We report the results of a study with Ti-doped AlN and GaN in the cubic-zincblende phase of the Al0.9375Ti0.0625N and Ga0.9375Ti0.0625N concentrations. All calculations were carried out using the Quantum ESPRESSO code through the pseudopotential method within the framework of density functional theory. The structural results show that the lattice constants of the Al0.9375Ti0.0625N and Ga0.9375Ti0.0625N compounds do not change compared to pure forms of c-AlN and c-GaN, yet the bond length of Ti-N increases compared to the bond length of Ga-N in pure c-AlN and c-GN. The electronic analyses reveal that both the Al0.9375Ti0.0625N and Ga0.9375Ti0.0625N compounds are ferromagnetic. The Al0.9375Ti0.0625N compound exhibits a metallic behavior with a total magnetic moment of 0.85 μ
β
/cell, whereas Ga0.9375Ti0.0625N exhibits a halfmetallic character with a magnetic moment of 1.0 μ
β
/cell. The magnetic effect in the Al0.9375Ti0.0625N and Ga0.9375Ti0.0625N compounds is the result of a strong hybridization between Ti-3d and N-2p. It is concluded that the Ga0.9375Ti0.0625N compound is a suitable candidate for a diluted magnetic semiconductor with potential use in applications such as spintronics, spin injection or magnetic memories.
The goal of failures forecasting is to predict faults in the network, doing that it is possible to guarantee reliability and quality of service in real time to maintain the network availability and reliability and to initiate appropriate actions of restoration of "normality". The following article describes the process performed for implementing failures prediction system in LAN using artificial neural networks multilayer Perceptron. It describes the system, the tests made for the selection of the own parameters of the neural network like the training algorithm and the obtained results.
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