Machine learning (ML) is reshaping pipeline integrity management (PIM) from physics-based to data-driven paradigms. This ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy of Sciences (CAS), has developed an innovative machine learning framework ...
More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...
A research group has developed SPACIER, an advanced polymer material design tool that integrates machine learning with molecular simulations. As a proof of concept, the group successfully synthesized ...
Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
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