929 resultados para Principal component analysis discriminant analysis
Resumo:
Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.
Resumo:
Psychometric analysis of the AF5 multidimensional scale of self-concept in a sample of adolescents and adults in Catalonia. The aim of this study is to carry out a psychometric study of the AF5 scale in a sample of 4.825 Catalan subjects from 11 to 63 years-old. They are students from secondary compulsory education (ESO), from high school, middle-level vocational training (CFGM) and from the university. Using a principal component analysis (PCA) the theoretical validity of the components is established and the reliability of the instrument is also analyzed. Differential analyses are performed by gender and normative group using a 2 6 factorial design. The normative group variable includes the different levels classifi ed into 6 sub-groups: university, post-compulsory secondary education (high school and CFGM), 4th of ESO, 3rd of ESO, 2nd of ESO and 1st of ESO. The results indicate that the reliability of the Catalan version of the scale is similar to the original scale. The factorial structure also fi ts with the original model established beforehand. Signifi cant differences by normative group in the four components of self-concept explored (social, family, academic/occupational and physical) are observed. By gender, signifi cant differences appear in the component of physical self-concept, academic and social but not in the family component
Resumo:
The spatial and temporal retention of metals has been studied in water and sediments of the Gavião River, Anagé and Tremedal Reservoirs, located in the semi-arid region, Bahia - Brazil, in order to identify trends in the fluxes of metals from the sediments to the water column. The determination of metals was made by ICP OES and ET AAS. The application of statistical methods showed that this aquatic system presents suitable conditions to move Cd2+ and Pb2+ from the water column to the sediment.
Resumo:
This study examined the spatial and temporal variations of 13 physico-chemical parameters in water and sediment samples collected along the rural and urban section of Verruga Stream. The metal concentrations were determined by FAAS. The conductivity and the concentration of Na+, Cl-, and Ca2+ showed the largest variations in the urban area demonstrating that these parameters are appropriate indicators of urban contamination. The application of cluster and principal component analysis showed that the Cd2+ and Mn2+ are associated with the use of fertilizers in the rural area.
Resumo:
This work shows results on the characterization, by liquid chromatography coupled to high resolution tandem mass spectrometry (LC-IT-TOF-MS) with electrospray ionization, of organic compounds present in raw and treated effluents from a combined sewage treatment systems (upflow anaerobic sludge blanket-trickling filter). The sewage samples were prepared by C18 solid phase extraction and the spectra obtained from the various extracts were submitted to principal component analysis to evaluate their pattern and identify the major deprotonated species. Some target compounds were submitted to semiquantitative analysis, using phenolphtalein as internal standard. The results showed the anaerobic step had little impact on the removal of anionic surfactants (LAS), fatty acids, and some contaminantes such as bisphenol A and bezafibrate, whereas the aerobic post-treatment was very efficient in removing these organics.
Resumo:
This paper presents the analytical application of a novel electronic tongue based on voltammetric sensors array. This device was used in the classification of wines aged in barrels of different origins and toasting levels. Furthermore, a study of correlation between the response of the electronic tongue and the sensory and chemical characterization of samples was carried out. The results were evaluated by applying both principal component analysis and cluster analysis. The samples were clearly classified. Their distribution showed a high correspondence degree with the characteristics of the analyzed wines, it also showed similarity with the classification obtained from organoleptic analysis.
Resumo:
In this study honey samples produced in the southwest of Bahia were characterized based on physicochemical and mineral (Ca, Mg, Na, K, Mn, Fe and Zn) composition. The metals were determined by atomic absorption spectrophotometry. The application of multivariate analysis showed that the honey colors are consequence of the mineral and physicochemical compositions. The darkest honey samples are characterized by higher values of pH and for presenting a strong relationship with Ca and Fe content.
Resumo:
Bulk and supported molybdenum based catalysts, modified by nickel, phosphorous or tungsten were studied by NEXAFS spectroscopy at the Mo L III and L II edges. The techniques of principal component analysis (PCA) together with a linear combination analysis (LCA) allowed the detection and quantification of molybdenum atoms in two different coordination states in the oxide form of the catalysts, namely tetrahedral and octahedral coordination.
