• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.52-57
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• 2010

Using the Operating Systems course that is offered by online, a blended learning mixed up with face-to-face lecture and e-learning for O.S. course has been carried out. In order to find a efficient management way of the blended learning, we build up two groups: one group named 01 takes a class which consists of two hours face-to-face lecture and one hour online study per week and the other group named 02 takes a class which consists of two hours online study and one hour face-to-face lecture. According to the result of a mid-term examination, the Cohen's d between two groups is 0.165. It means the small effect size. The 01 group has higer average and smaller variance than 02 group. However, 02 group has more students who earn high score than 01 group. In conclusion, if students can well carry out the self-regulated learning, then the blended learning mixed up with 02 group style is suitable. Otherwise, face-to-face lecture or the blended learning like 01 group style is suitable.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.987-999
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• 2021

Recently, Federated learning has become an issue due to privacy invasion caused by data. Federated learning is safe from privacy violations because it does not need to be collected into a server and does not require learning data. As a result, studies on application methods for utilizing distributed devices and data are underway. However, Federated learning is no longer safe as research on the reconstruction attack to restore learning data from gradients transmitted in the Federated learning process progresses. This paper is to verify numerically and visually how well data reconstruction attacks work in various data situations. Considering that the attacker does not know how the data is constructed, divide the data with the class from when only one data exists to when multiple data are distributed within the class, and use MNIST data as an evaluation index that is MSE, LOSS, PSNR, and SSIM. The fact is that the more classes and data, the higher MSE, LOSS, and PSNR and SSIM are, the lower the reconstruction performance, but sufficient privacy invasion is possible with several reconstructed images.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.144-152
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• 2019

Learning styles are the methods of gathering, processing, interpreting, organizing the information. VARK learnig inventory is instructional preference classified according to their visual(V), aural(A), read-write(R), and/or kinesthetic(K) sensory modality preferences(SMP). Learner-centered learning is emphasized, but there are few studies on VARK learning styles in Korean medical school. The purposes of this study were to assess the student' SMPs and compare those with gender, status, and academic achievement. The subjects of study were 394 students at C Medical School and Graduate School of Medicine. For the study style test, 16 questions were used in Korean version of VARK test paper© 7.0 developed by Fleming provided on the VARK website. Academic achievement was converted into a standardized score(t score). Frequency analysis, cross analysis, and variance analysis(t-test, ANOVA) were conducted to identify learning style disposition and differences between groups. The uni-modal type was 87(22.1%) and the multimodal was 307(77.9%). Regardless of gender, quasi-modal VARK was the most preferred. There was no significant difference in learning styles by gender. The first grade in medicine was the lowest in uni-modal type(8.8%) and the highest in quasi-modal VARK type(47.8%), while the fourth grade was the highest in uni-modal type(30.7%) and the lowest in quasi-modal VARK type(19.8%) and tri-modal type(19.8%). There was no difference in academic achievement by all learning types(F=1.09, p=0.37). The knowledge about students' learning styles is helpful for instructors to apply more learner-centered teaching strategies in medical education.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.227-237
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• 2020

This study was designed to examine whether the self-directed learning method could improve self-directed learning readiness and the effects of academic achievement level. Self-directed learning readiness was investigated among 63 first-year Medical Terminology undergraduates in the C area. A repeat measurement variance analysis of the general linear model was conducted to evaluate the effects of improving self-directed learning readiness according to the general characteristics and level of academic achievement, while a regression analysis was performed to identify the factors affecting self-directed learning readiness. Self-directed learning readiness increased from 177.3 to 180.8 for those under 18 years of age, and 192.9 to 196.5 for those over 19 years of age (p<0.05). After the team activity, the overall self-directed learning readiness was improved, and both high- and low-achieving groups showed statistically significant improvements (p<0.05). The environment surrounding learners was confirmed to have a positive effect on improving self-directed learning when given the right degree of self-directed learning and appropriate feedback. The study results are expected to form basic foundation material for professors and class designers who want to draw self-directed learning skills from memorizing subjects.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.643-655
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• 2022

