As atividades sócio-econômicas vêm provocando alterações nocivas ao meio ambiente que atualmente assumem proporções mundiais. Graças à maciça utilização de combustíveis fósseis para a geração de energia e às crescentes práticas de desmatamento e queimadas das florestas, a concentração de dióxido de carbono (CO2) na atmosfera vem aumentando drasticamente. Como este gás é o principal responsável pelo efeito estufa, ele tem grande importância nos estudos e na mitigação do aquecimento global. Para justificar o seqüestro de carbono como um dos caminhos para ajudar na solução deste problema, muitos estudos vêm sendo realizados para avaliar os efeitos nas plantas de uma maior concentração desse gás. As câmaras de topo aberto (OTC, do inglês, open top chambers) são estruturas propícias para tais estudos, pois permitem o controle da concentração de CO2 interno sem que outros fatores climáticos como temperatura, umidade e luminosidade sejam demasiadamente alterados. Este trabalho teve como objetivo o desenvolvimento de um sistema para controlar o nível de CO2 no interior de uma OTC. Em termos de instrumentação eletrônica, foram instalados um sensor de CO2 e uma válvula proporcional, integrados a uma placa de aquisição de dados. Um modelo linear relacionando o CO2 na câmara ao sinal elétrico aplicado à válvula proporcional foi obtido aplicando-se técnicas de Identificação de Sistemas aos dados experimentais coletados com o processo operando em malha aberta. Este modelo foi utilizado no projeto de um controlador com compensação de tempo morto, baseado na estrutura de um preditor de Smith. O desempenho do sistema projetado foi analisado através de simulações, antes de implementá-lo na forma de um instrumento virtual. Os testes mostraram que o sistema manteve a concentração de CO2 na câmara próxima do valor de referência (720 ± 35 ppm) mesmo diante de distúrbios externos criados propositadamente durante os ensaios. / The harmful changes to the environment caused by socio-economic activities are now spread worldwide. Due to the massive use of fossil fuels for energy generation, to the increase in deforestation and forest burning, the carbon dioxide (CO2) concentration in the atmosphere has drastically increased. As this gas is the main responsible for the greenhouse effect, it has great importance for the studies and the mitigation of global warming. In order to justify carbon sequestration as an alternative to help solve this problem, many studies have been conducted to evaluate the effect of a greater concentration of this gas on plants. Open-top chambers (OTCs) are well suited for such studies, because they allow the control of the internal CO2 concentration without significantly modifying other environmental factors such as temperature, humidity and luminosity. This work aimed to develop a system to control the CO2 level inside an OTC. In terms of electronic instrumentation, a CO2 sensor and a proportional valve, integrated to a data acquisition board, were used. A linear model relating CO2 in the chamber to the electric signal applied to the proportional valve was obtained applying System Identification techniques to the experimental data collected from the process operating in open-loop mode. This model was used in the project of a controller with dead time compensation, based on the Smith Predictor structure. The performance of the projected system was analyzed through simulations, before implementing it in the form of a virtual instrument. The tests showed that the system kept the CO2 concentration of the chamber near the set-point (720 ± 35 ppm) even in the presence of external disturbances purposely created during the experiments.

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.

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.

