832 resultados para PRINCIPAL COMPONENTS


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The full-scale base-isolated structure studied in this dissertation is the only base-isolated building in South Island of New Zealand. It sustained hundreds of earthquake ground motions from September 2010 and well into 2012. Several large earthquake responses were recorded in December 2011 by NEES@UCLA and by GeoNet recording station nearby Christchurch Women's Hospital. The primary focus of this dissertation is to advance the state-of-the art of the methods to evaluate performance of seismic-isolated structures and the effects of soil-structure interaction by developing new data processing methodologies to overcome current limitations and by implementing advanced numerical modeling in OpenSees for direct analysis of soil-structure interaction.

This dissertation presents a novel method for recovering force-displacement relations within the isolators of building structures with unknown nonlinearities from sparse seismic-response measurements of floor accelerations. The method requires only direct matrix calculations (factorizations and multiplications); no iterative trial-and-error methods are required. The method requires a mass matrix, or at least an estimate of the floor masses. A stiffness matrix may be used, but is not necessary. Essentially, the method operates on a matrix of incomplete measurements of floor accelerations. In the special case of complete floor measurements of systems with linear dynamics, real modes, and equal floor masses, the principal components of this matrix are the modal responses. In the more general case of partial measurements and nonlinear dynamics, the method extracts a number of linearly-dependent components from Hankel matrices of measured horizontal response accelerations, assembles these components row-wise and extracts principal components from the singular value decomposition of this large matrix of linearly-dependent components. These principal components are then interpolated between floors in a way that minimizes the curvature energy of the interpolation. This interpolation step can make use of a reduced-order stiffness matrix, a backward difference matrix or a central difference matrix. The measured and interpolated floor acceleration components at all floors are then assembled and multiplied by a mass matrix. The recovered in-service force-displacement relations are then incorporated into the OpenSees soil structure interaction model.

Numerical simulations of soil-structure interaction involving non-uniform soil behavior are conducted following the development of the complete soil-structure interaction model of Christchurch Women's Hospital in OpenSees. In these 2D OpenSees models, the superstructure is modeled as two-dimensional frames in short span and long span respectively. The lead rubber bearings are modeled as elastomeric bearing (Bouc Wen) elements. The soil underlying the concrete raft foundation is modeled with linear elastic plane strain quadrilateral element. The non-uniformity of the soil profile is incorporated by extraction and interpolation of shear wave velocity profile from the Canterbury Geotechnical Database. The validity of the complete two-dimensional soil-structure interaction OpenSees model for the hospital is checked by comparing the results of peak floor responses and force-displacement relations within the isolation system achieved from OpenSees simulations to the recorded measurements. General explanations and implications, supported by displacement drifts, floor acceleration and displacement responses, force-displacement relations are described to address the effects of soil-structure interaction.

