• The Journal of Art Theory & Practice
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• no.14
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• pp.217-245
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• 2012

The aim of this paper is to show how the paradigm of disaster resilience may help reorienting urban planning policies in order to mitigate various types of risks, thanks to carefully thought action on heritage and conservation practices. Resilience is defined as the "capacity of a social system to proactively adapt to and recover from disturbances that are perceived within the system to fall outside the range of normal and expected disturbances." It relies greatly on risk perception and the memory of catastrophes. States, regions, municipalities, have been giving territorial materiality to collective memory for centuries, but this trend has considerably increased in the second half of the 20th century. This is particularly true regarding the memory of disasters: for example, important traces of catastrophes such as urban ruins have been preserved, because they were supposed to maintain some awareness and hence foster urban resilience - Berlin's Gedachtniskirche is a well-known example of this policy. Yet, in spite of preserved traces of catastrophes and various warnings and heritage policies, there are countless examples of risk mismanagement and urban tragedies. Using resilience as a guiding concept might change the results of these failed risk mitigation policies and irrelevant disaster memory processes. Indeed, the concept of resilience deals with the complexity of temporal and spatial scales, and with partly emotional and qualitative processes, so that this approach fits the issues of urban memory management. Resilience might help underlining the complexity and the subtlety of remembrance messages, and lead to alternative paths better adapted to the diversity of risks, places and actors. However, when it is given territorial materiality, memory is almost always symbolically and politically framed and interpreted; Vale and Campanella had already outlined this political aspect of remembrance and resilience as a discourse. Resilience and the territorialization of memory are not ideologically neutral, but urban risk mitigation may come at that price.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.154-162
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• 2022

Purpose: The government intends to come up with measures to revitalize safety management at construction sites to shift safety management at construction sites from human capabilities to system-oriented management systems using advanced technologies AIoT and Mobile technologies. Method: The construction site safety management monitoring system using AIoT and Mobile technology conducted an experiment on the effectiveness of the construction site by applying three algorithms: virtual fence, fire monitoring, and recognition of not wearing a safety helmet. Result: The number of workers in the experiment was 215 and 7.61 virtual fence intrusion was 3.5% compared to the number of subjects and 0.16 fire detection were 0.07% compared to the subjects, and the average monthly rate of not wearing a safety helmet was 8.79, 4.05% compared to the subjects. Conclusion: It was found that the construction site safety management monitoring system using AIoT and Mobile technology has a valid effect on the construction site.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.591-598
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• 2019

The statistics of committing suicide in S. Korea is ranked in top with serious attempts of falling among OECD countries since 2003. The rates is slightly dropped by 5 percent point, nevertheless the falling is still high for the age of over 10 years old and this matter must be solved. Most of the case of suicides are the falling based on a trend view of falling which is serious matter and cannot be solved easily for both domestic and foreign countries. For example, the steel net of falling prevent was installed in the Golden Gate Bridge costed by 200 million-dollar. In New Zealand, the steel net of falling prevention had been removed and re-installed beccause of the high suicide rates. Canada and Australia also surrounded the bridge with steel fences to prevent suicide without consideration of the beauty of bridge. Therefore, this paper suggested a comparison study on both falling prevention systems in all countries and patent technologies. Also, it covers the blocking skills of approach in both security and limited area. This paper suggested the technical Rollinder system equipped with the mechanical apprentice to prevent effectively the falling sucides and wall passing. Before the installation of Rollinder System by 2016, there were 33 person who tried to fall in the river in Machang Bridge. However, the number of the committing suicides were dramatically reduced to zero after the installation of the system.

• Journal of the Korean earth science society
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• v.37 no.6
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• pp.346-358
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• 2016

This study built the volcano Data Base(DB) of 289 active volcanoes around the Korean Peninsula, Japan, China (include Taiwan), and Russia Kamchatka area. Twenty nine more hazardous volcanoes including Baekdusan, Ulleungdo and 27 Japanese volcanoes that can cause a widespread ash-fall on the Korean peninsula by potentially explosive eruption were selected. This selection was based on the presence of volcanic activity, whether or not containing dangerous explosive eruption rock types, distance from Seoul, and volcanoes having Plinian eruption history with volcanic explosivity index (VEI) 4 or more. The results of this study are utilized for screening high-risk volcanoes that may affect the volcanic disaster caused by a widespread fallout ash. By predicting the extent of spread of ash caused by these hazardous volcanic activities and by analyzing the impact on the Korean peninsula, we suggest that it should be used for helping to predict volcanic ash damages and conduct hazards mitigation research as well.

