This work concerns a particular application of the OptimalControl Theory to a model related to HIV infection dynamics. The mathematical model adopted in this work was proposed by Nowak et al., 1996 and describes the dynamics of viral concentration in t e m of interaction with CD4 cells and the cytotoxic T lymphocytes, which are responsible for the immune defense of the organism The control variable is the drug dose, which, in tum, affects the rate of infection of CD4 cells by HIV virus. The cost function to be minimized is a weighted sum of the jinal viral load and the accumulated side effects. Simulation results show that the optimal control scheme can achieve improved quality ofthe treatment in rems of reduction in the viral load and quantity of administered drugs, but has the inconvenience related to the necessity of frequent and periodic laboratory analysis to provide feedback information to adjust the doses.
This paper presents the development of an Artificial Neural Network system for Dynamometer Card pattern recognition in oil well rod pump systems. It covers the establishment of pattern classes and a set of standards for training and validation, the study of descriptors which allow the design and the implementation of features extractor, training, analysis and finally the validation and performance test with a real data base.
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