• Journal of the Korean Society of Earth Science Education
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• v.5 no.3
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• pp.276-286
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• 2012

This research is aimed to examine the differences through comparative analysis of the Earth Science contents in the science textbooks between Korea and DPRK. The contents of level and scope in science textbooks between Korea and DPRK are analysed by TIMSS frameworks. The results of this research are as follows : 1. The science textbooks of DPRK is lower in quality of paper, printing to that of Korea, and the illustrations, editing design in the textbooks of DPRK are fewer, monochromic and monotonous while those in Korea. 2. The contents of Earth Science in DPRK's science textbooks rank 37.0%, but those of Korea's science textbooks rank 25.5% of the whole textbooks. The learning units related to Earth Science are generally similar to the level and scope in science textbooks between Korea and DPRK. The type of inquire activities in the textbooks of DPRK largely takes on the model experiment, and it was shown that the number of experiments directly made by children is very small compared to Korea' textbooks. 3. There are lots of differences in Earth Science learning terms and predicates used in the textbooks between Korea and DPRK.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.88-98
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• 2017

The purpose of this study is to develop the teaching competency tool of university teachers with responsibility for college education and analyze the need for change. We have developed teaching competency to strengthen the competencies required for university professors' responsibilities and community activities in and out of universities and the contents validity was examined from 24 experts. The developed tools were used to diagnose the 83 teachers of K university in Chungcheongnam-do, and to derive basic competence, educational practice competence, and community competence through exploratory factor analysis and confirmatory factor analysis. The teaching competencies include 'Understanding of college education', 'Educational philosophy and attitude', 'Teacher attitude', 'Analysis design', 'Instruction execution', 'Guidance management', 'Evaluation feedback', 'Academic convergence', 'Sympathy learning culture', and 'Global sharing'. The results of the paired t-test and the analysis of the need for change through the analysis of Borich coefficient analysis were as follows: Understanding of university education (4th rank), analysis design (5th rank), instruction execution(2nd rank), empathy learning culture (1st rank), and global sharing (3rd rank). The competence of university teachers is not only the ability to practice teaching, but also the ability to understand university education and to empathize and share with the members of the university community. In the future, the university should actively develop and provide ongoing support programs to strengthen the capacity of professors.

• Journal of Dental Rehabilitation and Applied Science
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• v.33 no.2
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• pp.88-96
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• 2017

Purpose: The purpose of this study is to assess the relationship between the time spent designing custom abutments and repeated learning using dental implant computer aided design (CAD) software. Materials and Methods: The design of customized abutments was performed four stages using the 3DS CAD software and the EXO CAD software, and measured repeatedly three times by each stage. Learning effect by repetition was presented with the learning curve, and the significance of the reduction in the total time and the time at each stage spent on designing was evaluated using the Friedman test and the Wilcoxon signed rank test. The difference in the design time between groups was analyzed using the repeated measure two-way ANOVA. Statistical analysis was performed using the SPSS statistics software (P < 0.05). Results: Repeated learning of the customized abutment design displayed a significant difference according to the number of repetition and the stage (P < 0.001). The difference in the time spent designing was found to be significant (P < 0.001), and that between the CAD software programs was also significant (P = 0.006). Conclusion: Repeated learning of CAD software shortened the time spent designing. While less design time on average was spent with the 3DS CAD than with the EXO CAD, the EXO CAD showed better results in terms of learning rate according to learning effect.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.1-7
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• 2021

In this paper, we propose a feature selection technique for multi-label classification. Many existing feature selection techniques have selected features by calculating the relation between features and labels such as a mutual information scale. However, since the mutual information measure requires a joint probability, it is difficult to calculate the joint probability from an actual premise feature set. Therefore, it has the disadvantage that only a few features can be calculated and only local optimization is possible. Away from this regional optimization problem, we propose a feature selection technique that constructs a low-rank space in the entire given feature space and selects features with sparsity. To this end, we designed a regression-based objective function using Nuclear norm, and proposed an algorithm of gradient descent method to solve the optimization problem of this objective function. Based on the results of multi-label classification experiments on four data and three multi-label classification performance, the proposed methodology showed better performance than the existing feature selection technique. In addition, it was showed by experimental results that the performance change is insensitive even to the parameter value change of the proposed objective function.

• Computers and Concrete
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• v.32 no.3
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• pp.313-326
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• 2023

The seismic safety of the shear wall structure can be assessed through seismic fragility analysis, which requires high computational costs in estimating seismic demands. Accordingly, machine learning methods have been applied to such fragility analyses in recent years to reduce the numerical analysis cost, but it still remains a challenging task. Therefore, this study uses the ensemble machine learning method to present an improved framework for developing a more accurate seismic demand model than the existing ones. To this end, a rank-based selection method that enables determining an excellent model among several single machine learning models is presented. In addition, an index that can evaluate the degree of overfitting/underfitting of each model for the selection of an excellent single model is suggested. Furthermore, based on the selected single machine learning model, we propose a method to derive a more accurate ensemble model based on the bagging method. As a result, the seismic demand model for which the proposed framework is applied shows about 3-17% better prediction performance than the existing single machine learning models. Finally, the seismic fragility obtained from the proposed framework shows better accuracy than the existing fragility methods.

