• Journal of the Korean Geosynthetics Society
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• v.20 no.2
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• pp.23-33
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• 2021

In Korea, many reservoirs have been built for the purpose of solving the food shortage problem and supplying agricultural water. However, the current 75.6% of the reservoirs are in serious aged as more than 50 years have passed since the year of construction. In the case of such an aging reservoir, the stability due to scour and erosion inside the reservoir is very reduced, and if concentrated rainfall due to recent abnormal weather occurs, the aging reservoir may collapse, leading to a lot of damage to property and human life. Accordingly, each agency that manages aging reservoirs uses Ordinary Portland Cement (OPC) as an injection material and applies the grouting method. However, in the case of OPC, it may deteriorate over time and water leakage may occur again. And there are environmental problems such as consumption of natural resources and generation of greenhouse gases. So, there is a need to develop new materials and methods that can replace the OPC. In this study, an laboratory test and analysis were performed on the grout material developed to induce a curing reaction similar to that of OPC by recycling power plant byproduct. In addition, test in the field such as electric resistivity survey, Standard Penetration Test (SPT), and field permeability test were performed to analyzed to reinforcement effect and determine the possibility of using instead of OPC. As a results of the test, in the case of recycled power plant byproduct, the compressive strength was 2.9 to 3.2 times and the deformation modulus was 2.3 to 3.3 times higher, indicating that it is excellent in strength and can be used instead of OPC. And it was analyzed that the N value of the reservoir was increased by 1~2, and the coefficient of permeability (k) decreased to the level of 8.9~42.5%. showing sufficient reinforcing effect in terms of order.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.1-12
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• 2022

An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.903-913
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• 2021

In the flood season, the measurement of the river discharge has many restrictions due to reasons such as budget, manpower, safety, convenience in measurement and so on. In particular, when heavy rain events occur due to typhoons, etc., it is difficult to measure the amount of flood due to the above problems. In order to improve this problem, in this study, a method was developed that can measure the river discharge in a flood season simply and safely in a short time with minimal manpower by combining the functions of a drone and a surface velocity doppler radar. To overcome the mechanical limitations of drones caused by weather issues such as wind and rainfall derived from the measurement of the river discharge using the conventional drone, we developed a drone with P56 grade dustproof and waterproof performance, stable flight capability at a wind speed of up to 36 km/h, and a payload weight of up to 10 kg. Further, to eliminate vibration which is the most important constraint factor in the measurement with a surface velocity doppler radar, a damper plate was developed as a device that combines a drone and a surface velocity Doppler radar. The velocity meter DSVM (Dron and Surface Veloctity Meter using doppler radar) that combines the flight equipment with the velocity meter was produced. The error of ±3.5% occurred as a result of measuring the river discharge using DSVM at the point of Geumsan-gun (Hwangpunggyo) located at Bonghwang stream (the first tributary stream of the Geum River). In addition, when calculating the mean velocity from the measured surface velocity, the measurement was performed using ADCP simultaneously to improve accuracy, and the mean velocity conversion factor (0.92) was calculated by comparing the mean velocity. In this study, the discharge measured by combining a drone and a surface velocity meter was compared with the discharge measured using ADCP and floats, so that the application and utility of DSVM was confirmed.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.451-468
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• 2021

Predicting hazardous ground conditions ahead of a TBM (Tunnel Boring Machine) tunnel face is essential for efficient and stable TBM advance. Although there have been several studies on the electrical resistivity survey method for TBM tunnelling, sufficient experimental data considering TBM advance were not established yet. Therefore, in this study, the laboratory-scale model experiments for simulating TBM excavation were carried out to analyze the applicability of an electrical resistivity survey for predicting hazardous ground conditions ahead of a TBM tunnel face. The trend of electrical resistivity during TBM advance was experimentally evaluated under various hazardous ground conditions (fault zone, seawater intruded zone, soil to rock transition zone, and rock to soil transition zone) ahead of a tunnel face. In the course of the experiments, a scale-down rock ground was provided using granite blocks to simulate the rock TBM tunnelling. Based on the experimental data, the electrical resistivity tends to decrease as the tunnel approaches the fault zone. While the seawater intruded zone follows a similar trend with the fault zone, the resistivity value of the seawater intrude zone decreased significantly compared to that of the fault zone. In case of the soil-to-rock transition zone, the electrical resistivity increases as the TBM approaches the rock with relatively high electrical resistivity. Conversely, in case of the rock-to-soil transition zone, the opposite trend was observed. That is, electrical resistivity decreases as the tunnel face approaches the rock with relatively low electrical resistivity. The experiment results represent that hazardous ground conditions (fault zone, seawater intruded zone, soil-to-rock transition zone, rock-to-soil transition zone) can be efficiently predicted by utilizing an electrical resistivity survey during TBM tunnelling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.815-824
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• 2022

