• Korean Association of Arts Management
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• no.60
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• pp.121-153
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• 2021

The purpose of this study is to empirically clarify the relationship between the aesthetic experience of visitors and the effect of online exhibitions at museums on the degree of viewing an offline exhibition. For this reason, the attributes of online exhibitions are composed of accessibility, interaction, informativeness, playfulness, etc., and the aesthetic experience is composed of four factors: emotional, communicative, cognitive, and perceptual areas. A survey was conducted to analyze the effect on viewing intention. The results of multiple regression analysis of the questionnaire results revealed that first, the online exhibition service had a partially significant positive(+) effect on the aesthetic experience. It was analyzed that informativity had the greatest effect on the emotional domain of aesthetic experience, playfulness had the greatest impact on the communication and perceptual domains, and access had the greatest impact on the cognitive domain. Second, it was found that online exhibitions had a partially significant positive (+) effect on offline exhibition viewing intention in the order of playfulness, interactivity, and informativity. Third, it was found that aesthetic experiences had a significant positive (+) effect on offline exhibition viewing intention in the order of cognitive, emotional, communication, and perception. In addition, it was confirmed that the aesthetic experience partially mediated the intention to view online and offline exhibitions. We hope that this study will serve as an opportunity to spark academic discussion along with practical implications for inducing online exhibition users to offline exhibitions.

• Korean Journal of Cognitive Science
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• v.33 no.4
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• pp.205-228
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• 2022

This study aimed to confirm the effect of social and relational behavior types of robots on human cognition in human-robot interaction. In the experiment, the participants evaluated trust in robots by watching a video on the robot Nao interacting with a human, in which the robot made an error and then made an effort to restore trust. The trust recovery behavior was set as three conditions: an internal attribution in which the robot acknowledges and apologizes for an error, a condition in which the robot apologizes for an error but attributes it externally, and a non-action condition in which the robot denies the error itself and does not take any action for the error. As the result, in all three cases, the error was perceived as less serious when the robot apologized than when it did not, and the ability of the robot was also highly evaluated. These results provide evidence that human attitudes towards robots can respond sensitively depending on the robot's behavior and how they overcome errors, suggesting that human perception towards robots can change. In particular, the fact that robots are more trustworthy when they acknowledge and apologize for their own errors shows that robots can promote positive human-robot interactions through human-like social and polite behavior.

• Journal of Navigation and Port Research
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• v.47 no.4
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• pp.191-201
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• 2023

The provision of onboard Internet services is recognized as one of the measures to enhance the appeal of seafarers and improve seafarer welfare. This study aims to investigate the influence of seafarers' leisure activities using the Internet on shipboard culture. Shipboard culture was examined using Hofstede's cultural dimensions theory. An empirical analysis was conducted on crewmembers regarding their Internet-based leisure activities and the shipboard culture. As a result, it was observed that sociability activities through the Internet while onboard significantly influenced power distance, uncertainty avoidance, and long-term orientation. The investigation of shipboard culture revealed uncertainty avoidance, masculinity, and long-term orientation, along with low power distance and individualism cultures. In addition, an analysis of shipboard culture according to seafarers' characteristics showed significant differences in certain shipboard cultures based on seafarers' attributes.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.295-303
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• 2023

South Korea has recently witnessed an increasing number of seismic events, leading to a surge in studies focusing on seismic earth pressures, as well as the attributes of geological layers and ground where foundations are established. Consequently, earthquake-resistant design has become imperative to ensure the safety of subterranean structures. The slurry wall method, due to its superior wall rigidity, excellent water resistance, and minimal noise and vibration, is often employed in constructing high-rise buildings in urban areas. However, given the separation between panels that constitute the wall, slurry walls possess limited resistance to seismic loads in the longitudinal direction. As a solution, several studies have probed into the possibility of interconnecting slurry wall panels to augment their seismic performance. In this research, we developed and evaluated a method for linking slurry wall panels using mechanical joints, including concrete-confined steel pipes and headed bars, through mock-up tests. We also assessed the constructability of the suggested method and compared it with other analogous methods. Any challenges identified during the mock-up test were discussed to guide future research in resolving them. The results of this study aid in enhancing the seismic performance of slurry walls through the development of an interconnected panel method. Further research can build on these findings to address the identified issues and improve the efficacy and reliability of the proposed method.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.132-140
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• 2022

