A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.

A review of the classification of rabies virus lineages maintained by insectivorous bats in Brazil

Trabalho apresentado à 23ª Revista de Educação Continuada em Medicina Veterinária e Zootecnia, 2012, São Paulo

Supervised classification of basaltic aggregate particles based on texture properties

The strength and durability of materials produced from aggregates (e.g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials.

O uso da Classificação Internacional de Funcionalidade, Incapacidade e Saúde para acompanhamento de pacientes usuários de Implante Coclear.

Purpose: To characterize the profile of patients with cochlear implant as proposed by the International Classification of Functioning, Disability and Health for Children and Youth (ICF-CY). Methods: This is a descriptive, crosssectional retrospective study, which examined 30 medical records of patients using the cochlear implant of Centro de Pesquisas Audiológicas. To characterize the profile of the patients, the ICF-CY was used. Regarding the assessment, researchers relied on procedures performed in clinical routine, besides information registered in the medical record. After reviewing the information, it was related to codes from the ICF-CY; with the addition of a qualifier afterwards. Results: Overall, 55 codes from the ICF were related to the instruments to characterize this population. Regarding the Body Functions field, most participants did not have disabilities related to reception and expression of oral language and auditory functions, with only written language disabilities being found. These same findings were observed in the Activity and Participation Field. Regarding environmental factors, noise and the non-availability of technology resources to assist in the auditory comprehension of noise were characterized as a barrier, as well as the absence of speech therapy. Conclusion: This study concluded that most of the participating children showed no deficiency in the body functions, with difficulties being only reported in relation to school performance. Environmental factors (noise, non-availability of technological resources, absence of speech therapy) were characterized as a barrier. The need to expand assessments in the clinical routine was also noted.