Gyeongin National University of Education

www.ginue.ac.kr/
Incheon, South Korea

Gyeongin National University of Education is a national institution which provides training for future public elementary school teachers in South Korea. It was founded on May 23, 1946 under the name of Gaeseong School of Education in Gyeonggi-do. In 2003, the institution changed its name from Inchon National University of Education to Gyeongin National University of Education. The university is the largest educational institute for training future elementary school teachers in Korea. The university has two campuses: Incheon campus in Gyesan-dong, Gyeyang-gu, Incheon, and Gyeonggi campus in Seoksu-dong, Manan-gu, Anyang in Gyeonggi-do. The university offers graduate and undergraduate programs, and has an attached elementary school. Wikipedia.

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Lee S.,Gyeongin National University of Education
Lecture Notes in Electrical Engineering | Year: 2017

In collaborative filtering-based recommender systems, items are recommended by consulting ratings of similar users. However, if the number of ratings to compute similarity is not sufficient, the system may produce unreliable recommendations. Since this data sparsity problem is critical in collaborative filtering, many researchers have made efforts to develop new similarity metrics taking care of this problem. Jaccard index has also been a useful tool when combined with existing similarity measures to handle data sparsity problem. This paper proposes a novel improvement of Jaccard index that reflects the frequency of ratings assigned by users as well as the number of items co-rated by users. Performance of the proposed index is evaluated through extensive experiments to find that the proposed significantly outperforms Jaccard index especially in a dense dataset and that its combination with a previous similarity measure is superior to existing measures in terms of both prediction and recommendation qualities. © Springer Nature Singapore Pte Ltd. 2017.


Lee S.,Gyeongin National University of Education
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2017

As data sparsity may produce unreliable recommendations in collaborative filtering-based recommender systems, it has been addressed by many researchers in related fields. Jaccard index is regarded as effective when combined with existing similarity measures to relieve data sparsity problem. However, the index only reflects how many items are co-rated by two users, without considering whether their ratings are evaluated similar or not. This paper proposes a novel improvement of Jaccard index, reflecting not only the ratio of co-rated items but also whether the ratings of each co-rated item by two users are both high, medium, or low. A genetic algorithm is employed to find the optimal weights of the levels of evaluations and the optimal boundaries between them. We conducted extensive experiments to find that the proposed index significantly outperforms Jaccard index on moderately sparse to dense datasets, in terms of both prediction and recommendation qualities. © Springer International Publishing AG 2017.


Lee S.,Gyeongin National University of Education
Advanced Science Letters | Year: 2017

Collaborative filtering is a very popular technique used in recommender system. User-based collaborative filtering techniques recommend items based on the ratings data of similar users. Therefore, the system performance is critically dependent on similarity computation. This work attempts to find optimal weights best suited to each user in formulating the similarity measure. The resulting personalized similarity measure enables significant improvements over the traditional method in terms of both recommendation and prediction qualities. Moreover, such improvements are notable, for they are achieved on a sparse dataset as well as on a denser one. © 2017 American Scientific Publishers All rights reserved.


Hong S.-I.,Gyeongin National University of Education
European Journal of Physics | Year: 2016

As an instructive (gravitational potential) energy approach, we show that the elliptic roly-poly has a richer and more useful profile (including the tilted configuration) of stable equilibria than conventional spherical or cylindrical roly-polys. © 2016 IOP Publishing Ltd.


Park N.H.,Anyang University, South Korea | Joo K.H.,Gyeongin National University of Education
International Journal of Multimedia and Ubiquitous Engineering | Year: 2014

The conventional researches on a distributed On-Line Analytical Processing (OLAP) system have been in hardship to be adapted to real business environment. However, the recent spread of Cloud PaaS (Platform as a Services) provides new chances in the field of a distributed OLAP. OLAP query execution costs many minutes by its enormous data and OLAP query properties. On the other hand, MOLAP has fast responses. But it has a physical space limit to materialize all cells in possible combinations. Therefore, MOLAP is unsuited to analyze large data. In this paper, to provide not only flexibility and expandability of ROLAP but also the speediness of MOLAP, the cloud server architecture is proposed which shares clients' cube cache by P2P and manages central index on cube data on P2P nodes. In this paper, each node acts as not only a P2P duplicator of aggregated data cubes but also a hybrid server to process queries on sub-cubes. Also, the requests on server are confined to non-aggregated areas and multiple client nodes exchange data simultaneously and asynchronously in the proposed Cloud P2P OLAP. In particular, data are retrieved from physically or logically adjacent nodes. With time series properties, the volume of requested data is minimized and the reuse of past cache data is focused. While central managed P2P has blocked the extendibility, Cloud P2P OLAP guarantees the performance and the extendibility. While Grid OLAP should keep self-distributed system, Cloud use services as much as used by public services. Therefore, Cloud P2P OLAP solves a lot of theoretical limits of conventional distributed OLAP. © 2014 SERSC.


