• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.9-17
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• 2022

To take into account of the increasing speed of next generation high-speed trains, a new design code for the traffic safety of railway bridges is required. To solve dynamic responses of the bridge, this research offers a numerical analyses of PSC (Pre-stressed Concrete) box girder bridge, which is most representative of all the bridges on Gyungbu high-speed train line. This model takes into account of the inertial mass forces by the 38-degree-of-freedom and interaction forces as well as track irregularities. Our numerical analyses analyze the maximum vertical deflection and DAF (Dynamic Amplification Factor) between simple span and two-span continuous bridges to show the dynamic stability of the bridge. The third-order polynomial regression equations we use predict the maximum vertical deflections depending on varying running speeds of the train. We also compare the vertical deflections at several cross-sectional positions to check the influence of running speeds and the maximum irregularity at a longitudinal level. Moreover, our model analyzes the influence lines of vertical deflection accelerations of the bridge to evaluate traffic safety.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.185-200
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• 2022

The innovative development of museum cultural products is an important way for museums to play the function of cultural communication with their collections. In the context of consumer upgrading, traditional cultural product design and sales methods gradually fail to meet the diverse needs of consumers. This study aims to propose the construction of a customized interactive experience platform for museum cultural products, promote the development of museum cultural products, and facilitate the inheritance and preservation of museum culture. The research methodology analyzes the model and characteristics of existing cultural product customization platforms by collating existing literature studies, and distributes 159 questionnaires to investigate the needs of cultural product consumers, and finally combines the customization experience with existing e-tailing platform systems according to user needs, proposes a theoretical framework and conducts design practice and usability testing using the Shenyang Palace Museum as an example. The findings show that users have a high acceptance of the customized platform for cultural products and that the design of the customized platform can be used to promote the dissemination of the cultural connotations of museums, optimize the personalized user experience of cultural products, and provide new ideas for the development, design, and retailing of museum cultural products. Based on the above findings, this paper suggests that museums' cultural product development can utilize the design model of customized platforms to further enhance consumers' personalized service experience.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.119-137
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• 2022

Recent recommendation system studies apply various deep learning models to represent user and item interactions better. One of the noteworthy studies is ONCF(Outer product-based Neural Collaborative Filtering) which builds a two-dimensional interaction map via outer product and employs CNN (Convolutional Neural Networks) to learn high-order correlations from the map. However, ONCF has limitations in recommendation performance due to the problems with CNN and the absence of side information. ONCF using CNN has an inductive bias problem that causes poor performances for data with a distribution that does not appear in the training data. This paper proposes to employ a Vision Transformer (ViT) instead of the vanilla CNN used in ONCF. The reason is that ViT showed better results than state-of-the-art CNN in many image classification cases. In addition, we propose a new architecture to reflect side information that ONCF did not consider. Unlike previous studies that reflect side information in a neural network using simple input combination methods, this study uses an independent auxiliary classifier to reflect side information more effectively in the recommender system. ONCF used a single latent vector for user and item, but in this study, a channel is constructed using multiple vectors to enable the model to learn more diverse expressions and to obtain an ensemble effect. The experiments showed our deep learning model improved performance in recommendation compared to ONCF.

• Korean Journal of School Psychology
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• v.18 no.1
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• pp.31-48
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• 2021

The purpose of this study was to determine whether the retention of university freshmen could be predicted using their peer relationships in a specific department. In this study, retention was defined as a student staying enrolled in their university for a certain period of time. Social relationships are formed through interaction between people, so both students' self-perceptions and others' perceptions of them must be accounted for, so we used a social network analysis that did so. We examined social networks visualizations that allowed for a rich interpretation of numerical information. Participants in this study were freshmen who enrolled in an undergraduate program in 2017, 2018, or 2019. We used the name generator method to determine how quantitative friendship network variables predicted the academic retention up to the first semester of 2020. Cox proportional hazard model analysis showed that the weighted indegree centrality with intimacy positively predicted retention. The results of this study can be used to identify and conduct interventions for students who may be likely to disenroll. However all of the students did not participate in the department, it was difficult to examine their entire peer networks. Thus, this study's results cannot be generalized because the participants are students of a specific major, so further research is needed to produce more generalizable results.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• The Korean Journal of Franchise Management
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• v.13 no.1
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• pp.47-57
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• 2022

Purpose: Recently, it is common to see cases where an amount similar to the cost of a meal is spent on dessert, or an amount greater than the cost of a meal is spent on dessert. The generation MZ is showing a tendency of 'value consumption' by consuming values and beliefs in consideration of the recent impact on society and the environment. Therefore, this study aims to analyze the effect of dessert cafe quality and eco-friendly behavior on customer trust and loyalty targeting the generation MZ who have visited desert cafés. This study examined the mediating role of customer trust in the relationships between desert café quality, eco-friendly behavior and customer loyalty, and also the moderating effect of and eco-friendly behavior on customer trust and customer loyalty. Research design, data, and methodology: To achieve purposes of this study, 229 data were collected from respondents who visited desert café and analyzed using measurement model (reliability test and correlation analysis), Fornell-Larcker Criterion and Heterotrait-Monotrait Ratio (HTMT) assessment, and structural equation model (PLS-SEM) with SPSS 22.0 and SmartPLS 3.3.7. Results: The research results are as follows. First, desert cafes' quality positively influenced customer trust but did not customer loyalty. Second, desert cafes' eco-friendly behavior positively influenced customer trust and customer loyalty. Fourth, the interaction term of dessert cafe quality and eco-friendly behavior did not influence customer trust and customer loyalty. Conclusions: This study emphasized the necessity of service quality and eco-friendly behavior of dessert cafes by examining the relationship between the quality of dessert cafes and eco-friendly behaviors, customer trust and loyalty. It also found the importance of the role of trust in securing loyal customers. In order to secure and retain loyal customers, the owners of dessert cafes should make effortsto improve the quality of the cafes' products and services so that customers can feel a sense of trust, and actively publicize that they are practicing eco-friendly management. As a result of this study, it is intended to provide practical implications for the management of dessert cafes by understand ing the effects of product and service quality and eco-friendly behaviors of companies to bakery industry workers and start-ups.

