Scientific Research Publishing

Proposal for a Machine Learning Model to Improve Hauling Productivity in an Open-Pit Mine ()

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...
Scientific Research Publishing

A Multimodal Machine-Learning Framework for Predicting Lithium-Associated Renal Dysfunction from Synthetic Biomarker Trajectories ()

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant risk of progressive renal impairment in a subset of patients. Early ...
Devdiscourse

How machine learning and IoT are building factories of future

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...
IEEE

Introducing Ensemble Machine Learning Algorithms for Automatic Test Case Generation using Learning Based Testing

Abstract: Context: Ensemble methods are powerful machine learning algorithms that combine multiple models to enhance prediction capabilities and reduce generalization errors. However, their potential ...
Devdiscourse

Stacked AI model improves credit default forecasting

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...
IEEE

Predicting Employee Attrition Using Machine Learning Approaches

Abstract: Employee attrition is a costly problem for organizations, leading to loss of institutional knowledge, reduced productivity, and increased recruitment expenses. Machine learning offers a ...
EurekAlert!

Precision soil salinity mapping powered by UAV intelligence

Accurate assessment of soil salinity is critical for sustainable agriculture and food security, yet remains technically challenging at fine spatial scales.
Frontiers

fNIRS-based early identification of mild cognitive impairment: a large-scale multi-paradigm study with ensemble machine learning models

Early and accurate identification of mild cognitive impairment (MCI) is crucial for timely intervention and preventing further cognitive decline. Functional near-infrared spectroscopy (fNIRS) is a non ...