block-distinct and common variance partitions, using the DISCO-SCA approach. Finally, an algorithm for a similar rotation of a supervised (PLS) solution is presented using data available in the literature. To the best of our knowledge, this is the first time that such an approach for rotation of a supervised analysis in block-distinct and common partitions has been developed and tested.This newly developed DISCO-PLS algorithm clearly showed an increased potential for visualisation and interpretation of data, compared to standard PLS. This is shown bybiplots of observation scores and multiblock variable loadings.

We estimate the velocity field of the blood flow in a human face from videos. Our approach first performs spatial preprocessing to improve the signal-to-noise ratio (SNR) and the computational efficiency. The discrete Fourier transform (DFT) and a temporal band-pass filter are then applied to extract the frequency corresponding to the subjects heart rate. We propose multiple kernel based k-NN classification for removing the noise positions from the resulting phase and amplitude maps. The 2D blood flow field is then estimated from the relative phase shift between the pixels. We evaluate our approach about segmentation as well as velocity field on real and synthetic face videos. Our method produces the recall and precision as well as a velocity field with an angular error and magnitude error on the average.

This PhD thesis focuses on improving the limit of detection (LOD) of Raman biosensors by using surface enhanced Raman scattering (SERS) and/or hollow core photonic crystal fibers (HC-PCF), in conjunction with statistical methods. Raman spectroscopy is a multivariate phenomenon that requires statistical analysis to identify the relationship between recorded spectra and the property of interest. The objective of this research is to improve the performance of Raman biosensors using SERS techniques and/or HC-PCF, by applying partial least squares (PLS) regression and principal component analysis (PCA). I began my research using Raman spectroscopy, PLS analysis and two different validation methods to monitor heparin, an important blood anti-coagulant, in serum at clinical levels. I achieved lower LOD of heparin in serum using the Test Set Validation (TSV) method. The PLS analysis allowed me to distinguish between weak Raman signals of heparin in serum and background noise. I then focused on using SERS to further improve the LOD of analytes, and accomplished simultaneous detection of GLU-GABA in serum at clinical levels using the SERS and PLS models. This work demonstrated the applicability of using SERS in conjunction with PLS to measure properties of samples in blood serum. I also used SERS with HC-PCF configuration to detect leukemia cells, one of the most recurrent types of pediatric cancers. This was achieved by applying PLS regression and PCA techniques. Improving LOD was the next objective, and I was able to achieve this by improving the PLS model to decrease errors and remove outliers or unnecessary variables. The results of the final optimized models were evaluated by comparing them with the results of previous models of Heparin and Leukemia cell detection in previous sections. Finally, as a clinical application of Raman biosensors, I applied the enhanced Raman technique to detect polycystic ovary syndrome (PCOS) disease, and to determine the role of chemerin in this disease. I used SERS in conjunction with PCA to differentiate between PCOS and non-PCOS patients. I also confirmed the role of chemerin in PCOS disease, measured the level of chemerin, a chemoattractant protein, in PCOS and non-PCOS patients using PLS, and further improved LOD with the PLS regression model, as proposed in previous section.