• Journal of Korean Elementary Science Education
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• v.41 no.2
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• pp.373-394
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• 2022

This study aimed to find out the formation of ecologically educational place identity of nature trails in national parks, which elementary school students to adults can understand, by analyzing the connectivity between characteristics (signs) of nature trails and elementary science environment-related key concepts and the domain of ecological education in the course of environment and by developing a semiotic interpretation model of place identity based on Barthes's semiotic theory. When analyzing correlations between the interpretation board-focused surrounding environment of nature trails and the content system of ecological education, this study found out that it showed the highest connectivity with the domain of 'System of Ecological Environment'. When analyzing the formation of place identity of nature trails in terms of semiotics, this study discovered that geographical locations or landscapes, artificial environments and physical elements as characteristics of surrounding environments mostly acted on the formation of placeness. Besides, it was found that both knowledge and attachment elements equally could act on the formation of a sense of place. Being likely to develop through interaction between placeness and a sense of place, place identity was mostly composed of behavioral internal stages and sympathetic internal stages. To diversify the formation of place identity, however, this study found it necessary to develop environment education projects and create surrounding environments and interpretation boards with the environmental uniqueness of nature trails reflected much more.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.9-31
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• 2023

This study is a study on the different cognitive systems and different knowledge systems of members participating in complex and diverse consulting projects, and it is a study on team collaboration that affects the team performance of the project. The purpose of this study is to analyze the mediating effects of team shared cognition, team transactive memory, team knowledge integration, and team efficacy in the cognitive interaction process of a consulting project. This study established a research model and research hypothesis based on previous studies. Data were collected from consultants who actually participated in the consulting project. To empirically analyze the research hypothesis, demographic analysis, validity and reliability analysis, structural model analysis for hypothesis verification, and mediating effect analysis using phantom variables were performed. As a result of the study, in order to increase team performance, it is necessary to improve team shared cognition and team transactive memory, which are cognitive systems, and team knowledge integration, which is a knowledge system, must also be improved. Therefore, there is a need for a sense of team efficacy that integrates disparate cognitive and knowledge systems, trusts each other's expertise, and enables successful team work. In addition, future studies on sub-factors of cognitive processes are needed.

• Journal of Ginseng Research
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• v.47 no.2
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• pp.302-310
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• 2023

Background: The most common type of dementia, Alzheimer's disease (AD), is marked by the formation of extracellular amyloid beta (Aβ) plaques. The impairments of axons and synapses appear in the process of Aβ plaques formation, and this damage could cause neurodegeneration. We previously reported that non-saponin fraction with rich polysaccharide (NFP) from Korean Red Ginseng (KRG) showed neuroprotective effects in AD. However, precise molecular mechanism of the therapeutic effects of NFP from KRG in AD still remains elusive. Methods: To investigate the therapeutic mechanisms of NFP from KRG on AD, we conducted proteomic analysis for frontal cortex from vehicle-treated wild-type, vehicle-treated 5XFAD mice, and NFP-treated 5XFAD mice by using nano-LC-ESI-MS/MS. Metabolic network analysis was additionally performed as the effects of NFP appeared to be associated with metabolism according to the proteome analysis. Results: Starting from 5,470 proteins, 2,636 proteins were selected for hierarchical clustering analysis, and finally 111 proteins were further selected for protein-protein interaction network analysis. A series of these analyses revealed that proteins associated with synapse and mitochondria might be linked to the therapeutic mechanism of NFP. Subsequent metabolic network analysis via genome-scale metabolic models that represent the three mouse groups showed that there were significant changes in metabolic fluxes of mitochondrial carnitine shuttle pathway and mitochondrial beta-oxidation of polyunsaturated fatty acids. Conclusion: Our results suggested that the therapeutic effects of NFP on AD were associated with synaptic- and mitochondrial-related pathways, and they provided targets for further rigorous studies on precise understanding of the molecular mechanism of NFP.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.13-25
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• 2019

Since reaching the top in the Billboard Main Album Chart 'Billboard 200' with Love Yourself: Tear in May of 2018, BTS once again took first place after just three months in the 'Billboard 200'(September 3, 2018) with the repackaged album Love Yourself: Answer. It opened the doors to the 'Hallyu 4.0' by conquering the main Billboard Chart with a song sung in Korean. BTS rose to the top on the 'Billboard 200' twice, thus being recognized globally for their musical talent(song, dance, promotion, etc.), and took their place in the mainstream music market of the world. BTS moved away from intuitive interaction such as mysticism, abnormality, irregularity, etc. but instead created their own world(BTS Universe) with fans around the world through two-directional communication such as consensus, sharing and co-existence. They are recognized as artists that went beyond being an idol group that simply released a few hit songs that had now elevated popular music to a new form of art. In result, they retained a highly loyal global fan base(A.R.M.Y.) and they are continuously creating good influence with them. This study analyzed the success factors of BTS using the S-M-C-R-E model as follows. ① Sender: BTS'7-person 7-colors fantasy and 'All-in-one storytelling' strategy of producer Bang Shi-hyuk ② Message: Create global consensus of 'you' rather than 'me' ③ Channel: Created real-time common grounds with global fans through social network platforms such as Youtube, Facebook and Instagram ④ Receiver: Formed highly loyal global fandom(A.R.M.Y.) that extends outside of Korea and Asia ⑤ Effect: Created additional economic value and spread good influence