• Korean Journal of Materials Research
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• v.4 no.2
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• pp.177-186
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• 1994

The effect of solidification condition and vibration on structure refinement was investigatedfor unidirectionally solidified $AI-CuAI_{2}$ eutectic composites. Eutectic composites were unidirectionally solidifiedunder vibration with variation of growth rates (R) and thermal gradient((G), $32^{\circ}C$/cm, and 35$^{\circ}C$/cm. The lamellar structure was varied according to growth condition(G/R ratio). For the structure refinementthe effect of G/R was found out to be greater rather than that of vibration. The interlamellarspacing(l) in this materials was varied with the growth rates(R) by "$\lambda^{2}R$=Constant" relationshipquot; relationship

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.92-101
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• 2018

As the interactive AI speaker becomes popular, voice recognition is regarded as an important vehicle-driver interaction method in case of autonomous driving situation. The purpose of this study is to confirm whether multimodal interaction in which feedback is transmitted by auditory and visual mode of AI characters on screen is more effective in user experience optimization than auditory mode only. We performed the interaction tasks for the music selection and adjustment through the AI speaker while driving to the experiment participant and measured the information and system quality, presence, the perceived usefulness and ease of use, and the continuance intention. As a result of analysis, the multimodal effect of visual characters was not shown in most user experience factors, and the effect was not shown in the intention of continuous use. Rather, it was found that auditory single mode was more effective than multimodal in information quality factor. In the semi-autonomous driving stage, which requires driver 's cognitive effort, multimodal interaction is not effective in optimizing user experience as compared to single mode interaction.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.95-111
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• 2021

Despite the innovation of AI and Big Data, theoretical research bout the effect of AI and Big Data on market competition is still in early stages; therefore, this paper analyzes the effect of AI, Big Data, and data sharing on an entry firm by using game theory. In detail, the firms' business environments are divided into internal and external ones. Then, AI algorithms are divided into algorithms for (1) customer marketing, (2) cost reduction without automation, and (3) cost reduction with automation. Big Data is also divided into external and internal data. this study shows that the sharing of external data does not affect the incumbent firm's algorithms for consumer marketing while lessening the entry firm's entry barrier. Improving the incumbent firm's algorithms for cost reduction (with and without automation) and external data can be an entry barrier for the entry firm. These findings can be helpful (1) to analyze the effect of AI, Big Data, and data sharing on market structure, market competition, and firm behaviors and (2) to design policy for AI and Big Data.

• Korean Journal of Animal Reproduction
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• v.25 no.3
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• pp.227-230
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• 2001

To know and apply the factors affecting calf's gender may increase our competitiveness of Hanwoo industry. Thus, this study was carried out to analyse the effect of expected factors on calf's gender and to make an alternative idea for desired calf's gender. Gender of calves born by AI was not affected by AI year and cow parity, but significantly affected by sire and farm. Therefore, to obtain calves' gender that we want, both selecting optimum sire for AI and providing optimum feeding environment for cow should be required.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1996.10a
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• pp.113-121
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• 1996

AI7075 alloy has been used for aircraft components since it has the advantage of high strength, high toughness, and high corrosion resistance. Many airframe components consist of various combinations of rib-web structure. In this study, various process paramenters such as die design, lubricant, ram speed, forging temperature have been investigated using the experiment and F.E.M. simulation to develop the precision forging technology for AI7075. When lubricant is applied to both material and die, shear friction factor is 0.1 which shows best effect of lubricant. It is specific corner radius of die that minimized forging load regarding process conditions, especially according to the ratio of the width of rib and web. In conclusion, optimum corner radius is 2~3mm when the width of rib and web is 3mm and 20mm respectively.

