The persistence rate in online classes remains significantly lower than in comparable face-to-face classes. There is a lack of research on strategies to help learners persist in online classes. The purpose of this study was to investigate the relationship between face-to-face orientations, instructor verbal immediacy behaviors, and persistence in online classes. It also explored the relationship between verbal immediacy and student satisfaction. Due to the disagreement in the literature, this study also investigated the relationship between student demographic variables, grade point average, and persistence. This quantitative study combined both causal-comparative and correlational research methods. The study took place at a community college in the southeastern United States. The participants were 171 students enrolled in online classes selected for inclusion in the study using a purposive sampling method. Students were invited to attend a face-to-face orientation prior to the start of the semester. Prior to the end of the course, students were invited to complete a survey consisting of modified versions of Gorham’s (1988) Verbal Immediacy Scale and the college’s Student Perception of Instruction survey. At the end of the semester, demographic and course completion data were collected from the college’s student information system. A chi-square analysis revealed that there was not a significant relationship between orientation attendance and persistence. A Pearson correlation analysis and a linear regression analysis revealed that there was not a significant relationship between instructor verbal immediacy and persistence. A second linear regression analysis revealed a significant relationship between verbal immediacy and student satisfaction. Perceived instructor verbal immediacy explained 33% of the variance in satisfaction. A logistic regression analysis found that while GPA was a significant predictor of persistence, age, gender, and race/ethnicity were not. The results of this study suggest that online faculty should receive training on communication strategies, such as verbal immediacy behaviors. Colleges should also consider using predictor variables, such as GPA, to identify and assist at-risk students. This study was one of the first to examine the relationship between verbal immediacy and persistence in online classes. Future research should continue to investigate this topic as well as other strategies to help students persist.

This report gives the reader a detailed description of a computer engineering master thesis work done at the company Netlight Consulting AB. Netlight Consulting AB is a growing IT consulting company based in Stockholm with offices in major cities across Europe. One of their key success factors is their focus on personal and professional development amongst all employees. An essential part of this development program consist of reoccurring evaluation periods, where every employee receives written constructive feedback from some of their co-workers. This thesis’ focus lies in improving the algorithm that organizes which employee should evaluate who. The original algorithm turned out to harbor a number of flaws, e.g. it was not always able to deliver a satisfactory matching where every participant received the minimum number of evaluations.   In this thesis a new matching algorithm has been implemented that is platform independent and that facilitates future modifications with accessible source code written in Java. The input data for the matching algorithm, i.e. the set of all potential evaluation pairs, is of importance to obtain satisfactory matching results. The number of potential evaluation pairs determines the number of possible matching combinations, which in turn increases the probability to find a satisfactory matching. In this thesis the input data has been extended by utilizing a data mining technique known as SONAR. Two different data mining sources were evaluated, and one of them is shown to extend the number of potential evaluation pairs in the matching input by 20%. Finally, a new feature to support assignment of different evaluation sizes was added to the matching algorithm.

This work disusses estimates based on rounded data. The work describes the estimates of parameters in time series AR and MA and in linear regression, the work presents different kinds of estimates based on rounded data. The work focuses on time series model AR(1) and linear regression, where simulations are added to theories and methods are compared on rounded and unrounded data. In adition, the comparison of linear regression is shown at graphs. Powered by TCPDF (www.tcpdf.org)

