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‣ Fault detection in the Tennessee Eastman benchmark process using dynamic principal components analysis based on decorrelated residuals (DPCA-DR)

Rato, Tiago J.; Reis, Marco S.
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica
Português
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Current multivariate control charts for monitoring large scale industrial processes are typically based on latent variable models, such as principal component analysis (PCA) or its dynamic counterpart when variables present auto-correlation (DPCA). In fact, it is usually considered that, under such conditions, DPCA is capable to effectively deal with both the cross- and auto-correlated nature of data. However, it can easily be verified that the resulting monitoring statistics (T2 and Q, also referred by SPE) still present significant auto-correlation. To handle this issue, a set of multivariate statistics based on DPCA and on the generation of decorrelated residuals were developed, that present low auto-correlation levels, and therefore are better positioned to implement SPC in a more consistent and stable way (DPCA-DR). The monitoring performance of these statistics was compared with that from other alternative methodologies for the well-known Tennessee Eastman process benchmark. From this study, we conclude that the proposed statistics had the highest detection rates on 19 out of the 21 faults, and are statistically superior to their PCA and DPCA counterparts. DPCA-DR statistics also presented lower auto-correlation, which simplifies their implementation and improves their reliability.

‣ Biomimetic oxidative treatment of spruce wood studied by pyrolysis-molecular beam mass spectrometry coupled with multivariate analysis and (13)C-labeled tetramethylammonium hydroxide thermochemolysis: implications for fungal degradation of wood

ARANTES, Valdeir; QIAN, Yuhui; KELLEY, Stephen S.; MILAGRES, Adriane M. F.; FILLEY, Timothy R.; JELLISON, Jody; GOODELL, Barry
Fonte: SPRINGER Publicador: SPRINGER
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
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In this work, pyrolysis-molecular beam mass spectrometry analysis coupled with principal components analysis and (13)C-labeled tetramethylammonium hydroxide thermochemolysis were used to study lignin oxidation, depolymerization, and demethylation of spruce wood treated by biomimetic oxidative systems. Neat Fenton and chelator-mediated Fenton reaction (CMFR) systems as well as cellulosic enzyme treatments were used to mimic the nonenzymatic process involved in wood brown-rot biodegradation. The results suggest that compared with enzymatic processes, Fenton-based treatment more readily opens the structure of the lignocellulosic matrix, freeing cellulose fibrils from the matrix. The results demonstrate that, under the current treatment conditions, Fenton and CMFR treatment cause limited demethoxylation of lignin in the insoluble wood residue. However, analysis of a water-extractable fraction revealed considerable soluble lignin residue structures that had undergone side chain oxidation as well as demethoxylation upon CMFR treatment. This research has implications for our understanding of nonenzymatic degradation of wood and the diffusion of CMFR agents in the wood cell wall during fungal degradation processes.; Purdue University; Wood Science and Technology Laboratories[5192/06-4]

‣ Utilização de análise de componentes principais em séries temporais; Use of principal component analysis in time series

Teixeira, Sérgio Coichev
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 12/04/2013 Português
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Um dos principais objetivos da análise de componentes principais consiste em reduzir o número de variáveis observadas em um conjunto de variáveis não correlacionadas, fornecendo ao pesquisador subsídios para entender a variabilidade e a estrutura de correlação dos dados observados com uma menor quantidade de variáveis não correlacionadas chamadas de componentes principais. A técnica é muito simples e amplamente utilizada em diversos estudos de diferentes áreas. Para construção, medimos a relação linear entre as variáveis observadas pela matriz de covariância ou pela matriz de correlação. Entretanto, as matrizes de covariância e de correlação podem deixar de capturar importante informações para dados correlacionados sequencialmente no tempo, autocorrelacionados, desperdiçando parte importante dos dados para interpretação das componentes. Neste trabalho, estudamos a técnica de análise de componentes principais que torna possível a interpretação ou análise da estrutura de autocorrelação dos dados observados. Para isso, exploramos a técnica de análise de componentes principais para o domínio da frequência que fornece para dados autocorrelacionados um resultado mais específico e detalhado do que a técnica de componentes principais clássica. Pelos métodos SSA (Singular Spectrum Analysis) e MSSA (Multichannel Singular Spectrum Analysis)...

