• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.25-38
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• 2021

Purpose: To reduce the damage caused by continuously occurring typhoons, we proposed a standardized grid so that it could be actively utilized in the prevention and preparation stage of typhoon response. We established grid-based convergence information on the typhoon risk area so that we showed the effectiveness of information used in disaster response. Method: To generate convergent information on typhoon hazard areas that can be useful in responding to typhoon situation, we used various types of data such as vector and raster to establish typhoon hazard area small grid-based information. A standardized grid model was applied for compatibility with already produced information and for compatibility of grid information generated by each local government. Result: By applying the grid system of National branch license plates, a grid of typhoon risk areas in Seoul was constructed that can be usefully used when responding to typhoon situations. The grid system of National branch license plates defines the grid size of a multi-dimensional hierarchical structure. And a grid of typhoon risk areas in Seoul was constructed using grids of 100m and 1,000m. Conclusion: Using real-time 5km resolution grid based weather information provided by Korea Meteorological Administration, in the future, it is possible to derive near-future typhoon hazard areas according to typhoon travel route prediction. In addition, the national branch number grid system can be expanded to global grid systems for global response to various disasters.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.38-47
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• 2021

This study is about a blockchain-based collective quarantine management system and its commercialization model. The configuration of this system includes a biometric information transmission unit that generates biometric information based on measured values generated from wearable devices, a biometric information transmission unit that transmits biometric information generated here from a quarantine management platform, and action information transmitted from the community server. is a system including an action information receiving unit for receiving from the quarantine management platform. In addition, a biometric information receiving unit that collects biometric information from the terminal, an encryption unit that encodes biometric information generated through the biometric information receiving unit based on blockchain encryption technology, and a database of symptoms of infectious diseases to store symptom information and an infection diagnosis database. The generated database includes a location information check unit that receives from the terminal of the user identified as a symptomatic person and determines whether the user has arrived in the community based on the location information confirmation unit and the location of the user after the location is confirmed. It includes a community arrival judgment unit that judges. And, the community server helps the interaction between the generated information. Such a blockchain based collective quarantine management system can help to advance the existing quarantine management system and realize a safer and healthier society.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.173-184
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• 2021

This paper aims to examine the effects of perceived social fairness and upward social mobility on the individual emotional depression. Specifically, this study investigates the conditions under which the effects are more or less pronounced for the sake of shedding more light on the relationship between social-cognitive and psychological factors. The key proposition of this study is that as one holds more favorable beliefs about the fairness of the society to which (s)he belong, (s)he would have more optimistic expectations for the possibility of his or her own upward social mobility. Moreover, the decrease of this expectation could exacerbate his or her emotional depression with the expectation that (s)he might not get what (s)he deserves despite his or her time and effort put into achieving such goals. This study also adds further boundary conditions to these effects, such that the decrease of emotional depression is more pronounced when (1)social capital and (2)economic resources are scarce (versus abundant). To test these predictions, this study used the survey data on a total of 8000 people collected by Gallup Korea at the request of the Korea Institute of Public Administration. The analyses provided support for the proposed model of the present study. These results should contribute to laying the theoretical foundation for the establishment of policies and research models on the enhancement of fairness and prevention of depression in the future.

• Knowledge Management Research
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• v.22 no.2
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• pp.33-53
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• 2021

Use of mobile apps being extended, privacy concern on the side of the users is increased while they are willing to provide the private information to use the apps. In this study, we tried to identify the motivating elements that influence the users' intention to use the apps, based on the tendency towards regulatory focus and the privacy calculus theory. To verify the study model, we collected data from 151 adults who use health apps throughout the country, and analyzed the data using the PLS-SEM method. According to the result of the study, it was turned out that tendency towards promotion focus had negative impact on privacy concern and privacy danger, and tendency towards prevention focus had positive impact on privacy concern. Privacy concern had negative impact on the intention to use the mobile apps, and privacy benefit and privacy knowledge had positive impact on the intention to use the mobile apps. Finally, the intention to use the mobile apps had positive impact on the intention to continue to use the mobile apps. In this study, we identified different impacts of two types of tendency towards regulatory focus on privacy concern, and identified different influences on the intention to use the mobile apps accordingly.

