• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.3
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• pp.376-382
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• 2014

E-Actuator is an essential part of an eVGT, it receives the command from the main ECU and controls the vane. An e-Actuator failure can cause an abrupt change in engine output and it may induce an accident. Therefore, it is required to detect anomalies in the e-Actuator in real time to prevent accidents. In this paper, an e-Actuator fault detection method using on-line parameter identification is proposed. To implement on-line fault detection algorithm, many constraints are considered. The test input and sampling rate are selected considering the constraints. And new recursive system identification algorithm is proposed which reduces the memory and MCU power dramatically. The relationship between the identified parameters and real elements such as gears, spring and motor are derived. The fault detection method using the relationship is proposed. The experiments with the real broken gears show the effectiveness of the proposed algorithm. It is expected that the real time fault detection is possible and it can improve the safety of eVGT system.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.1-8
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• 2015

This paper presents a Electrocardiogram(ECG) identification method using adaptive weight based on Least Mean Square Error(LMSE) optimization. With a preprocessing for noise suppression, we extracts the average ECG signal and its standard deviation at every time instant. Then the extracted information is stored in database. ECG identification is achieved by matching an input ECG signal with the information in database. In computing the matching scores, the standard deviation is used. The scores are computed by applying adaptive weights to the values of the input signal over all time instants. The adaptive weight consists of two terms. The first term is the inverse of the standard deviation of an input signal. The second term is the proportional one to the standard deviation between user SAECGs stored in the DB. Experimental results show up to 100% recognition rate for 32 registered people.

• Speech Sciences
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• v.10 no.2
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• pp.249-258
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• 2003

This study attempted to examine a speaker identification method using difference sum and correlation coefficient determined from a pair of intensity level matrices of band-pass-filtered numeric sounds produced by ten female speakers of similar age and height. Subjects recorded three digit numbers at a quiet room at a sampling rate of 22 kHz on a personal computer. Collected data were band-pass-filtered at five different band ranges. Then, matrices of five intensity levels at 100 proportional time points were obtained. Pearson correlation coefficients and the sum of absolute intensity differences between a pair of given matrices were determined within and across the speakers. Results showed that very high correlation coefficient and small difference sum generally occurred within each speaker but some individual variation was also observed. Thus, the matrix pair with a higher coefficient and a smaller difference sum was averaged to form each individual's model. Comparison among the speakers yielded generally low coefficients and large differences, which suggests successful speaker identification, but among them there were a few cases with very high coefficients and small differences. Future studies will focus on finer band ranges and additional spectral parameters at some peak points of the intensity contour at a low frequency band.

• ETRI Journal
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• v.31 no.4
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• pp.376-386
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• 2009

An active radio frequency identification (RFID) system has the advantages of a long identification distance and a good identification rate, overcoming passive RFID drawbacks. Therefore, interest in the development of active RFID systems has been gradually increasing in areas of harbor logistics and national defense. However, some identification failures between active RFID systems developed under the same standards have been reported, presumably due to a lack of development of accurate evaluation methods and test equipment. We present a realization of the hardware and software of an emulator to evaluate the standard conformance of an active RFID system in a fully anechoic chamber. The performance levels of the designed emulator are analyzed using Matlab/Simulink simulations, and the applicability of the emulator is verified by evaluating the standard conformance of a real active RFID tag. Finally, we propose a new evaluation method by incorporating a self-running test mode environment into the RFID tags to reduce testing time and increase testing accuracy. The application of the suggested method to actual tags improves measurement uncertainty by 0.56 dB over that obtained using existing methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.9
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• pp.731-734
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• 2018

Many studies have been conducted on the accurate detection and identification of targets from ground clutter, in order to improve the accuracy rate of land guided weapons. Due to the variety and complicated characteristics of the ground clutter signal compared to the target, an active target identification technique is needed. In this paper, we propose a new algorithm to identify targets and divide them into different types by extracting the unique characteristics of the target through fractal dimension calculation with the characteristics of self-similarity. In the simulation using the algorithm, the probabilities of identifying the tank and truck were 100 % and 98.89 %, respectively, and the type of the target could be identified with a probability of 98 % or more.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.49 no.2
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• pp.214-223
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• 2016