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Une taxonomie révisée et une connaissance des limites d’espèces demeurent toujours importantes dans les points chauds en biodiversité comme les Antilles où de nombreuses espèces endémiques sont retrouvées. Des limites d’espèces divergentes impliquent un différent nombre d’espèces retrouvées dans un écosystème, ce qui peut exercer une influence sur les décisions prises face aux enjeux de conservation. Les genres Gesneria et Rhytidophyllum qui forment les principaux représentants de la famille des Gesneriaceae dans les Antilles comprennent plusieurs taxons aux limites d’espèces ambigües et quelques espèces qui ont des sous-espèces reconnues. C’est le cas de Gesneria viridiflora (Decne.) Kuntze qui comprend quatre sous-espèces géographiquement isolées et qui présentent des caractères végétatifs et reproducteurs similaires et variables. Une délimitation d’espèces approfondie de ce complexe d’espèce est effectuée ici à partir d’une approche de taxonomie intégrative considérant des données morphologiques, génétiques et bioclimatiques. Les données morphologiques quantitatives et qualitatives obtenues à partir de spécimens d’herbier sont utilisées pour délimiter des groupes morphologiques à l’aide d’une analyse en coordonnées principales. Ces groupes sont ensuite testés à l’aide de séquences d’ADN de quatre régions nucléaires en utilisant une méthode bayesienne basée sur la théorie de la coalescence. Finalement, les occurrences et les valeurs de variables de température et de précipitation qui y prévalent sont utilisées dans une analyse en composantes principales bioclimatique pour comparer les groupes délimités morphologiquement et génétiquement. Les résultats de l’analyse morphologique multivariée supportent la distinction entre les groupes formés par les sous-espèces actuellement reconnues de G. viridiflora. Les résultats, incluant des données génétiques, suggèrent une distinction jusqu’ici insoupçonnée des populations du Massif de la Hotte au sud-ouest d’Haïti qui sont génétiquement plus rapprochées des populations de Cuba que de celles d’Hispaniola. Bioclimatiquement, les groupes délimités par les analyses morphologiques et génétiques sont distincts. L’approche de taxonomie intégrative a permis de distinguer cinq espèces distinctes plutôt que les quatre sous-espèces acceptées jusqu’à aujourd’hui. Ces espèces sont : G. acrochordonanthe, G. quisqueyana, G. sintenisii, G. sylvicola et G. viridiflora. Une carte de distribution géographique, un tableau de la nouvelle taxonomie applicable et une clé d’identification des espèces sont présentés. La nouvelle taxonomie déterminée dans cette étude démontre un endémisme insoupçonné dans plusieurs régions du point chaud en biodiversité des Antilles et souligne l’importance d’investiguer les limites d’espèces dans les groupes diversifiés comprenant des taxons aux limites d’espèces incomprises.

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Multi-frequency eddy current measurements are employed in estimating pressure tube (PT) to calandria tube (CT) gap in CANDU fuel channels, a critical inspection activity required to ensure fitness for service of fuel channels. In this thesis, a comprehensive characterization of eddy current gap data is laid out, in order to extract further information on fuel channel condition, and to identify generalized applications for multi-frequency eddy current data. A surface profiling technique, generalizable to multiple probe and conductive material configurations has been developed. This technique has allowed for identification of various pressure tube artefacts, has been independently validated (using ultrasonic measurements), and has been deployed and commissioned at Ontario Power Generation. Dodd and Deeds solutions to the electromagnetic boundary value problem associated with the PT to CT gap probe configuration were experimentally validated for amplitude response to changes in gap. Using the validated Dodd and Deeds solutions, principal components analysis (PCA) has been employed to identify independence and redundancies in multi-frequency eddy current data. This has allowed for an enhanced visualization of factors affecting gap measurement. Results of the PCA of simulation data are consistent with the skin depth equation, and are validated against PCA of physical experiments. Finally, compressed data acquisition has been realized, allowing faster data acquisition for multi-frequency eddy current systems with hardware limitations, and is generalizable to other applications where real time acquisition of large data sets is prohibitive.

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Quantitative methods can help us understand how underlying attributes contribute to movement patterns. Applying principal components analysis (PCA) to whole-body motion data may provide an objective data-driven method to identify unique and statistically important movement patterns. Therefore, the primary purpose of this study was to determine if athletes’ movement patterns can be differentiated based on skill level or sport played using PCA. Motion capture data from 542 athletes performing three sport-screening movements (i.e. bird-dog, drop jump, T-balance) were analyzed. A PCA-based pattern recognition technique was used to analyze the data. Prior to analyzing the effects of skill level or sport on movement patterns, methodological considerations related to motion analysis reference coordinate system were assessed. All analyses were addressed as case-studies. For the first case study, referencing motion data to a global (lab-based) coordinate system compared to a local (segment-based) coordinate system affected the ability to interpret important movement features. Furthermore, for the second case study, where the interpretability of PCs was assessed when data were referenced to a stationary versus a moving segment-based coordinate system, PCs were more interpretable when data were referenced to a stationary coordinate system for both the bird-dog and T-balance task. As a result of the findings from case study 1 and 2, only stationary segment-based coordinate systems were used in cases 3 and 4. During the bird-dog task, elite athletes had significantly lower scores compared to recreational athletes for principal component (PC) 1. For the T-balance movement, elite athletes had significantly lower scores compared to recreational athletes for PC 2. In both analyses the lower scores in elite athletes represented a greater range of motion. Finally, case study 4 reported differences in athletes’ movement patterns who competed in different sports, and significant differences in technique were detected during the bird-dog task. Through these case studies, this thesis highlights the feasibility of applying PCA as a movement pattern recognition technique in athletes. Future research can build on this proof-of-principle work to develop robust quantitative methods to help us better understand how underlying attributes (e.g. height, sex, ability, injury history, training type) contribute to performance.

