• Clinical and Experimental Reproductive Medicine
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• v.32 no.4
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• pp.301-314
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• 2005

Objective: Rebamipide is a propionic acid derivative that has an action of the inhibition of superoxide production and removal of hydroxyl radical with the sperm incubation and cryopreservation. In the present study, to investigate whether rebamipide is useful to treat male infertility and sterility, the author observed the antioxidative effects in patient with male infertility and also examined its absorption and distribution in rat genital organ. Methods: To measure the distribution of rebamipide in reproductive organ in the rat, carbon indicated rebamipide, $^{14}C-OPC-12759$, was orally administered to 10 Spraque-Dawley rats and its organ concentration in serum, liver, kidney, stomach, duodenum, colon, urinary bladder, seminal vesicle, epididymis and testicle were measured each time after 0.5, 1, 2, 4, 8 and 24 hours by using HPLC fluorescent method. The concentrations in semen were measured by HPLC fluorescent method in a sample of 50 infertile males who took 900 mg of rebamipide daily for 3 months. To measure the antioxidative effect and fertility rate for 3 months, each month before and after the treatment, sperm motility, vitality, the oxygen free radical formation, level of peroxidation, fetilizing capacity of semen sample which were obtained from infertile male patients by masturbation after at least 48 hours abstinence were analyzed by computer assisted semen analyzer, eosin-nigrosin stain, chemiluminescence, thiobarbituric acid method and hypo-osmotic swelling test. Simultaneously in a sample that wanted baby, both pregnancy and delivery were researched. Results: The $^{14}C-OPC-12759$ concentration in the body of white rats was highest in gastrointestinal organ like stomach, smal intestine and duodenum and followed by genital organ like seminal vesicle, testis and epididymis. The rebamipide concentration in semen of infertile males was $220.77{\pm}327.84ng/mL$ (SD) which showed a large deviation but it was higher than serum which was $126{\pm}76ng/mL$ (SD). In the infertile males, after the treatment with rebamipide, the level of seminal reactive oxygen species (ROS) and lipid peroxidation have significantly decreased in duration of the treatment (p<0.05) and sperm vitality and fertilizing capacity except sperm motility significantly improved on post treatment of 2~3 months (p<0.05). Out of the 41 cases who hoped for pregnancy, 15 cases (36.6%) became pregnant and 12 cases had childbrith, 2 cases had miscarriage and one case is ongoing. The side effect was observed in 1 case (2%) which experienced diarrhea but it was lost spontaneously. Conclusions: We conclude from this study that rebamipide showed relatively high tendancy of absorption and excretion in the genital organ. In infertile males who had elevated ROS in semen, by specifically inhibiting the cell damage from the antioxidation, a way to preserve sperm motility, vitality and fertilizing capacity was confirmed.

• Steel and Composite Structures
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• v.34 no.5
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.265-285
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• 2006

In text categorization a certain level of correctness of labels assigned to training documents is assumed without solid knowledge on that of real-world collections. Our research attempts to explore the quality of pre-assigned subject categories in a real-world collection, and to identify the relationship between the quality of category assignment in training set and text categorization performance. Particularly, we are interested in to what extent the performance can be improved by enhancing the quality (i.e., correctness) of category assignment in training documents. A collection of 1,150 abstracts in computer science is re-classified by an expert group, and divided into 907 training documents and 227 test documents (15 duplicates are removed). The performances of before and after re-classification groups, called Initial set and Recat-1/Recat-2 sets respectively, are compared using a kNN classifier. The average correctness of subject categories in the Initial set is 16%, and the categorization performance with the Initial set shows 17% in $F_1$ value. On the other hand, the Recat-1 set scores $F_1$ value of 61%, which is 3.6 times higher than that of the Initial set.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.29-38
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• 2010

We propose an interactive projection technique to display details of a large image in a high resolution and brightness by tracking a portable projector. A closed-loop based tracking method is presented to update the projected image while a user changes the position of the detail area by moving the portable projector. A marker is embedded in the large image to indicate the position to be occupied by the detail image projected by the portable projector. The marker is extracted in sequential images acquired by a camera attached to the portable projector. The marker position in the large display image is updated under a constraint that the center positions of marker and camera frame coincide in every camera frame. The image and projective transformation for warping are calculated using the marker position and shape in the camera frame. The marker's four corner points are determined by a four-step segmentation process which consists of camera image preprocessing based on HSI, edge extraction by Hough transformation, quadrangle test, and cross-ratio test. The interactive projection system implemented by the proposed method performs at about 24fps. In the user study, the overall feedback about the system usability was very high.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.125-140
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• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.23 no.5
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• pp.213-217
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• 2013

