• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.745-752
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• 2009

Management of social infrastructure has been advanced from facility management (FM) to asset management (AM), which adopts the aggressive and proactive methods in predicting the deterioration of infrastructure, prevents failures, and eventually saves maintenance cost. Infrastructure asset management is not a simple engineering technique, but it is a new paradigm evolved from facility management practices. To implement the infrastructure asset management successfully, organizational reform is very important. This paper suggests critical success factors and key performance indicators to implement the infrastructure asset management for facility managers of government owned social infrastructures such as roads and bridges. Reorganizing the facility management group requires new vision, objectives, strategies for the paradigm-changing asset management. This paper uses Balanced Score Card (BSC) which is a proven method in measuring and setting new objectives for an organization. Once the performance indicators are reviewed repeatedly by facility managers through experts workshops, developed BSC can be used in practice. This paper discusses the development of robust BSC scoring method through in depth literature reviews and investigation of asset management practices of domestic and international cases.

• Information Systems Review
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• v.25 no.4
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• pp.89-112
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• 2023

In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.1-12
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• 2024

In this paper, we fine-tuned KoAlpaca, a large-scale Korean language model, and implemented a blog text generation system utilizing it. Blogs on social media platforms are widely used as a marketing tool for businesses. We constructed training data of positive reviews through emotion analysis and refinement of collected sponsored blog texts and applied QLoRA for the lightweight training of KoAlpaca. QLoRA is a fine-tuning approach that significantly reduces the memory usage required for training, with experiments in an environment with a parameter size of 12.8B showing up to a 58.8% decrease in memory usage compared to LoRA. To evaluate the generative performance of the fine-tuned model, texts generated from 100 inputs not included in the training data produced on average more than twice the number of words compared to the pre-trained model, with texts of positive sentiment also appearing more than twice as often. In a survey conducted for qualitative evaluation of generative performance, responses indicated that the fine-tuned model's generated outputs were more relevant to the given topics on average 77.5% of the time. This demonstrates that the positive review generation language model for sponsored content in this paper can enhance the efficiency of time management for content creation and ensure consistent marketing effects. However, to reduce the generation of content that deviates from the category of positive reviews due to elements of the pre-trained model, we plan to proceed with fine-tuning using the augmentation of training data.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Journal of Physiology & Pathology in Korean Medicine
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• v.28 no.5
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• pp.548-557
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• 2014

The purpose of this study was to understand how vegetarian diets in Taiwanese hospitals are well established and provide suggestion for successful implementation in Korea. Micro-ethnographic case study with in-depth interviews, field observations, and paper reviews were used for this study. Experiences of doctors and nutritionists from Taiwanese hospitals where deliver vegetarian hospital diets were analyzed. This research found out Taiwanese life respect culture has influence on introducing vegetarian diets in hospital, besides most Participants agreed to use vegetarian diets for the medical purpose according to their clinic experiences and research results. Meanwhile there is no restriction to compel patients to keep vegetarian diets. All participants answered food has a large effect on the human body and further study on vegetarian diets' efficacy is required. The hospital chief's decision making is crucial to introduce vegetarian diets in hospitals. For the bigger picture, social supports, organizational supports and national policy supports are all important factors for it. The implications and recommendations for Korean hospitals were discussed. The public awareness for vegetarian diet for medical purpose along with research on its efficacy would be needed. In order to make good use of a vegetarian diet for medical purposes, we first need to build a vegetarian-friendly environment, go deep into the study of a diet's effects using diverse methodologies, and combine the diet with traditional medicine theory. Based on the results of this primary study, more related studies should be carried out in the future.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.224-233
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• 2008

This study is planned and designed to develop an education program for students majoring health care in order to improve their knowledge and attitudes of ethics and service. First, this study examine the educational needs of 505 students majoring health care and 175 field workers through literature reviews, survey of questionnaire, and opinions of experts. And then, the educational goals, contents, methods are selected and established in this study. Lastly, the effects of the ethics and service education program shown by their knowledge and attitudes are examined. In the effect analyses, we can see there is meaningful difference in average variation of knowledge level in before and after the education, and also find that average scores after education was higher than before education in the field of intrinsic, social, and altruistic compensations. We can conclude that the developed education program in this study, has an effect on increasing a standard of value of the students participated in the program.

