• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.348-356
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• 2018

Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behavior and its spread. Thus, meteorological factors as well as topographical and forest factors were considered in the fire danger rating systems. This study aims to develop an advanced national integrated daily weather index(DWI) using weather data in the spring and fall to support forest fire prevention strategy in South Korea. DWI represents the meteorological characteristics, such as humidity (relative and effective), temperature and wind speed, and we integrated nine logistic regression models of the past into one national model. One national integrated model of the spring and fall is respectively $[1+{\exp}\{-(2.706+(0.088^*T_{mean})-(0.055^*Rh)-(0.023^*Eh)-(0.014^*W_{mean}))\}^{-1}]^{-1}$, $[1+{\exp}\{-(1.099+(0.117^*T_{mean})-(0.069^*Rh)-(0.182^*W_{mean}))\}^{-1}]^{-1}$ and all weather variables significantly (p<0.01) affected the probability of forest fire occurrence in the overall regions. The accuracy of the model in the spring and fall is respectively 71.7% and 86.9%. One integrated national model showed 10% higher accuracy than nine logistic regression models when it is applied weather data with 66 random sampling in forest fire event days. These findings would be necessary for the policy makers in the Republic of Korea for the prevention of forest fires.

• Journal of agricultural medicine and community health
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• v.45 no.4
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• pp.235-244
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• 2020

Objectives: Gyeongsangbuk-do has entered a super-aged society with 20.7% of the population aged 65 and older. As of April 30, 2020, the death rate of COVID-19(3.8 people) in Gyeongsangbuk-do is higher than the national mortality rate (2.3 people), and the fatality rate of COVID-19 by age accounts for more than half of the total of 58.6%, so it is time to propose to prevent infectious diseases in the event of additional infectious disease disasters COVID-19. Methods: We collected daily data on the number of confirmed cases and deaths due to COVID-19 from 19 February to 30 April 2020. The data collected was evaluated using the SPSS 21.0 statistical package. Results: As a result of comparing the incidence and death-related factors of confirmed patients in Gyeongsangbuk-do, there were significant differences in age group (p<0.001), underlying disease (p<0.001), and residence type (p<0.033). Conclusion: Factors affecting the mortality rate of confirmed patients in Gyeongsangbuk-do have been combined with individual level factors(age, gender, underlying disease), which means individual characteristics that have existed since before the disease, and regional level factors(Type of Residence), which are external factors that enable the use of medical resources. Therefore, each local government is required to establish preventive measures considering individual and regional level factors.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.53-62
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• 2023

Recently, due to the influence of climate change, the occurrence of damage to heavy rain is increasing around the world, and the frequency of heavy rain with a large amount of rain in a short period of time is also increasing. Heavy rains generate a large amount of outflow in a short time, causing flooding in the downstream part of the mountainous area before joining the small and medium-sized rivers. In order to reduce damage to downstream areas caused by flooding, it is very important to calculate the outflow of mountainous areas due to torrential rains. However, the sewage network flooding analysis, which is currently conducting the most analysis in Korea, uses the time and area method using the existing data rather than calculating the rainfall outflow in the mountainous area, which is difficult to determine that the soil characteristics of the region are accurately applied. Therefore, if the rainfall is analyzed for mountainous areas that can cause flooding in the downstream area in a short period of time due to large outflows, the accuracy of the analysis of flooding characteristics that can occur in the downstream area can be improved and used as data for evacuating residents and calculating the extent of damage. In order to calculate the rainfall outflow in the mountainous area, the rainfall outflow in the mountainous area was calculated using MIKE SHE among the MIKE series, and the flooding analysis in the downstream area was conducted through MIKE 21 FM (Flood model). Through this study, it was possible to confirm the amount of outflow and the time to reach downstream in the event of rainfall in the mountainous area, and the results of this analysis can be used to protect human and material resources through pre-evacuation in the downstream area in the future.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.1-8
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• 2024

