Equipamento microprocessado para geração de sinal de correção diferencial, em tempo real, para GPS

This work presents the development of low cost microprocessor-based equipment for generation of differential GPS correction signal, in real time, and configuration and supervision of the GPS base. The developed equipment contains a dedicated microcontroller connected to the GPS receiver, alphanumeric display and multifunction keyboard for configuration and operation of the system and communication interfaces. The electronic circuit has the function of receiving the information from GPS base; interpret them, converting the sentence in the RTCM SC-104 protocol. The microcontroller software makes the conversion of the signal received by the GPS base from the specific format to RTCM SC-104 protocol. The processing main board has two serials RS-232C standard interfaces. One of them is used for configuration and receiving the information generated by the GPS base. The other operates as output, sending the differential correction signal for the transmission system. The development of microprocessor-based equipment showed that it is possible the construction of a low cost private station for real time generation of differential GPS correction signal.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Análise do desempenho muscular do quadríceps e dos isquiotibiais em função da série temporal e da amplitude de movimento de atletas amadoras de futsal feminino = : Analysis of muscle performance of the quadriceps and hamstrings as a function of the times series and range of motion of amateurfemale futsal athletes

Universidade Estadual de Campinas . Faculdade de Educação Física