• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.600-610
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• 2022

While Korean piano pedagogy has seen a remarkable growth, the relatively weak attention to intermediate level has emerged as a pending problem. The limited literature review, specifically the lack of playing Korean original works, has been considered as a serious issue. To emphasize the usefulness of Kim Kukjin's "Pieces of Korean Melody for Piano" as an intermediate work, this study presents practical teaching guidelines by classifying of difficulty in his 25 pieces and providing step by step learning goals and teaching plan. The difficulty stage was based on Jane Magret's 10-step classification table for comparison with other intermediate piano literature, and this study more specifically classified Kim's pieces according to Korean melody, rhythm, and texture. As a result of the difficulty classification, it was found that the pieces from stages 4 to 10 was organized to systematically and comprehensively learn step by step from the most basic progression to Korean 'Jangdan' rhythm patterns, various articulations and decorations that express 'Sigimsae' of Korean Traditional Music, and heterophony texture. In addition, this study proposed the order of pieces for the effective teaching according to the characteristics and difficulty of the pieces. This study suggests that the findings lead to the expansion of Korean intermediate literature study and the revitalization of Korean original works teaching method.

• Journal of Korea Trade
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• v.26 no.8
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• pp.21-36
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• 2022

Purpose - Carbon emission standards are based on the "production-based carbon emissions" generated by the production of goods in the relevant country which were the existing measurement methods. However, can such carbon emissions measurement standards be established international? For example, some of the goods produced in developing countries are produced for the demand of developed countries. The method of measuring carbon emission based on the final demand of a certain country is called "consumption-based carbon emissions." This study compares productionand consumption-based CO₂ emissions according to economic growth in ninety-three countries categorized by income level. Design/methodology - Our empirical model considers the difference between production- and consumption-based CO₂ emissions according to economic growth. Also, our model investigated whether the EKC hypothesis in most of the previous studies that had been based on production-based emissions was also established in the consumption-based emission model. Considering the continuous characteristics of CO₂, we utilized the generalized method of moments (GMM), specifically a system GMM econometric technique because CO₂ in the previous period can affect CO₂ in the present period. Findings - Our main findings can be summarized as follows: The results show that for the consumption-based CO₂ emissions model, CO₂ continuously increases as economic growth increases in the upper-middle income countries. The inverted U-shaped result was found in the case of the production-based model. However, in the lower-income countries, an inverted-U shape in which CO₂ emissions decrease at some point as the economy grows in the production-based model does not appear. On the other hand, in the consumption-based model, an inverted U-shaped result was obtained when estimating with system-GMM. Additionally, the proportion of manufacturing, energy imports, and energy consumption had an effect on both the production- and the consumption-based model regardless of the group's CO₂ emissions. On the basis of such assessments, policymakers need to consider not only production- but also consumption-based options. Originality/value - Previous studies have mainly focused on production-based CO₂ emissions, with most of them revolving around economic growth or the effect of various social and economic factors on CO₂ emissions. However, this study considers the relationship with economic growth using consumption-based emissions as a dependent variable by classifying ninety-three countries by income level.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.199-206
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• 2023

This study utilizes deep learning algorithms to automatically classify construction waste into three categories: wood waste, plastic waste, and concrete waste. Two models, VGG-16 and ViT (Vision Transformer), which are convolutional neural network image classification algorithms and NLP-based models that sequence images, respectively, were compared for their performance in classifying construction waste. Image data for construction waste was collected by crawling images from search engines worldwide, and 3,000 images, with 1,000 images for each category, were obtained by excluding images that were difficult to distinguish with the naked eye or that were duplicated and would interfere with the experiment. In addition, to improve the accuracy of the models, data augmentation was performed during training with a total of 30,000 images. Despite the unstructured nature of the collected image data, the experimental results showed that VGG-16 achieved an accuracy of 91.5%, and ViT achieved an accuracy of 92.7%. This seems to suggest the possibility of practical application in actual construction waste data management work. If object detection techniques or semantic segmentation techniques are utilized based on this study, more precise classification will be possible even within a single image, resulting in more accurate waste classification

