• Smart Structures and Systems
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• v.1 no.2
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• Composites Research
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• v.20 no.6
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• pp.21-27
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• 2007

Low-velocity impact damage in a composite stiffened panel was detected using built-in piezoelectric active sensor arrays. Using these piezoelectric active sensors, various diagnostic signals were generated to propagate Lamb waves through the structure and the responses were picked up to detect changes in the structure's vibration signature due to the damage. Three algorithms - ADI(Active Damage Interrogation), TD RMS (Time Domain Root Mean Square) and STFT (Short Time Fourier Transform) - were examined to express the features of the signal changes as one damage index. From damage detecting tests, two impact induced delaminations were detected and the location was estimated with the algorithms and diagnostic signals.

• KIEE International Transactions on Electrophysics and Applications
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• v.3C no.2
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• pp.59-65
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• 2003

Electrical properties such as permittivity and tan$\delta$ of unaged (control) and aged (72 h at 18$0^{\circ}C$) mica/epoxy composites of 130 ${\mu}{\textrm}{m}$ thickness were measured and their surface conditions were characterized using scanning electron microscopy (SEM), Fourier transform infrared (FTIR), electron spectroscopy for chemical analysis (ESCA), differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Both permittivity and tan6 of control specimens were higher than those of short-time aged specimens. FTIR results show a new peak at 1710 $cm^{-1}$ / for short-time aged specimens, originating from carbonyl group formed by the oxidation reaction during the aging process. ESCA results show that the binding energy at 532.9 eV representing the singlet state of oxygen ( $O_{1s}$) decreases by 13.7%, whereas that at 534.6 eV increases by 13.7%. Glass transition temperatures of control and short-time aged specimens are observed to be 95.4$^{\circ}C$ and 113.4$^{\circ}C$, which increase with the increase of aging time. TGA results indicate that the control specimens contain a smaller amount of volatile components than the short-time aged specimens.s.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.58-63
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• 1998

B.Widrow established fundamental relations between the least-mean-square (LMS) algorithm and the digital Fourier transform［1］. By extending these relations, we proposed the short time spectra analysis system using the LMS algorithm［2]. In that paper, we used the normal LMS algorithm on the thought of dealing with only real analytical signal. This algorithm minimizes the real mean-square by recursively altering the complex weight vector at each sampling instant. But, the short time spectra analysis sometimes deals with the complex signal that is outputted from complex analog filter. So, in order to optimize and develop this methods, furthermore it is necessary to derive an algorithm for the complex analytical signal. In this paper, we first discuss the new adaptive system for the spectra analysis using the complex LMS algorithm and then derive convergence condition, time constant of coefficient adjustment and frequency resolution by extending the discussion. Finally, the effectiveness of the proposed method is experimentally demonstrated by applying it to the measurement of transfer performance on complex analog filter.

• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1646-1654
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• 2017

Pupil size variation can not be controlled intentionally by the user and includes various features such as the blinking frequency and the duration of a blink, so it is suitable for understanding the user's emotional state. In addition, an ocular feature based emotion classification method should be studied for virtual and augmented reality, which is expected to be applied to various fields. In this paper, we propose a novel emotion classification based on CNN with pupil size variation signals which include not only various ocular feature information but also time information. As a result, compared to previous studies using the same database, the proposed method showed improved results of 5.99% and 12.98% respectively from arousal and valence emotion classification.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1103-1108
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• 2023

In this paper, we propose a new algorithm for attenuating the background noises in acoustic signal. This algorithm improves the noise attenuation performance by using the FNN(: Full-connected Neural Network) deep learning algorithm instead of the existing adaptive filter after wavelet transform. After wavelet transforming the input signal for each short-time period, noise is removed from a single input audio signal containing noise by using a 1024-1024-512-neuron FNN deep learning model. This transforms the time-domain voice signal into the time-frequency domain so that the noise characteristics are well expressed, and effectively predicts voice in a noisy environment through supervised learning using the conversion parameter of the pure voice signal for the conversion parameter. In order to verify the performance of the noise reduction system proposed in this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed. As a result of the experiment, the proposed deep learning algorithm improved Mean Square Error (MSE) by 30% compared to the case of using the existing adaptive filter and by 20% compared to the case of using the STFT(: Short-Time Fourier Transform) transform effect was obtained.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.37-38
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• 2005

Although the law of classical fourier heat conduction predicts the heat conduction phenomena occurred in most engineering fields with a good accuracy, it is also well-known that the conventional fourier law of a heat conduction has an application limit when the heating and cooling are periodic for a short duration or when the heat conduction is analyzed in the extremely low temperature region. This application limit of classical fourier law results from the fact that it assumed the infinite speed of a heat wave. In this study, we investigated the feasibility of whether the molecular dynamics could be used to calculate the speed of a heat wave through a solid. The calculated sound velocity showed a good agrement with the theoretical prediction qualitatively. From the calculated results, we confirmed that the same methodology can be applied the evaluation of the speed of a heat wave.

• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.319-327
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• 2011

Skeletal muscle fatigue is defined as a 'any reduction in the maximal capacity to generate force or power output', and is the reduction of oxygen consumption and by-product of metabolism. For the muscle fatigue therapy, low level laser has been introduced that leads the mitochondrial respiratory and attributes the muscle fatigue recovery. This study analyzed the muscle fatigue signals from electromyography(EMG) during low-level laser therapy (LLLT). Healthy subjects performed voluntary elbow flexion-extension excercise and received placebo LLLT and active LLLT using a 830 nm laser diode. Then, EMG were measured for the evaluation of muscle fatigue. The acquired EMG data were analyzed with median frequency and short time fourier transform methods. The results showed that the LLLT had a significant symptomatic relief of muscle fatigue based on the EMG frequency analysis. Therefore, the muscle fatigue analysis with EMG signals can be applied to quantitative evaluation for the monitoring of LLLT effects.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.7
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• pp.848-851
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• 2012

As many radar systems are simultaneously operated with overlapping frequency bands, interference between systems inevitably occurs. Because interference can degrade radar performance, suppression of interference is a critical issue in radar systems. In this letter, a new interference detection and suppression method using a short-time Fourier transform and an adaptive notch filter is proposed. An experiment is carried out to validate the proposed method and the results demonstrate that the proposed method is suitable for application in real FMCW radars.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.899-905
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• 2012

Level Gauge using FMCW Radar is widely used and researched in many areas because of contactless, long range and flexibility. However FMCW level gauge requires wideband RF bandwidth for archiving high resolution of cm grade. In this paper we propose a new tx sawtooth waveform and processing algorithm with narrowband RF for wideband performance. The proposed method is based on STFT(Short-time fourier transform) and single sinusoidal carrier estimation method. From some experiments, we show that the resolution is improved upto 8 times with 300MHz FMCW radar.