A method for tuning the spring rate and damping rate of a mountain bike suspension based on a data-driven procedure is presented. The design and development of a custom data acquisition system, known as the "MTB DAQ," capable of measuring acceleration data at the front and rear axles of a bike are discussed. These data are input into a model that is used to calculate the vertical acceleration and pitching angular acceleration response of the bike and rider. All geometric and dynamic properties of the bike and rider system are measured and built into the model. The model is tested and validated using image processing techniques. A genetic algorithm is implemented with the model and used to calculate the best spring rate and damping rate of the mountain bike suspension such that the vertical and pitching accelerations of the bike and rider are minimized for a given trail. Testing is done on a variety of different courses and the performance of the bike when tuned to the results of the genetic algorithm is discussed. While more fine tuning of the model is possible, the results show that the genetic algorithm and model accurately predict the best suspension settings for each course necessary to minimize the vertical and pitching accelerations of the bike and rider.

A multi-unit tracked vehicle such as a continuous haulage system is widely used in underground mining applications due to its high mobility and payload capacity on rugged and soft terrain. To automate such a system, a high fidelity model of a tracked vehicle is essential in designing a controller for each tracked vehicle in the system, and a system model is required to simulate its response to input commands. This thesis presents the 2-D mathematical models of a tracked vehicle and a multi-unit tracked vehicle. All existing track-terrain interaction models are investigated and modified. By employing the modified track-terrain interaction model and applying Newton's second law of motion, the equations of motion of both single and multi-unit tracked vehicles can be derived. Computer programs for simulating the motions of these tracked vehicles on level ground have been implemented on a digital computer based on the derived system of differential equations. The fourth-order Runge-Kutta and Keun's methods are adopted to numerically integrate these differential equations. The simulation results clearly show that the programs can accurately predict the motion of a tracked vehicle maneuvered on horizontal plane, and closely predict the response of a multi-unit tracked vehicle operated on level ground its command inputs. / Master of Science

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No description available.

No description available.

Forests perform many important ecological functions and provide numerous environmental services to humanity. Currently forests are under ever increasing pressures from humans through deforestation, changes in land use, and anthropogenic climate change. Managed forests play an important role in supplying forest products to the global population, necessitating the need to predict how forests will respond to climate change and how this will influence future wood product supplies. In this dissertation I used loblolly pine (Pinus taeda), the most extensively cultivated tree species in the United States, as a study system to simulate how climate change and forest management could alter the dynamics of managed forests in the future. Using the land component (the Community Land Model) of the widely used Community Earth System Model (CESM), I developed and validated a set of tools necessary to simulate the loblolly pine plantation system using the vegetation demography model embedded in CESM (FATES). This included developing a representation of loblolly pine using data from the literature, which was better able to capture forest growth and development observed in field studies than FATES's existing conifer tree representation. I added the ability to simulate several aspects of forest management not previously supported in FATES by creating the Vegetation Management Module, which I showed was able to realistically reproduce the common management practice of stand thinning. I used these new tools to perform simulations of how loblolly pine will grow across the Southeastern United States until the end of the 21st century, under the high and low climate change scenarios developed by the scientific community in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our experiments show that loblolly pine productivity may as much as double by the end of the century, with total wood harvest over that period increasing by almost half. I also showed that different management activities had significant effects on loblolly plantation yields, with mid-rotation stand thinning having an effect under both climate scenarios on par with increases due to the extreme climate change scenario SSP5 RCP8.5. I showed that these changes in wood yields could decrease the forest area in the Southeast required to meet the wood product demands over the rest of the century. These changes in plantation productivity could interact with socioeconomic factors to drive changes in land use and carbon storage in the Southeastern U.S. This work increases our understanding of how managed forests in the U.S.