• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.232-236
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• 2000

Multi-regression statistical analyses were applied for the water quality data of shallow alluvial ground water (n = 47) collected from the Youngdeok area, in order to quantitatively generalize the natural (non-anthropogenic) causes of regional water quality variation. Seven samples having the high contamination index ( $C_{a}$ > 3) reflect the striong effects by anthropogenic activity. Most of the alluvial groundwaters have acquired their quality primarily due to the dissolution of carbonate minerals. The results of multi-regression analysis show that chlorine is mainly derived from seawater effect. Sulfur isotopic compositions of dissolved sulfur and the S $O_4$/Cl ratio also enable us to discriminate the samples (n = 18) which are affected by atmospheric input of marine aerosol (sea-spray) and also by mixing between freshwater and seawater. Hydrogen and oxygen isotope data of the samples collected lie close to the local meteoric water line obtained from nearby Pohang city but has lower slope (5.45) on the $\delta$D-$^{18}$ O plot, indicating that alluvial groundwater was recharged from infiltrated meteoric water which has undergone some degree of kinetic evaporation. The estimated initial isotopic composition of the recharged water ($\delta$D = -74.8$^{0}$ /$_{00}$, $\delta$$^{18}$ O = -10.8$^{[-1000]}$ /$_{[-1000]}$ ) suggests that the alluvial ground water recharge largely occurs during summer storm events.s.s.

• Korean journal of applied entomology
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• v.33 no.3
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• pp.166-172
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• 1994

This study was conducted to investigate the resistance development and cross-res~stance of house fly (Musco dornestica L.) selected with chlorpyrifos, dichlorvos and permethrin for 11 generations to various p u p s of insectiodes. The resistance ratio (RR) of the chlorpyrifos-selected (Q), the d~chlorvos- selected (&) a d the permethrin-selected (R,) stmlns were 42 0. 38 and 187 tlrnes in female. and 42.0, 4 1 and 16.4 time; in male from the susceptible strain, respectively. The Rc strain showed highest cross-resistance to permethlin among the insectic~des tested: RR=7.5 and 9.6 tunes in female and male, respectively, whereas negatively correlated cross-resistance to propoxur was observed. High cross-res~atance to chlorpyrifos were produced for female (RR= 13.3) and male (RR=15.9) of Rd strain, and female (RR=8.7) and male (RR= 9 7) of R, strain. respectively

• Journal of Hydrogen and New Energy
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• v.22 no.6
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• pp.925-933
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• 2011

The traditional feedstock for dimethyl ether (DME) has been natural gas obtained by pipeline from a nearby natural gas or oil field. This report focuses on other feedstock: Coal bed methane (CBM). The resource availability and suitability of CBM for DME manufacturing have been investigated. CBM in a short time has become an important industry, providing an abundant clean-burning fuel and also suggesting as a feedstock for gas industry. The use of CBM will have very little impact on the KOGAS' DME process design and economics up to 50 vol% of $CO_2$ in the CBM source. Many of the CBM sources in Asia are high in $CO_2$, but pose no difficulties for the KOGAS' DME plant. Since tri-reformer requires substantial $CO_2$ in its feed, no $CO_2$ removal from the CBM feed is needed. The $CO_2$ in the CBM means that less $CO_2$ needs to be recycled from the downstream in the process.

• BMB Reports
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• v.51 no.4
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• pp.200-205
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• 2018

Exercise and resveratrol supplementation exhibit anti-obesity functions in the long term but have not been fully investigated yet in terms of their early potential effectiveness. Mice fed with high-fat diet were categorized into control (Cont), exercise (Ex), resveratrol supplementation (Res), and exercise combined with resveratrol supplementation (Ex + Res) groups. In the four-week period of weight loss, exercise combined with resveratrol supplementation exerted no additional effects on body weight loss but significantly improved whole-body glucose and lipid homeostasis. The combined treatment significantly decreased intrahepatic lipid content but did not affect intramyocellular lipid content. Moreover, the treatment significantly increased the contents of mtDNA and cytochrome c, the expression levels of peroxisome proliferator-activated receptor gamma coactivator-1 alpha and its downstream transcription factors, and the activities of ATPase and citrate synthase. However, exercise, resveratrol, and their combination did not promote myofiber specification toward slow-twitch type. The effects of exercise combined with resveratrol supplementation on weight loss could be partly due to enhanced mitochondrial biogenesis and not to fiber-type shift in skeletal muscle tissues.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.23-34
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• 2020

Recently, the artificial intelligence deep learning field has been hard to commercialize due to the high computing power and the price problem of computing resources. In this paper, we apply a double pruning techniques to evaluate the performance of the in-depth neural network and various datasets. Double pruning combines basic Network-slimming and Parameter-prunning. Our proposed technique has the advantage of reducing the parameters that are not important to the existing learning and improving the speed without compromising the learning accuracy. After training various datasets, the pruning ratio was increased to reduce the size of the model.We confirmed that MobileNet-V3 showed the highest performance as a result of NetScore performance analysis. We confirmed that the performance after pruning was the highest in MobileNet-V3 consisting of depthwise seperable convolution neural networks in the Cifar 10 dataset, and VGGNet and ResNet in traditional convolutional neural networks also increased significantly.

