• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.227-243
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• 2015

In this paper, the effects of nonlinear soft clay on dynamic embedment of offshore pipeline were investigated. Seabed embedment by pipe-soil interactions has impacts on the structural boundary conditions for various subsea structures such as pipeline, riser, pile, and many other systems. A number of studies have been performed to estimate real soil behavior, but their estimation of seabed embedment has not been fully identified and there are still many uncertainties. In this regards, comparison of embedment between field survey and existing empirical models has been performed to identify uncertainties and investigate the effect of nonlinear soil parameter on dynamic embedment. From the comparison, it is found that the dynamic embedment with installation effects based on nonlinear soil model have an influence on seabed embedment. Therefore, the pipe embedment under dynamic condition by nonlinear parameters of soil models was investigated by Dynamic Embedment Factor (DEF) concept, which is defined as the ratio of the dynamic and static embedment of pipeline, in order to overcome the gap between field embedment and currently used empirical and numerical formula. Although DEF through various researches is suggested, its range is too wide and it does not consider dynamic laying effect. It is difficult to find critical parameters that are affecting to the embedment result. Therefore, the study on dynamic embedment factor by soft clay parameters of nonlinear soil model was conducted and the sensitivity analyses about parameters of nonlinear soil model were performed as well. The tendency on dynamic embedment factor was found by conducting numerical analyses using OrcaFlex software. It is found that DEF was influenced by shear strength gradient than other factors. The obtained results will be useful to understand the pipe embedment on soft clay seabed for applying offshore pipeline designs such as on-bottom stability and free span analyses.

• Journal of Sasang Constitutional Medicine
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• v.25 no.1
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• pp.51-61
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• 2013

Objectives We performed the simultaneous analysis for three compounds in Cheongsimyeonja-tang (CSYJT) and evaluated its anti-obesity effect. Methods The column for separation of three compounds was used Gemini $C_{18}$ column and maintained at $40^{\circ}C$. The mobile phase for gradient elution consisted of two solvent systems. The analysis was carried out at a flow rate of 1.0 mL/min with PDA detection at 275 nm. The injection volume was $10{\mu}L$. 3T3-L1 preadipocytes were differentiated into adipocytes by adding insulin, dexamethasone and 3-isobutyl-1-methylxanthine (IBMX) for 8 days in the absence or presence of CSYJT. Anti-obesity effects of CSYJT were evaluated by Oil Red O staining, glycerol-3-phosphate dehydrogenase (GPDH) activity, triglyceride contents, and leptin production. Results Calibration curves were acquired with $r^2$ >0.9999. The contents of baicalin, wogonoside and baicalein in CSYJT were 14.54-14.65 mg/g, 5.24-5.27 mg/g and 0.01-0.02 mg/g, respectively. CSYJT showed inhibitory effect on lipid accumulation and GPDH activity in the differentiated 3T3-L1 cells. Furthermore, CSYJT significantly decreased contents of triglyceride and leptin production in 3T3-L1 adipocytes. Conclusions These results will be helpful to improve quality control and anti-obesity effect of Taeeumin CSYJT.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.48-55
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• 2020

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1698-1706
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• 1997

In this paper, we envisioned a multimedia object recognition system processing and combinig information from all available sources, such as 2-D, 3-D, color and sound data. Out of the overall system, we proposed 3-D information extraction and object recognition methods. Firstly, surfaces are classified by z-gradient from the range data, surface features are extracted using the intersection of normal vectors. Also feature relationship such as intersection angle and distance is established between the surfaces. Secondly, recognition is accomplished by matching process which is improtant step in the image understanding systems. Matching process is very improtant procedures because of more general and more efficient method is needed in the field of multimedia sytem. Therefore, we focused the proposal of matching process and in this article, first of all, we deal with the matching process of the 3-D object. Similarity measures are calculated.

• Journal of Pharmaceutical Investigation
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• v.28 no.1
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• pp.25-33
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• 1998

Intestinal absorption of ${\beta}-lactam$ antibiotics and angiotensin converting enzyme(ACE) inhibitors has been shown to use the carrier-mediated transport system. In vitro experiments have established that the efficacy of uptake by enterocytes depends on an inwardly directed proton gradient. It was suggested that benazepril was mediated by tripeptide transport system and that amoxicillin was transported by dipeptide transport carrier. The aim of this study is to assess the influence of amoxicillin on the intestinal absorption of benazepril using in vitro diffusion chamber and in situ single pass perfusion technique in the rat in order to elucidate whether the above transport systems are competitive or not. We obtained the gastrointestinal pemeability coefficient of amoxicillin, benazepril and both of them using in vitro diffusion chamber. And also the gastrointestinal absorption clearance of amoxicillin, benazepril and both of them using in situ single-pass perfusion method at steady state were calculated. Amoxicillin and benazepril were analyzed by HPLC. The results by the use of diffusion chamber in vitro indicated that the apparent intestinal permeability coefficient of benazepril was significantly(p<0.01) decreased by amoxicillin(45.2%) and vice versa significantly(p<0.01) decreased(89.1%). The results by the in situ gastrointestinal single-pass perfusion method indicated that the intestinal absorption clearance of benazepril was significantly(p<0.05) decreased by amoxicillin (40.2%) and vice versa significantly(p<0.05) decreased(54.8%). These results might suggest that they share the same peptide carrier pathway for oral absorption.