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Objective: To determine the psychometric properties of two scales designed to examine attitudes regarding palliative care: Comfort Scale in Palliative Care (CSPC, Pereira et al.) and Tanatophobia Scale (TS, Merrill et al.)Method: Seventy-seven students who completed an online course on psychosocial aspects of palliative care offered by the Latin American Association of Palliative Care participated in the study. They also completed the scales before and after the course. Construct validity and reliability of the CSPC and the TS were assessed using a Principal Components Analysis, internal reliability coefficient and test-retest reliability. Further, comparative statistics between the pre-course and post-course results were obtained in order to determine changes in attitudes.Results: The Principal Components Analysis showed satisfactory fit to the data. 3 components were extracted: two for the CSPC and one for the TS, which explained 55.37% of the variance. Internal consistency coefficients were satisfactory in all cases and Cronbach´s Alphas were satisfactory for all the scales, particularly for the CSPC. Test-retest reliability in t1 and t2 was found to be non significant, indicating that measures were not related in time. Regarding pre-course/post-course comparisons, significant changes in comfort assisting patients (p = 0.004) and comfort assisting families (p = 0.001) following the course were identified, but changes in thanatophobia were non significant (p > 0.05).Conclusions: both scales are valid and reliable. Attitudes regarding the practice of palliative care and how they change, particularly regarding psychosocial issues, can be accurately measured using the examined scales.

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A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

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The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

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[EN]We investigate mechanisms which can endow the computer with the ability of describing a human face by means of computer vision techniques. This is a necessary requirement in order to develop HCI approaches which make the user feel himself/herself perceived. This paper describes our experiences considering gender, race and the presence of moustache and glasses. This is accomplished comparing, on a set of 6000 facial images, two di erent face representation approaches: Principal Components Analysis (PCA) and Gabor lters. The results achieved using a Support Vector Machine (SVM) based classi er are promising and particularly better for the second representation approach.

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The World Heritage List (WHL) is widely considered a powerful tool for national tourism campaigns. Sites inscribed on the WHL by the United Nations Educational, Scientific, and Cultural Organization (UNESCO) are commonly treated as catholicons in promoting the tourism industry, which in turn helps to promote economic growth and development. This study analyzes local community perceptions of the importance of the World Heritage Site (WHS) classification of the historic center of the Portuguese city of E ́vora. The research also includes an analysis of the local residents’ perceived tourism impacts on the municipality of E ́ vora. The methodology consists of quan- titative research based on a self-administered survey applied to convenience sam- ples of local residents of the municipality of E ́ vora in the beginning of 2014. The local residents’ perceptions of the level of importance of the WHS classification to the municipality and its impact in the increase of tourists is analyzed. Positive and negative tourism impacts are then ranked and a principal components factor analysis is employed separately to the two groups of impacts in order to identify underlying dimensions associated with residents’ perceptions on tourism develop- ment. Based on the results of the factor analysis, independent sample t-tests are used to investigate differences regarding positive and negative tourism impacts between residents that live near and far from the historic center, and between residents who work/have worked in the tourism sector and residents that work/ have worked in other sectors.

