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[pt] O processo de medição é constituído por um conjunto de sub processos no qual seu início está na seleção da amostra até o final da marcha analítica. Para melhor compreensão, estabeleceu-se que a incerteza proveniente do processo de medição é constituída pela associação da incerteza proveniente do conjunto desses sub processos. A literatura organizou esse conjunto em duas grandes vertentes, o processo de amostragem e o processo analítico, cada um com suas incertezas características. Visando melhor estimar a incerteza de medição, é necessário considerar integralmente a incerteza proveniente de ambos os processos, sem antecipadamente determinar qual componente será mais significativo para a incerteza de medição. Este trabalho teve como motivação o desconhecimento da contribuição da incerteza da amostragem na incerteza de medição. Uma vez que o processo de amostragem é normalmente realizado por profissionais pouco experientes, sem ter conhecimento do quanto a incerteza da amostragem pode impactar na incerteza de medição. O objetivo desta dissertação foi avaliar o quão significativa é a incerteza da amostragem na incerteza de medição, além de estimular a disseminação da cultura desta prática em medições físico-químicas. As metodologias utilizadas para o desenvolvimento deste trabalho foram a análise do estado da arte da incerteza da amostragem e o tratamento de um conjunto de dados por quatro diferentes técnicas estatísticas: análise de variância clássica, análise de variância robusta, e dois modelos diferentes da Range Statistics. Os resultados mostraram que não há um padrão de comportamento no que tange à incerteza da amostragem versus a incerteza analítica, bem como a ausência de metodologias que leve em consideração as características dos dados. Conclui-se que a incerteza da amostragem pode impactar a incerteza de medição, independente da matriz e/ou grandeza em questão. / [en] The measurement process consists of a set of sub-processes where the beginning is in the selection of the sample until the end of the analytical steps. In a simplified way, it can be established that the uncertainty coming from the measurement process is constituted by the association of the uncertainty coming from the set of these sub-processes. The literature has organized this set of subprocesses into two important areas, the sampling process and the analytical process, each one with its own uncertainties characteristics. In order to better estimate the measurement uncertainty, it is necessary to fully consider the uncertainty arising from both processes without firstly determining which component will be most significant for the measurement uncertainty. This work project was motivated by the indifference to the sampling process, which is usually carried out by little experienced professionals, without knowledge of how much uncertainty of sampling can affect the measurement uncertainty. The objective of this dissertation was to evaluate how much uncertainty is the uncertainty of the measurement uncertainty in addition to stimulating the dissemination of the culture of this practice in physicochemical measurements; since, actually, only analytical uncertainty is privileged. The methodologies used were the analysis of the state of art of sampling uncertainty and the treatment of a data set by four different statistical techniques: classical variance analysis, robust variance analysis, and two different models of the Range Statistics. The results showed that there is no behavior pattern regarding to sampling uncertainty versus analytical uncertainty, as well as the absence of methodologies that take into consideration the characteristics of the data. It is concluded that the sampling uncertainty can impact the uncertainty of measurement, regardless of the matrix and / or quantity in question.

With the intention of improving process efficiency and product quality, Design of Experiments (DoE) is often applied in industry as a tool for engineers in planning experiments and product design. One of the methods in DoE is the Taguchi method that provides a practical procedure to design experiments with an appropriate number of tests for identifying optimal parametric settings of products. The purpose of this study is to investigate how Design of Experiments, specifically the Taguchi method, can be applied to analyze the performance of the lubricants used to stainless fasteners which are common products in various industries. The study has been implemented at the case company which manufactures stainless fasteners. Combining with qualitative and quantitative methods, this thesis work started from reviewing the previous research on DoE, the Taguchi method and various analysis tools as well as information on lubricants. Experiments were designed based on observations, interview, and literature collection. The actual tests were carried out on the case company's wax process where lubricants with different levels for the respective parameters were applied to screws and nuts. The fasteners were tested in a friction machine and UV lamp at the case company. The implemented experiments and data analysis have demonstrated which levels for each parameter of the lubricant resulted in the least friction. The parameters considered in the experiments are mixing ratio, number of dips and time in dips, which have varying degrees of influence on friction. The outcomes contribute to improved process efficiency and product quality within the steel industry and similar sectors. The visualization of the lubricant by UV lamp confirmed that the coating varied according to the levels of the parameters. The theoretical contribution can facilitate further research while the practical contribution provides an approach for experiments in quality improvement on lubricants. The thesis work has also identified the need for further research into the drying process after lubricant application and the use of UV lamp to improve control of lubricant smoothness.

