This article is this edition's winner of the ASU Writing Competition. The competition is open quarterly to current ASU ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

The Canadian Data Rescue Project is supporting U.S. data rescue efforts, and setting up preventative measures for Canadian ...

Sparse coding is a popular technique for achieving compact data representation and has been used in many applications. However, the instability issue often causes degeneration in practice and thus ...

Based on sparse representation techniques, this article proposes a two-stage sparse representation clustering (TSSRC) method. The novelty of the proposed TSSRC algorithm comes from evaluating the ...

Union Budget recognizes gig workers, but PLFS fails to capture diverse gig work, hindering policy inclusivity.

This article discusses how racial categories, rooted in social history, are used in records and society. It argues race isn’t ...

Overcoming test data hurdles with realistic synthetic dataQuality datasets are crucial for AI training, but the need to protect real-world data can slow development and implementation. By Bryn ...