• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.285-286
• /
• 2023

우리 나라는 오래 전부터 민방위 차원에서 각 지역에 대피소를 선정해두고 정부 해당 부처의 게시판으로 알리고 있다. 그러나, 민방위 훈련이 거의 실시되지 않는 터라 대부분의 국민들은 어느지역에 어떤 대피소가 마련되어 있는지 알지 못한다. 최근에는 민방위 뿐만 아니라 바닷가 해일에 대비하기 위한 대피소도 늘어나고 있는데 이를 알고 있는 국민 또한 많지 않다. 따라서 이 연구에서는 현재 위치 주변에 어떤 대피소가 있는지와 가장 가까운 대피소까지의 길을 안내하는 긴급 대피소 안내 앱을 개발한다. 그 외에 이 앱은 지역별로 최근 발송된 재난 문자를 검색하는 기능도 제공한다.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.25 no.1
• /
• pp.211-224
• /
• 2015

Financial companies have invested a lot in their disaster recovery system and exercised training more than once a year to comply related laws and regulations. But massive PCs(Personal Computers) became disrupted simultaneously and it took a lot of time to recover massive PCs concurrently when March 20 cyber attack occurred. So, it was impossible to meet the tartgeted business continuity level. It was because the importance of PC recovery was neglected compared to other disaster recovery areas. This study suggests the measure to recover massive branch terminal PCs of financial companies simultaneously in cost-effective way utilizing the existing technology and tests recovery time. It means that in the event of disaster financial companies could recover branch terminal PCs in 3 hours which is recommended recovery time by regulatory body. Other financial companies operating similar type and volume of branches would refer to the recovery structure and method proposed by this study.

• Proceedings of the KAIS Fall Conference
• /
• 2009.12a
• /
• pp.774-777
• /
• 2009

2001년 9 11 테러 이후 미국에서 탄저균을 이용한 생물테러가 발생한 이래 미국을 비롯한 여러 나라에서는 생물무기 및 생물테러에 대한 대응방안들이 준비되고 있다. 따라서 이런 대응방안과 더불어 생물무기를 쓰는 테러리스트의 행동과 위협에 대비를 할 필요가 있다. 생물테러 전염병은 치명률이 높고, 인간 상호간에 전염이 용이하며 치료하기가 어려우므로, 인명의 손실을 최소화하기 위해서는 보건의료기관 등에서 근무하는 보건의료인이 생물테러로 의심되는 병원체 및 전염병을 조기에 인지하는 것이 가장 중요하다. 따라서 보건분야 전문가들은 환자나 일반 대중, 그리고 다른 보건전문가들에게 생물무기와 생물테러에 의해 퍼질 가능성이 있는 질병들에 대해 신중하게 대응할 수 있는 방법들을 교육해야 한다. 질병이 발생했을 때 보건전문가들은 조사에 착수할 역학자들과 협조를 해야 하고, 임상 또는 연구소에 일하는 보건전문가들은 생물무기로 사용될 수 있는 병원체나 생물무기를 생산하는데 사용되는 시설에 접근하는 것을 제한하도록 도울 수 있다. 2005년 질병관리본부 생물테러대응팀에서는 의료인, 다중시설이용 근무자, 보건요원을 대상으로 생물테러 인식도를 조사한 바 있다. 조사결과, 의료인에 대한 생물테러 교육 및 교육훈련의 필요성에 대해 94.2%가 필요하다고 응답하였다. 이런 자료를 바탕으로 하여 국내에서도 생물테러교육의 필요성이 대두되기 시작하였다. 본 연구는 미국, 영국에서 진행되고 있는 생물테러 관련 교육에 대한 관련 자료와 사례를 문헌 분석을 통해 우리나라에 맞는 생물테러 교육에 대한 방향을 제시하고 문제중심학습모듈을 개발하고자 하는데 그 목적이 있다.

• Journal of Industrial Convergence
• /
• v.22 no.3
• /
• pp.137-154
• /
• 2024

This study aimed to determine the characteristics of maternal stress during the COVID-19 pandemic. This review collected data from May 1 to August 10, 2023, focusing on literature published from 2020 on wards in English or Korean using key biomedical (PubMed, Embase, Cochrane Library, and CINAHL) and major Korean databases (RISS, KISS, and the National Library of Korea). The searched terms were "pregnan*," "maternity," "COVID," "corona," "pandemic," "infection," and "stress," as well as their Korean equivalents. In total, 13 papers were selected. The maternal stress level generally increased during the COVID-19 pandemic. The primary factors affecting maternal stress were the medical, psychological, and socio-economic factors. Interventions for stress reduction in pregnant women during the pandemic were found to be effective, such as online education and training This study can be used as a reference for developing stress reduction programs to prepare for novel infectious disease emergencies.

• Korean Journal of Construction Engineering and Management
• /
• v.14 no.6
• /
• pp.49-60
• /
• 2013

Evacuation process has been considered as one of the most important elements to be managed in public facilities. Although the importance is highlighted through numerous literatures, disaster evacuation planning, particularly fire accidents, faces a number of human behavior related limitations for a similar application to different types of facilities/occupants. To overcome the obstacles including complexity in human behaviors, a number of simulation techniques with limited consideration on human behaviors are utilized to predict foreseeable problems in evacuation process. Therefore, this research aims to propose system dynamics models incorporating human behaviors considering different types of occupants under disaster evacuation events. Analysis on emergent human behaviors such as group forming and interactions under urgent situation are conducted based on the main stream theories in social science field. The results suggest the influences of human behavior factors including cooperative intention, information sharing, and mobility change to evacuation behavior. The implications are expected to provide safety consideration at planning/designing phase of buildings and help facility safety managers for evacuation planning with more realistic management approaches.

