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Study of chemical changes and antioxidant activity variation induced by gamma-irradiation on wild mushrooms: comparative study through principal component analysis

Fernandes, Ângela; Barreira, João C.M.; Antonio, Amilcar L.; Santos, Pedro M.P.; Martins, Anabela; Oliveira, M.B.P.P.; Ferreira, Isabel C.F.R.
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
95.82%
Mushrooms are especially sensitive to senescence, browning, water loss and microbial attack. Furthermore, wild species are characterized for their seasonality, demanding the development of suitable preservation technology. Gamma-irradiation was previously tested in wild Lactarius deliciosus, being verified that its application up to 1 kGy did not imply significant changes in chemical parameters. Herein, the effects of higher gamma-irradiation doses, typically used in natural food matrices like fruits or vegetables, were assessed in Boletus edulis Bull.: Fr. and Hydnum repandum L.: Fr. by checking for changes in nutritional parameters, free sugars, tocopherols, fatty acids, organic acids and antioxidant activity indicators. To have representative samples, the used carpophores were collected in different maturity stages, using the same number of specimens for each stage and also for each mushroom species. The specific effects of each tested irradiation were evaluated in an integrated manner through principal component analysis. The correspondent biplots indicate that differences caused by gamma-irradiation are enough to separate irradiated and non-irradiated samples of both mushrooms. Nevertheless, nutritional profiles were not affected in high extension...

Relevant principal component analysis applied to the characterisation of Portuguese heather honey

Martins, Rui C.; Lopes, Victor V.; Valentão, Patrícia; Carvalho, João C. M. F.; Isabel, Paulo; Amaral, Maria T.; Batista, Maria T.; Andrade, Paula B.; Silva, Branca M.
Fonte: Taylor & Francis Publicador: Taylor & Francis
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
95.83%
The main purpose of this study was the characterisation of ‘Serra da Lousã’ heather honey by using novel statistical methodology, relevant principal component analysis, in order to assess the correlations between production year, locality and composition. Herein, we also report its chemical composition in terms of sugars, glycerol and ethanol, and physicochemical parameters. Sugars profiles from ‘Serra da Lousã’ heather and ‘Terra Quente de Tra´ s-os-Montes’ lavender honeys were compared and allowed the discrimination: ‘Serra da Lousã’ honeys do not contain sucrose, generally exhibit lower contents of turanose, trehalose and maltose and higher contents of fructose and glucose. Different localities from ‘Serra da Lousã ’ provided groups of samples with high and low glycerol contents. Glycerol and ethanol contents were revealed to be independent of the sugars profiles. These data and statistical models can be very useful in the comparison and detection of adulterations during the quality control analysis of ‘Serra da Lousã’ honey.; http://dx.doi.org/10.1080/14786410701825004

Análise de componentes principais na dinâmica da volatilidade implícita e sua correlação com o ativo objeto.; Principal component analysis over the implied volatility dynamic and its correlation with underlying.

Avelar, André Gnecco
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 03/07/2009 Português
Relevância na Pesquisa
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Como a volatilidade é a única variável não observada nas fórmulas padrão de apreçamento de opções, o mercado financeiro utiliza amplamente o conceito de volatilidade implícita, isto é, a volatilidade que ao ser aplicada na fórmula de apreçamento resulte no preço correto (observado) das opções negociadas. Por isso, entender como as volatilidades implícitas das diversas opções de dólar negociadas na BM&F, o objeto de nosso estudo, variam ao longo do tempo e como estas se relacionam é importante para a análise de risco de carteiras de opções de dólar/real bem como para o apreçamento de derivativos cambiais exóticos ou pouco líquidos. A proposta de nosso estudo é, portanto, verificar se as observações da literatura técnica em diversos mercados também são válidas para as opções de dólar negociadas na BM&F: que as volatilidades implícitas não são constantes e que há uma relação entre as variações das volatilidades implícitas e as variações do valor do ativo objeto. Para alcançar este objetivo, aplicaremos a análise de componentes principais em nosso estudo. Com esta metodologia, reduziremos as variáveis aleatórias que representam o processo das volatilidades implícitas em um número menor de variáveis ortogonais...