No / AIM: The aim of the study was to determine, objectively and non-invasively, whether changes in accommodative demand modify differentially the peripheral refraction in emmetropic and myopic human eyes. METHODS: Forty subjects (19 male, 21 female) aged 20-30 years (mean 22.7 (SD 2.8) years), 21 emmetropes (mean spherical equivalent refractive error (MSE) -0.13 (SD 0.29) D) and 19 myopes (MSE -2.95 (SD 1.76) D) participated in the study. Ametropia was corrected with soft contact lenses (etafilcon A, 58% water content). Subjects viewed monocularly a stationary, high contrast (85%) Maltese cross at 0.0, 1.0, 2.0 and 3.0 D of accommodative demand and at 0, 10, 20 and 30 degrees field angle (nasal and temporal) through a +3.0 D Badal optical system. Static recordings of the accommodation response were obtained for each accommodative level, at each field angle, with an objective, open-view, infrared optometer. RESULTS: Peripheral mean spherical equivalent (M) data showed that the emmetropic cohort exhibited relative myopic shifts into the periphery, while the myopic group showed hypermetropic shifts. Increasing accommodative demand did not alter the peripheral refractive profile in either the temporal (p = 0.25) or nasal (p = 0.07) periphery with no differential accommodative effect between refractive groups in either the temporal (p = 0.77) or nasal (p = 0.73) field. Significant shifts in the J(0) astigmatic component were seen in the temporal (p<0.0005) and nasal (p<0.0005) fields with increasing eccentricity. Interaction effects between eccentricity and accommodative demand illustrated that increasing accommodative demand significantly altered the peripheral refractive profile in the temporal J(0) astigmatic component (p<0.0005). The nasal periphery, however, failed to show such an effect (p = 0.65). CONCLUSIONS: Alterations in peripheral refraction augmented by changes in ocular accommodation are relatively unaffected by refractive error for young, healthy human eyes.

This dissertation explored the efficacy of the new Basel III banking standards in SACU, grounded on the conjecture that they are not reflective of economies of SACU, but are merely an intensification of Basel II, rather than a substantial break with it. Firstly, loans and assets were tested for causality, since Basel III believes growth in these variables led to securitization. The leverage ratio has been introduced in Basel III as an anti-cyclical buffer. The OLS technique was employed to test for its significance in determining growth in bank assets. SACU feels the impact of debt, with credit is marginally treated in Basel III and is not introspective of the realities of its economies. ANOVA tests using debt, credit and GDP were done to determine a better method of addressing cyclicality. The leverage ratio was insignificant in Namibia, with debt and credit having momentous impacts on GDP in SACU. / Economics / M. Com. (Economics)

The purpose of the study was to investigate how the online, computer-based learner's personal learning profile (Preference), the content delivery method supplemented with visual content based on Neil Fleming's VARK (visual, aural, read/write, kinesthetic) model (Content), and the interaction of Preference and Content, influenced learner performance (Performance) and/or learner self-reported satisfaction (Satisfaction). Participants were drawn from a population of undergraduates enrolled in a large public southwestern research university during the fall 2015 semester. The 165 student participants (13.79% completion rate) were comprised of 52 (31.5%) females and 113 (68.5%) males age 18-58+ years with 126 (76.4%) age 18-24 years. For race/ethnicity, participants self-identified as 1 (0.66%) American Indian/Alaska Native, 21 (12.7%) Asian/Pacific Islander, 27 (16.4%) Black, non-Hispanic, 28 (17%) Hispanic, 78 (47.3%) White, non-Hispanic, 10 (6.1%) other. Reported socioeconomic status was 22 (13.3%) withheld, 53 (32.1%) did not know, 45 (27.3%) low, 13 (7.9%) moderately low, 16 (9.7%) middle, 8 (4.8%) upper middle, and 8 (4.8%) upper. This causal-comparative and quasi-experimental, mixed-method, longitudinal study used researcher-developed web-based modules to measure Performance and Satisfaction, and used the criterion p < .05 for statistical significance. A two-way, 4 x 3 repeated measures (Time) analysis of variance (RM-ANOVA) using Preference and Content was statistically significant on each Performance measure over Time, and at two measures on Satisfaction over Time. The RM-ANOVA was statistically significant on between-subjects main effect Performance for read/write modality Content compared to aural and kinesthetic Content. There were no statistically significant main effects observed for Satisfaction. A Pearson r correlation analysis showed that participants that were older, married, and of higher socioeconomic status performed better. The correlation analysis also showed that participants who performed better reported greater likelihood to take online courses in the future, higher motivation, sufficient time and support for studies, and sufficient funding for and access to the Internet. The study results suggested that regardless of Preference, using read/write modality Content based on the VARK model while maintaining the verbal language can yield better Performance outcomes. The study results also suggested that while maintaining the verbal language, Preference, and Content based on the VARK model do not distinguish learner Satisfaction outcomes. However, because Satisfaction has been shown to impact Performance, efficacy, and retention, it matters to educational institutions. Future research should consider more granular models and factorial research methods, because models that utilize a single representative construct score can mask effects when analyzing Performance and Satisfaction.

