937 resultados para principal components analysis (PCA) algorithm
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In traffic accidents involving motorcycles, paint traces can be transferred from the rider's helmet or smeared onto its surface. These traces are usually in the form of chips or smears and are frequently collected for comparison purposes. This research investigates the physical and chemical characteristics of the coatings found on motorcycles helmets. An evaluation of the similarities between helmet and automotive coating systems was also performed.Twenty-seven helmet coatings from 15 different brands and 22 models were considered. One sample per helmet was collected and observed using optical microscopy. FTIR spectroscopy was then used and seven replicate measurements per layer were carried out to study the variability of each coating system (intravariability). Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were also performed on the infrared spectra of the clearcoats and basecoats of the data set. The most common systems were composed of two or three layers, consistently involving a clearcoat and basecoat. The coating systems of helmets with composite shells systematically contained a minimum of three layers. FTIR spectroscopy results showed that acrylic urethane and alkyd urethane were the most frequent binders used for clearcoats and basecoats. A high proportion of the coatings were differentiated (more than 95%) based on microscopic examinations. The chemical and physical characteristics of the coatings allowed the differentiation of all but one pair of helmets of the same brand, model and color. Chemometrics (PCA and HCA) corroborated classification based on visual comparisons of the spectra and allowed the study of the whole data set at once (i.e., all spectra of the same layer). Thus, the intravariability of each helmet and its proximity to the others (intervariability) could be more readily assessed. It was also possible to determine the most discriminative chemical variables based on the study of the PCA loadings. Chemometrics could therefore be used as a complementary decision-making tool when many spectra and replicates have to be taken into account. Similarities between automotive and helmet coating systems were highlighted, in particular with regard to automotive coating systems on plastic substrates (microscopy and FTIR). However, the primer layer of helmet coatings was shown to differ from the automotive primer. If the paint trace contains this layer, the risk of misclassification (i.e., helmet versus vehicle) is reduced. Nevertheless, a paint examiner should pay close attention to these similarities when analyzing paint traces, especially regarding smears or paint chips presenting an incomplete layer system.
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The present study evaluated the sensory quality of chocolates obtained from two cocoa cultivars (PH16 and SR162) resistant to Moniliophtora perniciosa mould comparing to a conventional cocoa that is not resistant to the disease. The acceptability of the chocolates was assessed and the promising cultivars with relevant sensory and commercial attributes could be indicated to cocoa producers and chocolate manufacturers. The descriptive terminology and the sensory profile of chocolates were developed by Quantitative Descriptive Analysis (QDA). Ten panelists, selected on the basis of their discriminatory capacity and reproducibility, defined eleven sensory descriptors, their respective reference materials and the descriptive evaluation ballot. The data were analyzed using ANOVA, Principal Component Analysis (PCA) and Tukey's test to compare the means. The results revealed significant differences among the sensory profiles of the chocolates. Chocolates from the PH16 cultivar were characterized by a darker brown color, more intense flavor and odor of chocolate, bitterness and a firmer texture, which are important sensory and commercial attributes. Chocolates from the SR162 cultivar were characterized by a greater sweetness and melting quality and chocolates from the conventional treatment presented intermediate sensory characteristics between those of the other two chocolates. All samples indicated high acceptance, but chocolates from the PH16 and conventional cultivars obtained higher purchase intention scores.
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In this present work, we are proposing a characteristics reduction system for a facial biometric identification system, using transformed domains such as discrete cosine transformed (DCT) and discrete wavelets transformed (DWT) as parameterization; and Support Vector Machines (SVM) and Neural Network (NN) as classifiers. The size reduction has been done with Principal Component Analysis (PCA) and with Independent Component Analysis (ICA). This system presents a similar success results for both DWT-SVM system and DWT-PCA-SVM system, about 98%. The computational load is improved on training mode due to the decreasing of input’s size and less complexity of the classifier.
