• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.325-331
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• 2016

This research developed a flood fragility curve of bridges considering the debris impacts. Damage and failures of civil infrastructure due to natural disasters can cause casualties as well as social and economic losses. Fragility analysis is an effective tool to help better understand the vulnerability of a structure to possible extreme events, such as earthquakes and floods. In particular, flood-induced failures of bridges are relatively common in Korea, because of the mountainous regions and summer concentrated rainfall. The main failure reasons during floods are reported to be debris impact and scour; however, research regarding debris impacts is considered challenging due to various uncertainties that affect the failure probability. This study introduces a fragility analysis methodology for evaluating the structural vulnerability due to debris impacts during floods. The proposed method describes how the essential components in fragility analysis are considered, including limit-state function, intensity measure of the debris impact, and finite element model. A numerical example of the proposed fragility analysis is presented using a bridge pier system under a debris impact.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.565-573
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• 2017

The ex-post evaluation of governmental crisis management is an important issues since it is necessary to prepare for the future disasters and becomes the cornerstone of our success as well. In this paper, we propose a data cube model with data mining techniques for the analysis of governmental crisis management strategies and ripple effects of foot-and-mouth(FMD) disease using the online news articles. Based on the construction of the data cube model, a multidimensional FMD analysis is performed using on line analytical processing operations (OLAP) to assess the temporal perspectives of the spread of the disease with varying levels of abstraction. Furthermore, the proposed analysis model provides useful information that generates the causal relationship between crisis response actions and its social ripple effects of FMD outbreaks by applying association rule mining. We confirmed the feasibility and applicability of the proposed FMD analysis model by implementing and applying an analysis system to FMD outbreaks from July 2010 to December 2011 in South Korea.

• Anxiety and mood
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• v.14 no.2
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• pp.71-79
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• 2018

Objective : Several earlier studies have reported similar symptoms in patients with posttraumatic stress disorder (PTSD) who have been repeatedly exposed to relevant media after disasters and trauma. This study aimed to examine the effects of indirect trauma experience through media rather than direct traumatic events on an individual's social life. Methods : Five hundred and fifty-four individuals participated in our online, self-reported questionnaire survey. All subjects were asked to complete a demographic questionnaire, Posttraumatic Diagnostic Scale, Beck Depression Inventory, the Impact of Event Scale-Revised, State-Trait Anxiety Inventory, Korean version of Alcohol Use Disorder Identification Test, Patient Health Questionnaire-15, Suicidal Behaviors Questionnaire-Revised. Participants were assessed in regards to their experience of violent media exposure within the past three months. Results : Data from our study indicates that the group exposed to violent media had significantly higher perceived stress, physical symptoms, insomnia, and suicide ideation in comparison to the control group. Among the major symptoms of PTSD, the proportion of intrusion symptoms was relatively high in the media exposed group. Conclusion : This suggests that indirect trauma caused by media exposure could cause post-traumatic stress symptoms. The PTSD caused by indirect trauma may have slight differences from the PTSD caused by direct trauma. Therefore, it is necessary to understand, prevent, and control the adverse effects of media.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.629-635
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• 2021

In the spring, 2020, the pandemic caused quarantine and all educational institutions switched to distance learning, which led to significant changes in the field of education around the world. It has become necessary to build its capacity to provide distance learning to protect education and create opportunities for more individualized approaches to teaching and learning not only during future pandemics but also during other possible issues, such as natural disasters, when a developed flexible curricula could be taught face-to-face or online. The article presents an analysis of distance education in the world during a pandemic, analyzes significant changes, and implements measures in the field of education in Ukraine and around the world. The role of public and international organizations in the implementation of quarantine in the conditions of COVID-19, which partially took over the functions of state and local authorities, is emphasized. The closure of schools under COVID-19 has led to a de facto deterioration in learning outcomes, so we have analyzed the effects of distance learning and digital inequality in the world. It is shown how the COVID-19 pandemic affected access to public services in Ukraine.

• Tunnel and Underground Space
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• v.29 no.1
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• pp.52-63
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• 2019

It is highly in demand to establish a bunker-type underground data center to ensure the safety of national critical data, such as financial information and medical information, and prevent those outflow of national important data. In particular, the security of a data center which is a key national structure has become a social issue due to EMP weapon and earthquakes, but data centers in the nation have not been able to deal with it properly. Therefore, it is necessary to develop an underground data center that is safe from human-induced and natural disasters while reducing power costs by utilizing the benefits of underground spaces such as constant temperature and isolation. In this analysis, the status and trends of data centers around the world were analyzed and based on those trend analyses, the research strategy for underground data center were discussed.

