• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.167-174
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• 1998

The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

• Journal of Microbiology and Biotechnology
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• v.26 no.12
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• pp.2199-2205
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• 2016

Vibrio cholerae O1 serogroup Wave 3 El Tor strains are presently prevalent worldwide. The Wave 3 El Tor strains contain a TLC:RS1:CTX array on chromosome 1, and no element is integrated on chromosome 2. A multiplex PCR optimized to identify the TLC:RS1:CTX array of Wave 3 strains has been developed in this study. By using eight primers, the multiplex PCR can identify the characteristic CTX and RS1 array of Wave 3 strains from various arrays of strains belonging to other Waves. The four amplified DNA fragments of Wave 3 strains have been cloned in a vector, which could be used as a positive control for the multiplex PCR. This multiplex PCR and the positive control set could be useful tools for rapid recognition of Wave 3 El Tor strains.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.157-165
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• 2013

The mid-20th century witnessed a wide spread of Korean culture in Japan, China and Southeast Asia and China now has become the biggest trade partner and export market, as well as the No. 1 source of import and the biggest investment country of Korea. With the spreading of the Korean popular culture in China, brand loyalty to Korean products is improved. Taking the Chinese market as the basis, this research aims to make an analysis of the implications of 'Korean Wave', Korean advertisements and the image of Korea on brand loyalty to cosmetics made in Korea. To achieve the research aim, questionnaires were used in conducting the survey, mainly in Beijing. Excluding the invalid ones, altogether 180 questionnaires were collected, based on which an empirical analysis was carried out on the correlation between 'Korean Wave', effects of Korean advertisements, image of Korea, brand recognition, and brand loyalty to products made in Korea. The major analyzing tools are SPSS 20.0 and AMOS 20.0. The findings are as follows: 1. Korean films, dramas, and attachment for Korean movie stars (representative of 'Korean Wave') all have a positive influence on brand loyalty. Recognition of the country image of Korea, to some extent, also has positive implications on brand recognition. 2. Empirical analysis assists in the testing of the degree of recognition and attachment of cosmetics made in Korea, as well as brand loyalty to them.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.4
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• pp.371-382
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• 2001

The recognition of such natural wave guides as plates, rods, hollow cylinders, multi-layer structures or simply an interface between two materials combined with an increased understanding of the physics and wave mechanics of guided wave propagation has led to a significant increase in the number of guided wave inspection applications being developed each year. Of primary attention Is the ability to inspect partially hidden structures, hard to access areas, and teated or insulated structures. An introduction to some physical consideration of guided waves followed by some sample problem descriptions in pipe, ice detection, fouling detection in the foods industry, aircraft, tar coated structures and acoustic microscopy is presented in this paper. A sample problem in Boundary Element Modeling is also presented to illustrate the move in guided wave analysis beyond detection and location analysis to quantification.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.290-291
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• 2008

The most popular speech feature used in speech recognition today is the Mel-Frequency Cepstral Coefficients (MFCC) algorithm, which could reflect the perception characteristics of the human ear more accurately than other parameters. This paper adopts MFCC and its first order difference, which could reflect the dynamic character of speech signal, as synthetical parametric representation. Furthermore, we quote Dynamic Time Warping (DTW) algorithm to search match paths in the pattern recognition process. We use the software "GoldWave" to record English digitals in the lab environments and the simulation results indicate the algorithm has higher recognition accuracy than others using LPCC, etc. as character parameters in the experiment for Digital Isolated Word Recognition (DIWR) system.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.263-264
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• 1998

In this paper, we present the result of feature points recognition and classification of radial pulse by the shape of pulse wave. And we analyze radial pulse in frequency domain. The recognition algorithm use the method which runs in parallel with both the data of ECG and differential pulse simultaneously to recognize the feature points. Also fie specified 3-time elements of pulse wave as main parameters for diagnosis and measured them by execution of algorithm, then we classify the shape of radial pulse by existence and position of feature points. lastly we execute frequency analysis on the feature points and get the power spectrum of radial pulse.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.9-14
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• 1998

The speech recognition on long vowels are carried out by electric circuits. A level compressor is able to transform the wave of voice to serial pulses. The obtained pulses have informations to distinguish the vowels. The sampling of the pulses is carried out by the register which picks up a series of serial signals in a pitch of a vowel as an unit. The timing control pulses such as sampling pulses are generated by using peak pulses in the speech wave. The parallel data in the register assign the phonetic symbol by means of the decision making circuit which carries out the IF-THEN rule.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.131-140
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• 1996

In this paper, we propose the method that extracts the speech feature using the hearing model through signal precessing techniques. The proposed method includes following procedure ; normalization of the short-time speech block by its maximum value, multi-resolution analysis using the discrete wavelet transformation and re-synthesize using thediscrete inverse wavelet transformation, differentiation after analysis and synthesis, full wave rectification and integration. In order to verify the performance of the proposed speech feature in the speech recognition task, korean digita recognition experiments were carried out using both the dTW and the VQ-HMM. The results showed that, in case of using dTW, the recognition rates were 99.79% and 90.33% for speaker-dependent and speaker-independent task respectively and, in case of using VQ-HMM, the rate were 96.5% and 81.5% respectively. And it indicates that the proposed speech feature has the potentials to use as a simple and efficient feature for recognition task.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.435-447
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• 1996

In this paper, we propose the method that extracts the speech feature using the hearing model through signal processing techniques. The proposed method includes the following procedure ; normalization of the short-time speech block by its maximum value, multi-resolution analysis using the discrete wavelet transformation and re-synthesize using the discrete inverse wavelet transformation, differentiation after analysis and synthesis, full wave rectification and integration. In order to verify the performance of the proposed speech feature in the speech recognition task, korean digit recognition experiments were carried out using both the DTW and the VQ-HMM. The results showed that, in the case of using DTW, the recognition rates were 99.79% and 90.33% for speaker-dependent and speaker-independent task respectively and, in the case of using VQ-HMM, the rate were 96.5% and 81.5% respectively. And it indicates that the proposed speech feature has the potential for use as a simple and efficient feature for recognition task

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.2
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• pp.63-66
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• 2005

This paper describes analysis and pattern recognition techniques for Partial Discharge(PD) signals in Gas Insulated Switchgears (GIS). Detection of PD signals is one of the most important factors in the predictive maintenance of GIS. One of the methods of detection is electro magnetic wave detection within the Ultra High Frequency (UHF) band (300MHz $\~$ 3GHz). In this paper, PD activity simulation is generated using three types of artificial defects, which were detected by a UHF PD sensor installed in the GIS. The detected PD signals were performed on three-dimensional phi-q-n analysis. Finally, parameters were calculated and an Artificial Neural Network (ANN) was applied for PD pattern recognition. As a result, it was possible to discriminate and classify the defects.