Persistent droughts due to climate change will intensify water shortage problems in Korea. According to the 1st National Water Management Plan, the shortage of domestic and industrial waters is projected to be 0.07 billion m³/year under a 50-year drought event. A long-term prediction of water demand is essential for effectively responding to water shortage problems. Unlike industrial water, which has a relatively constant monthly usage, domestic water is analyzed on monthly basis due to apparent monthly usage patterns. We analyzed monthly water usage patterns using water usage data from 2017 to 2021 in Chungcheong, South Korea. The monthly water usage rate was calculated by dividing monthly water usage by annual water usage. We also calculated the water distribution rate considering correlations between water usage rate and climate variables. The division method that divided the monthly water usage rate by monthly average temperature resulted in the smallest absolute error. Using the division method with average temperature, we calculated the water distribution rates for the Chungcheong region. Then we predicted future water usage rates in the Chungcheong region by multiplying the average temperature of the SSP5-8.5 scenario and the water distribution rate. As a result, the average of the maximum water usage rate increased from 1.16 to 1.29 and the average of the minimum water usage rate decreased from 0.86 to 0.84, and the first quartile decreased from 0.95 to 0.93 and the third quartile increased from 1.04 to 1.06. Therefore, it is expected that the variability in monthly water usage rates will increase in the future.

• Sleep Medicine and Psychophysiology
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• v.24 no.1
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• pp.46-54
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• 2017

Objectives: Domestic violence is related to many psychiatric diseases, such as depression, anxiety disorder, and PTSD. Heart rate variability (HRV) is an index of autonomic control of the heart and is related to cardiovascular and emotional disorders. Although there have been some studies on the effects of domestic violence on women's mental health, relatively little information is available on HRV in this population. The aim of this study is to investigate demographic data, psychological features, and HRV in female victims of domestic violence and difference between Korean and foreign female victims. Methods: A total of 210 female victims of domestic violence (166 Korean women and 44 foreign women) were recruited for this study. Psychological symptoms were measured using the Hamilton Rating Scale for Anxiety (HAM-A), Hamilton Rating Scale for Depression (HAM-D), and Impact of Event Scale-Revised (IES-R). HRV measures were assessed by time-domain and frequency-domain analyses. Results: The mean score of HAM-A was 13.81, that of HAM-D was 12.92, and that of IES-R was 33.61 ; there were no significant differences between Korean and foreign women in these measures. In HRV time domain analyses, approximate entropy (ApEn) was significantly increased in foreign women compared to the Korean women. The square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) was significantly decreased in foreign women compared to Korean women. There were no significant differences in the other HRV variables between Korean and foreign women. Conclusion: Female victims of domestic violence in Korea are associated with depression, anxiety, and PTSD symptoms. The physiologic factors of a female victim's nationality could be related to higher ApEn and lower RMSSD in foreign female victims. These findings have important implications for future study to study the relationships among ethnic and environmental factors and HRV variables.

• Journal of Gifted/Talented Education
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• v.24 no.4
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• pp.509-541
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• 2014

There was a great need to consider a core competency-based approach as a new direction of the science education for gifted students according to the value and vision of the 21st century knowledge-based societies. Therefore we developed a core competency model of scientist and examined its validity as a prerequisite for a core competency-based education of science gifted students. In order to this, the survey was conducted after developing questionnaire through the theoretical review of the various resources such as paper, book, and newspaper articles and the qualitative analysis of the behavioral event interview, and then an exploratory factor analysis was performed to validate the factor structure based on the results of the survey. The results revealed that the core competency model with the 5 cluster units of competency and the 15 core competencies was potentially constituted. And the reliability, convergent validity, and discriminant validity of the core competency model were verified through the confirmatory factor analysis. The cognitive cluster consisted of 5 competencies and they were as follows: creative, comprehensive, exploratory, analytical, and conceptual thinking competency. The achievement-orientation cluster consisted of 3 competencies and they were as follows: initiative, preparation & problem solving, and strategic influence competency. The scientific attitude cluster consisted of 3 competencies and they were as follows: flexible thinking & attitude, passion for research, and views about science competency. The personal effectiveness cluster consisted of 2 competencies and they were as follows: diverse experiences and global attitude competency. Finally, the networking cluster consisted of 2 competencies and they were as follows: personal understanding and communication competency. Findings were expected to provide the basic data for developing programs and establishing strategies based on the core competency as well as introducing the core competency model of scientist to science education for gifted students effectively.

