Conselho Nacional de Desenvolvimento Científico e Tecnológico / Farming systems can act as a source or sink of atmospheric carbon, depending on the type of culture and soil management system adopted. This thesis presents a comparative study between the data obtained from two micrometeorological stations installed on the corn crop, in order to assess the impact of two tillage systems for corn (conventional tillage-CT and no-till-NT) in net ecosystem exchange of carbon fluxes (NEE). The flux were evaluated by the method of eddy covariance (EC), during the 156 days of maize. The results show that the two systems of planting corn act as drain CO2 −C and that there is a difference in the absorption ofCO2−C between the two planting systems with a NT with higher net exchange of carbon in the ecosystem in relation to CT . The biggest difference between the systems occurs in the first half cycle of corn, and after 40 days the cultures behave as a source of CO2−C, with higher values of CT issue at this time in relation to NT, and from then culture behaves as CO2−C drain. We conducted a study on the relative role of low-frequency and turbulent processes in the nocturnal boundary layer through the analysis of two-point correlations of wind components. Noting that the low-frequency processes dominate the two-point correlations in weak wind conditions, that the vertical two-point correlations of the spanwise component are negative at the very low time scale limit and that the statistical properties of the turbulent field are preserved horizontally over distances for which the two-points correlation have already been largely reduced. / Os sistemas agrícolas podem atuar como dreno ou fonte de carbono atmosférico, dependendo do tipo da cultura e do sistema de manejo do solo adotado. Este trabalho apresenta um estudo comparativo entre os dados obtidos a partir de duas estações micrometeorológicas instaladas sobre a cultura de milho, com o objetivo de avaliar o impacto de dois sistemas de semeadura de milho (preparo convencional-PC e plantio direto-PD) na troca líquida do ecossistema dos fluxos de carbono (NEE). Os fluxos foram avaliados pelo método de covariância de vórtices turbulentos (MCV), durante o período de 156 dias da cultura do milho. Os resultados obtidos mostram que os dois sistemas de cultivo de milho atuam como dreno de C−CO2 e que a há uma diferença quanto a absorção de C−CO2 entre os dois sistemas de plantio, com o PD apresentando maior troca líquida de carbono no ecossistema em relação ao PC. A maior diferença entre os sistemas ocorre na primeira metade do ciclo da cultura do milho, sendo que nos primeiros 40 dias as culturas se comportam como fonte de C−CO2, com o PC apresentando valores maiores de emissão neste período em relação ao PD, e a partir de então a cultura se comporta como dreno de C−CO2. Realizou-se um estudo sobre o papel relativo das baixa frequências e dos processos turbulentos na camada limite noturna através da análise de correlações de dois pontos das componentes do vento. Verificando-se que os processos de baixa frequência dominam as correlações de dois ponto em condições de vento fraco, que as correlações verticais de dois pontos da componente lateral do vento são negativas no limite de escala de tempo muito baixa e que as propriedades estatísticas do campo turbulento são preservadas horizontalmente ao longo de distâncias para os quais as correlações de dois pontos já foram largamente reduzidos.

