H
Hwa-Young Jeong
Researcher at Kyung Hee University
Publications - 146
Citations - 907
Hwa-Young Jeong is an academic researcher from Kyung Hee University. The author has contributed to research in topics: Cloud computing & The Internet. The author has an hindex of 16, co-authored 142 publications receiving 792 citations.
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A secure authentication scheme with anonymity for session initiation protocol using elliptic curve cryptography
TL;DR: By a sophisticated analysis of the security of the proposed protocol, it is shown that the proposed authentication scheme with anonymity using elliptic curve cryptograph not only overcomes weaknesses in previous schemes but also is very efficient, suitable for applications with higher security requirements.
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Training soft skills via e‐learning: international chain hotels
TL;DR: This paper investigated the perceived importance of soft skills for hotel employees, their willingness to use electronic learning as a training tool to improve their soft skills, and the impact of hotel employees' individual characteristics (i.e., motivation, self-efficacy, technology anxiety) on their intentions to use elearning across different age groups.
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Personalized Learning Course Planner with E-learning DSS using user profile
TL;DR: The results indicate that the proposed Personalized Learning Course Planner (PLCP) improved learning effectiveness and student satisfaction and encouraged students to concentrate on the lesson.
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KDE based outlier detection on distributed data streams in multimedia network
TL;DR: Theoretical analysis and experiments on Storm with synthetic and real data show that the KDEDisStrOut algorithm is efficient and effective compared with existing outlier detection algorithms, and more suitable for data streams.
Journal Article
Best web service selection based on the decision making between QoS criteria of service
TL;DR: In this article, the authors proposed a best web service selection method which helps to find a service provider providing the optimal quality, which is different from the AHP method in that there's no need to perform a pair-wise comparison again when comparative alternatives are added or deleted.