• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.33-41
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• 2024

The continuous rise in the number of multicultural households and the issue of insufficient Korean language proficiency among marriage immigrants have highlighted the need to expand support programs for multicultural families and the importance of staffing multicultural centers. This paper designs and implements a diary application that leverages AI technology to enhance communication between parents and children in multicultural families based on diary entries. The proposed technology uses OCR, machine translation, Korean language correction, and sentiment analysis AI models to facilitate diary-based conversations between parents and children, addressing linguistic barriers and fostering emotional bonds. Additionally, it aims to provide direction for the development and harmony of future multicultural societies.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.613-625
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• 2024

This study analyzed the convergence case of AI painting and NFT art, art content created based on digital technology, an innovative technology of the 4th industrial technology, and explored its characteristics. Digital technology that innovates the paradigm of life in the 21st century is being used in creative art, and AI painting and NFT art that use it as an expression tool are changing the way they perceive and accept art. AI painting using big data and artificial intelligence technology is evolving into interactive daily art, and NFT art using blockchain and NFT technology is becoming the art of the metaverse with economic and cultural values. Therefore, this study attempted to explore various aspects and values of these digital convergence arts. For the study, representative examples of AI painting and NFT art were classified into cognitive creative AI painting and language generative AI, art economic NFTs, and art and cultural NFTs, and their characteristics, contents, and meanings were analyzed. It is hoped that the results of this study will contribute to the development of AI painting and NFT art, which are digital convergence arts.

• Herbal Formula Science
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• v.32 no.2
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• pp.141-153
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• 2024

Objective : Ephedrae Herba (Ephedra) has been frequently used in the East Asian traditional medicine including Korea, China and Japan in the clinical treatment of asthma, cold and influenza etc. This study was performed to explore an anti-fibrogenic potential of Ephedra Herba water extract (EHE) using immortalized human hepatic stellate cell line, LX-2 cells. Methods : We examined the anti-fibrogenic effects of EHE on canonical pathway of transforming growth factor-β1 (TGF-β1) signaling in LX-2 cells. Cell viability was measured using the MTT assay. mRNA levels were detected by real-time PCR. Proteins expression were detected by Western blot. Results : Treatment of EHE 30 ㎍/ml did not show any cytotoxicity on LX-2 cells. Pre-treatment of EHE (30 ㎍/mL) significantly inhibited α-smooth muscle actin expression induced by TGF-β1. Additionally, EHE significantly decreased Smad2 and Smad3 phosphorylations, Smad binding element-driven luciferase activity and plasminogen activator inhibitor type 1 expression by TGF-β1. Furthermore, increases of matrix metalloproteinases 2 genes by TGF-β1 was also attenuated by EHE treatment. Conclusion : These results suggest that EHE has an ability to suppress fibrogenic process in activated HSC via inhibition of TGF-β1-TGFBR mediated canonical (Smad dependent) pathway.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.513-520
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• 2024

This study investigates the changes in teachers' roles as the impact of AI on school education expands. Traditionally, teachers have been responsible for core aspects of classroom instruction, curriculum development, assessment, and feedback. AI can automate these processes, particularly enhancing efficiency through personalized learning. AI also supports complex classroom management tasks such as student tracking, behavior detection, and group activity analysis using integrated camera and microphone systems. However, AI struggles to automate aspects of counseling and interpersonal communication, which are crucial in student life guidance. While direct conversational replacement by AI is challenging, AI can assist teachers by providing data-driven insights and pre-conversation resources. Key competencies required for teachers in the AI era include expertise in advanced instructional methods, dataset analysis, personalized learning facilitation, student and parent counseling, and AI digital literacy. Teachers should collaborate with AI to emphasize creativity, adjust personalized learning paths based on AI-generated datasets, and focus on areas less amenable to AI automation, such as individualized learning and counseling. Essential skills include AI digital literacy and proficiency in understanding and managing student data.

• Information Systems Review
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• v.26 no.1
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• pp.119-149
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• 2024

This study investigates the antecedents and mechanisms influencing trust and behavioral intentions formation towards new AI chatbots, such as ChatGPT, as travel information searching services. Analyzing the roles of variables such as familiarity, novelty, personal innovativeness, information quality and perceived anthropomorphism, the research elucidates the impact of these factors on users' cognitive and affective trust, ultimately affecting their intention to adopt information and sustain the use of the AI chatbot. Results indicate that perceived familiarity and information quality positively influence both cognitive and affective trust, whereas perceived novelty contributes positively only to cognitive trust. Additionally, the personal innovativeness of new AI chatbot users was found to weaken the effect of familiarity on perceived trust, while the perceived level of anthropomorphism of the chatbot amplified the effects of novelty and familiarity on cognitive trust. These findings underscore the importance of considering factors such as familiarity, personal innovativeness, information quality and anthropomorphism in the design and implementation of AI chatbots, affecting trust and behavioral intention.