‣ Estudo da relação estrutura-atividade de saponinas hemolíticas e/ou imunoadjuvantes mediante uso de análise multivariada; Study of the structure-activity relationship of adjuvant and/or hemolytic saponins by use of multivariate analysis

Kaiser, Samuel; Pavei, Cabral; Gonzales Ortega, George
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Artigo de Revista Científica Formato: application/pdf
Português
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Entre as diversas atividades biológicas relatadas para as saponinas, merecem destaque aquelas relacionadas ao aumento da resposta imune e a ruptura das membranas dos eritrócitos. No desenvolvimento de vacinas, ambas as propriedades exercem atividades antagônicas, contudo, as informações sobre as relações estrutura-atividade são relativamente escassas e, às vezes, conflitantes. O presente trabalho visa contribuir no estabelecimento das relações estruturais envolvidas com as atividades imunoadjuvante e hemolítica de saponinas triterpênicas. Para isso, foram selecionadas vinte saponinas de estrutura triterpênica, isoladas das espécies Aesculus hippocastanum, Dolichos lablab e Glycine max. A relação entre grupamentos substituintes do anel triterpênico e as atividades biológicas foi estudada mediante análise de agrupamentos e análise de componentes principais. Os resultados confirmam a importância da presença de açúcares em C-3 para a atividade hemolítica. Porém o efeito causado pela presença de uma hidroxila em C-16, de CH2OH em C-17, de uma acetila em C-22 e de um grupamento acila em C-21 sobre essa atividade parece ser mais acentuado. Já a presença de uma hidroxila em C-21, de uma metila em C-17 e de dois açúcares ligados à aglicona parece ser determinante para a atividade imunoadjuvante. Além disso...

‣ Estimates of genetic parameters, and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population

Savegnago, R. P.; Caetano, S. L.; Ramos, S. B.; Nascimento, G. B.; Schmidt, G. S.; Ledur, M. C.; Munari, D. P.
Fonte: Poultry Science Assoc Inc Publicador: Poultry Science Assoc Inc
Tipo: Artigo de Revista Científica Formato: 2174-2188
Português
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES); Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); The objectives of this paper were to identify the phenotypic egg-laying patterns in a White Leghorn line mainly selected for egg production, to estimate genetic parameters of traits related to egg production and to evaluate the genetic association between these by principal components analysis to identify trait(s) that could be used as selection criteria to improve egg production. Records of 54 wk of egg production from a White Leghorn population were used. The data set contained records of the length: width ratio of eggs at 32, 37, and 40 wk of age; egg weight at 32, 37, and 40 wk of age; BW at 54 and 62 wk of age; age at first egg; early partial egg production rate from 17 to 30 wk and from 17 to 40 wk of age; late partial egg production rate from 30 to 70 wk and from 40 to 70 wk of age; and total egg production rate (TEP). The estimates of genetic parameters between these traits were estimated by the restricted maximum likelihood method. Multivariate analyses were performed: a hierarchical cluster analysis, a nonhierarchical clustering analysis by the k-means method of weekly egg production rate to describe the egg-laying patterns of hens...

‣ Exploração de dados multivariados de fontes e extratos de antocianinas ultilizando análise de componentes princiaipais e método do vizinho mais proximo; Exploring multivariate data of sources and extracts of anthocyanins using principal components analysis and method of nearest neighbor

Martha Maria Andreotti Favaro
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 29/02/2012 Português
Relevância na Pesquisa
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Antocianinas (ACYS) são corantes naturais responsáveis pela coloração de frutas, hortaliças, flores e grãos. Novas perspectivas de usos de antocianinas em diversos segmentos industriais estimulam estudos analíticos para sistematizar a identificação e a classificação de fontes e extratos desses corantes. Neste trabalho foram utilizadas fontes de ACYS como frutas típicas brasileiras: AMORA (Morus nigra), amora preta (Rubus sp.), jabuticaba (Myrciaria cauliflora), jambolão (Syzygium cumini), jussara (Euterpe edulis Mart.), morango (Fragaria x ananassa Duch) e uva (Vitis vinífera e Vitis vinífera L. Brasil); hortaliças: alface roxa (Lactuca sativa), berinjela (Solanum melongena), cebola roxa (Allium cepa), rabanete (Raphanus sativus), repolho roxo (Brassica oleraceae) e flores: beijo-turco (Impatiens walleriana), gerânio (Pelargonium hortorum e Pelargonium peltatum L.), hibisco (Hibiscus sinensis e Hibiscus syriacus) e hortênsia (Hydrangea macrophylla). A literatura descreve diversas técnicas para análise de ACYS em vegetais e seus extratos, com destaque para cromatografia líquida de alta eficiência (HPLC), espectrometria de massas (MS) e espectrofotometria (UV-Vis), sendo que todas elas foram aplicadas neste trabalho...

