• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.13-23
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• 2021

In this study, we performed a Random Walker analysis to predict the Major Movement Paths of otters. The scope of the research was a simulation analysis with a radius of 7.5 km set as the final range centered on the Ansim-wetland in Daegu City, and a field survey was used to verify the model. The number of virtual otters was set to 1,000, the number of moving steps was set to 1,000 steps per grid, and simulations were performed on a total of 841 grids. As a result of the analysis, an average of 147.6 objects arrived at the boundary point under the condition of an interval of 50 m. As a result of the simulation verification, 8 points (13.1%) were found in the area where the movement probability was very high, and 9 points (14.8%) were found in the area where the movement probability was high. On the other hand, in areas with low movement paths probabilities, there were 8 points (13.1%) in low areas and 4 points (6.6%) in very low areas. Simulation verification results In areas with high otter values, the actual otter format probability was particularly high. In addition, as a result of investigating the correlation with the otter appearance point according to the unit area of the evaluation star of the movement probability, it seems that 6.8 traces were found per unit area in the area where the movement probability is the highest. In areas where the probability of movement is low, analysis was performed at 0.1 points. On the side where otters use the major movement paths of the river area, the normal level was exceeded, and as a result, in the area, 23 (63.9%), many form traces were found, along the major movement paths of the simulation. It turned out that the actual otter inhabits. The EN-Simulator analysis can predict how spatial properties affect the likelihood of major movement paths selection, and the analytical values are used to utilize additional habitats within the major movement paths. It is judged that it can be used as basic data such as to grasp the danger area of road kill in advance and prevent it.

• Journal of Nutrition and Health
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• v.54 no.2
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• pp.179-198
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• 2021

Purpose: This study examined general characteristics, health status, accessibility to medical services, health-related quality of life, dietary behavior, and energy and nutrient intakes of the elderly at different levels of food security utilizing data from the 7th Korea National Health and Nutrition Examination Survey (2016-2018). Methods: The elderly subjects (1,721 males and 2,271 females) were divided into 3 groups (secure, mildly insecure, moderately/severely insecure) according to their food security levels. Health and nutrient status was determined using energy intake, nutrient density, the prevalence of insufficient nutrient intake, dietary behavior, and health status. Results: The elderly with food insecurities had a lower self-evaluated health status and a higher prevalence of physician-diagnosed chronic diseases such as arthritis, osteoarthritis, rheumatoid arthritis, osteoporosis for males, and hypertension, stroke, arthritis, and osteoarthritis for females. The associated financial burden was the major reason for not accessing medical services in the food insecure group. Furthermore, the food insecure group had a higher risk of impaired health-related quality of life compared to the secure group. The proportion of subjects with an energy intake below the estimated energy requirement was higher in the food insecure group and a significantly higher prevalence of insufficient intake was observed for all the nutrients (proteins, vitamin A, vitamin B₁, vitamin B₂, niacin, vitamin C, calcium, and iron) assessed in this study compared to the food secure group. Conclusion: This study suggests that food insecurity poses a challenge to the health and nutritional status of the elderly population in Korea and needs proper management. It would be helpful to develop food and nutrition assistance programs to ensure the food stability of the elderly population and assure quality to address gaps in their nutrient intake.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• 한국노년학
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• v.41 no.4
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• pp.547-566
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• 2021

The purpose of this study is to analyze the effect of social activities on healthy life expectancy (HLE) by gender difference. HLE implies an estimate of how long an individual can expect to live in full health or without disease and/or disability. Morbidity, mortality, and functional health status usually have been known as key variables. Many researchers have tried to investigate factors affecting HLE in countries level by performing comparative analyses. In micro level, there have been some studies about social factors affecting HLE in individual level. However, few studies are found focusing on the relationship between HLE and social activities. This study anlayzes 4,029 over 65 years of age from the first wave (2006) to the seventh wave (2018) of the Korean Longitudinal Study of Ageing (KLoSA), which is a national panel data collected by Korea Employment Information Service. The data has been collected as a part of social and economic policies planning for Korean government. HLE was measured by life period without disease or disability. One of findings is that male older adults (76.9 yrs) show higher HLE in comparing to female group (75.3 yrs). Female group appeared to be more likely to have higher incidence rate and disorders. Another finding indicates that age, number of chronic diseases, and subjective health status affect HLE of both groups. Finally, regarding social activities, religion affiliated activities appear to significantly affect HLE of both groups. In case of male older adults, alumni or hometown gathering also appeared another activities affecting HLE. This study indicates that the effect of social activities types on HLE among older adults appears differently by gender. Further, unlikely of longer life expectancy among female older adults as known, HLE shows a reverse estimate, longer healthy life expectancy among male older adults. This finding may imply that later life of female older adults shows lower quality of life in comparing to that of male group, even if female life expectancy has been higher. This study encourages to develop more social activity programs for older adults in community level. Specifically, more attention is required to planning for programs targeting female older adults.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.2
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• pp.127-136
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• 2022