Among the main facilities of the power plant, the circulating water used for cooling the power generation system is supplied through the Circulation Water Intake Basin (CWIB). The vortexes of various types generated in the Pump Sump (PS) of CWIB adversely affect the Circulation Water Pump (CWP) and pipelines. In particular, the free surface vortex accompanied by air intake brings about vibration, noise, cavitation etc. and these are the causes of degradation of CWP performance, damage to pipelines. Then power generation is interrupted by the causes. Therefore, it is necessary to investigate the hydraulic characteristics of CWIB through the hydraulic model experiment and apply an appropriate Anti Vortex Device (AVD) that can control the vortex to enable smooth operation of the power plant. In general, free surface vortex is controlled by Curtain Wall (CW) and the submerged vortex is by the anti vortex device of the curtain wall. The detailed specifications are described in the American National Standard for Pump Intake Design. In this study, the circulating water intake part of the Tripoli West 4×350 MW power plant in Libya was targeted, the actual operating conditions were applied, and the vortex reduction effect of the anti vortex device generated in the suction tank among the circulating water intake part was analyzed through a hydraulic model experiment. In addition, a floor splitter was basically applied to control the submerged vortex, and a new type of column curtain wall was additionally applied to control the vortex generated on the free surface to confirm the effect. As a result of analyzing the hydraulic characteristics by additionally applying the newly developed Column Curtain Wall (CCW) to the existing curtain wall, we have found that the vortex was controlled by forming a uniform flow. In addition, the vortex angle generated in the circulating water pump pipeline was 5° or less, which is the design standard of ANSI/HI 9.8, confirming the stability of the flow.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.1
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• pp.30-41
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• 2007

Purpose: Bone metastasis in breast cancer patients are usually assessed by conventional Tc-99m methylene diphosphonate whole-body bone scan, which has a high sensitivity but a poor specificity. However, positron emission tomography with $^{18}F-2-deoxyglucose$ (FDG-PET) can offer superior spatial resolution and improved specificity. FDG-PET/CT can offer more information to assess bone metastasis than PET alone, by giving a anatomical information of non-enhanced CT image. We attempted to evaluate the usefulness of FDG-PET/CT for detecting bone metastasis in breast cancer and to compare FDG-PET/CT results with bone scan findings. Materials and Methods: The study group comprised 157 women patients (range: $28{\sim}78$ years old, $mean{\pm}SD=49.5{\pm}8.5$) with biopsy-proven breast cancer who underwent bone scan and FDG-PET/CT within 1 week interval. The final diagnosis of bone metastasis was established by histopathological findings, radiological correlation, or clinical follow-up. Bone scan was acquired over 4 hours after administration of 740 MBq Tc-99m MDP. Bone scan image was interpreted as normal, low, intermediate or high probability for osseous metastasis. FDG PET/CT was performed after 6 hours fasting. 370 MBq F-18 FDG was administered intravenously 1 hour before imaging. PET data was obtained by 3D mode and CT data, used as transmission correction database, was acquired during shallow respiration. PET images were evaluated by visual interpretation, and quantification of FDG accumulation in bone lesion was performed by maximal SUV(SUVmax) and relative SUV(SUVrel). Results: Six patients(4.4%) showed metastatic bone lesions. Four(66.6%) of 6 patients with osseous metastasis was detected by bone scan and all 6 patients(100%) were detected by PET/CT. A total of 135 bone lesions found on either FDG-PET or bone scan were consist of 108 osseous metastatic lesion and 27 benign bone lesions. Osseous metastatic lesion had higher SUVmax and SUVrel compared to benign bone lesion($4.79{\pm}3.32$ vs $1.45{\pm}0.44$, p=0.000, $3.08{\pm}2.85$ vs $0.30{\pm}0.43$, p=0.000). Among 108 osseous metastatic lesions, 76 lesions showed as abnormal uptake on bone scan, and 76 lesions also showed as increased FDG uptake on PET/CT scan. There was good agreement between FDG uptake and abnormal bone scan finding (Kendall tau-b : 0.689, p=0.000). Lesion showed increased bone tracer uptake had higher SUVmax and SUVrel compared to lesion showed no abnormal bone scan finding ($6.03{\pm}3.12$ vs $1.09{\pm}1.49$, p=0.000, $4.76{\pm}3.31$ vs $1.29{\pm}0.92$, p=0.000). The order of frequency of osseous metastatic site was vertebra, pelvis, rib, skull, sternum, scapula, femur, clavicle, and humerus. Metastatic lesion on skull had highest SUVmax and metastatic lesion on rib had highest SUVrel. Osteosclerotic metastatic lesion had lowest SUVmax and SUVrel. Conclusion: These results suggest that FDG-PET/CT is more sensitive to detect breast cancer patients with osseous metastasis. CT scan must be reviewed cautiously skeleton with bone window, because osteosclerotic metastatic lesion did not showed abnormal FDG accumulation frequently.