The role of technology in optimizing ERP order processing has become increasingly important as businesses strive to improve ...

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...

An autonomous platform uses machine learning and patterned light to detect and terminate cardiac arrhythmias in real time without electrical shocks.

Researchers have developed a new way to recognize human emotions by combining fiber-based physiological signals with thermal ...

Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a ...

Conventional electronic noses rely on arrays of chemical sensors whose electrical responses are often affected by humidity, temperature fluctuations, and long-term drift. While these systems have ...

Engineers leverage both device-specific and tool-level data to identify a process “sweet spot.” Tight, frequent tool-to-tool matching enables greater yield and fab flexibility. Machine learning helps ...

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in complex two-dimensional (2D) data, with potential applications ranging from ...

In 2026, artificial intelligence (AI) systems are deployed at scale to support clinical decision-making. Algorithms detect cardiac arrhythmias from ECGs, classify skin lesions from photographs and ...

Explore advances in protein imaging techniques and spatial proteomics. Learn how modern imaging tools reveal protein dynamics and organization in cells.