This thesis is concerned with drawing out high-level insight from otherwise complex mathematical models of physical processes. This is achieved through detailed analysis of model behaviour as constituent parameters are varied. A particular focus is the well-posedness of parameter estimation from noisy data, and its relationship to the parametric sensitivity properties of the model. Other topics investigated include the verification of model performance properties over large ranges of parameters, and the simplification of models based upon their response to parameter perturbation. Several methodologies are proposed, which account for various model classes. However, shared features of the models considered include nonlinearity, parameters with considerable scope for variability, and experimental data corrupted by significant measurement uncertainty. We begin by considering models described by systems of nonlinear ordinary differen- tial equations with parameter dependence. Model output, in this case, can only be obtained by numerical integration of the relevant equations. Therefore, assessment of model behaviour over tracts of parameter space is usually carried out by repeated model simulation over a grid of parameter values. We instead reformulate this as- sessment as an algebraic problem, using polynomial programming techniques. The result is an algorithm that produces parameter-dependent algebraic functions that are guaranteed to bound user-defined aspects of model behaviour over parameter space. We then consider more general classes of parameter-dependent model. A theoretical framework is constructed through which we can explore the duality between model sensitivity to non-local parameter perturbations, and the well-posedness of parameter estimation from significantly noisy data. This results in an algorithm that can uncover functional relations on parameter space over which model output is insensitive and parameters cannot be estimated. The methodology used derives from techniques of nonlinear optimal control. We use this algorithm to simplify benchmark models from the systems biology literature. Specifically, we uncover features such as fast-timescale subsystems and redundant model interactions, together with the sets of parameter values over which the features are valid. We finally consider parameter estimation in models that are acknowledged to im- perfectly describe the modelled process. We show that this invalidates standard statistical theory associated with uncertainty quantification of parameter estimates. Alternative theory that accounts for this situation is then developed, resulting in a computationally tractable approximation of the covariance of a parameter estimate with respect to noise-induced fluctuation of experimental data.

This thesis investigates the interplay between explanatory issues in special relativity and the theory's metaphysical foundations. Special attention is given to the 'dynamical approach' to relativity, promoted primarily by Harvey Brown and collaborators, according to which the symmetries of dynamical laws are explanatory of relativistic effects, inertial motion, and even the Minkowskian geometrical structure of a specially relativistic world. The thesis begins with a review of Einstein's 1905 introduction to special relativity, after which brief historical introductions are given for the standard 'geometrical' approach to relativity and the unorthodox 'dynamical' approach. After a critical review of recent literature on the topic, the dynamical approach is shown to be in need of a metaphysical package that would undergird the explanatory claims mentioned above. It is argued that the dynamical approach is best understood as a form of relationalism - in particular, as a relativistic form of 'regularity relationalism', promoted recently by Nick Huggett. According to this view, some portion of a world's geometrical structure actually supervenes upon the symmetries of the best-system dynamical laws for a material ontology endowed with a primitive sub-metrical structure. To explore the plausibility of this construal of the dynamical approach, a case study is carried out on solutions to the Klein-Gordon equation. Examples are found for which the field values, when purged of all spatiotemporal structure but their induced topology, are still arguably best-systematized by the Klein-Gordon equation itself. This bolsters the plausibility of the claim that some system of field values, endowed with mere sub-metrical structure, might have as its best-systems dynamical laws a (set of) Lorentz-covariant equation(s), on which Minkowski geometrical structure would supervene. The upshot is that the dynamical approach to special relativity can be defended as what might be called an ontologically and ideologically relationalist approach to Minkowski spacetime structure. The chapters refer regularly to three appendices, which include a brief introduction to topological and differentiable spaces.

