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 Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

One of the biggest criticisms of the Set Shaping Theory is the lack of apractical application. This is due to the difficulty of its application. Infact, to apply this technique from an experimental point of view we must use atable that defines the correspondences between two sets. However, this approachis not usable in practice, because the table has A^N elements, with A number ofsymbols and N length of the message to be encoded. Consequently, these tablescan be implemented in a program only when A and N have a low value.Unfortunately, in these cases, there are no compression algorithms with suchefficiency as to detect the improvement introduced by this method. In thisarticle, we use a function capable of performing the transform without usingthe correspondence table; this allows us to apply this theory to a wide rangeof values of A and N. The results obtained confirm the theoretical predictions.

Practical applications of Set Shaping Theory in Huffman coding