• International Area Studies Review
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• v.21 no.4
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• pp.247-268
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• 2017

This paper analyzes for companies of 2011~2014 the effects of corporate social responsibility on audit efficiency. Using KEJI Index and its individual components which is published by Citizens' Coalition for Economic Justice Institute, this paper analyzes their effects on audit efficiency of audit fees and audit hours. The results of analyses are as followings. First, corporate social responsibility(CSR) composite index did not show any significant relationship between audit fees and audit hours. However, for analyses of the effects of CSR individual components on audit efficiency, variable such as CSR fairness(CSR2), CSR social contribution(CSR3), CSR environmental protection activity(CSR5) have the negative effects on the audit fees and audit time. and CSR customer protection(CSR4), CSR employee satisfaction(CSR6) have the positive effects on the audit fees and audit time. Results suggest that independent auditors may reduce audit risks associated with possible misrepresentation of financial statements for companies with high scores of CSR fairness (CSR2), CSR social contribution(CSR3), and CSR environmental protection activity(CSR5). Also, financial statement auditors may perceive surge of discretionary expenses, and set audit risk high for companies with CSR customer protection(CSR4), and CSR employee satisfaction(CSR6). Together, KEJI Index and its individual components appear to have differential effects on audit efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.88-95
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• 2018

Maintainability indicates how easily a system can be restored to the normal state when a system failure occurs. Systems developed to have high maintainability can be competitive due to reduced maintenance time, workforce and resources. Quantification of the maintainability is possible in many ways, but only after prototype production or with historical data. As such, the graph theory and 3D model data have been used, but there are limitations in management efficiency and early use. To solve this problem, we studied the maintainability index of weapon systems using SysML-based modeling and simulation technique. A SysML structure diagram was generated to simultaneously model the system design and maintainability of system components by reflecting the maintainability attributes acquired from the system engineering tool. Then, a SysML parametric diagram was created to quantify the maintainability through simulation linked with MATLAB. As a result, an integrated model to account for system design and maintainability simultaneously has been presented. The model can be used from early design stages to identify components with low maintainability index. The design of such components can be changed to improve maintainability and thus to reduce the risks of cost overruns and time delays due to belated design changes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.139-150
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• 2019

Though, fishing vessel accidents account for 70 % of all maritime accidents in Korean waters, most research has focused on identifying causes and developing mitigation policies in an attempt to reduce this rate. However, predicting and evaluating accident risk needs to be done before the implementation of such reduction measures. For this reasons, we havve performed a risk analysis to calculate the risk of accidents and propose a risk criteria matrix with 4 quadrants, within one of which forecasted risk is plotted for the relative comparison of risks. For this research, we considered 9 types of fishing vessel accidents as reported by Korea Maritime Safety Tribunal (KMST). Given that no risk evaluation criteria have been established in Korea, we established a two-dimensional frequency-consequence grid consisting of four quadrants into which paired frequency and consequence for each type of accident are presented. With the simple structure of the evaluation model, one can easily verify the effect of frequency and consequence on the resulting risk within each quadrant. Consequently, these risk evaluation results will help a decision maker employ more realistic risk mitigation measures for accident types situated in different quadrants. As an application of the risk evaluation matrix, accident types were further analyzed using accident causes including human error (factor) and appropriate risk reduction options may be established by comparing the relative frequency and consequence of each accident cause.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.152-161
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• 2019

The purpose of this study was to research the relationships among utilitarian perceptions, hedonic perceptions, perceived usefulness and behavioral intention. Recently, consumers rely heavily on user-generated contents of social media channels to support their purchase decisions, such as electronic word-of-mouth. Electronic word-of-mouth helps consumers to evaluate items before making purchase, to reduce purchase risks and to support their purchase decisions. This study was based on both the analysis derived from a hypothesis and literature reviews and data collected from 255 travelers who had used travel review website at least once. The results of empirical analysis showed as follows. First, Utilitarian perceptions(information quality) has a significant impact on the perceived usefulness of a travel review website. Second, Enjoyment has a significant impact on the perceived usefulness of a travel review website. Third, Curiosity fulfilment has a significant impact on the perceived usefulness of a travel review website. Finally, Perceived usefulness of a travel review website has a significant impact on behavioral intention. Based on these findings, the implications and limitations of the study were presented including some directions for future studies.

