• Journal of the Korean Society for Marine Environment & Energy
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• v.20 no.1
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• pp.55-61
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• 2017

This study conducted a survey to evaluate the disaster response capability of coastal residents and analyzed the characteristics. For the sampling process, nonrandom sampling method was used. Sample size is 4,520 and sample error is ${\pm}1.5%p$ at 95% confidence level. As a result of the survey, 72% and 68% of the respondents said that they recognized the emergency contact network and listened to the disaster broadcast. On the other hand, 17% and 18% said that they organized the local voluntary disaster prevention teams and participated in disaster preparedness training. In addition, male's disaster response capability was higher than female's, and first aid techniques and participation in disaster preparedness training were higher in teens and twenties. By occupation, public official possess the highest response capability. By region, it was high in the East coast and low in the South coast. It is necessary that the authorities improve the national disaster preparedness training and publicity to enhance the coastal disaster response capability of coastal residents.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.725-735
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• 2022

Currently, disasters occurring in Korea are characterized by unpredictability and complexity. Due to these features, property damage and human casualties are increasing. Since the initial response process of these disasters is directly related to the scale and the spread of damage, optimal decision-making is essential, and information of the site must be obtained through timely applicable sensors. However, it is difficult to make appropriate decisions because indiscriminate information is collected rather than necessary information in the currently operated Disaster and Safety Situation Office. In order to improve the current situation, this study proposed a framework that quickly collects various disaster image information, extracts information required to support decision-making, and utilizes it. To this end, a web-based display system and a smartphone application were proposed. Data were collected close to real time, and various analysis results were shared. Moreover, the capability of supporting decision-making was reviewed based on images of actual disaster sites acquired through CCTV, smartphones, and UAVs. In addition to the reviewed capability, it is expected that effective disaster management can be contributed if institutional mitigation of the acquisition and sharing of disaster-related data can be achieved together.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.458-460
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• 2021

The provision and application of public safety network in Korea is still insufficient for security response to the mobile app of public safety network in the stages of development, initial construction, demonstration, and initial service. The available terminals on the Disaster Safety Network (PS-LTE) are open, Android-based, dedicated terminals that potentially have vulnerabilities that can be used for a variety of mobile malware, requiring preemptive responses similar to FirstNet Certified in U.S and Google's Google Play Protect. In this paper, before listing the application service app on the public safety network mobile app store, we construct a data set for malicious and normal apps, extract features, select the most effective AI model, perform static and dynamic analysis, and analyze Based on the result, if it is not a malicious app, it is suggested to list it in the App Store. As it becomes essential to provide a service that blocks malicious behavior app listing in advance, it is essential to provide authorized authentication to minimize the security blind spot of the public safety network, and to provide certified apps for disaster safety and application service support. The safety of the public safety network can be secured.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.689-697
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• 2023

Purpose: The purpose of this study is to automatically extract information on underground facilities using a general-purpose smartphone in the process of applying the mini-trenching method. Method: Data sets for image learning were collected under various conditions such as day and night, height, and angle, and the object detection algorithm used the R-CNN algorithm. Result: As a result of the study, F1-Score was applied as a performance evaluation index that can consider the average of accurate predictions and reproduction rates at the same time, and F1-Score was 0.76. Conclusion: The results of this study showed that it was possible to extract information on underground buried materials based on smartphones, but it is necessary to improve the precision and accuracy of the algorithm through additional securing of learning data and on-site demonstration.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.426-427
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• 2016

본 논문에서는 Unmaned Aerial Vehicle(UAV)를 이용하여 양식어장에 유입될 수 있는 적조 모니터링에 대한 연구를 실시하였다. 적조는 한반도 주변 해역을 포함한 전 세계 연안 지역에서 물고기의 집단 폐사, 해안구조물에 대한 물리적 손상등과 같이 사회 경제적인 피해를 야기 시켜왔고, 최근 해수면 온도상승과 같은 기후 변화에 의한 영향으로 증가되고 있는 실정이다. 특히 남해안과 같이 생활하수가 다량 유입되고 저층에 퇴적된 영양물질이 용출되는 곳에서 상습적으로 발생한다. 1995년에 발생한 코클로디니움에 의한 적조는 764억원의 기록적인 피해를 입히면서, 적조에 대한 신속한 대응과 효과적인 방제작업의 필요성이 대두되었다. 이렇게 양식어장 운영에 다양한 문제가 발생이 된 후 대응하는 것보다 모니터링을 통해 사전에 유입을 차단하고 대처하는 연구가 필요하고 판단된다. 원격탐사를 활용한 적조 탐지 및 모니터링 연구는 UAV에서 취득한 RGB color 영상을 통한 적조 추출 및 분석, 시계열 분석을 위한 영상자료 수집, 현장관측 자료와 위성영상에서 추출한 클로로필 농도 비료글 통해 이루어 졌다. 또한 매년 발생하는 적조생물에 관한 속성정보를 통해 적조발생지역에 대한 적조생물종과 국내 연안에서 발생한 적조의 발생 범위 등의 정보를 지리정보기반에 의한 공간분석을 실시하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.310-310
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• 2022

