Validation versus SGA-based studies. by Francesco Di Nardo (734450)

“…Synchronized electrogoniometric and foot-floor-contact signals are also supplied to enable the spatial/temporal analysis of the sEMG signals. The experimental procedure involves subjects walking barefoot on level ground for approximately 5 minutes at their natural speed and pace, following an eight-shaped path featuring linear diagonal segments, curves, accelerations, and decelerations. …”

SNR values for all sEMG signals. by Francesco Di Nardo (734450)

“…Synchronized electrogoniometric and foot-floor-contact signals are also supplied to enable the spatial/temporal analysis of the sEMG signals. The experimental procedure involves subjects walking barefoot on level ground for approximately 5 minutes at their natural speed and pace, following an eight-shaped path featuring linear diagonal segments, curves, accelerations, and decelerations. …”

Enhancing the Robustness of Vehicle Re-Identification in Intelligent Transportation Systems by Mei Qiu (21081170)

Data Sheet 1_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…By applying the XGBoost algorithm and SHAP (SHapley Additive exPlanations), an explainable machine learning framework was established to evaluate the importance of various factors, explore the nonlinear relationships between variables and walking activity, and analyze the interaction effects among these variables.…”

Data Sheet 2_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…By applying the XGBoost algorithm and SHAP (SHapley Additive exPlanations), an explainable machine learning framework was established to evaluate the importance of various factors, explore the nonlinear relationships between variables and walking activity, and analyze the interaction effects among these variables.…”

DataSheet1_Leveraging environmental microbial indicators in wastewater for data-driven disease diagnostics.docx by Gayatri Gogoi (14936889)

“…After data preprocessing, correlation analyses identified 19 relevant environmental parameters. Unsupervised learning algorithms, including K-means and K-medoid clustering, were employed to categorize the data into four distinct clusters, revealing patterns of viral positivity and environmental conditions.…”

AdaptiveDet: Defect Detection for Digital Printing Fabric with Complex Background by Zebin Su (6910031)

“…First, the initial anchor box was generated using the K-means++ algorithm to better adapt to the complex target shape. …”