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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In the past decades, telemedicine applications have been widely recognized as a key technology to solve many problems faced by our aging society. Being part of this technological move, Mobile Patient Monitoring Systems (MPMSs) have attracted a great deal of attention due to its fitness on providing less intrusive and long-lasting telemedicine services. The first main contribution of this thesis is a set of task assignment algorthms designed for MPMSs. We propose two graph-based polynomial-time algorithms which deal with the "chain-chain assignment"and the "three-star assignment". When the targeted MPMS complies to such models, we recommend the use of these graphbased algorithms that can find the optimal solutions

Task distribution based adaptation in mobile patient monitoring systems