• Journal of the Korean earth science society
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• v.45 no.2
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• pp.111-120
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• 2024

Cloud coverage is a key factor in determining whether to proceed with observations. In the past, human judgment played an important role in weather evaluation for observations. However, the development of remote and robotic observation has diminished the role of human judgment. Moreover, it is not easy to evaluate weather conditions automatically because of the diverse cloud shapes and their rapid movement. In this paper, we present the development of a cloud monitoring program by applying a machine learning-based Python module "cloudynight" on all-sky camera images obtained at Miryang Arirang Astronomical Observatory (MAAO). The machine learning model was built by training 39,996 subregions divided from 1,212 images with altitude/azimuth angles and extracting 16 feature spaces. For our training model, the F1-score from the validation samples was 0.97, indicating good performance in identifying clouds in the all-sky image. As a result, this program calculates "Cloudiness" as the ratio of the number of total subregions to the number of subregions predicted to be covered by clouds. In the robotic observation, we set a policy that allows the telescope system to halt the observation when the "Cloudiness" exceeds 0.6 during the last 30 minutes. Following this policy, we found that there were no improper halts in the telescope system due to incorrect program decisions. We expect that robotic observation with the 0.7 m telescope at MAAO can be successfully operated using the cloud monitoring program.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.19-31
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• 2023

According to the climate change scenarios, the intensity of typhoons, a major factor in Korea's natural disaster, is expected to increase. The increase in typhoon intensity leads to a rise in wave heights, which is likely to cause large-scale disasters in coastal regions with high populations and building density for dwelling, industry, and tourism. This study, therefore, analyzed observation data of the Donghae ocean data buoy and conducted a numerical model simulation for wave estimations for the typhoon MAYSAK (202009) period, which showed the maximum significant wave height. The boundary conditions for wave simulations were a JMA-MSM wind field and a wind field applying the typhoon central pressure reduction rate in the SSP5-8.5 climate change scenario. As a result of the wave simulations, the wave height in front of the breakwater at Sokcho port was increased by 15.27% from 4.06 m to 4.68 m in the SSP5-8.5 scenario. Furthermore, the return period at the location of 147-2 grid point of deep-sea design wave was calculated to increase at least twice, it is necessary to improve the deep-sea design wave of return period of 50-year, which is prescriptively applied when designing coastal structures.

• Information Systems Review
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• v.21 no.1
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• pp.39-59
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• 2019

E-learning has improved the educational effect by making it possible to learn anytime and anywhere by escaping the traditional infusion education. As the use of e-learning system increases with the increasing popularity of e-learning, it has become important to measure e-learning satisfaction. In this study, we used the mixed research method to identify satisfaction factors of e-learning. The mixed research method is to perform both qualitative research and quantitative research at the same time. As a quantitative research, we collected reviews in Udemy.com by text mining. Then we classified high and low rated lectures and applied topic modeling technique to derive factors from reviews. Also, this study conducted an in-depth 1:1 interview on e-learning learners as a qualitative research. By combining these results, we were able to derive factors of e-learning satisfaction and dissatisfaction. Based on these factors, we suggested ways to improve e-learning satisfaction. In contrast to the fact that survey-based research was mainly conducted in the past, this study collects actual data by text mining. The academic significance of this study is that the results of the topic modeling are combined with the factor based on the information system success model.

• Information Systems Review
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• v.19 no.4
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• pp.63-85
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• 2017

Recent information technology achieves remarkable progress in almost all areas where it can be applied. However, this technology also causes technostress, such as fear and pressure to individuals, due to events, such as the threat of job loss. This technostress is becoming an important factor that can affect user performance and productivity in future society where information technology will be the focus. This kind of stress should be studied considerably in academic and practical applications. The effects of technostress on individual performance remain ambiguous. Therefore, academic research is needed to prove these effects. This study aimed to clarify the direct and indirect effects of technostress on information technology end-users. We developed a research model that integrates innovation resistance and technostress theory through previous studies and analyzed the questionnaire of 317 people. The PLS structural equation model and the study results of Baron and Kenny (1986) indicated that rapid change, connectivity, reliability, and complexity are crucial factors affecting the technostress of information technology. Technostress was analyzed indirectly only through innovation resistance, which affected the performance of end-users. This study will provide new implications for the relationship between technostress and performance or productivity in the IS field.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.246-263
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• 2023

The stabilization time of take-over refers to the time it takes for driving to stabilize after the take-over. Following a take-over request from an automated driving system, the driver must become aware of the road driving environment and perform manual driving, making it crucial to clearly understand the relationship between the driving environment and stabilization time of take-over. However, previous studies specifically focusing on stabilization time after take-over are rare, and research considering the driving environment is also lacking. To address this, our study conducted experiments using a driving simulator to observe take-over transitions. The results were analyzed using a liner mixed model to quantitatively identify the driving environment factors affecting the stabilization time of take-over. Additionally, coefficients for stabilization time based on each influencing factor were derived.

