926 resultados para Multivariate Statistical Process Monitoring


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In this study, 73 South American red wines (Vitis vinifera) from 5 varietals were classified based on sensory quality, retail price and antioxidant activity and characterised in relation to their phenolic composition. ORAC and DPPH assays were assessed to determine the antioxidant activity, and sensory analysis was conducted by seven professional tasters using the Wine Spirits Education Trust`s structured scales. The use of multivariate statistical techniques allowed the identification of wines with the best combination of sensory characteristics, price and antioxidant activity. The most favourable varieties were Malbec, Cabernet Sauvignon, and Syrah produced in Chile and Argentina. Conversely, Pinot Noir wines displayed the lowest sensory characteristics and antioxidant activity. These results suggest that the volatile compounds may be the main substances responsible for differentiating red wines on the basis of sensory evaluation. (C) 2011 Elsevier Ltd. All rights reserved.

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The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

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This paper is part of a large study to assess the adequacy of the use of multivariate statistical techniques in theses and dissertations of some higher education institutions in the area of marketing with theme of consumer behavior from 1997 to 2006. The regression and conjoint analysis are focused on in this paper, two techniques with great potential of use in marketing studies. The objective of this study was to analyze whether the employement of these techniques suits the needs of the research problem presented in as well as to evaluate the level of success in meeting their premisses. Overall, the results suggest the need for more involvement of researchers in the verification of all the theoretical precepts of application of the techniques classified in the category of investigation of dependence among variables.

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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

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Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

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The present study aimed investigate the age and gender influence on maximal molar bite force and at outlining the criteria for normal masticatory muscle development in a sample of 177 Brazilian Caucasian dentate individuals aged 7-80 years divided into five age groups: I(7-12 years), II (13-20 years), III (21-40 years), IV (41-60 years), and V (61-80 years). Except for Group V, which comprised nine women and eight men, all groups were equally divided in respect to gender (20 M/20 F). Bite force was recorded with a mouth-adapted 1000 N dynamometer and the highest out of three records was regarded as the maximal bite force. The data were submitted to multivariate statistical analysis (SPSS 17.0 p < 0.05). Effects of group and gender were found, but no interactions between them. The ANOVA showed significant differences between groups bilaterally. Bonferroni`s test showed that group I had significantly lower bite force means at both sides as compared to all groups, except group V. No differences were found between the left and right sides. In all the groups, gender was found to be a significant factor associated with maximal bite force. A global comparison including all the subjects and measures showed that the means of men were approximately 30% higher than those of women, within-group comparisons yielded similar results in all groups. Muscle thickness was measured with a SonoSite Titan ultrasound tool using a high-resolution real-time 56 mm/10 MHz linear-array transducer. Three ultrasound images were obtained from the bilateral masseter and temporal muscles at rest and at maximal voluntary contraction. The means of the three measures in each clinical condition were analyzed with multivariate statistical analysis (SPSS 17.0 p < 0.05). A gradual increase in thickness of the masseter and temporal muscles was found both at rest and maximal voluntary contraction for groups I to IV, whereas a decrease in muscle thickness was observed in group V. Multivariate analysis showed that in both conditions there was an effect of group and gender. The study of the development of the stomatognathic system in relation to age and gender can provide useful data for the identification of normal and impaired functioning patterns. The results of this study indicate that age and gender are associated with structural and functional alterations in the muscles of the stomatognathic system. (C) 2010 Elsevier Ltd. All rights reserved.

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It is common for a real-time system to contain a nonterminating process monitoring an input and controlling an output. Hence, a real-time program development method needs to support nonterminating repetitions. In this paper we develop a general proof rule for reasoning about possibly nonterminating repetitions. The rule makes use of a Floyd-Hoare-style loop invariant that is maintained by each iteration of the repetition, a Jones-style relation between the pre- and post-states on each iteration, and a deadline specifying an upper bound on the starting time of each iteration. The general rule is proved correct with respect to a predicative semantics. In the case of a terminating repetition the rule reduces to the standard rule extended to handle real time. Other special cases include repetitions whose bodies are guaranteed to terminate, nonterminating repetitions with the constant true as a guard, and repetitions whose termination is guaranteed by the inclusion of a fixed deadline. (C) 2002 Elsevier Science B.V. All rights reserved.

