937 resultados para principal components analysis (PCA) algorithm


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One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.

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A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

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Four perylene derivatives (PTCD) have been used as transducing materials in taste sensors fabricated with nanostructured Langmuir-Blodgett (LB) films deposited onto interdigitated gold electrodes. The Langmuir monolayers of PTCDs display considerable collapse pressures, with areas per molecule indicative of an edge-on or head-on arrangement for the molecules at the air/water interface. The sensing units for the electronic tongue were produced from 5-layer LB films of the four PTCDs, whose electrical response was characterized with impedance spectroscopy. The distinct responses of the PTCDs, attributed to differences in their molecular structures, allowed one to obtain a finger printing system that was able to distinguish tastes (salty, sweet, bitter and sour) at 1 μM concentrations, which, in some cases, are three orders of magnitude below the human threshold. Using Principal Component Analysis (PCA) data analysis, the electronic tongue also detected trace amounts of a pesticide and could distinguish among samples of ultrapure, distilled and tap water, and two brands of mineral water. © 2004 by American Scientific Publishers. All rights reserved.

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In this work, humic substances were extracted from water samples collected monthly from the Negro River basin in the Amazon state (Brazil) to study their properties in the Amazonian environment and interactions with the mercury ion considering the influence of seasonalness in this formation. The C/H, C/N and C/O atomic ratio parameters, functional groups, concentration of semiquinone-type free radicals, pH, pluviometric and fluviometric indices, and mercury concentrations were interpreted using hierarchical cluster analysis (HCA) and principal component analysis (PCA). The statistical analyses showed that when the pluviometric index was greater and the fluviometric index was smaller, the degree of humification of aquatic substances was greater. The following decreasing order of the degree of humification of the AHS collected monthly was established: Nov/02 to Feb/03 > Mar/02 to May/02 > Jun/02 to Oct/02. The greatest concentrations of mercury were detected in more humidified samples. These results suggest that due to inter and/or intra-molecular rearrangements, the degree of humification of aquatic humic substances is related to its affinity for Hg(II) ions. ©2007 Sociedade Brasileira de Química.

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Three small rivers belonging to the Rio das Pedras basin, located in the mid-southern region of Paraná state, were studied in order to evaluate the seasonal variation pattern of some physical and chemical parameters. Monthly samplings were carried out from April 2004 to March 2005. The following limnological parameters were measured: water temperature, specific conductance, oxygen saturation, pH, turbidity, current velocity and depth. The waters of the Rio das Pedras basin presented very peculiar characteristics, showing typical seasonal patterns for some of the studied limnological variables. An Analysis of Variance (Anova) showed significant differences only for pH and depth among streams. A Principal Component Analysis (PCA) showed a weak tendency to form groups based on seasons instead of sampling sites. The results, in general, indicate that temporal variations of the environmental parameters analyzed were not sufficient to draw a clear seasonal pattern in the Rio das Pedras basin. Most likely, the lack of an obvious seasonal pattern has been provoked by a particular regional precipitation regime, where rains are frequent and well-distributed throughout the year.

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The aim of this paper is to verify the correlation between environmental indicators and behaviors expressed by laying hens kept in cages. The birds react to a severe environment through their behaviors, end the behaviors can be monitored to identify the birds' welfare conditions. The behaviors birds display ere the result of stress caused by the combination of environmental temperature, relative humidity, radiant heat, and air speed (environmental temperature being the most important). In order to check the influence of the environment, an experiment was carried out on a commercial poultry farm, located in the city of Bastos. The study was initiated in March 2007, during four non-consecutive weeks. The birds' behaviors were recorded using video, by cameras installed in the cages. The birds behaviors were identified and noted for the frequency of occurrence for each bird, and the average duration of each behavior (in seconds), using video samples of 15 minutes recorded from 1 PM to 4 PM. The environmental variables collected were: air temperature, concentration of ammonia, relative air humidity, velocity of the air, noise, roof temperature, and light intensity. The observed behaviors were: opening wings, stretching, threatening, ruffling feathers, drinking water, aggressive pecking, eating, running, lying down, stretching head out of the cage, preening, mounting and prostrating. Principal Components Analysis was used to determine associations between the behavior variables and environmental variables described above. In this experiment, there were no significant correlations between behavioral variables and environmental variables.

