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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Virtual reality allows the development of digital environments that can explore users’ senses to provide realistic and immersive experiences. When used for training purposes, interaction data can be used to verify users skills. In order to do that, intelligent methodologies must be coupled to the simulations to classify users´ skills into N a priori defined classes of expertise. To reach that, models based on intelligent methodologies are composed from data provided by experts. However, online Single User’s Assessment System (SUAS) for training must have low complexity algorithms to do not compromise the performance of the simulator. Several approaches to perform it have been proposed. In this paper, it is made an analysis of performance of SUAS based on a Bayesian Network and also a comparison between that SUAS and another methodology based on Classical Bayes Rule.

Skills Assessment of Users in Medical Training Based on Virtual Reality Using Bayesian Networks