72 resultados para Análise de componentes principais (PCA)

em Universidade Federal do Rio Grande do Norte(UFRN)


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To contribute in the performance of policies and strategies formulated by development agencies, indexes have been created in anticipation of expressing the multiple dimensions of water resources in an easily interpretable form. Use of Hydro Poverty Index ( WPI) is spreading worldwide , with the same formed by the combination of sub - indices Resource, access, capacity , use and environment. S ome critics a s to its formation have emerged, a mong them stands out the allo cation of weights of sub - indexes , made by an arbitrary process attributing subjectivity to the selection criteria. By involving statistical analysis, when considering the characteristics of the variables generated by the Principal Component Analysis (PCA), it turns out that it is able to solve this problem. The objective of this study is to compare the results of the original WPI with content generated by Principal Com ponent Analysis (PCA) for the indicati on of the weights of sub - indec es applicable in the Seridó River hydrographic Basin . We conclude that the use of Principal Component Analysis in the allocation of weights of Water Poverty Index has identified the sub - indices Resources, Access and Environment are the most representative for the river basin Seridó , and that this new index, WPI' , presented the most comprehensive ranges of values , allowing more easily identify disparities among municipalities. In addition, t he evaluation of the sub - indec es in the study area has great potential to inform the decision - maker in the management of water resources, the most critical locations and deserve greater investments in the aspects analyzed, as the index itself can not cap ture this information.

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Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study

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A região semiárida sofre escassez hídrica. A fim de regularizar a disponibilidade hídrica nos períodos de estiagem, são construídas barragens. No entanto, a qualidade da água armazenada tem sofrido os efeitos do descarte irregular de resíduos no meio ambiente e das atividades antrópicas exercidas nas bacias hidrográficas. A degradação hídrica pode ser constatada a partir do monitoramento dos parâmetros de qualidade da água. Estes dados podem ser analisados através de métodos estatísticos tais como a Análise de Componentes Principais e a análise de agrupamento, que seleciona indivíduos com características semelhantes. O objetivo deste trabalho é realizar oagrupamento dos reservatórios do Rio Grande do Norte, com base nos parâmetros de qualidade da água, para a identificação de grupos homogêneos de reservatórios em termos de fontes de poluição. Serão objeto desse estudo as bacias Piranhas-Açu, Apodi-Mossoró, Trairí, Potengi e Ceará-Mirim. Os parâmetros mercúrio, chumbo, cromo, fósforo total, nitrogênio total e zinco contribuíram para a formação da primeira componente principal, que pode indicar poluição por metais pesados; sólidos totais, DBO, OD e cobre, para a segunda componente, que pode ser indicativo de poluição por matéria orgânica e atividades antrópicas; e clorofila a , cádmio e níquel, para a terceira componente, que pode indicar eutrofização e poluição por metais pesados. De posse das componentes principais se procedeu o agrupamento dos reservatórios, formando-se quatro grupos distintos. Os grupos 1 e 2 são constituídos por reservatórios da Bacia Piranhas-Açu, que apresentou maiores valores de metais pesados. O grupo 3, constituído por reservatórios das bacias Ceará-Mirim, Potengi e Trairí, apresentou maiores valores de DBO e sólidostotais e o grupo 4 é formado por reservatórios da Bacia Apodi-Mossoró. Nas Bacias do Trarí e Piranhas-Açu deve ser coibido o lançamento desordenado de efluentes e fontes de poluição difusas, e implantado um sistema de coleta de esgoto para minimizar a poluição por matéria orgânica

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This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification

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Ecomorphology is a science based on the idea that morphological differences among species could be associated with distinct biological and environmental pressures suffered by them. These differences can be studied employing morphological and biometric indexes denominated Ecomorphological attributes , representing standards that express characteristics of the individual in relation to its environment, and can be interpreted as indicators of life habits or adaptations suffered due its occupation of different habitats. This work aims to contribute for the knowledge of the ecomorphology of the Brazilian marine ichthyofauna, specifically from Galinhos, located at Rio Grande do Norte state. 10 different species of fish were studied, belonging the families Gerreidae (Eucinostomus argenteus), Haemulidae (Orthopristis ruber,Pomadasyscorvinaeformis,Haemulonaurolineatum,Haemulonplumieri,Haemulonsteindachneri), Lutjanidae (Lutjanus synagris), Paralichthyidae (Syaciummicrurum), Bothidae (Bothus ocellatus) and Tetraodontidae (Sphoeroidestestudineus), which were obtained during five collections, in the period time of September/2004 to April/2005, utilizing three special nets. The ecomorphological study was performed at the laboratory. Eight to ten samples of each fish specie were measured. Fifteen morphological aspects were considered to calculate twelve ecomorphological attributes. Multivariate statistical analysis methods such as Principal Component Analysis (PCA) and Cluster Analysis were done to identify ecmorphological patterns to describe the data set obtained. As results, H.aurolineatumwas the most abundant specie found (23,03%) and S.testudineusthe less one with 0,23%. The 1st Principal component showed variation of 60,03% with influence of the ecomorphological attribute related to body morphology, while the 2nd PC with 23,25% variation had influence of the ecomorphological attribute related to oral morphology. The Cluster Analiysis promoted the identification of three distinct groups Perciformes, Pleuronectiformes and Tetraodontiformes. Based on the obtained data, considering morphological characters differences among the species studied, we suggest that all of them live at the medium (E.argenteus,O.rubber, P.corvinaeformis,H.aurolineatum,H.plumieri,H.steindachneri,L.synagris) and bottom (S.micrurum,B.ocellatus,S.testudineus) region of column water.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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The demographic growth press environments that are more susceptible to perturbations, like riparian areas, without knowing about the effects of replacing these natural environments by different land uses on soil quality and, consequently, on watershed. The study of soil quality has evolved as an important tool for soil sustainable management of this component of the biosphere that affects aquatic and terrestrial ecosystems functions. Thus, physical and chemical soil proprieties were measured to assess soil quality under different land uses (agricultural, pasture, urban, industrial and natural vegetation,) in the riparian zone of Extremoz Lake, an important human water source, evaluating whether the soil offers potential risk to water pollution. Data were subjected to descriptive statistics and Principal Component Analysis (PCA). The results showed negative changes in soil quality such as alkalinization and increase in P, Pb, Mn and Zn contents in most anthropized areas. The sandy texture and low organic matter content in all soils showed the fragility of the soil to erosion and leaching of elements in excess to water bodies, evidencing that this soils has potential to diffuse contaminants. Conservative management of soil is necessary to provide an adequate ecological state in riparian zones of the Extremoz Lake, thus allowing controlling and buffering diffuse sources of pollution to this important water supply source

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The precision and the fast identification of abnormalities of bottom hole are essential to prevent damage and increase production in the oil industry. This work presents a study about a new automatic approach to the detection and the classification of operation mode in the Sucker-rod Pumping through dynamometric cards of bottom hole. The main idea is the recognition of the well production status through the image processing of the bottom s hole dynamometric card (Boundary Descriptors) and statistics and similarity mathematics tools, like Fourier Descriptor, Principal Components Analysis (PCA) and Euclidean Distance. In order to validate the proposal, the Sucker-Rod Pumping system real data are used

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Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

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In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

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Heavy metals can cause problems of human poisoning by ingestion of contaminated food, and the environment, a negative impact on the aquatic fauna and flora. And for the presence of these metals have been used for aquatic animals biomonitoramento environment. This research was done in order to assess the environmental impact of industrial and domestic sewage dumped in estuaries potiguares, from measures of heavy metals in mullet. The methods used for these determinations are those in the literature for analysis of food and water. Collections were 20 samples of mullet in several municipality of the state of Rio Grande do Norte, from the estuaries potiguares. Were analyzed the content of humidity, ash and heavy metals. The data were subjected to two methods of exploratory analysis: analysis of the main components (PCA), which provided a multivariate interpretation, showing that the samples are grouped according to similarities in the levels of metals and analysis of hierarchical groupings (HCA), producing similar results. These tests have proved useful for the treatment of the data producing information that would hardly viewed directly in the matrix of data. The analysis of the results shows the high levels of metallic species in samples Mugil brasiliensis collected in Estuaries /Potengi, Piranhas/Açu, Guaraíra / Papeba / Arês and Curimataú

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Nowadays, the use of chemicals that satisfactorily meet the needs of different sectors of the chemical industry is linked to the consumption of biodegradable materials. In this context, this work contemplated biotechnological aspects with the objective of developing a more environmentally-friendly corrosion inhibitor. In order to achieve this goal, nanoemulsion-type systems (NE) were obtained by varying the amount of Tween 80 (9 to 85 ppm) a sortitan surfactant named polyoxyethylene (20) monooleate. This NE-system was analyzed using phase diagrams in which the percentage of the oil phase (commercial soybean oil, codenamed as OS) was kept constant. By changing the amount of Tween 80, several polar NE-OS derived systems (O/W-type nanoemulsion) were obtained and characterized through light scattering, conductivity and pH, and further subjected to electrochemical studies. The interfacial behavior of these NE-OS derived systems (codenamed NE-OS1, S2, S3, S4 and S5) as corrosion inhibitors on carbon steel AISI 1020 in saline media (NaCl 3.5%) were evaluated by measurement of Open Circuit Potential (OCP), Polarization Curves (Tafel extrapolation method) and Electrochemical Impedance Spectroscopy (EIS). The analyzed NE-OS1 and NE-OS2 systems were found to be mixed inhibitors with quantitative efficacy (98.6% - 99.7%) for concentrations of Tween 80 ranging between 9 and 85 ppm. According to the EIS technique, maximum corrosion efficiency was observed for some tested NE-OS samples. Additionaly to the electrochemical studies, Analysis of Variance (ANOVA) and Principal Component Analysis (PCA) were used, characterization of the nanoemulsion tested systems and adsorption studies, respectively, which confirmed the results observed in the experimental analyses using diluted NE-OS samples in lower concentrations of Tween 80 (0.5 1.75 ppm)