• Journal of Korean Society for Quality Management
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• v.52 no.3
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• pp.459-478
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• 2024

Purpose: This study aims to identify protective factors enabling emotional workers to manage stress and cope proactively. By enhancing their internal resources, it aims to provide a theoretical foundation for fostering positive outcomes and offering a basis for integrated human resource management and employee welfare. Methods: The data analysis utilized SPSS 22.0 and Smart PLS 4.0. After conducting tests for normality, exploratory factor analysis, confirmatory factor analysis, reliability analysis, measurement model validation, and structural model validation were performed. Relationships between variables were examined, and the significance and suitability of hypothesis paths were verified. Results: Firstly, it was confirmed that self-compassion and positive self-talk positively influence resilience, self-control, work engagement and subjective well-being. Secondly, resilience positively influences self-control, work engagement and subjective well-being. Thirdly, self-control positively influences work engagement but does not statistically significantly influence subjective well-being. Fourthly, work engagement positively influences subjective well-being. Fifthly, work engagement was found to mediate between self-control and subjective well-being. Conclusion: The study confirmed that self-compassion and positive self-talk serve as antecedents to enhancing emotional workers' resilience, self-control, work engagement, and subjective well-being. Additionally, by analyzing the structural relationships between these factors, it established a theoretical framework.

• The Transactions of the Korea Information Processing Society
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• v.13 no.10
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• pp.529-536
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• 2024

Recent advancements in AI technology have led to its application across various fields. However, the lack of transparency in AI operations makes it challenging to guarantee the quality of its outputs. Therefore, we integrate requirements engineering in software engineering with conversational AI technology to ensure procedural fairness. Traditional requirements engineering research uses grammar-centered analysis, which often fails to fully interpret the semantic aspects of natural language. To solve this, we suggest combining Noam Chomsky's syntactic structure analysis with Charles Fillmore's semantic role theory. Additionally, we extend our previous research by analyzing adjectives in informal requirement sentence structures. This enables precise emotional analysis of the main characters in comics. Based on the results of the analysis, we apply the emotional states of the objects to the states in the UML state diagram. Then, we create the 3D object with Three.js based on the object that reflects the emotional states in the state diagram. With this approach, we expect to represent the emotional state of a 3D object.

• Journal of Biosystems Engineering
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• v.16 no.4
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• pp.384-398
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• 1991

A computer program was developed to select the optimum size of farm machine and analyze its operation costs according to various farming conditions. It was written in FORTRAN 77 and BASIC languages and can be run on any personal computer having Korean Standard Complete Type and Korean Language Code. The program was developed as a user-friendly type so that users can carry out easily the costs analysis for the whole farm work or respective operation in rice production, and for plowing, rotarying and pest controlling in upland. The program can analyze simultaneously three different machines in plowing & rotarying and two machines in transplanting, pest controlling and harvesting operations. The input data are the sizes of arable lands, possible working days and number of laborers during the opimum working period, and custom rates varying depending on regions and individual farming conditions. We can find out the results such as the selected optimum combination farm machines, the overs and shorts of working days relative to the planned working period, capacities of the machines, break-even points by custom rate, fixed costs for a month, and utilization costs in a hectare.

• Journal of dental hygiene science
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• v.12 no.2
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• pp.131-137
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• 2012

The purpose of this study was to examine the sociopsychological stress of dental hygiene students, any possible gaps among them according to their general characteristics and the most influential factor for their stress. The subjects in this study were the dental hygiene students who were selected by convenience sampling from three different colleges. After a survey was conducted for about a month between March and April, 2011, the answer sheets from 561 students were analyzed. As for the sociopsychological stress of the dental hygiene students, economic stress was the heaviest sociopsychological stress that the students suffered(3.17). Regarding differences in each stressor according to general characteristics, they were more stressed out about their economy, families, interpersonal relationships and studies when they had a less conversation with their families. And they had more stress about their economy, families, interpersonal relationships and studies when they found themselves to be more unhealthy. The gaps between them and the others were statistically significant. As a result of analyzing the influential factors for their stress, they had more stress when they had a less conversation with their families(p<0.001) and when they found themselves not to be in good health(p<0.001). It's required to seek ways for dental hygiene students to cope with their stress properly, and the development of stress management programs is necessary. Besides, education and training should be provided for them to regulate their own stress successfully.

• Journal of the Korean Chemical Society
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• v.50 no.6
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• pp.494-505
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• 2006

This study was performed for 7th grade students to analyze by leader style, the verbal interactions between students in a small group in an MBL(Microcomputer-Based Laboratory) experiment class. The study was performed after arranging the students into four kinds of groups, including groups with leaders of inclusive, persuasive, and alienating styles and a group with no clear leader. The analysis of total frequencies of verbal interaction revealed that the group with an inclusive leader showed the highest frequency of verbal interaction, followed by the group with a persuasive leader, an alienating leader and lastly, the group with no clear leader. The group with an inclusive leader showed the highest frequency of interaction from a cognitive aspect related to question(Q), response(R), making suggestion(MS), and receiving opinions(RO), while interactions from an affective aspect related to behavioral participation(BP) and students' attitudes(SA) were observed more often in a group including an alienating leader than in any other group. An analysis of characteristics of verbal interaction according to leader style showed that a group with an inclusive leader had a permissive atmosphere. It also showed that all members of the group actively participated in discussion and they had a sense of belonging and self-pride with their group. In a group with a persuasive leader, the leader took the lead of most experimental and discussion activities and he was rarely challenged by other students in the group. Rather, other group members showed a tendency to depend on their leader. In a group with an alienating leader, the relationship between leader and members of the group was not harmonious and unfiltered expressions of dissatisfaction and ignorance often took place. The leader's lack of concern about members' low achievement became an obstacle in active discussion. In a group with no clear leader, most interactions during discussion were short and simple. Many answers to the question given by their members were not clear and the interactions were sometimes interrupted for a short while.