• Industrial Engineering and Management Systems
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• v.13 no.3
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• pp.297-303
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• 2014

Stock pre-positioning is one of the most important decisions for preparing the stage of emergency logistics planning. In this paper, a mixed integer model for stock pre-positioning is derived to support an emergency disaster relief response against the event of earthquake. A maximum response time limit, budget availability, multiple item types, and capacity restrictions are considered. In the model, the decision of the distribution centers to cover a disaster area and the amount of supplies to be stocked in each distribution center are simultaneously determined to maximize the total expected relief demand of the disaster areas covered by the existing distribution centers. The proposed model is applied to a real case with 33 disaster areas and 16 distribution centers in Indonesia. Several sensitivity analyses are conducted to estimate the fluctuation on the emergency stock pre-positioning planning by changing the maximum response time and budgets.

• Geomechanics and Engineering
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• v.18 no.1
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• pp.21-27
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• 2019

Rockburst disasters pose serious threat to mining safety and underground excavation, especially in China, resulting in massive life-wealth loss and even compulsive closed-down of some coal mines. To investigate the mechanism of rockbursts that occur under a state of static forces, a stress model with sidewall as prototype was developed and verified by a group of laboratory experiments and numerical simulations. In this model, roadway sidewall was simplified as a square plate with axial compression and end (horizontal) restraints. The stress field was solved via the Airy stress function. To track the "closeness degree" of the stress state approaching the yield limit, an unbalanced force F was defined based on the Mohr-Coulomb yield criterion. The distribution of the unbalanced force in the plane model indicated that only the friction angle above a critical value could cause the first failure on the coal in the deeper of the sidewall, inducing the occurrence of rockbursts. The laboratory tests reproduced the rockburst process, which was similar to the prediction from the theoretical model, numerical simulation and some disaster scenes.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.617-625
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• 2019

Purpose: The fields manuals which is managed by the each disaster types are the integrated guideline. When the disaster occurred, all kinds of SOPs which are described in the manual does not need. Therefore, the person in charge is confused which SOP is executed. In this study, we propose the disaster response process model based on the specific disaster situation case. Method: Firstly, we define the disaster situation cases which is mentioned in the field manual, and then, we develop the disaster response process model including indispensible SOPs for the specific disaster situation case. As a verification and feedback process, we apply the model to Safety Korea Exercise scenario. Result: We developed SOP model and disaster response process model reflecting the concept of the disaster situation case. Conclusion: Safety Kore Exercise scenario reflecting the developed model may continuously upgrade the field manual.

• Journal of Environmental Impact Assessment
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• v.16 no.5
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• pp.373-379
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• 2007

Natural hazards such as typhoon, flood, landslide affect both coastal and inland areas more often according to increasement of severe and unusual weather. To provide adequate coastal disaster mitigation strategies, coastal disaster prevention system using GIS is very useful. Application methods of digital map on this issue was discussed in this study. For developing of coastal disaster prevention system, the data structures related to disaster monitoring is needed to be revised for interdisciplinary framework. To improve the current coastal disaster mapping methods, GIS based new model for coastal disaster mapping was suggested. In this study, coastal GIS showed the attribute data and structures of coastal disaster mapping.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.16-26
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• 1997

China is one of the few countries where natural disaster strike frequently and cause heavy damage. In this paper, we mathematically develop two models to assess fuzzy risk of natural disaster in China. One is to assess the risk based on database of historical disaster effects by using information diffusion method relevant in fuzzy information analysis. In another model, we give an overview over advanced method to calculate the risk of release, exposure and consequence assessent, where information distribution technique is used to calculate basic fuzzy relationships showing historical experience of natural disasters, and fuzzy approximate inference is employed to study loss risk based on these basic relationships. We also present an examples to show how to use the first model. Result show that the model is effective for natural disaster risk assessment.

