Interpretação de dados de GPR com base na hierarquização de superfícies limitantes e na adaptação de critérios sismoestratigráficos

Due to its high resolution, Ground Penetrating Radar (GPR) has been used to image subsurface sedimentary deposits. Because GPR and Seismic methods share some principles of image construction, the classic seismostratigraphic interpretation method has been also applied as an attempt to interpret GPR data. Nonetheless some advances in few particular contexts, the adaptations from seismic to GPR of seismostratigraphic tools and concepts unsuitable because the meaning given to the termination criteria in seismic stratigraphy do not represent the adequate geologic record in the GPR scale. Essentially, the open question relies in proposing a interpretation method for GPR data which allow not only relating product and sedimentary process in the GPR scale but also identifying or proposing depositional environments and correlating these results with the well known Sequence Stratigraphy cornerstones. The goal of this dissertation is to propose an interpretation methodology of GPR data able to perform this task at least for siliciclastic deposits. In order to do so, the proposed GPR interpretation method is based both on seismostratigraphic concepts and on the bounding surface hierarchy tool from Miall (1988). As consequence of this joint use, the results of GPR interpretation can be associated to the sedimentary facies in a genetic context, so that it is possible to: (i) individualize radar facies and correlate them to the sedimentary facies by using depositional models; (ii) characterize a given depositional system, and (iii) determine its stratigraphic framework highligthing how it evolved through geologic time. To illustrate its use the proposed methodology was applied in a GPR data set from Galos area which is part of the Galinhos spit, located in Rio Grande do Norte state, Northeastern Brazil. This spit presents high lateral sedimentary facies variation, containing in its sedimentary record from 4th to 6th cicles caused by high frequency sea level oscillation. The interpretation process was done throughout the following phases: (i) identification of a vertical facies succession, (ii) characterization of radar facies and its associated sedimentary products, (iii) recognition of the associated sedimentary process in a genetic context, and finally (iv) proposal of an evolutionay model for the Galinhos spit. This model proposes that the Galinhos spit is a barrier island constituted, from base to top, of the following sedimentary facies: tidal channel facies, tidal flat facies, shore facies, and aeolic facies (dunes). The tidal channel facies, in the base, is constituted of lateral accretion bars and filling deposits of the channels. The base facies is laterally truncated by the tidal flat facies. In the foreshore zone, the tidal flat facies is covered by the shore facies which is the register of a sea transgression. Finally, on the top of the stratigraphic column, aeolic dunes are deposited due to areal exposition caused by a sea regression

Medidas de associação em estudo transversal com delineamento complexo: razão de chances e razão de prevalência

O objetivo deste estudo foi apresentar e discutir a utilização das medidas de associação: razão de chances e razão de prevalências, em dados obtidos de estudo transversal realizado em 2001-2002, utilizando-se amostra estratificada por conglomerados em dois estágios (n=1.958). As razões de chances e razões de prevalências foram estimadas por meio de regressão logística não condicional e regressão de Poisson, respectivamente, utilizando-se o pacote estatístico Stata 7.0. Intervalos de confiança e efeitos do desenho foram considerados na avaliação da precisão das estimativas. Dois desfechos do estudo transversal com diferentes níveis de prevalência foram avaliados: vacinação contra influenza (66,1%) e doença pulmonar referida (6,9%). Na situação em que a prevalência foi alta, as estimativas das razões de prevalência foram mais conservadoras com intervalos de confiança menores. Na avaliação do desfecho de baixa prevalência, não se observaram grandes diferenças numéricas entre as estimações das razões de chances e razões de prevalência e erros-padrão obtidos por uma ou outra técnica. O efeito do desenho maior que a unidade indicou que a amostragem complexa, em ambos os casos, aumentou da variância das estimativas. Cabe ao pesquisador a escolha da técnica e do estimador mais adequado ao seu objeto de estudo, permanecendo a escolha no âmbito epidemiológico.

Modeling grouped survival data with time-dependent covariates

In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.

A Generalized Log-Normal Model for Grouped Survival Data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Search for associated production of charginos and neutralinos in the trilepton final state using 2.3 fb(-1) of data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Growth of the tambaqui Colossoma macropomum (Cuvier) (Characiformes: Characidae): which is the best model?