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Thesis (Master's)--University of Washington, 2016-07

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Currently the organizations are passing for continuous cycles of changes due to necessity of survival in the work market. The administration of the future points a way to the organizations of today and tomorrow, the search of the competitiveness from loyalty and motivation of its staff. Of this form, the model of the Auditoria do Sistema Humano (ASH), developed for Spanish researchers and that now it is being applied in Brazil, contemplates a series of dimensions about Human Resources management quality in the companies and the organizational effectiveness, such as the environment where the company is inserted, the strategies, the organizational drawing, the psychological and psychosocial processes, e the reached results. In this direction, the present research analyzed the factors of job satisfaction and organizational commitment, making, also, a relation of causality between the same ones. The quantitative-descriptive research had as population the employees of twenty three nourishing industries of the State of Rio Grande do Norte (Brazil), registered in the Federacy of the Industries of the state. The collection of the data occurred for the months of October of 2005 and March of 2006, by means of the application of questionnaire of model ASH. The sample was composed for 197 employees, however it was observed presence of five outliers, that they had been excluded from the analysis of the data. To extract the dimensions of the satisfaction and the commitment and identification the factorial analysis was used, with extraction method of principal components, rotation Varimax and normalization Kaiser. The gotten dimensions had been evaluated with the calculation of the coefficient Alpha of Cronbach. The factorial analysis of the pointers of the organizational commitment and identification had extracted ten factors. Of these, four had gotten significance of the analyses inside: affective commitment, values commitment, continuance commitment and necessity commitment. The result of the analysis of the pointers of job satisfaction indicated four factors: extrinsic, motivations, relation with the friends and auto-accomplishment. To deal with the data the relation between job satisfaction and organizational commitment it was used technique of multiple regression. The correlation between commitment and satisfaction was satisfactory, detaching the affective commitment with bigger index of correlation, followed of the affective one

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BACKGROUND: Health-related quality of life (HRQL) assessment is an important measure of the impact of a wide range of disease process on an individual. To date, no HRQL tool has been evaluated in an Iranian population with cardiovascular disorders, specifically myocardial infarction, a major cause of mortality and morbidity. The MacNew Heart Disease Health-related Quality of Life instrument is a disease-specific HRQL questionnaire with satisfactory validity and reliability when applied cross-culturally. METHOD: A Persian version of MacNew was prepared by both forward and backward translation by bilinguals after which a feasibility test was performed. Consecutive patients (n = 51) admitted to a coronary care unit with acute myocardial infarction were recruited for measurement of their HRQL with retest one month after discharge in the follow-up clinic. Principal components analysis, intra-class correlation reliability, internal consistency, and test-retest reliability were assessed. RESULTS: Trivial rates of missing data confirmed the acceptability of the tool. Principal component analysis revealed that the three domains, emotional, social and physical, performed as well as in the original studies. Internal consistency was high and comparable to other studies, ranging from 0.92 for the emotional and physical domains, to 0.94 for the social domain, and to 0.95 for the Global score. Domain means of 5, 5.3 and 4.9 for emotional, physical and social respectively indicate that our Iranian population has similar emotional and physical but worse social HRQL scores. Test-retest analysis showed significant correlation in emotional and physical domains (P < 0.05). CONCLUSION: The Persian version of the MacNew questionnaire is comparable to the English version. It has high internal consistency and reasonable reproducibility, making it an appropriate specific quality of life tool for population-based studies and clinical practice in Iran in patients who have survived an acute myocardial infraction. Further studies are needed to confirm its validity in larger populations with cardiovascular disease

