The field of additive manufacturing is undergoing a profound transformation as artificial intelligence (AI) and machine learning (ML) become integral to the ...
Abstract: Concurrency defects such as race conditions, deadlocks, and improper synchronization remain a critical challenge in developing reliable OpenMP-based parallel applications. Traditional static ...
The small and complicated features of TSVs give rise to different defect types. Defects can form during any of the TSV ...
Edge AI addresses high-performance, low-latency requirements by embedding intelligence directly into industrial devices.
The European Space Agency (ESA) is accelerating a quiet revolution on the factory floor: using artificial intelligence to design, inspect, ...
Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine learning algorithm designed to identify physical anomalies in solar ...
Abstract: This work proposes the use of machine learning-based techniques for enhanced testability and performance calibration of an industrial 79-GHz power amplifier (PA) designed for an automotive ...
Introduction: Accurate defect detection in dissimilar metal welds (DMWs) remains a major challenge due to heterogeneous microstructures and imaging noise. Methods: In this study, we propose a novel ...
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