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This dissertation focuses on two problems in dimension reduction. One is using permutation approach to test predictor contribution. The permutation approach applies to marginal coordinate tests based on dimension reduction methods such as SIR, SAVE and DR. This approach no longer requires calculation of the method-specific weights to determine the asymptotic null distribution. The other one is through combining clustering method with robust regression (least absolute deviation) to estimate dimension reduction subspace. Compared with ordinary least squares, the proposed method is more robust to outliers; also, this method replaces the global linearity assumption with the more flexible local linearity assumption through k-means clustering. / Statistics

With over 18% of the Canadian population born outside of Canada, the health of immigrants is an important concern. Heart health is of particular importance because heart disease is the leading cause of death among men and women in Canada. Using data from the National Population Health Survey (NPHS), the purpose of this thesis is to first establish whether immigrants to Canada have lower rates of coronary heart disease (CHD), and high blood pressure (HBP) than native-born Canadians, and second to determine the lifestyle and psychosocial factors that predict heart health and compare them between immigrants and native-born Canadians. Regression and survival analyses of the NPHS data indicate that lifestyle and psychosocial risk factors such as smoking status, body mass index, alcohol consumption and depression affect immigrants and native-born Canadians similarly. Immigration variables such as length of time in the host country and country of origin are significant risk factors for HBP, however, not in the incidence of CHD. Immigrants were more likely to have HBP than native-born Canadians. However, immigrants have a significantly lower incidence of CHD than native-born Canadians. Native-born Canadians are at a higher risk of heart disease at a younger age than immigrants. These results suggest that there must be other factors relating to immigration affecting the heart health of immigrants. Due to the complexity and high incidence of heart disease in Canada, it may never be possible to ascertain all of the risk factors for heart disease. However, this study has identified several key risk factors and has excluded other variables as possible risk factors. The risk factors identified in this study can form the basis for the development of heart health programs to target all Canadians-both native-and foreign-born. / Thesis / Master of Arts (MA)

Functional Electrical Stimulation (FES) is a technique that applies electrical currents to nervous tissue in order to actively induce muscle contraction. Recent research has shown that FES provides a promising treatment to restore functional tasks due to paralysis caused by spinal cord injury, head injury, and stroke, to mention a few. Therefore, the overarching goal of this research work is to develop FES controllers to enable patients with movement-disorder to control their limbs in a desired manner and, in particular, to aid Parkinson's patients to suppress hand tremor. In our effort to develop strategies for muscle stimulation control, we first implement a model-based control technique assuming that all the states are measurable. The Hill-type muscle model coupled with a simplified 2DoF model of the arm is used to study the performance of our proposed adaptive sliding mode controller for simulation purpose. However, in the more practical situations, human limb dynamics are extremely complicate and it is inadequate to use model based controllers, especially considering there are still technical limitations that allow in vivo measurements of muscle activity. To tackle these challenges, we have developed output feedback adaptive control approaches for a class of unknown multi-input multi-output systems. Such control strategies are first developed for linear systems, and then extended to the nonlinear case. The proposed controllers, supported by experimental results, require minimum knowledge of the system dynamics and avoid many restrictive assumptions typically found in the literature. Therefore, we expect that the results introduced in this dissertation can provide a solution for a wide class of nonlinear uncertain systems, with focus on practical issues such as partial state measurement and the presence of mismatched uncertainties. / Ph. D.

