Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" by Yingqi Li (9151304)

“…To perform accurate control for soft continuum robots, a reinforcement-learning (RL)-based framework is proposed, which integrates conventional piecewise curvature constant (PCC) model and adaptive learning strategies. The algorithm of deep deterministic policy gradient (DDPG) along with domain randomization and offline retraining facilitates fast initialization and stable path following, even under varying tip load, demonstrating its advantages over Jacobian model-based and supervised-learning-based control methods. …”

Data Sheet 1_Evaluating the effectiveness of AI-enhanced “One Body, Two Wings” pharmacovigilance models in China: a nationwide survey on medication safety and risk management.pdf... by Jian Yang (12136)

“…Participants were recruited through stratified convenience sampling to ensure a broad geographical and professional representation. Data were collected through a validated questionnaire and analyzed using ANOVA, regression analysis, decision tree models, and random forest algorithms. …”