‣ Integration of morphological and physiological data through Principal Component Analysis to identify the effect of organic overloads on anaerobic granular sludge

Costa, J. C.; Alves, M. M.; Ferreira, E. C.
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Conferência ou Objeto de Conferência
Publicado em //2007 Português
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Morphological parameters, obtained by quantitative image analysis techniques, together with physiological and reactor performance data were inserted in principal components analysis (PCA) to detect operational problems and control of high rate anaerobic reactors during organic overloads. Four lab-scale Expanded Granular Sludge Blanket reactors were used to performed organic overloads of 18 kg.mˉ³.day ˉ¹(R1 – HRT of 8h; and, R2 – HRT of 2.5h) and 50 kg.mˉ³.dayˉ¹ (R3 - fed for 3 days; and, R4 - fed for 16 days). The application of PCA allowed the visualization of the main effects caused by the organic overloads. The first Principal Component (PC) extracted, in each shock load, retains enough information to group observations in agreement with operational conditions (normal or overload). The variables from quantitative image analysis presented high loadings, suggesting that might play an important role in organic overloads control.; Fundação para a Ciência e a Tecnologia (FCT) - SFRH/BD/13317/2003, POCI/AMB/60141/2004.

‣ Multiple imputation and maximum likelihood principal component analysis of incomplete multivariate data from a study of the ageing of port

Ho, P.; Silva, M. C. M.; Hogg, T. A.
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica
Publicado em //2001 Português
Relevância na Pesquisa
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A multivariate data matrix containing a number of missing values was obtained from a study on the changes in colour and phenolic composition during the ageing of port. Two approaches were taken in the analysis of the data. The first involved the use of multiple imputation (MI) followed by principal components analysis (PCA). The second examined the use of maximum likelihood principal component analysis (MLPCA). The use of multiple imputation allows for missing value uncertainty to be incorporated into the analysis of the data. Initial estimates of missing values were firstly calculated using the Expectation Maximization algorithm (EM), followed by Data Augmentation (DA) in order to generate five imputed data matrices. Each complete data matrix was subsequently analysed by PCA, then averaging their principal component (PC) scores and loadings to give an estimation of errors. The first three PCs accounted for 93.3% of the explained variance. Changes to colour and monomeric anthocyanin composition were explained on PC1 (79.63% explained variance), phenolic composition and hue mainly on PC2 (8.61% explained variance) and phenolic composition and the formation of polymeric pigment on PC3 (5.04% explained variance). In MLPCA estimates of measurement uncertainty is incorporated in the decomposition step...

‣ Identification of Tibicen cicada species by a Principal Components Analysis of their songs

Ohya,Eiji
Fonte: Academia Brasileira de Ciências Publicador: Academia Brasileira de Ciências
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/06/2004 Português
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Specific identification of three Tibicen cicadas, T. japonicus, T. flammatus and T. bihamatus, by their chirping sounds was carried out using Principal Components Analysis (PCA). High quality recordings of each species were used as the standards. The peak and mean frequencies and the pulse rate were used as the variables. Out of 12 samples recorded in the fields one fell in the vicinity of T. japonicus and all other were positioned near T. bihamatus. Then the cluster analysis of the PCA scores clearly separated each species and allocated the samples in the same way.