This dissertation aims to develop a formal foundation to design an adaptive output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a reduced-order adaptive output-predictor scheme based on modal reduction and Lyapunov's method. Moreover, the credibility of the proposed reduced-order adaptive output-predictor scheme is validated by mathematical proof, and numerical and experimental studies, such as single pendulum, double pendulum, six-link pendulum, rope as a high-dimensional rope, and EEG data. Then the dissertation goal is to experimentally validate the proposed reduced-order model parameterization technique for tracking uncertain linear time-invariant (LTI) single-input, single-output (SISO) systems. The proposed theory focuses on parameterizing a high-dimensional, uncertain model and introduces a reduced-order adaptive output predictor capable of forecasting the system's output. This predictor utilizes auto-regressive filtered vectors, incorporating the input and output history. The adaptive output predictor is a simplified and known model, making it suitable for controlling high-dimensional, uncertain SISO systems without access to full-state measurements. Specifically, this work establishes the foundation for parameterizing uncertain models, creating a virtual structure that emulates the actual system, and offering a more manageable model for control when the objective is solely to regulate the system's output. The primary focus of this research is to assess the effectiveness and output-tracking capabilities of the proposed approach. These capabilities are extensively examined across diverse platforms and hardware configurations, relying solely on input and output data from the models without incorporating any additional information on the system dynamics. In the first experiment, the predictor's ability to track the angle of a single pendulum, including additional dynamics, is evaluated using only input-output data. The second experiment targets tracking the endpoint of a rope connected to a single pendulum, where the rope emulates a high-dimensional model. A vision system is designed and employed to acquire the rope endpoint position data. Before the rope experiment, a set of experiments is conducted on single pendulum hardware to ensure the accuracy of the vision system's data collection. Comparative analysis between data from object tracking via vision and data acquired through an encoder demonstrates negligible error. Finally, the input and the endpoint output data from the rope experiment are fed into the predictor to assess its capability to track the rope endpoint position without utilizing specific knowledge of the experimental hardware. Achieving negligible error in tracking implies that the predictor provides a simple and accurate representation of the rope dynamics. Consequently, designing a controller for this known model is equivalent to designing a controller for the actual rope system dynamics. The predictor, by closely emulating the behavior of the rope, becomes a reliable surrogate model for control design, simplifying the task of controller design for the complex and uncertain high-dimensional system. Finally, this study introduces a novel approach to enhance controller design for complex brain dynamics by employing a reduced-order adaptive output predictor proposed in [1], fine-tuned with chirp binaural beats. The proposed technique is promising for developing closed-loop controllers in non-invasive brain stimulation therapies, such as binaural beats stimulation, to improve working memory. The study focuses on parameterizing uncertain models and creates a predictor that utilizes auto-regressive filtered vectors to forecast mean phase lock values generated by binaural beats stimulation. The simplified and known model of the predictor proves effective in tracking brain responses, as demonstrated in experiments evaluating its ability to track mean phase locking values. The results indicate negligible tracking error, suggesting the predictor's reliability in representing brain dynamics and simplifying the task of controller design for the complex and uncertain high-dimensional system. / Doctor of Philosophy / This dissertation explores the development of a reduced-order adaptive output predictor for unknown systems with unknown or high-dimensional parameters and order. A reduced-order adaptive output predictor scheme is introduced, validated through mathematical proof, and tested in diverse scenarios, including pendulum systems and EEG data. The focus is on parameterizing uncertain models and creating a simplified adaptive output predictor capable of forecasting system output, specifically for SISO systems. Experimental validation involves tracking the angle of a single pendulum and the endpoint of a high-dimensional rope, demonstrating the predictor's accuracy without detailed knowledge of system dynamics. The study extends its application to complex brain dynamics, using the predictor fine-tuned with chirp binaural beats. Results show promise for developing closed-loop controllers in non-invasive brain stimulation therapies, offering a novel approach to improve working memory via helping to design closed-loop controllers.

Although evidence demonstrated efficacy of cognitive-behavioral therapy (CBT) in adolescents with binge-eating disorder (BED), treatment response is heterogeneous. This study uniquely examined baseline predictors of symptom trajectories in N = 73 adolescents (12–20 years) with an age-adapted diagnosis of BED (i.e., based on objective and subjective binge-eating episodes). Based on evidence from adult BED, dietary restraint, overvaluation of weight/shape, and depressive symptoms were used to predict changes in abstinence from binge eating and eating disorder psychopathology after 4 months of individual, face-to-face CBT using growth models. Longitudinal trajectories of abstinence from objective and subjective binge eating and global eating disorder psychopathology assessed via the Eating Disorder Examination were modeled for five time points (pre- and posttreatment, 6-, 12-, and 24-month follow-up). Beyond significant, positive effects for time, no significant predictors for abstinence from binge eating emerged. In addition to significant decreases in eating disorder psychopathology over time, higher pretreatment dietary restraint and overvaluation of weight/shape significantly predicted greater decreases in eating disorder psychopathology over time. Consistent with research in adult BED, adolescents with higher than lower eating disorder-specific psychopathology especially benefit from CBT indicating that restrained eating and overvaluation of weight/shape may be BED-specific prognostic characteristic across developmental stages. Future predictor studies with an additional focus on potential age-specific predictors, such as family factors, and within-treatment processes may be critical in further evaluating treatment-related symptom trajectories in adolescent BED.

The rapid growth in online learning opportunities and online courses in K-12 education is well documented in the literature. Studies conducted by various researchers that have focused on the K-12 population of online learners demonstrate that certain online learner characteristics and online learning environment characteristics may impact the likelihood of students passing or failing online courses. Research has produced models that predict online course success with measurable degrees of accuracy. This descriptive study examines characteristics of students enrolled in online high school courses provided by a virtual learning program administered by a single Virginia public school district. The study determined that students’ prior academic success; confidence in their technology skills and access to technology; confidence in their ability to achieve; and strong beliefs in their organizational skills proved to have a significant statistical relationship with online course success. The study developed a model with these factors that predicted success in online courses with a high degree of accuracy and predicted failure with a moderate degree of accuracy.The study has policy implications for public school leaders in Virginia as they implement recent state legislation requiring students to successfully complete a virtual course to graduate from public high school. The study indicates that additional research is warranted to further delineate learner and learning environment characteristics producing a model that more accurately predicts failure in online courses. Additional research is warranted with larger samples from single district virtual programs.

