• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.43-49
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• 2023

In Korea, the dependence on living donations is high due to the shortage of organs available for donation compared to the number of people waiting for transplants and the number of living organ donations continues to increase. In particular, the number of living-donor transplantations is high worldwide, highlighting the importance of pre-transplant psychosocial evaluation of living kidney donors. According to previous studies, when evaluating living organ donors before transplantation, it is crucial to determine whether the donor can give informed consent and be aware of the risks after surgery. Pre-transplant evaluation tests such as ELPAT living organ donor Psychological Assessment Tool (EPAT), Live Donor Assessment Tool (LDAT), Living Donation Expectancies Questionnaire (LDEQ), Minnesota Multiphasic Personality Inventory-2 questionnaire (MMPI-2) and Temperament and Character Inventory (TCI) are conducted for donors. After reviewing the literature on these pre-transplant psychosocial assessment tools, we will also look at legal considerations for living kidney donors in Korea and suggest an effective and essential pre-transplant screening evaluation method for living kidney transplant donors.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.964-970
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• 2023

As part of the International Maritime Organization ef orts to reduce greenhouse gas emissions, the maritime industry is exploring low-carbon fuels such as liquefied natural gas and methanol, as well as zero-carbon fuels such as hydrogen and ammonia, evaluating them as environmentally friendly alternatives. Particularly, ammonia has substantial operational experience as cargo on transport ships, and ammonia ship engines are expected to be available in the second half of 2024, making it relatively accessible for commercial use. However, overcoming the toxicity challenges associated with using ammonia as a fuel is imperative. Detection is possible at levels as low as 5 ppm through olfactory senses, and exposure to concentrations exceeding 300 ppm for more than 30 min can result in irreparable harm. Using the KORA program provided by the Chemical Safety Agency, an assessment of the potential risks arising from leaks during ammonia bunkering was conducted. A 1-min leak could lead to a 5 ppm impact within a radius of approximately 7.5 km, affecting key areas in Busan, a major city. Furthermore, the potentially lethal concentration of 300 ppm could have severe consequences in densely populated areas and schools near the bunkering site. Therefore, given the absence of regulations related to ammonia bunkering, the potential for widespread toxicity from even minor leaks highlights the requirement for the development of legislation. Establishing an integrated system involving local governments, fire departments, and environmental agencies is crucial for addressing the potential impacts and ensuring the safety of ammonia bunkering operations.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.1-16
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• 2023

Due to the progress of the 4th industrial revolution and the COVID-19 pandemic, the subscription economy was rapidly expanding. In particular, the subscription economy was expected to expand further as the servicing of products(servitization) rapidly progresses. In this study, we tried to empirically analyze the factors that promote and hinder the spread of the subscription economy from the consumer's point of view. To this end, based on the Service Profit Chain (SPC) model, which identified mechanisms leading from quality to satisfaction, loyalty, and performance, a research model was established by combining the framework of the Value-based Adoption Model (VAM), which covers both benefit and sacrifice factors. Usefulness and convenience were derived as benefit factors, and perceived risks and perceived costs were derived as sacrifice factors. The effects of these factors on satisfaction and continuous use intention were analyzed. For empirical analysis, a survey was conducted targeting people who have experience in subscription economy, and 300 effective samples were analyzed. The analysis was performed as a structural equation model using AMOS 24. As a result of the empirical study, it was found that convenience had a significant positive (+) effect on satisfaction. Perceived risk and perceived cost were analyzed to have a negative (-) effect on satisfaction. On the other hand, usefulness was found to have no significant effect on satisfaction. The influences affecting satisfaction were in the order of perceived cost, convenience, and perceived risk. Satisfaction was found to have a significant positive (+) effect on continuous use intention. The results of this study were considered meaningful in that they broadened the horizons of research by combining existing validated models at the academic level and testing their validity, and found that perceived cost was still an important factor at the practical level.

