Semiconductor Engineering

Overcoming Regression Debug Challenges With Machine Learning

Development of a modern semiconductor requires running many electronic design automation (EDA) tools many times over the course of the project. Every stage, from architectural exploration and design ...
Semiconductor Engineering

Using Machine Learning To Automate Debug Of Simulation Regression Results

Regression failure debug is usually a manual process wherein verification engineers debug hundreds, if not thousands of failing tests. Machine learning (ML) technologies have enabled an automated ...
ascopubs.org

Machine Learning Approach for Rapid, Accurate Point-of-Care Prediction of M-Spike Values in Multiple Myeloma

Random forest (RF) analysis identified the weighted value of each independent variable (N = 43) integrated into the ML algorithm. Pearson and Spearman coefficients indicated that the ML-predicted ...
pv magazine International

Machine learning-based fault detection technique for bifacial PV

CNN and random forest model to detect multiple faults in bifacial PV systems, including dust, shading, aging, and cracks. Using simulated I-V curves and a 180-day synthetic dataset, the model achieved ...