Resumo:
This work aims to study spatial and seasonal variability of some chemical-physical parameters in the Turvo/Grande watershed, São Paulo State, Brazil. Water samples were taken monthly, 2007/07-2008/11, from fourteen sampling stations sited along the Turvo, Preto and Grande Rivers and its main tributaries. The Principal Component Analysis and hierarchical cluster analysis showed two distinct groups in this watershed, the first one associated for the places more impacted by domestic effluent (lower levels of dissolved oxygen in the studied region). The sampling places located to downstream (Turvo and Grande rivers) were discriminate by diffuse source of pollutants from flooding and agriculture runoffs in a second group.
Resumo:
In this work, the volatile chromatographic profiles of roasted Arabica coffees, previously analyzed for their sensorial attributes, were explored by principal component analysis. The volatile extraction technique used was the solid phase microextraction. The correlation optimized warping algorithm was used to align the gas chromatographic profiles. Fifty four compounds were found to be related to the sensorial attributes investigated. The volatiles pyrrole, 1-methyl-pyrrole, cyclopentanone, dihydro-2-methyl-3-furanone, furfural, 2-ethyl-5-methyl-pyrazine, 2-etenyl-n-methyl-pyrazine, 5-methyl-2-propionyl-furan compounds were important for the differentiation of coffee beverage according to the flavour, cleanliness and overall quality. Two figures of merit, sensitivity and specificity (or selectivity), were used to interpret the sensory attributes studied.
Resumo:
In this work, the organic compounds of cigar samples from different brands were analyzed. The compound extraction was made using the matrix solid-phase dispersion (MSPD) technique, followed by gas chromatography and identification by mass spectrometry (GC-MS) and standards, when available. Thirty eight organic compounds were found in seven different brands. Finally, with the objective of characterizing and discriminating the cigar samples, multivariate statistical analyses were applied to data, e.g.; principal component analysis (PCA) and hierarchical cluster analysis (HCA). With such analyses, it was possible to discriminate three main groups of three quality levels.
Resumo:
The knowledge of the structure characteristic of the Organic Matter is important for the understanding of the natural process. In this context aquatic humic substances (principal fraction) were isolated from water sample collected from the two distinct rivers, using procedure recommended for International Humic Substances Society and characterized by elemental analysis, electron paramagnetic resonance and nuclear magnetic resonance (13C NMR). The results were interpreted using principal component analysis (PCA) and the statistical analyses showed different in the structural characteristics of the aquatic humic substances studied.
Resumo:
A fruit chemical composition reflects its maturation stage. For coffee, it is also the reflex of the post-harvesting processing type, dry, semi-wet and wet. The object of this work was to verify if headspace solid phase microextraction coupled to gas chromatography (HS-SPME-GC) could be used to discriminate between samples harvested in different maturation stages and treated by different processes. With application of principal component analysis to the area of 117 compounds extracted by SPME, using divinylbenzene/Carboxen/polydimethylsiloxane fiber, it was possible to discriminate, in the roasted and ground coffee, the maturity stage and processing type used .
Resumo:
This work applied a 2² factorial design to the optimization of the extraction of seven elements (calcium, magnesium, potassium, iron, zinc, copper and manganese) in brachiaria leaves, determined by flame atomic absorption spectrometry. The factors sample mass and digestion type were evaluated at two levels: 200/500 mg, and dry/wet, respectively. Principal component analysis allowed simultaneous discrimination of all the significant effects in one biplot. Wet digestion and mass of 200 mg were considered the best conditions. The decrease of 60% in sample mass allowed to save costs and reagents. The method was validated through the estimation of figures of merit.
Resumo:
This manuscript aims to show the basic concepts and practical application of Principal Component Analysis (PCA) as a tutorial, using Matlab or Octave computing environment for beginners, undergraduate and graduate students. As a practical example it is shown the exploratory analysis of edible vegetable oils by mid infrared spectroscopy.