\ will be affected by climate change and how our management choices modulate that response. The techniques and tools developed here open up new areas of research into the role of forest management in the climate system. / Doctor of Philosophy / Forests benefit humans by regulating Earth's climate and by providing natural resources such as wood. In the Southeastern United States forestry is an important industry. Tree farms of southern pine trees produce a large percentage of the region's wood. Predicting how forests will grow in the future is important for planning and making investments. However, the burning of fossil fuels has increased carbon dioxide in the atmosphere and is changing Earth's climate. This is affecting how fast trees grow and how much wood can be harvested from forests. The methods that foresters have traditionally used to predict how trees will grow in the future do not account for climate change, and thus may not be as accurate in the future. An alternative is to use the computer models that scientists have developed to predict both how global climate will change in the future and how forests are influenced by climate. These computer programs can be used to predict how natural forests will grow in the future, but aren't set up to predict managed forests well. I made changes to one of these programs to make it possible to simulate the managed loblolly pine forests of the Southeastern United States. First, I tested these changes to make sure that simulated forests grew like real forests do today. Then I simulated how pine forests in Southeastern United States could grow over the next century with climate change. I found that pine forests will grow faster and allow more wood to be harvested as carbon dioxide in the atmosphere increases. If climate changes are extreme, loblolly forests could produce 70\% more wood than today by the end of the 21st century. I also showed that the manner in which forests were managed in simulations changes the amount of wood they produced, with some management practices increasing wood harvested by 50\% over the rest of the century. Because climate change could increase the amount of wood that can be produced from a fixed area of forest, I investigated how this might change the area of forest plantation in the Southeastern United States. Based on projections of demand for wood for the rest of the century I calculated how much loblolly pine forest would be needed to produce this wood over the next century. I found that increases in forest productivity due to climate change and forest management could decrease the forest area required to grow the wood we need. This could change how we use forests in the Southeastern United States, which in turn could have impacts on the climate.

People’s selection of leisure activities is a complex choice because of implicit human factors and explicit environmental factors. Satisfactory participation in leisure activities is an important task since keeping a regular active lifestyle can help to maintain and improve the wellbeing of people. Technology could help in selecting the most appropriate activities by designing and implementing activities, collecting people profiles and their preferences relations. In fact, recommendation systems, have been successfully used in the last years in similar tasks with different types of recommendation systems. This thesis aims at the design, implementation, and evaluation of recommendation systems that could help us to better understand the complex choice of selecting leisure activities. In this work, we first define an evaluation framework for different recommendations systems. Then we compare their performances using different evaluation metrics. Thus, we explore and try to better understand the user’s preferences over leisure activities. After, having a comprehensive analysis of modelling recommended items and leisure activities, we also design and implement a content-based leisure activity recommendation system to make use of a taxonomy of activities. Moreover, in the course of our research, we have collected and evaluated two datasets obtained one from the Meetup social network and the other from crowd-workers and made them available as open data sources for further evaluation in the recommendation system research community.

A modelagem farmacocinética permite prever a concentração de medicamentos em diferentes tecidos do organismo humano. O desenvolvimento de modelos matemáticos é importante para verificar a adequação de certos procedimentos realizados na administração de medicamentos. O objetivo deste trabalho é o desenvolvimento de um modelo farmacocinético capaz de prever a concentração plasmática de drogas no organismo para diversas formas de infusão. Foram utilizados dois tipos de abordagem. Inicialmente, na abordagem monocompartimental, considerou-se que a droga adentra ao organismo diretamente no compartimento sanguíneo, que representa todo o corpo humano. Já na abordagem bicompartimental foram considerados os seguintes compartimentos: um representando o meio pelo qual a droga é infundida no organismo (podendo ser via gastrointestinal, transdermal ou pulmonar) e outro representando o plasma sanguíneo. Em ambos os casos, foi considerada a hipótese de concentração homogênea da droga nos compartimentos em questão. O modelo foi estruturado na forma de diagramas de blocos e a solução foi feita