• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.2
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• pp.126-132
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• 2010

An approach to calculating expected damage of breakwater assisted by artificial neural network was developed. Wave height in front of a breakwater was predicted by a trained artificial neural network with inputs of wave height in deep ocean and tidal level. Prediction results by the neural network can be comparable to that by professional numerical model for wave transformation. Using the wave prediction neural network, it was very easy and fast to obtain a number of significant waves at breakwater and finally analysis time for expected damage can be shortened. In addition, the effect of considering tidal level in the calculation of expected damage was revealed by comparing the expected damages with and without tidal variation. Therefore, it was pointed out that tidal variation should be considered to improve prediction accuracy.

• Korean Journal of Plant Resources
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• v.35 no.2
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• pp.169-182
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• 2022

This study was conducted to predict the distribution of rare·endemic plants (Sophora koreensis Nakai) in the border forests where wildfire damage occurred and to quantify the damage. For this purpose, we tried to derive more accurate results through forest area damage (NBR) according to the Burn severity of wildfires, damage by tree species type (Vegetation map), and MaxEnt model. For Burn severity analysis, satellite imagery (Landsat-8) was used to analyze Burn severity (ΔNBR2016-2015) and to derive the extent of damage. To prepare the Vegetation map, the land cover map prepared by the Ministry of Environment, the Vegetation map prepared by the Korea Forest Service, and the vegetation survey conducted by itself were conducted to prepare the clinical map before and after the forest fire. Lastly, for MaxEnt model analysis, the AUC value was derived by using the habitat coordinates of Sophora koreensis Nakai based on the related literature and self-report data. As a result of combining the Maxent model analysis data with the Burn severity data, it was confirmed that 45.9% of the 44,760 m² of habitat (predicted) area of Sophora koreensis Nakai in the wildfire damaged area or 20,552 m², was damaged.

• Korean Journal of Organic Agriculture
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• v.29 no.1
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• pp.97-109
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• 2021

Plant parasitic nematodes are causing significant damage in crop production. There is a need to develop eco-friendly nematicide that reduces the damage of nematode and has little effect on the environment and human. In this study, we have isolated a substance having nematicidal activity from Ginkgo biloba L. outer seedcoat. Studies of G. biloba L. outer seedcoat are insufficient compared to the seed and leaves due to their odor and toxicity. The dried G. biloba L. outer seedcoat was extracted with dichloromethane:methanol (1:1) and fractionated into hexane, ethyl acetate and H₂O. Four steps TLC were performed from EtOAc fraction to purely isolate GB4-3 with nematicidal activity. To compare nematicidal activity, G. biloba L. seedcoat methanol extract and purified GB4-3 were investigated in terms of treatment concentration and time. As a result, the nematicidal activity increased with concentration and time. In the place treated with 20 ㎍/mL of crude G. biloba L. seedcoat MeOH extract, strong activity appeared after 12 hours, and 46% nematicidal activity shown after 18 hours. About 69% of nematicidal activity was confirmed in the place where GB4-3 purified from outer seedcoat was treated with 20 ㎍/mL, and the possibility of development as nematicide was very high. This study could be used as a basic data for the development of a nematode preparation from G. biloba L. outer seedcoat.

• Journal of fish pathology
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• v.26 no.3
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• pp.193-206
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• 2013

The ark shell, Scapharca broughtonii is a marine bivalve mollusks belonging to the family Arcidae and important seafood for Korean and Japanese, and southern coast is brisk bays for the ark shell aquaculture. However, productivity of ark shell from these regions were rapidly reduced during the last decade due to mass mortality. The reason of this great damage has not yet been identified. To overcome this economic loss, diverse investigations were focused on environmental factors that affects in the physiology of S. broughtonii, but microbiological researches were performed insufficiently. Hemoglobin is one of the major blood component of ark shell and is damaged by some species of bacterial toxins. We concentrated on this red pigment because hemolysis could be the cause of ark shell mortality. In this study, we analyzed microbial diversity of underwater sediments in coastal regions and also existences in the body of S. broughtonii. We investigate about 4,200 isolates collected from June to September for microbial diversity of sediments and ark shell. We screened all of culturable microorganisms, and identified 25 genera 118 species, 24 genera 89 species, 30 genera 109 species and 39 genera 141 species, and selected 140 unique colonies for identification and challenge assay.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.45-52
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• 2023

Due to natural disasters such as heavy rain that occurred in the metropolitan area in August 2022, human casualties and property damage are increasing. Accordingly, the government is making efforts to respond to natural disasters, but due to the absence of related standards and standardized standards, problems such as increased construction costs and deterioration in construction quality for disaster prevention facility maintenance projects are occurring. Accordingly, a rough construction cost estimation module was developed and applied to 25 new pumping stations in Korea. As a result of the analysis, the accuracy of the rough construction cost derived through the module recorded 70% of the detailed design cost, which is 4% higher than the previously used rough construction cost accuracy of 66% by the Ministry of Environment. Accordingly, it is expected that the efficiency of the disaster prevention project can be increased if the developed module is used to calculate the rough construction cost for storm and flood disaster prevention in the future.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.724-726
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• 2001