Joint time-frequency images of the broadband acoustic echoes of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution (SPWVD). The acoustic features were extracted by changing the sliced window widths and dividing the time window by a 0.02-ms interval and the frequency window by a 20-kHz bandwidth. The 22 spectrum amplitudes obtained in the time and frequency domains of the SPWVD images were fed as input parameters into an artificial neural network (ANN) to verify the effectiveness for species-dependent features related to fish species identification. The results showed that the time-frequency approach improves the extraction of species-specific features for species identification from broadband echoes, compare with time-only or frequency-only features. The ANN classifier based on these acoustic feature components was correct in approximately 74.5% of the test cases. In the future, the identification rate will be improved using time-frequency images with reduced dimensions of the broadband acoustic echoes as input for the ANN classifier.

• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.331-350
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• 2017

Based on the alternative stabilization diagram by varying the time lag parameter in the stochastic subspace identification analysis, this study aims to investigate the measurements from several cases of civil structures for extending the applicability of a recently noticed criterion to ensure stable identification results. Such a criterion demands the time lag parameter to be no less than a critical threshold determined by the ratio of the sampling rate to the fundamental system frequency and is firstly validated for its applications with single measurements from stay cables, bridge decks, and buildings. As for multiple measurements, it is found that the predicted threshold works well for the cases of stay cables and buildings, but makes an evident overestimation for the case of bridge decks. This discrepancy is further explained by the fact that the deck vibrations are induced by multiple excitations independently coming from the passing traffic. The cable vibration signals covering the sensor locations close to both the deck and pylon ends of a cable-stayed bridge provide convincing evidences to testify this important discovery.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.3
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• pp.425-429
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• 2003

Staphylococcus aureus is a major pathogen for cattle, causing various forms of subclinical and clinical mastitis and could be a causative agent of food poisoning, it produces various superantigenic exotoxins which have a great public health significance. A total of 72 S. aureus clinical isolates from dairy farms located in Kyunggi Province Korea were examined for the species identification by biochemical method, and for the detection of $\beta$-lactamase, enterotoxin and other exotoxins genes by PCR. The results of species identification by biochemical method agreed with those of PCR done with species specific primer STA-AU. $\beta$-lactamase is an enzyme closely associated with the resistance to antibiotic penicillin, which is an important means of treatment of mastitis, all the isolates were positive for the presence of genes encoding $\beta$-lactamase, which were reproduced in penicillin susceptibility disc assay. Six types of toxin genes, Staphylococcal enterotoxin (SE)A, SEB, SEC, SEE, toxic shock syndrome toxin (TSST-1) and exfoliative toxin A (ET A) were detected in 72 isolates by PCR associated genotypic method in this study, none of the isolates carried the genes for enterotoxin D (SED) and exfoliative toxin B (ETB). The occurrence rate of exotoxin genes rated as 12.5%, and the precision of the PCR identification results has been confirmed using the reference strains.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.4
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• pp.163-168
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• 2005

In this paper, we propose a character-based summarization algorithm using speaker identification method from the dialog in video. First, we extract the dialog of shots containing characters' face and then, classify the scene according to actor/actress by performing speaker identification. The classifier is based on the GMM(Gaussian Mixture Model) using the 24 values of MFCC(Mel Frequency Cepstrum Coefficient). GMM is trained to recognize one actor/actress among four who are all trained by GMM. Our experiment result shows that GMM classifier obtains the error rate of 0.138 from our video data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.2
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• pp.69-75
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• 1985

The proposed seal identification procedure consists of the smoothing, rotation, thinning, and matching techniques. The seal images which are scanned by CCTV are thresholded into the binary prctures of $256{\times}256$ pixels through A/D converter and 6502 microcomputer. After the sample and target images are ratated into an identical orientation, a thinning process is used to extract the skeletons of the character strobes. The wighted map is constructed by distance weight from which the distance weighted correlation C is computed. The C is compared with the dicision constant C or C for the purpose of seal indentification. The identification rate is 95% and the total CPU time is less than 3 minutes for each identification in the experiment.