• Journal of Korean Society on Water Environment
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• v.35 no.3
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• pp.224-233
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• 2019

Nitrogen components in liquid manure can reduce safety and quality of environment harmfully. To minimize the environmental risks of manure, understanding fate of manure in environment is necessary. This study aimed at investigating applicability of a simplified Level III fugacity model for simulating $NH_3-N$ component to analyze environmental fate and transport of $NH_3-N$ in liquid manure and to provide basis for improving management of N in the liquid manure system and for minimizing the environmental impacts of N. The model simulation conducted for four environmental compartments (air, water, soil, and rice plants) during rice-cropping to trace $NH_3-N$ component and provided applicability of the Level III fugacity model in studying the environmental fate of $NH_3-N$ in manure. Most of $NH_3-N$ was found in water body and in rice plants depending upon the physicochemical properties and proper removal processes. For more precise model results, the model is needed to modify with the detailed removal processes in each compartment and to collect proper and accurate information for input parameters. Further study should be about simulations of various N-typed fertilizers to compare with the liquid manure based on a modified and relatively simplified Level III fugacity model.

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.4
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• pp.483-491
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• 2021

The identification of regional collision risks in water areas is significant for the safety of navigation. This paper introduces a new method of collision risk assessment that incorporates a clustering method based on the distance factor - hierarchical clustering - and uses real-time data in case of several surrounding vessels, group methodology and preliminary assessment to classify vessels and evaluate the basis of collision risk evaluation (called HCAAP processing). The vessels are clustered using the hierarchical program to obtain clusters of encounter vessels and are combined with the preliminary assessment to filter relatively safe vessels. Subsequently, the distance at the closest point of approach (DCPA) and time to the closest point of approach (TCPA) between encounter vessels within each cluster are calculated to obtain the relation and comparison with the collision risk index (CRI). The mathematical relationship of CRI for each cluster of encounter vessels with DCPA and TCPA is constructed using a negative exponential function. Operators can easily evaluate the safety of all vessels navigating in the defined area using the calculated CRI. Therefore, this framework can improve the safety and security of vessel traffic transportation and reduce the loss of life and property. To illustrate the effectiveness of the framework proposed, an experimental case study was conducted within the coastal waters of Mokpo, Korea. The results demonstrated that the framework was effective and efficient in detecting and ranking collision risk indexes between encounter vessels within each cluster, which allowed an automatic risk prioritization of encounter vessels for further investigation by operators.

• Journal of Navigation and Port Research
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• v.45 no.1
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• pp.33-41
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• 2021

In the last 5 years, a total of 567 accidents of operating vessels occurred under the influence of alcohol at sea, most of which occurred in fishing boats. Accidents caused by operating vessels under the influence of alcohol at sea are causing human and physical damages. There were 69 accidents caused by operating vessels under the influence of alcohol, leading to five deaths and one missing. The social damage due to operating vessels under the influence of alcohol is also increasing. Under the current law, punishment is given lightly compared to the seriousness of violation. In order to prevent the recurrence of accidents caused by operating vessels under the influence of alcohol, cases in Korea need to be analyzed. Regulations on the crackdown in foreign countries were compared to those in Korea and reviewed. In addition, risks of operating vessels under the influence of alcohol should be provided to ship workers while improving related laws and systems. In addition, efforts should be made to reduce the number of accidents due to operating vessels under the influence of alcohol by strengthening crackdowns on ships at sea so that accidents caused by operating vessels under the influence of alcohol could be prevented in advance in the future.

• Convergence Security Journal
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• v.20 no.4
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• pp.187-196
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• 2020

In order to manage information security risk, various information security level evaluation and information security management system certification have been conducted on a larger scale than ever. However, there are continuous cases of infringement of information protection for companies with excellent information security evaluation and companies with excellent information security management system certification. The existing information security risk management methodology identifies and analyzes risks by identifying information assets inside the information system. Existing information security risk management methodology lacks a review of where cyber threats come from and whether security devices are properly operated for each route. In order to improve the current risk management plan, it is necessary to look at where cyber threats come from and improve the containment level for each inflow section to absolutely reduce unnecessary cyber threats. In addition, it is essential to measure and improve the appropriate configuration and operational level of security equipment that is currently overlooked in the risk management methodology. It is necessary to block and enter cyber threats as much as possible, and to detect and respond to cyber threats that inevitably pass through open niches and use security devices. Therefore, this paper proposes additional evaluation items for evaluating the containment level against cyber threats in the ISMS-P authentication items and vulnerability analysis and evaluation items for major information and communication infrastructures, and evaluates the level of security equipment configuration for each inflow.