• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1011-1022
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• 2021

The Korea Coast Guard(KCG) is the only comprehensive maritime administrative agency in Korea that performs various tasks taking place in the ocean, including rescue operations, disaster management, policing, Drug and smuggling crackdown, responding to Response to invasion of maritime territory, environmental conservation, and maritime security. It is vital to inform the public of the role and mission of KCG as the only comprehensive maritime administrative agency in Korea. However, most citizens, excluding residents of the coastal and island areas, have little knowledge of the security administration services of the KCG due to lack of exposure. This study reviewed the KCG's public relations(PR) organization and current status using KCG promotional materials, diagnosed the actual conditions of KCG's PR, and suggested ways to improve public relations activities through a questionnaire survey of public relations personnel. Through literature research and questionnaire survey, the KCG's public relations status was estimated and the measures to enhance publicity was derived as follows: strengthening the PR organization by reinforcing the personnel in charge of PR, improving customized promotion by clarifying the promotion strategy according to the promotion target, enhancing job training for PR personnel, and increasing the interest and support of commanders and internal members in charge of PR work.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.