918 resultados para Linear quadratic Gaussian control


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Pós-graduação em Zootecnia - FCAV

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Pós-graduação em Engenharia Mecânica - FEIS

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In the present study, the daily relative growth rates (DRGR, in percent per day) of the red macroalga Gracilaria domingensis in synthetic seawater was investigated for the combined influence of five factors, i.e., light (L), temperature (T), nitrate (N), phosphate (P), and molybdate (M), using a statistical design method. The ranges of the experimental cultivation conditions were T, 18-26A degrees C; L, 74-162 mu mol photons m(-2) s(-1); N, 40-80 mu mol L-1; P, 8-16 mu mol L-1; and M, 1-5 nmol L-1. The optimal conditions, which resulted in a maximum growth rate of a parts per thousand yen6.4% d(-1) from 7 to 10 days of cultivation, were determined by analysis of variance (ANOVA) multivariate factorial analysis (with a 2(5) full factorial design) to be L, 74 mu mol photons m(-2) s(-1); T, 26A degrees C; N, 80 mu mol L-1; P, 8 mu mol L-1; and M, 1 nmol L-1. In additional, these growth rate values are close to the growth rate values in natural medium (von Stosch medium), i.e., 6.5-7.0% d(-1). The results analyzed by the ANOVA indicate that the factors N and T are highly significant linear terms, X (L), (alpha = 0.05). On the other hand, the only significant quadratic term (X (Q)) was that for L. Statistically significant interactions between two different factors were found between T vs. L and N vs. T. Finally, a two-way (linear/quadratic interaction) model provided a quite reasonable correlation between the experimental and predicted DRGR values (R (adjusted) (2) = 0.9540).

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The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

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In order to overcome the limitations of the linear-quadratic model and include synergistic effects of heat and radiation, a novel radiobiological model is proposed. The model is based on a chain of cell populations which are characterized by the number of radiation induced damages (hits). Cells can shift downward along the chain by collecting hits and upward by a repair process. The repair process is governed by a repair probability which depends upon state variables used for a simplistic description of the impact of heat and radiation upon repair proteins. Based on the parameters used, populations up to 4-5 hits are relevant for the calculation of the survival. The model describes intuitively the mathematical behaviour of apoptotic and nonapoptotic cell death. Linear-quadratic-linear behaviour of the logarithmic cell survival, fractionation, and (with one exception) the dose rate dependencies are described correctly. The model covers the time gap dependence of the synergistic cell killing due to combined application of heat and radiation, but further validation of the proposed approach based on experimental data is needed. However, the model offers a work bench for testing different biological concepts of damage induction, repair, and statistical approaches for calculating the variables of state.