최근 통신의 발달로 인하여 웹(Web)상에는 다양한 데이터들이 실시간으로 생산되고 있으며 해당 내용은 다양한 산업에서 활용되고 있다. 특히 최근에는 재난과 관련 상황에서도 소셜 네트워크 서비스(SNS) 데이터가 활용되기도 하며 기존의 수치 계측 데이터가 아닌 하나의 센서 역할을 하는 개인의 비정형데이터의 업로드가 다양한 재난 모니터링 부분에 활용되고 있는 실정이다. 특히 홍수 등의 자연재해 발생 시 개개인의 업로드 한 웹 데이터에는 시간에 따른 인구의 유동성이나 간단한 위치 정보 등을 포함하여 실제 피해의 정도를 보다 빠르고 다양한 정보로 모니터링이 가능하다. 홍수 발생 시 일반적으로 활용하는 수문 데이터는 피해의 규모가 크게 예측되는 대하천 위주로 관측이 이루어지며 관측지역과 데이터의 양이 한정되어있어 비정형데이터를 함께 활용한 연구가 필요하다. 따라서 본 연구에서는 웹에 있는 비정형 데이터들을 추출해내는 웹 크롤러를 구성하고 해당 프로그램을 활용하여 추출한 데이터들에 대해 강우 사상과 공간적 패턴을 비교 분석하여 크라우드 소싱 데이터를 적용한 홍수 피해지도의 활용방안을 제시하고자 한다.

• Journal of the Korean Institute of Gas
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• v.25 no.3
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• pp.9-15
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• 2021

In this paper, a study on the construction of a knowledge base based on natural language processing and the design of a chemical substance estimation system for the development of a knowledge service for a real-time sensor information fusion detection system and symptoms of contact with chemical substances in industrial sites. The information on 499 chemical substances contact symptoms from the Wireless Information System for Emergency Responders(WISER) program provided by the National Institutes of Health(NIH) in the United States was used as a reference. AllegroGraph 7.0.1 was used, input triples are Cas No., Synonyms, Symptom, SMILES, InChl, and Formula. As a result of establishing the knowledge base, it was confirmed that 39 symptoms based on ammonia (CAS No: 7664-41-7) were the same as those of the WISER program. Through this, a method of establishing was proposed knowledge base for the symptom extraction process of the chemical substance estimation system.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.

• Journal of radiological science and technology
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• v.44 no.2
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• pp.117-122
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• 2021

This study is desinged to examine for radiation protection effect of Protaetia Brevitarsis Larvae extracts on the blood and prostate of male rat as a natural radiation protection agent. 5 groups were classified using 90 male rat as experimental animals. Each group was clssified as normal control group (NC Group), the group administered protaetia brevitarsis larvae extracts (PBE Group), irradiated group (IR Group), irradiated group after administration of protaetia brevitarsis larvae extracts (PBE+IR Group), the group administered protaetia brevitarsis larvae extracts after irradiaton (IR+PBE Group). In IR Group, 7 Gy/h of Co-60 gamma ray was irradiated to SD rats. In PBE+IR Group, protaetia brevitarsis larvae extacts wewe injected at 200 mg/kg/day for 14 days before irradiation, In IR+PBE Group, protaetia brevitarsis larvae extract was injeted after irradiation. On the 1, 7 and 21 days after irradiation, the experimental animals were sacrificed to evaluate the changes in blood cell component, superoxide dismutase (SOD) activity, histopathological evaluation of the liver and prostate gland. As a result, the PBE+IR Group and IR+PBE Group showed a significantly recovery of white blood cell (p<0.01, p<0.01), platelet (p<0.01, p<0.01) than the IR Group. It was also confirmed that SOD activity of PBE+IR Group (p<0.01) and IR+PBE Group (p<0.01) was significantly increased than the IR Group. Also PBE+IR Group and IR+PBE Group showed less inflammatory reactions of cystoplasm in the prostate gland than the IR Group. In conclusion, the protaetia brevitarsis larvae have radioprotection effect against blood and prostate gland. It is expected to be useful for research of radiation protection agent.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.339-340
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• 2017

화학공장의 누출사고는 초기에 적절히 대응하지 못할 경우 화재 폭발과 같은 2차 3차의 복합재난사고로 확산될 위험성이 매우 높다. 이러한 이유로 누출사고 발생 초기에 누출이 발생한 지점을 신속히 파악하여 현장안전요원에게 알림으로써, 보다 체계적이고 효율적인 초기대응을 가능하게 하여, 사고피해를 완화시킬 수 있는 통합적인 누출사고 대응시스템 구축은 매우 중요하다고 할 수 있다. 본 연구에서는, 통합적인 누출사고 대응시스템 구축을 위한 선행연구로, 딥러닝 기반의 누출원추적 모델 개발을 제안한다. 여수에 위치한 실제 화학공장을 대상으로 누출사고 시나리오에 대한 Computational Fluid Dynamics (CFD) 시뮬레이션을 진행한 뒤, 화학공장 경계면에 배치된 각 센서별 위치에서의 농도, 풍향 그리고 풍속데이터를 추출하고, 센서 좌표를 추가하여 인공신경망을 학습시켰다. 학습된 모델은 40개의 누출후보군에 대해 학습에 사용되지 않은 상황들에서도 75.43%의 정확도로 누출이 일어난 지점을 실시간 예측해냄을 확인하였다. 또한 누출지점 예측이 일치하지 않은 경우도, 예측된 지점이 실제 누출이 일어난 지점과 물리적으로 매우 인접함을 확인함으로써 제안된 모델을 실제 현장에 적용할시 기대되는 효과는 더 클 것으로 판단하였다.