This paper studies and predicts the number growth of China＇s mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolut...This paper studies and predicts the number growth of China＇s mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well.展开更多
The energy expression is presented for a failure mechanism, and it is appliedin an Accelerated Life Test (ALT) and an Accelerated Reliability Growth Test (ARGT). The conditionsof the common failure mechanism are obtai...The energy expression is presented for a failure mechanism, and it is appliedin an Accelerated Life Test (ALT) and an Accelerated Reliability Growth Test (ARGT). The conditionsof the common failure mechanism are obtained. The essential relationship between the conditions andthe Accelerated Factor (A_f) is proposed by using the energy model.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.70871082)the Shanghai Leading Academic Discipline Project,China(Grant No.S30504)
文摘This paper studies and predicts the number growth of China＇s mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well.
基金supported by Aeronautical Science Foundation(Grant No.00B53010)Astronautical Base Science Foundation(Grant No.2003CH0502)Natural Science Foundation of Shaanxi Province(Grant No.2003CS0501).
文摘The energy expression is presented for a failure mechanism, and it is appliedin an Accelerated Life Test (ALT) and an Accelerated Reliability Growth Test (ARGT). The conditionsof the common failure mechanism are obtained. The essential relationship between the conditions andthe Accelerated Factor (A_f) is proposed by using the energy model.
