• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1934-1938
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• 2008

Formation of air bubble is the one of common defects in UV nano imprint lithography. Location of dispensing and volume of droplets are among the most important parameters in the process. ]n this study, UV curable resin droplets with different volumes were dispensed at different locations and pressed to investigate air bubble formation. By varying volume of droplet and dispensing location, process conditions were found for minimum air bubble area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.561-564
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• 2008

본 논문에서 제안하는 버블(Bubble) 크기 보정 기법은 영상의 히스토그램의 모드법에 의한 최적의 임계값을 결정함으로써 버블의 크기를 정확하게 측정하는 기술이다. 제안하는 기술은 Ladle 탕면을 관측할 수 있는 CCD 카메라에 의한 측정시스템을 구현하며, 관측된 영상으로부터 방면거리, 버블크기 등을 알고리듬에 의해 구하여 탕의 용강 성분을 제어하기 위한 데이터를 제공하기 위하여 전송하게 된다. 본 논문에서 제안한 기법을 적용하여 실험한 결과 기존의 알고리듬에 의한 단순한 계산 및 히스토그램의 중간치 계산에 의한 결과와 비교하여 0.9%의 오차범위에서 개선된 버블크기를 얻을 수 있었다.

• Journal of Korea Game Society
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• v.7 no.4
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• pp.117-123
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• 2007

This paper presents the Stone Influence, the Influence Point, and the Influence Area on computer Go. The Stone Influence is defined using the distance between stone and empty point. The Influence Point is defined using threshold value on the Stone Influence. The Influence Area is defined using lump of the Influence Points and its Core. In experiments using the Jeongseok data, the author obtained the threshold of Influence Points. The proposed method was verified by experiments where it was success fully applied to the influence in game of Go.

• Journal of Ocean Engineering and Technology
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• v.26 no.2
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• pp.26-32
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• 2012

In this paper, the effects of irregular bead shapes on fatigue life were investigated. A modified S-N curve method was used to estimate the fatigue life, which considered the inherent multiaxiality caused by the geometrical feature produced by the welding process. The point method of the critical distance method was used to determine the fatigue effective stress. Three types of fillet joint models were tested in the fatigue experiments. For each model, real bead shapes were collected using a 3D laser scanner, and finite element analyses were performed. The results of the analyses with actual bead shapes were compared with those using an idealized bead shape model. The results of the present analytical methods showed good agreement with the experimental results.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.473-481
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• 2005

In this paper, we propose an image segmentation method preserving object's boundaries by using the number of quantized colors and merging regions using adaptive threshold values. First of all, the proposed method quantizes an original image by a vector quantization and the number of quantized colors is determined differently using PSNR each image. We obtain initial regions from the quantized image, merge initial regions in CIE Lab color space and RGB color space step by step and segment the image into semantic regions. In each merging step, we use color distance between adjacent regions as similarity-measure. Threshold values for region-merging are determined adaptively according to the global mean of the color difference between the original image and its split-regions and the mean of those variations. Also, if the segmented image of RGB color space doesn't split into semantic objects, we merge the image again in the CIE Lab color space as post-processing. Whether the post-processing is done is determined by using the color distance between initial regions of the image and the segmented image of RGB color space. Experiment results show that the proposed method splits an original image into main objects and boundaries of the segmented image are preserved. Also, the proposed method provides better results for objective measure than the conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.494-500
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• 2020

This paper proposes a new distance estimation technique for indoor localization in ultra wideband (UWB) systems. The proposed technique is based on recurrent neural network (RNN), one of the deep learning methods. The RNN is known to be useful to deal with time series data, and since UWB signals can be seen as a time series data, RNN is employed in this paper. Specifically, the transmitted UWB signal passes through IEEE802.15.4a indoor channel model, and from the received signal, the RNN regressor is trained to estimate the distance from the transmitter to the receiver. To verify the performance of the trained RNN regressor, new received UWB signals are used and the conventional threshold based technique is also compared. For the performance measure, root mean square error (RMSE) is assessed. According to the computer simulation results, the proposed distance estimator is always much better than the conventional technique in all signal-to-noise ratios and distances between the transmitter and the receiver.

• Journal of Bio-Environment Control
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• v.24 no.3
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• pp.210-216
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• 2015

Purpose of this study was a development of an image processing algorithm to recognize paprika and acquire it's 3D coordinates from stereo images to precisely control an end-effector of a paprika auto harvester. First, H and S threshold was set using HSI histogram analyze for extracting ROI(region of interest) from raw paprika cultivation images. Next, fundamental matrix of a stereo camera system was calculated to process matching between extracted ROI of corresponding images. Epipolar lines were acquired using F matrix, and $11{\times}11$ mask was used to compare pixels on the line. Distance between extracted corresponding points were calibrated using 3D coordinates of a calibration board. Non linear regression analyze was used to prove relation between each pixel disparity of corresponding points and depth(Z). Finally, the program could calculate horizontal(X), vertical(Y) directional coordinates using stereo camera's geometry. Horizontal directional coordinate's average error was 5.3mm, vertical was 18.8mm, depth was 5.4mm. Most of the error was occurred at 400~450mm of depth and distorted regions of image.

• Aerospace Engineering and Technology
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• v.6 no.1
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• pp.201-208
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• 2007

A fuel pump and turbine rotordynamic design is performed for a 75 ton thrust liquid rocket engine. A distance from the rear bearing to the turbine was considered as a design parameter for load distribution of the bearings. Asynchronous eigenvalue analysis was performed as a function of rotating speeds, turbine mass and bearing stiffness to investigate critical speed of the fuel pump and turbine. From the numerical analysis, it is found that the effect of the front bearing stiffness is negligible in the critical speed due to the large mass moment of inertia of the turbine. With the rear bearing stiffness over $2{\times}10^{8}N/m$ and the turbine mass below 20 kg, the critical speed of the fuel pump and turbine in long shaft case is at least 70 % higher than the operating speed 11,000 rpm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.487-496
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• 2011

This study is aimed to perform more reliable unsupervised change detection through the re-extraction of the changed pixels which were extracted with global thresholding by applying buffer zone concept. First, three buffer zone was divided on the basis of the thresholding value which was determined using range average and the maximum distance point from a straight line. We re-extracted the changed pixels by performing unsupervised classification for buffer zone II which consists of changed pixels and unchanged pixels. The proposed method was implemented in Hyperion hyperspectral images and evaluated comparing to the existing global thresholding method. The experimental results demonstrated that the proposed method performed more accuracy change detection for vegetation area even if extracted slightly more changed pixels.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.297-302
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• 2004

In this paper, the 3-D shape description for the objects with the cone ridge and valley surfaces, and the corresponding threshold value selection for surface classification are considered. The existing method based on the mean and Gaussian curvatures(H and K) of differential geometries cannot properly describe cone primitives, which are some of the most common objects in the real world. Also the existing method for surface classification based on the sign values of H and K has Problems in practical applications. For this, cone surface shapes are classified cone ridges and cone valleys are derived from surfaces using the fact that H values are constant case of cylinder surfaces and variable for cone surfaces, respectively. Also threshold value selection for surface classification from a statistical point of view is proposed. The effectiveness of the proposed methods are verified through experiments.