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.178-185
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• 2022

This study compared and analyzed the characteristics of new words by classifying 197 newly coined Korean and Chinese characters in 2017 and 2018 into single, compound, derivative, abbreviated, and hybrid words according to the coined method. In the case of a single language, Korean is all words borrowed from Chinese and English. However, no monolingual language appeared in Chinese. In the case of compound words, the format of the Chinese synthesis method was much more diverse and the generative power was stronger than that of Korea. In the case of derivatives, there are not many prefixes in both countries, and Korean suffixes have the strongest productivity of Chinese suffixes and weak productivity of foreign and native suffixes. Korean foreign language suffixes were characterized by relatively more appearance than Chinese. In the case of abbreviations, it can be seen that the productivity of dark syllables is stronger for Korean abbreviations, and the productivity of empty syllables is stronger for Chinese abbreviations. In the case of mixed languages, the hybrid form of Korean was much more diverse than that of Chinese. Through this study, it will be possible to help Chinese Korean learners understand the process of forming a new language, and to develop their ability to guess the meaning of Korean words while learning a new language.

• Korea Trade Review
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• v.43 no.6
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• pp.51-70
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• 2018

This study is to define the relationship between capital structure and the market share in the global shipping market, estimating the debt-equity ratio. To analyze the impact of the debt-equity ratio on market share, this study collected data from the 100 largest shipping companies from 2010 to 2017. Results identified that global shipping lines moderate their debt-equity rates to 62%, and all of them strategically utilize debt in order to increase market share in global shipping market. In comparison between the group focused on cargo volume and another group focused on freight rates, it is found that the group focused on cargo volume increase their handling cargo volume through increasing the debt rates. Another group used debt rate for reducing the freight rate and enhancing market power. Furthermore, after classifying the samples into high-growth and low-growth companies, this study compared the group focused on cargo volume and another group focused on freight rates. As a result, the low-growth group showed more significant impacts of the debt rate on market share than the high-growth group. The results of this study provide useful insight for future strategic decision making of shipping lines in the global shipping market.

• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.33-44
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• 2022

Rental services have recently come to be provided in which people can experience traditional Korean culture in the form of Hanok villages, allowing everyone can easily rent and wear hanbok, a traditional Korean garment, regardless of gender and age. Users of hanbok rental services share photos of themselves wearing hanbok on social media, contributing to the increasing popularity of hanbok experiences. However, the trend of wearing hanbok has no become established in people's daily lives, apart from the specific places that offer hanbok experiences. To promote hanbok as everyday clothes, hanbok design should be developed to provide wearers with both convenience and emotional satisfaction. Using 28 emotion words that express consumers' emotions toward hanbok that were extracted from previous studies, this study measured consumers' emotions toward different types of hanbok with on a seven-point Likert scale. Emotion words and categories that obtained scores of five points or above, signifying a rating of "felt fairly" or higher in relation to specific hanbok types were extracted. This study also examined differences in the average scores for emotional categories according to hanbok types and gender. The results indicated that only average scores for the "favorable feeling" category showed a significant difference between men and women. Finally, differences in the average scores for emotional categories were examined by classifying hanbok types: traditional (e.g., baenaet-jeogori, saekdong-jeogori, traditional hanbok for adults, and traditional wedding clothes) and modern (e.g., daily hanbok for children, for women, and for men). The results indicated significant differences between traditional and modern hanbok in six emotional categories (i.e., the cheerful, esthetic, harmonious, fresh, favorable, and stable feeling). This study derived analytic results for terms related to emotions that hanbok wearers feel according to types of hanbok. The findings can be used by hanbok retailers and rental services to provide consumers with greater emotional satisfaction.

