• Journal of Forest and Environmental Science
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• v.35 no.3
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• pp.197-204
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• 2019

A tree-length harvesting system using the HAM300, which is mounted on a farm tractor prototype machine, have been recently introduced in South Korea for thinning old (>30 years) forests. However, no research has previously been conducted on the characteristics of residual stand damage associated with cable yarding systems on thinning treatment stands in South Korea. Therefore, there were assessed on the degree and quantity of residual stand damage caused by felling and yarding process to broaden the knowledge of residual stand damage on semi-mechanized skyline thinning operations. This study investigated scar size, direction, area, shape type and their distribution on the residual stand damage caused by felling and yarding operations. Damage to residual trees was generated for 7.4% and 6.9% of residual trees in felling and yarding operations, respectively. Damaged direction of scars was located in front-side (38.9%) and up-side (34.7%) for felling operations while the highest scar damage was found on down-side (44.6%) for yarding operations. Scar heights of felling damage were higher than those of yarding damage. In yarding operation, the most of the scars was located within l0m from the center of the skyline corridor. These results should be useful information for forest managers and landowners to reduce residual stand damages and retain valuable timber volume from thinning treatments.

• Journal of Environmental Health Sciences
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• v.46 no.6
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• pp.726-734
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• 2020

Objectives: The aim of this study was to analyze and classify the characteristics of potential damage from hazardous chemical accidents in 229 administrative units in South Korea by reflecting the social and environmental characteristics of areas where chemical accidents can occur. Methods: A number of indicators were selected through preceding studies. Factor analysis was performed on selected indicators to derive factors, and cluster analysis was performed based on the factor scores. Results: As a result of the cluster analysis, 229 administrative units were divided into three clusters, and it was confirmed that each cluster had its own characteristics. Conclusions: The first cluster, "areas at risk of accident occurrence and spread of damage" was a type with a high potential for accident damage and a high density of hazardous facilities. The second cluster, "Urban infrastructure damage hazard areas" appeared to be a cluster with high urban development characteristics. Finally, the third cluster 'Urban and environmental damage hazard areas' appeared to be a cluster with an excellent natural environment. This study went further from the qualitative discussion related to existing chemical accidents to identify and respond to accident damage by reflecting the social and environmental characteristics of the region. Distinct from the previous studies related to the causes of accidents and the response system, it is meaningful to conduct empirical research focusing on the affected areas by analyzing the possibility of accident damage in reflection of the social and environmental characteristics of the community.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.273-276
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• 2014

In 2014, the leakage of personal information from 3 credit card companies resulted in divulging approximately 10,000 customers' personal information. Although the credit card companies concluded that there was no secondary loss due to the leakage of personal information, secondary financial losses resulting from the leakage of personal information currently occur. In particular, hackers who employ smishing masquerade acquaintances by using the divulged personal information to ask payment for Ms. Kim's Sochi Olympics legal processing or exposed traffic violations. The hackers cause secondary financial losses through smartphones. This study aims to conduct a forensic analysis of smishing incidents in smartphones through the leakage of personal information, and to make a forensic analysis of financial losses due to the smishing incidents.

• Korean Journal of Agricultural Science
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• v.31 no.2
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• pp.87-96
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• 2004

This study concentrates on the trail of the CNU(Chungnam National University) forest. The amount of use and the pattern of damage are considered, as well as the extent of environmental damage. Finally, some managerial strategies are proposed in connection with sustainable maintenance. The trail of the university forest is composed of three sections; one is the neighborhood park and the Institute of Information Technology/Communications, the second is the Institute of Information Technology/Communications and the Dormitory, and the third section is the Dormitory and the Foreign prof's Apt. The total length of the trail is 2.6km. The daily amount of use is 1,269 visitors per day. The amount of using increased three times the amount of that in 1998. This study shows the pattern of damage of the trail in the order of root-exposure, widening, rock-exposure, deepening and the divergence in the frequency of occurrence of all these factors. Environmental damage is also graded thus: grade 3 is 27.4m, grade 4 is 0.8m, grade 5 is 1.5m, and grade 6 is 0.2m. Accordingly, some managerial strategies were proposed in connection with the sustainable trail maintenance.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.271-278
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• 2011