As atividades sócio-econômicas vêm provocando alterações nocivas ao meio ambiente que atualmente assumem proporções mundiais. Graças à maciça utilização de combustíveis fósseis para a geração de energia e às crescentes práticas de desmatamento e queimadas das florestas, a concentração de dióxido de carbono (CO2) na atmosfera vem aumentando drasticamente. Como este gás é o principal responsável pelo efeito estufa, ele tem grande importância nos estudos e na mitigação do aquecimento global. Para justificar o seqüestro de carbono como um dos caminhos para ajudar na solução deste problema, muitos estudos vêm sendo realizados para avaliar os efeitos nas plantas de uma maior concentração desse gás. As câmaras de topo aberto (OTC, do inglês, open top chambers) são estruturas propícias para tais estudos, pois permitem o controle da concentração de CO2 interno sem que outros fatores climáticos como temperatura, umidade e luminosidade sejam demasiadamente alterados. Este trabalho teve como objetivo o desenvolvimento de um sistema para controlar o nível de CO2 no interior de uma OTC. Em termos de instrumentação eletrônica, foram instalados um sensor de CO2 e uma válvula proporcional, integrados a uma placa de aquisição de dados. Um modelo linear relacionando o CO2 na câmara ao sinal elétrico aplicado à válvula proporcional foi obtido aplicando-se técnicas de Identificação de Sistemas aos dados experimentais coletados com o processo operando em malha aberta. Este modelo foi utilizado no projeto de um controlador com compensação de tempo morto, baseado na estrutura de um preditor de Smith. O desempenho do sistema projetado foi analisado através de simulações, antes de implementá-lo na forma de um instrumento virtual. Os testes mostraram que o sistema manteve a concentração de CO2 na câmara próxima do valor de referência (720 ± 35 ppm) mesmo diante de distúrbios externos criados propositadamente durante os ensaios. / The harmful changes to the environment caused by socio-economic activities are now spread worldwide. Due to the massive use of fossil fuels for energy generation, to the increase in deforestation and forest burning, the carbon dioxide (CO2) concentration in the atmosphere has drastically increased. As this gas is the main responsible for the greenhouse effect, it has great importance for the studies and the mitigation of global warming. In order to justify carbon sequestration as an alternative to help solve this problem, many studies have been conducted to evaluate the effect of a greater concentration of this gas on plants. Open-top chambers (OTCs) are well suited for such studies, because they allow the control of the internal CO2 concentration without significantly modifying other environmental factors such as temperature, humidity and luminosity. This work aimed to develop a system to control the CO2 level inside an OTC. In terms of electronic instrumentation, a CO2 sensor and a proportional valve, integrated to a data acquisition board, were used. A linear model relating CO2 in the chamber to the electric signal applied to the proportional valve was obtained applying System Identification techniques to the experimental data collected from the process operating in open-loop mode. This model was used in the project of a controller with dead time compensation, based on the Smith Predictor structure. The performance of the projected system was analyzed through simulations, before implementing it in the form of a virtual instrument. The tests showed that the system kept the CO2 concentration of the chamber near the set-point (720 ± 35 ppm) even in the presence of external disturbances purposely created during the experiments.

No description available.

Hotels have lost $3.4 billion over the last 5 years because of high rates of employee turnover. Leaders must use the tools necessary to increase job satisfaction and retain professional employees. The problem was that insufficient data described the relationships between transformational leadership, gender, education, and job satisfaction for hotel professionals. The purpose of this survey study was to understand the relationship between transformational leadership and job satisfaction for the hotel professionals in the United States. A total of 248 hotel professionals from the Colorado Lodging and Hotel Association were surveyed using the Multifactor Leadership Questionnaire and the Job Satisfaction Survey. The theoretical foundation of transformational leadership informed this study. Using a survey design, data were collected and a multiple regression technique was applied to analyze the data. Gender, education, and transformational leadership accounted for 20% of the variation in job satisfaction. Transformational-leadership style and gender were significant predictors of job satisfaction; however, education was not a significant predictor of job satisfaction. Results from this study may aid managers in learning to use transformational leadership to create necessary opportunities for hotel professionals to help increase their job satisfaction. Such leadership can lead to better productivity in the hotel industry with a positive contribution to hotel guests.