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A absorção de água por carcaças de frango na etapa de pré-resfriamento da linha abate representa uma característica de qualidade importante relacionada ao rendimento do produto final. Uma forma de manter o padrão de qualidade de um produto é garantir que as etapas do processo sejam estáveis e replicáveis. Ao empregar o Controle Estatístico de Processo (CEP) é possível obter estabilidade e melhorias nos processos, por meio da redução da variabilidade. Neste contexto, o objetivo deste trabalho foi a aplicação de gráficos de controle, análise de correlação, estatística descritiva, testes de hipóteses e regressão linear múltipla na linha de abate de um abatedouro-frigorífico de aves para monitorar a variabilidade da absorção de água pelas carcaças de frango após a etapa de pré-resfriamento. Como resultado, verificou-se que o teor de absorção de água das carcaças de frango apresentou elevada variabilidade, sendo que 10% (8/80) das carcaças apresentaram absorção de água superior ao limite de 8% definido pela legislação brasileira. Do total de 16 variáveis de entrada analisadas, as mais impactantes no teor de absorção de água foram o “tempo de retenção da carcaça no pré-chiller” e o “tempo de espera da carcaça após a etapa de gotejamento”. Entretanto, o modelo de regressão obtido apresentou baixa correlação (R²=0,16) que foi associada à elevada variabilidade da variável-resposta. Os resultados da estatística descritiva demonstraram que as variáveis de entrada também apresentaram elevada variabilidade, com coeficiente de variação entre 7,95 e 63,5%. Verificou-se, pela análise dos gráficos de controle de medida individual e da amplitude móvel, que 15 das 16 variáveis de entrada se apresentaram fora de controle estatístico assim como a variável-resposta. Baseado no fluxograma e na descrição das etapas da linha de abate, previamente realizados, atribuiu-se à falta de padronização na condução das etapas e de procedimentos para o controle de qualidade das operações na linha de abate como fatores relevantes que poderiam estar associados à presença de causas especiais no processo. Concluiu-se que para reduzir a elevada variabilidade das variáveis e eliminar as causas especiais presentes são necessários ajustes operacionais para, dessa forma, obter um processo mais estável e mais uniforme garantindo o padrão de qualidade das carcaças de frango em relação ao teor de absorção de água.

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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

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Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

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Esta dissertação apresenta um estudo da capacidade do processo inserido uma empresa de panificação. Antes de iniciar o estudo propriamente dito, foi realizada uma calibração à balança na qual este estudo seria realizado. Os índices de capacidade do processo têm como principal finalidade verificar se a média e a variabilidade do processo estão em concordância com o alvo e os limites de especificação. Esta verificação permite o ajustamento do processo de maneira a reduzir a produção de produtos defeituosos. Neste trabalho foram utilizados os índices de capacidade considerando que as condições são ideais, isto é, quando existe normalidade nas amostras. Quando as condições não são ideais, como foi verificado, foram utilizadas técnicas para o cálculo dos índices de capacidade para este tipo de situações. A aplicação da metodologia de análise da capacidade do processo foi realizada com sucesso com recurso a amostras retiradas numa balança calibrada para o efeito.

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A Distribuição Individual Diária em Dose Unitária deve assegurar o maior rigor no Processo de Distribuição de Medicamentos, o que nem sempre se verificou no Hospital Pedro Hispano, dado que as Doses Unitárias devolvidas pelos Serviços de Internamento, nem sempre seguiam os Parâmetros de Qualidade. Assim, desenvolveu-se um estudo quasi-experimental, longitudinal, prospetivo e analítico, entre 1 de Março a 30 de Junho de 2012, no qual se analisaram as Doses Unitárias, devolvidas pelos Serviços de Internamento da Unidade Local de Saúde de Matosinhos a funcionam com Distribuição Individual Diária em Dose Unitária, tendo-se recolhido as não conformes relativamente aos Parâmetros de Qualidade instituídos. Na 1.ª fase do estudo (Recolha de amostras), foram contabilizadas 337 amostras, correspondentes a uma perda de 471 €. Na 2.ª fase do estudo (Implementação de acções correctivas às amostras previamente recolhidas), foram rejeitadas definitivamente 129 amostras, correspondentes a uma perda de 198 €. Na 4.ª fase do estudo (Segunda recolha de amostras), foram contabilizadas 228 amostras, correspondentes a uma perda de 199 €. A 3.ª fase do estudo incluiu a divulgação dos resultados às enfermeiras chefes dos serviços envolvidos no estudo e a 5.ª fase a comparação dos resultados obtidos na 1.ª, 2.ª e 4.ª fase do estudo. As amostras foram recolhidas em 16 serviços de internamento, sendo os valores monetários mais relevantes associados ao Espessante para alimentos líquidos e ao Imipeno + Cilastatina. A prática observada e sujeita a estudo aumenta os riscos associados ao consumo do medicamento e os custos relativos ao Processo, sendo de eliminar. A sua monitorização deve constituir uma rotina, uma vez que houve mudança de comportamentos. A redução/eliminação desta prática não conforme conduz à integração de novas tarefas com valor acrescentado, com aumento da fiabilidade do Processo.

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Dissertação apresentada na faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Industrial