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
Relevância na Pesquisa
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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)...

Focused Principal Component Analysis : a graphical method for exploring dietary patterns; Análise de Componente Principal Focada : um método gráfico para explorar padrões alimentares

Canuto, Raquel; Camey, Suzi Alves; Gigante, Denise Petrucci; Menezes, Ana Maria Baptista; Olinto, Maria Teresa Anselmo
Tipo: Artigo de Revista Científica Formato: application/pdf
Português
Relevância na Pesquisa
95.85%
O presente estudo teve objetivo de apresentar a Análise de Componentes Principais Focada (ACPF) como um método exploratório para investigar padrões alimentares a partir de características da amostra. Para exemplificar utilizou-se as variáveis idade, renda e escolaridade de um banco de dados de 1.968 adultos. O consumo alimentar foi obtido através questionário de frequência alimentar (QFA) com 26 itens alimentares. As análises foram realizadas no programa R. Os gráficos gerados evidenciaram iniquidades socioeconômicas na conformação dos padrões alimentares. Alimentos integrais, frutas e verduras foram diretamente correlacionados com renda e escolaridade, e cereais refinados, gordura animal e pão branco tiveram associação inversa. A idade mostrou-se como associada inversamente a alimentos fast-food e industrializados e, diretamente, a um padrão “saudável” que inclui frutas, salada verde e outros vegetais. De maneira fácil e direta, a ACPF permitiu a visualização de correlações entre alimentos a partir de variáveis escolhidas como foco.; The aim of the present study was to introduce Focused Principal Component Analysis (FPCA) as a novel exploratory method for providing insight into dietary patterns that emerge based on a given characteristic of the sample. To demonstrate the use of FPCA...

Estudo da ocorrência de fluxos no perfil vertical do vento na baixa atmosfera com análise das componentes principais (ACP) e a sua relação com a precipitação no Rio Grande do Sul; Vertical wind profile uses a principal component analysis, and of their relation to precipitation events in Rio Grande do Sul

Corrêa, Cleber Souza; Clarke, Robin Thomas; Silveira, André Luiz Lopes da
Tipo: Artigo de Revista Científica Formato: application/pdf
Português
Relevância na Pesquisa
95.82%
Neste estudo busca-se entender as relações dos Jatos de Nível Baixo (JNB) e dos fluxos no perfil vertical do vento na geração de convecção em escala sinótica e a sua associação com a precipitação, observa-se o perfil vertical do vento através de radiossondagens realizadas no Aeroporto Internacional Salgado Filho em Porto Alegre, Estado do Rio Grande do Sul, Brasil. Estimam-se características predominantes da dinâmica dos fluxos dentro da baixa atmosfera, descrevendo a interação dos JNB e fluxos na geração da precipitação. Os JNB associados neste intenso transporte apresentam uma tendência de estarem ligados a eventos convectivos noturnos e na geração de Sistemas Convectivos de Mesoescala (SCM), que geram elevados índices pluviométricos que podem causar importante influência econômica. Utiliza-se a técnica da Análise das Componentes Principais para realização deste estudo, comparando suas componentes com a precipitação de sessenta e quatro estações pluviométricas sobre Estado do Rio Grande do Sul. O emprego desta metodologia facilita o entendimento da complexidade das interações das diferentes escalas meteorológicas envolvidas nos processos sinóticos de macro e mesoescala, mostrando neste método uma melhor representação das características dinâmicas dos processos baroclínicos na convecção. Em tal complexidade...

