• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.10a
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• pp.303-308
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• 2003

In this paper, wave numerical modeling was experimented for the analysis of impact factors for the wave transmission as the incident wave and topographic conditions in the narrow channel sea. Recently, Although the results of many researcher for the wave modelling, numerical equations have limited to simulation of wave transformation effects. Despite of thispresent problems, the models was used to design the coastal structures in barrow channel sites. Finally, this paper estimated the wave model(mild slope eq. model) as the analysis of the wave energy transmission according to changing of impact factors(width of channel, bottom slope in channel, incident wave angle, wave period). As the results of numerical experiment, the major impact factors which influence to wave energy transmission were the width of channel and incident wave direction. But in the case that the width of channel is larger than 3L(L=Length of wave), the reduction of wave energy was small.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.46-56
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• 2021

Predicting the incident clearance time is important for eliminating the high transportation costs and congestion from non-repetitive congestion caused by incidents. In this study, the factors influencing the clearance time suitable for domestic road conditions were analyzed, using a training dataset for predicting the incident clearance time using artificial neural networks. In a previous study, the under-prediction problem for high incident clearance time was used. In the present study, over-sampling training data applied using the SMOGN technique was obtained and applied to the model as a solution. As a result, the DNN model applying the SMOGN technique could compensate for the limitations of the previously developed prediction model by predicting the clearance time with the highest accuracy among the models developed in the research process with MAE = 18.3 minutes.

• Journal of Climate Change Research
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• v.6 no.2
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• pp.121-131
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• 2015

As the temperature has changed by climate change, changes in its own characteristic values of the chemical substance or the movement and distribution of chemicals take place in accordance with the changes of hydrological and meteorological phenomena. Depending on the impact of climate change on the chemical behavior, it is necessary to understand and predict quantitative changes in the dynamics of the environment of pollutants due to climate change in order to predict in advance the occurrence of environmental disasters, and minimize the impact on the life and the environment after the incident. In this study, we have analysed and compared chemical fate models validated by previous studies in terms of model configuration, application size and input/output factors. The potential models applicable to municipal and industrial areas were selected on the basis of characteristic of each model, availability of input parameters and consideration for climate change, identified the problems, and then presented an approach to improve applicability.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.41-62
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• 2016

In Internet of Things (IoT) era, more diverse types of information are collected and the environment of information usage, distribution, and processing is changing. Recently, there have been a growing number of cases involving breach and infringement of personal information in IoT services, for examples, including data breach incidents of Web cam service or drone and hacking cases of smart connected car or individual monitoring service. With the evolution of IoT, concerns on personal information protection has become a crucial issue and thus the risk analysis and management method of personal information should be systematically prepared. This study shows risk factors in IoT regarding possible breach of personal information and infringement of privacy. We propose "a risk analysis framework of protecting personal information in IoT environments" consisting of asset (personal information-type and sensitivity) subject to risk, threats of infringement (device, network, and server points), and social impact caused from the privacy incident. To verify this proposed framework, we conducted risk analysis of IoT services (smart communication device, connected car, smart healthcare, smart home, and smart infra) using this framework. Based on the analysis results, we identified the level of risk to personal information in IoT services and suggested measures to protect personal information and appropriately use it.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.637-651
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• 2019

In the event of a major accident such as an explosion in a refinery or a petrochemical plant, it has caused a serious loss of life and property and has had a great impact on the insurance market. In the case of catastrophic incidents occurring in process industries such as refinery and petrochemical plants, only the proximate causes of loss have been drawn and studied from inspectors or claims adjustors responsible for claims of property insurers, incident cause investigators, and national forensic service workers. However, it has not been done well for conducting root cause analysis (RCA) and identifying the factors that contributed to the failure and establishing preventive measures before leading to chemical plant's catastrophic incidents. In this study, the criteria of warning signs on CCPS catastrophic incident waning sign self-assessment tool which was derived through the RCA method and the contribution factor analysis method using the swiss cheese model principle has been reviewed first. Secondly, in order to determine the major incident warning signs in an actual chemical plant, 614 recommendations which have been issued during last the 17 years by loss control engineers of global reinsurers were analyzed. Finally, in order to facilitate the assessment index for catastrophic incident warning signs, the criteria for the catastrophic incident warning sign index at chemical plants were grouped by type and classified into upper category and lower category. Then, a catastrophic incident warning sign index for a chemical plant was developed using the weighted values of each category derived by applying the analytic hierarchy process (pairwise comparison method) through a questionnaire answered by relevant experts of the chemical plant. It is expected that the final 'assessment index for catastrophic incident warning signs' can be utilized by the refinery and petrochemical plant's internal as well as external auditors to assess vulnerability levels related to incident warning signs, and identify the elements of incident warning signs that need to be tracked and managed to prevent the occurrence of serious incidents in the future.