Predictive control relies on predictions of the future behaviour of the system to be controlled. These predictions are calculated from a model of this system, thus making the model the cornerstone of the predictive controller. Furthermore predictive control is the only advanced control methodology that has managed to become widely used in the industry. The necessity of good models in the predictive control context can thus be motivated both from the very nature of predictive control and from its widespread use in industry. This thesis is concerned with examining the use of multiple models in the predictive controller. In order to do this the standard predictive control formulation has been extended to incorporate the use of multiple models. The most general case of this new formulation allows the use of an individual model for each prediction horizon. The models are estimated using measurements of the input and output sequences from the true system. When using this data to find a good model of the system it is important to remember the intended purpose of the model. In this case the model is going to be used in a predictive controller and the most important feature of the models is to deliver good k-step ahead predictions. The identification algorithms used to estimate the models thus strives for estimating models good at calculating these predictions. Finally this thesis presents some complete simulations of these ideas showing the potential of using multiple models in the predictive control framework.

The ¡§Congestion Management¡¨ (CM) always has been an outstanding and major problem in power system operation. To solve this problem, experts compose solutions in a wide variety. This thesis, based on the equivalent current, applies the Equivalent Current Injection (ECI) concept and circuit parameters to derive the Power Flow Tracing Method (PFTM) . By means of this method we can get a Sensitive Matrix (SM), which is also called the Contribution Matrix (CM), to show the linear relationship between the input power and tidal current discharge of each generator set, with the linear relationship we can derive the mathematic model of treating the congestion problem discussed in this thesis. Combining the Predictor-Corrector Interior Point Algorithm (PCIPA), we can manipulate the change of each generator set in the prospective of solving the congestion problem resulting from the system contingency (SC). The thesis performed various simulations for the IEEE 30 Bus system. Regarding the power contingencies, the solutions of the power-congestion problems can be resulted from the following incidents: heavy load addition, transmission line tripped, generator malfunction as well as the multi-contingencies, etc., which can all be solved with solutions within reasonably restricted domains. We can thus verify the effectiveness of the method .

With the deregulation of power industry and the market competition, low cost, reliable power supply, and secured system operations are major concerns of the advanced deregulation markets. Power system protection is important for service reliability and quality assurance. To reduce the outage duration and promptly restore power services, fault section estimate has to be done effectively and accurately with fault alarms. First, an operational strategy for secondary power system restoration using Modified Grey Relational Analysis (MGRA) is proposed. The Restoration Scheme (RS) can be divided into three steps involving fault section determination, recovering process, and voltage correction process. Three GRAs are incorporated to design the overall restoration scheme. The first GRA uses network switching status to identify the fault. The second GRA combines switching states and load levels for network recovery. The third GRA uses capacitor bank control to support bus voltages. For security operation of restoration scheme, an Equivalent Current Injection (ECI) based hybrid current-power Optimal Power Flow (OPF) model with Predictor-Corrector Interior Point Algorithm (PCIPA) is used to verify the proposed scheme by off-line analysis to confirm a secure overall network operation including load-power balance, power generation limits, voltage limits, and power flow limits. The proposed method can further decompose into two sub-problems. Computer simulations were conducted with an IEEE 30-bus power system to show the effectiveness of the proposed restoration scheme and the PCIPA technique is very accurate, robust, and efficient for the modified OPF solution.

<p>Predictive control relies on predictions of the future behaviour of the system to be controlled. These predictions are calculated from a model of this system, thus making the model the cornerstone of the predictive controller. Furthermore predictive control is the only advanced control methodology that has managed to become widely used in the industry. The necessity of good models in the predictive control context can thus be motivated both from the very nature of predictive control and from its widespread use in industry. </p><p>This thesis is concerned with examining the use of multiple models in the predictive controller. In order to do this the standard predictive control formulation has been extended to incorporate the use of multiple models. The most general case of this new formulation allows the use of an individual model for each prediction horizon. </p><p>The models are estimated using measurements of the input and output sequences from the true system. When using this data to find a good model of the system it is important to remember the intended purpose of the model. In this case the model is going to be used in a predictive controller and the most important feature of the models is to deliver good k-step ahead predictions. The identification algorithms used to estimate the models thus strives for estimating models good at calculating these predictions. </p><p>Finally this thesis presents some complete simulations of these ideas showing the potential of using multiple models in the predictive control framework.</p>