学位授与大学：京都大学 ; 取得学位: 博士(工学) ; 学位授与年月日: 2007-09-25 ; 学位の種類: 新制・課程博士 ; 学位記番号: 工博第2843号 ; 請求記号: 新制/工/1418 ; 整理番号: 25528 / The unsteady buffeting forces and the gust response prediction of bridges in the atmospheric turbulent flows is recently attracted more attention due to uncertainties in both experiment and analytical theory. The correction functions such as the aerodynamic admittance function and the spatial coherence function have been supplemented to cope with limitations of the quasi-steady theory and strip one so far. Concretely, so-called single-variate quasi-steady aerodynamic admittance functions as the transfer functions between the wind turbulence and induced buffeting forces, as well as coherence of wind turbulence has been widely applied for the gust response prediction. Recent literatures, however, pointed out that the coherence of force exhibits higher than that of turbulence. These correction functions, in the other words, contain their uncertainties which are required to be more understanding. Proper orthogonal decomposition (POD), known as the Karhunen-Loeve decomposition has been applied popularly in many engineering fields. Main advantage of the POD is that the multi-variate correlated random fields/processes can be decomposed and described in such simplified way as a combination of limited number of orthogonally low-order dominant eigenvectors (or turbulent modes) which is convenient and applicable for order-reduced representation, simulation of the random fields/processes such as the turbulent fields, turbulent-induced force fields and stochastic response prediction as well. The POD and its proper transformations based on either zero-time-lag covariance matrix or cross spectral one of random fields/processes have been branched by either the covariance proper transformation (CPT) in the time domain or the spectral proper transformation (SPT) in the frequency domain. So far, the covariance matrix-based POD and its covariance proper transformation in the time domain has been used almost in the wind engineering topics due to its simplification in computation and interpretation. In this research, the unsteady buffeting forces and the gust response prediction of bridges with emphasis on the POD applications have been discussed. Investigations on the admittance function of turbulent-induced buffeting forces and the coherence one of the surface pressure as well as the spatial distribution and correlation of the unsteady pressure fields around some typically rectangular cylinders in the different unsteady flows have been carried out thanks to physical measurements in the wind tunnel. This research indicated effect of the bluff body flow and the wind-structure interaction on the higher coherence of buffeting forces than the coherence of turbulence, thus this effect should be accounted and undated for recent empirical formulae of the coherence function of the unsteady buffeting forces. Especially, the multi-variate nonlinear aerodynamic admittance function has been proposed in this research, as well as the temporo-spectral structure of the coherence functions of the wind turbulence and the buffeting forces has been firstly here using the wavelet transform-based coherence in order to detect intermittent characteristics and temporal correspondence of these coherence functions. In POD applications, three potential topics in the wind engineering field have been discussed in the research: (i) analysis and identification, modeling of unsteady pressure fields around model sections; (ii) representation and simulation of multi-variate correlated turbulent fields and (iii) stochastic response prediction of structures and bridges. Especially, both POD branches and their proper transformations in the time domain and the frequency one have been used in these applications. It found from these studies that only few low-order orthogonal dominant modes are enough accuracy for representing, modeling, simulating the correlated random fields (turbulence and unsteady surface pressure, unsteady buffeting forces), as well as predicting stochastic response of bridges in the time and frequency domains. The gust response prediction of bridges has been formulated in the time domain at the first time in this research using the covariance matrix-based POD and its covariance proper transformation which is very promising to solve the problems of the nonlinear and unsteady aerodynamics. Furthermore, the physical linkage between these low-order modes and physical causes occurring on physical models has been interpreted in some investigated cases. / Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第13372号 / 工博第2843号 / 新制||工||1418(附属図書館) / 25528 / UT51-2007-Q773 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 松本 勝, 教授 河井 宏允, 准教授 白土 博通 / 学位規則第4条第1項該当