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

High precision GPS network with precise ephemerides and earth body tide model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Efeito da Idade da Vaca ao Parto e da Data Juliana de Nascimento sobre Características Pré-desmama de Bezerros da Raça Gir

Objetivou-se com este trabalho estimar a influência da idade da vaca ao parto (IDV) e da data juliana de nascimento (DJN) sobre o peso à desmama (PD) e a média do ganho diário no período pré-desmama (GMD) de bezerros Gir, determinando fatores de correção para estes efeitos. Foram analisados 10.685 e 18.339 dados de PD e GMD de bezerros Gir, provenientes do Arquivo da Associação Brasileira dos Criadores de Zebu (ABCZ), pertencentes a 1229 e 1979 grupos contemporâneos (GC), respectivamente. PD e GMD foram pré-ajustados para o efeito da idade do bezerro à desmama. O efeito de IDV sobre PD e GMD foi modelado como polinômio segmentado quadrático-quadrático-quadrático, com nós, ou pontos de junção aos 4,1; 12,7 e 4,0; 8,2 anos, respectivamente, para machos e como polinômio segmentado quadrático-quadrático, com nó, ou ponto de junção aos 3,8 anos, para fêmeas sobre as duas características. A DJN foi modelada como um polinômio segmentado quadrático-quadrático com nó aos 126 dias para PD e 167 dias para GMD. Os resultados mostraram que a determinação dos fatores de correção para IDV deve ser feita, separadamente, para machos e fêmeas e, para DJN, deve-se considerar cada estação do ano, para que as diferenças entre elas sejam bem observadas. Os fatores de correção para o efeito da idade da vaca variaram de 0,94750 a 1,08033 sobre PD e 0,91714 a 1,07689 sobre GMD, para machos, e de 0,90937 a 1,07415 sobre PD e 0,96055 a 1,14007 sobre GMD, para fêmeas. Para o efeito de DJN, a amplitude foi de 0,9256 a 1,0340 sobre PD e 0,9112 a 1,0551 sobre GMD.

Analysis of beef cattle longitudinal data applying a nonlinear model

The objective of this work was to evaluate the Nelore beef cattle, growth curve parameters using the Von Bertalanffy function in a nested Bayesian procedure that allowed estimation of the joint posterior distribution of growth curve parameters, their (co)variance components, and the environmental and additive genetic components affecting them. A hierarchical model was applied; each individual had a growth trajectory described by the nonlinear function, and each parameter of this function was considered to be affected by genetic and environmental effects that were described by an animal model. Random samples of the posterior distributions were drawn using Gibbs sampling and Metropolis-Hastings algorithms. The data set consisted of a total of 145,961 BW recorded from 15,386 animals. Even though the curve parameters were estimated for animals with few records, given that the information from related animals and the structure of systematic effects were considered in the curve fitting, all mature BW predicted were suitable. A large additive genetic variance for mature BW was observed. The parameter a of growth curves, which represents asymptotic adult BW, could be used as a selection criterion to control increases in adult BW when selecting for growth rate. The effect of maternal environment on growth was carried through to maturity and should be considered when evaluating adult BW. Other growth curve parameters showed small additive genetic and maternal effects. Mature BW and parameter k, related to the slope of the curve, presented a large, positive genetic correlation. The results indicated that selection for growth rate would increase adult BW without substantially changing the shape of the growth curve. Selection to change the slope of the growth curve without modifying adult BW would be inefficient because their genetic correlation is large. However, adult BW could be considered in a selection index with its corresponding economic weight to improve the overall efficiency of beef cattle production.

Conceptual model for adaptable and extensible visual data exploration

Interactive visual representations complement traditional statistical and machine learning techniques for data analysis, allowing users to play a more active role in a knowledge discovery process and making the whole process more understandable. Though visual representations are applicable to several stages of the knowledge discovery process, a common use of visualization is in the initial stages to explore and organize a sometimes unknown and complex data set. In this context, the integrated and coordinated - that is, user actions should be capable of affecting multiple visualizations when desired - use of multiple graphical representations allows data to be observed from several perspectives and offers richer information than isolated representations. In this paper we propose an underlying model for an extensible and adaptable environment that allows independently developed visualization components to be gradually integrated into a user configured knowledge discovery application. Because a major requirement when using multiple visual techniques is the ability to link amongst them, so that user actions executed on a representation propagate to others if desired, the model also allows runtime configuration of coordinated user actions over different visual representations. We illustrate how this environment is being used to assist data exploration and organization in a climate classification problem.

The Brazilian Seismographic Integrated Systems (BRASIS): Infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of São Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation. © 2011 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data

This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

A useful empirical bayesian method to analyse industrial data from saturated factorial designs

The use of saturated two-level designs is very popular, especially in industrial applications where the cost of experiments is too high. Standard classical approaches are not appropriate to analyze data from saturated designs, since we could only get the estimates of the main factor effects and we would not have degrees of freedom to estimate the variance of the error. In this paper, we propose the use of empirical Bayesian procedures to get inferences for data obtained from saturated designs. The proposed methodology is illustrated assuming a simulated data set. © 2013 Growing Science Ltd. All rights reserved.

Comunidades de peixes e integridade biótica do Córrego da Água Limpa na fase de pré-recuperação de matas ciliares

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