• 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.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.44-50
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• 2021

Recently, enterprise storage systems that require large-capacity storage devices to accommodate big data have used large-capacity flash memory-based storage devices with high density compared to cost and size. This paper proposes a high-efficiency life prediction method with slope descent to maximize the life of flash memory media that directly affects the reliability and usability of large enterprise storage devices. To this end, this paper proposes the structure of a matrix for storing metadata for learning the frequency of defects and proposes a cost model using metadata. It also proposes a life expectancy prediction policy in exceptional situations when defects outside the learned range occur. Lastly, it was verified through simulation that a method proposed by this paper can maximize its life compared to a life prediction method based on the fixed number of times and the life prediction method based on the remaining ratio of spare blocks, which has been used to predict the life of flash memory.

• Ocean Systems Engineering
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• v.8 no.4
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• pp.381-407
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• 2018

This paper presents a hybrid numerical approach, which combines a two-phase Navier-Stokes model (NS) and the fully nonlinear potential theory (FNPT), for modelling wave-structure interaction. The former governs the computational domain near the structure, where the viscous and turbulent effects are significant, and is solved by OpenFOAM/InterDyMFoam which utilising the finite volume method (FVM) with a Volume of Fluid (VOF) for the phase identification. The latter covers the rest of the domain, where the fluid may be considered as incompressible, inviscid and irrotational, and solved by using the Quasi Arbitrary Lagrangian-Eulerian finite element method (QALE-FEM). These two models are weakly coupled using a zonal (spatially hierarchical) approach. Considering the inconsistence of the solutions at the boundaries between two different sub-domains governed by two fundamentally different models, a relaxation (transitional) zone is introduced, where the velocity, pressure and surface elevations are taken as the weighted summation of the solutions by two models. In order to tackle the challenges associated and maximise the computational efficiency, further developments of the QALE-FEM have been made. These include the derivation of an arbitrary Lagrangian-Eulerian FNPT and application of a robust gradient calculation scheme for estimating the velocity. The present hybrid model is applied to the numerical simulation of a fixed horizontal cylinder subjected to a unidirectional wave with or without following current. The convergence property, the optimisation of the relaxation zone, the accuracy and the computational efficiency are discussed. Although the idea of the weakly coupling using the zonal approach is not new, the present hybrid model is the first one to couple the QALE-FEM with OpenFOAM solver and/or to be applied to numerical simulate the wave-structure interaction with presence of current.

• Smart Structures and Systems
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• v.23 no.2
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• pp.141-153
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• 2019

This research deals with wave propagation of the functionally graded (FG) nano-beams based on the nonlocal elasticity theory considering surface and flexoelectric effects. The FG nano-beam is resting in Winkler-Pasternak foundation. It is assumed that the material properties of the nano-beam changes continuously along the thickness direction according to simple power-law form. In order to include coupling of strain gradients and electrical polarizations in governing equations of motion, the nonlocal non-classical nano-beam model containg flexoelectric effect is used. Also, the effects of surface elasticity, dielectricity and piezoelectricity as well as bulk flexoelectricity are all taken into consideration. The governing equations of motion are derived using Hamilton principle based on first shear deformation beam theory (FSDBT) and also considering residual surface stresses. The analytical method is used to calculate phase velocity of wave propagation in FG nano-beam as well as cut-off frequency. After verification with validated reference, comprehensive numerical results are presented to investigate the influence of important parameters such as flexoelectric coefficients of the surface, bulk and residual surface stresses, Winkler and shear coefficients of foundation, power gradient index of FG material, and geometric dimensions on the wave propagation characteristics of FG nano-beam. The numerical results indicate that considering surface effects/flexoelectric property caused phase velocity increases/decreases in low wave number range, respectively. The influences of aforementioned parameters on the occurrence cut-off frequency point are very small.