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-08-28T16:36:07Z No. of bitstreams: 1 CELINA CÂNDIDA FERREIRA RODRIGUES – DISSERTAÇÃO (PPGMET) 2018.pdf: 5069139 bytes, checksum: b64db0a7038e8010a2b92ce822daf969 (MD5) / Made available in DSpace on 2018-08-28T16:36:07Z (GMT). No. of bitstreams: 1 CELINA CÂNDIDA FERREIRA RODRIGUES – DISSERTAÇÃO (PPGMET) 2018.pdf: 5069139 bytes, checksum: b64db0a7038e8010a2b92ce822daf969 (MD5) Previous issue date: 2018-02-28 / CNPq / As florestas desempenham um papel importante na mitigação das mudanças climáticas, atuando como grandes armazenadoras de carbono por meio de sua produtividade primária. A produtividade primária bruta corresponde ao total de carbono fixado pela vegetação por meio do processo de fotossíntese. Neste sentido, o objetivo do trabalho foi avaliar a capacidade de fixação de carbono na bacia do rio Mogi-Guaçu, em especial nas áreas de cerrado e cana-de-açúcar no município de Santa Rita do Passa Quatro - SP, com base em estimativas efetivadas por meio de técnicas de sensoriamento remoto e proceder uma validação dos resultados segundo medidas realizadas pelo método da Eddy Coariance. Para a determinação da produtividade primária bruta foram determinados os balanços de radiação e energia por meio de imagens TM - Landsat 5 e OLI/TIRS - Landsat 8 utilizando a metodologia do SEBAL, para posterior comparação com a produtividade primária bruta do produto MOD17A2H e a estimada pelo método de eddy covariance. Foram selecionadas imagens sem presença de nuvens nos anos de 2005 e 2015, e empregadas as medições do fluxo de CO2 obtidas em duas torres micrometeorológicas instaladas em área de cana-de-açúcar e de Cerradão. As imagens Landsat proporcionaram maior concordância entre os dados de produtividade primária bruta em relação aos obtidos nas torres micrometeorológicas, diferentemente dos valores gerados com o MOD17A2H. A sazonalidade da produtividade primária bruta apresenta boa correspondência com os dados de precipitação pluviométrica registrados na área de estudo. O cerrado se comportou como sumidouro de carbono durante todo o ano, mesmo com precipitação abaixo da média, o que evidencia a necessidade de preservação deste bioma. / The forests play an important role in the mitigation of climate change by acting as large carbon sinks through their primary productivity. The gross primary productivity corresponds to the total carbon fixed by the vegetation through the photosynthesis process. In this way, the objective of this work was to evaluate the carbon fixation capacity in the Mogi-Guaçu river basin, especially in the cerrado and sugar cane areas in the municipality of Santa Rita do Passa Quatro - SP, based on estimates made by means of remote sensing techniques and validate the results according to measurements performed by the Eddy Coariance method. For the gross primary productivity determination, the radiation and energy balances were determined using TM - Landsat 5 and OLI / TIRS - Landsat 8 images using the SEBAL methodology, for further comparison with the gross primary productivity of the product MOD17A2H and the estimated by the eddy covariance method. Images were selected without clouds in the years 2005 and 2015, and measurements of the CO2 flux obtained in two micrometeorological towers installed in the area of sugarcane and Cerradão were used. The Landsat images provided greater agreement between the gross primary productivity data in relation to those obtained in the micrometeorological towers, unlike the values generated with the MOD17A2H. The seasonality of the gross primary productivity shows good correspondence with the rainfall data recorded in the study area. The cerrado has behaved as a carbon sink throughout the year, even with below-average precipitation, which it evidences the need for preservation of this biome.

The goal of the paper is to compare impacts of interest rate risk measuring meth-ods on capital requirements. The first section identifies methods for measuring interest rate risk and capital requirements for interest rate risk set by regulators. The second section compares capital requirements of model portfolio calculated by using standardized methods as well as internal models.

We discuss efficient Bayesian estimation of dynamic covariance matrices in multivariate time series through a factor stochastic volatility model. In particular, we propose two interweaving strategies (Yu and Meng, Journal of Computational and Graphical Statistics, 20(3), 531-570, 2011) to substantially accelerate convergence and mixing of standard MCMC approaches. Similar to marginal data augmentation techniques, the proposed acceleration procedures exploit non-identifiability issues which frequently arise in factor models. Our new interweaving strategies are easy to implement and come at almost no extra computational cost; nevertheless, they can boost estimation efficiency by several orders of magnitude as is shown in extensive simulation studies. To conclude, the application of our algorithm to a 26-dimensional exchange rate data set illustrates the superior performance of the new approach for real-world data. / Series: Research Report Series / Department of Statistics and Mathematics

