Functional Data

Anomaly detection is an essential task for quality management in smart manufacturing. An accurate data-driven detection method usually needs enough data and labels. However, in practice, there commonly exist newly set-up processes in manufacturing, …

The dependency structure of complex data is always a challenge in formulating and yielding accurate estimates. Dr Laura M. Sangalli’s paper offers a well-developed method to formulate the boundary spatial dependency by using the PDE regularization …