Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models like regression, dec ...

Infinite dilution activity coefficient is a key thermodynamic parameter in solvent design for chemical processes. Although conductor-like screening ...

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, ...

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 ...

Reliable and scalable water level prediction is crucial in hydrology for effective water resources management, especially ...

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 ...

Dao is part of a central group that provides data and machine-learning capabilities to the company. He ensures the data team has the right tools to complete their work. He also aims to make it easy ...

Mastercard has developed a transaction-specific AI model to detect fraud, enhance loyalty programmes and deliver personalised ...

The Uncertainty Engine is guiding research in fusion plasma physics. Could similar approaches benefit fission research as well?

Researchers at the Department of Energy's SLAC National Accelerator Laboratory and collaborating institutions recently built a generative AI model that can recreate molecular structures from the ...

Deep-Learning Paradigm Achieves Global Precision in Nuclear Charge Density PredictionsThe charge density distribution of an atomic nucleus is a ...

Google-Tesla MagNet Challenge is an annual competition. It’s designed to accelerate innovation in magnetic modeling using ...