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김철희,김효성,권민철,배근중,안주희,이학주,강하영,이현용 한국약용작물학회 2006 한국약용작물학회지 Vol.14 No.6
This study was performed to compare effect of anticancer activities on Rhodiola sachalinensis by ultrasonifi-cation process and solvent. Compared the yield to the water extracts (WE), wafer extracts with ultrasonification (WEU) at60, loot and ethyl alcohol extracts (EE), ethyl alcohol extracts with ultrasonification (EEU) at 60 ˚C from Rhodiola sachalinensis. Experimental studies were progressed through the anticancer activities such as cell cytotoxicity, inhibition activities of cell growth. The cell cytotoxicity using human embryonic kidney cell (HEK293) was showed cytotoxicity of below 26.26%by extracts of Rhodiola sachalinensis in 1.0 mg/ml concentration, The anticancer activities were increased in over 70% by extracts of Rhodiola sachalinensis in A549, AGS, Hep3B and MCF-7 cells. From the results, the extract Rhodiola sachalinensis were showed useful anticancer activities.
매립공사 시 비산먼지 발생량 및 AERMOD를 이용한 영향예측에 관한 연구
윤배근,서종범,김영식,최원준,김윤수,오광중,Yoon, Bae-Geun,Seo, Jong-Beom,Kim, Young-Seek,Choi, Won-Joon,Kim, Yun-Su,Oh, Kwang-Joong 한국환경보건학회 2009 한국환경보건학회지 Vol.35 No.4
A new harbor as been constructing in Gadukdo. However, a lot of fugitive dust gas been often generated from construction site reclaiming sea sand, especially when the Northwester is blown strongly. It has resulted insome appeals of residents in Gadukdo. In this study, we estimated the amount of fugitive dust caused by new harbor construction using Fugitive dust formula. Also, the concentration of PM10 for recipient is predicted by AERMOD. The amount of fugitive dust is 26.56 ${\mu}g/sec{\cdot}m^2$ and 11.84 ${\mu}g/sec{\cdot}m^2$ respectively by the Fugitive dust formula. PM10 outlet concentration and the amount of fugitive dust increase according to wind velocity and directions. AERMOD is performed on the basis of weather data and the amount of fugitive dust generated with wind velocity. As a result of AERMOD, the PM10 concentration of Sunchang and Oinul are predicted over 100 ${\mu}g/m^3$. The PM10 concentration of Sunchang and Oinul are predicted over 130 ${\mu}g/m^3$ when wind velocity of northwester in winter is over 11 m/s (Air Quality for Particulate Matter (100 ${\mu}g/m^3$ for 24 hours)). Also, the measured error between AERMOD and actual measurement is lower than 5%.
Fast Ellipse Detection based on Three Point Algorithm with Edge Angle Information
강동중,권배근,Zhu Teng,노태정 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.3
In this paper, we introduce a fast ellipse detection method that uses the geometric properties of threepoints on an ellipse. Many conventional ellipse detection methods carry out detection using five points, but arandom selection of such points among candidate edges requires much redundant processing. To search for anellipse with the minimum number of points, this study used the normal and differential equations of an ellipse,which requires three points based on their locations and edge angles. First, to reduce the number of candidateedges, the edges were divided into 8 groups depending on the edge angle, and then a new geometric constraintcalled the quadrant condition was introduced to reduce noisy candidate edges. Clustering was employed to findprominent candidates in the space of a few ellipse parameters. Experiments using many real images showed thatthe proposed method satisfies both reliability and computing speed for ellipse detection.
Fast Defect Detection for Various Types of Surfaces using Random Forest with VOV Features
권배근,원종섭,강동중 한국정밀공학회 2015 International Journal of Precision Engineering and Vol.16 No.5
Defect detection on an object surface is one of the most important tasks of an automated visual inspection system. The most modern defect detection systems are required to operate in real-time and handle high-resolution images. One of main difficulties in system applications is that it cannot be used for general inspection of various types of surface without tuning the internal parameters. In this paper, we demonstrate how to solve the problem mentioned above by using simple variance profile values of pixel intensities and applying it to the random-forest-based machine learning algorithm. Variance of Variance (VOV) profiles are used to describe the texture of an object surface and to amplify the irregularity of intensity variations. The feature amplification property of the VOV method can be applied generally to various types of surface and defect. For effective learning and reduction of false detection, a defect-size insensitive approach and a hard sample retraining process are introduced. The experimental results demonstrate reliable defect detection for various surface types without changing parameters.
Machine Learning-Based Imaging System for Surface Defect Inspection
박제강,강동중,권배근,박준협 한국정밀공학회 2016 International Journal of Precision Engineering and Vol.3 No.3
Modern inspection systems based on smart sensor technology like image processing and machine vision have been widely spread into several fields of industry such as process control, manufacturing, and robotics applications in factories. Machine learning for smart sensors is a key element for the visual inspection of parts on a product line that has been manually inspected by people. This paper proposes a method for automatic visual inspection of dirties, scratches, burrs, and wears on surface parts. Imaging analysis with CNN (Convolution Neural Network) of training samples is applied to confirm the defect's existence in the target region of an image. In this paper, we have built and tested several types of deep networks of different depths and layer nodes to select adequate structure for surface defect inspection. A single CNN based network is enough to test several types of defects on textured and non-textured surfaces while conventional machine learning methods are separately applied according to type of each surface. Experiments for surface defects in real images prove the possibility for use of imaging sensors for detection of different types of defects. In terms of energy saving, the experiment result shows that proposed method has several advantages in time and cost saving and shows higher performance than traditional manpower inspection system.