[pt] Esta dissertação tem por objetivo investigar métodos de estimação da idade a partir de imagens faciais. Avalia-se o impacto de distintos fatores sobre a acurácia da estimativa, especificamente, a acurácia da localização de pontos fiduciais, métodos de extração de atributos, de redução de dimensionalidade, e técnicas de regressão. Adicionalmente, foi estudada a influência da raça e do sexo na acurácia da estimação da idade desenvolvido. Consideraram-se cinco métricas de desempenho do sistema, especificamente, o erro médio absoluto (MAE), o erro médio absoluto por década (MAE/D), o erro médio absoluto por idade (MAE/A), o escore acumulado (CS), e os intervalos de confiança (IC). Os experimentos foram realizados empregando dois bancos de dados públicos, cujas imagens estão rotuladas com a idade da face. Os resultados indicaram que o método automático para detecção de pontos fiduciais da face tem uma repercussão moderada sobre a acurácia das estimativas. Entre as variantes analisadas, a que apresentou a melhor acurácia foi o sistema que emprega os AAMs (Active Appearance Models) como método de extração de atributos, o PCA (Principal Components Analysis) como método para reduzir dimensionalidade, e as SVRs (Support Vector Regression) como técnica para fazer regressão. / [en] This thesis aims to investigate methods for age estimation from facial images. The impact of distinct factors over the estimate’s accuracy is assessed, specifically the accuracy in the location of face fiducial points, feature extraction and dimensionality reduction methods, and regression techniques. Additionally, the dependence on race and gender in the accuracy of age estimation is assessed. Five performance metrics have been considered: the mean absolute error (MAE), the mean absolute error per decade (MAE / D), the mean absolute error for age (MAE / A), the cumulative score (CS) and confidence intervals (CI). The experiments were performed using two public databases, whose images are labeled with the age of the face. The results showed the impact of the automatic method for detection of fiducial points of the face has a moderate impact on the accuracy of the estimates. Among the analyzed variants, the one with the best accuracy was the system that employs the Active Appearance Models (AAMs) as feature extraction method, the Principal Components Analysis (PCA) as dimensionality reduction method, and Support Vector Regression (SVRs) as a technique to do regression.

This thesis analyses the impact of announcements of macroeconomic indicators in United States on price development of the VIX Futures, S&P500 Futures and EUR/USD FX rate. Theoretical part contains construction and description of individual markets. Empirical part investigates the reaction of market prices after 1, 10 and 30 minutes after announcement of an individual indicator value on a market surprise demonstrated as a difference between reported value and analysts' expectations. We tried to find a systematic reaction of market participants and the pace of absorption of new information into the market price. There have been found minimum of situations, where we explained the market move as a linear combination of market surprise. However, there was a several cases, where the market did not adjust to announced information quickly and was inefficient in a short period. In the second part of empirical research we tested all significant models on an out-sample data. The goal was to determine whether the market inefficiencies persisted and stable profit could be achieved. We analysed the brutto performance, then netto performance including all transaction costs. Finally, we defined a simple trading rules with a purpose of profit stabilization and lowering the riskiness of trades. For VIX Futures and EUR/USD markets we achieved a low loss, respectively negligible profit. For S&P 500 Futures we obtained a profit strategies for all selected indicators, total profit was high with a very low volatility of invested capital.

Background: Hypertension, a leading risk factor for cardiovascular disease, exhibited in 17.7% of the Canadian population, and attributed to 13% of world mortality, is influenced by both the environment and genetics. Salt sensitivity is described at higher rates in the hypertensive population. The NEDD4-like (NEDD4L) protein is important in sodium reabsorption and has been implicated in essential hypertension and salt sensitivity. Objectives: Two variations (rs4149601/rs2288774) found in NEDD4L have been associated with salt sensitivity and hypertension; a third (rs576416) is in linkage disequilibrium with rs4149601. The purpose of this study is to assess the relationship between the NEDD4L rs4149601, rs2288774, and rs576416 single nucleotide polymorphisms with sodium and age on blood pressure (BP). Methods: Canadian hypertensive patients were recruited through the University of Ottawa Heart Institute, with genotyped data from Leuven, Belgium, and the DNA of subjects from Warsaw, Poland also included in the study. Eligible subjects were studied off anti-hypertensive medications. Daytime BP was measured using 24hr ambulatory BP monitoring in 662 Caucasian hypertensives (BP ≥130/85 mmHg). 24hr urine Na+ was collected. DNA from Canada and Poland was genotyped on the GeneTitan Affymetrix Axiom platform and through TaqMan MGB probe-based RT-PCR, while the Belgium samples were analyzed on Illumina 1M-duo arrays. Simple and multivariate linear regression modelling with SAS 9.4.0 was used for genotypic comparisons affecting BP, combined with age and corrected urine sodium. Results: The three hypertensive populations were significantly different (P<0.05) across all demographic and clinical measures, even when stratified by sex. The Polish and female hypertensives from Canada and Belgium were removed from the analysis for lacking the general populations’ trend of increasing BP with age. Multiple linear regressive modelling found a significant association (Pmodel=0.0034) of rs4149601 GA (P=0.0129) and GG (P=0.0082), with age and urine sodium, on SBP in the Belgium male hypertensives (n=273). No significant models analyzing the association of rs576416 and rs2288774 with BP in the Belgium population were found. In the Canadian hypertensive population (n=120) no association on the discrete analyses of the rs4149601, rs576416, and rs2288774 genotypes were found; however the combination of the GG rs4149601 and AA rs576416 (β=0.021, P=0.03) and the GG rs4149601 and CC rs2288774 (β=0.020, P=0.04) genotypes showed significant associations with BP in borderline significant models (P=0.055 and P=0.094 respectively), when analyzed with urine sodium levels and age. Conclusions: A significant influence of the rs4149601 G-allele, with urine sodium and age, was found to be associated with an increase in BP in the Belgium males. Multiple linear modelling describing borderline significant findings in the interaction of rs4149601 with rs576416, and rs4149601 with rs2288774 in Canadian male hypertensives suggests of the possible synergism between polymorphisms and development of salt sensitive hypertension. Future research could evaluate the role of NEDD4L on the sex differences in early-onset salt-sensitive hypertension.

