5 resultados para Programmable logic

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

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This paper presents the new active absorption wave basin, named Hydrodynamic Calibrator (HC), constructed at the University of São Paulo (USP), in the Laboratory facilities of the Numerical Offshore Tank (TPN). The square (14 m 14 m) tank is able to generate and absorb waves from 0.5 Hz to 2.0 Hz, by means of 148 active hinged flap wave makers. An independent mechanical system drives each flap by means of a 1HP servo-motor and a ball-screw based transmission system. A customized ultrasonic wave probe is installed in each flap, and is responsible for measuring wave elevation in the flap. A complex automation architecture was implemented, with three Programmable Logic Computers (PLCs), and a low-level software is responsible for all the interlocks and maintenance functions of the tank. Furthermore, all the control algorithms for the generation and absorption are implemented using higher level software (MATLAB /Simulink block diagrams). These algorithms calculate the motions of the wave makers both to generate and absorb the required wave field by taking into account the layout of the flaps and the limits of wave generation. The experimental transfer function that relates the flap amplitude to the wave elevation amplitude is used for the calculation of the motion of each flap. This paper describes the main features of the tank, followed by a detailed presentation of the whole automation system. It includes the measuring devices, signal conditioning, PLC and network architecture, real-time and synchronizing software and motor control loop. Finally, a validation of the whole automation system is presented, by means of the experimental analysis of the transfer function of the waves generated and the calculation of all the delays introduced by the automation system.

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The ever-growing production and the problematization of Environmental Health have shown the need to apprehend complex realities and deal with uncertainties from the most diversified instruments which may even incorporate local aspects and subjectivities by means of qualitative realities, while broadening the capacity of the information system. This paper presents a view on the reflection upon some challenges and possible convergences between the ecosystemic approach and the Fuzzy logic in the process of dealing with scientific information and decision-making in Environmental Health.

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OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

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Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We propose algorithms for link prediction that use a probabilistic ontology to enhance the analysis of the domain and the unavoidable uncertainty in the task (the ontology is specified in the probabilistic description logic crALC). The scalability of the approach is investigated, through a combination of semantic assumptions and graph-based features. We evaluate empirically our proposal, and compare it with standard solutions in the literature.