• Journal of the Society of Disaster Information
• /
• v.19 no.3
• /
• pp.498-509
• /
• 2023

Purpose: This paper proposes a method detecting the falling of a maintenance worker in the underground utility tunnel, by applying deep learning techniques using CCTV video, and evaluates the applicability of the proposed method to the worker monitoring of the utility tunnel. Method: Each rule was designed to detect the falling of a maintenance worker by using the inference results from pre-trained YOLOv5 and OpenPose models, respectively. The rules were then integrally applied to detect worker falls within the utility tunnel. Result: Although the worker presence and falling were detected by the proposed model, the inference results were dependent on both the distance between the worker and CCTV and the falling direction of the worker. Additionally, the falling detection system using YOLOv5 shows superior performance, due to its lower dependence on distance and fall direction, compared to the OpenPose-based. Consequently, results from the fall detection using the integrated dual deep learning model were dependent on the YOLOv5 detection performance. Conclusion: The proposed hybrid model shows detecting an abnormal worker in the utility tunnel but the improvement of the model was meaningless compared to the single model based YOLOv5 due to severe differences in detection performance between each deep learning model

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.21 no.6
• /
• pp.662-671
• /
• 2015

As the type of Hazardous and Noxious Substances(HNS) becomes various and the transport volume of HNS increases, HNS spill incidents occur frequently on land and the sea. In view of various damages to human lives and properties by HNS spills, it is necessary to educate and train professional personnel in preparation for and response to potential HNS spills. This study shows the current state of response systems and education courses against HNS spill incidents on land and the sea to compare those with each other between land and sea in Korea. Incident command system on land are basically similar to that at sea, but leading authority which is responsible for combating HNS spills at sea is changeable depending on the location of HNS spill, as it were, Korea Coast Guard(KCG) is responsible for urgent response to HNS spill at sea, while municipalities are responsible for the response to HNS drifted ashore. Education courses for HNS responders on land are established at National Fire Service Academy(NFSA), National Institute of Chemical Safety(NICS), etc., and are diverse. Education and training courses for HNS responder at sea are established at Korea Coast Guard Academy(KCGA) and Marine Environment Research & Training Institute(MERTI), and are comparatively simple. Education courses for dangerous cargo handlers who work in port where land is linked to the sea are established at Korea Maritime Dangerous Goods Inspection & Research Institute(KOMDI), Korea Port Training Institute(KPTI) and Korea Institute of Maritime and Fisheries Technology(KIMFT). Through the comparison of education courses for HNS responders between land and sea, some recommendations such as extension of education targets, division of an existing integrated HNS course into two courses composed of operational level and manager level with respective refresh course, on-line cyber course and joint inter-educational institute course in cooperation with other relevant institutes are proposed for the improvement in education courses of KCG and KOEM(Korea Marine Environment Management Corporation) to educate and train professionals for combating HNS spills at sea in Korea.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1107-1118
• /
• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of Digital Convergence
• /
• v.15 no.11
• /
• pp.245-250
• /
• 2017

Flash floods is defined as the flooding of intense rainfall over a relatively small area that flows through river and valley rapidly in short time with no advance warning. So that it can cause damage property and casuality. This study is to establish the flash-flood warning system using 38 accident data, reported from the National Disaster Information Center and Land Surface Model(TOPLATS) between 2009 and 2012. Three variables were used in the Land Surface Model: precipitation, soil moisture, and surface runoff. The three variables of 6 hours preceding flash flood were reduced to 3 factors through factor analysis. Decision tree, random forest, Naive Bayes, Support Vector Machine, and logistic regression model are considered as big data methods. The prediction performance was evaluated by comparison of Accuracy, Kappa, TP Rate, FP Rate and F-Measure. The best method was suggested based on reproducibility evaluation at the each points of flash flood occurrence and predicted count versus actual count using 4 years data.

• Journal of Korean Society of Disaster and Security
• /
• v.6 no.3
• /
• pp.43-48
• /
• 2013

This paper focused on the continuing the citizen safety, the contributing the local economy's activation, and the improving the safe and the social walfare on the civil environment. Seoul metropolitan nominated the model village the Buggaja 2 dong of the Seodaemoon-gu for the making safe village in the 2013. It is designed the village map for the safe life, discovered the dangerous factor about the various and social facilities which is a road, a walking way, a school, a enjoy place for the children, a Thema place, the leasure place, facilities etc., and improved the model village for the incident's and accident's reduction education and training from 2011 to 2013. The results on the discovering and improving activities by the resilient safe monitoring activity, in the 2011 the village is reduced the 23 people from the 151 people to the 128 people in the dead number into the total citizen 34,000 during a year, is showed the excellent values, which the dead people reduced the 23 people in the village, which the safe-life result was over the 12.8% in the national average. For the making resilient city, for the supporting the visitors which it looks around the safe-life model village, the tracking road map is designed, and the tenth safe life factors is showed.