• Journal of the Korean Society of Safety
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• v.34 no.6
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• pp.50-57
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• 2019

In this study, various types of deep learning models that have been proposed recently are classified according to data input / output types and analyzed to find the deep learning model suitable for constructing a crack detection model. First the deep learning models are classified into image classification model, object segmentation model, object detection model, and instance segmentation model. ResNet-101, DeepLab V2, Faster R-CNN, and Mask R-CNN were selected as representative deep learning model of each type. For the comparison, ResNet-101 was implemented for all the types of deep learning model as a backbone network which serves as a main feature extractor. The four types of deep learning models were trained with 500 crack images taken from real concrete structures and collected from the Internet. The four types of deep learning models showed high accuracy above 94% during the training. Comparative evaluation was conducted using 40 images taken from real concrete structures. The performance of each type of deep learning model was measured using precision and recall. In the experimental result, Mask R-CNN, an instance segmentation deep learning model showed the highest precision and recall on crack detection. Qualitative analysis also shows that Mask R-CNN could detect crack shapes most similarly to the real crack shapes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.77-82
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• 2021

There are three types of urinalysis: physical test, chemical test, and microscopic test. Among these, the chemical urinalysis is an easily accessible method of the general public to compare the chemical reaction of urinalysis strip with a standard colorimetric table by sight or purchase the portable urinalysis machine separately. Currently, with the popularization of smartphone, research on the urinalysis service using smartphone is increasing. The urinalysis screening application is one of the urinalysis services using a smartphone. However, the RGB values of the urinalysis pad taken by the urinalysis screening application have large deviations due to the effect of lighting. Deviation of RGB value debases the accuracy of urinalysis discrimination. Therefore, in this paper, the accuracy of urinaylsis pad image discrimination is improved through CNN after classifying urinalysis strips taken by the urinalysis screening application based on smartphone by urinalysis pad items. Urinalysis strip was taken from various backgrounds to generate CNN image, and urinalysis discrimination was analyzed using the ResNet-50 CNN model.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.45-53
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• 2020

The purpose of this paper is to reduce the ratio of the patient accidents that may occur in nursing hospitals. In other words, it determines whether the person approaching the dangerous area is a elderly (patient uniform) group or a practitioner(Casual Clothing) group, based on the clothing displayed by CCTV. We collected the basic learning data from web crawling techniques and nursing hospitals. Then model training data was created with Image Generator and Labeling program. Due to the limited performance of CCTV, it is difficult to create a good model with both high accuracy and speed. Therefore, we implemented the ResNet model with relatively excellent accuracy and the YOLO3 model with relatively excellent speed. Then we wanted to allow nursing hospitals to choose a model that they wanted. As a result of the study, we implemented a model that can distinguish patient and casual clothes with appropriate accuracy. Therefore, it is believed that it will contribute to the reduction of safety accidents in nursing hospitals by preventing the elderly from accessing the danger zone.

• Applied Chemistry for Engineering
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• v.22 no.6
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• pp.658-663
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• 2011

The SNCR-SCR (selective non-catalytic reduction-selective catalytic reduction) hybrid system is an economical NOx removal system. In this study, the effect of the operating parameters of the SNCR-SCR hybrid system on NOx removal efficiency was investigated. When the SNCR reactor was operated at a temperature lower than the optimum temperature ($900{\sim}950^{\circ}C$), an additional NO removal is obtained basesd on the utilization of $NH_3$ slip. On the other hand, the SNCR reactor operated above the temperature resulted in no additional NO removal of SCR due to decomposition of $NH_3$. Therefore, the SNCR process should be operated at optimum temperature to obtain high NO removal efficiency and low $NH_3$ slip. Thus, it is important to adjust NSR (normalized stoichiometric ratio) so that $SR_{RES}$ can be maintained at an appropriate level.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.1
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• pp.1-9
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• 2022

The goal of this paper is to create a deep learning model based on triplet loss for generating similar child drawing selection algorithms. To assess the similarity of children's drawings, the distance between feature vectors belonging to the same class should be close, and the distance between feature vectors belonging to different classes should be greater. Therefore, a similar child drawing selection algorithm was developed in this study by building a deep learning model combining Triplet Loss and residual network(ResNet), which has an advantage in measuring image similarity regardless of the number of classes. Finally, using this model's similar child drawing selection algorithm, the similarity between the target child drawing and the other drawings can be measured and drawings with a high similarity can be chosen.