Seleção de variáveis para clusterização através de índices de importância das variáveis e Análise de Componentes Principais; Clustering variable selection through variable importance indices and principal component analysis

Cervo, Victor Leonardo
Tipo: dissertação Formato: application/pdf
Português
Relevância na Pesquisa
95.83%
A presente dissertação propõe novas abordagens para seleção de variáveis com vistas à formação de grupos representativos de observações. Para tanto, sugere um novo índice de importância das variáveis apoiado nos parâmetros oriundos da Análise de Componentes Principais (APC), o qual é integrado a uma sistemática do tipo forward para seleção de variáveis. A qualidade dos agrupamentos formados é medida através do Silhouette Index. Um estudo de simulação é projetado para avaliar a robustez e o desempenho da sistemática proposta em dados com diferentes níveis de correlação, ruído e número de observações a serem clusterizadas. Na sequência, é apresentada uma versão modificada da sistemática original, a qual utiliza funções kernel para remapeamento dos dados com vistas ao incremento da qualidade de clusterização e redução das variáveis retidas para formação dos agrupamentos. A versão modificada é aplicada em 3 bancos de dados da indústria química, aumentando a qualidade da clusterização medida pelo SI médio em 150% e utilizando em torno de 6% das variáveis originais.; This thesis proposes new approaches for variable selection aimed at forming representative groups of observations. For that matter...

Reduction capability of soil humic substances from the Rio Negro basin, Brazil, towards Hg(II) studied by a multimethod approach and principal component analysis (PCA)

Serudo, Ricardo Lima; de Oliveira, Luciana Camargo; Rocha, Julio Cesar; Paterlini, William Cesar; Rosa, Andre Henrique; da Silva, Heliandro Cordovil; Botero, Wander Gustavo
Fonte: Elsevier B.V. Publicador: Elsevier B.V.
Tipo: Artigo de Revista Científica Formato: 229-236
Português
Relevância na Pesquisa
95.83%
This paper characterizes humic substances (HS) extracted from soil samples collected in the Rio Negro basin in the state of Amazonas, Brazil, particularly investigating their reduction capabilities towards Hg(II) in order to elucidate potential mercury cycling/volatilization in this environment. For this reason, a multimethod approach was used, consisting of both instrumental methods (elemental analysis, EPR, solid-state NMR, FIA combined with cold-vapor AAS of Hg(0)) and statistical methods such as principal component analysis (PCA) and a central composite factorial planning method. The HS under study were divided into groups, complexing and reducing ones, owing to different distribution of their functionalities. The main functionalities (cor)related with reduction of Hg(II) were phenolic, carboxylic and amide groups, while the groups related with complexation of Hg(II) were ethers, hydroxyls, aldehydes and ketones. The HS extracted from floodable regions of the Rio Negro basin presented a greater capacity to retain (to complex, to adsorb physically and/or chemically) Hg(II), while nonfloodable regions showed a greater capacity to reduce Hg(II), indicating that HS extracted from different types of regions contribute in different ways to the biogeochemical mercury cycle in the basin of the mid-Rio Negro...

Genetic parameter estimates and principal component analysis of breeding values of reproduction and growth traits in female Canchim cattle

Buzanskas, M. E.; Savegnago, R. P.; Grossi, D. A.; Venturini, G. C.; Queiroz, S. A.; Silva, L. O C; Júnior, R. A. A. Torres; Munari, D. P.; Alencar, M. M.
Tipo: Artigo de Revista Científica Formato: 775-781
Português
Relevância na Pesquisa
95.91%
Phenotypic data from female Canchim beef cattle were used to obtain estimates of genetic parameters for reproduction and growth traits using a linear animal mixed model. In addition, relationships among animal estimated breeding values (EBVs) for these traits were explored using principal component analysis. The traits studied in female Canchim cattle were age at first calving (AFC), age at second calving (ASC), calving interval (CI), and bodyweight at 420 days of age (BW420). The heritability estimates for AFC, ASC, CI and BW420 were 0.03±0.01, 0.07±0.01, 0.06±0.02, and 0.24±0.02, respectively. The genetic correlations for AFC with ASC, AFC with CI, AFC with BW420, ASC with CI, ASC with BW420, and CI with BW420 were 0.87±0.07, 0.23±0.02, -0.15±0.01, 0.67±0.13, -0.07±0.13, and 0.02±0.14, respectively. Standardised EBVs for AFC, ASC and CI exhibited a high association with the first principal component, whereas the standardised EBV for BW420 was closely associated with the second principal component. The heritability estimates for AFC, ASC and CI suggest that these traits would respond slowly to selection. However, selection response could be enhanced by constructing selection indices based on the principal components. © CSIRO 2013.

