ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

To overcome the limitations of traditional roller-compacted concrete (RCC) compaction monitoring—which relies on macroscopic experiments, overlooks microscopic mechanisms, and lacks model ...

Implement a CPU Scheduling Algorithms Simulator using Streamlit to visualize and compare different CPU scheduling strategies interactively. This feature will allow users to simulate various scheduling ...

The consortium running the European Space Agency's (ESA) Euclid mission has published the most extensive simulation of the cosmos to date. The modeling was based on algorithms developed by UZH ...

Underwater waste detection with YOLOv8 Underwater image enhancement using Dark Channel Prior Water quality classification with XGBoost Aquatic habitat assessment ...

NVIDIA has unveiled a major milestone in scalable machine learning: XGBoost 3.0, now able to train gradient-boosted decision tree (GBDT) models from gigabytes up to 1 terabyte (TB) on a single GH200 ...

Purpose: To develop effective machine learning models that analyze pattern visual evoked potentials (PVEPs) to predict the stabilized visual acuity (VA) of patients with treated ocular trauma. Methods ...

Abstract: Water leakage in distribution networks poses significant challenges, including resource wastage and increased operational costs. This paper presents the ANN-XGBoost algorithm, an innovative ...

Classification of gas wells is an important part of optimizing development strategies and increasing the recovery. The original classification standard of gas wells in the Sulige gas field has weak ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...