The purpose of this study was to verify the moderating effect of parental learning involvement in the effect of adolescents' time management ability on face-to-face and non-face-to-face learning flow. The participants were 363 middle and high school adolescents, and data were collected through an online survey. The main statistical analysis methods were ANOVA, correlation analysis, and regression analysis. The major findings were as follows. First, learning flow was significantly higher in the face-to-face class than in the non-face-to-face class. Second, there was a statistically significant positive correlation among time management ability, parental involvement in learning, and learning flow. Third, in the effect of time management ability on face-to-face learning flow, the moderating effect of parental learning involvement was statistically significant. Fourth, in the effect of time management ability on non-face-to-face learning flow, the moderating effect of parental learning involvement was statistically significant. In other words, the higher the positive parental involvement in learning, the stronger the effect of adolescents' time management ability on learning flow. Finally, the importance of positive parental involvement for the improvement of adolescents' learning flow and methods of enhancing time management ability were discussed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.55-61
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• 2010

In this paper, we proposed selective extraction method of frequency information and PCA-ELM based diagnosis system for three-phase induction motors. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by variance As the next step, feature extraction is performed by principal component analysis (PCA). Finally, we used the classifier based on Extreme Learning Machine (ELM) with fast learning procedure. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.512-518
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• 2013

A resource allocation algorithm has a high impact on user satisfaction as well as the ability to accommodate and process services in a distributed cloud computing. In other words, service rejections, which occur when datacenters have no enough resources, degrade the user satisfaction level. Therefore, in this paper, we propose a resource allocation algorithm considering the cloud domain's remaining resources to minimize the number of service rejections. The resource allocation rate based on Q-Learning increases when the remaining resources are sufficient to allocate the maximum allocation rate otherwise and avoids the service rejection. To demonstrate, We compare the proposed algorithm with two previous works and show that the proposed algorithm has the smaller number of the service rejections.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.29-30
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• 2019

본 논문에서는 다중 컨트롤러가 존재하는 분산 SDN 환경에서 과도한 제어 메시지로 인한 과부하된 컨트롤러의 부하를 줄이기 위하여 이주할 스위치를 K-means 군집화와 Harmony Search(HS)를 기반으로 선정 하는 기법을 제안하였다. 기존에 HS를 이용하여 이주할 스위치를 선택하는 기법이 제시되었으나, 시간 소모에 비하여 정확도가 부족한 단점이 있다. 또한 Harmony Memory(HM) 구축을 위해 메모리 소모 또한 크다. 이를 해결하기 위하여 본 논문에서는 유클리드 거리를 기반으로 하는 K-means 군집화를 이용하여 이주할 스위치를 골라내어 HM의 크기를 줄이고 이주 효율을 향상 시킨다.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.703-708
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• 2022

K-means clustering is a representative clustering technique. However, there is a limitation in not being able to integrate the performance evaluation scale and the method of determining the minimum number of clusters. In this paper, a method for numerically determining the minimum number of clusters is introduced. The explained variance is presented as an integrated measure. We propose that the k-means clustering method should be performed in the subspace of the PCA in order to simultaneously satisfy the minimum number of clusters and the threshold of the explained variance. It aims to present an explanation in principle why principal component analysis and k-means clustering are sequentially performed in pattern recognition and machine learning.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.267-274
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• 2021

The purpose of this study is to investigate differences in learning flow and teaching presence according to the lecturer's appearance and the lecturer's speech rate. For this experiment, 183 freshman students from Xingtai University in China were selected as subjects of the experiment, and a total of four types of lecture videos were developed to test the lecturer's appearance and their speech rates. Data was analyzed through multivariate analysis of variance. According to the results of the analysis, first, learning flow and teaching presence of groups who experienced the presence of the lecturer appeared were significantly higher than the groups who learned without the appearance of the lecturer. Second, the groups who learned from videos with a fast speech rate showed higher learning flow and teaching presence than the group who learned at a slow speech rate. Third, there were no significant differences in both learning flow and teaching presence according to the lecturer's appearance and speech rate. This result provides a theoretical and practical basis for developing customized videos according to learners' characteristics.