com a utilização da Transformada de Laplace. Foi feita a validação dos modelos e verificou-se que os resultado gerados foram muito próximos dos resultados presentes na literatura. A utilização do modelo monocompartimental permitiu comparar os resultados da administração da mesma quantidade de droga por infusão constante e por infusão periódica. A análise dos resultados gerados pelo modelo mostrou que as concentrações atingidas pelos dois métodos não são as mesmas. O modelo bicompartimental permitiu simular administrações orais e transdermais, e inalação. Foi possível prever a concentração sanguínea após a interrupção da terapia com anti-concepcionais e anti-depressivos e foi verificado o tempo necessário para que esta concentração seja atingida novamente. Foram propostos métodos para que esta concentração fosse atingida em um menor período de tempo. Outra aplicação foi na comparação entre o tratamento com comprimidos inteiros e tomados pela metade em um intervalo menor de tempo. Verificou-se que a concentração atingida é diferente mesmo que a massa ingerida seja a mesma. O modelo também foi utilizado para calcular a concentração de nicotina após o consumo de cigarros e verificou-se que, o indivíduo que fuma a cada três horas não consegue eliminar totalmente a nicotina de seu organismo. Além disso, foi possível simular a sobredosagem de um anti-inflamatório e verificar o tempo em que a concentração fica acima do nível terapêutico. Foi proposto um método para obtenção do parâmetro farmacocinético relacionado à absorção, que pode ser obtido facilmente a partir de dados presentes nas bulas dos medicamentos. Este método é muito mais simples e preciso do que e proposto na literatura, que utiliza análise gráfica e dados clínicos que não são obtidos com tanta facilidade. / The pharmacokinetic modeling can predict the concentration of drug in different tissues of the human body. The development of mathematical models is an important tool to verify the appropriateness of certain procedures performed in medication administration. The objective of this work is to develop a pharmacokinetic model able to predict the plasma concentration of drug in the body after various forms of infusion. Two approaches were used. Initially, in the one-compartment approach it was considered that the drug enters the body directly into the blood compartment, which represents the entire human body. In the two-compartment approach it was considered the following compartments: one representing the means by which the drug is infused into the body (either via the gastrointestinal tract, lung, or transdermal) and one representing the blood plasma. In both cases, it was considered homogeneous concentration of the drug in the compartments. The model was built by using block diagrams and the solution was obtained using the Laplace Transform. The model was validated by comparing its results to literature data, with very good agreement. The model allowed comparing the one-compartment constant infusion of drug in the body with the periodic infusion. The analysis of the results generated by the model showed that the concentrations achieved by these methods are not the same. The two-compartment model allowed simulating oral and transdermal administration, and inhalation. It was possible to predict blood concentration after interruption of therapy with anti-depressants and anti-conceptional drugs. The model was able to verify the time it takes to reach the former level. Methods have been proposed to achieve the same concentration in a shorter period of time. Another application was the comparison of the treatment with whole tablets and taken by half in a smaller interval of time. It was found that the concentration achieved is different even though the same mass is ingested in both cases. The model was also used to calculate the concentration of nicotine after cigarette smoking and it was found that the individual who smokes every three hours, nicotine is not entirely eliminated from body. Furthermore, it was possible to simulate overdose of an anti-inflammatory and the period of time when the concentration is above the therapeutic level. It has been proposed a method to obtain pharmacokinetic parameter related to absorption, which can be easily obtained based on data present in the drug bull. This method is much simpler and more accurate than the method proposed in the, which uses graphical analysis and clinical data that are not so easy to be obtained.

O modelamento matemático de sistemas físicos é fundamental para diversas aplicações de processamento digital de sinais (PDS). Em muitos dos problemas enfrentados nesse contexto, para que um modelo seja útil, é necessário que ele represente seu análogo físico com precisão e possua características favoráveis para implementação, como estabilidade e compacidade. A obtenção de um modelo que atenda a estes requisitos depende da escolha de um formalismo matemático apropriado. Em se tratando do modelamento de sistemas (significativamente) não-lineares, tal decisão é particularmente desafiadora, uma vez que muitos formalismos com propriedades diferentes foram propostos na literatura. Basicamente, isto se deve à inexistência de uma teoria completa e geral para sistemas não-lineares, diferentemente do que ocorre no caso linear. Porém, em diversos trabalhos que lidam com aplicações nas quais