• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.320-323
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• 2014

Today is going with the advancement of intelligent transportation systems and traffic environment and helping to provide safe and convenient service through a mobile device work with the popularization of the vehicle black box. The traffic flow by a variety of causes is constantly changing, it is often unable to prepare the driver, depending on external factors can not be controlled by the power of the public, leading to a major accident. The system needs to pass the real-time weather data in the inter-operator to prevent this. The proposed detection algorithm weather information delivered real-time weather information for this paper. The weather condition is detected by using the contrast between the histogram of the motion of the wiper and the clear day algorithm. In general, the wiper is worked in extreme weather conditions that will have a value different contrast due to rain or snow. Situation was considered clear, snowy conditions, such as using it on a rainy situation. First, designated as ROI (Region Of Interest) of the minimum area that can be detected in order to reduce the amount of calculation for the wiper, the wiper, which was detected through the operation of the threshold Thresholding the brightness of the vehicle wiper. In addition, we distinguish the value of each meteorological situation by using contrast. Results was obtained to 80% for the snow conditions, a rainy situation.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1837-1846
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• 2022

The annual increase in chemical accidents is causing damage to life and the environment due to the spread and residual of substances. Environmental damage investigation is more difficult to determine the geographical scope and timing than human damage investigation. Considering the reality that there is a lack of professional investigation personnel, it is urgent to develop an efficient quantitative evaluation method. In order to improve this situation, this paper conducted a chemical accidents investigation using unmanned aerial vehicles(UAV) equipped with various sensors. The damaged area was calculated by Ortho-image and strength of agreement was calculated using the normalized difference vegetation index image. As a result, the Cohen's Kappa coefficient was 0.649 (threshold 0.7). However, there is a limitation in that analysis has been performed based on the pixel of the normalized difference vegetation index. Therefore, there is a need for a chemical accident investigation plan that overcomes the limitations.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.297-303
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• 2021

When sound waves propagate over long distances in shallow water, measured transmission loss is greater than predicted one using underwater acoustic model with the Rayleigh reflection model due to inhomogeneity of the bottom. Accordingly, the US Navy predicts sound wave propagation by applying the empirical formula-based High Frequency Bottom Loss (HFBL) model. In this study, the measurement and analysis of transmission loss was conducted using mid-frequency (2.3 kHz, 3 kHz) in the shallow water of the East Sea in summer. BELLHOP eigenray tracing output shows that only sound waves with lower grazing angle than the critical angle propagate long distances for several kilometers or more, and the difference between the predicted transmission loss based on the Rayleigh reflection model and the measured transmission loss tend to increase along the propagation range. By comparing the Rayleigh reflection model and the HFBL model at the high grazing angle region, the bottom province, the input value of the HFBL model, is estimated and BELLHOP transmission loss with HFBL model is compared to measured transmission loss. As a result, it agrees well with the measurements of transmission loss.

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.643-659
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• 2022

Geologic sequestration technologies such as CCS (carbon capture and storage), EGS (enhanced geothermal systems), and EOR (enhanced oil recovery) have been widely implemented in recent years, prompting evaluation of the mechanical stability of storage sites. As fluid injection can stimulate mechanical instability in storage layers by perturbing the stress state and pore pressure, poroelastic models considering various injection scenarios are required. In this study, we calculate the pore pressure, stress distribution, and vertical displacement along a surface using commercial finite element software (COMSOL); fault slips are subsequently simulated using PyLith, an open-source finite element software. The displacement fields, are obtained from PyLith is transferred back to COMSOL to determine changes in coseismic stresses and surface displacements. Our sequential use of COMSOL-PyLith-COMSOL for poroelastic modeling of fluid-injection and induced-earthquakes reveals large variations of pore pressure, vertical displacement, and Coulomb failure stress change during injection periods. On the other hand, the residual stress diffuses into the remote field after injection stops. This flow pattern suggests the necessity of numerical modeling and long-term monitoring, even after injection has stopped. We found that the time at which the Coulomb failure stress reaches the critical point greatly varies with the hydraulic and poroelastic properties (e.g., permeability and Biot-Willis coefficient) of the fault and injection layer. We suggest that an understanding of the detailed physical properties of the surrounding layer is important in selecting the injection site. Our numerical results showing the surface displacement and deviatoric stress distribution with different amounts of fault slip highlight the need to test more variable fault slip scenarios.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.471-484
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• 2023

Deep learning models based on generative adversarial neural networks are specialized in generating new information based on learned information. The deep generative models (DGMR) model developed by Google DeepMind is an generative adversarial neural network model that generates predictive radar images by learning complex patterns and relationships in large-scale radar image data. In this study, the DGMR model was trained using radar rainfall observation data from the Ministry of Environment, and rainfall prediction was performed using an generative adversarial neural network for a heavy rainfall case in August 2021, and the accuracy was compared with existing prediction techniques. The DGMR generally resembled the observed rainfall in terms of rainfall distribution in the first 60 minutes, but tended to predict a continuous development of rainfall in cases where strong rainfall occurred over the entire area. Statistical evaluation also showed that the DGMR method is an effective rainfall prediction method compared to other methods, with a critical success index of 0.57 to 0.79 and a mean absolute error of 0.57 to 1.36 mm in 1 hour advance prediction. However, the lack of diversity in the generated results sometimes reduces the prediction accuracy, so it is necessary to improve the diversity and to supplement it with rainfall data predicted by a physics-based numerical forecast model to improve the accuracy of the forecast for more than 2 hours in advance.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.3
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• pp.56-63
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• 2023