• Journal of Korean Society of Rural Planning
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• v.27 no.3
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• pp.11-20
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• 2021

Recently, natural disasters caused by climate change have become more frequent across the world. Our country is also not exceptional, and it is urgent to come up with appropriate measures in the agricultural sector as the size and intensity of drought are becoming severe. Consequently, the Ministry of Agriculture and Food has continuously raised the need for efficient water management and governance to overcome the periodic drought. Thus, there is a need for water-saving education and water conservation governance for sustainable and efficient use of agricultural water. Governance is a cooperative mechanism involving various stakeholders, such as central, local, civil society, and businesses, to solve regional or social problems, with different definitions and concepts depending on the field or scope. In this study, we aim to present basis of a governance framework for direct water management participation involving the key agricultural water use stakeholders to imbibe the culture of water savings and conservation practices. Based on this, water-saving governance was established and operated in Gyeongju and Yeoju, in South Korea as a 'water conservation practice', while the water management status of local farmers, the reliability and importance of stakeholders, and the need for governance were investigated. The results indicate that the involvement of various stakeholders in the governance of water management yielded water-saving effects. This study provides the directions of making a framework for water-saving governance establishment and operation. It is expected that sustainable agricultural water use can be achieved in response to climate change if the governance builds and operates with agricultural water use stakeholders based on the continuous government supports.

• Korean Journal of Agricultural Science
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• v.48 no.1
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• pp.103-117
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• 2021

The severe effects of climate change, such as global warming and the El Niño phenomenon, have become more prevalent. In recent years, natural disasters such as drought, heavy rain, and typhoons have taken place, resulting in noticeable damage. Korea is affected by droughts that cause damage to rice fields and crops. Societal interest in droughts is growing, and measures are urgently needed to address their impacts. As the demand for high-quality agricultural products expands, farmers have become more interested in water management, and the demand for field irrigation is increasing. Therefore, we investigated water demand in the irrigation of drought-vulnerable crops. Specifically, we determined the water requirements for crops including cabbage, red pepper, apple, and bean in four regions by calculating the consumptive water use (evapotranspiration), effective rainfall, and irrigation capacity. The total consumptive water use (crop evapotranspiration) estimates for Dangjin-si (cabbage), Yesan-gun (apple), Cheongyang-gun (pepper) in Chungnam, and Goesan-gun (bean) in Chungbuk were 33.5, 206.4, 86.1, and 204.5 mm, respectively. The volumes of groundwater available in the four regions were determined to be the following: Dangjin-si, 4,968,000 m³; Yesan-gun, 4,300,000 m³; Cheongyang-gun, 1,114,000 m³, and Goesan-gun, 3,794,000 m³. The annual amounts available for the representative crops, compared to the amount of evapotranspiration, were 313.9% in Dangjin-si, 29.5% in Yesan-gun, 56.1% in Cheongyang-gun, and 20.1% in Goesan-gun.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.211-215
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• 2021

The number of megacities are increasing, due to the global urbanization. Along with this change, climate change, social development and technology advance make the calamities complicated and more devastating. Especially, megacities are hyper-netted, hyper-connected and hyper-converged with population more than 10 million and their domain. When calamities break out, the damage will be aggravated for they lead to another ones. Since megacities are the center of politics, economics and culture of a nation. so when complex disaster break out in megacities, this may be developed to a peril to the national security. Therefore, pan-government effort must be concentrated in preparing abilities to forecast, react, rapid response and resilience.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.890-895
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• 2021

Recently, the "Act of Serious Disasters, etc" was enacted and institutional and social interest in safety accidents is increasing. In this paper, we analyze statistical data published by government agency on safety accidents that occur in manufacturing sites, and compare various object detection models based on deep learning to build a model to determine dangerous situations to reduce the occurrence of safety accidents. The data-set was directly constructed by collecting images from CCTVs at the manufacturing site, and the YOLO-v4, SSD, CenterNet models were used as training data and evaluation data for learning. As a result, the YOLO-v4 model obtained a value of 81% of mAP. It is meaningful to select a class in an industrial field and directly build a dataset to learn a model, and it is thought that it can be used as an initial research data for a system that determines a risk situation and infers it.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.135-142
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• 2022

Recently, with the development of data processing technology and the increase of computational power, methods to solving social problems using Artificial Intelligence (AI) are in the spotlight, and AI technologies are replacing and supplementing existing traditional methods in various fields. Meanwhile in Korea, heavy rain is one of the representative factors of natural disasters that cause enormous economic damage and casualties every year. Accurate prediction of heavy rainfall over the Korean peninsula is very difficult due to its geographical features, located between the Eurasian continent and the Pacific Ocean at mid-latitude, and the influence of the summer monsoon. In order to deal with such problems, the Korea Meteorological Administration operates various state-of-the-art observation equipment and a newly developed global atmospheric model system. Nevertheless, for precipitation nowcasting, the use of a separate system based on the extrapolation method is required due to the intrinsic characteristics associated with the operation of numerical weather prediction models. The predictability of existing precipitation nowcasting is reliable in the early stage of forecasting but decreases sharply as forecast lead time increases. At this point, AI technologies to deal with spatio-temporal features of data are expected to greatly contribute to overcoming the limitations of existing precipitation nowcasting systems. Thus, in this project the dataset required to develop, train, and verify deep learning-based precipitation nowcasting models has been constructed in a regularized form. The dataset not only provides various variables obtained from multiple sources, but also coincides with each other in spatio-temporal specifications.