• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.477-480
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• 2005

In this paper, we propose a preprocess method to needs for Car License Plate Recognition on poor environment. This preprocess method use multi images to get low value to compare images value. Last method was Opening operation that Using Edge pixel to add and subtraction. The Result was removed White pixel and very mini feather. But This method needs many process times and License Plate Recognition is low quality problem. Another method is median filter and conversion. This paper key idea that rain & snow is high value. So This paper propose get low value to compare image value.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1338-1340
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• 1987

This paper describes the design of ECG data preprocess module for the ECG signals. This module process the data obtained from two channels. It is composed of the AID converter, QRS detector, one chip micro-computer and memory. This module performs the following functions;digital filtering, R wave detection and determination of reference point for the ST segment. The measured points are transfered to the next data module by the interrupt process. This preprocessor data module is available to the basis for the parallel data processing for the real time automatic diagnosis.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.5
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• pp.145-151
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• 1989

A new preprocess technique is presented which can improve the routing efficiency in the gate array layout designs. In order to resolve the cycle problem in the detailed routing, we exchange the logically equivalent pins in each channel. The signal nets are divided, and doubly connected signal net components are removed, so that the increase in the number of tracks can be controlled.

• Korea Journal of Hospital Management
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• v.12 no.2
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• pp.69-92
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• 2007

This research has classified waiting times into the three different ones according to service offering process and investigated the antecedents and consequences of types of waiting times. A service provider's concern and customer involvement were modeled as antecedent variables and negative emotion and service value as dependent variables. The empirical results of the study are as follows. A service provider's concern had significant influences on all the three types of waiting times whereas customer involvement was found to affect preprocess-waiting and postprocess-waiting times. Preprocess-waiting time had a significant impact on both negative emotion and service value and inprocess-waiting time only affects negative emotion. However, postprocess-waiting time had influenced none of the variables. The findings illustrate an important role of concern and involvement regarding to a customer's perceived waiting time and relative importance of waiting types on negative emotion and service value. A summary of the results are reported and managerial implications are discussed.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.11-18
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• 2004

In this paper, the classification of artificial defects in semiconductor packages is studied by using pattern recognition technology. For this purpose, the pattern recognition algorithm includes the user made MATLAB code. And preprocess is made of the image process and self-organizing map, which is the input of the back-propagation neural network and the dimensionality reduction method, The image process steps are data acquisition, equalization, binary and edge detection. Image process and self-organizing map are compared to the preprocess method. Also the pattern recognition technology is applied to classify two kinds of defects in semiconductor packages: cracks and delaminations.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.105-107
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• 2004

In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on size, angle, and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value(255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking parameters.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.617-622
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• 2004

In this work, we suggested the method which improves the efficiency of the face detection algorithm using Pulse-Coupled Neural Network. Face detection algorithm which uses the color information is independent on pose, size and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise, and so on. Depending on these conditions, we obtained the mean and variance of the skin-tone colors by experiments. Then we introduce a preprocess that the pixel with a mean value of skin-tone colors has highest level value (255) and the other pixels in the skin-tone region have values between 0 and 255 according to a normal distribution with a variance. This preprocess leads to an easy decision of the linking coefficient of Pulse-Coupled Neural Network.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.560-568
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• 2000

The aims of this research were to investigate the preprocessing effect of spectrum data on prediction performance and to develop a robust model to predict SSC in intact apple. Spectrum data of 320 Fuji apples were measured with the on-line transmittance measurement system at the wavelength range of 550∼1100nm. Preprocess methods adopted for the tests were Savitzky Golay, MSC, SNV, first derivative and OSC. Several combinations of those methods were applied to the raw spectrum data set to investigate the relative effect of each method on the performance of the calibration model. PLS method was used to regress the preprocessed data set and the SSCs of samples, and the cross-validation was to select the optimal number of PLS factors. Smoothing and scattering corection were essential in increasing the prediction performance of PLS regression model and the OSC contributed to reduction of the number of PLS factors. The first derivative resulted in unfavorable effect on the prediction performance. MSC and SNV showed similar effect. A robust calibration model could be developed by the preprocessing combination of Savitzky Golay smoothing, MSC and OSC, which resulted in SEP= 0.507, bias=0.032 and R$^2$=0.8823.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.9_10
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• pp.1015-1025
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• 2003

This paper proposes a method for constructing the virtual characters adopting the personal body types for the clothing coordination. At first, the method produces the 38 kinds of the Korean 3D body models considering sex, ages and body types, and constructs model DB. We select a model similar to the personal body size from DB and deform the selected model according to body size. The method deforms the model linearly for height 12 items, width 6 items, depth 5 items and round 13 items, and constructs the personal character fitted to the personal body size. The preprocess for model deformation consists of grouping for body part and establishing the feature points. Linear deformation for each group leads us to easy construction of the virtual personal characters. This method has two advantages as follows: 1. Large reduction of man power, cost and time for DB construction of the body 3D models, since the preprocess permits us to effectively use the various body models whose geometrical structures are different, 2 Suitability to Web-based clothing coordination, since the body deformation method is simple and its speed is very high.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.149-156
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• 2015

In this paper, we propose a Korean sentence symbol preprocessor for a SSML (speech synthesis markup language) supported speech synthesis system in order to improve the quality of the synthesized result. After the analysis of Korean Wikipedia documents, we propose 8 categories for the meaning of sentence symbols and 11 regular expression for the classification of each category. After the development of a Korean sentence symbol preprocess system we archived 56% of precision and 71.45% of recall ratio for 63,000 sentences.