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The objective of this work was to verify the application of cluster analysis to evaluate soil erosion risk for different soil classes, soil slopes and soil managements. The study was conducted in a 33 ha section of a large field located in Carmo do Rio Claro County, MG, Brazil. The field had been managed in a corn/bean rotation under conventional tillage and under coffee plantation for seven years, both under sprinkle irrigation. Soil samples were obtained at every 10 m at 0.20 m depth along a transect of 1050 m. Soil erosion risk (A), natural potential erosion (PN), and erosion expectation (EE) were determined and submitted to a cluster and principal component analysis. The application of clustering analysis showed high correlation between the clusters and soil types. With clustering analysis plus principal components analysis, it was possible to identify groups of high and low soil erosion expectation, showing that the areas with higher soil erosion expectation are correlated to the soil class, soil slope and soil management. Among the studied variables, the natural potential erosion (PN) showed to be the most important factor to identify different soil erosion groups. The cluster analysis showed that 98% of the variables were classified within each group, and that they should be managed differently due to the soil erosive potential of each group,.

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The velvetbean caterpillar Anticarsia gemmatalis Hübner attacks peanut leaves, and the use of resistant varieties has directly contributed to ecological and economic aspects of pest control. The aim of this work was to select resistant peanut genotypes to A. gemmatalis using cluster analyses (dendogram obtained by Ward's methods and K-means) and Principal Components analysis for data interpretation. The evaluated genotypes were: IAC 5, IAC 8112, IAC 22 and IAC Tatu ST with upright growth habit, and IAC 147, IAC 125, IAC Caiapó and IAC Runner 886 with runner growth habit, and soybean genotype BR 16 as a susceptible control. The biological parameters: leaf consumption, larval (4o instar) and pupal (24h old) weight, larval and pupal development time and adult longevity were evaluated at laboratory conditions. The genotypes IAC 147 and IAC Runner 886 were resistant to A. gemmatalis in both cluster tests, grouping apart from most of the other genotypes. Both dendrogram and K-means methods provided satisfactory biological explanation, and they can be complementary used together with Principal Component and vice-versa. These results suggest that cluster analyses may be an important statistical tool in the selection of host plant resistance.

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Predicting and mapping productivity areas allows crop producers to improve their planning of agricultural activities. The primary aims of this work were the identification and mapping of specific management areas allowing coffee bean quality to be predicted from soil attributes and their relationships to relief. The study area was located in the Southeast of the Minas Gerais state, Brazil. A grid containing a total of 145 uniformly spaced nodes 50 m apart was established over an area of 31. 7 ha from which samples were collected at depths of 0. 00-0. 20 m in order to determine physical and chemical attributes of the soil. These data were analysed in conjunction with plant attributes including production, proportion of beans retained by different sieves and drink quality. The results of principal component analysis (PCA) in combination with geostatistical data showed the attributes clay content and available iron to be the best choices for identifying four crop production environments. Environment A, which exhibited high clay and available iron contents, and low pH and base saturation, was that providing the highest yield (30. 4l ha-1) and best coffee beverage quality (61 sacks ha-1). Based on the results, we believe that multivariate analysis, geostatistics and the soil-relief relationships contained in the digital elevation model (DEM) can be effectively used in combination for the hybrid mapping of areas of varying suitability for coffee production. © 2012 Springer Science+Business Media New York.

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The aim of this study was to evaluate the incidence of pleiomorphisms and its influence on the distribution of sperm morphometric subpopulations in ejaculates from the vulnerable Goeldi's monkey (Callimico goeldii) by using a combination of computerized analysis system and Principal Component Analysis (PCA) methods Each sperm head was measured for four primary spermatozoal head dimensional parameters (area [A (μm2)], perimeter [P (μm)], length [L (μm)] and width [W (μm)]) and three head shape derived parameters (ellipticity [(L/W)], elongation [(L-W)/(L+W)] and rugosity [(4πA/P2)]) Six separate subpopulations (SPs) were identified: SP1, constituted by very large, narrow and very elliptical spermatozoa (A=16.85±1.56μm2, W=2.75±0.42μm and ellipticity=2.16±0.24); SP2, characterized by average sized, short, wide and round spermatozoa (A=15.00±1.92μm2, L=5.06±0.49μm, W=3.51±0.31μm and ellipticity=1.44±0.15); SP3, represented by small, wide and slightly round spermatozoa (A=14.95±1.75μm2, W=3.47±0.29μm and ellipticity=1.48±0.14); SP4 included very small, short and very round spermatozoa (A=14.15±2.38μm2, L=4.90±0.57μm and elongation=0.18±0.05); SP5 consisted of average sized and slightly elliptical spermatozoa (A=15.14±1.72μm2 and ellipticity=1.49±0.14); and SP6 included large and round spermatozoa (A=16.30±1.62μm2 and elongation=0.19±0.04) There were differences in the sperm subpopulation distribution (P<0.001) among the five donors analyzed In conclusion, the results of the current study confirmed that the use of computer sperm analysis methods combined with PCA cluster analyses are useful methods to identify, classify, and characterize different sperm head morphometric subpopulations in neotropical primates Broadening our knowledge of C goeldii sperm morphometric abnormalities as well as developing reliable techniques for sperm evaluation may be essential for ex situ conservation of this threatened species © 2012 Elsevier B.V.