Storm and flood such as torrential rains and major typhoons has often caused damages on a large scale in Korea and damages from storm and flood have been increasing by climate change and warming. Therefore, it is an essential work to maneuver preemptively against risks and damages from storm and flood by predicting the possibility and scale of the disaster. Generally the research on numerical model based on statistical methods, the KDF model of TCDIS developed by NIDP, for analyzing and predicting disaster risks and damages has been mainstreamed. In this paper, we introduced the model for prediction of damage cost from storm and flood by the neural network algorithm which outstandingly implements the pattern recognition. Also, we compared the performance of the neural network model with that of KDF model of TCDIS. We come to the conclusion that the robustness and accuracy of prediction of damage cost on TCDIS will increase by adapting the neural network model rather than the KDF model.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.201-210
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• 2020

This paper proposes a framework for the battle damage assessment (BDA) of electronic warfare linked to cyber warfare. Thanks to the rapid development of information and communication technology, the importance of cyber warfare and electronic warfare in cyberspace is increasing. Therefore, the BDA for cyber warfare and its associated electronic warfare in cyberspace is an important factor that affects the success or failure of military operations. In this paper, we propose a method to calculate measure of performance and measure of effectiveness by classifying the electronic warfare system into large / medium / small classes according to the type of electronic warfare. By setting up a hypothetical scenario, we show the effectiveness of the proposed framework.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.5
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• pp.95-105
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• 2021

Drought is a disaster that causes prolonged and wide scale damage. Recently, the severity and frequency of drought occurrences, and drought damage have been increased significantly due to climate change. As a result, a quantitative study of drought factors is needed to better understand and prevent future droughts. In the case of agricultural drought, several existing studies examine the economic damage caused by droughts and their causes, but these studies are not well suited to estimating crop-oriented agricultural drought damage and the factors that absolutely affect agricultural drought. This study determines which factors most affect agricultural drought. It examines meteorological factors and those related to agricultural water supplied by irrigation facilities. Rice paddy production per unit area is lower than the average from the last two years where agricultural drought occurred. We compare the relative frequency of agricultural drought impacts with irrigation facilities, effective reservoir storage, the number of water supply facilities, and the meteorological drought index such as Standardized Precipitation Index (SPI). To identify factors that affect agricultural drought, we correlate rice paddy production anomalies with irrigation water supply for the past two years. There was a high positive correlation between rice paddy production and irrigation water usage, and there was a low or moderate negative correlation between rice paddy production anomalies compared to the average of the past two years and SPI. As a result, agricultural water supply by irrigation facilities was judged to be more influential than meteorological factors in rice paddy production. This study is expected to help local governments establish policies related to agricultural drought response.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Journal of Environmental Science International
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• v.15 no.11
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• pp.1003-1010
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• 2006

It is very difficult to forecast accurately a damage from the natural disasters which occurs frequently. If the significant weather event was forecasted one or two days ago, we will be able to minimize a damage from the severe weather event through the suitable prevention activities. It said that 2000's our country's total damages from the meteorological disasters was several trillion won(Park et al, a, b, 2005). Therefore, we analyzed the Korea Meteorological Administration(KMA) and television broadcasting's reports, information contents, and transmission system, an ex post facto valuation about typhoon Nabi which struck the Korean peninsula from September 5 to 7, 2005. Through these investigations, we want to present the basic data to rises the application effect of disaster prevention meteorological information. We think KMA must present many information report to promote a citizen's understanding about the meteorological information and the serious disaster situation. And also we think the KMA and television broadcasting must present an advisable reports, the contents which is suitable to disaster response stages. And we must grasp the problem of disaster prevention meteorological information through an ex post facto examination, improve it effectively.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1119-1130
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• 2020

Flood disasters have been recently increasing worldwide due to climate change and extreme weather events. Since flood damage recovery has been conducted as a common coping strategy to flood disasters in the Republic of Korea, it is necessary to predict the regional flood damage costs by rainfall characteristics for a preventative measure to flood damage. Therefore, the purpose of this study is to present the regression functions for human and economic flood damage assessments for the 7 metropolises in the Republic of Korea. A comprehensive regression analysis was performed through the total 48 simple regression models on the two types of flood damage records for human and economic costs over the past two decades from 1998 to 2017 using the four kinds of nonlinear equations with each of the six rainfall variables. The damage assessment functions for each metropolis were finally selected by the evaluation of the regression results with the coefficient of determination and the statistical significance test, and then used for the human and economic flood damage assessments for 100-year rainfall in the 7 metropolises. The results of this study are expected to provide the basic information on flood damage cost assessments for flood damage mitigation measures.