The prairie communities that once dominated the landscape of Illinois have been reduced to a fraction of their former extent. Subsequently, considerable effort has been invested in the restoration of these lost communities, yet the comprehensive assessment of restoration success has only recently garnered interest. The objectives of this study were 1) to gauge the success of a prairie restoration project by measuring the components of ecological fidelity (structure/composition, function, and durability), and 2) to determine the factors that influenced success. Nineteen prairie plantings (ranging from two to 19 growing seasons old) at The Nature Conservancy's Nachusa Grasslands preserve were chosen for the assessment. Floristic quality was calculated to assess the composition component of ecological fidelity. Aboveground net primary productivity, soil bulk density, total soil nitrogen and total soil carbon were measured to assess the function component (soil measurements were taken at 0-5 and 5-15 cm depths). Results were compared to benchmark values taken from the literature and from samples of remnant prairies. Durability was determined by comparing measurements across a restoration chronosequence. To further evaluate the prairie plantings and restoration success, non-metric multidimensional scaling ordination was used to compare plantings based on their vegetation composition and soil characteristics (prairie remnants were also included in the comparison based on soil characteristics). Values of Mean C and FQI indicated successful levels among younger plantings, but durability was less successful according to the chronosequence. Seed-mix quality had the greatest influence (positive) on composition success. Aboveground net primary productivity levels were successful and durable overall, however, younger plantings exhibited successful levels of production more consistently than older plantings. Aboveground net primary productivity was most influenced (negatively) by the abundance of the exotic C3 grass genera Poa and Bromus. Functional success based on soil characteristics was limited. Soil bulk density, total nitrogen, and total carbon levels all differed among plantings and remnants at both depths, and evidence of levels recovering toward levels of remnants was not detected. The results of this study indicated that some components of ecological fidelity have been successfully restored, while others have not, and using a high-quality seed mix that resembles the species pool of remnant prairie and limiting the abundance of the dominant native C4 and exotic C3 grasses can improve the restoration of plant composition and ecological function in Illinois prairie plantings. The mixed results underscore the importance of examining more than one component of ecological fidelity when measuring success. Long-term monitoring is also recommended for evaluating restoration durability, especially for detecting changes among soil properties over time.

O modelo misto é comumente utilizado em dados de medidas repetidas devido a sua flexibilidade de incorporar no modelo a correlação existente entre as observações medidas no mesmo indivíduo e a heterogeneidade de variâncias das observações feitas ao longo do tempo. Este modelo é composto de efeitos fixos, efeitos aleatórios e o erro aleatório e com isso na seleção do modelo misto muitas vezes é necessário selecionar os melhores componentes do modelo misto de tal forma que represente bem os dados. Os critérios de informação são ferramentas muito utilizadas na seleção de modelos, mas não há muitos estudos que indiquem como os critérios de informação se desempenham na seleção dos efeitos fixos, efeitos aleatórios e da estrutura de covariância que compõe o erro aleatório. Diante disso, neste trabalho realizou-se um estudo de simulação para avaliar o desempenho dos critérios de informação AIC, BIC e KIC na seleção dos componentes do modelo misto, medido pela taxa TP (Taxa de verdadeiro positivo). De modo geral, os critérios de informação se desempenharam bem, ou seja, tiveram altos valores de taxa TP em situações em que o tamanho da amostra é maior. Na seleção de efeitos fixos e na seleção da estrutura de covariância, em quase todas as situações, o critério BIC teve um desempenho melhor em relação aos critérios AIC e KIC. Na seleção de efeitos aleatórios nenhum critério teve um bom desempenho, exceto na seleção de efeitos aleatórios em que considera a estrutura de simetria composta, situação em que BIC teve o melhor desempenho. / The mixed model is commonly used in data of repeated measurements because of its flexibility to incorporate in the model the correlation existing between the observations measured in the same individual and the heterogeneity of variances of observations made over time. This model is composed of fixed effects, random effects and random error and with this in the selection of the mixed model it is often necessary to select the best components of the mixed model in such a way that it represents the data well. Information criteria are tools widely used in model selection, but there are not many studies that indicate how information criteria play out in the selection of fixed effects, random effects, and the covariance structure that makes up the random error. In this work, a simulation study was performed to evaluate the performance of the AIC, BIC and KIC information criteria in the selection of the components of the mixed model, measured by the TP (True positive Rate). In general, the information criteria performed well, that is, they had high TP rate in situations where the sample size is larger. In the selection of fixed effects and in the selection of the covariance structure, in almost all situations, the BIC criterion had a better performance in relation to the AIC and KIC criteria. In the selection of random effects no criterion had a good performance, except in the selection of Random effects in which it considers the compound symmetric structure, situation in which BIC had the best performance.

This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis of thirteen information theoretic criterion (IC), one of which is a novel derivation. The simulation exercise considers the evaluation of seven alternative error restricted vector autoregressive models with four different lag lengths. Alternative sample sizes and parameterisations are also evaluated and compared to results in the existing literature. The results of the comparative analysis provide strong support for the efficiency based criterion of Akaike and in particular the selection capability of the novel criterion, referred to as a modified corrected Akaike information criterion, demonstrates useful finite sample properties.

The thesis discusses in detail some concepts of speech and prosody that can contribute to build a speech corpus for the speaker segmentation purpose. Moreover, the Elan multimedia annotator used for labeling is described. The theoretical part highlights some frequently used speech features such as MFCC, PLP and LPC and deals with currently most popular speech segmentation methods. Some classification algorithms are also mentioned. The practical part describes implementation of Bayesian information criterium algorithm in system for automatic speaker segmentation. For classification of speaker change point in speech, were used different speech features. The results of tests were evaluated by the graphic method of receiver operating characteristic (ROC) and his quantitative indices. As the best speech features for this system were provided MFCC and HFCC.

In this reviewwe discuss methodology to ascertain the amount of information in given data sets with respect to determination of model parameters with desired levels of uncertainty.We do this in the context of least squares (ordinary,weighted, iterative reweightedweighted or "generalized", etc.) based inverse problem formulations. The ideas are illustrated with several examples of interest in the biological and environmental sciences.

京都大学 / 0048 / 新制・課程博士 / 博士(経済学) / 甲第18763号 / 経博第514号 / 新制||経||273(附属図書館) / 31714 / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 西山 慶彦, 准教授 奥井 亮, 講師 末石 直也 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DGAM

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