Coprocessador neuro-genetico para analise de componentes principais; Neuro-Genetic Coprocessor for Principal Component Analysis

George Emmanuel Bozinis
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 31/07/2007 Português
Relevância na Pesquisa
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O propósito deste trabalho é estudar em detalhe a implementação em hardware de algoritmos neuro-genéticos. Uma representação numérica inédita com características neurais e genéticas e um algoritmo para sua utilização são apresentados e usados no desenvolvimento de um coprocessador com uma seção neural baseada na análise de componentes principais (PCA). As operações genéticas recombinação, mutação, mutação de máscara e intercâmbio, específicas para este modelo, são apresentadas. Também foi criada e implementada uma metodologia de cálculo da curva de ativação neural usando apenas lógica combinacional. Como resultado adicional a implementação, realizada na linguagem VHDL e seguindo a norma Wishbone, pode ser facilmente reutilizada; The intention of this work is to study the hardware implementation of neuro-genetic algorithms in detail. A novel numerical representation with neural and genetic characteristics and an algorithm for its utilization are presented and used in the development of a coprocessor with a neural section based on the principal component analysis (PCA). The genetic operations: crossover, mutation, mask mutation and swap, specific for this mode!, are presented. Also, a methodology for the calculation of the neural activation curve was created and implemented using only combinational logic. Additionally...

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.
Tipo: info:eu-repo/semantics/conferenceobject
Publicado em //2007 Português
Relevância na Pesquisa
85.87%
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.m?³.day ?¹(R1 – HRT of 8h; and, R2 – HRT of 2.5h) and 50 kg.m?³.day?¹ (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.

Predicting effects of toxic events to anaerobic granular sludge with quantitative image analysis and principal component analysis

Costa, J. C.; Alves, M. M.; Ferreira, E. C.
Tipo: info:eu-repo/semantics/conferenceobject
Publicado em 24/06/2008 Português
Relevância na Pesquisa
95.86%
Detergents and solvents are included in the list of compounds that can be inhibitory or toxic to anaerobic digestion processes. Industrial cleaning stages/processes produce vast amounts of contaminated wastewater. In order to optimize the control of these wastewaters it is important to know and predict the effects on the activity and physical properties of anaerobic aggregates in an early stage. Datasets gathering morphological, physiological and reactor performance information were created from three toxic shock loads (SL1 – 1.6 mgdetergent/L; SL2 – 3.1 mgdetergent/L; SL3 – 40 mgsolvent/L). The use of Principal Component Analysis (PCA) allowed the visualization of the main effects caused by the toxics, by clustering the samples according to its operational phase, exposure or recovery. The morphological parameters showed to be sensitive enough to detect the operational problems even before the COD removal efficiency decreased. Its high loadings in the plane defined by the first and second principal components, which gathers the higher variability in datasets, express the usefulness of monitor the biomass morphology in order to achieve a suitable control of the process. PCA defined a new latent variable t[1], gathering the most relevant variability in dataset...

Principal component analysis and quantitative image analysis to predict effects of toxics in anaerobic granular sludge

Costa, J. C.; Alves, M. M.; Ferreira, E. C.
Fonte: Elsevier Ltd. Publicador: Elsevier Ltd.
Tipo: Artigo de Revista Científica
Publicado em /02/2009 Português
Relevância na Pesquisa
95.86%
Principal component analysis (PCA) was applied to datasets gathering morphological, physiological and reactor performance information, from three toxic shock loads (SL1 – 1.6 mgdetergent/L; SL2 – 3.1 mgdetergent/L; SL3 – 40 mgsolvent/L) applied in an expanded granular sludge bed (EGSB) reactor. The PCA allowed the visualization of the main effects caused by the toxics, by clustering the samples according to its operational phase, exposure or recovery. The aim was to investigate the variables or group of variables that mostly contribute for the early detection of operational problems. The morphological parameters showed to be sensitive enough to detect the operational problems even before the COD removal efficiency decreased. As observed by the high loadings in the plane defined by the first and second principal components. PCA defined a new latent variable t[1], gathering the most relevant variability in dataset, that showed an immediate variation after the toxics were fed to the reactors. t[1] varied 262%, 254% and 80%, respectively, in SL1, SL2 and SL3. The high loadings/weights of the morphological parameters associated with this new variable express its influence in shock load monitoring and control, and consequently in operational problems recognition.; Fundação para a Ciência e a Tecnologia (FCT) -Bolsa SFRH/BD/13317/2003...