Made available in DSpace on 2014-06-11T19:26:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-04-29Bitstream added on 2014-06-13T18:54:01Z : No. of bitstreams: 1 santos_dja_me_jabo.pdf: 949817 bytes, checksum: 99fe4837bb2182ae9951f9ef2a71f250 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Parâmetros genéticos para a produção de leite no dia do controle (PLDC) de primeiras lactações de vacas da raça Guzerá foram estimados utilizando modelo multicaracterísticas de dimensão finita (TMDO) e modelos de regressão aleatória (MRA). A produção acumulada em 305 dias (P305), duração da lactação (DL) e persistência da lactação (PS) também foram analisadas. Para o TMDO, foram analisadas as PLDC juntamente com a P305 e a DL, considerando como aleatórios, o efeito genético aditivo e o residual e, como fixo, o grupo de contemporâneos e a covariável idade da vaca ao parto. Para os MRA, foram considerados como aleatório, o efeito genético aditivo, de ambiente permanente e residual e como efeito fixo, o grupo de contemporâneos, os efeitos linear e quadrático da covariável idade ao parto e a curva média da população. Para os MRA foram consideradas as funções de ajuste de Wilmink (WL), Ali & Schaeffer (AS), uma combinação entre a função de Wilmink com polinômios ortogonais de Legendre (LM), polinômios ortogonais de Legendre (LEG) e funções B-spline (BS). Os efeitos aleatórios genético aditivo e de ambiente permanente foram modelados por meio destas funções, bem como a curva média da população, com a exceção dos modelos ajustados por funções BS que tiveram a curva média ajustada por polinômio de Legendre ou pela função de Ali & Schaeffer. O resíduo foi ajustado considerando variância homogênea ou em classes heterogêneas de variância residual. O modelo empregando funções BS cúbica com número de coeficientes de regressão aleatória igual cinco tanto para efeito genético aditivo como de ambiente permanente com a curva média modelada pela função de Ali & Schaeffer e resíduo ajustado por seis classes variância residual foi o mais adequado. Entretanto, os melhores MRA para cada função de ajuste, não apresentaram diferenças para... / Genetic parameters for milk production in the test day model (PLDC) for Guzerat dams’ first lactations were estimated by multitrait finite model (TMDO) and random regression models (MRA). The cumulative production at 305 days (P305), lactation length (DL) and lactation persistency (PS) were also analyzed. For TMDO, the PLDC were analyzed together with P305 and DL, considering the additive genetic effect and residual effect as random effects , the contemporary group as a fixed effect, and the age of dam at calving as a covariate. For MRA, additive genetic effect, permanent environmental effect and residual effect were considered as random effects and the contemporary group, the linear and quadratic covariate of age at calving and the average curve of the population as fixed effects. Also for the MRA, the Wilmink (WL) and the Ali & Schaeffer (AS) adjustment functions, a combination of the Wilmink function with Legendre orthogonal polynomials (LM), Legendre orthogonal polynomials (LEG) and B-spline functions (BS) were considered. The random additive genetic and permanent environmental effects were modeled by means of these functions, as well as the population average curve , with the exception of the adjusted models by the BS functions that had the average curve adjusted by the Legendre polynomial or by the Ali & Schaeffer function. The residual error was adjusted considering homogeneous variance or heterogeneous classes of residual variance. The model using cubic BS functions with random regression coefficient numbers equal to five for additive genetic effect as well as for permanent environmental with average curve modeled by the Ali & Schaeffer function and residual error adjusted for six classes of residual variance was the more appropriate. However, the best MRA for each adjustment function presented no differences in the estimates of genetic parameters and for order correlation ... (Complete abstract click electronic access below)

Made available in DSpace on 2014-06-11T19:32:15Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-02-26Bitstream added on 2014-06-13T20:03:29Z : No. of bitstreams: 1 bignardi_ab_dr_jabo.pdf: 1324029 bytes, checksum: eefcd7697892e45dbbe5b9ff67fbe3ce (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Parâmetros genéticos para a produção de leite no dia do controle (PLDC) de primeiras lactações de vacas da raça Holandesa foram estimados utilizando os modelos multicaracterísticas e modelos de regressão aleatória (MRA). Para os modelos multicaracterísticas foram analisados 15.896 controles mensais de produção de leite de 1.820 primeiras lactações de vacas da raça Holandesa. As análises foram realizadas por meio de sete modelos: multicaracterísticas padrão, três modelos de posto reduzido ajustando os primeiros 2,3 e 4 componentes principais genéticos e três modelos utilizando análise de fatores com 2,3 e 4 fatores. Para todos os modelos foram considerados os efeitos aleatórios genético aditivo e residual, e os efeitos sistemáticos do grupo de contemporâneo e da