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Objective: To compare lower incisor dentoalveolar compensation and mandible symphysis morphology among Class I and Class III malocclusion patients with different facial vertical skeletal patterns. Materials and Methods: Lower incisor extrusion and inclination, as well as buccal (LA) and lingual (LP) cortex depth, and mandibular symphysis height (LH) were measured in 107 lateral cephalometric x-rays of adult patients without prior orthodontic treatment. In addition, malocclusion type (Class I or III) and facial vertical skeletal pattern were considered. Through a principal component analysis (PCA) related variables were reduced. Simple regression equation and multivariate analyses of variance were also used. Results: Incisor mandibular plane angle (P < .001) and extrusion (P = .03) values showed significant differences between the sagittal malocclusion groups. Variations in the mandibular plane have a negative correlation with LA (Class I P = .03 and Class III P = .01) and a positive correlation with LH (Class I P = .01 and Class III P = .02) in both groups. Within the Class III group, there was a negative correlation between the mandibular plane and LP (P = .02). PCA showed that the tendency toward a long face causes the symphysis to elongate and narrow. In Class III, alveolar narrowing is also found in normal faces. Conclusions: Vertical facial pattern is a significant factor in mandibular symphysis alveolar morphology and lower incisor positioning, both for Class I and Class III patients. Short-faced Class III patients have a widened alveolar bone. However, for long-faced and normal-faced Class III, natural compensation elongates the symphysis and influences lower incisor position.
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PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.
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We presented a bird-monitoring database inMediterranean landscapes (Catalonia, NE Spain) affected by wildfires and we evaluated: 1) the spatial and temporal variability in the bird community composition and 2) the influence of pre-fire habitat configuration in the composition of bird communities. The DINDIS database results fromthemonitoring of bird communities occupying all areas affected by large wildfires in Catalonia since 2000.We used bird surveys conducted from 2006 to 2009 and performed a principal components analysis to describe two main gradients of variation in the composition of bird communities, which were used as descriptors of bird communities in subsequent analyses. We then analysed the relationships of these community descriptors with bioclimatic regions within Catalonia, time since fire and pre-fire vegetation (forest or shrubland).We have conducted 1,918 bird surveys in 567 transects distributed in 56 burnt areas. Eight out of the twenty most common detected species have an unfavourable conservation status, most of them being associated to open-habitats. Both bird communities’ descriptors had a strong regional component and were related to pre-fire vegetation, and to a lesser extent to the time since fire.We came to the conclusion that the responses of bird communities to wildfires are heterogeneous, complex and context dependent. Large-scale monitoring datasets, such as DINDIS, might allow identifying factors acting at different spatial and temporal scales that affect the dynamics of species and communities, giving additional information on the causes under general trends observed using other monitoring systems
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The aim of this work is to present a tutorial on Multivariate Calibration, a tool which is nowadays necessary in basically most laboratories but very often misused. The basic concepts of preprocessing, principal component analysis (PCA), principal component regression (PCR) and partial least squares (PLS) are given. The two basic steps on any calibration procedure: model building and validation are fully discussed. The concepts of cross validation (to determine the number of factors to be used in the model), leverage and studentized residuals (to detect outliers) for the validation step are given. The whole calibration procedure is illustrated using spectra recorded for ternary mixtures of 2,4,6 trinitrophenolate, 2,4 dinitrophenolate and 2,5 dinitrophenolate followed by the concentration prediction of these three chemical species during a diffusion experiment through a hydrophobic liquid membrane. MATLAB software is used for numerical calculations. Most of the commands for the analysis are provided in order to allow a non-specialist to follow step by step the analysis.
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One of the major interests in soil analysis is the evaluation of its chemical, physical and biological parameters, which are indicators of soil quality (the most important is the organic matter). Besides there is a great interest in the study of humic substances and on the assessment of pollutants, such as pesticides and heavy metals, in soils. Chemometrics is a powerful tool to deal with these problems and can help soil researchers to extract much more information from their data. In spite of this, the presence of these kinds of strategies in the literature has obtained projection only recently. The utilization of chemometric methods in soil analysis is evaluated in this article. The applications will be divided in four parts (with emphasis in the first two): (i) descriptive and exploratory methods based on Principal Component Analysis (PCA); (ii) multivariate calibration methods (MLR, PCR and PLS); (iii) methods such as Evolving Factor Analysis and SIMPLISMA; and (iv) artificial intelligence methods, such as Artificial Neural Networks.