Este trabalho apresenta todo um projeto de um sistema de supervisão e controle de um trocador de calor, desde os ensaios experimentais para a elaboração de um modelo matemático até a implementação do sistema de controle e supervisão em microcomputador. O sistema implementado consiste de um software didático e um sistema de aquisição de dados que irão realizar a supervisão e controle de um trocador de calor tipo casco e tubos. Neste software didático é possível implementar o controle PID e suas variações PI-D e I-PD além de permitir a implementação do sistema de controle adaptativo estrutura gain scheduling o qual muda os parâmetros de um controle PID de acordo com a mudança da dinâmica do trocador de calor. Como o trocador de calor apresenta um tempo morto em sua dinâmica, então optou-se por adicionar ao software didático um controle com algoritmo preditivo estrutura Preditor de Smith desta forma é possível realizar ensaios com e sem o algoritmo preditivo para uma comparação de resultados. Este sistema de supervisão e controle do trocador de calor poderá ser usado como ferramenta didática para alunos de diversos cursos, onde é possível realizar ensaios de diferentes estruturas de controle para posterior comparação e estudo de seus resultados. Resultados práticos de todas as estruturas de controle que o software implementa são apresentados e comparados neste trabalho. / This work presents thorough a supervision and control system project of a heat exchanger, from the experimental tests for the mathematical model rising to the control system implementation and supervision in a microcomputer. The implemented system consists of didactic software and a data acquisition system that will perform the supervision and control of a heat exchanger shell and tube type. In this didactic software it is possible to implement the PID control and its variations PI-D and I-PD besides allowing the implementation of the adaptive control system gain scheduling structure, which changes the PID control parameters according to the changes of the heat exchanger dynamics. As the heat exchanger presents dead time on its dynamics, it was opted to add to the didactic software a control with Smith Predictor structure predictive algorithm, thus it is possible to perform tests with and without the predictive algorithm for result comparison. This supervision and control system of the heat exchanger will be able to be used as a didactic tool for students from several courses, where it is possible to perform tests with different control structures to further comparison and study of its results. Pratical results of all the control structures that the software implements are presented and compared in this work.