idade da vaca ao parto (efeito linear e quadrática) e do número de dias em lactação (efeito linear). A matriz de (co)variâncias residual, para todos os modelos, foi assumida ter posto completo. Os resultados indicam que somente dois componentes principais são requeridos para modelar a estrutura de (co)variâncias genéticas entre as produções de leite no dia do controle. Além disso, o modelo de posto reduzido diminui consideravelmente o número de parâmetros, sem reduzir a qualidade de ajuste. Para os MRA foram analisados 152.145 controles semanais de produção de leite de 7.317 primeiras lactações de vacas da raça Holandesa, provenientes de rebanhos da região Sudeste do Brasil. As produções de leite no dia do controle (PLDC) foram consideradas em 44 classes semanais de dia em lactação. Os grupos de contemporâneos foram definidos como rebanho-ano-semana do controle compondo 2.539 classes e, contendo, no mínimo, seis animais. O modelo utilizado incluiu os efeitos aleatórios genético aditivo direto, de ambiente permanente e o residual. Foram considerados como efeitos fixos, o grupo de... / Genetic parameters for first lactation test-day milk yields of Holstein cattle were estimated using multivariate and random regression models (RRM). For multivariate model a total of 15,896 individual monthly test-day milk yields (10 test-days), from 1,820 complete first lactations of Holstein cattle. A standard multivariate analysis, reduced rank analyses fitting the first 2, 3 and 4 genetic principal components, and analyses that fitted a factor analytic structure considering 2, 3 and 4 factors, were carried out. All models included also fixed effects of the contemporary groups, age of cow (linear and quadratic effects) and days in milk (linear effect). The residual covariance matrix was assumed to have full rank throughout. The results indicate that only two principal components are required to model the genetic covariance structure among the test-days milk yield. Furthermore, reduced rank model allows decreasing the number of parameter without reducing the goodness of fit considerably. For RRM A total of 152,145 weekly test-day milk yield records from 7,317 first lactations of Holstein cows distributed across 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of days in milk (DIM). The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM, and additive genetic and permanent environmental effects were estimated using B-splines. Residual variances were modeled by step function with 6 variance classes. Although all the model selection criteria utilized indicated the model employing cubic B-splines to both random effects, with 6 knots, a more parsimonious model ... (Complete abstract click electronic access below)

abstract: Tracking a time-varying number of targets is a challenging dynamic state estimation problem whose complexity is intensified under low signal-to-noise ratio (SNR) or high clutter conditions. This is important, for example, when tracking multiple, closely spaced targets moving in the same direction such as a convoy of low observable vehicles moving through a forest or multiple targets moving in a crisscross pattern. The SNR in these applications is usually low as the reflected signals from the targets are weak or the noise level is very high. An effective approach for detecting and tracking a single target under low SNR conditions is the track-before-detect filter (TBDF) that uses unthresholded measurements. However, the TBDF has only been used to track a small fixed number of targets at low SNR. This work proposes a new multiple target TBDF approach to track a dynamically varying number of targets under the recursive Bayesian framework. For a given maximum number of targets, the state estimates are obtained by estimating the joint multiple target posterior probability density function under all possible target existence combinations. The estimation of the corresponding target existence combination probabilities and the target existence probabilities are also derived. A feasible sequential Monte Carlo (SMC) based implementation algorithm is proposed. The approximation accuracy of the SMC method with a reduced number of particles is improved by an efficient proposal density function that partitions the multiple target space into a single target space. The proposed multiple target TBDF method is extended to track targets in sea clutter using highly time-varying radar measurements. A generalized likelihood function for closely spaced multiple targets in compound Gaussian sea clutter is derived together with the maximum likelihood estimate of the model parameters using an iterative fixed point algorithm. The TBDF performance is improved by proposing a computationally feasible method to estimate the space-time covariance matrix of rapidly-varying sea clutter. The method applies the Kronecker product approximation to the covariance matrix and uses particle filtering to solve the resulting dynamic state space model formulation. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015