‣ Comparative study of metal contents in Brazilian coffees cultivated by conventional and organic agriculture applying principal component analysis

Santos,José S. dos; Santos,Maria Lúcia P. dos; Conti,Melina M.
Fonte: Sociedade Brasileira de Química Publicador: Sociedade Brasileira de Química
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/01/2010 Português
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The aim of this study was to evaluate of availability of nutrients and toxic elements in green coffees produced in traditional, technological and transitional organic farms in Southwest Bahia-Brazil. Levels of the nutrients minerals were determined directly in samples of soils and coffee tissues from four farms by flame atomic absorption spectrometry (FAAS) and toxic elements (Cr, Ni, Cd and Pb) by inductively coupled plasma optical emission spectrometry (ICP OES). The application of statistical methods (cluster and principal components analysis) revealed the importance of the conversion period to guarantee a product genuinely organic during the change to organic agriculture. On the other hand, the study of correlations between agricultural methods and metals concentrations in coffee suggested that Cd, Cu, Zn and other toxic elements contained in some inorganic fertilizers used in the traditional and technological coffee farms may cause an increase of toxic metals concentration in the crop soil, be taken up by plants, and passed on in the food chain.

‣ Simulation of an industrial wastewater treatment plant using artificial neural networks and principal components analysis

Oliveira-Esquerre,K.P.; Mori,M.; Bruns,R.E.
Fonte: Brazilian Society of Chemical Engineering Publicador: Brazilian Society of Chemical Engineering
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2002 Português
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This work presents a way to predict the biochemical oxygen demand (BOD) of the output stream of the biological wastewater treatment plant at RIPASA S/A Celulose e Papel, one of the major pulp and paper plants in Brazil. The best prediction performance is achieved when the data are preprocessed using principal components analysis (PCA) before they are fed to a backpropagated neural network. The influence of input variables is analyzed and satisfactory prediction results are obtained for an optimized situation.

‣ Using supervised principal components analysis to assess multiple pollutant effects

Roberts, Steven; Martin, Michael
Fonte: Universidade Nacional da Austrália Publicador: Universidade Nacional da Austrália
Tipo: Journal article; Published Version Formato: 6 pages
Português
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BACKGROUND: Many investigations of the adverse health effects of multiple air pollutants analyze the time series involved by simultaneously entering the multiple pollutants into a Poisson log-linear model. This method can yield unstable parameter estimates when the pollutants involved suffer high intercorrelation ; therefore, traditional approaches to dealing with multicollinearity, such as principal component analysis (PCA) , have been promoted in this context. OBJECTIVES: A characteristic of PCA is that its construction does not consider the relationship between the covariates and the adverse health outcomes. A refined version of PCA, supervised principal components analysis (SPCA) , is proposed that specifically addresses this issue. METHODS: Models controlling for long-term trends and weather effects were used in conjunction with each SPCA and PCA to estimate the association between multiple air pollutants and mortality for U.S. cities. The methods were compared further via a simulation study. RESULTS: Simulation studies demonstrated that SPCA, unlike PCA, was successful in identifying the correct subset of multiple pollutants associated with mortality. Because of this property, SPCA and PCA returned different estimates for the relationship between air pollution and mortality. CONCLUSIONS: Although a number of methods for assessing the effects of multiple pollutants have been proposed...

‣ Characterization of transition diets spanning infancy and toddlerhood: a novel, multiple-time-point application of principal components analysis

Brazionis, L.; Golley, R.; Mittinty, N.; Smithers, L.; Emmett, P.; Northstone, K.; Lynch, J.
Fonte: Amer Soc Clinical Nutrition Publicador: Amer Soc Clinical Nutrition
Tipo: Artigo de Revista Científica
Publicado em //2012 Português
Relevância na Pesquisa
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BACKGROUND: The portrayal of diet over time is a natural progression from the characterization of diet at single time points. The transition dietary period, a dynamic period of rapid dietary change spanning infancy and toddlerhood when children shift from a milk-based to a food-based diet, has not been characterized. OBJECTIVE: The objective was to summarize variation in dietary intakes spanning infancy and toddlerhood. DESIGN: A prospective principal components analysis was applied to dietary intakes from 3 successive follow-ups of children enrolled in the ALSPAC (Avon Longitudinal Study of Parents and Children). The frequency of food and beverage consumption was assessed via questionnaire at ages 6, 15, and 24 mo (n = 2169). RESULTS: Two types of transition diet were identified. The first transition diet was characterized by the consumption of home-prepared and raw foods ("healthy") at all time points and the second by ready-prepared and discretionary foods ("less healthy") consistently over time. Higher educational level and maternal age were associated with higher scores on the "healthy" diet, whereas younger maternal age and a lower educational level were associated with higher scores on the "less healthy" diet. Maternal BMI, number of older siblings...

