• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.876-883
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• 2003

In this paper, we propose an algorithm for organ recognition in ultrasound images using log power spectrum. The main procedure of the algorithm consists of feature extraction and feature classification. In the feature extraction, as a translation invariant feature, log power spectrum is used for extracting the information on echo of the organs tissue from a preprocessed input image. In the feature classification, Mahalanobis distance is used as a measure of the similarity between the feature of an input image and the representative feature of each class. Experimental results for real ultrasound images show that the proposed algorithm yields the improvement of maximum 30% recognition rate than the recognition algorithm using power spectrum and Euclidean distance, and results in better recognition rate of 10-40% than the recognition algorithm using weighted quefrency complex cepstrum.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.4
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• pp.614-624
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• 2013

The resonance power buoy is a convincing tool that can increase the extraction efficiency of wave energy. The buoy needs a corresponding draft, to move in resonance with waves within the peak frequency band where wave energy is concentrated. However, it must still be clarified if the buoy acts as an effective displacement amplifier, when there is insufficient water depth. In this study, the vertical displacement of a circular cylinder-type buoy was calculated, with the spectrum data observed in a real shallow sea as the external wave force, and with the corresponding draft, according to the mode frequency of normal waves. Such numerical investigation result, without considering Power Take-Off (PTO) damping, confirmed that the area of the heave responses spectrum can be amplified by up to about tenfold, compared with the wave energy spectrum, if the draft corresponds to the peak frequency, even with insufficient water depth. Moreover, the amplification factor of the buoy varied, according to the seasonal changes in the wave spectra.

• Proceedings of the KWS Conference
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• 1999.05a
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• pp.134-137
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• 1999

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.959-966
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• 2010

Quantitative ultrasound analysis provides fundamental information of various ultrasound parameters using spectral information of the short-gated radiofrequency(RF) data. Therefore, accurate extraction of spectral information from backscattered RF signal is crucial for further analysis of medical ultrasound parameters. In this paper, we propose two techniques for calculating a more accurate power spectrum which are based on the phase-compensation using the normalized cross-correlation to minimize estimation errors due to phase variations, and the weighted averaging technique to maximize the signal-to-noise ratio(SNR). The simulation results demonstrate that the proposed method estimates better results with 10% smaller estimation variances compared to the conventional methods.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.4
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• pp.739-749
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• 2015

A new conceptual dual-buoy Wave Energy Converter (WEC) for the enhancement of energy extraction efficiency is suggested. Based on actual wave data, the design process for the suggested WEC is conducted in such a way as to ensure that it is suitable in real sea. Actual wave data measured in Korea's East Sea (position: $36.404N^{\circ}$ and $129.274E^{\circ}$) from May 1, 2002 to March 29, 2005 were used as the input wave spectrum for the performance estimation of the dual-buoy WEC. The suggested WEC, a point absorber type, consists of two concentric floating circular cylinders (an inner and a hollow outer buoy). Multiple resonant frequencies in proposed WEC affect the Power Ttake-off (PTO) performance of the WEC. Based on the numerical results, several design strategies are proposed to further enhance the extraction efficiency, including intentional mismatching among the heave natural frequencies of dual buoys, the natural frequency of the internal fluid, and the peak frequency of the input wave spectrum.

• Biomolecules & Therapeutics
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• v.8 no.1
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• pp.63-72
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• 2000

We intended to show some basic requirements for spectrum analysis of electroencephalogram (EEG) by visualizing the differences of the results according to different values of some parameters for analysis. Spectrum analysis is the most popular technique applied for the quantitative analysis of the electroen- cephalographic signals. Each step from signal acquisition through spectrum analysis to presentation of parameters was examined with providing some different values of parameters. The steps are:(1) signal acquisition; (2) spectrum analysis; (3) parameter extractions; and (4) presentation of results. In the step of signal acquisition, filtering and amplification of signal should be considered and sampling rate for analog-to-digital conversion is two-time faster than highest frequency component of signal. For the spectrum analysis, the length of signal or epoch size transformed to a function on frequency domain by courier transform is important. Win dowing method applied for the pre-processing before the analysis should be considered for reducing leakage problem. In the step of parameter extraction, data reduction has to be considered so that statistical comparison can be used in appropriate number of parameters. Generally, the log of power of all bands is derived from the spectrum. For good visualization and quantitative evaluation of time course of the parameters are presented in chronospectrogram.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.2
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• pp.50-55
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• 2000

This paper presents the feature extraction of fault currents related to the multi-shot reclosing scheme in the power distribution system. In order to get the fault current waveform, we have measured the fault currents by the fault recorders which have been installed at the secondary side of 154/22.9[kV] substation transformer. These waveforms are classified into temporary and permanent fault. For the classified waveforms, Fourier transform is used to extract the feature of the fault current waveforms. After the waveforms are analyzed by using Fourier transform, the magnitude spectrum and the relative variation of THD (Total Harmonic Distortion) are calculated. And then the relative variation of THD is great in the temporary faults, and is small in the permanent faults.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.217-222
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• 2004

A person does communication between each other using language. But, In the case of disabled person, cannot communicate own idea to use writing and gesture. We embodied communication system using the EEG so that disabled person can do communication. After feature extraction of the EEG included facial muscle signals, it is converted the facial muscle into control signal, and then did so that can select character and communicate idea.

• Speech Sciences
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• v.1
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• pp.285-293
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• 1997

This paper was constructed to investigate strange attractor in considering speech which is regarded as chaos in that the random signal appears in the deterministic raising system. This paper searches for the delay time from AR model power spectrum for constructing fit attractor for speech signal. As a result of applying Taken's embedding theory to the delay time, an exact correlation dimension solution is obtained. As a result of this consideration of speech, it is found that it has more speaker recognition characteristic parameter, and gains a large speaker discrimination recognition rate.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1375-1384
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• 2014

Flashover of power transmission line insulators is a major threat to the reliable operation of power system. This paper deals with the flashover prediction of polymeric insulators used in power transmission line applications using the novel condition monitoring technique developed by PD signal time-frequency map and neural network technique. Laboratory experiments on polymeric insulators were carried out as per IEC 60507 under AC voltage, at different humidity and contamination levels using NaCl as a contaminant. Partial discharge signals were acquired using advanced ultra wide band detection system. Salient features from the Time-Frequency map and PRPD pattern at different pollution levels were extracted. The flashover prediction of polymeric insulators was automated using artificial neural network (ANN) with back propagation algorithm (BPA). From the results, it can be speculated that PD signal feature extraction along with back propagation classification is a well suited technique to predict flashover of polymeric insulators.