Biblio

Filters: Author is Geng, J.  [Clear All Filters]
2020-12-11
Geng, J., Yu, B., Shen, C., Zhang, H., Liu, Z., Wan, P., Chen, Z..  2019.  Modeling Digital Low-Dropout Regulator with a Multiple Sampling Frequency Circuit Technology. 2019 IEEE 13th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :207—210.

The digital low dropout regulators are widely used because it can operate at low supply voltage. In the digital low drop-out regulators, the high sampling frequency circuit has a short setup time, but it will produce overshoot, and then the output can be stabilized; although the low sampling frequency circuit output can be directly stabilized, the setup time is too long. This paper proposes a two sampling frequency circuit model, which aims to include the high and low sampling frequencies in the same circuit. By controlling the sampling frequency of the circuit under different conditions, this allows the circuit to combine the advantages of the circuit operating at different sampling frequencies. This shortens the circuit setup time and the stabilization time at the same time.

2017-02-27
Geng, J., Ye, D., Luo, P..  2015.  Forecasting severity of software vulnerability using grey model GM(1,1). 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). :344–348.

Vulnerabilities usually represents the risk level of software, and it is of high value to forecast vulnerabilities so as to evaluate the security level of software. Current researches mainly focus on predicting the number of vulnerabilities or the occurrence time of vulnerabilities, however, to our best knowledge, there are no other researches focusing on the prediction of vulnerabilities' severity, which we think is an important aspect reflecting vulnerabilities and software security. To compensate for this deficiency, we borrows the grey model GM(1,1) from grey system theory to forecast the severity of vulnerabilities. The experiment is carried on the real data collected from CVE and proves the feasibility of our predicting method.