‣ Principal components analysis for quality evaluation of cooled banana 'Nanicão' in different packing

Sanches,Juliana; Leal,Paulo Ademar Martins; Saravali,José Henrique; Antoniali,Silvia
Fonte: Sociedade Brasileira de Fruticultura Publicador: Sociedade Brasileira de Fruticultura
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/08/2003 Português
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This work aims determinate the evaluation of the quality of 'Nanicão' banana, submitted to two conditions of storage temperature and three different kinds of package, using the technique of the Analysis of Principal Components (ACP), as a basis for an Analysis of Variance. The fruits used were 'Nanicão' bananas, at ripening degree 3, that is, more green than yellow. The packages tested were: "Torito" wood boxes, load capacity: 18 kg; "½ box" wood boxes, load capacity: 13 kg; and cardboard boxes, load capacity: 18 kg. The temperatures assessed were: room temperature (control); and (13±1ºC), with humidity controlled to 90±2,5%. Fruits were discarded when a sensory analysis determined they had become unfit for consumption. Peel coloration, percentages of imperfection, fresh mass, total acidity, pH, total soluble solids and percentages of sucrose were assessed. A completely randomized design with a 2-factorial treatment structure (packing X temperature) was used. The obtained data were analyzed through a multivariate analysis known as Principal Components Analysis, using S-plus 4.2. The conclusion was that the best packages to preserve the fruit were the ½ box ones, which proves that it is necessary to reduce the number of fruits per package to allow better ventilation and decreases mechanical injuries and ensure quality for more time.

‣ Métodos robustos de estimación de componentes principales funcionales y el modelo de componentes principales comunes; Robust methods for estimation of functional principal components and for the model of common principal components

Bali, Juan Lucas
Fonte: Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires Publicador: Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires
Tipo: info:eu-repo/semantics/doctoralThesis; tesis doctoral; info:eu-repo/semantics/publishedVersion Formato: application/pdf
Publicado em //2012 Português
Relevância na Pesquisa
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En muchas situaciones prácticas, los datos se registran sobre un período de tiempo o corresponden a imágenes. Por esta razón, conviene considerarlos como realizaciones de un proceso estocástico en lugar de discretizarlos y estudiarlos como realizaciones de datos multivariados. Un método ampliamente usado para describir los principales modos de variación de las observaciones es el de componentes principales funcionales. Sin embargo, los procedimientos clásicos basados en el desvío estándar o el operador de covarianza muestral son muy sensibles a datos atípicos. Para resolver este problema, en esta tesis, se introducen estimadores robustos para las componentes principales mediante un enfoque basado en el método de projection–pursuit. Estimadores de projection–pursuit, para el caso finito– dimensional, fueron inicialmente propuestos en Huber (1981) como una forma de obtener estimadores robustos de la matriz de covarianza. Posteriormente, fueron considerados por Li y Chen (1985) para el problema de componentes principales como una aproximación directa al problema sin necesidad de obtener estimadores robustos de la matriz de escala (ver, también Huber, 1985). En esta tesis, se extiende dicha propuesta al caso funcional. Por otra parte...

‣ On properties of functional principal components analysis

Hall, Peter; Hosseini-Nasab, Seyed
Fonte: Aiden Press Publicador: Aiden Press
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
77.317397%
Functional data analysis is intrinsically infinite dimensional; functional principal component analysis reduces dimension to a finite level, and points to the most significant components of the data. However, although this technique is often discussed, it

‣ Perceptual audio classification using principal component analysis

Burka, Zak
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
Português
Relevância na Pesquisa
77.172075%
The development of robust algorithms for the recognition and classification of sensory data is one of the central topics in the area of intelligent systems and computational vision research. In order to build better intelligent systems capable of processing environmental data accurately, current research is focusing on algorithms which try to model the types of processing that occur naturally in the human brain. In the domain of computer vision, these approaches to classification are being applied to areas such as facial recognition, object detection, motion tracking, and others. This project investigates the extension of these types of perceptual classification techniques to the realm of acoustic data. As part of this effort, an algorithm for audio fingerprinting using principal component analysis for feature extraction and classification was developed and tested. The results of these experiments demonstrate the feasibility of such a system, and suggestions for future implementation enhancements are examined and proposed.

