Machines fail. By creating a time-series prediction model from historical sensor data, you can know when that failure is coming Anomaly detection covers a large number of data analytics use cases.

Dr. Kitts is currently the Director of SCU’s Robotic Systems Laboratory. He holds the William and Janice Terry Endowed Professorship in Engineering and is a Fellow of the American Society of ...

The proposed industrial anomaly detection model is computationally efficient, memory-friendly, and also suitable for low-light conditions, common in manufacturing environments, making it well-suited ...

One of the best chances for proving beyond-the-standard-model physics relies on something called the Cabibbo-Kobayashi-Maskawa (CKM) matrix. The standard model insists that the CKM matrix, which ...