• English Language & Literature Teaching
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• v.9 no.1
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• pp.131-152
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• 2003

The purpose of this study is to investigate the correlation between the introduction order of 9 English morphemes in the English textbook used in the middle school and the learning order of the morphemes by the 7th graders learning English as a foreign language. The subjects are 139 students in two middle schools, who learn English with different textbooks. The introduction order of each morpheme in two textbooks was examined according to its quantity and frequency. Data on the real learning order were collected through the written SLOPE test, and each morpheme was ranked by its group score. The introduction order of each morpheme in the textbook and the real learning order were analyzed by Spearman rank order correlation. It was shown that the correlation between the two was very low. This means that those textbooks do not take the learning order of English morphemes into account. Also it was shown that in the earlier stage of learning English the introduction order of each morpheme in the textbook had much influence on its learning order, but in the later stage such influence reduced gradually. This means that the learning order of English morphemes approaches the natural order as time passes by.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1163-1185
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• 2024

With the sharp increase in the volume of literature data, researchers must spend considerable time and energy locating desired papers. A paper recommendation is the means necessary to solve this problem. Unfortunately, the large amount of data combined with sparsity makes personalizing papers challenging. Traditional matrix decomposition models have cold-start issues. Most overlook the importance of information and fail to consider the introduction of noise when using side information, resulting in unsatisfactory recommendations. This study proposes a paper recommendation method (PR-SLSMF) using document-level representation learning with citation-informed transformers (SPECTER) and low-rank and sparse matrix factorization; it uses SPECTER to learn paper content representation. The model calculates the similarity between papers and constructs a weighted heterogeneous information network (HIN), including citation and content similarity information. This method combines the LSMF method with HIN, effectively alleviating data sparsity and cold-start issues and avoiding topic drift. We validated the effectiveness of this method on two real datasets and the necessity of adding side information.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.49-58
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• 2020

Lately, a large amount of textual data have been poured out of the Internet and the technology to refine them is needed. Most of these data are long text and often have no title. Therefore, in this paper, we propose a technique to combine the sequence-to-sequence model of RNN and the REINFORCE algorithm to generate the title of the long text automatically. In addition, the TextRank algorithm was applied to extract a summarized text to minimize information loss in order to protect the shortcomings of the sequence-to-sequence model in which an information is lost when long texts are used. Through the experiment, the techniques proposed in this study are shown to be superior to the existing ones.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.176-182
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• 2023

With about 80% of the global economy expected to shift to the global market by 2030, exports of reverse direct purchase products, in which foreign consumers purchase products from online shopping malls in Korea, are growing 55% annually. As of 2021, sales of reverse direct purchases in South Korea increased 50.6% from the previous year, surpassing 40 million. In order for domestic SMEs(Small and medium sized enterprises) to enter overseas markets, it is important to come up with export strategies based on various market analysis information, but for domestic small and medium-sized sellers, entry barriers are high, such as lack of information on overseas markets and difficulty in selecting local preferred products and determining competitive sales prices. This study develops an AI-based product recommendation and sales price estimation model to collect and analyze global shopping malls and product trends to provide marketing information that presents promising and appropriate product sales prices to small and medium-sized sellers who have difficulty collecting global market information. The product recommendation model is based on the LTR (Learning To Rank) methodology. As a result of comparing performance with nDCG, the Pair-wise-based XGBoost-LambdaMART Model was measured to be excellent. The sales price estimation model uses a regression algorithm. According to the R-Squared value, the Light Gradient Boosting Machine performs best in this model.

• Journal of the Korean Society of Earth Science Education
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• v.8 no.1
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• pp.76-86
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• 2015

The purpose of this study is to take advantage of the smart teaching - learning programs about the unit of 'Earth and Moon' and find out how to apply the effect appears. Teaching-Learning program was conducted over eight lessons. And we analyzed the effect of the program at any time through the evaluation and interview. The results are as follows. First, this study proposed a method to assist in the teaching and learning of spatial ability for students' movement of the Earth and the Moon. The program takes advantage of N-Screen Applications were configured to allow both Earth observation insider perspective and the external multilateral perspective. This improves students' understanding qualitatively. Second, we applied the teaching and learning programs utilizing smart smart devices, and the result was a lot of low rank students' average score rises. In addition, we were able to see that many students' understanding and interest, self-confidence are improved.