• Journal of the Korea Institute of Building Construction
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• v.24 no.3
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• pp.363-370
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• 2024

The escalating frequency and intensity of natural disasters and extreme weather events due to climate change have caused increasingly severe damage to societal infrastructure and buildings. Government agencies and private companies are actively working to evaluate these damages, but existing technologies and methodologies often fall short of meeting the practical demands for accurate assessment and prediction. This study proposes a novel approach to assess building damage resulting from natural disasters, focusing on typhoons-one of the most devastating natural hazards experienced in the country. The methodology leverages deep learning algorithms to evaluate typhoon-related damage, providing a comprehensive framework for assessment. The framework and outcomes of this research can provide foundational data for the evaluation of natural disaster-induced damage over the entire life cycle of buildings and can be applied in various other industries and research areas for assessing risk of damage.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.442-448
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• 2009

Recently, the natural disaster has occurred as a heavy snow fall, drought and flood by abnormal weather. The damage of human and property by flood is most serious problem among those natural disaster. In order to prepare structural or non-structural measure, to estimate exact flood discharge is important element. This study analyze frequency of hour-unit rainfall data and estimate probability flood discharge by HEC-HMS as changing method of runoff analysis. Also, this study analyze the peak flood discharge sensibility according to Curve Number(CN) with the return period. As a result of estimation of probability flood discharge with the variety CN, to select Antecedent Moisture To select suitable condition(AMC) is important parameter because flood discharge is estimated 40% gap according to AMC.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.150-162
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• 2011

For the period between 1991 and 2009, the annual average of 448 forest fires occurred in Korea. Above all, approximately 94% of the total fires frequently occurred during the spring and fall seasons. Therefore, we need to minimize the damage of forest fire and manage them systematically. In this study, we analyzed the spatio-temporal distribution patterns for the frequency of forest fire occurrences by each city and gun during dry season between 1990s and 2000s using GIS. Then we compared to analyze the frequency of forest fire occurrence by ten-day intervals in 2000s with that in 1990s. As a result of analysis, early April showed the highest frequency of forest fire occurrence in both 1990s and 2000s. Compared to the 1990s and 2000s, the regional change of forest fire showed the most frequent fire events around Chungcheong province. Especially extra 27 fires increased in Daejeon city, and the second most frequent fire had more than 10 fires in Jeolla province and Incheon. However, the number of fire frequency decreased by 12 fires at the end of April in Hongcheon-gun(the province of Gangwon). This is the largest drop over the study period. We consider that this paper will utilize usefully to establish regional counterplan for forest fire prevention by understanding regional forest fire patterns from seasonal change.

• Journal of KIBIM
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• v.6 no.2
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• pp.39-46
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• 2016

While institutional matters such as improvement on Basic Guidelines for Construction Safety are greatly concerned to reduce falling accidents at construction sites, there are short of studies on how to practically predict accident signs at construction sites and to preemptively prevent them. As one of existing accident prevention methods, it was attempted to build the early warning system based on standardized accident scenarios to control the situations. However, the investment cost was too high depending on the site situation, and it did not help construction workers directly since it was developed to mainly provide support operational work support to safety managers. In the long run, it would be possible to develop the augmented reality based accident prevention method from the worker perspective by extracting product information from BIM, visually rendering it along with site installation materials term and comparing it with the site situation. However, to make this method effective, the BIM model should be implemented first and the technology that can promptly process site situations should be introduced. Accordingly, it is necessary to identify risk signs through lightweight image processing to promptly respond only with currently available resources. In this study, it was intended to propose the system concept that identified potential risk factors of falling accidents by histogram equalization, which was known as the fastest image processing method presently, used visual words, which could enhance model classification by wording image records, to determine the risk factors and notified them to the work manager.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.399-408
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• 2018

Purpose: Recently, the ground subsidence has caused social problem, because it occurred life and economic damage. Method: Ground subsidence is different from a sink hole. Ground subsidence occurred cavities from loss of by groundwater flow, surface layer is collapsed due to relaxation and expansion. Results: According to the survey, the caused of ground subsidence are classified as ground cavities, surrounding ground relaxation and pipe joint failure. Conclution: Cavities of ground is mainly caused by cavities formed by rainfall induced infiltration of the heavy rainfall, loss of soil due to rise and fall of ground water level and repeated sewage runoff.