• Journal of Korean Public Health Nursing
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• v.34 no.3
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• pp.391-404
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• 2020

Purpose: This study investigates the disaster preparedness behaviors of people residing in disaster areas and the factors affecting such behaviors, by examining the application of a Health Belief Model. Methods: A mixed-method approach was used for this study. Local residents were surveyed in Gyeongju and Pohang, which had experienced earthquakes one to two years earlier. Quantitative data (N=233) were collected through a questionnaire and analyzed using t-test, one-way ANOVA, Scheffe test and multiple regression. Qualitative data (N=11) were collected through focus group and individual interviews, and evaluated through content analysis. Results: Disaster preparedness behaviors scored 7.04 out of 18 points, and factors that significantly affected disaster preparedness included cut to action, marriage status, experience of education and training related to disaster, benefit-barriers factors of disaster preparedness behaviors, and gender. The focus group and individual interviews confirmed the contents corresponding to each variable of the disaster preparedness behaviors and heal belief model. Conclusion: The findings of this study indicate that in order to induce disaster preparedness behaviors as well as education and training opportunities related to disaster relief, we need to examine cue to action of disaster preparedness behaviors, benefits, and barriers for motivating interventions.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3211-3229
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• 2022

To solve the problems existing in the process of Weibo disaster rumor recognition, such as lack of corpus, poor text standardization, difficult to learn semantic information, and simple semantic features of disaster rumor text, this paper takes Sina Weibo as the data source, constructs a dataset for Weibo disaster rumor recognition, and proposes a deep learning model BERT_AT_Stacked LSTM for Weibo disaster rumor recognition. First, add adversarial disturbance to the embedding vector of each word to generate adversarial samples to enhance the features of rumor text, and carry out adversarial training to solve the problem that the text features of disaster rumors are relatively single. Second, the BERT part obtains the word-level semantic information of each Weibo text and generates a hidden vector containing sentence-level feature information. Finally, the hidden complex semantic information of poorly-regulated Weibo texts is learned using a Stacked Long Short-Term Memory (Stacked LSTM) structure. The experimental results show that, compared with other comparative models, the model in this paper has more advantages in recognizing disaster rumors on Weibo, with an F1_Socre of 97.48%, and has been tested on an open general domain dataset, with an F1_Score of 94.59%, indicating that the model has better generalization.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.465-486
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• 2021

Purpose: Since most disaster information systems are centered on non-disabled people, the reality is that there is a lack of disaster information delivery systems for the vulnerable, such as the disabled, the elderly, and children, who are relatively vulnerable to disasters. The purpose of the service is to improve the safety of the disabled and the elderly by eliminating blind spots of informatization and establishing customized disaster information services to respond to disasters through IoT-based integrated control technology. Method: The model at the core of this study is the disaster alert propagation model and evacuation support model, and it shall be developed by reflecting the behavioral characteristics of the disabled and the elderly in the event of a disaster. The disaster alert propagation model spreads disaster situations collected using IoT technology, and the evacuation support model uses geomagnetic field-based measuring technology to identify the user's indoor location and help the disabled and the elderly evacuate safely. Results: Demonstration model demonstration resulted in an efficient qualitative evaluation of indoor location accuracy, such as the suitability of evacuation route guidance and satisfaction of services from the user's perspective. Conclusion: Disaster information and evacuation support services were established for the safety vulnerable groups of mobile app for model verification. The disaster situation was demonstrated through experts in the related fields and the disabled by limiting it to the fire situation. It was evaluated as "satisfaction" in the adequacy of disaster information delivery and evacuation support, and its functional satisfaction and user UI were evaluated as "normal" due to the nature of the pilot model. Through this, the disaster information and evacuation support services presented in this study were evaluated to support the safety vulnerable groups to a faster disaster evacuation without missing the golden time of disaster evacuation.

• Journal of the Society of Disaster Information
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• v.7 no.4
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• pp.294-304
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• 2011

Disaster prevention resources consist of persons, equipments, goods, and facilities. Specially, equipments and goods are internally managed in the regional office, and may be leased to the inter-offices. National Disaster Management System(NDMS) managed the resources in the separated system. That is, one system is managed by regional disaster prevention system, the other is managed by the central disaster prevention system which receives the data from the regional disaster prevention system. Because the regional disaster prevention system updates the resource information quarterly, it is difficult to confirm the exact information. In this study, we propose the model which makes to supply in timely the resource to the disaster using the managed resource with RFID technology. Firstly, we classified the resources based on the resource types for the easily search. After then, we defined ID and attributes information of the resources. From the information, we described the management model for the real time resource.