This study was conducted to identify the optimal lotion manufacturing conditions with decursin and decursinol angelate of Angelica gigas Nakai extraction. Lotion was confirmed that it had viscosity (5,208±112 cPs), assay (99.71±1.01%), and pH (5.62) for 3 months. The optimization of manufacturing conditions of mixing 4 for lotion formulation were made by 22+3 full factorial design. Mixing temperature (40-80℃) and mixing time (10-30 min) were used as independent variables with three responses(assay, pH, and weight variation) as critical quality attributes (CQAs). The model for assay and weight variation identified a proper fit having a determination coefficient of the regression equation (about 0.9) and a p-value less than 0.05. Estimated conditions for the optimal manufacturing process of lotion were 61.93℃ in mixing temperature and 15.85 min in mixing time. Predicted values at the mixing temperature (60℃) and mixing time (20 min) were 100.69% of assay, 5.57 of pH, and 98.07% of weight variation. In the verification of the actual measurement the obtained values showed 100.29±0.98% of assay, 5.57±0.02 of pH, and 98.27±0.89% of weight variation, respectively, in good agreement with predicted values.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.499-510
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• 2023

Recently, an intelligent and advanced cyber attack attacks a computer network of a public institution using a file containing malicious code or leaks information, and the damage is increasing. Even in public institutions with various information protection systems, known attacks can be detected, but unknown dynamic and encryption attacks can be detected when existing signature-based or static analysis-based malware and ransomware file detection methods are used. vulnerable to The detection method proposed in this study extracts the detection result data of the system that can detect malicious code and ransomware among the information protection systems actually used by public institutions, derives various attributes by combining them, and uses a machine learning classification algorithm. Results are derived through experiments on how the derived properties are classified and which properties have a significant effect on the classification result and accuracy improvement. In the experimental results of this paper, although it is different for each algorithm when a specific attribute is included or not, the learning with a specific attribute shows an increase in accuracy, and later detects malicious code and ransomware files and abnormal behavior in the information protection system. It is expected that it can be used for property selection when creating algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.199-206
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• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.317-323
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• 2008

Mass transit information can contribute many benefits to users. Especially, transportation information technology is developing highly with information technology in Korea recently. Hereafter, it is expected to give customized transportation information to users individually with the advent of ubiquitous age in earnest. This public transportation information service can be realized by path finding algorithm in public transportation networks including travel and transfer attributes. In this research, constraints are constructed with the primary facts influencing users. Moreover, the method reducing user's path finding condition arbitrarily is proposed by making the maximum value as variables. In this study, transfer frequency, total travel time, seat confirmation, transfer time and travel time become constraint condition based on k path finding algorithm considering service time constraint condition. Moreover, case study about user customized transfer information is performed in Seoul and metropolitan subway networks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.577-585
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• 2010

Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.367-377
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• 2023

This study investigates the utility of the Triglyceride-glucose(TyG) index and Cardiometabolic Index(CMI) as predictors for diagnosing metabolic syndrome. The study involved 1970 males, 1459 females, totaling 3429 participants who underwent health checkups at P Hospital in Busan between January 2023 and June 2023. Metabolic syndrome diagnosis was based on the presence of 3 or more risk factors out of the 5 criteria outlined by the American Heart Association/National Heart, Lung, and Blood Institute(AHA/NHLBI), and participants with 2 or fewer risk factors were categorized as normal. Statistical analyses included independent sample t-tests, chi-square tests, Pearson's correlation analysis, Receiver Operating Characteristic(ROC) curve analysis, and logistic regression analysis, using the Statistical Package for the Social Sciences(SPSS) program. Significance was established at p<0.05. The comparison revealed that the metabolic syndrome group exhibited attributes such as advanced age, male gender, elevated systolic and diastolic blood pressures, high blood sugar, elevated triglycerides, reduced LDL-C, elevated HDL-C, higher Cardiometabolic Index, Triglyceride-glucose index, and components linked to abdominal obesity. Pearson correlation analysis showed strong positive correlations between waist circumference/height ratio, waist circumference, Cardiometabolic Index, and triglycerides. Weak positive correlations were observed between LDL-C, body mass index, and Cardiometabolic index, while a strong negative correlation was found between Cardiometabolic Index and HDL-C. ROC analysis indicated that the Cardiometabolic Index(CMI), Triglyceride-glucose(TyG) index, and waist circumference demonstrated the highest Area Under the Curve(AUC) values, indicating their efficacy in diagnosing metabolic syndrome. Optimal cut-off values were determined as >1.34, >8.86, and >84.5 for the Cardiometabolic Index, Triglyceride-glucose index, and waist circumference, respectively. Logistic regression analysis revealed significant differences for age(p=0.037), waist circumference(p<0.001), systolic blood pressure(p<0.001), triglycerides(p<0.001), LDL-C(p=0.028), fasting blood sugar(p<0.001), Cardiometabolic Index(p<0.001), and Triglyceride-glucose index (p<0.001). The odds ratios for these variables were 1.015, 1.179, 1.090, 3.03, and 69.16, respectively. In conclusion, the Cardiometabolic Index and Triglyceride-glucose index are robust predictive indicators closely associated with metabolic syndrome diagnosis, and waist circumference is identified as an excellent predictor. Integrating these variables into clinical practice holds the potential for enhancing early diagnosis and prevention of metabolic syndrome.