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
85.9%
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...

Focused Principal Component Analysis: a graphical method for exploring dietary patterns

Canuto,Raquel; Camey,Suzi; Gigante,Denise P.; Menezes,Ana M. B.; Olinto,Maria Teresa Anselmo
Fonte: Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz Publicador: Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/11/2010 Português
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95.83%
The aim of the present study was to introduce Focused Principal Component Analysis (FPCA) as a novel exploratory method for providing insight into dietary patterns that emerge based on a given characteristic of the sample. To demonstrate the use of FPCA, we used a database of 1,968 adults. Food intake was obtained using a food frequency questionnaire covering 26 food items. The focus variables used for analysis were age, income, and schooling. All analyses were carried out using R software. The graphs generated show evidence of socioeconomic inequities in dietary patterns. Intake of whole-wheat foods, fruit, and vegetables was positively correlated with income and schooling, whereas for refined cereals, animal fats (lard), and white bread this correlation was negative. Age was inversely associated with intake of fast-food and processed foods and directly associated with a pattern that included fruit, green salads, and other vegetables. In an easy and direct fashion, FPCA allowed us to visualize dietary patterns based on a given focus variable.

Principal component analysis of changes due to water stress for some osmolytes, pigments and antioxidant enzymes in Gmelina arborea Robx: leaves from trees planted in northern Colombia

Crespo,Sandra C.; Moreno-Chacón,Andres L.; Rojas,Andrea; Melgarejo,Luz M.
Fonte: Sociedade Brasileira de Química Publicador: Sociedade Brasileira de Química
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2011 Português
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Gmelina arborea is a tree having great economic impact due to its advantages as a fast-growing timber tree. G. arborea is currently being planted on the North Coast of Colombia, especially on the dry plains near the Caribbean. However, the stress conditions produced by drought to which they are periodically subjected lead to plantation loss. This study was thus aimed at measuring catalase, peroxidase and ascorbate peroxidase activities as well as total sugar, reducing sugar, proline, carotenoids, chlorophyll A, B and total chlorophyll content in G. arborea leaves sampled during three seasons of the year. Principal component analysis showed that the measured variables had patterns depending on age and season, in addition to an inverse correlation between chlorophyll A, B and total chlorophyll and the other measured variables.

Antioxidant capacity, total phenolic content, fatty acids and correlation by principal component analysis of exotic and native fruits from Brazil

Ribeiro,Alessandra B.; Bonafé,Elton G.; Silva,Beatriz C.; Montanher,Paula F.; Santos Júnior,Oscar O.; Boeing,Joana S.; Visentainer,Jesuí V.
Fonte: Sociedade Brasileira de Química Publicador: Sociedade Brasileira de Química
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/05/2013 Português
Relevância na Pesquisa
95.82%
The antioxidant capacities of seven exotic and native fruits from Brazil were evaluated using DPPH•, ABTS•+ and FRAP assays, in addition to their total phenolic content and fatty acid composition. Murici and dovialis presented the highest total phenolic contents (243.42 and 205.98 mg GAE 100 g-1, respectively), and the highest antioxidant capacities by the FRAP assay (24.97 and 23.70 µmol Fe2+ g-1, respectively). In the DPPH• and ABTS•+ assays, dovialis presented the highest antioxidant capacity, 9.59 and 10.41 TE g-1, respectively. The highest alpha-linolenic and linoleic acid contents were found in siriguela (107.86 mg FA g-1 TL) and tomatinho do mato (215.50 mg FA g-1 TL), respectively. The principal component analysis (PCA) of fatty acids yielded three significant PCs, which accounted for 99.75% of the data set total variance. The PCA data of the antioxidant analyses yielded two significant PCs, which accounted for 97.00% of the total variance.

