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/

Global: Zendy Plus annual

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

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Query optimization in heterogeneous database systems is not always possible since the component DBMS may not have the ability to transmit necessary information. However, these systems need query optimization because the cost of transmitting large quantities of data across diverse databases is very high. We propose a query strategy which uses hypothesis testing to determine which of two sets of data are larger. Our experiments show that this strategy is very likely to select the smaller set when the sampling results fall outside a region of uncertainty we call the “grey zone.” This provides query optimization without transmission of database statistics.

Using statistical sampling for query optimization in heterogeneous library information systems