• Proceedings of the KSR Conference
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• 2008.06a
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• pp.143-146
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• 2008

With unexpected torrential rainfall, flash flooding is occurring frequently and its impacts are tremendous. Thus proper natural disaster management plans are required. The disaster management system of the Bimodal tram utilizes the SWMM as a core engine to simulate runoff and urban sewer networks for flooding simulation. To develop the efficient Bimodal tram disaster management system, very detailed subcatchment boundaries and flow networks have to be developed in a GIS data format. Thus the objective of this study is to develop ArcView GIS based module (AV2SWMM) for easy preparation of model input for the tram disaster management system. With the AV2SWMM module, very detailed subcatchment boundaries and flow networks can be developed for accurate simulation of flash flooding at the study site, which were not/hardly possible with SWMM 5.0 interface. The AV2SWMM can be used in developing accurate model input for other regions where the Bimodal tram system is expected to be introduced.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.826-831
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• 2008

In this paper, an evaluation model of disaster management system which is developed by using GRI G3 version and BCP process for the sustainability management of small and middle enterprises was proposed. The proposed evaluation model can be used to evaluate the disaster management system directly, and to establish the disaster management system as an index. Also, the rules obtained by pattern analysis using fuzzy ID3 for the proposed evaluation model are expected to use the guideline effectively for self evaluation in the small and middle enterprises.

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.18-24
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• 2023

Severe natural disasters and man-made attacks such as terrorism are causing unprecedented disruptions in power systems. Due to rapid climate change and the aging of energy infrastructure, both the frequency of failure and the level of damage are expected to increase. Resilience is a concept proposed to respond to extreme disaster events that have a low probability of occurrence but cause enormous damage and is defined as the ability of a system to recover to its original function after a disaster. Resilience is a comprehensive indicator that can include system performance before and after a disaster and focuses on preparing for all possible disaster scenarios and having quick and efficient recovery actions after an incident. Various studies have been conducted to evaluate resilience, but studies on economic damage considering the duration of a power outage are scarce. In this study, we propose an optimal algorithm that can identify failures after an extreme disaster and restore the load on the distribution system through emergency distributed power generation input and system reconfiguration. After that, the cost of power outage damage is analyzed by applying VoLL and CDF according to each restoration strategy.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.351-362
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• 2017

Recently, analysis techniques to extract new meanings using big data analysis and various services using them have been developed. A disaster safety service among such services has been paid attention as the most important service. In this paper, we design and implement a flood disaster safety system using real time weather big data. The proposed system retrieves and processes vast amounts of information being collected in real time. In addition, it analyzes risk factors by aggregating the collected real time and past data and then provides users with prediction information. The proposed system also provides users with the risk prediction information by processing real time data such as user messages and news, and by analyzing disaster risk factors such a typhoon and a flood. As a result, users can prepare for potential disaster safety risks through the proposed system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.4
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• pp.359-365
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• 2006

Recently generated natural disaster of rainfall is transformed into nationwide generate form from a specific region of generated form that damages are steadily growing. such natural disaster lead to much influence such as socioeconomic, financial, physical and casualties etc, therefore model collection can be a step required establishment of systematically management foundation and offer of systematic solved plan. this study proposed to analyze and arrange pattern of disaster and systems designed plan and establishment further scientific, prompt service of disaster. with GIS technique for decision-making offer the necessary preliminary data. also, each city have orthophoto and digital elevation model that analyze real topography and situation. with establish management system in order to carry out appropriate service of disaster management and establish realistic management system. system had established that OpenGL make three dimensional illustrate scale image data and digital elevation model therefore a module of section analysis developed way to illustrate and to analyze topography and longitudinal section in screen.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.91-99
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• 2021

In the current business environment where dependence on IT has increased rapidly, the risk from disasters or cyber-attacks is also increasing. Business continuity, the ability to continue to provide service in the event of a business disruption caused by a disaster, is essential. In other words, you need to have a plan in place to keep your core business functions uninterrupted with rapid recovery within a predetermined Recovery Time Objective (RTO) and Recovery Point Objective (RPO) time frame. In this paper, we propose a disaster recovery system construction method that can minimize RTO and RPO to ensure business continuity. The system configuration adopts Tier 7 disaster recovery model, synchronous storage replication, hot disaster recovery site, and operation management automation solution. This ensures continuity of core business with virtually no data loss and minimal RTO and RPO.

• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.75-83
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• 2016

There are various types of disasters now, and accordingly it is practically difficult to manage all types of disasters effectively. If we are able to reconstruct the disaster event and investigate the cause, it may be possible to prepare the recurrence of similar patterns of disasters. The vehicle-based system equipped with state-of-the-art sensors has been proposed in order to reconstruct the disaster site as much as possible and help the disaster investigator to analyze the cause of the disaster by providing high-quality information. However, the data quality obtained from the sensors can be lowered due to unpredictable circumstances of disaster site. In this aspect it is essential to provide practical procedures that assess and analyze the performance of the equipment on site. In this paper, we selected critical elements of performance that can evaluate the vehicle-based image acquisition system, since it is the most critical piece of information in the disaster sites. The quality of the images obtained from vehicle-based image system was analyzed and verified on the test site. From the results of spatial resolution based on GRD(Ground Resolved Distance), we were able to identify maximum 5mm of spatial resolution at a distance of 70m distance. The result of field test is expected to be used for data acquisition plan in future disaster situations.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1167-1177
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• 2020

In this study, we established the process for collecting and utilizing video scripts of disaster site based on public-private partnerships. It is for the purpose of actively utilizing private capabilities in disaster management, and quickly sharing video scripts to identify field conditions. Based on the experience of actual operation of public-private partnerships system in the event of typhoon in 2019, we also derived implications for continuous operation of the process. Results are meaningful in that the government established the process for collecting and utilizing video scripts through public-private partnerships during the initial disaster response phase. And we also confirmed the possibility of spreading positive perception of disaster management organizations. However, there is a limit to the actualization and practical use of performance as an experimental pilot operation in the R&D stage. In addition, for continuous operation of the system, it is necessary to prepare institutional support measures such as organization, infrastructure for operating, programs of education and training, and policy making.

• Fire Science and Engineering
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• v.33 no.4
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• pp.163-174
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• 2019

This study examined the current situation of the problem and to suggest an improvement plan for the general public officers who are currently working as the Special Judicial Police for Disaster Safety in Gyeonggi-do and Kangwon-do provinces. The disaster safety special judicial police have the expertise of the investigative environment and human factors. The present situation of the operation was analyzed, and the problems, improvement plan, and activation plan of the system were derived. To cope with crime prevention, which is complicated and diversified progressively, this paper proposed the direction of reestablishing disaster safety special judicial police personnel for disaster safety.