• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.74-85
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• 2022

The purpose of this paper is to review the applicability of the current standards for the evaluation method of input variables and performance level in seismic performance evaluation by dynamic plastic analysis of the concrete gravity-type dam to which MCE is applied, and to suggest improvements. To this end, a domestic concrete gravity-type dam was selected as a target facility, dynamic plasticity analysis was performed under various conditions, and applicability to input variables such as concrete tensile strength and breaking energy, was reviewed. By analyzing the effect of cracks at the bottom of the gravity dam on the stability of the activity, an improvement plan for the performance level evaluation method required to secure the water storage function was derived. If the proposed improvement plan is applied, it will have the effect of deriving more reasonable evaluation results than the current seismic performance evaluation method to which MCE is applied.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.551-560
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• 2021

Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9313-9317
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• 2014

Fragile histidine triad (FHIT) is a suppressor gene related to cervical cancer through CpG island hypermethylation. Folate is a water-soluble B-vitamin and an important cofactor in one-carbon metabolism. It may play an essential role in cervical lesions through effects on DNA methylation. The purpose of this study was to observe effects of folate and FHIT methylation and HPV 16 on cervical cancer progression. In this study, DNA methylation of FHIT, serum folate level and HPV16 status were measured using methylation-specific polymerase chain reaction (MSP), radioimmunoassay (RIA) and polymerase chain reaction (PCR), respectively, in 310 women with a diagnosis of normal cervix (NC, n=109), cervical intraepithelial neoplasia (CIN, n=101) and squamous cell carcinoma of the cervix (SCC, n=101). There were significant differences in HPV16 status (${\chi}^2=36.64$, P<0.001), CpG island methylation of FHIT (${\chi}^2=71.31$, P<0.001) and serum folate level (F=4.57, P=0.011) across the cervical histologic groups. Interaction analysis showed that the ORs only with FHIT methylation (OR=11.47) or only with HPV 16 positive (OR=4.63) or with serum folate level lower than 3.19ng/ml (OR=1.68) in SCC group were all higher than the control status of HPV 16 negative and FHIT unmethylation and serum folate level more than 3.19ng/ml (OR=1). The ORs only with HPV 16 positive (OR=2.58) or with serum folate level lower than 3.19ng/ml (OR=1.28) in CIN group were all higher than the control status, but the OR only with FHIT methylation (OR=0.53) in CIN group was lower than the control status. HPV 16 positivity was associated with a 7.60-fold increased risk of SCC with folate deficiency and with a 1.84-fold increased risk of CIN. The patients with FHIT methylation and folate deficiency or with FHIT methylation and HPV 16 positive were SCC or CIN, and the patients with HPV 16 positive and FHIT methylation and folate deficiency were all SCC. In conclusion, HPV 16 infection, FHIT methylation and folate deficiency might promote cervical cancer progression. This suggests that FHIT may be an effective target for prevention and treatment of cervical cancer.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.401-408
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• 2022

As research on a controlled environment system based on crop growth environment sensing for sustainable production of horticultural crops and its industrial use has been important, research on how to properly utilize soil moisture sensors for outdoor cultivation is being actively conducted. This experiment was conducted to suggest the proper method of utilizing the TEROS 12, an FDR (frequency domain reflectometry) sensor, which is frequently used in industry and research fields, for each orchard soil in three regions in Korea. We collected soils from each orchard where fruit trees were grown, investigated the soil characteristics and soil water retention curve, and compared TEROS 12 sensor calibration equations to correlate the sensor output to the corresponding soil volumetric water content through linear and cubic regressions for each soil sample. The estimated value from the calibration equation provided by the manufacturer was also compared. The soil collected from all three orchards showed different soil characteristics and volumetric water content values by each soil water retention level across the soil samples. In addition, the cubic calibration equation for TEROS 12 sensor showed the highest coefficient of determination higher than 0.95, and the lowest RMSE for all soil samples. When estimating volumetric water contents from TEROS 12 sensor output using the calibration equation provided by the manufacturer, their calculated volumetric water contents were lower than the actual volumetric water contents, with the difference up to 0.09-0.17 m³·m^-3 depending on the soil samples, indicating an appropriate calibration for each soil should be preceded before FDR sensor utilization. Also, there was a difference in the range of soil volumetric water content corresponding to the soil water retention levels across the soil samples, suggesting that the soil water retention information should be required to properly interpret the volumetric water content value of the soil. Moreover, soil with a high content of sand had a relatively narrow range of volumetric water contents for irrigation, thus reducing the accuracy of an FDR sensor measurement. In conclusion, analyzing soil water retention characteristics of the target soil and the soil-specific calibration would be necessary to properly quantify the soil water status and determine their adequate irrigation point using an FDR sensor.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.52-67
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• 2008

Recently, frequent occurrence of flash floods caused by climactic change has necessitated prompt and quantitative prediction of precipitation. In particular, the usability of rainfall radar that can carry out real-time observation and prediction of precipitation behavior has increased. Moreover, the use of distributed hydrological model that enables grid level analysis has increased for an efficient use of rainfall radar that provides grid data at 1km resolution. The use of distributed hydrologic model necessitates grid-type spatial data about target basins; to enhance reliability of flood runoff simulation, the use of visible and precise data is necessary. In this paper, physically based $Vflo^{TM}$ model and ModClark, a quasi-distributed hydrological model, were used to carry out flood runoff simulation and comparison of simulation results with data from Imjin River Basin, two-third of which is ungauged. The spatial scope of this study was divided into the whole Imjin River basin area, which includes ungauged area, and Imjin River basin area in South Korea for which relatively accurate and visible data are available. Peak flow and lag time outputs from the two simulations of each region were compared to analyze the impact of uncertainty in topographical parameters and soil parameters on flood runoff simulation and to propose effective methods for flood runoff simulation in ungauged regions.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.4
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• pp.11-23
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• 2018