• Architectural research
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• v.24 no.4
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• pp.105-111
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• 2022

During pandemic period, college students lost lots of such academic opportunities as extra-curriculum social activities, contact classes, and friendly socializing in university campus area, etc. Previous many studies have shown that physical environment has certain relevance on the well-being of human-beings. Recent public statistics on mental health had shown an increase in psychological distress and a decrease in college students and people's well-being during the lockdown in response to the Covid-19 pandemic. However, there were little evidence on what the college students in dormitory suffered from COVID-19 incident in relation with their physical environment. The purpose of this study is to investigate the relationship between environmental factors and psychological well-being of dormitory students in university campus. In order to explore the impact of physical environment on students' psychological well-being, survey instrumentation consisted of 25 indices were employed to measure the level of awareness to each index. A Chi-square analysis on individual characteristics of 200 students found that number of students living in single dwelling unit was statistically significant to maintain their psychological well-being, except for number of students living in each dwelling unit (χ² =128.92, p= .004). Pearson correlation analysis also found that there exists statistically significant relationship between psychological well-being of students and environmental factors. Further, stepwise multiple regression analysis revealed that the most prime predictor for psychological well-being of students residing in dorm was "use of furniture" (β= .281), implying careful design, lay-out and easy-access to interior furniture by facility planner. The study also demonstrated that as the level of positive perception of physical environmental features rose, overall psychological well-being of students also responded positively at specified rate. Finally, the findings reinforce a solid evidence that carefully well-coordinated physical environments play an important role in maintaining emotional stability of college students in dorm even in pandemic period.

• Journal of Korean Academy of Nursing
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• v.54 no.1
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• pp.18-31
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• 2024

Purpose: This study aimed to investigate the impact of anthropometric indices of obesity (body mass index [BMI], waist circumference, waist hip ratio, and body fat percentage) on the incidence of hypertension in adults with prehypertension. Methods: A longitudinal study design using secondary data form the Korean Genome and Epidemiology Study was employed. The study included 1,838 adults with prehypertension tracked every two years from 2001 to 2018. Statistical analyses, including frequency assessments, number of cases per 1,000 person-years, log-rank tests, Kaplan-Meier curves, and Cox's proportional hazards regression, were conducted using SPSS version 25. Results: Over the observation period (15,783.6 person-years), 1,136 individuals developed hypertension. The incidence of hypertension was significantly higher in the obesity groups defined by BMI (hazard ratio [HR] = 1.33), waist circumference (HR = 1.34), waist hip ratio (HR = 1.29), and body fat percentage (HR = 1.31) compared to the non-obese group. These findings indicate an increased risk of hypertension associated with obesity as measured by these indices. Conclusion: The study underscores the importance of avoiding obesity to prevent hypertension in individuals with prehypertension. Specifically, BMI, waist circumference, waist hip circumference, and body fat percentage were identified as significant risk factors for hypertension. The results suggest the need for individualized weight control interventions, emphasizing the role of health professionals in addressing the heightened hypertension risk in this population.

• Convergence Security Journal
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• v.21 no.3
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• pp.81-91
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• 2021

The purpose of this study is to examine COVID-19 situation in temrs of war-theory and to find out ways to overcome it. Just as the war changes the paradigm in the international situation and the national crisis management system, the current COVID-19 pandemic is bringing about the entry of the so-called "New Normal" era having the characteristics including untact culture. Although academic research on COVID-19 is mainly dealt with in terms of medical, tourism, and economics, the military research has not yet begun from the perspective of military science or war theory. In the concept of a comprehensive crisis that COVID-19 can cause enormous damage to the life and property of a country, it can be regarded as a target or enemy to be overcome. Among various war theories, the similarities with COVID-19 incident are analyzed in terms of the nature and aspect of the war and the factors of victory. Qualitative and questionnaire analysis results show that the COVID-19 outbreak is very similar to war when considering a variety of war-characteristics. In addition this research proposes ways to overcome COVID-19 based on the victorious factors of the past war, and predicts the impact of the international community after the end of COVID-19 pandemic. As a result of analyzing the priority of overcoming factors through the Analytical Hierarchy Process (AHP) shows that clear goals and establishment of alliances should be prioritized for successfully overcoming COVID-19.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.153-165
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• 2022

The COVID-19 Pandemic incident forced all educational and learning activities to move online, so it is no longer an option to use information and communication technology for education and learning. Venture capital has made the largest investment ever in Edu-tech startups. This study investigates the factors influencing the intention to use digital technology in education, taking into account the Unified Theory of Acceptance and Use of Technology (UTAUT) along with digital literacy, which has become an essential ability in the digital age. As a result of the structural equation model analysis, we find that performance expectation, effort expectation, and social influence have a positive effect on the intention to use digital technology in education. Moreover, digital literacy has a positive effect on performance expectation, effort expectation, and social impact, but the direct effect on the intention to use digital technology on learning is not significant. Furthermore, to see the moderating effect of age, the results of multi-group analysis present that the differences between 10s and 60s, between 20s and 60s, between 30s and 60s on the path of social influence on the intention to use digital technology in education are significantly reduced. This study academically contributes to expanding the research on the factors affecting the intention to use digital technology in a specific situation of education by considering both digital literacy and Unified Theory of Acceptance and Use of Technology (UTAUT). In addition, it can be used as a practical guide to the factors to be considered for each age when making learning participants more actively use digital technology.

• The Journal of Bigdata
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• v.5 no.2
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• pp.111-120
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• 2020

Despite the recent economic contraction caused by the Corona 19 incident, interest in the residential environment is growing as more people live at home due to the increase in telecommuting, thereby increasing demand for remodeling. In addition, the government's real estate policy is also expected to have a visible impact on the sales of the interior and furniture industries as it shifts from regulatory policy to the expansion of housing supply. Accurate demand forecasting is a problem directly related to inventory management, and a good demand forecast can reduce logistics and inventory costs due to overproduction by eliminating the need to have unnecessary inventory. However, it is a difficult problem to predict accurate demand because external factors such as constantly changing economic trends, market trends, and social issues must be taken into account. In this study, LSTM model and 1D-CNN model were compared and analyzed by artificial intelligence-based time series analysis method to produce reliable results for manufacturers producing furniture components.