As reinternações psiquiátricas são consequência de uma complexa combinação de situações que vão além da severidade do próprio transtorno mental. Vários fatores relacionados ao paciente, comunidade e ao sistema de saúde têm sido associados com admissões psiquiátricas recorrentes. A Reforma Psiquiátrica determinou uma mudança da base assistencial fortalecendo modalidades de tratamento comunitário. Neste contexto, a análise das readmissões assumiu um papel de destaque para a organização das redes de saúde mental, pois a dinâmica das re-internações poderá ser um indicador de qualidade dos serviços hospitalares e comunitários possibilitando a compreensão das relações entre estes serviços. Como a região de Ribeirão Preto passou a enfrentar problemas pelo aumento do número de internações e pela falta de leitos psiquiátricos disponíveis para admissão de novos pacientes, organizamos esta pesquisa objetivando verificar eventuais mudanças nas características clínicas e sócio-demográficas dos pacientes admitidos pela primeira vez além de analisar possíveis fatores preditores de re-internações psiquiátricas. Nesse estudo, todos os pacientes admitidos nos serviços de internação entre os anos de 2000 e 2007 foram analisados utilizando banco de dados único criado para a pesquisa de modo que todas as admissões e readmissões do período pudessem ser estudadas. A análise dos pacientes internados no decorrer dos anos foi realizada utilizando a razão dos pacientes em relação ao ano índice para cada variável e com análise bivariada utilizando o teste do qui-quadrado. Para analisar o risco de readmissão, foi utilizada regressão logística para estimar as razões de risco relativo com seus respectivos intervalos de confiança. A análise do tempo entre a primeira e a segunda internação (readmissão) foi executada com curvas de sobrevivência. Durante o período estudado, 6.261 pacientes foram admitidos sendo verificado aumento na proporção de pacientes com algumas características sócio-demográficas (jovens, idosos e inativos profissionalmente) e clínicas (internações breves e com diagnósticos de transtornos depressivos, transtornos de personalidade e os transtornos relacionados ao uso de substâncias psicoativas). Cerca de 1/3 dos pacientes admitidos sofreram readmissões durante o estudo e os principais preditores para re-internação foram faixas etárias menores, internações prolongadas e diagnósticos transtornos psicóticos e afetivos bipolares. O risco de re-internação precoce esteve relacionado com fatores de desproteção social (menor faixa etária e ausência de vínculos conjugais e ocupacionais) e de gravidade clínica (diagnósticos mais severos, tempo de permanência prolongado e internação nas enfermarias do hospital geral e do hospital psiquiátrico). Nossos dados alcançaram os objetivos propostos e novas pesquisas são necessárias para definição de preditores pera re-internações, pois usuários frequentes do sistema hospitalar geram custos para a rede de saúde. Portanto, as políticas de saúde mental devem priorizar estes pacientes. / Psychiatric readmissions are mainly due to a complex combination of factors which go beyond the mental illness itself. Several factors associated to the patient, community and health care system have been associated to recurrent psychiatric admissions. The Psychiatric Reform has determined a shift in the basic services strengthening community treatment modalities. In this context, re-admission analyses have taken a major role in organizing mental health networks, because the dynamics of re-admissions could be an indicator of the quality of the hospital and community-based services offered allowing a better understanding of the relations between these services. As the Ribeirão Preto region has suffered from the increase of admissions and the lack of beds in psychiatric wards, we organized this research aiming at verifying possible changes in the socio-demographic and clinical characteristics of patients admitted for the first time besides analyzing possible factors for re-admissions. In this study, all patients admitted to psychiatric wards between 2000 and 2007 were analyzed using a single data base created for this research so that all admissions and re-admissions during the period could be studied. The hospitalized patients analysis along the years was accomplished using the ratio patient/index year for each variable and through a bivariant analysis using the chi-square test. In order to analyze the re-admission risk, logistic regression was used to evaluate the relative risk reasons with their respective confidence interval. Analysis of the time between first and second admission (re-admission) was made according to survival curves. During the time under study, 6.261 patients were admitted. It occurred an increase in the proportion of patients with some socio-demographic (young and elderly people clinically affected as well as professionally inactive) and clinical characteristics (short stays due to depressive, personality and psychoactive substance abuse diagnostics). About 1/3 of admitted patients went through a re-admission during the research and the main predictors for re-admission were: younger age group, prolonged length of stay in hospitals and psychotic or bipolar affective disorder diagnoses. Precocious re-admission risk was related to a lack of social protection (younger age group and absence of occupational and marital bonds) as well as the clinical seriousness (more severe dignoses, longer stay in hospital (general or psychiatric). Our data has reached the proposed goals but new researches are needed in order to define better the re-admission predictors, because frequent users of the health care system entail higher costs. Therefore, mental health policies must prioritize these patients.

Os modelos beta mistos são amplamente utilizados na análise de dados que apresentam uma estrutura hierárquica e que assumem valores em um intervalo restrito conhecido. Com o objetivo de propor um método de predição dos componentes aleatórios destes, os resultados previamente obtidos na literatura para o preditor de Bayes empírico foram estendidos aos modelos de regressão beta com intercepto aleatório normalmente distribuído. O denominado melhor preditor empírico (MPE) proposto tem aplicação em duas situações diferentes: quando se deseja fazer predição sobre os efeitos individuais de novos elementos de grupos que já fizeram parte da base de ajuste e quando os grupos não pertenceram à tal base. Estudos de simulação foram delineados e seus resultados indicaram que o desempenho do MPE foi eficiente e satisfatório em diversos cenários. Ao utilizar-se da proposta na análise de dois bancos de dados da área da saúde, observou-se os mesmos resultados obtidos nas simulações nos dois casos abordados. Tanto nas simulações, quanto nas análises de dados reais, foram observados bons desempenhos. Assim, a metodologia proposta se mostrou promissora para o uso em modelos beta mistos, nos quais se deseja fazer predições. / The mixed beta regression models are extensively used to analyse data with hierarquical structure and that take values in a restricted and known interval. In order to propose a prediction method for their random components, the results previously obtained in the literature for the empirical Bayes predictor were extended to beta regression models with random intercept normally distributed. The proposed predictor, called empirical best predictor (EBP), can be applied in two situations: when the interest is predict individuals effects for new elements of groups that were already analysed by the fitted model and, also, for elements of new groups. Simulation studies were designed and their results indicated that the performance of EBP was efficient and satisfatory in most of scenarios. Using the propose to analyse two health databases, the same results of simulations were observed in both two cases of application, and good performances were observed. So, the proposed method is promissing for the use in predictions for mixed beta regression models.