Jian Sun

Kui Wang, Jian Sun, Chenye Wu et al.

Conductor galloping is the high-amplitude, low-frequency oscillation of overhead power lines due to wind. Such movements may lead to severe damages to transmission lines, and hence pose significant risks to the power system operation. In this paper, we target to design a prediction framework for conductor galloping. The difficulty comes from imbalanced dataset as galloping happens rarely. By examining the impacts of data balance and data volume on the prediction performance, we propose to employ proper sample adjustment methods to achieve better performance. Numerical study suggests that using only three features, together with over sampling, the SVM based prediction framework achieves an F_1-score of 98.9%.

Jian Sun, Xiaofeng Zhong, Xuan Zhou et al.

Popular videos are often clicked by a mount of users in a short period. With content recommendation, the popular contents could be broadcast to the potential users in wireless network, to save huge transmitting resource. In this paper, the contents propagation model is analyzed due to users' historical behavior, location, and the converging properties in wireless data transmission, with the users' communication log in the Chinese commercial cellular network. And a recommendation scheme is proposed to achieve high energy efficiency.