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https://doi.org/10.1109/mipro....
Article . 2014 . Peer-reviewed
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Using hybrid mobile applications for adaptive multimedia content delivery

Authors: Aleksandar Karadimce; Dijana Capeska Bogatinoska;

Using hybrid mobile applications for adaptive multimedia content delivery

Abstract

Increasingly more people are using smart mobile devices for delivering multimedia content such as text, video, images and audio in everyday communication. Therefore, there is an increased interest for developing mobile applications that will be supported by different mobile devices. The hybrid mobile applications are built using HTML5 and JavaScript native container that provide access to native platform features, such as built-in camera, accelerometers, GPS and gyroscopic sensors for navigation. This way application can extensively use the mobile device features in order to provide multimedia content that is adapted to learners in m-learning environment. The research focuses on methods and concepts for adaptive multimedia content delivery systems that are considering real-time multimedia delivery to hybrid mobile devices. The adaptive process requires considering the influence from interactive functionality and technical capabilities of mobile devices in m-learning environment. We will conclude the paper with a case study based on the hybrid mobile application used in mobile learning environment.

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Keywords

adaptive multimedia content, m-learning, hybrid mobile applications

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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