Abstract: This paper aims to investigate the efficacy of EEG-based stress detection using a Random Forest classifier during the Stroop Test, a key psychological assessment probing cognitive functions ...
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
CERES program updates include operational satellite instruments, algorithm advancements, machine learning applications, and ongoing missions measuring Earth’s energy budget and climate system changes.
Indian Defence Review on MSN
Scientists map hidden DNA switches in brain cells tied to Alzheimer’s disease
Researchers have uncovered nearly 150 hidden DNA “switches” inside brain support cells that control the activity of genes ...
A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...
Abstract: By evaluating intricate datasets to maximize plant growth, boost yields, and advance sustainability, smart agriculture—powered by Random Forest machine learning—is transforming botany.
Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
The review reports that blockchain-enhanced federated learning systems typically achieve slightly lower raw accuracy than ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
A Hebrew University study suggests AI tools could help growers better manage water use by predicting healthy plant behavior and flagging early signs of stress.
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