Accurately diagnosing bearing faults is crucial for maintaining the efficient operation of
rotating machinery. However, traditional diagnosis methods face challenges due to the …

Abstract Large Language Models (LLMs) are artificial intelligence systems trained to
understand and predict human language. In this study I programmatically create numerous …

The building sector accounts for almost 40% of global energy consumption. However,
buildings' Heating, Ventilation, and Air Conditioning (HVAC) systems are susceptible to …

With the advancement of carbon emissions reduction initiatives, there is a rapid increase in
the current demand for electrical power, which necessitates a more efficient and reliable grid …

This paper proposes a transformative approach to language learning by harnessing the
power of neural networks for adaptive assessment in English teaching. Traditional methods …