• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2875-2878
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• 2003

In this paper, we propose an EEG-based mental state prediction method during a mental tasks. In the experimental task, a subject goes through the process of responding to visual stimulus, understanding the given problem, controlling hand motions, and hitting a key. Considering the subject's varying brain activities, we model subjects' mental states with defining selection time. EEG signals from four subjects were recorded while they performed three mental tasks. Feature vectors defined by these representations were classified with a standard, feed-forward neural network trained via the error back-propagation algorithm. We expect that the proposed detection method can be a basic technology for brain-computer interface by combining with left/right hand movement or cognitive decision discrimination methods.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.127-132
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• 2000

Though the increment of using computer vision system, there are lots of difficulties to measure precisely because of measurement error or distortion phenomenon. Among these reasons, the distortion of edge is dominant reason which is occurred by the blurred image. So, the problem of clear judgment about image focal point is very important. We must fix the discrimination criteria which is collected by image recognition of precise focus. To solve these problems, we compare with make processing methods using image intensity gradient, laplacian, and sum -modified laplacian operator. These experimental results showed modified mask processing method is effective.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.126-131
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• 1998

In computer vision system of modern industry precise measuring has lots of dfficulties because of measurement error due to distortion phenomenon. Among the difficulties, the distortion of edge is regraded as a dominent problem. which is caused by the vlurred image. The blurred image apperar when camera can not discriminate its precise focus. So. it is very important to decide focus of lens and to develop algorithm in order to correct distortion phenomenon. Thus. discrimination criteria obtained by image information of precise focus must be fixed in advance. The gray level histogram of image acquired from blurred edge tends to show a uniform distribution. Bimodal intensity histogram is related with condition of focus, and it is possible to find good condition of focus by using bimodal histogram of entropy.

• Tribology and Lubricants
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• v.29 no.3
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• pp.143-148
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• 2013

In this study, several sensor parts used to obtain better signal stability are designed, a separate control circuit for the sensor is developed, and the results obtained using this control circuit are analyzed. The capacitances of the whole sensor system are measured using the control circuit connected to an improved flexible printed circuit board and an asymmetric dual sensor coated with a ceramic material. To realize good discrimination for a small change in the measured capacitance as the engine oil deteriorates, a commercial application-specific integrated circuit is installed on the control circuit as a capacitance-to-digital converter. The absolute error of a measured signal is found to be approximately ${\pm}4fF$.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.239-240
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• 2006

In this study, we examined all peaks of confocal Raman spectra as peaks are the most important features for discrimination between basal cell carcinoma (BCC) and normal tissue (NOR). 14 peaks were extracted from these peaks using decision tree. For dimension reduction, frequently selected 4 peaks were chosen. They are located at 1014, 1095, 1439, $1523cm^{-1}$. These peaks were used as an input feature of the multilayer perceptron networks (MLP). According to the experimental results, MLP gave classification error rate of about 6.5%.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.52-55
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• 1996

Though the increment of using computer vision system in modern industry, there are lots of difficulties to measure precisely because of measurement error distortion phenomenon. Between these reasons, the distortion of edge is dominant reason which is occured by the blurred image. The blurred image is happened when camera can not discriminate its precise focus. To correct and generalize distortion phenomenon is imprrtant. Thus we must fix the discrimination criteria which is collected by image recognition of precise focus. The edge of image means discontinuous point of intensity, and the component of edge is discribed as high frequency component at special domain specturm of image. The good condition of focus means there are much high frequency energy in image. The method of discribing high frequency energy is gradient operater which determines the condition of focus.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1405-1416
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• 1995

An effective algorithm for implementation of unmanned surveillance system which detects moving object from image sequences, predicts the direction of it, and drives the camera in real time is proposed. Outputs of proposed algorithm are coordinates of location of moving object, and they are converted to the values according to camera model. As a pre- processing, extraction of moving object and shape discrimination are performed. Existence of the moving object or scene change is detected by computing the temporal derivatives of consecutive two or more images in a sequence, and this result of derivatives is combined with the edge map from one original gray level image to obtain the position of moving object. Shape discri-mination(Target identification) is performed by analysis of distribution of projection profiles in x and y directions. To reduce the prediction error due to the fact that the motion cha- racteristic of walking man may have an abrupt change of moving direction, an order adaptive lattice structured linear predictor is proposed.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.125-130
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• 2007

The principal morphological characters used for identification of hydrangea cultivars are often dependent on agroclimatic conditions. Furthermore, information on the selection or the genetic background of the hydrangea breeding is so rare that a molecular marker system for cultivar identification is needed. Amplified fragment length polymorphism (AFLP) markers were employed for fingerprinting Hydrangea macrophylla cultivars and candidate cultivars of H. macrophylla selected in Korea. One AFLP primer combination was sufficient to distinguish 17 H. macrophylla cultivars and 4 candidate cultivars. The profile of 19 loci that can minimize the error of amplification peak detection was constructed. AFLP markers were efficient for identification, estimation of genetic distances between cultivars, and cultivar discrimination. Based on the observed AFLP markers, genetic relationship was reconstructed by the UPGMA method. Seventeen H. macrophylla cultivars and H. macrophylla for. normalis formed a major cluster, and candidate cultivars selected in Korea formed another cluster.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.12-15
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• 2003

Korea Institute of Geoscience and Mineral Resources(KIGAM) is operating Wonju Korea Seismic Research Station(KSRS), 29 regional seismic research stations and 5 Korea-China joint seismic stations in China. Also KIGAM is operating Korea Earthquake Monitoring System (KEMS) to archive the real-time data stream and to determine event parameters (epicenter, origin time, and magnitude) by the automatic processing and analyst review. To do this, KEMS used KIGAM's regional seismic network and other institute's network in a near real-time base. From Dec. 1, 2001 to Nov. 30, 2002, 3,827 seismic events were analyzed in a automatic processing procedure and finally 3,437 events were analyzed by analyst and archived. But problem is this event catalog includes not only natural earthquake, but also artificial events produced by the blast. More than 80 % events were concentrated in daytime and many events were concentrated in the confirmed blast sites, Pyeongyang, Pocheon, Yeongjong-do, Donghae city, etc. Because these artificial events are a major potential cause of error when estimating the seismicity of a specific region, discrimination procedure has to be developed in the first place.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.35-38
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• 2008

This paper develops an aero engine LPV mathematical model to exactly describe aero engine dynamic process characteristics, eliminate the effect of modeling error. Design FDF with eigenstructure assignment. The simulation results of turbofan engine control system sensor fault show that this method has good performance in focusing discrimination in fault signal with modeling eror, enhancing the robustness to unknown input, detecting accuracy is high and satisfiying real-time requirement.