860 resultados para Principal Component Analysis (PCA)
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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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A erodibilidade é um fator de extrema importância na caracterização da perda de solo, representando os processos que regulam a infiltração de água e sua resistência à desagregação e o transporte de partículas. Assim, por meio da análise de dependência espacial dos componentes principais da erodibilidade (fator K), objetivou-se estimar a erodibilidade do solo em uma área de nascentes da microbacia do Córrego do Tijuco, Monte Alto-SP, e analisar a variabilidade espacial das variáveis granulométricas do solo ao longo do relevo. A erodibilidade média da área foi considerada alta, e a análise de agrupamento k-means apontou para uma formação de cinco grupos: no primeiro, os altos teores de areia grossa (AG) e média (AM) condicionaram sua distribuição nas áreas planas; o segundo, caracterizado pelo alto teor de areia fina (AF), distribui-se nos declives mais convexos; o terceiro, com altos teores de silte e areia muito fina (AMF), concentrou-se nos maiores declives e concavidades; o quarto, com maior teor de argila, seguiu as zonas de escoamento de água; e o quinto, com alto teor de matéria orgânica (MO) e areia grossa (AG), distribui-se nas proximidades da zona urbana. A análise de componentes principais (ACP) mostrou quatro componentes com 87,4 % das informações, sendo o primeiro componente principal (CP1) discriminado pelo transporte seletivo de partículas principalmente em zonas pontuais de maior declividade e acúmulo de sedimentos; o segundo (CP2), discriminado pela baixa coesão entre as partículas, mostra acúmulo da areia fina nas áreas de menor cota em toda a área de concentração de água; o terceiro (CP3), discriminado pela maior agregação do solo, concentra-se principalmente nas bases de grandes declives; e o quarto (CP4), discriminado pela areia muito fina, distribui-se ao longo das declividades nas maiores altitudes. Os resultados sugerem o comportamento granulométrico do solo, que se mostra suscetível ao processo erosivo devido às condições texturais superficiais e à movimentação do relevo.
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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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This paper reports on a sensor array able to distinguish tastes and used to classify red wines. The array comprises sensing units made from Langmuir-Blodgett (LB) films of conducting polymers and lipids and layer-by-layer (LBL) films from chitosan deposited onto gold interdigitated electrodes. Using impedance spectroscopy as the principle of detection, we show that distinct clusters can be identified in principal component analysis (PCA) plots for six types of red wine. Distinction can be made with regard to vintage, vineyard and brands of the red wine. Furthermore, if the data are treated with artificial neural networks (ANNs), this artificial tongue can identify wine samples stored under different conditions. This is illustrated by considering 900 wine samples, obtained with 30 measurements for each of the five bottles of the six wines, which could be recognised with 100% accuracy using the algorithms Standard Backpropagation and Backpropagation momentum in the ANNs. (C) 2003 Elsevier B.V. All rights reserved.
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The versatility of sensor arrays made from nanostructured Langmuir-Blodgett (LB) and layer-by-layer (LBL) films is demonstrated in two ways. First, different combinations of sensing units are employed to distinguish the basic tastes, viz. sweet, sour, bitter, and salty tastes, produced, respectively, by small concentrations (down to 0.01 g/mol) of sucrose, HCl, quinine, and NaCl solutions. The sensing units are comprised of LB and/or LBL films from semiconducting polymers, a ruthenium complex, and sulfonated lignin. Then, sensor arrays were used to identify wines from different sources, with the high distinguishing ability being demonstrated in principal component analysis (PCA) plots. Particularly important was the fact that the sensing ability does not depend on specific interactions between analytes and the film materials, but a judicious choice of materials is, nevertheless, required for the materials to respond differently to a given sample. It is also shown that the interaction with the analyte may affect the morphology of the nanostructured films, as indicated with scanning electron microscopy. For instance, in wine analysis these changes are not irreversible and the original film morphology is retrieved if the sensing unit is washed with copious amounts of water, thus allowing the sensor unit to be reused.
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The synthesis of a poly(azo)urethane by fixing CO2 in bis-epoxide followed by a polymerization reaction with an azodiamine is presented. Since isocyanate is not used in the process, it is termed clean method and the polymers obtained are named NIPUs (non-isocyanate polyurethanes). Langmuir films were formed at the air-water interface and were characterized by surface pressure vs mean molecular area per met unit (Pi-A) isotherms. The Langmuir monolayers were further studied by running stability tests and cycles of compression/expansion (possible hysteresis) and by varying the compression speed of the monolayer formation, the subphase temperature, and the solvents used to prepare the spreading polymer solutions. The Langmuir-Blodgett (LB) technique was used to fabricate ultrathin films of a particular polymer (PAzoU). It is possible to grow homogeneous LB films of up to 15 layers as monitored using UV-vis absorption spectroscopy. Higher number of layers can be deposited when PAzoU is mixed with stearic acid, producing mixed LB films. Fourier transform infrared (FTIR) absorption spectroscopy and Raman scattering showed that the materials do not interact chemically in the mixed LB films. The atomic force microscopy (AFM) and micro-Raman technique (optical microscopy coupled to Raman spectrograph) revealed that mixed LB films present a phase separation distinguishable at micrometer or nanometer scale. Finally, mixed and neat LB films were successfully characterized using impedance spectroscopy at different temperatures, a property that may lead to future application as temperature sensors. Principal component analysis (PCA) was used to correlate the data.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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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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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)