• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2525-2527
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• 2004

This paper classify using Adaptive Resonance Theory 1(ART1) as a vigilance parameter of pattern clustering algorithm. Inherent characteristics of the model are analyzed. In particular the vigilance parameter $\rho$ and its role in classification of patterns is examined. Our estimates show that the vigilance parameter as designed originally does not necessarily increase the number of categories with its value but can decrease also. This is against the claim of solving the stability-plasticity dilemma. However, we have proposed a modified vigilance parameter setting criterion which takes into account the problem of subset and superset patterns and stably categorizes arbitrarily many input patterns in one list presentation when the vigilance parameter is closer to one. And this paper goal is the input pattern cognition and classification using neural network.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.447-452
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• 2000

The grinding plays a key role which decide the quality of a product finally. But the grinding process is very irregular, so it is very difficult to analyse the process accurately. Therefore it is very important in the aspect of precision and automation to reduce the idle time and to decide the proper dressing time by visualizing. In this study, we choose the direct method of observation by making use of computer vision, and apply pattern classification technique to the method of measuring the wheel surface. Pattern classification technique is proper to analyse complex surface image. We observe the change of the wheel surface by making use of the gray level run lengths which are representative prince in this technique.

• International Journal of CAD/CAM
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• v.8 no.1
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• pp.69-72
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• 2009

In this paper, we present a new shape descriptor, which is named Poisson equation-Fourier-Mellin moment Descriptor. We solve the Poisson equation in the shape area, and use the solution to get feature function, which are then integrated using Fourier-Mellin moment to represent the shape. This method develops the Poisson equation-geometric moment Descriptor proposed by Lena Gorelick, and keeps both advantages of Poisson equation-geometric moment and Fourier-Mellin moment. It is proved better than Poisson equation-geometric moment Descriptor in shape recognition and classification experiments.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.3
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• pp.391-406
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• 1993

The purpose of this study was to utilize of apparel CAD System by the classification of the basic pattern block in pattern making process. Gerber AM-300 CAD System was used for this study. The results form this study were as follows; 1. New shirts block were developed. 2. The sensory test was applied to evaluate the new shirts block for women by comparing it with Japanese Bunka shirts blouse pattern making method. According to a statistical analysis of the result of the 20 items on the questionnaire, the 19 items showed significant difference(${\alpha}{\leq}0.01$)between the two, with the new shirts block having higher scores. 3. A basic pattern block was selected by the design sketch. 4. P/D/S were enabled to be constructed directly from a block pattern. The drawing, deletion. duplication, and movement of all points and lines in the pattern might be made freely, and the split, pivot, and movement of the pattern, and the attachment of two patterns were possible. 5. Automatic grading of finished pattern have been developed by creation and modification of grading rules of block pattern.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.9
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• pp.513-520
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• 2004

In the paper, we summarize the result of the experimental research for the overload criteria of domestic distribution transformers considering the electric consumption patterns of customers. For the basic characteristic data of distribution transformer overload, the actual experiments are accomplished. The field data of loads are surveyed from sample transformers for analyzing the consumption pattern of customer load. The load data acquisition devices are equipped, and the algorithm of load pattern classification is applied. In addition to this efforts, various load pattern data. in past are gathered. Then the representative load pattern of each customer type in domestic is extracted. The final results of overload criterions are presented as tabular form through the results of experiments and survey are combined. The field test of the experiment results is peformed using the special manufactured transformers, which can measure both the load and top-oil temperature of transformer. Through this, we verify that the results of field test are similar to the laboratory one and the Proposed overload criteria can be effectively applied to the real system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.119-127
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• 2000

In this study the classified researches the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing feature extraction feature selection and classifi-er selection is teated by bulk,. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function the empirical Bayesian classifier. Also the pattern recognition technology is applied to classifica-tion problem of natural flaw(i.e multiple classification problem-crack lack of penetration lack of fusion porosity and slag inclusion the planar and volumetric flaw classification problem), According to this result it is possible to acquire the recognition rate of 83% above even through it is different a little according to domain extracting the feature and the classifier.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1554-1560
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• 1989

This paper suggests the algorihtm which extracts the classification parameter relative to the only feature of document patterns even though they are rotated or scaled, and also classifies them. With the complex logarithmic conformal mapping, the sample of the document pattern image makes the pattern image of the complex logarithmic plane. Because the power spectrum of this plane is invariant to the rotation, and scale of the pattern image, it is used as the characteristics parameter of the patten image. By using the coherence function, this method analyzes the standard and input power spectrum. additionally, it classifies the input pattern image. Even though input image is rotated, our algorithm can classify it without reference to the rotation, and this is possible when the scale is in the range of 0.5-1.5.

• Journal of the Korea Fashion and Costume Design Association
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• v.5 no.3
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• pp.89-97
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• 2003

This study is to review the development of calico printing pattern design for fabric through historical perspective. Calico is a cotton cloth named from Calicut, a city of India. It was first brought to England by the East India company in 1621. Although the name is generally given and plain white cotton cloth, and in America it is applied to small-scale printed cottons, today it applies to indian cotton cloth, coarse or fine, woven with colored geometrical large-scale and small-scale patterns, painted or printed. Therefore this paper proposes the classification and feature extraction of calico printing pattern from the early of 16th century to 21th century. The results of this study can be effectively applied to develop competitive calico pattern design in domestic cotton textile industry.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.320-326
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• 2008

In this paper, we propose a new algorithm emulating the DNA characteristics for noise-tolerant pattern matching problem on digital system. The digital pattern matching becomes core technology in various fields, such as, robot vision, remote sensing, character recognition, and medical diagnosis in particular. As the properties of natural DNA strands allow hybridization with a certain portion of incompatible base pairs, DNA-inspired data structure and computation technique can be adopted to bio-signal pattern classification problems which often contain imprecise data patterns. The key feature of noise-tolerance of DNA computing comes from control of reaction temperature. Our hardware system mimics such property to diagnose cardiovascular disease and results superior classification performance over existing supervised learning pattern matching algorithms. The hardware design employing parallel architecture is also very efficient in time and area.

• Journal of Oriental Neuropsychiatry
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• v.26 no.4
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• pp.407-416
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• 2015

Objectives: This study was performed to evaluate the reliability and validity of the instrument on pattern identifications for depression. Methods: Two assessors carried out an evaluation about the instrument on pattern identifications for depression, targeting 201 participants, who after taking the HAM-D score over 12 or under 7 twice. Results: Inter-assessor reliability was higher than intra-assessor reliability in a reliability analysis about classification of pattern identification evaluated by the instrument on pattern identifications for depression. Reliability of intra-assessor and inter-assessor showed a moderate to strong agreement when reliability analysis about classification score of the pattern identification had been performed. Reliability analysis to evaluate the validity of the instrument on pattern identifications for depression showed moderate agreement. Conclusions: The results reveal that reliability analysis of the instrument on pattern identifications for depression showed an over moderate agreement and validity analysis represented a positive correlation.