Pharmaceutical drug development is a costly and time consuming process. Reportedly, it takes about 10-15 years and ~900 million dollars of investment to launch a new drug in the world market. Any measure that increases the power and also decreases uncertainty about that power also increases drug net present value. For some time now, it has been argued that judicious utilization of available data might lead to more efficient use of resources during drug development. Conventionally, assessment of effectiveness has been based on comparing change from baseline at some pre-specified time for the control and test treatment (SPA). The last observation carry forward (LOCF) is a widely used technique if the data are missing due to any reason. Although, LOCF is known to introduce bias, the direction and magnitude is debatable.The primary aim of the proposed simulation experiments was to assess the properties of the random effects model (REM) and mixed model repeated measures (MMRM) methods that utilize all the data collected during pivotal trials. A total of 43 scenarios based on disease progression, magnitude of drug effect, between and within subject variability and patient drop-outs were analyzed. Three analysis methods, viz. SPA, REM and MMRM, were investigated. For the SPA method, the missing data were imputed with four different methods, such as LOCF, mean imputation, population and individual regression. The false-positive, false-negative inferences and bias in estimating the effect size for each method was assessed.The most important finding of this report is that the REM and MMRM methods are efficient alternatives to the SPA methods with ~50% savings on sample size. These methods are based on sound scientific principles and provide stronger evidence against the null hypothesis. The choice of the REM versus MMRM method is dependent on the purpose of the analysis and data gathered from the experimental design. The results support the use of likelihood-based MMRM methods for regulatory decision making. The REM methods are useful in understanding the time course of the disease and drug effect, making predictions based on the data and gaining insights into time to steady state effect for rational decision making. The SPA methods are less powerful across all the scenarios. The SPA-LOCF yielded anticonservative results in some cases with type-1 error rate exceeding 15% if data were missing due to toxicity. On the other hand, the drug effect was consistently underestimated (~40%), if data were missing due to lack of effectiveness. The results demonstrate that the SPA-LOCF methods make it practically impossible to establish effectiveness in these areas with a reasonable sample size.

