SinoXivBased on the recycling technology of waste concrete, the preparation of regenerated aggregate and regenerated fine powder, and the use of them to replace quartz sand and cement, and the preparation of...
This study presents a forecasting and comparative analysis of moderate geomagnetic storms using artificial neural networks (ANNs). Four moderate geomagnetic storm events that occurred during 2022, in ...
Clustering is widely used to discover interpretable structure in data, but conventional unsupervised methods group examples by \emph{feature similarity} alone, ignoring any available prediction tar...
Background Meningitis remains a critical public health threat in the "Meningitis Belt" of sub-Saharan Africa, necessitating high-resolution predictive tools for targeted intervention. This study model...
Federated learning has emerged as the dominant paradigm for privacy-preserving intrusion detection across distributed networks, yet its vulnerability to adversarial manipulation of the training proces...
Adverse pregnancy outcomes (APOs), including preeclampsia, preterm birth, and maternal heart failure, pose substantial risks for women with pre-existing heart disease. Soluble ST2 (sST2), a biomarker ...
Timely and accurate electricity price forecasting is essential for the efficient operation of competitive electricity markets. However, predicting day-ahead electricity prices remains challenging due ...
Groundwater regimes are key determinants influencing the outcome of peatland ecosystem restoration programmes. Despite widespread application, impacts of ditch blocking on water table levels (WTLs) re...
Modeling air quality concentration plays a crucial role in predicting and mitigating airborne pollutant levels. This study collected and organized daily average air quality data and meteorological dat...
A fully reproducible expected-goals (xG) modelling pipeline is presented as an interpretable machine learning approach using open football event data from StatsBomb for La Liga 2015/2016 and the 2018 ...
