English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Taguchi’s quality loss function for larger-the-better performance characteristics uses a reciprocal transformation to compute quality loss. This paper suggests that reciprocal transformation unnecessarily complicates and may distort results. Examples of this distortion include the signal-to-noise ratio based on mean squared deviation and the signal-to-noise ratio based on complexity. The concept of complexity is an important element of axiomatic design and axiomatic quality. This paper shows that a simple linear transformation as used in the unified loss function can give an appropriate and comparable signal-to-noise ratio based on mean squared deviation and signal-to-noise ratio based on complexity for larger-the-better characteristics. Mathematical derivations are given and two examples are discussed to demonstrate the proposed methodology.

Signal-to-Noise ratio and design complexity based on Unified Loss Function – LTB case with Finite Target