Dispersed hydroxyapatite bioglass 45S5 composites: Comparative evaluation of the use of bovine bone and synthetic hydroxyapatite

The bovine bone and sintetic hydroxyapatite (HA) bioceramics are reference materials to employment as a bone substitute, however, their slow rate of degradation and its low rate of bioactivity index (Ib) are presented as limiting factors for application as bone graft. In contrast, the bioglass is a resorbable and osteoinductive material. the present work objective the development of composites of dispersed bovine bone or sintetic HA in silicate-phosphate bioglass, seeking to obtain a biomaterial with properties suitable for application as bone grafts. The composites were prepared by mixing between the powder components followed by sintering for 1h. Were used HA and bioglass (45S5) with particle size <240μm. The tested proportions of HA/45S5 were 20/80, 30/70 and 40/60 (wt%). The composites characterization was made employing scanning electron microscopy, Infra-Red Spectrometry and hydrolytic resistance test. The test results indicate the potential use of the materials developed for applications such as bone graft. © (2012) Trans Tech Publications, Switzerland.

A comparative study of the corrosion resistance of incoloy MA 956 and PM 2000 superalloys

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

Multi-shot person re-identification via relational stein divergence

Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

Gaussian mixture modeling with Gaussian process latent variable models

Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristics of the data. Recently, the Gaussian Process Latent Variable Model (GPLVM) has successfully been used to find low dimensional manifolds in a variety of complex data. The GPLVM consists of a set of points in a low dimensional latent space, and a stochastic map to the observed space. We show how it can be interpreted as a density model in the observed space. However, the GPLVM is not trained as a density model and therefore yields bad density estimates. We propose a new training strategy and obtain improved generalisation performance and better density estimates in comparative evaluations on several benchmark data sets. © 2010 Springer-Verlag.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Vantagens e limitações das imagens de alta resolução como suporte ao planejamento urbano: o exemplo de Sobradinho - Distrito Federal

Pós-graduação em Geografia - IGCE

Representações do absurdo e da loucura em Marat/Sade, de Peter Weiss

The present text aims to evaluate some effects of the use of elements in the representation of the madness and of the absurdity in the play Marat/Sade, written by the German author Peter Weiss. To accomplish this task, the analysis is built on comparative evaluations between text elements of the absurdity and of the surrealism, pursuing its textual construction.