• Journal of Information Science Theory and Practice
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• 제9권4호
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• pp.35-49
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• 2021

In a situation where there are multiple diverse datasets, it is essential to have an efficient method to provide users with the datasets they require. To address this suggestion, necessary datasets should be selected on the basis of the relationships between the datasets. In particular, in order to discover the necessary datasets for disaster resolution, we need to consider the disaster resolution stage. In this paper, in order to provide the necessary datasets for each stage of disaster resolution, we constructed a disaster type and disaster management process ontology and designed a method to determine the necessary datasets for each disaster type and disaster management process step. In addition, we introduce a method to determine relationships between datasets necessary for disaster response. We propose a method for discovering datasets based on minimal relationships such as "isA," "sameAs," and "subclassOf." To discover suitable datasets, we designed a knowledge exploration model and collected 651 disaster-related datasets for improving our method. These datasets were categorized by disaster type from the perspective of disaster management. Categorizing actual datasets into disaster types and disaster management types allows a single dataset to be classified as multiple types in both categories. We built a knowledge exploration model on the basis of disaster examples to ensure the configuration of our model.

• Journal of Information Technology Applications and Management
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• 제17권3호
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• pp.163-189
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• 2010

The purpose of this research is to develop a decision-making model for the calculation of the National Disaster Management System's standard prevention workforce quota. The final purpose of such model is to support in arranging a rationally sized prevention workforce for local authorities by providing information about its calculation in order to support an effective and efficient disaster management administration. In other words, it is to establish and develop a model that calculates the standard disaster prevention workforce quota for basic local governments in order to arrange realistically required prevention workforce. In calculating Korea's prevention workforce, it was found that the prevention investment expenses, number of prevention facilities, frequency of flood damage, number of disaster victims, prevention density, and national disaster recovery costs have positive influence on the dependent variable when the standard prevention workforce was set as the dependent variable. The model based on the regression analysis-which consists of dependent and independent variables-was classified into inland mountainous region, East coast region, Southwest coastal plain region to reflect regional characteristics for the calculation of the prevention workforce. We anticipate that the decision-making model for the standard prevention workforce quota will aid in arranging an objective and essential prevention workforce for Korea's basic local authorities.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.671-672
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• 2015

Due to harsh conditions of disaster areas, understanding of current feature of collapsed buildings, terrain, and other infrastructures is critical issue for disaster managers. However, because of difficulties in acquiring the geographical information of the disaster site such as large disaster site and limited capability of rescue workers, comprehensive site investigation of current location of survivors buried under the remains of the building is not an easy task for disaster managers. To overcome these circumstances of disaster site, this study makes use of an unmanned aerial vehicle, commonly known as a drone to effectively acquire current image data from the large disaster areas. The framework of 3D model reconstruction of disaster site using aerial imagery acquired by drones was also presented. The proposed methodology is expected to assist rescue workers and disaster managers in achieving a rapid and accurate identification of survivors under the collapsed building.

• 한국재난정보학회 논문집
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• 제15권4호
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• pp.502-513
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• 2019

연구목적: 본 연구는 기업재난관리표준의 요구사항에 대한 재해경감활동계획 수립절차와 재해경감활동관리체계를 검토하고자 한다. 연구방법: 기업재난관리표준의 적용범위에 규정된 재난관리 단계별 각 활동을 포함한 요구사항을 파악하고 'A'기관의 운용사례를 검토하였으며 요구사항에 맞는 업무연속계획 대상을 검토하였다. 연구결과: 기업재난관리표준의 요구사항인 재난관리 단계별 내용과 절차를 명확히 정의하고, 4단계별 활동에 대한 업무연속성계획 수립이 필요한 것으로 검토되었다. 결론: 기업재난관리표준 요구사항에 대하여 재난관리활동 각 단계별 활동을 포함한 PDCA모델을 제시하였고, 재난의 예방 및 대비계획을 포함하는 광의의 재난관리 개념의 재해경감활동관리체계 모델을 제안하였다.

• 한국위성정보통신학회논문지
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• 제12권4호
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• pp.34-41
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• 2017

본 논문은 기존에 개발된 자연재난 예측 모형과 사회재난 예측 모형을 통합한 복합재난 예측 모형을 구성하기 위하여 기존 예측 모형들의 입출력 파라미터를 분석하였다. 복합 재난 예측 모형은 단일 재난이 아닌 다수의 재난이 복합적으로 일어나는 상황을 나타낸다. 이러한 복합재난은 주로 자연재난으로 인해 발생한 사회재난으로 연계되는 경우가 주를 이루기 때문에 자연재난과 사회재난 예측 모형의 연결방안에 대해 연구를 진행하였다. 기존에 개발된 예측 모형 중 재난 유형별로 몇 가지 예측 모형을 기준으로 분석하였으며 재난 유형별로 공통적으로 적용되는 입출력 파라미터가 도출되었다. 본 논문은 향 후 진행되어질 복합재난 예측 모형 구축을 위한 연구에 도움이 될 것이라 생각한다.

