A new study shows an application of machine-learning directed optimization (ML-DO) that efficiently searches for ...

Traditional 3D printing relies on trial-and-error methods, manual adjustments, and predefined settings. However, ML ...

Researchers develop a novel methodology called Roughness-CANUPO-Dip-Facet (R-C-D-F), which leverages machine learning to perform geological assessments of rock faces. R-C-D-F accurately measures dip ...

Noise and vibration cause mechanical wear, degraded sensor readings, and reduced effectiveness in control algorithms. This ...

The result is a cutting-edge construction material that not only enhances structural ... machine learning model combining the Extra Trees (ET) technique and the Moth-Flame Optimization (MFO ...

Researchers at the University of Toronto's Faculty of Applied Science & Engineering have used ... multi-objective Bayesian optimization machine learning algorithm. This algorithm learned from ...

Machine learning (ML) algorithms are constantly finding new applications in all scientific fields, and geological engineering is no exception. Over the last decade, researchers have developed various ...

In the quest for stronger, more resilient buildings and infrastructure, engineers are turning to innovative solutions, such as concrete-filled steel tube columns (CFST) strengthened with carbon ...

AI-driven automation, tighter design-test collaboration, and evolving BiST techniques are redefining DFT strategies.

Researchers developed ProtGPS, an AI tool that predicts protein localization in cells and how mutations affect disease. The ...

Eko Health has been advancing the use of artificial intelligence to help providers detect the early signs of disease, ...