• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.11
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• pp.655-660
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• 2003

This paper describes a transformer protective relaying algorithm based on the ratio of increments of flux linkages (RIFL) of the primary and secondary windings. The algorithm uses integration approximation. The RIFL is equal to the turns ratio for all operating conditions except for an internal fault. For a single-phase transformer and a Y-Y transformer, the increments of flux linkages (IFL) are calculated. For a Y-$\Delta$ transformer, the difference of IFL are calculated to use the line currents rather than the delta winding currents, which are unavailable. Their ratios are compared with the turns ratio. The comparative study between the proposed and conventional differentiation approximation methods was conducted. The test results show that the algorithm reduces the approximation errors of the conventional methods.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1667-1676
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• 2010

In this paper, we propose a packet scheduling algorithm that assigns different number of HS-PDSCH(High Speed Primary Downlink Shared Channel) to the service user according to the received signal to interference ratio of CPICH(Common Pilot Channel) and to the traffic characteristics. Assigned channel number is determined by the signal to interference ratio level from CPICH. The highest signal to interference ratio user gets the number of channels based on the signal to interference ratio table and the remained channels are assigned to the other level users. Therefore the proposed scheme can provide the similar maximum service throughput and higher fairness than existing scheduling algorithm. Simulation results show that our algorithm can provide the similar maximum service throughput and higher fairness than MAX C/I algorithm and can also support the higher service throughput than proportional fairness scheme.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.65-73
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• 1989

In this paper, we propose a text-independent speaker identification algorithm based on VQ(vector quantization) and vowel classification, and its performance is studied and compared with that of a conventional speaker identification algorithm using VQ. The proposed speaker identification algorithm is composed of three processes: vowel segmentation, vowel recognition and average distortion calculation. The vowel segmentation is performed automatlcally using RMS energy, BTR(Back-to-Total cavity volume Ratio)and SFBR(Signed Front-to-Back maximum area Ratio) extracted from input speech signal. If the Input speech signal Is noisy, particularity when the SNR is around 20dB, the proposed speaker identification algorithm performs better than the reference speaker identification algorithm when the correct vowel segmentation is done. The same result is obtained when we use the noisy telephone speech signal as an input, too.

• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.280-289
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• 2022

In this paper, we present a QRS-complex detection algorithm to calculate an accurate heartbeat and clearly recognize irregular rhythm from ECG signals. The conventional Pan-Tompkins algorithm brings false QRS detection in the derivative when QRS and noise signals have similar instant variation. The proposed algorithm uses amplitude differences in 7 adjacent samples to detect QRS-complex which has the highest amplitude variation. The calculated amplitude is cubed to dominate QRS-complex and the moving average method is applied to diminish the noise signal's amplitude. Finally, a decision rule with a threshold value is applied to detect accurate QRS-complex. The calculated signals with Pan-Tompkins and proposed algorithms were compared by signal-to-noise ratio to evaluate the noise reduction degree. QRS-complex detection performance was confirmed by sensitivity and the positive predictive value(PPV). Normal ECG, muscle noise ECG, PVC, and atrial fibrillation signals were achieved which were measured from an ECG simulator. The signal-to-noise ratio difference between Pan-Tompkins and the proposed algorithm were 8.1, 8.5, 9.6, and 4.7, respectively. All ratio of the proposed algorithm is higher than the Pan-Tompkins values. It indicates that the proposed algorithm is more robust to noise than the Pan-Tompkins algorithm. The Pan-Tompkins algorithm and the proposed algorithm showed similar sensitivity and PPV at most waveforms. However, with a noisy atrial fibrillation signal, the PPV for QRS-complex has different values, 42% for the Pan-Tompkins algorithm and 100% for the proposed algorithm. It means that the proposed algorithm has superiority for QRS-complex detection in a noisy environment.

• Journal of Korean Society of Steel Construction
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• v.21 no.4
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• pp.361-373
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• 2009

Using the genetic algorithm, the optimal-design technique of the Nielsen arch bridge was proposed in this paper. The design parameters were the arch-rise ratio and the steel weight ratio of the Nielsen arch bridge, and optimal-design techniques were utilized to analyze the behavior of the bridge. The optimal parameter values were determined for the estimated optimal level. The parameter determination requires the standardization of the safety, utility, and economic concepts as the critical factors of a structure. For this, a genetic algorithm was used, whose global-optimal-solution search ability is superior to the optimization technique, and whose object function in the optimal design is the total weight of the structure. The constraints for the optimization were displacement, internal stress, and time and space. The structural analysis was a combination of the small displacement theory and the genetic algorithm, and the runtime was reduced for parallel processing. The optimal-design technique that was developed in this study was employed and deduced using the optimal arch-rise ratio, steel weight ratio, and optimal-design domain. The optimal-design technique was presented so it could be applied in the industry.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1064-1069
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• 2014

In this paper, we propose a novel approach to improve the performance of a voice activity detection(VAD) which is based on the adaptive band-partitioning with the likelihood ratio(LR). The previous method based on the adaptive band-partitioning use the weights that are derived from the variance of the spectral. In our VAD algorithm, the weights are derived from LR, and then the weights are incorporated with the entropy. The proposed algorithm discriminates the voice activity by comparing the weighted entropy with the adaptive threshold. Experimental results show that the proposed algorithm yields better results compared to the conventional VAD algorithms. Especially, the proposed algorithm shows superior improvement in non-stationary noise environments.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1737-1744
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• 2004

In the compression methods widely used today, the image compression by VQ is the most popular and shows a good data compression ratio. Almost all the methods by VQ use the LBG algorithm that reads the entire image several times and moves code vectors into optimal position in each step. This complexity of algorithm requires considerable amount of time to execute. To overcome this time consuming constraint, we propose an enhanced self-organizing neural network for color images. VQ is an image coding technique that shows high data compression ratio. In this study, we improved the competitive learning method by employing three methods for the generation of codebook. The results demonstrated that compression ratio by the proposed method was improved to a greater degree compared to the SOM in neural networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• Journal of Distribution Science
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• v.12 no.3
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• pp.33-41
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• 2014

Purpose - The purpose of this study was to predict the selection of independent auditors in the companies listed on the Tehran Stock Exchange (TSE) using a combination of PSO algorithm and CART. This study involves applied research. Design, approach and methodology - The population consisted of all the companies listed on TSE during the period 2005-2010, and the sample included 576 data specimens from 95 companies during six consecutive years. The independent variables in the study were the financial ratios of the sample companies, which were analyzed using two data mining techniques, namely, PSO algorithm and CART. Results - The results of this study showed that among the analyzed variables, total assets, current assets, audit fee, working capital, current ratio, debt ratio, solvency ratio, turnover, and capital were predictors of independent auditor selection. Conclusion - The current study is practically the first to focus on this topic in the specific context of Iran. In this regard, the study may be valuable for application in developing countries.

• Structural Engineering and Mechanics
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• v.17 no.6
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• pp.819-828
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• 2004

A new process for estimating the natural frequency and the corresponding damping ratio in large structures is discussed. In a practical situation, it is very difficult to analyze large structures precisely because they are too complex to model using the finite element method and too heavy to excite using the exciting force method; in particular, the measured signals are seriously influenced by ambient noise. In order to identify the structural impulse response associated with the information of natural frequency and the corresponding damping ratio in large structures, the analysis process, a so-called "multiresolution blind system identification algorithm" which combines Mallat algorithm and the bicepstrum method. High time-frequency concentration is attained and the phase information is kept. The experimental result has demonstrated that the new analysis process exploiting the natural frequency and the corresponding damping ratio of structural response are useful tools in structural analysis application.