Assessment of walker-assisted gait based on Principal Component Analysis and wireless inertial sensors

Martins,Maria; Elias,Arlindo; Cifuentes,Carlos; Alfonso,Manuel; Frizera,Anselmo; Santos,Cristina; Ceres,Ramón
Fonte: SBEB - Sociedade Brasileira de Engenharia Biomédica Publicador: SBEB - Sociedade Brasileira de Engenharia Biomédica
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/09/2014 Português
Relevância na Pesquisa
95.88%
INTRODUCTION:This study investigates a gait research protocol to assess the impact of a walker model with forearm supports on the kinematic parameters of the lower limb during locomotion. METHODS: Thirteen healthy participants without any history of gait dysfunction were enrolled in the experimental procedure. Spatiotemporal and kinematic gait parameters were calculated by using wireless inertial sensors and analyzed with Principal Component Analysis (PCA). The PCA method was selected to achieve dimension reduction and evaluate the main effects in gait performance during walker-assisted gait. Additionally, the interaction among the variables included in each Principal Component (PCs) derived from PCA is exposed to expand the understanding of the main differences between walker-assisted and unassisted gait conditions. RESULTS:The results of the statistical analysis identified four PCs that retained 65% of the data variability. These components were associated with spatiotemporal information, knee joint, hip joint and ankle joint motion, respectively. CONCLUSION: Assisted gait by a walker model with forearm supports was characterized by slower gait, shorter steps, larger double support phase and lower body vertical acceleration when compared with normal...

Optimization of end milling parameters under minimum quantity lubrication using principal component analysis and grey relational analysis

Murthy,K. Sundara; Rajendran,I.
Fonte: Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM Publicador: Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/09/2012 Português
Relevância na Pesquisa
95.85%
Machining is the major reliable practice in accomplishment of metal cutting industries. The accelerated growing competition demands top superior and large quantity with low cost products. Metal working fluids have significant fragment of manufacturing cost and causes ecological impacts and health problems. This work attempts to advance a competent machining alignment with no ecological impacts. The prediction of quality characteristics and enhancement of machining field are consistently accepting great interest in machining sectors to compress the accomplishment costs. In this paper, GA based ANN prediction model proposes to envisage the quality characteristics of surface roughness and tool wear. The comparison of predicted and experimental values acknowledges the precision of the model. The end milling experiments are conducted beneath minimum quantity lubrication. This paper as well deals with the multiple objective optimization with principal component analysis, grey relational analysis and Taguchi method. ANOVA was carried out to determine each parameter contribution percentage on quality characteristics. The results show that cutting speed is the most influencing parameter followed by feed velocity, lubricant flow rate and depth of cut. The confirmation tests acknowledge that the proposed multiple-objective methodology is able in determining optimum machining parameters for minimum surface roughness and tool wear.

Principal Component Analysis applied to digital image compression

Santo,Rafael do Espírito
Fonte: Instituto Israelita de Ensino e Pesquisa Albert Einstein Publicador: Instituto Israelita de Ensino e Pesquisa Albert Einstein
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/06/2012 Português
Relevância na Pesquisa
95.95%
OBJECTIVE: To describe the use of a statistical tool (Principal Component Analysis ? PCA) for the recognition of patterns and compression, applying these concepts to digital images used in Medicine. METHODS: The description of Principal Component Analysis is made by means of the explanation of eigenvalues and eigenvectors of a matrix. This concept is presented on a digital image collected in the clinical routine of a hospital, based on the functional aspects of a matrix. The analysis of potential for recovery of the original image was made in terms of the rate of compression obtained. RESULTS: The compressed medical images maintain the principal characteristics until approximately one-fourth of their original size, highlighting the use of Principal Component Analysis as a tool for image compression. Secondarily, the parameter obtained may reflect the complexity and potentially, the texture of the original image. CONCLUSION: The quantity of principal components used in the compression influences the recovery of the original image from the final (compacted) image.