본 논문에서는 컴퓨터 바이러스의 자기 복제 특성을 용한 바이러스 탐지 및 복구 방안을 제안한다. 바이러스의 행동 패턴은 바이러스의 종류 만큼 다양하지만 파일 바이러스의 경우, 자기 복제 행동 패턴은 대부분의 바이러스가 유사하다. 파일 바이러스가 시스템 감염시키기 위해서는 기생할 실행파일을 열고, 자기 자신을 그 실행 파일에 복사해야 한다. 이와 같은 자기 복제 행위를 통해 바이러스가 광범위하게 선과될 때 피 피해도 커지게 된다. 바이러스치 자기 복제 특성을 감안하여 본 연구에서 제안하는 바이러스 탐지 알고리즘은 다음과 같은 득징을 가진다. 첫째, 바이러스의 자기복세 행동 패턴은 파일 입출력 이벤트로 표현하여 바이러스의 행동 패턴으로 일반화시켰다. 둘째, 바이러스의 1차 감염행위는 허용하고 2차 이후 감염 행위부터 탐지하고, 탐지되기 이전에 감염되었던, 파일들을 복구한다. 이는 일반적인 바이러스들이 자기 복제를 지속적으로 수행한다는 점에 착안하여 false-positive 오류를 줄이기 위한 것이다. 본 고에서 제안하는 방법을 사용함으로써 특정 문자열에 의한 바이러스 탐지 및 복구 방법의 단점을 보안할 수 있을 것으로 기대된다.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.163-174
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• 2012

CBI(Composite Burn Index) developed by USDA Forest Service is a index to measure burn severity based on remote sensing. In Korea, the CBI has been used to investigate the burn severity of fire sites for the last few years. However, it has been an argument on that CBI is not adequate to capture unique characteristics of Korean forests, and there has been a demand to develop KCBI(Korean Composite Burn Index). In this regard, this study aimed to develop KCBI by adjusting the CBI and to validate its applicability by using remote sensing technique. Uljin and Youngduk, two large fire sites burned in 2011, were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. Burn severity(BS) of the study areas were estimated by analyzing NDVI from SPOT images taken one month later of the fires. Applicability of KCBI was validated with correlation analysis between KCBI index values and NDVI values and their confusion matrix. The result showed that KCBI index values and NDVI values were closely correlated in both Uljin (r = -0.54 and p<0.01) and Youngduk (r = -0.61 and p<0.01). Thus this result supported that proposed KCBI is adequate index to measure burn severity of fire sites in Korea. There was a number of limitations, such as the low correlation coefficients between BS and KCBI and skewed distribution of KCBI sampling plots toward High and Extreme classes. Despite of these limitations, the proposed KCBI showed high potentials for estimating burn severity of fire sites in Korea, and could be improved by considering the limitations in further studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.712-721
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• 2017

Recently, the intensity and frequency of floods has increasing worldwide, and flood disasters have become a big problem. Flood disasters, which account for the largest portion of disasters, are floods accompanied by typhoons and localized heavy rainfall. As a result, they cause damage of levee overtopping, in which the water level of a river rises to the levee crown. Therefore, countermeasures are essential and necessary because of the damage to the facility itself as well as to life and other property. The damage magnitude depends on the collapse of the levee. A levee that is difficult to collapse will reduce the discharge inland significantly. Accordingly, the protection of the inland slope, where the collapse of the levee is initiated, is one of the most important countermeasures In this study, revetments with various porosity and forms were suggested and hydraulic experiments were carried out for each type. The hydraulic experiments showed that the stability of a revetment in an inland slope is strongly correlated with the weight per unit area of the revetment. The relationship between the critical velocity, which is the velocity at the moment of leaving the revetment, and the weight per unit area was derived. Through this study, by applying the nature friendly revetment, which has not yet been applied to Korea, it is expected that life and property damage caused by levee overtopping during flooding can be reduced, and a nature friendly river space can be constructed.

• Korean Journal of Weed Science
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• v.30 no.3
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• pp.282-290
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• 2010

The objective of this research was to discover the best method for weed management in environment-friendly rice paddy fields through the study on the effect of weed control and injury levels of rice plants as affected by size, input time, and input amount of golden apple snail (GAS). The efficacy of weed control as affected by GAS when applied at 5, 10, and 15 days after transplanting (DAT) was 98, 89, and 58%, respectively. The efficacy of weed control had declined as late the input time of GAS. On the other hand, the efficacy of weed control as affected by rice bran followed by GAS treatment was higher than by GAS treatment alone. Weed species such as Persicaria hydropiper, Echinochloa crus-galli, Scirpus juncoides, and Monochoria vaginalis were not completely controlled by GAS when applied late. Input amount and time of adult GAS (70 days after hatching) for effective weed control were 3 kg $10a^{-1}$ at 5 DAT, 6-7 kg $10a^{-1}$ at 10 DAT, and 7 kg $10a^{-1}$ at 15 DAT. Input time and amount of young GAS (35 days after hatching) for effective weed control were 0 day after harrow (DAH) and 1 kg $10a^{-1}$, respectively. The young GAS when applied 0 DAH at 1 kg $10a^{-1}$ provided 100% control of P. hydropiper, E. crus-galli, S. juncoides, M. vaginalis, Ludwigia prostrata, Eleocharis kuroguwai, Sagittaria trifolia and Cyperus difformis. The rice foliar injury caused by adult (3 kg $10a^{-1}$) and young (1 kg $10a^{-1}$) GAS were 5-7% and 1% respectively. There was no significant difference in rice injury by size and input amount of GAS on plant height and number of tiller. These data indicate that the young GAS when applied 1 kg $10a^{-1}$ at 0 day after harrow was the best method for weed management in environment-friendly rice paddy fields.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.