Aplicación de técnicas estadísticas en el estudio de fenómenos ambientales y ecosistémicos

208 p.

Um estudo da abundância de lítio, rotação, atividade cromosférica e magnetismo das estrelas análogas e gêmeas solares

The study physical process that control the stellar evolution is strength influenced by several stellar parameters, like as rotational velocity, convective envelope mass deepening, and magnetic field intensity. In this study we analyzed the interconnection of some stellar parameters, as Lithium abundance A(Li), chromospheric activity and magnetic field intensity as well as the variation of these parameters as a function of age, rotational velocity, and the convective envelope mass deepening for a selected sample of solar analogs and twins stars. In particular, we analyzed the convective envelope mass deepening and the dispersion of lithium abundance for these stars. We also studied the evolution of rotation in subgiants stars, because its belong to the following evolutionary stage of solar analogs, and twins stars. For this analyze, we compute evolutionary models with the TGEC code to derive the evolutionary stage, as well as the convective envelope mass deepening, and derive more precisely the stellar mass, and age for this 118 stars. Our Investigation shows a considerable dispersion of lithium abundance for the solar analogs stars. We also realize that this dispersion is not by the convective zone deep, in this way we observed which the scattering of A(Li) can not be explained by classical theories of mixing in the convective zone. In conclusion we have that are necessary extra-mixing process to explain this decrease of Lithium abundance in solar analogs and twins stars. We analyzed the subgiant stars because this are the subsequent evolutionary stage after the solar analogs and twins stars. For this analysis, we compute the rotational period for 30 subgiants stars observed by Co- RoT satellite. For this task we apply two different methods: Lomb-Scargle algorithm, and the Plavchan Periodogram. We apply the TGEC code we compute models with internal distribution of angular momentum to confront the predict results with the models, and the observational results. With this analyze, we showed which solid body rotation models are incompatible with the physical interpretation of observational results. As a result of our study we still concluded that the magnetic field, convective envelope mass deepening, and internal redistribution of angular momentum are essential to explain the evolution of low-mass stars, and its observational characteristics. Based on population synthesis simulation, we concluded that the solar neighborhood presents a considerable quantity of solar twins when compared with the discovered set nowadays. Altogether we foresee the existence around 400 solar analogs in the solar neighborhood (distance of 100 pc). We also study the angular momentum of solar analogs and twins, in this study we concluded that added angular momentum from a Jupiter type planet, putted in the Jupiter position, is not enough to explain the angular momentum predicted by Kraft law (Kraft 1970)

Métodos estatísticos recursivos aplicados ao problema de estimação de vazão de gás em plantas de Plunger-lift

This work has as main objective to find mathematical models based on linear parametric estimation techniques applied to the problem of calculating the grow of gas in oil wells. In particular we focus on achieving grow models applied to the case of wells that produce by plunger-lift technique on oil rigs, in which case, there are high peaks in the grow values that hinder their direct measurement by instruments. For this, we have developed estimators based on recursive least squares and make an analysis of statistical measures such as autocorrelation, cross-correlation, variogram and the cumulative periodogram, which are calculated recursively as data are obtained in real time from the plant in operation; the values obtained for these measures tell us how accurate the used model is and how it can be changed to better fit the measured values. The models have been tested in a pilot plant which emulates the process gas production in oil wells

Impact of artifact correction methods on R-R interbeat signals to quantifying heart rate variability (HRV) according to linear and nonlinear methods.

In the analysis of heart rate variability (HRV) are used temporal series that contains the distances between successive heartbeats in order to assess autonomic regulation of the cardiovascular system. These series are obtained from the electrocardiogram (ECG) signal analysis, which can be affected by different types of artifacts leading to incorrect interpretations in the analysis of the HRV signals. Classic approach to deal with these artifacts implies the use of correction methods, some of them based on interpolation, substitution or statistical techniques. However, there are few studies that shows the accuracy and performance of these correction methods on real HRV signals. This study aims to determine the performance of some linear and non-linear correction methods on HRV signals with induced artefacts by quantification of its linear and nonlinear HRV parameters. As part of the methodology, ECG signals of rats measured using the technique of telemetry were used to generate real heart rate variability signals without any error. In these series were simulated missing points (beats) in different quantities in order to emulate a real experimental situation as accurately as possible. In order to compare recovering efficiency, deletion (DEL), linear interpolation (LI), cubic spline interpolation (CI), moving average window (MAW) and nonlinear predictive interpolation (NPI) were used as correction methods for the series with induced artifacts. The accuracy of each correction method was known through the results obtained after the measurement of the mean value of the series (AVNN), standard deviation (SDNN), root mean square error of the differences between successive heartbeats (RMSSD), Lomb\'s periodogram (LSP), Detrended Fluctuation Analysis (DFA), multiscale entropy (MSE) and symbolic dynamics (SD) on each HRV signal with and without artifacts. The results show that, at low levels of missing points the performance of all correction techniques are very similar with very close values for each HRV parameter. However, at higher levels of losses only the NPI method allows to obtain HRV parameters with low error values and low quantity of significant differences in comparison to the values calculated for the same signals without the presence of missing points.

Classificador máquina de suporte vetorial com análise de Fourier aplicada em dados de EEG e EMG

The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.

Caracterización de señales sísmicas del Volcán Cotopaxi utilizando estimadores espectrales clásicos y de máxima entropía

Se presenta un estudio de detección y caracterización de eventos sísmicos del tipo volcano tectónicos y largo periodo de registros sísmicos generados por el volcán Cotopaxi. La estructura secuencial de detección propuesta permite en un registro sísmico maximizar la probabilidad de presencia de un evento y minimizar la ausencia de este. La detección se la realiza en el dominio del tiempo en cuasi tiempo real manteniendo una tasa constante de falsa alarma para posteriormente realizar un estudio del contenido espectral de los eventos mediante el uso de estimadores espectrales clásicos como el periodograma y paramétricos como el método de máxima entropía de Burg, logrando así, categorizar a los eventos detectados como volcano tectónicos, largo periodo y otros cuando no poseen características pertenecientes a los otros dos tipos como son los rayos.