• Smart Media Journal
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• v.6 no.3
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• pp.15-20
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• 2017

Recently, the automotive industry has been studied about driver assistance systems for helping drivers to drive their cars easily by integrating them with the IT technology. This study suggests a method of detecting lanes, robust to road condition changes and applicable to lane departure warning and autonomous vehicles mode. The proposed method uses the method of detecting candidate areas by using the Gaussian filter and by determining the Otsu threshold value and edge. Moreover, the proposed method uses lane gradient and width information through the Hough transform to detect lanes. The method uses road lane information detected before to detect dashed lines as well as solid lines, calculates routes in which the lanes will be located in the next frame to draw virtual lanes. The proposed algorithm was identified to be able to detect lanes in both dashed- and solid-line situations, and implement real-time processing where applied to Raspberry Pi 2 which is open source hardware.

• Transactions on Electrical and Electronic Materials
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• v.14 no.2
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• pp.78-81
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• 2013

$0.95(Na_{0.5}K_{0.5})NbO_3-0.05BaTiO_3+0.2wt%\;Ag_2O$ (hereafter, No excess NKN) ceramics and $0.95(Na_{0.5}K_{0.5})NbO_3-0.05BaTiO_3+0.2wt%\;Ag_2O$ with excess $(Na_{0.5}K_{0.5})NbO_3$ (hereafter, Excess NKN) were fabricated by the conventional solid state sintering method, and their phase transition properties and dielectric properties were investigated. The crystalline structure of No excess NKN ceramics and Excess NKN ceramics were shown characteristics of polymorphic phase transition (hereafter, PPT), especially shift from the orthorhombic to tetragonal phase by increasing sintering temperature range from $1,100^{\circ}C$ to $1,200^{\circ}C$. Also, the temperature coefficient of capacitance (hereafter, TCC) of No excess NKN ceramics and Excess NKN ceramics from $-40^{\circ}C$ to $100^{\circ}C$ was measured to evaluate temperature stability for applications in cold regions. The TCC of No excess NKN and Excess NKN ceramics showed positive TCC characteristics at a temperature range from $-40^{\circ}C$ to $100^{\circ}C$. Especially, Excess NKN showed a smaller TCC gradient than those of Excess NKN ceramics in range from $-40^{\circ}C$ to $100^{\circ}C$. Therefore, NKN piezoelectric ceramics combined with temperature compensated capacitor having negative temperature characteristics is desired for usage in cold regions.

• Journal of Soil and Groundwater Environment
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• v.8 no.1
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• pp.9-16
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• 2003

A new method has been proposed and developed that solves the problem of decreasing electroosmotic flow rate by excess $H^{+}$ and precipitation of heavy metal by $OH^{-}$. An electrolytic solution was circulated between the anode and cathode compartments that enabled the pH at the anode and cathode to be controlled. The change of the soil pH by circulation systems affects the operation time, by lowering the rate of increase of the electric potential gradient, and the removal efficiency of heavy metals, by affecting the soil pH. Since there was no effluent from the cathode compartment in circulation system, there was no need to treat the wastewater after the experiment, which resulted in the reduction of influent electrolyte volume.

• Korean Journal of Pharmacognosy
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• v.46 no.2
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• pp.160-166
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• 2015

Yijung-tang (YJT) is a traditional herbal formula comprising 4 medicinal herbs. In the present study, we performed the simultaneous analysis for three compounds of YJT and examined anti-allergic effects in vitro. The column for separation of three compounds was used Gemini C18 column and maintained at 40$^{\circ}C$. The mobile phase for gradient elution consisted of two solvent systems. To evaluate Th2 chemokines, YJT was treated into tumor necrosis factor (TNF)-${\alpha}$ and interferon (IFN)-${\gamma}$-stimulated HaCaT cells, and performed ELISA for thymus and activation regulated chemokine (TARC) and regulated on activation, normal T-cell expressed and secreted (RANTES). To measure Th2 cytokines, YJT was added into primary mouse splenocytes, and performed ELISA for interleukin (IL)-4, 5, 13. Calibration curves were acquired with r² >0.9999. The contents of liquiritin, glycyrrhizin, and 6-gingerol in YJT were 4.50 mg/g, 11.10 mg/g, and 1.33 mg/g, respectively. YJT inhibited production of TARC and RANTES in TNF-${\alpha}$ and IFN-${\gamma}$-treated HaCaT cells. YJT also reduced production of IL-4, 5, and 13 in primary mouse splenocytes. In conclusion, our data will be a valuable information to improve quality control and anti-allergic effects of YJT.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.1
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• pp.35-43
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• 2020

Turbidity has various effects on the water quality and ecosystem of a river. High turbidity during floods increases the operation cost of a drinking water supply system. Thus, the management of turbidity is essential for providing safe water to the public. There have been various efforts to estimate turbidity in river systems for proper management and early warning of high turbidity in the water supply process. Advanced data analysis technology using machine learning has been increasingly used in water quality management processes. Artificial neural networks(ANNs) is one of the first algorithms applied, where the overfitting of a model to observed data and vanishing gradient in the backpropagation process limit the wide application of ANNs in practice. In recent years, deep learning, which overcomes the limitations of ANNs, has been applied in water quality management. LSTM(Long-Short Term Memory) is one of novel deep learning algorithms that is widely used in the analysis of time series data. In this study, LSTM is used for the prediction of high turbidity(>30 NTU) in a river from the relationship of turbidity to discharge, which enables early warning of high turbidity in a drinking water supply system. The model showed 0.98, 0.99, 0.98 and 0.99 for precision, recall, F1-score and accuracy respectively, for the prediction of high turbidity in a river with 2 hour frequency data. The sensitivity of the model to the observation intervals of data is also compared with time periods of 2 hour, 8 hour, 1 day and 2 days. The model shows higher precision with shorter observation intervals, which underscores the importance of collecting high frequency data for better management of water resources in the future.