• Journal of Information Science Theory and Practice
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• v.9 no.4
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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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• v.17 no.3
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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.

• International conference on construction engineering and project management
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• 2015.10a
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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.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.502-513
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• 2019

Purpose: This study intends to review the procedures for the establishment of the plan for disaster mitigation activities and the system for the management of disaster mitigation activities for the requirements of the enterprise disaster management standard. Method: The requirements, including the activities of each stage of disaster management defined within the scope of the corporate disaster management standard, were identified, the operational cases of 'A' institution were reviewed, and the targets of continuous planning were reviewed to meet the requirements. Result: It was reviewed that the contents and procedures of each phase of disaster management, which is a requirement of the enterprise disaster management standard, are clearly defined, and a task continuity plan is established for each stage of activity. Conclusion: Conclusion : The PDCA model including the activities of each stage of disaster management activities was presented for the requirements of the enterprise disaster management standard, and the disaster mitigation activity management system model of the broad concept of disaster management including prevention and preparedness plans for disasters was presented.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.34-41
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• 2017

In this paper, the I/O parameters of existing predictive models were analyzed to construct a composite disaster prediction model that incorporates a previously developed natural disaster prediction model and a prediction of social disaster prediction models. A complex disaster prediction model indicates a combination of multiple disasters, not a single disaster. Such a complex disaster was mainly linked to a social disaster caused by natural disasters resulting from natural disasters, so it conducted a study of natural disasters and social disaster prediction models. Several estimates were analyzed based on several predictive models of prediction models, and the I/O parameters applied universally were derived by the types of disaster types. In this paper, It will help develop a study aimed at building a complex disaster prediction model.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.1-9
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• 2021

Disaster alerts are text messages sent by government to people in the area in the event of a disaster. Since the number of disaster alerts has increased, the number of people who block disaster alerts is increasing as many unnecessary disaster alerts are being received. To solve this problem, this study proposes a deep learning model that automatically classifies disaster alerts by disaster type, and allows only necessary disaster alerts to be received according to the recipient. The proposed model embeds disaster alerts via KoBERT and classifies them by disaster type with LSTM. As a result of classifying disaster alerts using 3 combinations of parts of speech: [Noun], [Noun + Adjective + Verb] and [All parts], and 4 classification models: Proposed model, Keyword classification, Word2Vec + 1D-CNN and KoBERT + FFNN, the proposed model achieved the highest performance with 0.988954 accuracy.

• Journal of Korean Academy of Nursing
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• v.28 no.1
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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.

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.115-139
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• 2018

Due to the value and the importance of preservation of disaster web records, to build disaster archives is globally becoming a national challenge. This study proposes a acquisition methods based on the issue life cycle model for collecting disaster web records. We firstly analyzed web records acquisition status, methods and period of domestic and foreign disaster archives. In addition, the issue life cycle model was derived by collecting and analyzing the disaster issues in the last 10 years. As the results of the analysis, the issue life cycle model was divided into the sudden type and periodic type according to the characteristics of the disaster. In conclusion, this study propose a method to collect web records according to each model and verify its applicability.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.493-504
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• 2020

Purpose: The purpose of this study is to propose an analytical methodology for selecting the priority of preventive projects in the course of carrying out disaster prevention projects that improve disaster-hazardous areas. Method: Data analysis was performed using RFM model which can divide data grade and perform target marketing based on Recency, Frequency, and Monetary. Result: The top 10% of the area with high RFM value was mainly in the East Sea and the South Sea coast, and the number of damage in private facilities was high. Conclusion: In this study, we used the RFM model to select the priority of disaster risk and to implement the regional disaster risk using GIS. These results are expected to be used as basic data for selecting priority project sites for disaster prevention projects and as basic data in the decision-making process for disaster prevention projects.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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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.