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En este proyecto se desarrolla un sistema electrónico para variar la geometría de un motor de un monoplaza que participa en la competición Fórmula SAE. Fórmula SAE es una competición de diseño de monoplazas para estudiantes, organizado por “Society of Automotive Enginners” (SAE). Este concurso busca la innovación tecnológica de la automoción, así como que estudiantes participen en un trabajo real, en el cual el objetivo es obtener resultados competitivos cumpliendo con una serie de requisitos. La variación de la geometría de un motor en un vehículo permite mejorar el rendimiento del monoplaza consiguiendo elevar el par de potencia del motor. Cualquier mejora en del vehículo en un ámbito de competición puede resultar determinante en el desenlace de la misma. El objetivo del proyecto es realizar esta variación mediante el control de la longitud de los tubos de admisión de aire o “runners” del motor de combustión, empleando un motor lineal paso a paso. A partir de la información obtenida por sensores de revoluciones del motor de combustión y la posición del acelerador se debe controlar la distancia de dichos tubos. Integrando este sistema en el bus CAN del vehículo para que comparta la información medida al resto de módulos. Por todo esto se realiza un estudio aclarando los aspectos generales del objetivo del trabajo, para la comprensión del proyecto a realizar, las posibilidades de realización y adquisición de conocimientos para un mejor desarrollo. Se presenta una solución basada en el control del motor lineal paso a paso mediante el microcontrolador PIC32MX795F512-L. Dispositivo del fabricante Microchip con una arquitectura de 32 bits. Este dispone de un módulo CAN integrado y distintos periféricos que se emplean en la medición de los sensores y actuación sobre el motor paso a paso empleando el driver de Texas Instruments DRV8805. Entonces el trabajo se realiza en dos líneas, una parte software de programación del control del sistema, empleando el software de Microchip MPLABX IDE y otra parte hardware de diseño de una PCB y circuitos acondicionadores para la conexión del microcontrolador, con los sensores, driver, motor paso a paso y bus CAN. El software empleado para la realización de la PCB es Orcad9.2/Layout. Para la evaluación de las medidas obtenidas por los sensores y la comprobación del bus CAN se emplea el kit de desarrollo de Microchip, MCP2515 CAN Bus Monitor Demo Board, que permite ver la información en el bus CAN e introducir tramas al mismo. ABSTRACT. This project develops an electronic system to vary the geometry of a car engine which runs the Formula SAE competition. Formula SAE is a design car competition for students, organized by "Society of Automotive Engineers" (SAE). This competition seeks technological innovation in the automotive industry and brings in students to participate in a real job, in which the objective is to obtain competitive results in compliance with certain requirements. Varying engine’s geometry in a vehicle improves car’s performance raising engine output torque. Any improvement in the vehicle in a competition field can be decisive in the outcome of it. The goal of the project is the variation by controlling the length of the air intake pipe or "runners" in a combustion engine, using a linear motor step. For these, uses the information gathered by speed sensors from the combustion engine and by the throttle position to control the distance of these tubes. This system is integrated in the vehicle CAN bus to share the information with the other modules. For all this is made a study to clarify the general aspects of the project in order to understand the activities developed inside the project, the different options available and also, to acquire knowledge for a better development of the project. The solution is based on linear stepper motor control by the microcontroller PIC32MX795F512-L. Device from manufacturer Microchip with a 32-bit architecture. This module has an integrated CAN various peripherals that are used in measuring the performance of the sensors and drives the stepper motor using Texas Instruments DRV8805 driver. Then the work is done in two lines, first, control programming software system using software MPLABX Microchip IDE and, second, hardware design of a PCB and conditioning circuits for connecting the microcontroller, with sensors, driver stepper motor and CAN bus. The software used to carry out the PCB is Orcad9.2/Layout. For the evaluation of the measurements obtained by the sensors and CAN bus checking is used Microchip development kit, MCP2515 CAN Bus Monitor Demo Board, that allows you to see the information on the CAN bus and enter new frames in the bus.

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Background: Epidemiologic evidence suggests that serum carotenoids are potent antioxidants and may play a protective role in the development of chronic diseases including cancers, cardiovascular disease, and inflammatory diseases. The role of these antioxidants in the pathogenesis of diabetes mellitus remains unclear. Objective: This study examined data from a cross-sectional survey to investigate the association between serum carotenoids and type 2 diabetes. Design: Study participants were adults aged >= 25 y (n = 1597) from 6 randomly selected cities and towns in Queensland, Australia. Study examinations conducted between October and December 2000 included fasting plasma glucose, an oral-glucose-tolerance test, and measurement of the serum concentrations of 5 carotenoid compounds. Results: Mean 2-h postload plasma glucose and fasting insulin concentrations decreased significantly with increasing quintiles of the 5 serum carotenoids-alpha-carotene, beta-carotene, beta-cryptoxanthin, lutein/zeaxanthin, and lycopene. Geometric mean concentrations for all serum carotenoids decreased (all decreases were significant except that of lycopene) with declining glucose tolerance status. beta-Carotene had the greatest decrease, to geometric means of 0.59, 0.50, and 0.42 mu mol/L in persons with normal glucose tolerance, impaired glucose metabolism, and type 2 diabetes, respectively (P < 0.01 for linear trend), after control for potential confounders. Conclusions: Serum carotenoids are inversely associated with type 2 diabetes and impaired glucose metabolism. Randomized trials of diets high in carotenoid-rich vegetables and fruit are needed to confirm these results and those from other observational studies. Such evidence would have very important implications for the prevention of diabetes.

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Since Shannon derived the seminal formula for the capacity of the additive linear white Gaussian noise channel, it has commonly been interpreted as the ultimate limit of error-free information transmission rate. However, the capacity above the corresponding linear channel limit can be achieved when noise is suppressed using nonlinear elements; that is, the regenerative function not available in linear systems. Regeneration is a fundamental concept that extends from biology to optical communications. All-optical regeneration of coherent signal has attracted particular attention. Surprisingly, the quantitative impact of regeneration on the Shannon capacity has remained unstudied. Here we propose a new method of designing regenerative transmission systems with capacity that is higher than the corresponding linear channel, and illustrate it by proposing application of the Fourier transform for efficient regeneration of multilevel multidimensional signals. The regenerative Shannon limit -the upper bound of regeneration efficiency -is derived. © 2014 Macmillan Publishers Limited. All rights reserved.

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2000 Mathematics Subject Classification: 62-04, 62H30, 62J20

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2000 Mathematics Subject Classification: 62H30, 62J20, 62P12, 68T99

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The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.