The aim of this academic paper is to analyse the possible presence of discrimination against women in the job market. The analysis attempts to endogenous the discrimation section within the model. That is the essential difference in regard to other papers on this topic as these ascribe the influence of discrimination to the unexplained gender wage gap. The basic thought of this model is the idea, that if dicrimination against women is present in the job market, then it must exhibit the signs of a normal good. An examined characterisitc is the correlation of the wage gap, taken as a good, and extra variables as pensions. Investigation of possible correlation is done according to the linear regression analysis. The regression results are not satisfactory over long time periods as there are many variables that affect the outcome that the model does not consider. More precise results were achieved by means of testing individual workplaces, where especially the regression conducted with available data from analytic management occupations suggests that discrimination against women may be present

The purpose of this study was to assess the effect of performance feedback on Athletic Trainers’ (ATs) perceived knowledge (PK) and likelihood to pursue continuing education (CE). The investigation was grounded in the theories of “the definition of the situation” (Thomas & Thomas, 1928) and the “illusion of knowing,” (Glenberg, Wilkinson, & Epstein, 1982) suggesting that PK drives behavior. This investigation measured the degree to which knowledge gap predicted CE seeking behavior by providing performance feedback designed to change PK. A pre-test post-test control-group design was used to measure PK and likelihood to pursue CE before and after assessing actual knowledge. ATs (n=103) were randomly sampled and assigned to two groups, with and without performance feedback. Two independent samples t-tests were used to compare groups on the difference scores of the dependent variables. Likelihood to pursue CE was predicted by three variables using multiple linear regression: perceived knowledge, pre-test likelihood to pursue CE, and knowledge gap. There was a 68.4% significant difference (t101= 2.72, p=0.01, ES=0.45) between groups in the change scores for likelihood to pursue CE because of the performance feedback (Experimental group=13.7% increase; Control group= 4.3% increase). The strongest relationship among the dependent variables was between pre-test and post-test measures of likelihood to pursue CE (F2,102=56.80, p<0.01, r=0.73, R2=0.53). The pre- and post-test predictive relationship was enhanced when group was included in the model. In this model [YCEpost=0.76XCEpre-0.34 Xgroup+2.24+E], group accounted for a significant amount of unique variance in predicting CE while the pre-test likelihood to pursue CE variable was held constant (F3,102=40.28, p<0.01,: r=0.74, R2=0.55). Pre-test knowledge gap, regardless of group allocation, was a linear predictor of the likelihood to pursue CE (F1,102=10.90, p=.01, r=.31, R2=.10). In this investigation, performance feedback significantly increased participants’ likelihood to pursue CE. Pre-test knowledge gap was a significant predictor of likelihood to pursue CE, regardless if performance feedback was provided. ATs may have self-assessed and engaged in internal feedback as a result of their test-taking experience. These findings indicate that feedback, both internal and external, may be necessary to trigger CE seeking behavior.