‣ Application of PQS for image quality analysis in visible spectral imaging

Sun, Qun; Fairchild, Mark
Fonte: Society for Imaging Science and Technology Publicador: Society for Imaging Science and Technology
Tipo: Proceedings
Português
Relevância na Pesquisa
77.317397%
An image quality investigation in visible spectral imaging was performed. Spectral images were simulated using different number of imaging channels, wavelength steps, and noise levels based on practical spectral imaging systems. A mean opinion score (MOS) was determined from a subjective visual assessment scale experiment for image quality of spectral images rendered to a three-channel display. A set of partial image distortion measures, including color difference for color images, were defined based on classified and quantified actual distortions produced by spectral imaging systems. Principal components analysis was then carried out to quantify the correlation between distortion factors. Finally, a multiple regression analysis (MRA) was carried out between the principal component vectors and the measured MOS values to determine the picture quality scale (PQS). The obtained quality metric, PQS, had high correlation with the subjective measure, MOS. The importance of contribution of the distortion factors in the image quality metric was also evaluated.; Location: Scottsdale, Arizona - Publisher book can be found here: http://www.imaging.org/store/physpub.cfm?seriesid=4&pubid=303

‣ Non-linear principal component analysis (approximation by a second-order Taylor series)

Viggiano, John
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
Português
Relevância na Pesquisa
77.689556%
Linear Principal Component Analysis (LPCA) has been applied in multivariate analysis because of its many optimality properties. However, when applied to locate singularities in a set of data, LPCA is only able to locate linear singularities. If the problem being considered tends to produce variables with non-linear relationships, such as with non-linear regression, LPCA is necessarily of limited utility in identifying singularities. Non-linear generalizations of PCA have been suggested in the literature. Essentially, these involve augmenting the data with higher-order terms, in particular square and cross product terms, and running a LPCA on the augmented data set. The problem with this approach is that the fundamental property of parsimony is violated because the number of principal components is greater than the number of original variates. Further, the dimensionality of the augmented data set increases quadratically with respect to the number of original variates. This greatly increases the computational load for practical-sized problems. A new method is proposed in this thesis. It involves writing the general non-linear model as a Taylor Series and truncating after the second-order terms. The data are centered about their means...

‣ The application of principal components analysis to the study of postural control; A aplicação da análise dos componentes principais para o estudo do controle postural

Mochizuki, Luis; Amadio, Alberto Carlos
Fonte: Universidade de São Paulo. Escola de Educação Física e Esporte Publicador: Universidade de São Paulo. Escola de Educação Física e Esporte
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; ; ; Formato: application/pdf
Publicado em 01/03/2007 Português
Relevância na Pesquisa
87.52267%
O objetivo do estudo é aplicar a análise dos componentes principais (ACP) no estudo do ajuste postural antecipatório (APA) e compensatório (APC). Utilizamos uma plataforma de força para determinar o COP e momento de força no apoio e um eletromiográfo para obter a atividade eletromiográfica (EMG) do mm. tibial anterior esquerdo e direito e mm. gastrocnêmico lateral esquerdo e direito. Participaram 43 crianças saudáveis divididas em grupos (Não-Ginasta, Ginasta Intermediário e Ginasta Avançado) que executaram a elevação da coxa esquerda o mais rápido possível e ficaram paradas durante 2 s com os olhos abertos ou fechados. Analisamos as variáveis atividade eletromiográfica, centro de pressão, momentos de força e força de reação do solo durantes os ajustes posturais antecipatório e compensatório. Usamos ACP para estudar as variáveis. Com os olhos abertos, as variâncias dos componentes principais do Momento de força e EMG apresentaram diferença entre grupos e ajustes posturais. Com os olhos fechados, as variâncias de COP, momento de força e EMG apresentaram diferenças entre grupos e ajustes posturais. Cada variável apresentou redução do número de dimensões do sistema e as variabilidades nos componentes do COP...