• Journal of The Korean Society of Emergency Medicine
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• v.29 no.6
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• pp.603-615
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• 2018

Objective: We analyzed the association between regional weather and temporal changes on the daily occurrence of trauma emergencies and their severity. Methods: In this cross-sectional prospective study, we investigated daily atmospheric patterns in trauma episodes in 1,344 patients in Cheongju city, South Korea, from January 2016 to December 2016 and analyzed the association of trauma occurrence and Injury Severity Scores (ISS) with weather conditions on a daily scale. Results: The mean age of trauma patients was $53.0{\pm}23.8years$ and average ISS was $9.0{\pm}2.0$. Incidence of trauma was positively correlated with average temperature (r=0.512, P<0.001) and atmospheric pressure (r=0.332, P=0.010) and negatively correlated with air pollutants (particulate matter less than $2.5{\mu}m^3$ [PM2.5], r=-0.629, P<0.001; particulate matter less than $10{\mu}m^3$ [PM10], r=-0.679, P<0.001). ISS was not significantly correlated with climate parameters and air pollutants, and variability was observed in the frequency and severity of trauma by time of day (highest occurrence, 16-20 pm; highest ISS, 4-8 am), day of the week (highest occurrence and highest ISS, Saturday), month of the year (highest occurrence, July; highest ISS, November), and season (highest incidence, summer; highest ISS, autumn). Conclusion: The study shows a positive relationship between trauma occurrence and specific weather conditions, such as atmospheric temperature and pressure. There was a negative relationship between concentrations of PM2.5 or PM10, and trauma occurrence. However, no correlation was observed between weather conditions or the concentrations of air pollutants and ISS. In addition, seasonal, circaseptan, and circadian variations exist in trauma occurrence and severity. Thus, we suggest that evaluation of a larger, population-based data set is needed to further investigate and confirm these relationships.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.1
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• pp.45-51
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• 2006

This paper proposes a method to evaluate the Total Transfer Capability (TTC) by considering uncertainty of weather conditions. TTC is limited not only by the violation of system thermal and voltage limits, but also restricted by transient stability limit. Impact of the contingency on the power system performance could not be addressed in a deterministic way because of the random nature of the system equipment outage and the increase of outage probability according to the weather conditions. For these reasons, probabilistic approach is necessary to realize evaluation of the TTC. This method uses a sequential Monte Carlo simulation (MCS). In sequential simulation, the chronological behavior of the system is simulated by sampling sequence of the system operating states based on the probability distribution of the component state duration. Therefore, MCS is used to accomplish the probabilistic calculation of the TTC with consideration of the weather conditions.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.4
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• pp.45-55
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• 2003

Weather conditions have played a vital role in a war. Many historical records reported that the miss use of weather information is the main reason of the lost a war. In this study we demonstrated the possibility of applying the numerical weather prediction system(NWPS) for military operations. The NWPS consists of PC-cluster as a super computer, data assimilation system ingesting many remote sensing observation, and graphic systems. High resolution prediction in NWPS can provide useful weather information such as wind, temperature, sea fog and so on for military operations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.561-564
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• 2007

Recently, The detection of weather conditions and weather related hazards with a weather radar are being actively investigated based on the echo intensity and the Doppler spectrum analysis. For this purpose, many types of simulated weather signals are needed for investigation. Therefore, this paper analyzed the method to simulate the many weather radar signals.

• Journal of Environmental Science International
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• v.5 no.4
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• pp.453-462
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• 1996

This study was conducted to evaluate the level of atmospheric heavy metals and the relationship of that concentration with weather conditions. This research monitored the concentration of Total Suspended Particulates (TSP) at every three hours by using High Volume Air Sampler from December 24th, of 1995 to Febuary 20th, 1996 in Kimhae area, which recently became a rapidly growing residential and industrial sitc. The items such as air-temperature, relative humidity, radition, wind speed, and wind direction were monitored by using Atmospheric Weather System at the same time. From the collected TSP, the concentration of heavy metals were analyzed by using the Atomic Absorption Spcetrophotometry. The mean concentration of TSP was 110.4 $\mu\textrm{g}$/$m^3$, and the mean concentration of lead (Pb), copper(Cu), chromium (Cr), manganese (Mn), cadmium (Cd), were 0.837 $\mu\textrm{g}$/$m^3$, 0486 $\mu\textrm{g}$/$m^3$, 0.264$\mu\textrm{g}$/$m^3$). The concentration of Pb and Mn was higher in the moring and that of Cu, Cr and Cd was higher in the afternoon and the evening. Regarding the relationship between the concentration of pollutants and weather condition, the-concentration TSP revealed positive correlation with temperature, humidity, wind speed, but negative correlation with tradition (p<0.01). The concentration of Mn revealed positive correlation with temperature and humidity, but negative correlation with wind speed (p<0.01). And the the concentration of pollutants and weather condition revealed higher correlation within the same time period. In summary, the paralleled mornitoring of air conditions and weather condition should be recommended to. get the correct informations concerning the pollution and to prevent the deterioration of air conditions.

• 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.

• Journal of Ginseng Research
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• v.40 no.1
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• pp.90-96
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• 2016

Background: Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Methods: Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Results: Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between $8^{\circ}C$ and $27^{\circ}C$, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Conclusion: Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.85-96
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• 2023

The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

• Journal of Climate Change Research
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• v.8 no.2
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• pp.171-175
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• 2017

The purpose of the farmstead-specific early warning service system for weather risk management is to develop custom-made risk management recommendations for individual farms threatened by climate change and its variability. This system quantifies weather conditions into a "weather risk index" that is customized to crop and its growth stage. When the risk reaches the stage where it can cause any damage to the crops, the system is activated and the corresponding warning messages are delivered to the farmer's mobile phone. The messages are sent with proper recommendations that farmers can utilize to protect their crops against potential damage. Currently, the technology necessary to make the warning system more practical has been developed, including technology for forecasting real-time weather conditions, scaling down of weather data to the individual farm level and risk assessments of specific crops. Furthermore, the scientific know-how has already been integrated into a web-based warning system (http://new.agmet.kr). The system is provided to volunteer farmers with direct, one-on-one weather data and disaster warnings along with relevant recommendations. In 2016, an operational system was established in a rural catchment ($1,500km^2$) in the Seomjin river basin.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.317-330
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• 2013

The yield of rice production is affected severely by abnormal weather events, such as flood, drought, high temperature etc. The objective of this paper is to assess impacts of abnormal weather events on rice production, using a panel model which analyzes both cross-section data and ti- me series data. Abnormal weather is defined as the weather event which goes beyond the range of ${\pm}2{\sigma}$ from the average of a weather factor. The result of an analysis on impacts of high temperature on rice production showed that the yield of rice was decreased 5.8% to 16.3% under the conditions of extremely high temperature, and it was decreased 8.8 to 20.8% under the conditions of both extremely high and heavy rain. Adaptation strategies, development of new varieties enduring high temperature and heavy rain, adaptation of crop insurance, modernization of irrigation facilities are needed to minimize the impacts of abnormal weather on rice production, and to stabilize farmers' income.