• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.1-12
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• 2014

Crown fire, the main propagation type of large forest fire, has caused extreme damage with the fast spread rate and the high flame intensity. In this paper, we developed the probability equation to predict the crown fires using the spatial features of topography, fuel and weather in damaged area by crown fire. Eighteen variables were collected and then classified by burn severity utilizing geographic information system and remote sensing. Crown fire ratio and logistic regression model were used to select related variables and to estimate the weights for the classes of each variables. As a results, elevation, forest type, elevation relief ratio, folded aspect, plan curvature and solar insolation were related to the crown fire propagation. The crown fire propagation probability equation may can be applied to the priority setting of fuel treatment and suppression resources allocation for forest fire.

• Quality Improvement in Health Care
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• v.10 no.1
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• pp.20-27
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• 2003

Background : The doctors' strike was not only a manmade disaster but also a chance to apply a new pattern of emergency medical service for patients. We hope to propose a new pattern of emergency medical service by comparing the patterns of emergency medical service given by resident and staff during the doctors' strike. Methods : We reviewed the medical records of patients who received emergency medical service in the Emergency Department(ED) of Deagu Catholic University Hospital during 3 days a week prior to the residents' strike (July 21-23, 2000) with those of patients receiving emergency medical service during the first 3 days of the residents' strike (July 28-30, 2000). We evaluated the patient's severity, the cause of the ED visit, the performance on the laboratory study, ECG, and radiological study, the disposition, and the length of ED stay. Also, we compared the collected data by presenting doctor and by patient's severity. Results : The staff performed fewer tests admitted fewer emergent and non-emergent patients than the residents. Also, the length of ED stay was shorter in both the emergent (212.76 vs. 321.40 minutes) and the non-emergent groups (117.68 vs. 171.39 minutes) for patients presenting to staff. Conclusion : It is desirable that emergency medical service is given by staff, not by resident.

• Smart Structures and Systems
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• v.2 no.2
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• pp.127-140
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• 2006

In this study, a wavelet-based covariance-driven system identification technique is proposed for damage assessment of structures under ambient excitation. Assuming the ambient excitation to be a white-noise process, the covariance computation is shown to be able to separate the effect of random excitation from the response measurement. Wavelet transform (WT) is then used to convert the covariance response in the time domain to the WT magnitude plot in the time-scale plane. The wavelet coefficients along the curves where energy concentrated are extracted and used to estimate the modal properties of the structure. These modal property estimations lead to the calculation of the stiffness matrix when either the spectral density of the random loading or the mass matrix is given. The predicted stiffness matrix hence provides a direct assessment on the possible location and severity of damage which results in stiffness alteration. To demonstrate the proposed wavelet-based damage assessment technique, a numerical example on a 3 degree-of-freedom (DOF) system and an experimental study on a three-story building model, which are all under a broad-band excitation, are presented. Both numerical and experimental results illustrate that the proposed technique can provide an accurate assessment on the damage location. It is however noted that the assessment of damage severity is not as accurate, which might be due to the errors associated with the mode shape estimations as well as the assumption of proportional damping adopted in the formulation.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.4
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• pp.77-84
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• 2013

With the increase in occurrence frequency and severity of natural disasters due to climate changes arising from global warming, damage in the landscaping field is rising. This leads to legal disputes, and is increasing social and economic damage, too. Especially even though landscape trees which are highly affected by external environments, suffer lots of damage from natural disasters, there is no specific scope of disaster criteria and thus it brings plenty of problems of damage restoration and compensation. Therefore, this study aims to suggest that gives ways to improve related criteria for damage of landscape trees from natural disasters. For this objective, this study analyzed damage cases of landscape trees and precedents, and compared Korean and Japanese legal systems and criteria regarding natural disasters with each other. The analysis result showed that opinions of experts have a great deal of influence on judgment results, since there is no definite legal basis on damage from natural disasters in the landscaping field. This implies the need for a professional and objective appraisal process. According to the comparative analysis of Korean and Japanese legal systems and criteria regarding natural disasters, Korea lacked in laws and criteria on natural disasters of landscape plants in Korea, whereas there were concrete disaster assessment standards of landscape trees in Japan. For improving natural disaster-related systems and criteria in the landscaping field, therefore, this study presented 'Revision of related laws', 'Revision of appraisal and loss assessment criteria', 'Revision of standard specification of landscaping project', 'Compulsory insuring against disasters', 'Reasonable fulfillment of contract', and 'Compulsory cost estimation for disaster restoration', as improvement plans.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.83-90
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• 2009

Natural disasters, such as the recent floods in the Midwest, Hurricane Ike in the Gulf coast region (U.S.), and the earthquake in Sichuan (China), cause severe damage to the infrastructure as well as the associated industries and communities that rely on the infrastructure. The estimated damages due to Hurricane Ike in 2008 were a staggering $27 billion, the third worst in U.S. history. In addition, the worst earthquake in three decades in Sichuan resulted in about 90,000 people dead or missing and $20 billion of the estimated loss. A common observation in the analyses of these natural disaster events is the inadequacy of critical infrastructure to withstand the forces of natural calamities and the lack of mitigation strategies when they occur on the part of emergency-related organizations, industries, and communities. If the emergency-related agencies could identify and fortify the vulnerable critical infrastructure in the preparedness stage, the damage and impacts can be significantly reduced. Therefore, it is important to develop a decision support system (DSS) for identifying region-specific mitigation strategies based on the inter-relationships between the infrastructure and associated industries and communities in the affected region. To establish effective mitigation strategies, relevant data were collected from the affected areas with respect to the technical, social, and economic impact levels. The data analysis facilitated identifying the major factors, such as vulnerability, criticality, and severity, for developing a DSS. Customized mitigation strategies that will help agencies prepare, respond, and recover according to the disaster response were suggested.

