• Korean Journal of Optics and Photonics
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• v.13 no.6
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• pp.486-492
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• 2002

In this paper. we presented 1 & 2 dimensional minimum mean-squared-error (MMSE) equalization scheme in a digital holographic data storage system to improve bit-error-rate (BER) and to mitigate inter-symbol interference (ISI) which were generated during the data storage and retrieval processes. We showed experimentally for ten data pages retrieved from the holographic storage system that BER and signal-to-noise ratio (SNR) were improved by adopting MMSE equalization.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.97-102
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• 2011

Lots of 2D vision algorithms have been applied for inspection. However, these 2D vision algorithms have limitation in inspection applications which require 3D information data such as the height of semiconductor chips. Stereo vision is a well known method to measure the distance from the camera to the object to be measured. But it is difficult to apply for inspection directly because of its measurement error. In this paper, we propose two adjustment methods to reduce the error of the measured height data for stereo vision. The weight value based model is used to minimize the mean squared error. The average value based model is used with simple concept to reduce the measured error. The effect of these algorithms has been proved through the experiments which measure the height of semiconductor chips.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.223-224
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• 2021

Recently, the demand for high fluidity concrete has been increased due to skyscrapers. However, it has its own limits. First of all, high fluidity concrete has large variation and through trial & error it costs lots of money and time. Neural network model has repetitive learning process which can solve the problem while training the data. Therefore, the purpose of this study is to predict optimum mix design of 40MPa, 60MPa high fluidity concrete by using neural network model and verifying compressive strength by applying real data. As a result, comparing collective data and predicted compressive strength data using MATLAB, 40MPa mix design error rate was 1.2%~1.6% and 60MPa mix design error rate was 2%~3%. Overall 40MPa mix design error rate was less than 60MPa mix design error rate.

• Atmosphere
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• v.22 no.3
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• pp.309-319
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• 2012

It is important to characterize and quantify the inherent error in the radar rainfall to make full use of the radar rainfall. This study verified the error structure of the reflectivity and corrected the range dependent error in the CAPPI using a VPR (vertical profile of reflectivity) model. The error of the CAPPI to display the reflectivity data becomes bigger for the range longer than 100 km. This range dependent error, however, is significantly improved by corrected the CAPPI data using the VPR model.

• Journal of Sasang Constitutional Medicine
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• v.19 no.2
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• pp.30-39
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• 2007

1. Objectives The Face is an important standard for the classification of Sasang Constitution. We are developing 3D Automatic Face Recognition Apparatus(3D-AFRA) to analyse the facial characteristics. This apparatus show us 3D image and data of man's face and measure facial figure data. So we should examine the figure restoration error of 3D Automatic Fare Recognition Apparatus(3D-AFRA) in hardware Error Analysis. 2. Methods We scanned Face status by using 3D Automatic Face Recognition Apparatus(3D-AFRA). And also we scanned Face status by using laser scanner(vivid 9i). We compared facial shape data be restored by 3D Automatic Face Recognition Apparatus(3D-AFRA) with facial shape data that be restorated by 3D laser scanner. And we analysed the average error and the maximum error of two data. 3. Results and Conclusions In frontal face, the average error was 0.48mm. and the maximum error was 4.60mm. In whole face, the average error of was 0.99mm. And the maximum error was 6.64mm. In conclusion, We assessed that accuracy of 3D Automatic Face Recognition Apparatus(3D-AFRA) is considerably good.

• Journal of the Optical Society of Korea
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• v.10 no.3
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• pp.118-123
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• 2006

We present an optical security method for binary data information by using 4-step phase-shifting digital holography and we analyze tolerance error for the decrypted data. 4-step phase-shifting digital holograms are acquired by moving the PZT mirror with equidistant phase steps of ${\pi}/2$ in the Mach-Zender type interferometer. The digital hologram in this method is a Fourier transform hologram and is quantized with 256 gray level. The decryption performance of the binary data information is analyzed. One of the most important errors is the quantization error in detecting the hologram intensity on CCD. The greater the number of quantization error pixels and the variation of gray level increase, the more the number of error bits increases for decryption. Computer experiments show the results for encryption and decryption with the proposed method and show the graph to analyze the tolerance of the quantization error in the system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.1
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• pp.126-134
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• 1999

In this paper, a new error compensating technique for form-error compensation of rough-surface profile obtained by contact stylus profilometer is proposed. By the method, the real contact points of rough-surface and diamond stylus can be estimated and the measured profile data corrected. To verify the compensation effect, the properties(Ra, RMS, Kurtosis, Skewness) of measured profile data and compensated data were compared. And, the cumulative RMS slope was proposed to assess the compensated effect of upper area of profile. The results show that the measuring error could be compensated very well in amplitude parameters and in proposed cumulative RMS slope by the developed form-error compensating technique.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.371-381
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• 2017

The performance of the statistical context-sensitive spelling error correction depends on the quality and quantity of the data for statistical language model. In general, the size and quality of data in a statistical language model are proportional. However, as the amount of data increases, the processing speed becomes slower and storage space also takes up a lot. We suggest the improved statistical language model to solve this problem. And we propose an effective spelling error candidate generation method based on a new statistical language model. The proposed statistical model and the correction method based on it improve the performance of the spelling error correction and processing speed.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.13-23
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• 2011

In this study, Mike11 will be used as the numerical model where a data assimilation method will be applied to it. This paper aims to gain an insight and understanding of data assimilation in flood forecasting models. It will start with a general discussion of data assimilation, followed by a description of the methodology and discussion of the statistical error forecast model used, which in this case is the linear regression. This error forecast model is applied to the water level forecast simulated by MIKE11 to produced improved forecast and validated against real measurements. It is found that there exists a phase error in the improved forecasts. Hence, 2 general formula are used to account for this phase error and they have shown improvement to the accuracy of the forecasts, where one improved the immediate forecast of up to 5 hours while the other improved the estimation of the peak discharge.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.53-61
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• 1999

STL has several errors such as orientation error, hole error, and acute triangle error on being translated from CAD software. These errors should be corrected before using in Rapid Prototyping. So the software is necessary to correct errors. In this study, STL Editor which is a system for STL error correction and shape modification is developed and contains following characteristics. 1.Apply the triangle based data st겨cture. 2.Use the graphic user interface for easy work. 3.Use the Diet method to reduce data size. 4.Use the Delaunay triangulation method to enhance the quality of STL. 5.Modify the STL errors manually.