A fase intermediária de um programa de melhoramento de soja caracteriza-se pela avaliação de grande número de genótipos (cerca de 100 linhagens) em diversos ambientes, fato que torna esta etapa bastante dispendiosa. A utilização de métodos estatísticos que permitam uma análise da interação genótipos x ambientes (GxE) mais refinada, pode permitir, com o ganho em precisão gerado, uma compensação ao aumento esperado na interação GxE em conseqüência da diminuição do número de repetições nesses experimentos. A metodologia de Eberhart & Russell (1966) (ER) utiliza a regressão linear como ferramenta para modelar a interação GxE, enquanto que a metodologia AMMI utiliza a análise da variância para modelar os efeitos de genótipos e de ambientes e a decomposição de valores singulares para modelar apenas a interação GxE. O objetivo deste trabalho foi avaliar a possibilidade de redução do número de repetições em experimentos com 72 linhagens em delineamento em blocos casualizados com duas repetições subdivididas em conjuntos experimentais (BCCE), conduzidos em quatro locais / épocas de cultivo e três anos agrícolas. Os experimentos foram analisados em BCCE e também em blocos aumentados (BA) considerando-se aleatoriamente uma das duas repetições. Como ferramentas auxiliares foram empregadas as metodologias ER e AMMI. A análise conjunta dos 12 ambientes através da metodologia AMMI foi utilizada como padrão para comparações, através de correlações de Spearman (rs). Em relação a este padrão, a média das rs dos três anos foi estimada em: 54% para as médias dos experimentos em BA; 64% para os experimentos em BCCE; 65% para os experimentos em BA analisados pela metodologia ER; 69% para os experimentos em BCCE analisados pela metodologia ER; 73% para os experimentos em BA analisados pela metodologia AMMI e 74% para os experimentos em BCCE avaliados pela metodologia AMMI. Os resultados obtidos permitiram concluir que as metodologias para o estudo da interação GxE são capazes de aumentar as rs com o padrão, indicando a possibilidade de redução de duas para uma repetição nos experimentos intermediários através do uso de: a) metodologia AMMI ao invés da seleção baseada nas médias das duas repetições; b) metodologia ER (em dois dos três anos avaliados) ao invés da seleção baseada nas médias das duas repetições; c) metodologia AMMI (em dois dos três anos avaliados) ao invés da seleção baseada na metodologia ER. Com a redução do número de repetições (duas para uma) é possível diminuir sensivelmente os custos com a experimentação na fase intermediária de programas de melhoramento. / The intermediary phase of a soybean breeding program involves the evaluation of a large number of genotypes (about 100 lines) in several environments, becoming this a very expensive step. The utilization of statistical methods that allow a refined analysis of the genotype x environment (GxE) interaction, may generate gains in precision as a compensation to the expected increase in the GxE estimate and, thus, to permit the reduction of the replication number. Eberhart & Russell (1966) (ER) methodology utilizes linear regression to study G x E interaction; the AMMI methodology employs the analysis of variance to fit effects of genotypes and environments and singular values decomposition to fit only the GxE interaction. The objective of this research was to evaluate experiments with 72 lines in randomized block design with two replications subdivided in sets with common checks (BCCE); these experiments were carried out in four locations / sow dates during three agriculture years. The experiments were analyzed in BCCE and also in augmented blocks (BA) by considering only one replication taking at random. As auxiliary tools were used ER and AMMI methodologies. The joint analysis of the 12 environments through the AMMI methodology was used as pattern for comparisons through Spearman correlation (rs). In relation to this pattern, the mean of rs in the three years was estimated in: 54% for means of BA experiments, 64% for BCCE experiments, 65% for BA experiments analyzed with ER, 69% for BCCE experiments analyzed with ER methodology, 73% for BA experiments analyzed with AMMI methodology and, 74% for BCCE experiments analyzed with AMMI methodology. The results indicated that the application of auxiliary methods for understanding GxE interaction were able to increase the rs with the pattern, opening the possibility for reducing the replication number in the experiments of the intermediary steps of soybean breeding programs. In conclusion, it was verified the possibility to reduce from two (BCCE) by one (BA) replication by using the following auxiliary methods of analysis: a) AMMI method instead of means of two replications as the unique selection criterion; b) ER method (in two of the three evaluated years) instead of means of two replications as the unique selection criterion; c) AMMI method (in two of the three evaluated years) instead of selection as based on ER method. The reduction from two to one replication makes possible to lower reasonably the experimental costs during the intermediary step of breeding programs.