• 한국컴퓨터정보학회논문지
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• 제26권12호
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• pp.1-9
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• 2021

재난문자는 재난 발생 시 국가에서 해당 지역에 있는 시민들에게 보내는 문자 메시지다. 재난문자의 발송 건수는 점점 증가하여, 불필요한 재난문자가 많이 수신됨에 따라 재난문자를 차단하는 사람들이 증가하고 있다. 이와 같은 문제를 해결하기 위하여, 본 연구에서는 재난문자를 재난 유형별로 자동으로 분류하고 수신자에 따라 필요한 재난의 재난문자만 수신하게 하는 딥러닝 모델을 제안한다. 제안 모델은 재난문자를 KoBERT를 통해 임베딩하고, LSTM을 통해 재난 유형별로 분류한다. [명사], [명사 + 형용사 + 동사], [모든 품사]의 3가지 품사 조합과 제안 모델, 키워드 분류, Word2Vec + 1D-CNN 및 KoBERT + FFNN의 4종류 분류 모델을 활용하여 재난문자를 분류한 결과, 제안 모델이 0.988954의 정확도로 가장 높은 성능을 달성하였다.

• 대한간호학회지
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• 제28권1호
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• pp.210-220
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• 1998

The various and serious types of disaster occur everyday and everywhere on the earth. There is no doubt that it is very timely to discuss about the effectiveness and preparedness of disaster. The purpose of this study is to develop a curriculum on the disaster management through reviewing disaster concepts and the disaster management system. For the empirical relevance of the study, researchers participated in a couple or more disaster training program, reviewed references, and consulted to the experts working on action parts in the area. As a result, the 'Integrated Disaster Management System Model (IDMSM)' was designed, in which four dimensions were explained. Then the 'Disaster Curriculum Model (DCM)' was explored with its theoretical framework based on the system model. The developed curriculum is composed of four levels ; the introductory course, the fundamental course, the advanced course, and the expert course. From this DCM, basically the course-outlines of two subjects in the introductory course, 18 subjects in the fundamental course (5 of direct services. 13 of indirect services) were developed. Also each course-outline was explored by its course objective, learning objectives, contents, and its length. Finally to make the most of the results, suggestions are proposed. The governmental considerations on the policy should support the systematic and integrated educational program to practice, appointing 「Disaster School」 or 「Disaster Training Center」 of relevance and accountabilities. The further study should explore the higher levels of the DCM through interdisciplinary efforts, and develop the text aterials. ilities. The further study should explore the higher levels of the DCM through interdisciplinary efforts, and develop the text materials.

• 정보관리학회지
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• 제35권2호
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• pp.115-139
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• 2018

재난 웹 기록물의 가치와 보존의 중요성으로 인해 전 세계적으로 재난 아카이브의 구축은 국가적인 과제가 되어가고 있다. 본 연구는 재난 아카이브의 웹 기록물 수집에 있어서 이슈 생존 주기 모형에 기반한 수집 방안을 제시하는 것을 목적으로 한다. 이를 위해 먼저 국내외 재난 아카이브의 웹 기록물 수집 현황, 수집 방법 및 기간에 대하여 분석하였다. 또한, 최근 10년간 발생한 재난 이슈를 수집 및 분석하여 이슈 생존 주기 모형을 도출하였다. 이슈 생존 주기 모형은 재난의 특성에 따라 돌발형 및 주기형으로 구분되며, 각 모형에 따른 웹 기록물 수집 방안을 제시하였고 적용 가능성을 검증하였다.

• 한국재난정보학회 논문집
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• 제16권3호
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• pp.493-504
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• 2020

연구목적: 본 연구는 재해위험지역을 개선하는 재해예방사업을 실시하는 과정에서 예방사업의 우선순위를 선정하기 위한 분석 방법론 제안을 목적으로 한다. 연구방법:최근성(Recency), 빈도성(Frequency), 화폐성(Monetary)을 기준으로 데이터의 등급을 나누고 타겟 마케팅을 수행할 수 있는 RFM 모형을 활용하여 데이터 분석을 수행하였다. 연구결과: RFM 값이 높은 상위 10% 지역이 동해와 남해 연안을 중심으로 나타났으며, 피해 유형을 살펴보면 사유시설의 피해 건수가 크게 나타났다. 결론: 본 연구에서는 RFM 모형을 활용하여 재해위험의 우선순위를 선정하고 GIS를 활용한 지역재해위험도를 구현하였다. 이러한 결과는 재해예방사업의 우선 사업대상지를 선정할 수 있는 기초자료와 재해예방사업의 의사결정 과정에서 기초자료로 활용되기를 기대한다.

• 산업경영시스템학회지
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• 제44권1호
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• pp.26-36
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• 2021

The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.