• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.309-314
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• 2023

This study examines the development and limitations of current artificial intelligence (AI) music composition programs. AI music composition programs have progressed significantly owing to deep learning technology. However, they possess limitations pertaining to the creative aspects of music. In this study, we collect, compare, and analyze information on existing AI-based music composition programs and explore their technical orientation, musical concept, and drawbacks to delineate future directions for AI music composition programs. Furthermore, this study emphasizes the importance of developing AI music composition programs that create "personalized" music, aligning with the era of personalization. Ultimately, for AI-based composition programs, it is critical to extensively research how music, as an output, can touch the listeners and implement appropriate changes. By doing so, AI-based music composition programs are expected to form a new structure in and advance the music industry.

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.279-288
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• 2021

The interest in artificial intelligence education in education is also high based on recent social interest in artificial intelligence. Accordingly, Korea is preparing a foothold for revitalizing artificial intelligence education in the future, such as announcing an artificial intelligence education plan by expanding from software (SW) education that has become a regular curriculum after the 2015 revised curriculum, and various studies are being conducted. However, research on the curriculum related to what and how to educate in artificial intelligence education is still in its infancy and further research is needed. A look at related research shows many similarities and differences in research related to domestic and foreign AI curriculum, because there are differences in the areas and content elements that each research focuses on. Therefore, in this study, in preparation for the future independence of the information subject and the formalization of AI education, literature studies on domestic and foreign AI curriculum are conducted, and based on this, the direction of the curriculum composition for elementary school AI education is to be explored.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.869-876
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• 2021

In the field of music, various AI composition methods using machine learning have recently been attempted. However, most of this research has been centered on Western music, and little research has been done on Korean traditional music. Therefore, in this paper, we will create a data set of Korean traditional music, create a melody using three algorithms based on the data set, and compare the results. Three models were selected based on the similarity between language and music, LSTM, Music Transformer and Self Attention. Using each of the three models, a melody generator was modeled and trained to generate melodies. As a result of user evaluation, the Self Attention method showed higher preference than the other methods. Data set is very important in AI composition. For this, a Korean traditional music data set was created, and AI composition was attempted with various algorithms, and this is expected to be helpful in future research on AI composition for Korean traditional music.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.433-441
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• 2020

The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.

• Information Systems Review
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• v.25 no.3
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• pp.43-57
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• 2023

In this study, we developed an AI-based system to generate sentences that assist in creating Korean poetry. Instead of replacing the creative aspect of composition, which is considered a unique domain of humans, the focus was on generating foundational sentences to enhance human imagination efficiently. By conducting interviews with poets, the researchers extracted sentences from eight distinct datasets, enabling the generation of poetry across eight different genres. This study stands out for its innovation in developing a method for crafting literary works in Korean. Its significance lies in its potential to facilitate the creation of diverse literary forms such as essays, prose, or novels.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.261-266
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• 2018

This study aimed to provide an overview of artificial intelligence based music composition programs. The artificial intelligence-based composition program has shown remarkable growth as the development of deep neural network theory and the improvement of big data processing technology. Accordingly, artificial intelligence based composition programs for composing classical music and pop music have been proposed variously in academia and industry. But there are several limitations: devaluation in general populations, missing valuable materials, lack of relevant laws, technology-led industries exclusive to the arts, and so on. When effective measures are taken against these limitations, artificial intelligence based technology will play a significant role in fostering national competitiveness.

• Journal of Nutrition and Health
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• v.30 no.10
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• pp.1140-1152
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• 1997