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Objectives: To investigate if the participation of Atopobium vaginae, Megasphaera sp. and Leptotrichia sp. in the bacterial community of bacterial vaginosis (BV) is associated with distinct patterns of this condition. Methods: In this cross-sectional controlled study, 205 women with BV and 205 women with normal flora were included. Vaginal rinsing samples were obtained for measuring the levels of pro-inflammatory cytokines and bacterial sialidases. Real-time PCR was used to quantify the BV-associated bacteria and to estimate the total bacterial load using the 16S rRNA. Principal component analysis (PCA) using the measured parameters was performed to compare the BV samples with lower and higher loads of the species of interest. Results: Higher bacterial load (p<0.001), levels of interleukin 1-β (p<0.001) and sialidase activity (p<0.001) were associated with BV. Women with BV and higher relative loads of A vaginae, Megasphaera sp. and Leptotrichia sp. presented increased sialidase activity, but unchanged cytokine levels. PCA analysis did not indicate a different pattern of BV according to the loads of A vaginae, Megasphaera sp. and Leptotrichia sp. Conclusions: Greater participation of A vaginae, Megasphaera sp. and Leptotrichia sp. in vaginal bacterial community did not indicate a less severe form of BV; moreover, it was associated with increased sialidase activity.

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Nanostructured films of dioctadecyldimethylammonium bromide (DODAB) and nickel tetrasulfonated phthalocyanine (NiTsPc) were layer-by-layer (LbL) assembled to achieve a synergistic effect considering the distinct properties of both materials. Prior to LbL growth, the effect of NiTsPc on the structure of DODAB vesicles in aqueous medium was investigated by differential scanning calorimetry (DSC). Therefore, DODAB/NiTsPc LbL films were prepared using NiTsPc at concentrations below and above the limit concentration of vesicle formation according to our DSC experiments. As a result, LbL films with distinct nanostructures were obtained, which were studied at micro and nanoscales by micro-Raman and atomic force microscopy, respectively. A linear growth of the LbL films was observed by ultraviolet-visible absorption spectroscopy. However, the bilayer thickness and the surface morphology of the LbL films were radically affected depending on NiTsPc concentration. The electrostatic interaction between DODAB and NiTsPc was identified via Fourier transform infrared (FTIR) absorption spectroscopy as the main driving force responsible for LbL growth. Because LbL films have been widely applied as transducers in sensing devices, DODAB/NiTsPc LbL films having distinct nanostructures were tested as proof-of-principle in preliminary sensing experiments toward dopamine detection using impedance spectroscopy (e-tongue system). The real capacitance vs. dopamine concentration curves were treated using Principal Component Analysis (PCA) and an equivalent electric circuit, revealing the role played by the LbL film nanostructure and the possibility of building calibration curves. © 2013 Elsevier B.V.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The aims of this study were to assess the validity and the feasibility of the qualitative behavior assessment (QBA) method as indicator of Nellore cattle temperament under field conditions, evaluating its associations with four other traditional methods and weight gain. The temperament and live weight of 2229 Nellore cattle was assessed at approximately 550 days of age. Five measurements of cattle temperament were recorded: flight speed test (FS, in m/s), visual scores of movement in the crush (MOV), crush score (CS), temperament score (TS), and the qualitative behavior assessment method (QBA), by using a list of 12 behavioral based adjectives as descriptors of temperament. Average daily weight gain (ADG) was calculated for each animal. For statistical analysis of QBA data, the Principal Component Analysis was used. A temperament index (TI) was defined for each animal using the scores for the first principal component. Pearson's correlation coefficients were estimated between TI with FS and ADG. A mixed model ANOVA was used to analyze the TI variation as a function of TS, CS, and MOV. The score plot for the first and second principal components was used to classify the cattle in four groups (from very bad to very good temperament). The first principal component explained 49.50% of the variation in the data set, with higher positive loadings for the adjectives 'agitated' and 'active', and higher negative loadings for 'calm' and 'relaxed'. TI was significantly correlated with FS (r=0.49; P<0.01) and ADG (r=-0.10; P<0.01). The means of ADG, FS, and the temperament scores (CS, TS, MOV) differed significantly (P<0.01) among the four groups, from very bad to very good temperament. The QBA method could discriminate different behavioral profiles of Nellore cattle and were in agreement with other traditional methods used as indicators of cattle temperament. Additional studies are needed to assess the inter- and intra-observers reliability and to study its association with physiological parameters. © 2013 Elsevier B.V.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)