Rate of change in salivary amylase pre- and post-VR operation. by Akihiro Kakimoto (343218)

Multiple-choice questions and performance pre- and post-VR operation. by Akihiro Kakimoto (343218)

Average scores of TDMS-ST pre- and post-VR operation. by Akihiro Kakimoto (343218)

Average scores of POMS2 pre- and post-VR operation. by Akihiro Kakimoto (343218)

Increase in multiple-choice question scores pre- and post-VR operation. by Akihiro Kakimoto (343218)

Accuracy and loss of LSTM model training and testing. by Leijie Wang (21485157)

Subjects:

Search strategy defined by population, concept, context framework, with Boolean operators. by Emily M. Jones (21989800)

Flow of operation of improved KMA. by Li Yuan (102305)

Retention and extinction of operant learning. by Ella R. Dockendorf (21533334)

Retention (memory) of operant conditioning. by Ella R. Dockendorf (21533334)

Effects of injury on operant conditioning and memory. by Ella R. Dockendorf (21533334)

Prediction (a-d) and infusion deviation (e-f) results under different training sets and test sets. by Leijie Wang (21485157)

Subjects:

AdaBoost training flowchart. by Yang Guo (399435)

“…HINGO enhances the uniformity of the initial population distribution by means of refraction opposition-based learning strategy in initialization, and improves the local and global search ability of the algorithm by means of sine and cosine strategy, Lévy flight and nonlinear decreasing factor in the search stage. The HINGO-LSSVM-IAdaBoost model is trained and validated on the typical air conditioning fault samples of ASHRAE RP-1043. …”

The parameters of the training phase. by Zhongjian Xie (4633099)

Hyperparameter Configurations in PPO Training. by Honglei Pang (22693724)

“…<div><p>Vehicle lateral stability control under hazardous operating conditions represents a pivotal challenge in intelligent driving active safety. …”

AI KRegression by CHIN-CHENG CHU (20718575)

Example of short escape latency during training, i.e., animals that did escape well within 180 sec trial duration. by Ella R. Dockendorf (21533334)

Training -validation accuracy & lost for ANN. by Gaurav Sandeep Dave (21519884)

“…Additionally, it decreases model training time by 180 seconds, facilitating predictive maintenance of critical performance metrics and minimizing downtime. …”

VR training system for radiopharmaceutical administration. by Akihiro Kakimoto (343218)

Training loss variation of GNN-FTuckER on the TeaPle dataset. by Jun Li (6494)