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Yaser Jararweh

Researcher at Jordan University of Science and Technology

Publications -  324
Citations -  8851

Yaser Jararweh is an academic researcher from Jordan University of Science and Technology. The author has contributed to research in topics: Cloud computing & Computer science. The author has an hindex of 44, co-authored 297 publications receiving 6045 citations. Previous affiliations of Yaser Jararweh include University of Arizona & Pennsylvania State University.

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Proceedings ArticleDOI

Measuring the Impacts of Virtualization on the Performance of Thread-Based Applications

TL;DR: This paper presents a performance-based evaluation for thread-based applications that are hosted on different virtualization frameworks and evaluates the effects of virtualization techniques on sequential and multithreaded applications.
Proceedings ArticleDOI

Completing IEEE 802.11e implementation in NS-3

TL;DR: This work complete the implementation of the IEEE 802.11e standard in NS-3, which was developed as an amendment to the original802.11 standard to provide QoS support.
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Social Networking Sites and Deaf and Hard of Hearing People in Jordan: Characteristics and Preferences

TL;DR: This survey shows how SNSs are integrated with deaf people as a communication tool and the positive impact resulted from using them and it was found that Arabic sign language is most frequently used more than any other communication mode.
Proceedings ArticleDOI

A Mobile-Edge Computing Bio-Surveillance Framework for Multiple Biological Attacks Detection

TL;DR: This work proposes a multi-agent framework for multiple biological threat detection that utilizes recent advances in wearable sensors to monitor human vital signs and intelligent agents are defined in the context of mobile-edge computing platforms to group monitoring information into focused clusters.
Proceedings ArticleDOI

An Emotional Feedback Based on Facial Action Coding System for MOOCs with Computer-Based Assessment

TL;DR: A new emotional feedback based on facial action coding system for MOOCs is proposed, which aims to make the learners aware of their emotional states via the analysis of their facial expressions using the facialaction coding system during the courses as well as integrate computer based assessment for evaluating learners' emotional states, thus improving their motivation, engagement, self-regulation and learning achievement.