The purpose of this study is to identify the ecological characteristics and biological interactions between species of the abandoned rice paddy field in mountainous areas and to suggest a management strategy for stable food chain formation and biodiversity enhancement. The study site is located in Uldae wetland of Songchu district Bukhansan National Park, site characteristics and biological habitat characteristics were identified through site survey and literature survey. With regard to physical environment, among geographical features, the Uldae Wetland and the neighborhood inside the basin was a gently sloping area($5{\sim}15^{\circ}$). And 64.0% of basin faced the north. With regard to water environment, the Uldae Wetland was wetland of rainfed paddy field depending on precipitation and the system of stream flowing into the wetland from valley. According to the results of examining flora in plant ecology, in general, they were herbaceous wetland species. 88.6% of existing plants inside the Uldae Wetland basin was a forest in the mountain. And Quercus spp. community and Pinus densiflora community accounted for 64.6% of that, and was dominant. Except for that, Salix koreensis community was distributed. The existing vegetation of Uldae Wetland inhabited wetland species and terrestrialization indicator species, and it was thought that partial terrestrialization inside the Uldae Wetland was in progress after the discontinuation of paddy cultivation, such as the expansion of Salix koreensis distribution area. In the status of appearing faunae in the Uldae Wetland with regard to wildbirds of appearing principal species, The Uldae wetland was based on a abandoned rice paddy field various wildlife, and was a wildlife feeding, spawning, and resting place. The water environment was an important factor in maintaining the wetland living creatures function, habitat of waterbirds and benthic macroinvertebrates, amphibians and odonate are spawning ground and habitat, it was affecting the vegetation ecosystem based on wetlands. In order to maintain the diversity of wildlife, it was important to maintain smooth water supply and water level. A stable food chain will be formed and the Uldae wetland biodiversity will be abundant by establishing the relationship between the species of Uldae wetland, which is abandoned rice paddy field, and the habitat environment favored by species belonging to the ecosystem stepwise linkage. The ecological characteristics of the Uldae wetlands and the relation between the species were analyzed and the environmental conditions were reflected in the planning and management plan of Uldae wetland ecology.

• The Korean Journal of Pesticide Science
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• v.9 no.1
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• pp.70-80
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• 2005

To evaluate the exposure of molinate in agricultural environment and its effect against the non-target crop in air, this experiment was conducted to elucidate volatilization characteristics of molinate in aquatic condition and to determine critical concentration of molinate in the air causing phytotoxicity to Chili pepper. Cumulative volatilized rate of molinate from water was 22.7% at $35^{\circ}C$ for water temperature and 20 L/min for air velocity while 3.2% at $25^{\circ}C$ and 10 L/min within 47 hour after applied under closed system, respectively. The molinate concentrations in air above 60 cm height from soil surface of valley and open paddy rice field were reached the highest value of 18.17 and $11.59{\mu}g/m^3$, respectively within 24 hours after applying granular formulation at dose rate of molinate 150 g/1,000 $m^2$. However, their concentrations were drastically diminished to around 0.18 and $0.51{\mu}g/m^3$ level in 20 days after application, which volatilization pattern were similar to both regions. Also, the concentration of molinate in air above 60 cm height from soil surface was distributed higher 2 times than that above 180 cm height. Meanwhile, a phytotoxic symptom against the nearby chili pepper was revealed within three days after applied and molinate was detected $0.004{\sim}0.006$ mg/kg level from severe damaged leaves. The dose and exposure relations of molinate in the air against the non-target crop was also investigated in lab trial. The phytotoxic symptom, shriveled leaves, of the chili pepper was encountered by exposing two days with concentration of $13.6{\mu}g/m^3$, three days with $6.8{\mu}g/m^3$ or four days with $3.4{\mu}g/m^3$. The symptom was still recovered within four weeks after the plants had received fresh air. On the other hand, the phytotoxic response through root uptake of the herbicide in water culture was relatively insensitive, in which the symptom is observed ten days with the concentration of 300 ${\mu}g/L$.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.203-211
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• 2018

Dam discharge is carried out for the management of rivers and area around rivers due to rainy season or drought. Dam discharge should be based on an accurate understanding of the flow rate that can be accommodated in the river. Therefore, understanding the allowable storage capacity of river is an important factor in the management of the environment around the river. However, the methods using water level meters and images, which are currently used to determine the allowable flow rate of rivers, show limitations in terms of accuracy and efficiency. In order to solve these problems, this paper proposes a method to automatically calculate the allowable storage capacity of river based on the images taken by drone. In the first step, we create a 3D model of the river by using the drone images. This generation process consists of tiepoint extraction, image orientation, and image matching. In the second step, the allowable storage capacity is calculated by cross section analysis of the river using the generated river 3D model and the road and river layers in the target area. In this step, we determine the maximum water level of the river, extract the cross-sectional profile along the river, and use the 3D model to calculate the allowable storage capacity for the area. To prove our method, we used Bukhan river's data and as a result, the allowable storage volume was automatically extracted. It is expected that the proposed method will be useful for real - time management of rivers and surrounding areas and 3D models using drone.