Unlocking subsurface geoenergy and storage potential using machine learning

FAYETTEVILLE, GA, UNITED STATES, March 20, 2026 /EINPresswire.com/ -- Using machine learning regression models, we ...
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 ...
IEEE

Comparison of Spelling Error Detection in Turkish Texts With Machine Learning and Transformer-Based Approaches

Abstract: This study aims to compare the performance of five different models for spelling error detection, a crucial task in natural language processing. In this ...
Frontiers

Traditional machine learning in biomedical image analysis: before you go too deep

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
IEEE

Physical-Optics-Inspired Machine Learning Scheme for Analysis of Electrically Large Radome

Abstract: Analysis of radome effects on the antenna scanning performance constitutes a critical aspect in radar line-of-sight calibration and boresight error (BSE ...
The New York Times

Times Analysis Finds Errors in Trump’s Supreme Court Filing That Calls for National Guard in Chicago

The Trump administration has claimed the police were slow to protect federal agents on Oct. 4, but videos and audio show that their rationale conflates hours of events involving a shooting, a protest, ...
electronics360.globalspec

AI-assisted debugging: How machine learning is revolutionizing signal analysis

Traditional signal processing techniques have achieved much, but they face notable limitations when confronted with complex, high-volume data. Classical methods often rely on manual feature extraction ...
C&EN

Global Meta-Analysis Integrated with Machine Learning Assesses Context-Dependent Microplastic Effects on Soil Microbial Biomass Carbon and Nitrogen

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Here, we integrated quantitative meta-analysis with ML ...
chromatographyonline

Machine Learning for Oligonucleotide Analysis in Practice

Torgny Fornstedt describes how machine learning can work in practice for oligonucleotide analysis. Recent advances in machine learning have significantly improved the ability to evaluate data quality ...