no code implementations • 12 Dec 2022 • Hui Wang, Jialin Liu, Feng Li, Hao Ji, Bin Jia, Ziyou Gao
Numerical cases of Beijing Metro Line 9 verify the efficiency and effectiveness of our proposed model, and results show that: (1) when occurring a disruption event during peak hours, the impact on the normal timetable is greater, and passengers in the direction with fewer train services are more affected; (2) if passengers stranded at the terminal stations of disruption area are not transported in time, they will rapidly increase at a speed of more than 300 passengers per minute; (3) compared with the fixed shortest path, using the response vehicles reduces the total travel time about 7%.
no code implementations • 3 Apr 2022 • Ji Fang, Vincent CS Lee, Hao Ji, HaiYan Wang
This study aims to fill this gap by developing a machine learning algorithm that dynamically updates auto-suggestion exercise goals using retrospective data and realistic behavior trajectory.
no code implementations • 10 Sep 2019 • Eitan Rothberg, Tingting Chen, Luo Jie, Hao Ji
Today's state-of-the-art image classifiers fail to correctly classify carefully manipulated adversarial images.
no code implementations • 14 Jul 2016 • Bin Liu, Hao Ji, Yi Dai
The proposed method consists of three elemental operators, that are dynamic texture model based motion segmentation, feature extraction and Gaussian process (GP) regression.