Esse trabalho teve como objetivo comparar métodos de estimação de componentes de variância e parâmetros genéticos, considerando tanto o delineamento estatístico fatorial instalado em látice quadrado como o delineamento genético III. Como referência, foram utilizados três conjuntos de dados reais, em melhoramento genético de milho, relativos aos caracteres de produção de grãos (gramas por parcela), altura da folha bandeira ao chão (centímetros) e o número de folhas entre a primeira espiga e o pendão; sendo que a altura da folha bandeira e o número de folhas foram obtidos pela média entre cinco plantas competitivas para cada parcela. O método da Análise da Variância (ANOVA), conforme indicado pelo Delineameno III, foi utilizado na análise dos dados e estimação dos componentes de variância relativos ao modelo matemático, variâncias genéticas, coeficiente de herdabilidade e grau médio de dominância para cada um dos três caracteres estudados. Essas estimativas foram utilizadas na simulação de 1000 conjuntos de dados com características semelhantes a cada um dos conjuntos de dado reais considerados. Os métodos da ANOVA e da máxima verossimilhança restrita (REML) foram utilizados na predição dos parâmetros já mencionados para cada um dos conjuntos de dados simulados dentro de cada caráter. As 1000 estimativas obtidas por cada método, para cada caráter estudado, foram utilizadas no cálculo de estatísticas descritivas (média, desvio-padrão e acurácia relativa) e na montagem de gráficos de Box-plot. Utilizando as informações obtidas a partir das estimativas fornecidas por cada método e em posse dos valores reais que essas estimativas deveriam prever (valor utilizado na simulação dos dados) foi possível comparar ambos os métodos quanto à eficiência das estimativas por eles fornecidas. Ambos os métodos apresentaram características semelhantes na predição da maioria dos componentes de variância relativos ao modelo matemático, sendo que as maiores disparidades se deram para os componentes relativos aos efeitos de progênie (?p2) e as interações entre progênie e linhagem (?pt2) e entre progênie, linhagem e ambiente (?pta2); os quais são os componentes de maior peso no cálculo das variâncias e parâmetros genéticos. O método da ANOVA foi o bastante eficiente na predição de ?p2, sendo que o método da REML se aproxima dos resultados obtidos pelo método da ANOVA conforme diminuem os valores de referência para esse componente; para ?pt2 o método da REML se mostrou mais eficiente conforme maior é o valor de referência, porém, perde eficiência e se aproxima do método da ANOVA conforme o valor de referência do componente diminui. Ambos os métodos se mostraram ineficientes na predição de ?pta2, porém o método da REML foi o menos eficiente. O melhor desempenho do método da ANOVA na predição dos componentes de variância de maior peso no cálculo das variâncias genéticas levou a um melhor desempenho desse método na predição de todos os parâmetros genéticos, com exceção da variância de dominância, a qual depende unicamente de ?pt2. Porém, foi observada uma tendência no método da ANOVA, em média, na superestimação do grau médio de dominância em cerca de 45% do seu valor de referência, independentemente do caráter estudado. / This work aimed to compare estimation methods for variance components and genetic parameters, considering the factorial statistical design set in randomized blocks and the genetic Design III. As reference, three sets of real data were used, on maize genetic improvement, related to the characters: grain yield (grams by plot), plant height, measured from the ground to the °ag leaf in centimeters, and the number of leaves above the uppermost ear. The analysis of variance method (ANOVA), accordingly to the proposed by the Design III, was used on the analysis of the data and estimation of the variance components derived from the mathematical model, genetic variances, heritability and average degree of dominance for each of the studied characters. This estimatives were used on the simulation of 1000 data sets with similar characteristics to the real data analyzed. The ANOVA and restricted maximum likelihood (REML) methods were used on the prediction of the already mentioned parameters for each of the simulated data sets within each character. The 1000 estimatives obtained by each method, for each studied character, were used on the calculation of descriptive statistics (mean, standard deviation and relative accuracy) and for the ¯tting of box-plot graphics. Through the information obtained from the estimatives given by each method and in possession of the actual values that they should predict (values used in the simulation of the data sets) it was possible to compare both methods as to the e±ciency of the estimatives given by them. Both methods presented similar characteristics on the prediction of most of the variance components derived from the mathematical model, being that most di®erences were pertinent to the components related to the e®ects of progeny (¾2 p) and to the interactions between progeny and parental inbred (¾2 pt) and between progeny, parental inbred and environment (¾2 pta); which are the components of greater importance on the calculation of the genetic parameters. The ANOVA method was very e±cient on the prediction of ¾2 p, being that the smaller the reference value for this component, more the REML method approached the results obtained by the ANOVA method; for larger values of ¾2 pt the most e±cient was the REML method, but its e±ciency decayed and approached the ANOVA method for smaller reference values for this component. Both methods were poorly e±cient on the prediction of ¾2 pta, but the REML method was the least e±cient. The better performance of the ANOVA method on the prediction of the variance components of greater importance on the calculation of the genetic variances lead to a better performance of the ANOVA method on the prediction of all genetic parameters, with exception to the dominance variance, which depended solely on ¾2 pt. However, it was observed a tendency on the ANOVA method, in average, on the overestimation of the average degree of dominance of around 45% of the actual reference value, independently of the studied character.

