935 resultados para PRINCIPAL COMPONENTS-ANALYSIS


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Tree island ecosystems are important and distinct features of Florida Everglades wetlands. We described the inter-relationships among abiotic factors describing seasonally flooded tree islands and characterized plant–soil relationships in tree islands occurring in a relatively unimpacted area of the Everglades. We used Principal Components Analysis (PCA) to reduce our multi-factor dataset, quantified forest structure and vegetation nutrient dynamics, and related these vegetation parameters to PCA summary variables using linear regression analyses. We found that, of the 21 abiotic parameters used to characterize the ecosystem structure of seasonally flooded tree islands, 13 parameters were significantly correlated with four principal components, and they described 78% of the variance among the study islands. Most variation was described by factors related to soil oxidation and hydrology, exemplifying the sensitivity of tree island structure to hydrologic conditions. PCA summary variables describing tree island structure were related to variability in Chrysobalanus icaco (L.) canopy cover, Ilex cassine (L.) and Salix caroliniana (Michx.) canopy cover, Myrica cerifera (L.) plot frequency, litter turnover, % phosphorus resorption of co-dominant species, and nitrogen nutrient-use efficiency. This study supported findings that vegetation characteristics can be sensitive indicators of variability in tree island ecosystem structure. This study produced valuable, information which was used to recommend ecological targets (i.e. restoration performance measures) for seasonally flooded tree islands in more impacted regions of the Everglades landscape.

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The authors examine underlying dimensions of private club leadership using principal components analysis. The data were collected between 1996 and 2003 from 702 club managers or club chief operating officers who are members of the Club Managers Association of America (CMAA). Five factors - innovation, vision, inner values, stewardship, and communication - were identified as essentials of private club leadership.

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TEXL86 and TEXH86 are organic palaeothermometers based on the lipids of Group 1 Crenarchaeota, recently proposed as a modified version of the original TEX86 index, but with significantly improved geographical coverage. Since few data from the global core top calibration are from the Pacific, this study was carried out to assess whether the global core top calibration is regionally biased or not. The result of principal components analysis of the fractional abundance of GDGTs, an analysis of variance (ANOVA) and the comparison of the residuals of TEXH 86 derived sea surface temperature (SST) estimates of the Pacific subset with that of the global data set suggest that the Pacific subset has a similar TEXH 86-SST relationship with the global data set. However, the regression line through the Pacific data and an ANOVA on the residuals of TEXL 86 derived SST estimates suggest otherwise. The contradictory findings are likely to stem from the large scatter in the Pacific TEXL 86 values in the mid temperature range. While regionality does not seem to exert a strong bias on TEXL 86 and TEXH 86 calibration, it appears that there is a strong need to resolve the large scatter in the global data set, especially in the mid and high latitudes, in order to improve the calibration for a better SST estimation.

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

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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.

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Física, Programa de Pós-Graduação em Física, 2016.

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Produced water is characterized as one of the most common wastes generated during exploration and production of oil. This work aims to develop methodologies based on comparative statistical processes of hydrogeochemical analysis of production zones in order to minimize types of high-cost interventions to perform identification test fluids - TIF. For the study, 27 samples were collected from five different production zones were measured a total of 50 chemical species. After the chemical analysis was applied the statistical data, using the R Statistical Software, version 2.11.1. Statistical analysis was performed in three steps. In the first stage, the objective was to investigate the behavior of chemical species under study in each area of production through the descriptive graphical analysis. The second step was to identify a function that classify production zones from each sample, using discriminant analysis. In the training stage, the rate of correct classification function of discriminant analysis was 85.19%. The next stage of processing of the data used for Principal Component Analysis, by reducing the number of variables obtained from the linear combination of chemical species, try to improve the discriminant function obtained in the second stage and increase the discrimination power of the data, but the result was not satisfactory. In Profile Analysis curves were obtained for each production area, based on the characteristics of the chemical species present in each zone. With this study it was possible to develop a method using hydrochemistry and statistical analysis that can be used to distinguish the water produced in mature fields of oil, so that it is possible to identify the zone of production that is contributing to the excessive elevation of the water volume.