From predictive analytics to autonomous control, AI is making renewable energy systems smarter, faster, and more efficient.

In diabetes care, AI has propelled the field forward through predictive modeling, decision support, and real-time glycemic ...

A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline ...

Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, despite significant advancements in diagnosis and treatment. However, the integration of artificial ...

A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline ...

As Internet of Things (IoT) devices proliferate in sectors like smart cities, health care, and industrial systems, they have ...

A recent study introduces an advanced anomaly-based intrusion detection system (IDS) designed to address the increasing cyber ...

A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a ...

This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional Gated ...

By introducing deep learning Long Short-Term Memory (LSTM) and Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) models to analyze the sensing spectra, we overcome the limitations of ...

We utilized range-Doppler maps to capture temporal changes in range and Doppler frequency and employed deep learning models, including a 3D-CNN and a combination of LSTM with a 2D-CNN, to classify ...