Temas relacionados ao desenvolvimento de novos materiais têm sido cada vez mais abordados e discutidos, num contexto em que questões como meio ambiente, sociedade, economia de energia e aproveitamento de resíduos, vêm se tornando relevantes. Neste cenário, faz-se necessário estudar aplicações de insumos alternativos na produção de pisos de madeira, tanto para reduzir o consumo de essências tropicais quanto para suprir o aumento da demanda de madeira nas indústrias deste segmento. O objetivo deste estudo foi produzir painéis de partículas homogêneos de alta densidade, com resíduos de madeira de Pinus elliottii e casca de aveia (Avena sativa), aderidos sob pressão com dois tipos de adesivo, poliuretano à base de óleo de mamona e melamina formaldeído, nos percentuais de 11 e 13%, e avaliar o desempenho físico-mecânico de tais painéis para aplicação em pisos. O desempenho físico-mecânico dos painéis (Planejamento I - 20 tratamentos) foi avaliado com base nas normas ABNT NBR 14810 (2006 e 2013). Realizou-se análise de variância (ANOVA) para testar a influência dos fatores individuais (percentual de casca de aveia, percentual de adesivo e tipo de adesivo), além das interações entre tais fatores (dois a dois e três a três) nas propriedades físico-mecânicas dos painéis. Também foi avaliado o desempenho para pisos, tanto dos painéis (Planejamento II - 12 tratamentos) quanto de três espécies de madeira tropical (Angelim Vermelho, Dinizia excelsa; Cumaru, Dipteryx odorata e Jatobá, Hymenaea sp.), segundo diversas normas relacionadas a pisos de madeira. Os resultados apontaram propriedades físico-mecânicas dos painéis, em alguns tratamentos superiores aos requisitos estipulados por normas nacionais e internacionais. Quanto ao desempenho para pisos, os painéis apresentaram desempenho semelhante as três espécies de madeira, na maioria das propriedades avaliadas. A análise de porosimetria por intrusão de mercúrio confirmou a similaridade entre os painéis (do Planejamento II) e as três espécies de madeira avaliadas, evidenciando a potencialidade dos painéis produzidos para aplicação na indústria de pisos engenheirados. / Matters related to the development of new materials have been increasingly addressed and discussed in a context where issues such as the environment, society, energy and waste recovery economy, is becoming relevant. In this scenario, it is necessary to study alternative inputs for applications in the production of wood floors, both to reduce the consumption of tropical essences as to meet the increasing demand for wood in industries in this segment. The aim this study was to produce high density homogeneous particleboard with waste wood of Pinus elliottii and oat hulls (Avena sativa), adhered under pressure with two types of adhesive, castor oil-based polyurethane and melamine formaldehyde, the percentage of 11 and 13%, and evaluate the physical and mechanical performance of such panels for use in floors. The physical-mechanical performance of the panels (Planning I - 20 treatments) was evaluated based on the NBR 14810 (2006 and 2013) standards. We conducted an analysis of variance (ANOVA) to evaluate the influence of individual factors (oat hulls percentage, adhesive percentage and type of adhesive), and the interactions between these factors (two by two and three by three) on the physical properties-mechanical panels. It was also evaluated the performance for floors, both panels (Planning II - 12 treatments) as three species of tropical wood (Angelim Vermelho, Dinizia excelsa; Cumaru, Dipteryx odorata e Jatobá, Hymenaea sp.), according to various standards related to wood floors. The results indicated physical and mechanical properties of the panels, in some treatments superior to the requirements stipulated by national and international standards. As for performance flooring, panels statistically equivalent to the three species of wood, most of the evaluated properties. Porosimetry analysis by mercury intrusion confirmed the similarity between the panels (from Planning II) and the three wood species evaluated, demonstrating the potential of the panels produced for use in the flooring industry engineered.