Objectives : The study aimed to identify factors associated with suicidal attempt in Korean adults experiencing thoughts of suicide. Methods : This study analyzed outcomes of suicidal behavior in the Korea National Health and Nutrition Examination Survey (KNHANES) 2015, 2017, and 2019. This survey was administered by the Korea Centers for Disease Control and Prevention (KCDC). The suicidal idea group was divided into individuals who had attempted suicide (n=92) and those who had not (n=831). Complex samples crosstabs analysis was conducted to compare the two groups' sociodemographic, psychiatric, and clinical characteristics. In addition, factors related to attempted suicide were investigated using complex samples logistic regression analysis. Results : The attempted suicide group had significantly higher rates of depression, recent psychiatric counseling, and suicidal plan (p<0.001) than the non-attempting group. In addition, the groups differed significantly in the frequency of binge drinking and smoking (p<0.05). Adjusted multivariate analysis revealed that the presence of a suicidal plan (Odds ratio [OR]=8.46, 95% Confidential Intervals [CI]=4.72-15.00), daily binge drinking (OR=3.14, 95% CI=1.26-7.84), psychiatric counseling within the past year (OR=3.03, 95% CI=1.75-5.23), low income level (OR=2.89, 95% CI=1.17-7.10), and history of depression (OR=2.39, 95% CI=1.29-4.42) were significantly associated with suicidal attempt. Conclusions : Factors associated with suicidal attempt among suicidal ideators in the general Korean population were identified across all sociodemographic, psychiatric, and clinical variables. Assessment of and intervention in suicidal plan, binge drinking, income level, and depression might prevent progression to suicidal attempt among those contemplating suicide.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.121-142
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• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Korean Journal of Forensic Psychology
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• v.12 no.1
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• pp.15-33
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• 2021

In this study, we analyzed the difference in survival rates of those subject to electronic supervision of sex crimes based on the tracking of the period of recidivism and whether they were recidivism, and wanted to confirm the ability of the criminal record to predict recidivism. The criteria for recidivism were defined as cases where a conviction was confirmed due to a criminal case that occurred during the execution of electronic monitoring, and the date of recidivism was the date of occurrence of a case that was confirmed guilty. A total of 122 re-offenders were used in the analysis, and all of them were charged with electronic supervision for committing sex crimes. Studies have confirmed that the subjects commit the most recidivism within three years. In addition, in this study, the difference in survival rate between groups was analyzed after classifying mixed and sex recidivism cases. The number of members was 88 for the mixed recidivism group and 34 for the sex recidivism group. The analysis confirmed that both groups had the most recidivism within three years. There was a slight difference between the survival rate of the mixed recidivism group and the survival rate of the sex recidivism group. So the Log Rank Test and the Generalized Wilcoxon Test were conducted, but no statistically significant differences were identified(Wilcoxon statistic = 2.326, df = 1, p = .13, Log Rank = 1.345, df = 1, p = .25). Next, a Cox Regression analysis was performed to confirm the ability of the criminal record to predict recidivism. As a result, the number of criminal records(sex offense, violent crime) have been confirmed to be a good predictor of recidivism(X²=27.33, df=1, p< .001). As a result, the recidivism rate is gradually decreasing due to the implementation of the electronic monitoring. However, the duration of recidivism required by sex offenders in high-risk groups was found to be rather short. Currently, security measures against felons are being strengthened, so it is necessary to select high-risk groups. Therefore, based on the related studies, the characteristics of high-risk groups and the results of recidivism studies will be used as a basis for disposal within the criminal justice system, which will play a major role in granting objectivity.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.