The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.
Abstract: In this paper, a compact sparse array is designed for the upper 6 GHz (U6G) band, specifically optimized for the 6.5-7 GHz band. Based on this array, the hybrid beamforming (HBF) algorithm ...
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