A research team affiliated with UNIST has reported a new simulation tool to better understand how liquid-phase chemical ...

Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...

The test data of metals, brittle materials and polymers in high, medium and low strain-rate range were summarized. It was found that the dynamic strength or yield stress of these materials was not ...

Abstract: Recent advances in distributed machine learning and wireless network technologies are bringing new opportunities for Internet of Things (IoT) systems, where smart devices are often ...

Abstract: To provide accurate key variable prediction, data-driven soft sensing techniques have extracted much attention in recent years. Due to different control strategies in industrial processes, ...