• Journal of Fisheries and Marine Sciences Education
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• v.23 no.3
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• pp.351-360
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• 2011

In order to reduce the casualties of fishing boats, the author analyzed the fishing boat accident on the 412 cases in Korean maritime safety tribunal for the 2005~2009, and then studied the relation between the weather element and the accidents. According to this studies, the occurring ratio of sea casualty for fishing boat in fog weather was appeared 1 boat per 1.6 days. It means that the restricted visibility condition gives the most influence on the fishing boat accident. The casualties in winter season from November to next January occurred 139(33.7%), and small boats less than 50tons broke out more casualties with 68.4%. From this we can find that small fishing boats are very deeply affected on the sea weather condition. According to the boat types for fishing the casualty of jig boat was ranked first, and collision accident account for first with 77.9% for the types of casualties. As mentioned above, most sea casualties for small fishing boats were resulted from the human factors such as poor watch keeping in invisibility and the bad sea condition, it is necessary for navigation operators and the manager to take more attention to the meteorological factors.

• The Plant Pathology Journal
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• v.39 no.6
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• pp.548-565
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• 2023

Armillaria root disease affects forests around the world. It occurs in many habitats and causes losses in the infested stands. Weather conditions are important factors for growth and development of Armillaria species. Yet, the relation between occurrence of damage caused by Armillaria disease and weather variables are still poorly understood. Thus, we used generalized linear mixed models to determine the relationship between weather conditions of current and previous year (temperature, precipitation and their deviation from long-term averages, air humidity and soil temperature) and the incidence of Armillaria-induced damage in young (up to 20 years old) and older (over 20 years old) coniferous stands in selected forest districts across Poland. We used unique data, gathered over the course of 23 years (1987-2009) on tree damage incidence from Armillaria root disease and meteorological parameters from the 24-year period (1986-2009) to reflect the dynamics of damage occurrence and weather conditions. Weather parameters were better predictors of damage caused by Armillaria disease in younger stands than in older ones. The strongest predictor was soil temperature, especially that of the previous year growing season and the current year spring. We found that temperature and precipitation of different seasons in previous year had more pronounced effect on the young stand area affected by Armillaria. Each stand's age class was characterized by a different set of meteorological parameters that explained the area of disease occurrence. Moreover, forest district was included in all models and thus, was an important variable in explaining the stand area affected by Armillaria.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.3 no.4
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• pp.359-372
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• 2005

The strong protection method of radiation emergency preparedness is the evacuation when a great deal of radionuclide material is released to environment. Required factors for evacuation time estimate of Ulchin nuclear power plant site were investigated. The traffic capacity and the traffic volume by season were investigated for the traffic analysis and simulation within EPZ of Ulchin site. As a result, the background traffic volume by season were established. The NETSIM code was applied to simulate for 12 scenarios in the event of normal traffic/summer peak traffic/winter peak traffic, daytime/night, and normal weather/adverse weather conditions. The results showed that the evacuation time required for total vehicles to move out from EPZ took generally $210\~315$ minutes. The evacuation time took longer about 45 minutes at night than in the daytime, and 45 minutes in adverse weather than normal condition.

• The Korean Journal of Emergency Medical Services
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• v.23 no.3
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• pp.123-134
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• 2019

Purpose: This study aimed to analyze the number of patients with and without medical history transported to the emergency department due to changes in daily temperature and season. Methods: Data on emergency activity sheet and daily weather were collected from March 2016 to February 2017 in the city of Gyeonggi-do. In total, 13,531 patients were transferred to the emergency department in 119 ambulance. Data were analyzed using the Statistical Package for the Social Sciences (version 21). Results: The daily average number of patients transferred was the highest in August and September, i.e., the summer season. The higher the daily highest and lowest temperatures, higher the daily average number of patients transferred. In contrast, patients with medical history of hypertension, diabetes, heart disease, cerebrovascular disease, and pulmonary disease had a higher incidence of transfers in the winter season and on days with lower temperature. Conclusion: The results indicate that as people become more active during the summer when temperatures are high, the chances of daily emergencies increases, whereas patients with medical history are more likely to experience emergencies when the temperatures were lower. Hence, 119 ambulances will have to be prepared in advance to deal with this trend.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.16-18
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• 2011

Evaluation of climate change on the rice productivity was conducted using crop growth simulation model, where Odae, Hwaseong, Ilpum were used as a representative cultivar of early, medium, and medium-late rice maturity type, respectively, and climate change scenario 'A1B' was applied to weather data for future climate change at 57sites. When cropping season was fixed, rice yield decreased by 4~35% as climate change which was caused by poor filled grain ratio with high temperature and low irradiation during grain-filling. When cropping season was changed, rice yield decreased by only 0~5% as climate change which was caused poor filled grain ratio with low irradiation during grain-filling period. However, this irradiation decline was less than when cropping season was fixed. Therefore, we need to develop rice cultivars resistant to low irradiation which can maintain high filled grain ratio under poor irradiation condition, and late maturity rice cultivars whose growing period is longer than the present medium-late maturity type.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.49-73
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• 1996