The GaN layer was typical III-V nitride semiconductor and was grown on the sapphire substrate which cheap and convenient. However, sapphire substrate is non-conductivity, low thermal conductivity and has large lattice mismatch with the GaN layer. In this paper, the poly GaN epilayer was grown by HVPE on the metallic compound graphite substrate with good heat dissipation, high thermal and electrical conductivity. We tried to observe the growth mechanism of the GaN epilayer grown on the amorphous metallic compound graphite substrate. The HCl and $NH_3$ gas were flowed to grow the GaN epilayer. The temperature of source zone and growth zone in the HVPE system was set at $850^{\circ}C$ and $1090^{\circ}C$, respectively. The GaN epilayer grown on the metallic compound graphite substrate was observed by SEM, EDS, XRD measurement.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.10-27
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• 2014

HAZUS-MH is a GIS-based computer program that estimates potential losses from multi-hazard phenomena: earthquakes, floods and hurricanes. With respect to seismic disaster, characteristics of a hypothetical or actual earthquake are entered into HAZUS. Then HAZUS estimates the intensity of ground shaking and calculates the correspondent losses. In this study, HAZUS was used as a part of the preparations of the future seismic events at a coastal plant facility area. To reliably characterize the target facility area, many geotechnical characteristics data were synthesized from the existing site investigation reports. And the buildings and facilities were sorted by analyzing their material and structural characteristics. In particular, the study area was divided into 17 blocks taking into account the situation of both land development and facility distribution. The ground conditions of blocks were categorized according to the site classification scheme for earthquake-resistant design. Moreover, seismic fragility curves of a main facilities were derived based on the numerical modeling and were incorporated into the database in HAZUS. The results estimated in the study area using HAZUS showed various seismic damage and loss potentials depending on site conditions and structural categories. This case study verified the usefulness of the HAZUS for estimating earthquake losses in coastal facility areas.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.3
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• pp.239-248
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• 2017

According to the structure, solenoid valve can be categorized as spool valve or poppet valve. While various research on spool valve which has simple structure and fine susceptibility to contamination has been conducted, poppet valve which has less susceptibility to contamination and advantage in a long time operation still need much research because of its complicated structure. In order to design the poppet valve, various parameters such as the diameter of the poppet, the angle of the poppet, the diameter of the disk, the spring stiffness, the spring preload and flow path structure should be considered. Conventional studies on poppet valve usually take only one design parameters and did not much focused on the effect of the parameters on flow characteristics. In this paper, the change of the flow characteristics according to the design parameters of the poppet valve for 3/2Way solenoid valve is analyzed. The previous studies and the results of initial model analysis was referred for the selection of the design parameters. The effects of design parameters on maximum pressure, minimum pressure, and pressure drop was examined using analysis of means(ANOM).

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.106-106
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• 2014

SIGMA (Scientific cubesat with Instrument for Global Magnetic field and rAdiation)는 근 지구공간에서 우주방사선량 측정과 자기장 변화 검출의 과학적 목적과 교육적 목적을 가지고 개발하고 있는 초소형 큐브위성이다. $100mm{\times}100mm{\times}340.5mm$의 크기로 약 3.6 kg의 무게를 가지며, 탑재체는 방사선에 대하여 인체와 동일한 산란 흡수 특성을 가진 Tissue Equivalent Proportional Counter (TEPC)와 자기장 측정을 위한 Magnetometer (Mag)이다. 위성체는 구조계, 자세제어계, 전력계, 명령 및 데이터처리계, 통신계로 구성되어있다. 구조계는 위성의 뼈대인 Chassis와 Mag deployer로 이루어져있고, 위성의 안정적인 자세유지를 목적으로 Attitude Control System (ACS) Board와 Torque Coil이 자세제어계로 구성된다. 전력의 생산과 공급 및 충전은 태양전지판과 Electrical Power System (EPS), 리튬 배터리로 구성된 전력계에서 이뤄지며, 명령 및 데이터처리계는 On Board Computer (OBC)와 Instrument Interface board (IIB)를 중심으로 서브시스템의 명령체계와 데이터처리를 다룬다. 통신계는 Uplink인 VHF 안테나와 Downlink인 UHF, S-band 안테나로 구성되며 지상과 명령을 송수신한다. SIGMA는 타임인터럽트 기능을 활용한 Flight Software (FSW)로 운용되며 임무에 따른 6가지 모드의 시나리오로 위성을 운용한다. 이에 SIGMA의 개발과 테스트 결과를 소개한다. 본 큐브위성 개발기술을 바탕으로 향후 천문관측용 위성에도 활용할 예정이다.