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The ¹H NMR data set of a series of 3-aryl (1,2,4)-oxadiazol-5-carbohydrazide benzylidene derivatives synthesized in our group was analyzed using the chemometric technique of principal component analysis (PCA). Using the original ¹H NMR data PCA allowed identifying some misassignments of the proton aromatic chemical shifts. As a consequence of this multivariate analysis, nuclear Overhauser difference experiments were performed to investigate the ambiguity of other assignments of the ortho and meta aromatic hydrogens for the compound with the bromine substituent. The effect of the 1,2,4-oxadiazol group as an electron acceptor, mainly for the hydrogens 12,13, has been highlighted.
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The concentrations of Cu, Pb, Zn, Cr, Ni, Al, Mn and Fe were measured by atomic absorption spectrometry, of 19 topsoil samples collected in the Teresina city urban area to discriminate natural and anthropic contributions and identify possible sources of pollution. The average concentrations of Cu, Zn, Pb and Cr of the urban soils were 6.11, 8.56, 32.12 and 7,17 mg/kg-1, respectively. Statistical analysis techniques, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA), were used to analyze the data. Mn, Ni and Cr levels were interpreted as natural contributions, whereas Pb, Zn and, in part, Cu were accounted for mainly by anthropic activities. High Pb levels were observed in the ancient avenues.
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This study presents a catalogue of synoptic patterns of torrential rainfall in northeast of the Iberian Peninsula (IP). These circulation patterns were obtained by applying a T-mode Principal Component Analysis (PCA) to a daily data grid (NCEP/NCAR reanalysis) at sea level pressure (SLP). The analysis made use of 304 days which recorded >100 mm in one or more stations in provinces of Barcelona, Girona and Tarragona (coastland area of Catalonia) throughout the 1950-2005 period. The catalogue comprises 7 circulation patterns showing a great variety of atmospheric conditions and seasonal or monthly distribution. Likewise, we computed the mean index value of the Western Mediterranean Oscillation index (WeMOi) for the synoptic patterns obtained by averaging all days grouped in each pattern. The results showed a clear association between the negative values of this teleconnection index and torrential rainfall in northeast of the IP. We therefore put forward the WeMO as an essential tool for forecasting heavy rainfall in northeast of Spain
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An activity for introducing hierarchical cluster analysis (HCA) and principal component analysis (PCA) during the Instrumental Analytical Chemistry course is presented. The posed problem involves the discrimination of mineral water samples according to their geographical origin. Thirty-seven samples of 9 different brands were considered and the results from the determination of Na, K, Mg, Ca, Sr and Ba were taken into account. Non-supervised methods for pattern recognition were explored to construct a dendrogram, score and loading plots. The devised activity can be adopted for introducing Chemometrics devoted to data handling, stressing its importance in the context of modern Analytical Chemistry.
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In this study atmospheric particulates of PAHs were measured in Araraquara, Piracicaba and São Paulo in July 2003 (sugarcane harvest season in Araraquara and Piracicaba) and in Araraquara in March of 2003. The results were normalized to the total PAH concentrations. Comparison among the sites and principal component analysis (PCA) were used to investigate possible tracers of emission. Fluoranthene and pyrene concentrations were higher in Piracicaba and Araraquara samples. These PAH were also responsible for the largest negative loadings on the second principal component and account for the negative scores and for the formation of the Araraquara and Piracicaba group.
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Energy dispersive X-ray fluorescence methodology (EDXRF) was used to determine Al, Ba, Ca, Cr, Fe, K, Mn, Pb, Rb, S, Si, Sr, Ti, V, Zn in pottery sherds from seven archaeological sites in the central region of Rio Grande do Sul State, Brazil. The potteries' chemical fingerprints from Ijuí River, Ibicuí Mirim River, Vacacaí Mirim River and Jacuí River were identified. Interactions between sites from the Jacuí River, Vacacaí Mirim River and Ibicui Mirim River could have occurred because some samples from these sites are overlapping in a principal component analysis (PCA) graphic. The pottery provenance could be the same.
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The hedonic level of commercial cachaças, was evaluated by consumers and by a tasters. The results of sensorial methods analyzed trough Principal Components Analysis, Hierarchical Cluster Analysis and the Pearson linear correlation indicated that the best classified cachaças were produced in copper stills and aged in oak casks. By contrast the worst classified exhibited as the main features be not aged and high alcohol percentage. The index of preference is positively correlated with the intensity of yellow color, wood flavor, sweetness and fruit aroma. There is a negative preference correlation with the acidity, the taste of alcohol and bitterness.