• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.492-496
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• 2007

This paper focused on "the information management for the disaster prevention", which is based on If, which copes with partial or whole national disaster effectively and which helps to reduce the damage by natural or artificial disasters promptly.

• Journal of the Korean Geotechnical Society
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• v.28 no.10
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• pp.89-96
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• 2012

In this study landslide causal factors which are considered to have the same effect in assessment techniques are categorized and their impact on landslides is analyzed to acquire reasonable weighting factors in the landslide hazard. Results are compared to those of the Assessment Chart developed by National Institute for Disaster Prevention (NIDP) and the adequacy and proper portion for landslide causal factors are considered. The Artificial Neural Network (ANN) method applied to 28 landslide areas is incorporated to evaluate the reasonable rating. Results show that the following items in the Chart are necessary to modify their portions in order to implement the precise assessment results: 1) Estimated damage; 2) Tension crack; 3) Existence of valley.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.759-763
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• 2010

Currently available evaluation checklists are developed for specific purposed using different parameters and items determined by different weighting factors. Those items with different weighting are sometimes said that they are based on the engineering judgement and leap of faith and, therefore, there is a limitation to adapt those checklists for slope-stability evaluation in the field. This study reviews factors affecting Rock-slope stability, analyze the relationship between those factors and slope failures using artificial neural network, and proposed a slope-stability evaluation model for adequate weighting for the factors.

• Journal of the Society of Disaster Information
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• v.11 no.3
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• pp.406-412
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• 2015

Recently, frequent earthquakes can cause serious damage to the bridge. So newly constructed bridge is considered earthquake resistant design, and for the existing old bridge evaluation of damage state is needed. In this paper, replacement of US-artificial earthquakes which are used for the construction of fragility curve for evaluating damage state to Korean artificial earthquakes to meet the Korean specifications is studied. For the generation of artificial earthquakes, the fragility curves are constructed for the PGA, for the cases of having isolated bearing and not having that.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.755-770
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• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.741-753
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• 2018

Local drought in South Korea has recently increased interest in the efficient use of groundwater and then induces a growing need to introduce artificial recharge of groundwater that stores water in sedimentary layer. In order to evaluate the potential artificial recharge sites in the alluvial basins in Chungcheongnamdo province, an AHP (Analytical hierarchy process) model consisting of three primary and seven secondary factors was developed in this study. In the AHP model, adding candidate sites changes final evaluation score through a mathematical calculation process. By contrast ANN (Artificial neural network) model always provides an unchanged score for each candidate area. Therefore, the score can be used as a selection criterion for artificial recharge sites. It is concluded that the possibility of artificial recharge is relatively low if the score of the ANN model is less than about 1.5. Further studies and field surveys on the other regions in Korea will lead to draw out a more applicable ANN model.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.127-136
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• 2022

This study was conducted using a multiple regression model to empirically analyze the impact of personal emotions and social change perceptions of pandemic experienced by Korean people in the COVID-19 situation on the perception of disaster response after the endemic. For this end, we used the survey data with 996 respondents on 「Daily Changes of the People After COVID-19」conducted by the Korea Press Promotion Foundation. The results showed that COVID-19 positive emotions and social change perception factors had a positive (+) effect on disaster response perception, while the sense of community had a moderating effect that alleviated COVID-19 negative emotions which had a negative (-) effect. The most influential factors on disaster response perception after the endemic were COVID-19 positive emotions and community sense that had pride and stability in Korean society during disaster situations. Therefore, this study suggests that systematic disaster response manuals and control towers that give the public pride and stability are more strongly requested for the government's prior and follow-up measures performed in the post-endemic disaster situation, and that the people are asked to have the community sense to overcome disasters together rather than to respond with personal actions and judgments.

• Health Policy and Management
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• v.28 no.3
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• pp.308-314
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• 2018

Injury is a serious problem that not only causes death but also significantly degrades the quality of life of the people and causes loss of socioeconomic opportunities and costs. Damage occurs as a result of an accident. Among them, natural disasters and artificial disasters take lives of many people in a short time and threaten their physical and mental health. The United States has responded to the disaster by establishing relevant laws and regulations and a response system with the recognition that health is recognised soon to be as national security in the wake of the 9/11 terrorist attacks and the Katrina disaster. It is necessary to build a knowledge infrastructure to train disaster response experts in public health area and to have health competence to cope with disasters.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.421-431
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• 2023

Purpose: The purpose of this study is to analyze the safety and disaster prevention effects of the Smart Safety System used to prevent safety accidents in construction machinery and demonstrate its safety. Method: Among construction machines, the behavioral patterns of workers according to the presence or absence of a smart safety system were analyzed for excavators with high risk and frequent accidents. Result: When the smart safety system was installed in the construction machine, the safety of workers from accidents caused by constriction and collision with the construction machine was secured. Conclusion: It is judged that the smart safety system installed in construction machinery can increase the effectiveness of disaster reduction and major disaster prevention related to construction machinery.

• Journal of Ocean Engineering and Technology
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• v.33 no.6
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• pp.590-596
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• 2019

Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.