é necessário modelar dispositivos não-lineares, adota-se alguma representação sem que sejam fornecidas justificativas claras e fundamentadas em características físicas do sistema a ser modelado. Ao invés disso, esse importante aspecto é discutido apenas superficialmente, com base em argumentos informais ou heurísticos. Adicionalmente, a definição de certas características estruturais de um modelo que possuem grande impacto sobre seu desempenho frequentemente não é feita de maneira sistemática, o que dificulta uma compreensão precisa do potencial do formalismo subjacente. Visando auxiliar na escolha por um formalismo adequado em aplicações de PDS, neste trabalho propõe-se uma metodologia de avaliação do desempenho de formalismos não-lineares que se apoia sobre considerações físicas. Para tanto, emprega-se um modelo físico do sistema de interesse como referência. Mais especificamente, a estratégia adotada baseia-se em fazer uso do método de bilinearização de Carleman para se obter, a partir deste modelo e de um conjunto de parâmetros típicos, um conjunto de núcleos de Volterra de referência. Uma vez que os núcleos de referência são obtidos, pode-se estimar, por exemplo, a ordem e a extensão de memória mínimas que um filtro de Volterra convencional deve possuir para se atingir o nível de precisão desejado, o que permite avaliar se o uso de modelos deste tipo é viável em termos de custo computacional. Quando este não é o caso, as informações fornecidas pelos núcleos podem ser exploradas para se escolher outra representação, como uma estrutura modular ou uma estrutura de Volterra alternativa. Além disso, os núcleos de referência são úteis ainda para se realizar uma avaliação quantitativa do desempenho da estrutura escolhida e compará-lo com aquele apresentado por um filtro de Volterra convencional. Para a realização do cômputo dos núcleos de referência, um algoritmo que implementa eficientemente o método de Carleman foi proposto. Tal algoritmo, juntamente com a ideia básica da metodologia desenvolvida, constituem as principais contribuições deste trabalho. Como estudo de caso, emprega-se um modelo físico para alto-falantes disponível na literatura para a avaliação da adequação de diversas estruturas ao modelamento de dispositivos deste tipo. Com este exemplo, demonstra-se a utilidade dos núcleos de referência para as finalidades supracitadas. / The mathematical modeling of physical systems is essential for several digital signal processing (DSP) applications. In many problems faced in this context, if a model is to be useful, it must represent its physical analog with precision and possess characteristics that favour implementation, such as stability and compactness. In order to obtain a model that meets those requirements, it is indispensable to choose an appropriate formalism. Regarding the modeling of (significantly) nonlinear systems, this decision is a particularly challenging problem, since many formalisms with different properties have been proposed in the literature. Basically, this is due to the inexistence of a complete and general theory for nonlinear systems as there is in the linear case. In several works that deal with applications in which it is necessary to model nonlinear devices, some representation is adopted without the provision of clear and physically motivated justifications. Instead, this important aspect is discussed only superficially, based on an informal or heuristic reasoning. Additionally, the definition of certain structural characteristics of a model which have great influence on its performance is frequently done in a non-systematic manner, which difficults a precise comprehension of the potential of the underlying formalism. Aiming to assist the choice of an adequate formalism in DSP applications, in this work we propose a methodology for evaluating the performance of nonlinear models that relies on physical considerations. For this purpose, a physical model of the system of interest is used as a reference. Specifically, the adopted strategy is based on using the Carleman bilinearization method for obtaining a set of reference Volterra kernels from that model, considering typical parameter values. Once the reference kernels are obtained, we can estimate, for instance, the order and the minimal memory extension that a conventional Volterra filter must have in order to achieve the desired precision level, which allows us to assess whether using models of this type is feasible in terms of computational cost. When this is not the case, the information provided by the kernels may be exploited for choosing another representation, as a modular structure or an alternative Volterra structure. Furthermore, the reference kernels are also useful for quantitatively evaluating the performance of the chosen structure and for comparing it with a conventional Volterra filter. To perform the reference kernels computation, an efficient algorithm for the Carleman method is proposed. This algorithm, together with the basic idea of the developed methodology, constitute the main contributions of this work. As a case study, a physical model for loudspeakers available in the literature is employed for assessing the suitableness of several structures for modeling devices of this kind. With this example, we show the utility of the reference kernels for the aforementioned purposes.