• Health Policy and Management
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• v.31 no.1
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• pp.114-124
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• 2021

Background: In this study, we aimed to investigate the interaction effects of individual socioeconomic status and regional deprivation on the onset of diabetes complications and diabetes-related hospitalization among type 2 diabetes patients. Methods: Korean National Health Insurance Service National Sample Cohort data from 2002 to 2013 were used. A total of 50,954 patients newly diagnosed with type 2 diabetes from 2004 to 2012 and aged 30 years or above were included. We classified patients into six groups according to individual income level and neighborhood deprivation: 'high in advantaged,' 'high in disadvantaged,' 'middle in advantaged,' 'middle in disadvantaged,' 'low in advantaged,' and 'low in disadvantaged.' We calculated hazard ratios (HR) of onset of diabetes complication and diabetes-related hospitalization using the Cox proportional hazard model, with the reference group as diabetes patients with high income in advantaged regions. Results: In terms of the interaction effects of individual income level and regional socioeconomic level, even with the same low individual income level, the group with a high regional socioeconomic level (low in advantaged) showed low HRs for the onset of diabetes complication (HR, 1.04; 95% confidence interval [CI], 1.00-1.08) compared to the 'low in disadvantaged' group (HR, 1.10; 95% CI, 1.05-1.16). In addition, the 'high in advantaged' group showed slightly higher HRs for the onset of diabetes complication (HR, 1.06; 95% CI, 1.00-1.11) compared to the 'low in advantaged' and it appeared to be associated with slight mitigation of the risk of diabetes complication. For the low-income level, the patients in disadvantaged regions showed the highest HRs for diabetes-related hospitalization (HR, 1.29; 95% CI, 1.19-1.41) compared to the other groups. Conclusion: Although we need to perform further investigations to reveal the mechanisms that led to our results, interaction effects individual socioeconomic status and regional deprivation might be associated with on onset of diabetes complications and diabetes-related hospitalization among type 2 diabetes patients.

• Journal of Nutrition and Health
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• v.54 no.4
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• pp.412-421
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• 2021

Purpose: Thioacetamide (TAA) produces reactive oxygen species (ROS) in the liver, and the generated ROS induces liver injury through inflammatory reactions. The current study was undertaken to investigate the hepatoprotective effect of Artemisiae Capillaris Herba water extract (AC), imparted via its antioxidant activity, in an animal model of TAA-induced liver injury. Methods: Animal experiments were conducted in 5 groups: normal, control (TAA 200 mg/kg), SM (TAA 200 mg/kg + silymarin 100 mg/kg), ACL (TAA 200 mg/kg + AC 100 mg/kg), ACH (TAA 200 mg/kg + AC 200mg/kg). TAA (intraperitoneal) and treatment compounds (per oral) were administered for 3 days. Serum levels of ammonia concentration and myeloperoxidase (MPO) activity were subsequently measured. Liver tissues were subjected to western blot analysis for measuring the oxidative stress (NADPH oxidase), anti-oxidative activity (Nrf2, heme oxygenase-1 [HO-1], superoxide dismutase [SOD], catalase, and GPx-1/2), tissue inhibitors of metalloproteinase (TIMP)-1, and matrix metalloproteinases (MMPs) protein expressions. Results: Serum ammonia levels and MPO activity were significantly increased in the TAA-induced control group, whereas groups administered AC treatment showed markedly reduced levels. Western blot analysis revealed significantly increased NOX2 and p22^phox expressions, (oxidative stress-related factors) in the TAA-induced control group. These levels were determined to be significantly decreased after AC exposure. Moreover, antioxidant-related factors including Nrf2, HO-1, SOD, catalase, and GPx-1/2 were significantly decreased in the control group and increased in the AC treated groups. In addition, MMP expressions were significantly suppressed in the AC treatment group due to increased levels of TIMP-1. Conclusion: Taken together, these data indicate that exposure to AC reduces the oxidative stress by inhibiting the expression of NADPH oxidase (NOX2 and p22^phox) through the Nrf2 signaling pathway. We therefore propose the potential of AC for the prevention and treatment of TAA-induced liver injury.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.469-482
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• 2022

