Abstract Machine learning have been widely adopted in a variety of fields including
engineering, science, and medicine revolutionizing how data is collected, used, and stored …

Machine learning has been an emerging scientific field serving the modern multidisciplinary
needs in the Materials Science and Manufacturing sector. The taxonomy and mapping of …

The present investigation employed information mining and knowledge learning processes
to showcase their efficacy in comprehending the viscoelastic properties of nanocomposites …

High-utility pattern mining (HUPM) is an emerging topic in recent years instead of
association-rule mining to discover more interesting and useful information for decision …

This paper presents a semantic Resistance Spot Welding (RSW) weldability prediction
framework. The framework constructs a shareable weldability knowledge database based …

Bone defect is a highly prevalent disorder. Given that many people, especially the elderly
are suffering from it, there's an urgent need for the development of bone tissue regeneration …

Nowadays, polymer reaction engineers seek robust and effective tools to synthesize
complex macromolecules with well-defined and desirable microstructural and architectural …

Materials processing is challenging because the final structure and properties often depend
on the process conditions as well as the composition. Past research reported in the archival …

To find ternary Cu-based catalysts (Cu/Cu 2 O/CuO) compositions with the highest M2
selectivity (S M2) in Rochow-Müller reaction, a machine learning (ML) framework including …

Active flow control of surface dielectric barrier discharge (SDBD) plasma is a technology that
converts electrical energy into kinetic energy to achieve flow control. Its main application …