FET HUMAC Researchers Achieve Success with Two Patent Filings

We are proud to celebrate the successful filing of two patents, "Method for Adaptive Regression" (PI2026002497) and "NLDD-Based Methods for Sequencing and Analyzing Sparse Spatiotemporal Data in Multivariate Data" (PI2026002498). 

 

These innovations were developed by Herrick Yeap Han Lin and Lim Le Ying, both Doctor of Philosophy (Computing) researchers, under the supervision of Professor Ir. Ts. Yap Kian Meng and Ir. Dr. Steven Eu Kok Seng.

 

The first method sequences data objects from sparse spatiotemporal data using regression, adaptive validation, and noise filtering, with fallback predictions for insufficient datasets. The second introduces a Normalized Least Dependent Difference (NLDD) metric to assess linearity, homoskedasticity, and outliers in multivariate data. 

 

Both methods are efficient and scalable and have been applied in a library robot system to detect misplaced books and improve inventory management.