This study produces quantitatively weather entropy and information ratio using information theory about frequency in the appearance of precipitation phenomenon and monthly change, and then applies them to observation of the change of their space scale by time. As a result of these, this study defines Pusan, Chongju and Kwangju's weather representativeness and then establishes the range of weather representativeness. Based on weather entropy (statistical parameter)-the amount of average weather information-and information ratio, we can define each area's weather representativeness, which can show us more constant form included topographical, geographical factors and season change. The data used for this study are the daily precipitotion and cloudiness during the recent five years($1990{\sim}1994$) at the 69 stations in Korea. It is divided into class of no precipitation, that of precipitation. The results of this study can be summarized as follows: (1) The four season's mean value of information ratio is the highest value. as 0.641, on the basis of Chongju. It is the lowest as 0.572, on the basis of Pusan. On a seasonal basis, the highest mean value of information rate is April's (spring) in Chongju, and the lowest is October's(fall) in Pusan. Accordingly weather representativeness has the highest in Chongju and the lowest in Pusan. (2) To synthesize information ratio of decaying tendancy and half-decay distance, Chonju's weather representativeness has the highest in April, July and October. And kwangju has the highest value in January and the lowest in April and July. Pusan's weather representativeness is not high, that of Pusan's October is the lowest in the year. (3) If we establish the weather representative character on the basis of Chongju-Pusan, the domain of Chongju area is larger than that of Pusan area in October, July and April in order. But Pusan's is larger than Chongju's in January. In the case of Chongju and Kwangju, the domain of Chongju area is larger than that of Kwangju in October, July and April in order, but it is less than that of Kwangju area in January. In the case of Kwangju-Pusan, the domain of Kwangju is larger than that of Pusan in October, July in order. But in April it is less than Pusan's.

• Journal of Sericultural and Entomological Science
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• v.36 no.2
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• pp.110-114
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• 1994

Abnormally cool and wet weather conditions during the summer of 1993 offered an opportunity to evaluate the effects of abnormal weather conditions on mulberry growth and to develop cultivation practicies to reduce leaf yield loss under the similar abnormal weather conditions. Different methods of nutrient supplementation were evaluated in Suwon and Kongju. Nitrogen was supplemented by foliar spray of urea(1.7%) or composite chemical fertilizer Jamsibiryo #8, or by the application of ammonium sulfate(60kg/ha) to the soil. During the period between the late June and the early September which corresponds to the mulberry growing season after summer pruning, mean temperature was 1.4$^{\circ}C$ lower and precipitation 83mm higher than normal year. This weather condition in 1993 caused reduction in leaf yield by 16.4% than common year. Soil nitrogen content decreased due to higher precipitation. Leaf yield loss was reduced by the supplementation of nitrogen to the soil. Leaf nitrogen content increased with the foliar urea spray and nitrogen supplementation to the soil.

• Journal of Trauma and Injury
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• v.33 no.4
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• pp.248-255
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• 2020

Purpose: Trauma incidence and hospitalizations of trauma patients are generally believed to be affected by season and weather. The objective of this study was to explore possible associations of the hospitalization rate of trauma patients with weather and time variables at a single regional trauma center in South Korea. Methods: Trauma hospitalization data were obtained from a regional trauma center in South Korea from January 1, 2017 to December 31, 2019. In total, from 6,788 patients with trauma, data of 3,667 patients were analyzed, excluding those from outside the city where the trauma center was located. Hourly weather service data were obtained from the Korea Meteorological Administration. Results: The hospitalization rate showed positive correlations with temperature (r=0.635) and wind speed (r=0.501), but a negative correlation with humidity (r=-0.620). It showed no significant correlation (r=0.036) with precipitation. The hospitalization rate also showed significant correlations with time of day (p=0.033) and month (p=0.22). Conclusions: Weather and time affected the number of hospitalizations at a trauma center. The findings of this study could be used to determine care delivery, staffing, and resource allocation plans at trauma centers and emergency departments.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.249-260
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• 2022

Student pilots receiving flight education are inexperienced in piloting and situation judgment skills and are greatly affected by various factors such as psychological, physical, and environmental factors. In particular, one of the most influential factors in the flight education of student pilots is the weather conditions. Unlike large aircraft used in the air transportation business, small aircraft used for flight education have a great impact on education, such as flight restrictions depending on weather conditions, psychological pressure in severe weather, and deterioration of student skills. Therefore, in this study, the meteorological characteristics of meteorological factors that have a great influence on small aircraft were analyzed. As a result of the analysis, an efficient and safe training operation method was suggested to a professional pilot aviation training organization through the adjustment of the training period for the season, the increase in aircraft operation rate, and a safe solo flight plan considering the weather.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.136-136
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• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.