• Knowledge Management Research
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• v.24 no.2
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• pp.87-115
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• 2023

This study aims to examine the causal relationships between sales and employment for public technology-based startups. Although there is a limit to statistical generalization due to the poor understanding of the actual conditions of public technology start-up companies, these companies were analyzed by classifying them into high-growth companise, potential growth companies, and other companies. In order to understand the causal relationship, and to estimate the time required to be effective, panel vector autoregression was applied. As a result, the performance creation mechanism was identified as government supoort and private investment was mutually causal with employment, sales did not cause employment, and employment caused sales. In other words, it was found that employment plays an mediator role in public technology based startups' performance mechanism. In addition, private investment had the effect of improving employment and sales in the short time than governments support, and showed that firms with high employment can attract government support and private investment. This study are academically meaningful in that they empirically revealed the process of performance creation, whereas previous studies had only shown whether there was an effect on performance. It also has a policy contribution by suggesting the need for effective policy promotion by considering the 'employment' factor, such as human resource support, as more important.

• Journal of Christian Education in Korea
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• v.72
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• pp.183-203
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• 2022

The purpose of this study is to construct factors of AI education utilization competency. AI education utilization competency is used as basic data for education to enhance the AI education competency of pre-service early childhood teachers. To this end, 7 studies related to competency factors and models were selected by searching for previous studies. Seven preceding studies were analyzed. As a result, 18 competency factors were extracted, including understanding of artificial intelligence. The extracted competency elements were divided into six areas, which are divided into understanding subject knowledge through coding, class preparation, class management, class result feedback, class guidance, and self-development. And 15 factors were constructed. The draft formed through coding was improved through review by three early childhood education experts. Factors improved through expert review were structured by classifying them into knowledge, skills, and attitudes to organize the curriculum. The validity of the structured competency factor was verified through expert Delphi. As a result of the Delphi verification, all factors were converged in the first survey. Through this, 6 competency areas, 11 competency factors, and 19 competency factors were composed of knowledge, 10 skills, and 5 attitudes. The implication is that the competency factors presented as a result of this study can be used as basic data for organizing a curriculum to improve the ability of pre-service early childhood teachers to use artificial intelligence education.

• Journal of Christian Education in Korea
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• v.74
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• pp.255-271
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• 2023

Purpose of study: The purpose of this study is to explore the moderating effect of learning motivation in the effect of cognitive presence on cognitive regulation. Research content and method: The subjects of this study were 160 preservice teachers who are enrolled in the Faculty of Education of a university. The survey measured cognitive control, human presence, and learning motivation. Among the collected data, learning motivation was averaged. In addition, a group with low learning motivation and a group with high motivation were distinguished. Next, this study compared the averages of cognitive control by classifying the learning motivation levels. The collected data was analyzed using a multiple regression (Stepwise) method to explore the effect of cognitive presence on cognitive control. First, multiple regression analysis was performed on the entire group. Second, multiple regression analysis was performed by dividing the group with low learning motivation from the group with high motivation. Conclusions and Suggestions: As a result of the analysis, the group with high learning motivation showed a higher level of cognitive control than the group with low motivation. In the group with high learning motivation, only content understanding among the sub-factors of cognitive presence had an effect on cognitive control. In the group with low learning motivation, all factors of cognitive presence were affected.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.759-766
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• 2008

Road classification system is the first step for determining the road function and design standards. Currently, roads are classified by various indices such as road location and function. In this study, we classify road using various traffic indices as well as to identify traffic characteristics for each type of road. To accomplish the objectives, mixture model was applied for classifying road and analyzing traffic characteristics using traffic data that observed at permanent traffic count stations. A total of 8 variables were applied: annual average daily traffic(AADT), $K_{30}$ coefficient, heavy vehicle proportion, day volume proportion, peak hour volume proportion, sunday coefficient, vacation coefficient, and coefficient of variation(COV). A total of 350 permanent traffic count points were categorized into three groups : Group I (Urban road), Group II (Rural road), and Group III (Recreational road). AADT were 30,000 for urban, 16,000 for rural, and 5,000 for recreational road. Group III was typical recreational road showing higher average daily traffic volume during Sunday and vacational periods. Group I showed AM peak and PM peak, while group II and group III did not show AM peak and PM peak.