In this paper, we studied the effect of electron beam irradiation on sol-gel indium-gallium-zinc oxide (IGZO) thin films under air and nitrogen atmosphere and carried out the electrical characterization of the s ol-gel IGZO thin film transistors (TFTs). To investigate the optical properties, crystalline structure and chemical state of the sol-gel IGZO thin films after electron beam irradiation, UV-Visible spectroscopy, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) were carried out. The sol-gel IGZO thin films exhibited over 80% transmittance in the visible range. The XRD analysis confirmed the amorphous nature of the sol-gel IGZO films regardless of electron beam irradiation. When electron beam irradiation was conducted in a nitrogen (N₂) atmosphere, we observed an increased proportion of peaks related to M-O bonding contributed to the improved quality of the thin films. Sol-gel IGZO TFTs subjected to electron beam exposure in a nitrogen atmosphere exhibited enhanced electrical characteristics in terms of on/off ratio and electron mobility. In addition, the electrical parameters of the transistor (on/off ratio, threshold voltage, electron mobility, subthreshold swing) remained relatively stable over time, indicating that the electron beam exposure process in a nitrogen atmosphere could enhance the reliability of IGZO-based thin-film transistors in the fabrication of sol-gel processed TFTs.

• The Journal of Engineering Geology
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• v.15 no.3
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• pp.337-348
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• 2005

Jurassic granite from Pocheon area were tested to investigate the effect of microcracks on mechanical properties of the granite. Three oriented core specimens were used for uniaxial compressive tests and each core specimen are perpendicular to the axes'R'(rift plane),'c'(grain plane) and'H'(hardway plane), respectively Among vacious elastic constants, the variation of Poisson's ratio as function of the directions was examined. From the related chart between ratio of failure strength and Poisson's ratio, H-specimen shows the highest range in Poisson's ratio and Poisson's ratio decreases in the order of C-specimen and R-specimen. The curve pattern is nearly linear in stage $I\simIII$ but the slope increases abruptly in stage H-3. As shown in the related chart, diverging point of a curve is formed when ratio of failure strength is $0.92\sim0.96$ Stage IV -3 is out of elastic region. The behaviour of rock in the four fracturing stages was analyzed in term of the stress-volumetric strain me. From the stress increment-volumetric strain equations governing the behaviour of rock, characteristic material constants, a, n, Q, m and $\varepsilon_v^{mcf}$, were determined. Among these, inherent microcrack porosity$(a, 10^{-3})$ and compaction exponent(n) in the microcrack closure region(stage I ) show an order of $a^R(3.82)>a^G(3.38)>a^H(2.32)\;and\;n^R(3.69)>n^G(2.79)>n^H(1.99)4, respectively. Especially, critical volumetric microcrack strain($\varepsilon_v^{mcf}$) in the stage W is highest in the H-specimen, normal to the hardway plane. These results indicate a strong correlation between two major sets of microcracks and mechanical properties such as Poisson's ratio and material constants. Correlation of strength anisotropy with microcrack orientation can have important application in rock fracture studies.

• Progress in Medical Physics
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• v.21 no.2
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• pp.153-164
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• 2010

To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.

• Korean Chemical Engineering Research
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• v.40 no.6
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• pp.703-708
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• 2002

High pressure phase behavior data for poly(propyl acrylate) and poly(propyl methacrylate) with supercritical $CO_2$, ethylene, propane, butane, propylene, 1-butene, dimethyl ether, and $CHClF_2$ were measured in the temperature range from $23^{\circ}C$ to $186^{\circ}C$ and at pressures up to 2,400 bar. The cloud point were obtained at dissolved pressure below 2,070, 1,400, 1,880, 450, 2,200, 250, and 150 bar for poly(propyl acrylate) in supercritical $CO_2$, ethylene, propane, propylene, butane, 1-buthen, and dimethyl ether, respectively. The temperature range is $23-175^{\circ}C$. The poly(propyl methacrylate) does not dissolve in $CO_2$ at temperature of $240^{\circ}C$ and pressure 2,900 bar. The poly(propyl methacrylate)-propane, poly(propyl methacrylate)-butane, poly(propyl methacrylate)-propylene, poly(propyl methacrylate)-1-butene, and poly(propyl methacrylate)-$CHClF_2$ systems were dissolved at the pressures less than 2,390 bar, below 2,100 bar, below 570 bar, below 310 bar, below 300 bar, and below 170 bar, respectively. The temperature range shows from 40 to $186^{\circ}C$. The phase behavior of between binary poly(propyl acrylate)-$CO_2$ and poly(propyl acrylate)-dimethyl ether system were measured from upper critical solution temperature region to lower critical solution temperature region with added dimethyl ether concentrations of 5, 15 and 50 wt%.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.