Possible New Syndrome: Left Ventricular Noncompaction, Partial Agenesis of the Corpus Callosum, and Developmental Delay in a Brazilian Child

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Knowledge of general dentists in the current guidelines for emergency treatment of avulsed teeth and dental trauma prevention

A high prevalence of dental trauma exists and its effects on function and esthetics deserve the attention of general dentists. The aim of this study was to assess the level of general dental practitioners' (GDPs) knowledge about guidelines for dental avulsion and its prevention using a questionnaire. The 21-item questionnaire was distributed among 264 GDPs and the survey was realized between August-November 2006. The data obtained were statistically analyzed using descriptive analysis and Pearson's Chi-square test to determine associations between knowledge regarding emergency treatment and dentists from public or private dental schools and years of experience. The results showed that the participants exhibited appropriate knowledge concerning procedures in cases of tooth avulsion and its prevention. The number of correct answers was low in relation to recommended treatment at the site of injury. Storage medium, preparation of the alveolus and splint time for receiving the avulsed tooth received a high number of correct answers. One statistically significant association between years of experience and recommended treatment at the site of the injury in the case an avulsed tooth (KH2 = 9.384, P = 0.009). In conclusion, this survey showed appropriate knowledge of dental avulsion management and its prevention among the surveyed dentists. The findings also showed that communication between dentists and the population is deficient, especially concerning practitioners of high risk and contact sports.

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

Dysarthria and quality of life in neurologically healthy elderly and patients with Parkinson's disease

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)