Recent Advances in Technologies by Maurizio A Strangio

By Maurizio A Strangio

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03 Probability to failure node3 (old age) 0 20 40 Month used 60 80 0 20 40 Month used 60 80 Fig. 13. CIFs of failure (left), abandonment (middle), and switching (right) event for each terminal node of the multivariate DT. 33) and uses other modern methods of contraception (left panel of Figure 13). This node is also associated with high risk of switching and high risk of abandonment up to about 3 years. This is rational since the younger women are inexperienced users who most probable to fail and also have a strong willingness to be pregnant, so they most probably abandon the contraceptive methods.

Lin, D. Y. (2000) Nonparametric Analysis of Recurrent Events and Death. Biometrics, 56:554-562. Gordon, L. & Olshen, R. (1985). Tree-structured survival analysis. Cancer Treatment Reports, 69:1065–1069. Gray, R. J. (1988). A class of k-sample tests for comparing the cumulative incidence of a competing risk. Annals of Statistics, 16:1141-1154. J. (1992). Flexible method for analyzing survival data using splines, with applications to breast cancer prognosis. Journal of the American Statistical Association.

The effects of stator resistance Rr variations in the calculation of slip frequency and transformation angle is compensated by motion controller. The nonlinearities caused by magnetic saturation can be compensated by the inverse magnetizing characteristic. 3. 1. Adaptive Neural Networks A general architecture graph of Multilayer Perceptron (MLP) is shown in "Figure 4". This network which can be multiplexed for each output of the controller has been found to possess acceptable performance in many industrial applications.

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