• Pediatric Infection and Vaccine
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• v.8 no.2
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• pp.135-149
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• 2001

Purpose : To describe the characteristics of the claims for compensation and the methodology of investigations concerning adverse events following immunization(AEFI) and epidemiologic characteristics of the AEFI. From these results, to give a suggestion for improving AEFI surveillance system, consequently to stabilize National Immunization Program. Methods : Totally 61 cases were reported to the National Compensation Program and surveillance system of AEFI from 1995 to 2000. Documents from National Compensation Program, medical records and epidemiologic investigation reports of the cases were collected and analyzed. Results : The number of reported cases was 12 in 1995, 3 in 1996, 12 in 1998, 5 in 1999, and 29 in 2000, respectively. That of deaths was 24(39.3%) and 16 cases among them were autopsied(66.7%). That of claims for compensation was 36 and 17 cases among them were compensated(47.2%). The proportion of claim was lower in 1999~2000 than in 1995~1998, but proportion of compensation increased. Although proportion of investigation was lower in 1999~2000 than in 1995~1998, cases which were not epidemiologically investigated, decreased. The epidemiologic investigation launched within 24 hours after report increased from 25% in 1995~1998 to 48.3% in 1999~2000. Among reported cases, the number of boys was 31(50.8%), and 75.4% of subjects were from 2 months to 24 months old. 78.4% of adverse events occurred within one week after immunization. Conclusion : We can find that surveillance system of AEFI and quality of epidemiologic investigation has been somewhat improved. But, it seems that severe cases were more frequently reported than moderate or mild cases, and reporting rate was lower than that of other developed countries. We could not identify the detailed epidemiologic characteristics of AEFI due to these limitation of data. To achieve the stabilization of National Immunization Program, reporting rate and the quality of investigation should be improved.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.917-930
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• 2017

To understand the temporal and spatial variations of surface chlorophyll-a concentration (Chl-a) distribution in the Indian Ocean ($30^{\circ}E{\sim}120^{\circ}E$, $30^{\circ}S{\sim}30^{\circ}N$) by the Indian Ocean Dipole (IOD), we conducted EOF and K means analyses of monthly satellite-derived Chl-a data in the region during 1998~2016 periods. Chl-a showed low values in the central region of the Indian Ocean and relatively high values in the upwelling region and around the marginal regions of the Indian Ocean. It also had a strong seasonal variation of Chl-a, showing the lowest value in the spring and the highest value in summer due to the change of the monsoon and current system. The EOF analysis showed that Chl-a variation in EOF mode 1 is related to ENSO (El $Ni{\tilde{n}}o$/Southern Oscillation) and that of mode 2 is linked to IOD. Both modes explained spatially opposite trends of Chl-a in the east and west Indian Ocean. From K means analysis, the Chl-a variation in the east and west Indian Ocean, and around India have relatively good relationship with IOD while that in the tropical and middle Indian Ocean closely associated with ENSO. The spatial and temporal distribution of Chl-a also showed distinct spatial and temporal variations depend on the different types of IOD events. IOD classifies two patterns, which occurred during the developing ENSO (First Type IOD) and the year following ENSO event (Second Type IOD). Chl-a variation in the First Type IOD started in summer and peaked in fall around the east and west Indian Ocean. Chl-a variation in the Second Type IOD occurred started in spring, peaked in summer and fall, and disappeared in winter. In the Chl-a variation related to IOD, developing process appearing in the Chl-a difference between the east and west Indian ocean was similar. Chl-a variation in the northern Indian Ocean were opposite trend with changing developing phase of IOD.