• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.538-540
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• 2001

최근 전세계적으로 치열한 시장 경쟁이 벌어지고 있는 세계화 시대에서 특히, 제조 업종에 종사하는 업체들이 살아남기 위해서는 새로운 제품들을 최적시에 시장에 출하하는 것이 최대 관건으로 등장하고 있다. 이를 극복하기 위해서는 생산성 향상에 의한 납기 단축 도모는 물론, 제품 설계에 소요되는 시간과 설계의 시행착오에 의한 납기 지연을 줄이는 것이 필수적인 과제이다. 이러한 배경으로 설계에 있어 컴퓨터를 이용하여 합리적인 설계를 이루고자 노력이 이루어지고 있다. 보통 설계하기 위해서 AutoCAD를 이용하고 있으나, 실제로 AutoCAD 환경에서 심도 있는 설계를 위해서는 개별적인 제품 하나 하나에 대한 설계를 해야한다는 제약과, 통계적인 수치값을 얻지 못한다는 한계점을 갖고 있다. 본 논문에서는 AutoCAD에서의 설계 제약을 극복하기 위해, 한 제조 회사의 설계 자동화 시스템(GDS: Gloating automatic drawing system)에서 도면에 대한 정보를 자동 생성하기 위한 응용 시스템 설계 및 구현한 사례를 보이고자 한다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.1
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• pp.91-99
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• 2009

In this paper, a standard field generation method using a micro-TEM ceil is described and its measurement uncertainty is evaluated. The standard field generation system consists of an auto-leveling signal source, a micro-TEM cell operating up to 1.2 GHz, and a power measuring Instrument using a thermistor mount. Measurement results of a field strength key comparison (CCEM.RF-K20) for the field strength of 20 V/m at frequencies between 10 MHz and 1 GHz are presented for validating the standard field generation method.

• Laser Solutions
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• v.15 no.1
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• pp.6-9
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• 2012

In TFT-LCD manufacturing process, various defects are generated by manufacturing machine trouble or particle. These defects can be repaired through the TFT-Laser repair process that only can't be automated in TFT-LCD manufacturing Process. In this Paper, we propose auto defect algorithm for TFT-LCD laser repair machine using image processing algorithm in order to automate process. Proposed algorithm can detect very small defects (< 2um) in 98% success ratio, and generated laser repair path guarantee highly precise position accuracy. Through proposed system, much of the work still done the old-fashioned way, by hand, can be automated and manufacturing company can be strengthed the competitiveness of cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.366-385
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• 2013

In this paper, we propose a compressed sensing (CS) based Wyner-Ziv (WZ) codec using motion-aligned auto regressive model (MAAR) based side information (SI) extrapolation to improve the compression performance of low-delay distributed video coding (DVC). In the CS based WZ codec, the WZ frame is divided into small blocks and CS measurements of each block are acquired at the encoder, and a specific CS reconstruction algorithm is proposed to correct errors in the SI using CS measurements at the decoder. In order to generate high quality SI, a MAAR model is introduced to improve the inaccurate motion field in auto regressive (AR) model, and the Tikhonov regularization on MAAR coefficients and overlapped block based interpolation are performed to reduce block effects and errors from over-fitting. Simulation experiments show that our proposed CS based WZ codec associated with MAAR based SI generation achieves better results compared to other SI extrapolation methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1229-1234
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• 2010

High quality and high speed multimedia services will be required in the next generation mobile communications. To satisfy these services, powerful error correction techniques are used. ARQ(Auto Repeat Request) techniques, aspects of the throughput, and FEC(Forward Error Correct) techniques have disadvantages in terms of reliability. H-ARQ(Hybrid Auto Repeat Request) systems have been studied extensively as a solution of these disadvantages. In this paper introduce double layer coding and H-ARQ type, proposed H-ARQ system using double layer coding methods. Simulate BER performance and throughput. And we suggest that according to channel condition suitable H-ARQ type.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.73-76
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• 2007

Photodynamic diagnosis(PDD) is a method to diagnose the possibility of cancer, both by the principle that if a photosensitizer is injected into an organic tissue, it is accumulated in the tissue of a malignant tumor selectively after a specific period, and by a comparison of the intensity of the fluorescence of normal tissue with abnormal tissue after investigating the excitation light of a tissue with accumulated photosensitizer. Since the selection of the wavelength band of excitation light has an interrelation with fluorescence generation according to the selection of a photosencitizer, it plays an important role in POD. This study aims at designing and evaluating light source devices that can stably generate light with various kinds of wavelengths In order to make possible PDD using a photosensitizer and diagnosis using auto-fluorescence. The light source device was a Xenon lamp and filter wheel, composed of an optical output control through Iris and filters with several wavelength bands It also makes the inducement of auto-fluorescence possible because it is designed to generate a wavelength band of 380-400. The transmission part of the light source was, developed to enhance the efficiency of light transmission. To evaluate this light source device, the characteristics of the light output and wavelength band were verified. To validate the capability of this device as PDD the detection of auto-fluorescence using mouse was performed.

• Journal of Digital Convergence
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• v.8 no.4
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• pp.73-82
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• 2010

Auto-industry is very difficult to standardize item code generation rule, because it has more than 20,000 parts in this industry. As finished good companies have already used the ERP system such as SAP, they have a good Master Data Management(MDM) system. However, since many supplier companies have poor MDM system, they have a lot of barriers on system implementation like ERP, MES. PDM systems. This study surveys various benchmarking sites and investigates the standardization of item code of the auto-parts manufacturing companies. Finally, this study proposes the implementation guide (IMG) of auto-industry MDM standardization.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.219-230
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• 2010

In nuclear power plants (NPPs), periodic sensor calibrations are required to assure that sensors are operating correctly. By checking the sensor's operating status at every fuel outage, faulty sensors may remain undetected for periods of up to 24 months. Moreover, typically, only a few faulty sensors are found to be calibrated. For the safe operation of NPP and the reduction of unnecessary calibration, on-line instrument calibration monitoring is needed. In this study, principal component-based auto-associative support vector regression (PCSVR) using response surface methodology (RSM) is proposed for the sensor signal validation of NPPs. This paper describes the design of a PCSVR-based sensor validation system for a power generation system. RSM is employed to determine the optimal values of SVR hyperparameters and is compared to the genetic algorithm (GA). The proposed PCSVR model is confirmed with the actual plant data of Kori Nuclear Power Plant Unit 3 and is compared with the Auto-Associative support vector regression (AASVR) and the auto-associative neural network (AANN) model. The auto-sensitivity of AASVR is improved by around six times by using a PCA, resulting in good detection of sensor drift. Compared to AANN, accuracy and cross-sensitivity are better while the auto-sensitivity is almost the same. Meanwhile, the proposed RSM for the optimization of the PCSVR algorithm performs even better in terms of accuracy, auto-sensitivity, and averaged maximum error, except in averaged RMS error, and this method is much more time efficient compared to the conventional GA method.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.651-652
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• 2004

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.734-734
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• 2006