• Korean Journal of Culture and Social Issue
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• v.8 no.1
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• pp.165-187
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• 2002

This study examines Korean representation of the biotechnology and psychological factors which can influence lay people's perception and attitude about biotechnology. Korean college students(N=433) and lay adults(N=90) whom had college education participated in the study. Participants of the study 1 were asked to list words which comes to mind when associate with the biotechnology in broad sense, and several specific applications in health, medicines, agriculture and research. Participants of the study 2 were asked to list possible benefits and costs of biotechnology and their specific applications. In study 3, Participants responded the questionnaires about perceptions and attitudes of biotechnology. Korean people associated the biotechnology with its costs or risks and benefits. Korean college students mainly got the informations of the biotechnology from TV, newspapers, or internet. They trusted the scientist group and NGO group on their judgements about the assessment of risk and benefit of the biotechnology. College students showed the positive attitude with the applications in medicines and negative attitude with the applications in agriculture and public using of individual's genetic information. The radicalism, sensitivity in behavioral activation system, and trust/cynicism were to be found as a significant influencing factor for interest/knowledge and behavioral intention in related with biotechnology. Finally, more extensive knowledge of biotechnology did not lead to greater acceptance of it.

• Explosives and Blasting
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• v.41 no.3
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• pp.62-72
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• 2023

The aging of plant structures due to industrialization in the 1970s has increased the demand for blast demolition. While blasting can reduce exposure to environmental pollution by shortening the demolition period, improper blasting design and construction plans pose significant safety risks. Thus, it is vital to consider optimal blasting demolition conditions and other factors through collapse behavior simulation. This study utilizes a 3-D combined finite-discrete element method (FDEM) code-based 3-D DFPA to simulate the collapse of a chimney structure in a thermal power plant in Seocheon, South Korea. The collapse behavior from the numerical simulation is compared to the actual structure collapse, and the numerical simulation result presents good agreement with the actual building demolition. Additionally, various numerical simulations have been conducted on the chimney models to analyze the impact of the duct size in the pre-weakening area. The no-duct, duct, and double-area duct models were compared in terms of crack pattern and history of Z-axis displacement. The findings show that the elapse-time for demolition decreases as the area of the duct increases, causing collapse to occur quickly by increasing the load-bearing area.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.347-373
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• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.

• Korean Association of Arts Management
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• no.50
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• pp.213-241
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• 2019

Recently, many interests in the economic contribution of performing arts for the city's tourist attractions have been increasing, and the policy projects supporting surtitle for foreign tourists are expanding. Therefore, the purpose of this study is to explore the acceptance process of subtitle systems using the TAM(Technical Acceptance Model) to understand the influential relations of factors affecting the viewing of the performance of subtitling service by foreign tourists. Data for empirical analysis were collected in a survey of foreign tourists who had experienced performance subtitles with smart pads in three languages. The results of this study are as follows. First, the higher the information system quality of the performance subtitles, the higher the perceived usefulness of the subtitles. Second, for Korean performances, the decreasing level of both the performance-based risk and the psychological risk has a positive influence on the viewing intent. But, the decreasing level of the financial risk has a negative influence on the viewing intent. Third, the decreasing level of performance risk has a positive influence on the perceived usefulness, while the decreasing level of psychological risk has a negative influence on the perceived usefulness. Finally, the psychological risk has the moderating effect of the viewing intention, which it has a negative influence on the perceived usefulness.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.136-147
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• 2024

It has recently be emphasized in science education that lessons that can develop "scientific participation and action" should be implemented to scientifically recognize various problems and respond to them as well as risks that occur in real life. This study aims to analyze the characteristics of scientific participation and action lessons as perceived by the preservice primary school teachers. To do that, the researchers collected and analyzed the lesson plans designed by the preservice teachers based on the achievement standard related to noise for grades 3-4 in 2022 revised science curriculum. Focusing on the stages of "problem recognition," "data collection and analysis," and "implementation and sharing," the results identity the four main characteristics as problem-solving activity, inquiry activity, investigative activity, and activity that encourages practical actions. The two or three features were found to be combinated in a lesson depending on its context. In some cases, only one feature was seen in a lesson. Based on the results, educational implications were discussed in terms of the teaching and learning methods and teacher education for implementing scientific participation and action.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1213-1224
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• 2021

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.