L’objectif de cette étude est d'évaluer la qualité de l'eau dans le basin inférieur du Litani (sud Liban) et d’évaluer son potentiel d'utilisation polyvalente comme une des solutions aux problèmes aggravés d’eau au Liban. Pour identifier les sources possibles de métaux et ensuite caractériser le comportement chimique de ces métaux dans l'eau et dans les sédiments, des échantillons d’eau et des sédiments ont été prélevés de six sites représentatifs. Ils ont été analysés durant les trois saisons de l'année 2011-2012 (c'est-à-dire pluvieuse, mi- pluvieuse et sèche). L’ACP (l'analyse en composante principale), a ensuite été utilisé pour interpréter les concentrations dans l'eau fluviale. Les résultats montrent que parmi les 18 variables, qui ont été évaluées pour Caractériser les propriétés physico-chimiques, il y en a 4) Fe, NO2, CaCO3, Cu) qui permettent de qualifier le type d'environnement étudié; trois groupes ont été identifiés et différenciés par ACP selon les saisons. Le premier groupe inclut toutes les spécificités du milieu en saison pluviale et montre des concentrations importantes en Fe et NO2 et faibles en NH4. Le deuxième groupe est formé par les échantillons prélevés lors de la saison sèche et montre des caractéristiques physicochimiques opposés à celles observées dans le premier groupe. Enfin, le troisième groupe regroupe les observations de la saison mi- pluvieuse caractérisée par des concentrations faible en K+, PO43-et le Cl-. Les résultats montrent que les concentrations de Pb, Fe sont élevées sur deux sites avec dans un cas des valeurs de Cr et Ni importantes, Les sédiments ont été caractérisés par différentes techniques comme la capacité d'échange de cations, la granulométrie, la diffraction des rayons X (XRD) et la spectroscopie infrarouge à transformée de Fourier (FTIR). L'analyse FTIIR montre que la quantité de la montmorillonite est plus faible que la kaolinite et beaucoup inférieure que le quartz et la calcite. La corrélation de Pearson a été également effectuée dans cette étude pour comparer et déterminer la relation entre les métaux lourds dans les sédiments. L’indice de Géo accumulation (Igeo) , le facteur de Contamination (Cf), et le degré de contamination (Cd) ont été également déterminés pour évaluer le niveau de contamination dans les sites. Les valeurs obtenus montrent que les concentrations de Pb et de Fe sont élevés dans les deux sites et la valeur de Cr, Ni, sont élevés dans un seul site. Ces résultats suggèrent qu'une attention particulière doit être accordée à la question remobilisation des éléments, car une grande partie des éléments dans les sédiments sont susceptibles de se libérer dans l'eau. Tous les sites sont caractérisés par modérées à très polluée microbienne, nous avons encore observé que le dégrée de contamination a augmenté durant la saison sèche. Cependant, aucune pollution critique n'a été rapportée dans cette partie de la rivière ; sauf la haute concentration de Fe et NO2-dans tous les sites examinés en raison des rejets d'eaux usées et l'activité touristique dans le LLRB, les Concentrations de sept métaux lourds (Cu, Fe, Cd, Mn, Cr, Zn, Ni et Pb) dans les sédiments ont été déterminés pour évaluer leurs niveaux et leurs distribution spatiale / The objective of this study was to evaluate water quality of the lower Litani River and assess its feasibility for multi-purpose usage as one of the solutions to the aggravated water problems in Lebanon, To identify possible sources of metals (i.e. geological and/or anthropogenic) and then to characterize the chemical behavior of these metals in water and bed sediments, water and bed load sediments were sampled at six representatives sites which are investigated over three seasons of the year 2011-2012 (i.e. rainy, mid-rainy and dry seasons), The PCA (principal component analysis) method was used to interpret the elemental concentrations in the river water. Results show that among 18 variables, which were evaluated to characterize their physic-chemistry and metals, there are only 4 (Fe, NO2-, CaCO3, Cu) that were determined the type of environmental studied; Three groups were identified and differentiated by PCA according to the seasons. The first group includes all statements made in the mid rainy season and has a dialogue rich in Fe and NO2, and low in NH4 and EC. The second group formed in dry season, and surveys show physicochemical characteristics opposite to those in the first group, the third group formed in mid rainy, and showed the low concentration of K+, PO43- and Cl-. Sediments were characterized by a set of cations exchange capacity, granulometric, diffraction (XRD) and Fourier transformed infrared spectroscopy (FTIR( The FTIR analysis shows that the amount of montomorillonite is less than kaolinite and very much less than quartz and calcite. Pearson’s correlation was also performed in this study to compare to and determine the correlation between heavy metals in the sediments. Geo-accumulation (Igeo) index, Contamination Factor (Cf), and contamination degree (Cd) were also applying to assess the level of contamination in the sites. The results shows that the concentration of Pb, Fe are high in the site S5, S6 and the value of Cr ,Ni, are high in the S6, this results suggest that special attention must be given to the issue of element re-mobilization, because a large portion of elements in sediments are likely to release back into the water column. All the sites are characterized by moderate to highly microbial polluted range. The degree of contamination was increased in dry season. However, no critical physicochemical pollution has been reported in this part of the river; except the high concentration of Fe and NO2- in all investigated sites due to the reject of wastewater and to the distribution of touristic activities in the LLRB, the Concentrations of seven heavy metals is high(Cu, Fe, Cd , Mn , Cr, Zn, Ni and Pb) for sediment is higher according to Consensus-based sediment quality guidelines of Wisconsin (Wisconsin Department of Natural Resources, 2003) were applied to assess metal contamination in sediment