• Management & Information Systems Review
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• v.30 no.3
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• pp.85-105
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• 2011

The primary purpose of this study is to examine the effects of privacy concern on user's satisfaction and continuance intention in SNS. Based on relevant literature reviews, this study posits five characteristics, that is, privacy concern, perceived usefulness, perceived enjoyment, satisfaction, and continuance intention as key factors. And then we structured a research model and hypotheses about relationship between these variables. A total 298 usable survey responses of SNS users have been employed in the analysis. The major findings from the data analyses are as follows. Firstly, privacy concern had a significant influence upon perceived usefulness and enjoyment, however, privacy concern had not a significant influence upon satisfaction Secondly, perceived usefulness and enjoyment had a positive influence upon satisfaction. Lastly, user's perceived usefulness, perceived enjoyment, and satisfaction had significantly related to continuance intention in SNS. From this study, we expect to suggest practical and managerial implications to SNS providers.

• International Commerce and Information Review
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• v.18 no.3
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• pp.227-248
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• 2016

World aviation market has been expanded every year caused by improvement of economic level quality of individual life, increase of the development of tourist industry. Aviation companies have compete to develpe the service program for the maintaining of sustainable choice by customer and develop the market share. This study aims to suggest customer service strategy which is based on the relations between satisfaction by providing a differentiated service quality. This paper is focusing on the investigation with the mediating role of commitments on customer satisfaction in Aviation company. For this purpose, we do literature reviews, develop research model and conduct an empirical research. The literature review covers theoretical discussion on customer satisfaction and core variables for hypothesis setting. This analysis shows the airline service factors have a positive effect on the customers' satisfaction and re-choice intention. And it is necessary to improve airlines' systematic management and strategic development on airline service factors for better airlines' customer service.

• Research in Community and Public Health Nursing
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• v.28 no.4
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• pp.513-523
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• 2017

Purpose: We evaluated the psychometric properties of a questionnaire on the acceptance of the quality improvement information system (QIIS) among long-term care workers (mostly nurses). Methods: The questionnaire composes of 21 preliminary questions with 5 domains based on the Technology Acceptance Model and related literature reviews. We developed a prototype web-based comprehensive resident assessment system, and collected data from 126 subjects at 75 long-term care facilities and hospitals, who used the system and responded to the questionnaire. A priori factor structure was developed using an exploratory factor analysis and validated by a confirmatory factor analysis; its reliability was also evaluated. Results: A total of 16 items were yielded, and 5 factors were extracted from the explanatory factor analysis: Usage Intention, Perceived Usefulness, Perceived Ease of Use, Social Influence, and Innovative Characteristics. The five-factor structure model had a good fit (Tucker-Lewis index [TLI]=.976; comparative fit index [CFI]=.969; standardized root mean squared residual [SRMR]=.052; root mean square error of approximation [RMSEA]=.048), and the items were internally consistent(Cronbach's ${\alpha}=.91$). Conclusion: The questionnaire was valid and reliable to measure the technology acceptance of QIIS among long-term care workers, using the prototype.

• Journal of Korean Academy of Nursing
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• v.47 no.2
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• pp.242-256
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• 2017

Purpose: This study was done to clarify attributes, antecedents, and consequences of spirituality. Methods: Rodgers's evolutionary concept analysis was used to analyze fifty seven studies from the literature related to spirituality as it appears in systematic literature reviews of theology, medicine, counseling & psychology, social welfare, and nursing. Results: Spirituality was found to consist of two dimensions and eight attributes: 1) vertical dimension: 'intimacy and connectedness with God' and 'holy life and belief', 2) horizontal dimension: 'self-transcendence', 'meaning and purpose in life', 'self-integration', and 'self-creativity' in relationship with self, 'connectedness' and 'trust' in relationship with others neighbors nature. Antecedents of spirituality were socio-demographic, religious, psychological, and health related characteristics. Consequences of spirituality were positive and negative. Being positive included 'life centered on God' in vertical dimension, and among horizontal dimension 'joy', 'hope', 'wellness', 'inner peace', and 'self-actualization' in relationship with self, 'doing in love' and 'extended life toward neighbors and the world' in relationship with others neighbors nature. Being negative was defined as having 'guilt', 'inner conflict', 'loneliness', and 'spiritual distress'. Facilitators of spirituality were stressful life events and experiences. Conclusion: Spirituality is a multidimensional concept. Unchangeable attributes of spirituality are 'connectedness with God', 'self-transcendence', 'meaning of life' and 'connectedness with others nature'. Unchangeable consequences of spirituality are 'joy' and 'hope'. The findings suggest that the dimensional framework of spirituality can be used to assess the current spiritual state of patients. Based on these results, the development of a Korean version of the scale measuring spirituality is recommended.