The purpose of this study is to analyze regional variation factors of hypertension treatment rate in COVID-19 based on the analysis results based on ecological methodology. To this end, data suitable for ecological analysis were collected from the Korea Centers for Disease Control and Prevention's regional health statistics, local government COVID-19 confirmed cases, National Health Insurance Corporation, Health Insurance Review and Assessment Service's welfare statistics, and Korea Transport Institute's traffic access index. Descriptive statistics and correlation analysis were conducted using SPSS Statistics 23 for regional variation and related factors in hypertension treatment rate, and geographical weighted regression analysis was conducted using Arc GIS for regional variation factors. As a result of the study, the overall explanatory power of the calculated geo-weighted regression model was 27.6%, distributed from 23.1% to 33.4% by region. As factors affecting the treatment rate of hypertension, the higher the rate of basic living security medical benefits, diabetes treatment rate, and health institutions per 100,000 population, the higher the rate of hypertension treatment, the lower the number of COVID-19 confirmed patients, the lower the rate of physical activity, and the alcohol consumption. Percentage of alcohol consumption decreased due to COVID-19 pandemic. It was analyzed that the lower the ratio, the higher the treatment rate for hypertension. Based on these results, the analysis of regional variables in the treatment rate of hypertension in COVID-19 can be expected to be effective in managing the treatment rate of hypertension, and furthermore, it is expected to be used to establish community-centered health promotion policies.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.10-18
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• 2022

Purpose: For smooth performance of flood analysis due to heavy rain disasters at energy storage facilities in the Incheon area, field surveys, observational surveys, and pre-established reports and drawings were analyzed. Through the field survey, the characteristics of pipelines and rivers that have not been identified so far were investigated, and based on this, the input data of the SWMM model selected for inundation analysis was constructed. Method: In order to determine the critical duration through the probability flood analysis according to the calculation of the probability rainfall intensity by recurrence period and duration, it is necessary to calculate the probability rainfall intensity for an arbitrary duration by frequency, so the research results of the Ministry of Land, Transport and Maritime Affairs were utilized. Result: Based on this, the probability of rainfall by frequency and duration was extracted, the critical duration was determined through flood analysis, and the rainfall amount suggested in the disaster prevention performance target was applied to enable site safety review. Conclusion: The critical duration of the base was found to be a relatively short duration of 30 minutes due to the very gentle slope of the watershed. In general, if the critical duration is less than 30 minutes, even if flooding occurs, the scale of inundation is not large.

• Smart Media Journal
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• v.11 no.5
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• pp.9-16
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• 2022

Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.87-94
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• 2022

Recently, with the development of information and communication infrastructure, the number of Internet access devices is rapidly increasing. Smartphones, laptops, computers, and even IoT devices are receiving information and communication services through Internet access. Since most of the device operating environment consists of web (WEB), it is vulnerable to web cyber attacks using web shells. When the web shell is uploaded to the web server, it is confirmed that the attack frequency is high because the control of the web server can be easily performed. As the damage caused by the web shell occurs a lot, each company is responding to attacks with various security devices such as intrusion prevention systems, firewalls, and web firewalls. In this case, it is difficult to detect, and in order to prevent and cope with web shell attacks due to these characteristics, it is difficult to respond only with the existing system and security software. Therefore, it is an automated defense system through the collection and analysis of web shells based on artificial intelligence machine learning that can cope with new cyber attacks such as detecting unknown web shells in advance by using artificial intelligence machine learning and deep learning techniques in existing security software. We would like to propose about. The machine learning-based web shell defense system model proposed in this paper quickly collects, analyzes, and detects malicious web shells, one of the cyberattacks on the web environment. I think it will be very helpful in designing and building a security system.