• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.703-710
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• 2018

Although various efforts have been made every year to reduce electric fire accidents such as accident analysis and inspection for electric fire accidents, there is no effective countermeasure due to lack of effective decision support system and existing cumulative data utilization method. The purpose of this study is to develop an algorithm for predicting electric fire based on data such as electric safety inspection data, electric fire accident information, building information, and weather information. Through the pre-processing of collected data for each institution such as Korea Electrical Safety Corporation, Meteorological Administration, Ministry of Land, Infrastructure, and Transport, Fire Defense Headquarters, convergence, analysis, modeling, and verification process, we derive the factors influencing electric fire and develop prediction models. The results showed insulation resistance value, humidity, wind speed, building deterioration(aging), floor space ratio, building coverage ratio and building use. The accuracy of prediction model using random forest algorithm was 74.7%.

• Journal of Wetlands Research
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• v.21 no.3
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• pp.215-223
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• 2019

In this study, we analyzed the water quality characteristics of major tributaries of Nakdong River through statistical analysis such as correlation analysis, principal component and factor analysis, and cluster analysis. Organic matter and nutrients are highly correlated, and are high in spring and autumn, and seasonal water quality management is required. Principal component and factor analysis showed that 82% of total variance could be explained by 4 principal components such as organic matter, nutrients, nature, and weather. BOD, COD, TOC, and TP items were analyzed as major influencing factors. As a result of the cluster analysis, the four clusters were classified according to seasonal organic matter and nutrient pollution. Kumho River watershed showed high pollution characteristics in all seasons. Therefore, effective management of water quality in tributary streams requires measures in consideration of spatio-temporal characteristics and multivariate statistical techniques may be useful in water quality management and policy formulation.

• Environmental and Resource Economics Review
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• v.28 no.2
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• pp.177-200
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• 2019

Energy demand forecast which serves as an essential input in energy policy is exposed to multiple factors of uncertainty such as GDP and weather forecast uncertainty. The Master Plan of Electricity Market in Korea which is biennially prepared is critically based on fluctuating energy demand forecast whereas its resulting proposal on electricity generation mix is substantially irreversible. The paper provides a real options model to evaluate energy transition policy by considering Knightian uncertainty as a measure to study multiple uncertainties with multiple set of probability distributions. Our finding is that the current energy transition policy under the master plan is not robust in terms of securing stable management of electricity demand and supply system.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.218-237
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• 2018

The purpose of this study is to propose a mid - range low - orbit water disaster monitoring satellite development plan to revolutionize water disaster management infrastructure through securing an independent and leading observation infrastructure and to secure safety against disaster prepared for climate change. Water and water disaster satellites should be able to detect changes in the surface of the ground and observe hydrological factors during daytime, nighttime, and bad weather. In addition, independent technology development should be possible. To do this, we selected C-band image radar payload considering domestic technology and water resources management, and suggested detailed development plan. In this way, it is reflected in the national next-generation mid-satellite 2-phase project plan to secure the basis for building a disaster monitoring system related to wide-area water.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.589-601
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• 2019

Various applications of radar rainfall data have been actively employed in the field of hydro-meteorology. Since radar rainfall is estimated by using predefined reflectivity-rainfall intensity relationships, they may not have sufficient reproducibility of observations. In this study, a generalized linear model is introduced to better capture the Z-R relationship in the context of bias correction within a Bayesian regression framework. The bias-corrected radar rainfall with the generalized linear model is more accurate than the widely used mean field bias correction method. In addition, we analyzed variability of the bias correction parameters under various geomorphological conditions such as the height of the weather station and the separation distance from the radar. The identified relationship is finally used to derive a regionalized formula which can provide bias correction factors over the entire watershed. It can be concluded that the bias correction parameters and regionalized method obtained from this study could be useful in the field of radar hydrology.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.38-39
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• 2019

Optimal route planning is the route planning to minimize voyage time or fuel consumption in a given ocean environment. Unlike the previous studies on weather routing, this study proposes an optimization method for the route planning to avoid the grounding risk in the coast. The route way-points were searched using Dijkstra algorithm, and then the optimization was performed to minimize fuel consumption by setting the optimization design parameter to the engine rpm. To set the engine rpm, a method to use the fixed rpm from the departure point to the destination point, and a method to use the rpm for each section by dividing the route were used. The ocean environmental factors considered for route planning were wind, wave, and current, and the depth information was utilized to compute grounding risk. The proposed method was applied to the ship passing between Mokpo and Jeju, and then it was confirmed that fuel consumption was reduced by comparing the optimum route and the past navigated route.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.157-162
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• 2019