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In a industrial environment, to know the process one is working with is crucial to ensure its good functioning. In the present work, developed at Prio Biocombustíveis S.A. facilities, using process data, collected during the present work, and historical process data, the methanol recovery process was characterized, having started with the characterization of key process streams. Based on the information retrieved from the stream characterization, Aspen Plus® process simulation software was used to replicate the process and perform a sensitivity analysis with the objective of accessing the relative importance of certain key process variables (reflux/feed ratio, reflux temperature, reboiler outlet temperature, methanol, glycerol and water feed compositions). The work proceeded with the application of a set of statistical tools, starting with the Principal Components Analysis (PCA) from which the interactions between process variables and their contribution to the process variability was studied. Next, the Design of Experiments (DoE) was used to acquire experimental data and, with it, create a model for the water amount in the distillate. However, the necessary conditions to perform this method were not met and so it was abandoned. The Multiple Linear Regression method (MLR) was then used with the available data, creating several empiric models for the water at distillate, the one with the highest fit having a R2 equal to 92.93% and AARD equal to 19.44%. Despite the AARD still being relatively high, the model is still adequate to make fast estimates of the distillate’s quality. As for fouling, its presence has been noticed many times during this work. Not being possible to directly measure the fouling, the reboiler inlet steam pressure was used as an indicator of the fouling growth and its growth variation with the amount of Used Cooking Oil incorporated in the whole process. Comparing the steam cost associated to the reboiler’s operation when fouling is low (1.5 bar of steam pressure) and when fouling is high (reboiler’s steam pressure of 3 bar), an increase of about 58% occurs when the fouling increases.

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Une taxonomie révisée et une connaissance des limites d’espèces demeurent toujours importantes dans les points chauds en biodiversité comme les Antilles où de nombreuses espèces endémiques sont retrouvées. Des limites d’espèces divergentes impliquent un différent nombre d’espèces retrouvées dans un écosystème, ce qui peut exercer une influence sur les décisions prises face aux enjeux de conservation. Les genres Gesneria et Rhytidophyllum qui forment les principaux représentants de la famille des Gesneriaceae dans les Antilles comprennent plusieurs taxons aux limites d’espèces ambigües et quelques espèces qui ont des sous-espèces reconnues. C’est le cas de Gesneria viridiflora (Decne.) Kuntze qui comprend quatre sous-espèces géographiquement isolées et qui présentent des caractères végétatifs et reproducteurs similaires et variables. Une délimitation d’espèces approfondie de ce complexe d’espèce est effectuée ici à partir d’une approche de taxonomie intégrative considérant des données morphologiques, génétiques et bioclimatiques. Les données morphologiques quantitatives et qualitatives obtenues à partir de spécimens d’herbier sont utilisées pour délimiter des groupes morphologiques à l’aide d’une analyse en coordonnées principales. Ces groupes sont ensuite testés à l’aide de séquences d’ADN de quatre régions nucléaires en utilisant une méthode bayesienne basée sur la théorie de la coalescence. Finalement, les occurrences et les valeurs de variables de température et de précipitation qui y prévalent sont utilisées dans une analyse en composantes principales bioclimatique pour comparer les groupes délimités morphologiquement et génétiquement. Les résultats de l’analyse morphologique multivariée supportent la distinction entre les groupes formés par les sous-espèces actuellement reconnues de G. viridiflora. Les résultats, incluant des données génétiques, suggèrent une distinction jusqu’ici insoupçonnée des populations du Massif de la Hotte au sud-ouest d’Haïti qui sont génétiquement plus rapprochées des populations de Cuba que de celles d’Hispaniola. Bioclimatiquement, les groupes délimités par les analyses morphologiques et génétiques sont distincts. L’approche de taxonomie intégrative a permis de distinguer cinq espèces distinctes plutôt que les quatre sous-espèces acceptées jusqu’à aujourd’hui. Ces espèces sont : G. acrochordonanthe, G. quisqueyana, G. sintenisii, G. sylvicola et G. viridiflora. Une carte de distribution géographique, un tableau de la nouvelle taxonomie applicable et une clé d’identification des espèces sont présentés. La nouvelle taxonomie déterminée dans cette étude démontre un endémisme insoupçonné dans plusieurs régions du point chaud en biodiversité des Antilles et souligne l’importance d’investiguer les limites d’espèces dans les groupes diversifiés comprenant des taxons aux limites d’espèces incomprises.