O modelamento matemático de sistemas físicos é fundamental para diversas aplicações de processamento digital de sinais (PDS). Em muitos dos problemas enfrentados nesse contexto, para que um modelo seja útil, é necessário que ele represente seu análogo físico com precisão e possua características favoráveis para implementação, como estabilidade e compacidade. A obtenção de um modelo que atenda a estes requisitos depende da escolha de um formalismo matemático apropriado. Em se tratando do modelamento de sistemas (significativamente) não-lineares, tal decisão é particularmente desafiadora, uma vez que muitos formalismos com propriedades diferentes foram propostos na literatura. Basicamente, isto se deve à inexistência de uma teoria completa e geral para sistemas não-lineares, diferentemente do que ocorre no caso linear. Porém, em diversos trabalhos que lidam com aplicações nas quais é necessário modelar dispositivos não-lineares, adota-se alguma representação sem que sejam fornecidas justificativas claras e fundamentadas em características físicas do sistema a ser modelado. Ao invés disso, esse importante aspecto é discutido apenas superficialmente, com base em argumentos informais ou heurísticos. Adicionalmente, a definição de certas características estruturais de um modelo que possuem grande impacto sobre seu desempenho frequentemente não é feita de maneira sistemática, o que dificulta uma compreensão precisa do potencial do formalismo subjacente. Visando auxiliar na escolha por um formalismo adequado em aplicações de PDS, neste trabalho propõe-se uma metodologia de avaliação do desempenho de formalismos não-lineares que se apoia sobre considerações físicas. Para tanto, emprega-se um modelo físico do sistema de interesse como referência. Mais especificamente, a estratégia adotada baseia-se em fazer uso do método de bilinearização de Carleman para se obter, a partir deste modelo e de um conjunto de parâmetros típicos, um conjunto de núcleos de Volterra de referência. Uma vez que os núcleos de referência são obtidos, pode-se estimar, por exemplo, a ordem e a extensão de memória mínimas que um filtro de Volterra convencional deve possuir para se atingir o nível de precisão desejado, o que permite avaliar se o uso de modelos deste tipo é viável em termos de custo computacional. Quando este não é o caso, as informações fornecidas pelos núcleos podem ser exploradas para se escolher outra representação, como uma estrutura modular ou uma estrutura de Volterra alternativa. Além disso, os núcleos de referência são úteis ainda para se realizar uma avaliação quantitativa do desempenho da estrutura escolhida e compará-lo com aquele apresentado por um filtro de Volterra convencional. Para a realização do cômputo dos núcleos de referência, um algoritmo que implementa eficientemente o método de Carleman foi proposto. Tal algoritmo, juntamente com a ideia básica da metodologia desenvolvida, constituem as principais contribuições deste trabalho. Como estudo de caso, emprega-se um modelo físico para alto-falantes disponível na literatura para a avaliação da adequação de diversas estruturas ao modelamento de dispositivos deste tipo. Com este exemplo, demonstra-se a utilidade dos núcleos de referência para as finalidades supracitadas. / The mathematical modeling of physical systems is essential for several digital signal processing (DSP) applications. In many problems faced in this context, if a model is to be useful, it must represent its physical analog with precision and possess characteristics that favour implementation, such as stability and compactness. In order to obtain a model that meets those requirements, it is indispensable to choose an appropriate formalism. Regarding the modeling of (significantly) nonlinear systems, this decision is a particularly challenging problem, since many formalisms with different properties have been proposed in the literature. Basically, this is due to the inexistence of a complete and general theory for nonlinear systems as there is in the linear case. In several works that deal with applications in which it is necessary to model nonlinear devices, some representation is adopted without the provision of clear and physically motivated justifications. Instead, this important aspect is discussed only superficially, based on an informal or heuristic reasoning. Additionally, the definition of certain structural characteristics of a model which have great influence on its performance is frequently done in a non-systematic manner, which difficults a precise comprehension of the potential of the underlying formalism. Aiming to assist the choice of an adequate formalism in DSP applications, in this work we propose a methodology for evaluating the performance of nonlinear models that relies on physical considerations. For this purpose, a physical model of the system of interest is used as a reference. Specifically, the adopted strategy is based on using the Carleman bilinearization method for obtaining a set of reference Volterra kernels from that model, considering typical parameter values. Once the reference kernels are obtained, we can estimate, for instance, the order and the minimal memory extension that a conventional Volterra filter must have in order to achieve the desired precision level, which allows us to assess whether using models of this type is feasible in terms of computational cost. When this is not the case, the information provided by the kernels may be exploited for choosing another representation, as a modular structure or an alternative Volterra structure. Furthermore, the reference kernels are also useful for quantitatively evaluating the performance of the chosen structure and for comparing it with a conventional Volterra filter. To perform the reference kernels computation, an efficient algorithm for the Carleman method is proposed. This algorithm, together with the basic idea of the developed methodology, constitute the main contributions of this work. As a case study, a physical model for loudspeakers available in the literature is employed for assessing the suitableness of several structures for modeling devices of this kind. With this example, we show the utility of the reference kernels for the aforementioned purposes.