• Korean Journal of Childcare and Education
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• v.19 no.2
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• pp.61-85
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• 2023

Objective: This study aims to investigate whether science teaching attitude of early childhood teachers mediates the relationship between the professional learning environment of institutions and their intention to accept artificial intelligence (AI) technology, and whether the experience of using smart and digital devices moderates the effect of science teaching attitude. Methods: An online survey was conducted targeting 118 teachers with more than 1 year of experience in kindergarten and day care center settings. Descriptive statistical analysis, correlation analysis, and The Process macro model 4, 14 were performed using SPSS 27.0 and The Process macro 3.5. Results: First, the science teaching attitude of early childhood teachers served as a mediator between the professional learning environment of institutions and teachers' intention to accept AI technology. Second, the experience of using smart and digital devices was found to moderate the effect of teachers' science teaching attitude on their intention to accept AI technology. Conclusion/Implications: This results showed that an institutional environment that supports teachers' professionalism development and provides rich experience is crucial for promoting teachers' active acceptance of AI technology. The findings highlight the importance of creating a supportive institutional envionment for teacher's professional growth, enhancing science teaching attitudes, and facilitating the use of various devices.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.471-481
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• 2021

The purpose of this study is to analyze the effectiveness of AI convergence education program. To this end, the "Elementary Science AI Convergence Education Program for Machine Learning" developed in previous research were taught to elementary school students in the fourth to sixth grades in eight times. The quantitative changes of each factor were analyzed by R program, and the effectiveness of education was analyzed by Pearson correlation and paired samples t-test. As a result, there is a deep correlation between "Attitude to AI technology, Scientific preference and STEAM Literacy" and technical average has improved in many factors. Therefore, AI convergence education program is meaningful in terms of education, and if AI education and AI convergence education are implemented into the primary formal education curriculum, they will have a positive effect.

• Animal cells and systems
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• v.7 no.1
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• pp.69-73
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• 2003

Serum lipid and lipoprotein levels are influenced by genetic factors, and exorcise increases the concentrations of cardio-protective parameters such as high-density lipoprotein cholesterol (HDL-cholesterol) and apolipoproteinAI (apoAI) in human serum. In the present study, we tested the effect of adaptation to endurance exercise on the association of a genetic polymorphism (Pst 1 RFLP) in the apoAI gene with these biochemical parameters. The genotype and allele frequencies for the Pst 1 RFLP were not significantly different between the elite athletes and sedentary controls (P>0.05). There were also no significant associations between the Pst 1 RFLP of the apoAI gene and the biochemical parameters in elite athletic group. Thus, our results suggest that the Pst 1 RFLP of the apoAI gene was not significantly associated with the serum apoAI and HDL-cholesterol concentrations as well as athletic performance in Koreans.

• Knowledge Management Research
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• v.21 no.1
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• pp.175-195
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• 2020

The development of platform service based on the information and communication technology has revolutionized patterns of commercial transactions, driving the growth of global economy. Furthermore, the radical advancement of artificial intelligence(AI) presents the huge potential to innovate almost all the industrial and economic activities. Given these technological developments, the goal of this paper is to investigate AI's impact on the platform service innovation as well as its influence on the business performance. For the goal, this paper presents the review of the types of service innovation, the nature of platform services, and technological characteristics of leading AI technologies, such as chatbot and recommendation system. As an empirical study, this paper performs a multiple case study of Kakao Group which is the leading mobile platform service with the most advanced AI in Korea. To understand the role and effect of AI on Kakao platform service, this study investigated three cases, including chatbot agent of Kakao Bank, Smart Call service of Kakao Taxi, and music recommendation system of Kakao Mellon. The analysis results of the case study show that AI initiated innovations in platform service concepts, service delivery, and customer interface, all of which lead to a significant decrease in the transaction costs and the personalization of services. Finally, for the successful development of AI, this research emphasizes the significance of the accumulation of customer and operational data, the AI human capital, and the design of R&D organization.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.779-790
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• 2021

This study analyzed the effect of AI maker coding education on improving students' computational thinking. The subjects of the study were 10 students at H Elementary School in Ansan, and a total of 8 AI maker coding education using the Instructional Model for Maker Education based on SW Coding was applied to students to find out the degree of improvement of computational thinking. Students who participated in the class performed a process of solving real-life problems through coding and making activities, measured the degree of improvement in computing thinking before and after education through a computing thinking test paper, and observed students' thinking processes related to computing thinking components through interviews. As a result, it was confirmed that the average score of all students' computational thinking skills was improved, and the deviation of scores between students decreased. Through the interview, it was found that students actively utilize their thinking skills related to computational thinking skills in the problem-solving process. Through this, it was confirmed that AI maker coding education can have a positive effect on improving students' computing thinking skills.