• Health Policy and Management
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• v.17 no.4
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• pp.99-112
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• 2007

The purpose of this study was to analyze the effect of fire fighters' duty type on occurrence and severity of low back pain. Data were collected with questionnaire to 450 fire fighters working at 119 safety center and rescue unit of 30 fire stations in Gyeonggi-do. Finally the study was analyzed for 360 persons among them. The risk of experiencing of lower back pain occurred in the order of Rescue[odds ratio(OR) 3.36, 95% confidence interval(95% CI) 1.18-9.52], Vehicle operation(OR 2.63, 95% CI 1.26-5.50), First aid(OR 2.18, 95% CI 1.03-4.59), and Putting out a fire. The risk on severity of lower back pain occurred in the order of Vehicle operation(OR 4.00, 95% CI 1.57-9.80), First aid(OR 1.88, 95% CI 1.00-4.81), Putting out a fire, and Rescue. These result suggest that duty type of fire fighters may be a prognostic factor for occurrence and severity of low back pain. The potential implications of these findings are discussed about different approach for primary and secondary prevention by duty type of fire fighters.

• Research in Plant Disease
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• v.19 no.3
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• pp.196-200
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• 2013

This study was carried out to investigate yield loss due to soybean leaf spot disease caused by Cercospora sojina Hara and to determine the economic threshold level. The investigations revealed highly significant correlations between disease severity (diseased leaf area) and yield components (pod number per plant, total grain number per plant, total grain weight per plant, percent of ripened grain, weight of hundred seed, and yield). The correlation coefficients between leaf spot severity and each component were -0.90, -0.90, -0.92, -0.99, -0.90 and -0.94, respectively. The yield was inversely proportional to the diseased leaf area increased. The regression equation, yield prediction model, between disease severity (x) and yield (y) was obtained as y = -3.7213x + 354.99 ($R^2$ = 0.9047). Based on the yield prediction model, economic injury level and economic threshold level could be set as 3.3% and 2.6% of diseased leaf area of soybean.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Wind and Structures
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• v.2 no.3
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• pp.133-150
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• 1999

Significant costs to the public and private sectors due to recent extreme wind events have motivated the need for systematic post-hurricane damage data collection and analysis. Current post disaster data are collected by many different interested groups such as government agencies, voluntary disaster relief agencies, representatives of media companies, academicians and companies in the private sector. Each group has an interest in a particular type of data. However, members of each group collect data using different techniques. This disparity in data is not conducive to quantifying damage data and, therefore, inhibits the statistical and spatial description of damage and comparisons of damage among different extreme wind events. The data collection does not allow comparisons of data or results of analyses within a group and also prohibits comparison of damage data and information among different groups. Typically, analyses of data from a given event lead to different conclusion depending upon the definition of damage used by individual investigators and the type of data collected making it difficult for members of groups to compare the results of their analyses with a common language and basis. A formal method of data collection and analysis-within any single group-would allow comparisons to be made among different individuals, hazardous events and eventually among different groups, thus facilitating the management and reduction of damage due to future disaster. This research introduces a definition of damage to single family dwellings, and a common method of data collection and analysis suited for groups interested in regional characterization of damage. The current state-of-data is presented and a method for data collection is recommended based on these existing data collection methods. A fixed-scale damage index is proposed to consider the damage to a dwelling's feature. Finally, the damage index is applied to three dwellings damaged by Hurricane Iniki (1992). The damage index reflects the reduced functionality of a structure as a single family detached dwelling and provides a means to evaluate regional damage due to a single event or to compare damage due to events of different severity. Evaluation of the damage index and the data available support recommendation for future data collection efforts.

• Journal of the Korean GEO-environmental Society
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• v.17 no.12
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• pp.5-16
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• 2016

This study aims to assess the influence of rainfall patterns on shallow landslides initiation. Doing so, five typical rainfall patterns with the same cumulative amount and intensity components comprising Advanced (A1 and A2), Centralized (C), and Delayed (D1 and D2) were designed based on a historical rainstorm event in Jinbu. Mt area. Those patterns were incorporated as the hydrological conditions into the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model (TRIGRS) to assess their influences on groundwater pressure and changes in the stability of the slope. The results revealed that not only the cumulative rainfall thresholds necessary to initiate landslides, but also the rate at which the factor of safety decreases and the time required to reach the critical state, are governed by rainfall patterns. The sooner the peak rainfall intensity, the smaller the cumulative rainfall threshold, and the shorter the time until landslide occurrence. Left-skewed patterns were found to have a greater effect on landslide initiation. Specifically, among five rainfalls, pattern (A1) produced the most critical state. The severity of response was followed by patterns A2, C, D1, and D2. Our conclusion is that rainfall patterns have a significant effect on the cumulative rainfall threshold, the build-up of groundwater pressure, and the occurrence of shallow landslides.