Serum and liver lipid levels and fatty acid composition of liver phospolipids (PL) were investigated in 36 rats which consumed either one of five different dietary fats or a high carbohydrate diet for 4 weeks. As the sources of five dietary fats, concentrated cicosapentaenoic acid(EPA), fish oil (FO), perilla oil(PO), corn oil(CO) and beef tallow (BT) were provided to the rats. As a control group, cron starch (CS) replaced dietary fat. The FO group showed lower serum total cholesterol (TC), high density lipiprotein cholesterol(HDL-C) and serum PL levels than those of the CO group(p<0.05). There were no significant differences in serum TC and serum HDL-C levels between the polyunsatured fatty acid(PUFA) groups and the EPA, FO and PO groups. The CS group showed the highest level serum TC. Compared with the CS group, both the EPA and CO groups showed significantly lower atherogenic indices(AI). However, there were no significant differences in AI among different dietary fat groups. No significant differences in liver triglyceride (TG) , TC and PL levels were detected among the six experimental groups. Phosphatidylcholine(PC) and phosphatidylethanolamine(PE) composed 30-40% and 15-20% of total liver PL, respectively. The fatty acid composition of liver PC and PE reflected dietary fatty acid composition . Compared to the different dietary fat based diets used in our study, the high carbohydrate diet had the most adverse effects on serum lipid profiles. However, we can not conclude from this result that long chain n-3 PUFA diets such as the EPA and FO based diets have more beneficial effects on serum lipid profiles than n-6 PUFA diet such as the CO based diet or shorter chain n-3 PUFA diets like the PO based diet.

• Trans-
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• v.13
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• pp.117-140
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• 2022

Recently, artificial intelligence technology is being used throughout the industry. Currently, Currently, AI art generators are used in the NFT industry, and works using them have been exhibited and sold. AI art generators in the art field include Gated Photos, Google Deep Dream, Sketch-RNN, and Auto Draw. AI art generators in the music field are Beat Blender, Google Doodle Bach, AIVA, Duet, and Neural Synth. The characteristics of AI art generators are as follows. First, AI art generator in the art field are being used to create new works based on existing work data. Second, it is possible to quickly and quickly derive creative results to provide ideas to creators, or to implement various creative materials. In the future, AI art generators are expected to have a great influence on content planning and production such as visual art, music composition, literature, and movie.

• Journal of the East Asian Society of Dietary Life
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• v.15 no.6
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• pp.675-686
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• 2005

It is known that appropriate exercise changes body composition and improves coronary artery disease. This study was undertaken to evaluate the relationships between aerobic exercise, body composition, and the blood lipid levels in the middle-aged women(33 to 54 years old). The 57 subjects were divided into two groups based on their exercise: the aerobic exercise group(A group: 44) which performed at about $60\%$ of $VO_2max$ during over 6 months and the sedentary one(S group: 13). The percentages of body fat waist/hip ratio(WHR), body mass, and lean body mass of two groups were measured and compared in serum HDLC level and oxidized LDL level, the two most effective factors of coronary artery disease. The subjects in A group showed the lower percentages of body fat and WHR, when compared with the ones in S group. The body mass and lean body mass of A group subjects were higher than those of S group subjects. The serum HDL-C level$(58.6\pm12.7mg/mL)$ was significantly higher for A than S group subjects.(p<0.05) The sem ox-LDL level $(6.64\pm4.11Eu/mL)$ for A group subjects was lower than S group ones. The fat mass showed significantly positive correlations with atherogenic index(AI)(r=0.301, p<0.05), and with blood glucose levels(r=0.334, p<0.05). Also the WHR whowed significantly positive correlations with LDL-C levels(r=0.277, p<0.05), and with AI(r=0.466, p<0.01). In summary, the subjects in A group have the lower percentages of body fat and WHR, when compared with the ones in S group. Also, A group subject showed a tendency that exercise enhances serum HDL-C levels and decreases oxidized LDL levels. And aerobic exercise showed positive results which change body composition and improve blood lipid levels. There were significantly positive correlations among the percentages of body fat At and blood glucose level. These results suggest that moderately intensive exercise is a significant factor in reducing coronary artery disease.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.199-214
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• 2007

Recently, there have been a lot of works trying to realize automated composition of semantic web services though application of AI planning techniques. The traditional AI planning techniques, however, have some limitations: it is not easy to represent a web service process with complex control constructs as an action or a plan; it is hardly possible to consider enough the rich information contained in domain ontologies during the planning process; it is impossible to model directly the data flow from the outputs of a web service to the inputs of another web service; it is difficult to predict and deal with uncertainty and dynamics of the environment because the plan generation phase is supposed to be separated from the plan execution phase. In order to overcome some of these limitations, this paper suggests a reactive planning approach to automated composition of semantic web services. Through some experiments using several e-commerce web services, we found that the reactive planning is an effective way to realize automated composition of semantic web services.