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This work examined the possibility of using mussel Mytella falcata as bioindicator sample to detect metal ions in several estuaries potiguares, since species substances that accumulate in their tissues due to its characteristics filter feeders have been used for environmental monitoring. The chemometrics by principal components analysis was used to reduce the size of the original data in order to establish a pattern of distribution of metal ion. Samples were collected at three different points in the estuaries Curimataú, Guaraíra-Papeba, Potengi, Galinhos-Guamaré and Piranhas-Assu having been marked with the location using GPS (Global Positioning System). The determination of humidity content and digestion of the samples were performed using methods described in the Compendium of analytical standards of the Institute Adofo Lutz (2005) and the determination of metal ions of the elements Al, Ba, Cd, Cr, Cu, Mn, Ni, Pb, Sn and Zn were performed by optical emission spectrometry with inductively coupled plasma as described by USEPA method 6010C. The results show that it is possible to use this molluscum Mytella falcata in the estuaries of Rio Grande do Norte for the determination of metal ions. The data were subjected to principal components analysis (PCA) which enabled us to verify the distribution pattern of the metal ions studied in several estuaries potiguares and group them according to the metal ions in common with and relate them to the activities in each region

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Aiming to consumer s safety the presence of pathogenic contaminants in foods must be monitored because they are responsible for foodborne outbreaks that depending on the level of contamination can ultimately cause the death of those who consume them. In industry is necessary that this identification be fast and profitable. This study shows the utility and application of near-infrared (NIR) transflectance spectroscopy as an alternative method for the identification and classification of Escherichia coli and Salmonella Enteritidis in commercial fruit pulp (pineapple). Principal Component Analysis (PCA), Independent Modeling of Class Analogy (SIMCA) and Discriminant Analysis Partial Least Squares (PLS-DA) were used in the analysis. It was not possible to obtain total separation between samples using PCA and SIMCA. The PLS-DA showed good performance in prediction capacity reaching 87.5% for E. coli and 88.3% for S. Enteritides, respectively. The best models were obtained for the PLS-DA with second derivative spectra treated with a sensitivity and specificity of 0.87 and 0.83, respectively. These results suggest that the NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in the fruit pulp

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Cattleya granulosa Lind is a large and endemic orchid in Atlantic Forest fragments in Northeast Brazil. The facility of collecting, uniqueness of their flowers, which have varying colors between green and reddish brown, and distribution in coastal areas of economic interest make their populations a constant target of predation, which also suffer from environmental degradation. Due to the impact on their populations, the species is threatened. In this study, we evaluate the levels of spatial aggregation in a preserved population, analyze the phylogenetic relationships of C. granulosa Lindl. with four other Laeliinae species (Brassavola tuberculata, C. bicolor, C. labiata and C. schofieldiana) and also to evaluate the genetic diversity of 12 remaining populations of C. granulosa Lindl. through ISSR. There was specificity of epiphytic C. granula Lindl. with a single host tree, species of Eugenia sp. C. granulosa Lindl. own spatial pattern, with the highest density of neighbors within up to 5 m. Regarding the phylogenetic relationships and genetic patterns with other species of the genus, C. bicolor exhibited the greatest genetic diversity (HE = 0.219), while C. labiata exhibited the lowest level (HE = 0.132). The percentage of genetic variation among species (AMOVA) was 23.26%. The principal component analysis (PCA) of ISSR data showed that unifoliate and bifoliolate species are genetically divergent. PCA indicated a close relationship between C. granulosa Lindl. and C. schofieldiana, a species considered to be a variety of C. granulosa Lindl. by many researchers. Population genetic analysis using ISSR showed all polymorphic loci. The high genetic differentiation between populations (ФST = 0.391, P < 0.0001) determined the structure into nine groups according to log-likelihood of Bayesian analysis, with a similar pattern in the dendrogram (UPGMA) and PCA. A positive and significant correlation between geographic and genetic distances between populations was identified (r = 0.794, P = 0.017), indicating isolation by distance. Patterns of allelic diversity suggest the occurrence of population bottlenecks in most populations of C. granulosa Lindl. (n = 8). Genetic data indicate that enable the maintenance of genetic diversity of the species is complex and is directly related to the conservation of different units or groups that are spatially distant.