O escopo desta dissertação é o desenvolvimento de uma metodologia para a detecção e diagnóstico de falhas em processos industriais baseado em modelos empíricos no subespaço das variáveis do processo com expansão não linear das bases. A detecção e o diagnóstico de falhas são fundamentais para aumentar a segurança, confiabilidade e lucratividade de processos industriais. Métodos qualitativos, quantitativos e baseados em dados históricos do processo têm sido estudados amplamente. Para demonstrar as vantagens da metodologia proposta, ela será comparada com duas metodologias consideradas padrão, uma baseada em Análise de Componentes Principais (PCA) e a outra baseada em Mínimos Quadrados Parciais (PLS). Dois estudos de casos são empregados nessa comparação. O primeiro consiste em um tanque de aquecimento com mistura e o segundo contempla o estudo de caso do processo da Tennessee Eastman. As vantagens da metodologia proposta consistem na redução da dimensionalidade dos dados a serem usados para um diagnóstico adequado, além de detectar efetivamente a anormalidade e identificar as variáveis mais relacionadas à falha, permitindo um melhor diagnóstico. Além disso, devido à expansão das bases dos modelos é possível trabalhar efetivamente com sistemas não lineares, através de funções polinomiais e exponenciais dentro do modelo. Adicionalmente o trabalho contém uma metodologia de validação dos resultados da metodologia proposta, que consiste na eliminação das variáveis do melhor modelo obtido pelos Modelos Empíricos, através do método Backward Elimination. A metodologia proposta forneceu bons resultados na área do diagnóstico de falhas: conseguiu-se uma grande diminuição da dimensionalidade nos sistemas estudados em até 93,55%, bem como uma correta detecção de anormalidades e permitiu a determinação das variáveis mais relacionadas às anormalidades do processo. As comparações feitas com as metodologias padrões permitiram demonstrar que a metodologia proposta tem resultados superiores, pois consegue detectar as anormalidades em um espaço dimensional reduzido, detectando comportamentos não lineares e diminuindo incertezas. / Fault detection and diagnosis are critical to increasing the safety, reliability, and profitability of industrial processes. Qualitative and quantitative methods and process historical data have been extensively studied. This article proposes a methodology for fault detection and diagnosis, based on historical data of processes and the creation of empirical models with the expansion of nonlinear bases (polynomial and exponential bases) and regularization techniques. To demonstrate the advantages of the proposed approach, it is compared with two standard methodologies: Principal Components Analysis (PCA) and the Partial Least Squares (PLS), performed in two case studies: a mixed heating tank and the Tennessee Eastman Process. The advantages of the proposed methodology are the reduction of the dimensionality of the data used, in addition to the effective detection of abnormalities, identifying the variables most related to the fault. Furthermore, the work contains a methodology to validate the diagnosis results consisting of variable elimination from the best empirical models with the Backward Elimination algorithm. The proposed methodology achieved a promising performance, since it can decrease the dimensionality of the studied systems up to 93.55%, reducing uncertainties, and capturing nonlinear behaviors.

Neural Processes (NPs) are a class of regression models that learn a map from a set of input-output pairs to a distribution over functions. NPs are computationally tractable and provide a number of benefits over traditional nonlinear regression models. Despite these benefits, there are two main domains where NPs fail. This thesis is focused on presenting extensions of the Neural Process to these two areas. The first of these is the extension of Neural Processes graph and network data which we call Graph Neural Processes (GNP). A Graph Neural Process is defined as a Neural Process that operates on graph data. It takes spectral information from the graph Laplacian as inputs and then outputs a distribution over values. We demonstrate Graph Neural Processes in edge value imputation and discuss benefits and drawbacks of the method for other application areas. The second extension of Neural Processes comes in the fundamental training mechanism. NPs are traditionally trained using maximum likelihood, a probabilistic technique. We show that there are desirable classes of problems where NPs fail to learn. We also show that this drawback is solved by using approximations of the Wasserstein distance. We give experimental justification for our method and demonstrate its performance. These Wasserstein Neural Processes (WNPs) maintain the benefits of traditional NPs while being able to approximate new classes of function mappings.