Recently, the occurrence of unusual heavy snow and cold are increasing due to the unusual global climate change. In particular, the temperature dropped to minus 69 degrees Celsius in the United States on January 8, 2018. In Korea, on February 17, 2014, the auditorium building in Gyeongju Mauna Resort was collapsed due to the heavy snowfall. Because of the tragic accident many studies on the reduction of snow damage is being conducted, but it is difficult to predict the exact damage due to the lack of historical damage data, and uncertainty of meteorological data due to the long distance between the damaged area and the observatory. Therefore, in this study, available data were collected from factors that are thought to be corresponding to snow damage, and the amount of snow damage was estimated categorically using a random forest. At present, the prediction accuracy was not sufficient due to lack of historical damage data and changes of the design code for green houses. However, if accurate weather data are obtained in the affected areas. the accuracy of estimates would increase enough for being used for be the degree preparedness of disaster management.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.111-117
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• 2019

The purpose of this study was a convergence study to find a way to shorten pre-hospital emergency medical response time in vehicle accident. This study analyzed the factors of hospital emergency response time by utilizing weather, road type, accident type, and rescue response to 353 vehicle passengers who visited the three emergency medical centers from January 1, 2011 to July 30, 2016 in Korea In-Depth Accident Study. The results of the study showed that the highway used the most time to prehospital emergency medical response time and was a factor affecting the overall time (${\beta}=.543$, p<.001). In order to shorten the emergency medical response time in highway, the operation of emergency services on the highway, the active use of emergency turn road and the automatic emergency rescue service with individual devices were proposed.

• Korean Journal of Medicinal Crop Science
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• v.28 no.6
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• pp.463-470
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• 2020

Background: Evaluation of transpiration is required for agricultural and environmental management applications, as crop yields and plant growth are primarily water limited. This study aimed to determine the transpiration and carbon accumulation of Cnidium officinale. Methods and Results: The transpiration of C. officinale was evaluated using weighing lysimeter. The relationship between transpiration and factors such as solar radiation, air temperature, and leaf area was assessed. Transpiration increased as the leaf area increased with the growth stage. Furthermore, daily transpiration per unit leaf area was 0.69 ± 0.16 g·cm-2·day-1 and there were no significant differences in daily transpiration during the cultivation period. The maximum transpiration was 620.6 g m-2·h-1 and diurnal changes in transpiration were highly correlated with solar radiation although the maximum transpiration was observed at the air temperatures of 20℃ - 26℃. The ratio of carbon accumulation to transpiration was 0.12%. Conclusions: Our results indicated that the transpiration of C. officinale is primarily regulated by solar radiation energy on clear days and that 97% of the water is discharged through transpiration for heat dissipation. Therefore, weighing lysimeters can measure transpiration accurately and may be useful in interpreting plant growth.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.8
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• pp.101-109
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• 2019

Korea's transportation paradigm is shifting from a vehicle-oriented transportation plan to a pedestrian-friendly environment that emphasizes walking safety. However, the level of pedestrian traffic accidents in Korea is still high and serious. The purpose of this study is to investigate factors affecting the severity of pedestrians traffic accidents using the multilevel logistic regression model based on 2015-2017 pedestrian accidents data provided by the Traffic Accident Analysis System(TAAS). The main results of the multilevel logistic regression model showed that 89% of pedestrian traffic accidents in Seoul were explained by individual characteristics such as drivers and pedestrians, and 11% were explained by neighborhood environmental characteristics. The results are as follows : In the individual characteristics such as pedestrians and drivers, the older the pedestrians and the drivers, the higher the traffic accident severity. The severity of traffic accidents was high when the pedestrians were female and the drivers were male. In the case of accident types, traffic accidents were more serious in the cases of heavy vehicles, inclement weather, and occurring at intersections and crosswalks. The results of the neighborhood environmental characteristics are as follows. The intersection density and the crosswalk density tended to reduce the severity of traffic accidents. On the other hand, the traffic light density and the school zones were founded to related to the higher level of traffic accident severity. This study suggests that both individual and neighborhood environmental characteristics should be considered together to prevent and reduce the severity of pedestrian traffic accidents.