A percepção dos docentes da UFRN sobre o programa de apoio a planos de reestruturação e ampliação das universidades federais - REUNI

In recent decades higher education in Brazil has gone through several changes. The Programa de Reestruturação e Expansão das Universidades Federais REUNI has been the greatest overhaul performed by the government in public universities in the last years. REUNI is presented as the biggest reform in tertiary education in contemporary times, having as the main goal a gradual increase in the average rate of conclusion in live learning graduation courses up to 90%, as well as a rate expansion of graduating students in face to face classes per professor. This research aims at studying the perception of professors from UFRN concerning the REUNI program in execution from 2008 until 2012. The study seeks to understand how professors evaluate the program and what the dimensions that most influence in this evaluation are. The study made use of a research tool (survey) which was sent through the internal system of the university, SIGAdmin, to all professors of superior teaching from UFRN. The answers generated by the survey were processed using SPSS statistical software (Statistical Package for Social Science). Factorial Analysis and Multiple Linear Regression were used as an analysis technique. 180 answers were obtained, reaching all UFRN Centers and some academic units, as well as some campuses in the countryside of the state. Through the research was possible to analyze how professors from UFRN perceive the REUNI program implemented in the institution. The results point to the program approval by the professors. Statistical tests showed that the average values obtained in the Centers and academic units are basically the same. It was demonstrated that the extent that most influenced in the answers is linked to practical outcomes of the program, whereas the knowledge of REUNI goals was the least that impacted on the marks given to the program. Another dimension which influenced the perception of professors relates to the influence of REUNI in their activities. It was observed that professors from UFRN don t see REUNI as an impediment to them

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.