Lee S.,Gyeongin National University of Education
Computers in Human Behavior | Year: 2015

With the growing speed of SNS accelerated recently, there are increasing concerns about the possibility of young students doing negative SNS behavior. This study tried to discover the relationship between various variables such as gender, grade, SNS usage time, motives to use SNS, degree of using advanced functions of SNS, SNS dependency, and perceptions about SNS with negative SNS behaviors among elementary and middle school students. The analyses revealed that regardless of gender and grade, the most frequently committed negative behavior is 'stealing others' private information' and the least is 'cyber bullying', while 'contacting strangers' showing the most significant increase with the age. With the seriousness of negative SNS behaviors classified into four levels, it was found that the biggest significant difference across the levels appears on illegal use of photos and videos, followed by on verbal abuse and on cyber bullying. It was also found that a significant positive correlation exists between each of the factors considered and the negative SNS behavior. Based on these findings, a regression analysis was conducted to successfully extract several factors as significant predictors of the negative SNS behaviors. Furthermore, factors distinguishing the lowest level from the highest level of the negative SNS behaviors were identified to be gender, SNS dependency, utilization of advanced SNS functions, and grade, with its accuracy rate reaching as high as 85.6%. © 2014 Elsevier Ltd. All rights reserved.


Hong S.-I.,Gyeongin National University of Education
Physics Education | Year: 2016

A comic strip about a plane mirror was used in a high school optics test, and it was perceived that a large portion of the students believed that the mirror should be larger than the object so the virtual image could be entirely visible. Inspired on the comic strip, an experimental demonstration with flat mirrors was developed, in order to readdress this topic learning. Students were encouraged to create their own investigation of the phenomenon with a simple instrumental apparatus and also suggest different experimental approaches. © 2016 IOP Publishing Ltd.


Ahn S.,Gyeongin National University of Education
Proceedings - 2014 International Conference on Soft Computing and Machine Intelligence, ISCMI 2014 | Year: 2014

In this paper, I research about if the digital textbook has an effect on ability of self-directed learning that many Korean has an interest in. In order to know if the digital textbook has an effect on ability of self-directed learning, I measure the ability of self-directed of students up twice. I found that digital textbook have a effect on ability of selfdirected learning. © 2014 IEEE.


Lee S.,Gyeongin National University of Education
Lecture Notes in Electrical Engineering | Year: 2015

Similarity is a most critical index in collaborative filteringbased recommdender systems, which suggest items to their customers by consulting most similar neighbors. Current popular similarity measures may mislead the user to unwanted items in certain cases, due to their inherent properties. This study suggests a novel idea to significantly decrease such occurrences by enforcing qualifying conditions to neighbors using some simple criteria, to make consultations for their ratings. From extensive experiments, the proposed idea is found to substantially improve prediction performance of collaborative filtering based on existing similarity measures. This result is noticeable considering that such improvements are achieved by simply consulting only those neighbors satisfying the given criteria, without adopting any sophisticated similarity measure. © Springer-Verlag Berlin Heidelberg 2015.


Hong S.-I.,Gyeongin National University of Education
European Journal of Physics | Year: 2015

Due to reversibility of light rays, th.e thin-lens equation (TLE) is symmetric under the exchange of the object distance and the image distance. To measure the focal length of a converging lens, the displacement method (or Bessels method) utilizes the two different configurations of the real object, the converging lens and the real image which correspond to the two symmetric solutions of the TLE. Theoretically, we show that this method can be generalized to all possible pairs of symmetric solutions of the TLE for both converging and diverging lenses. © 2015 IOP Publishing Ltd.

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