This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...
Objective Biologics for systemic lupus erythematosus (SLE) demonstrate variable treatment responses across trials. We evaluated baseline biomarkers as predictors of response to guide personalised ...
Abstract: Optimizing sensor placement is crucial for enhancing the coverage and data-acquisition efficiency of ocean monitoring systems. Traditional approaches primarily rely on univariate ocean data ...
Statistical analysis is essential in research. As modern production processes evolve, the increasing volume of data needing processing has demanded techniques like multivariate analysis for ...
The AERCA algorithm performs robust root cause analysis in multivariate time series data by leveraging Granger causal discovery methods. This implementation in PyTorch facilitates experimentation on ...
Halva—‘grapHical Analysis with Latent VAriables’—is a Python package dedicated to statistical analysis of multivariate ordinal data, designed specifically to handle missing values and latent variables ...
Ultrafine Slag; Foamed Concrete; Sustainability; Artificial Neural Network (ANN); Porosity While these contributions are significant, most of these works focus on either strength or durability but not ...
Laboratoire de Matériaux et Environnement (LAME), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso. In recent decades, the impact of climate change on natural resources has increased. However, ...
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