• Animal Bioscience
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• v.37 no.2
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• pp.173-183
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• 2024

Objective: This study aimed to evaluate whether the methane (CH₄) to carbon dioxide (CO₂) ratio (CH₄/CO₂) and methane-related traits obtained by the sniffer method can be used as indicators for genetic selection of Holstein cows with lower CH₄ emissions. Methods: The sniffer method was used to simultaneously measure the concentrations of CH₄ and CO₂ during milking in each milking box of the automatic milking system to obtain CH₄/CO₂. Methane-related traits, which included CH₄ emissions, CH₄ per energy-corrected milk, methane conversion factor (MCF), and residual CH₄, were calculated. First, we investigated the impact of the model with and without body weight (BW) on the lactation stage and parity for predicting methane-related traits using a first on-farm dataset (Farm 1; 400 records for 74 Holstein cows). Second, we estimated the genetic parameters for CH₄/CO₂ and methane-related traits using a second on-farm dataset (Farm 2; 520 records for 182 Holstein cows). Third, we compared the repeatability and environmental effects on these traits in both farm datasets. Results: The data from Farm 1 revealed that MCF can be reliably evaluated during the lactation stage and parity, even when BW is excluded from the model. Farm 2 data revealed low heritability and moderate repeatability for CH₄/CO₂ (0.12 and 0.46, respectively) and MCF (0.13 and 0.38, respectively). In addition, the estimated genetic correlation of milk yield with CH₄/CO₂ was low (0.07) and that with MCF was moderate (-0.53). The on-farm data indicated that CH₄/CO₂ and MCF could be evaluated consistently during the lactation stage and parity with moderate repeatability on both farms. Conclusion: This study demonstrated the on-farm applicability of the sniffer method for selecting cows with low CH₄ emissions.

• Journal of Digital Convergence
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• v.21 no.3
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• pp.1-14
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• 2023

This raises the question of how competitive advantage can be created, prompting firms to enhance their capacity for change. In this context, the role of knowledge creation becomes increasingly vital. This research aims to explore the role of intellectual capital and how to improve knowledge cration ability through absorptive capacity framework. It examines the links among knowledge acquisition, learning of new knowledge, knowledge creation, intellectual capital, and competitive advantage, drawing from both internal and external sources. The study focuses on small and medium-sized supplier firms in Korea, with data collected from 15 industries, totaling 106 responses. The research model employs structural equation modeling (SEM) and utilizes AMOS 22 for analysis. As anticipated, all hypotheses were supported. The study provides robust evidence that absorptive capacity is a pivotal factor in cultivating suppliers' competitive advantage. Furthermore, it posits that intellectual capital should be viewed as a criucial component of suppliers' knowledge stock, significantly enhancing the impact of absorptive capacity on their competitive edge. Future studies should aim to validate the research model in different international settings or across multinational corporations to enhance its generalizabulity.

• Environmental and Resource Economics Review
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• v.33 no.2
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• pp.159-178
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• 2024

This study aims to assess the direct and indirect impacts of local fiscal expenditures on water quality. Panel data spanning from 2010 to 2018 for 173 cities and districts in Korea are assembled, and a two-stage dynamic panel model is utilized for our estimation. The empirical findings reveal several key insights. Firstly, local fiscal expenditures on water quality are effective in ameliorating both Biological Oxygen Demand (BOD) and Total Phosphorus (T-P). Notably, the direct impact on T-P surpasses that on BOD in the short and long run. Secondly, expenditures dedicated to water quality improvement demonstrate a positive effect on local economic growth, and an inverted U-shaped relationship is observed between BOD and local economic growth. Due to the positive linkage, the indirect effect on BOD suggests, on average, a deterioration in water quality during local economic growth. Thirdly, concerning BOD, the direct effect of government expenditure on water quality improvement outweighs the indirect effect, but in the case of T-P, the indirect effect is not significant, and the total effect is solely determined by the direct impact. Despite local fiscal expenditures potentially exacerbating water quality through regional economic growth, the study finds that the direct enhancement of water quality remains a more substantial factor in the short and long run.

• The Journal of Fisheries Business Administration
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• v.55 no.3
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• pp.1-13
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• 2024

The purpose of this study is to examine the determinants of management performance in the remaining offshore fishing industry after the resource management-oriented fisheries structure improvement policy by the fisheries vessel buy-back program and Total Allowable Catch (TAC). The results of the analysis of the determinants of management performance of offshore fishing can be summarized as follows. First, based on the management performance determinant model of offshore fishing, it is confirmed that the government's resource-managed fishing structure improvement policy, such as the fishing boat reduction project and the TAC policy, is improving the management performance of the resource-managed remaining fishing boat. Second, looking at the specific management performance determinants based on the management performance model of offshore fishing, the leverage ratio (TLTA), which is the total debt ratio, shows a statistically significant positive (+) relationship with management performance, which increases management performance directly proportional to the leverage ratio. The increase in the leverage ratio (total debt ratio) was expected to lead to a high interest cost burden, resulting in a reverse (-) financial leverage effect; however, rather a positive (+) financial leverage effect occurred with a high profit covering interest costs. The total catch (TCATCH) has a positive (+) relationship with management performance at a statistical significance level of less than 1%, indicating that an increase in catch is improving or increasing the management performance of fishing companies. The selling price (UPRICE) shows a positive (+) relationship with management performance at a very high statistical significance level of less than 1%, and it can be seen that high fishing prices are a major factor in improving or increasing the management performance of offshore fishing. On the other hand, fishing vessel tonnage (TON), fishing vessel horsepower (RHP), and operating days (WDAYS), which indicate have a statistically significant negative (-) relationship with management performance, which deviates from the existing fisheries common sense that the size of fishing vessel tonnage and fishing vessel horsepower and the increase in the number of operating days is proportional to management performance. As a result of the increase in fishing vessel tonnage, horsepower, and the number of operating days, it was confirmed that the higher the fishing cost, such as oil costs, is worsening the management performance of fishing companies. Participation in TAC has a statistically significant positive (+) value with management performance, indicating that the remaining offshore fishing companies participating in TAC are improving or increasing management performance compared to offshore fishing companies that do not. Third, there are conflicting results depending on the industry as a result of estimating the management performance determinants of offshore fishing by TAC participation, and TAC participation had a negative impact on management performance in anchovy boat seine and southern west sea bottom trawl in fishing industry while TAC participation had a positive impact on management performance in large stow nets on anchor in fishing industry.