• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.496-503
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• 2009

In the life environment changed with not only the material abundance but also the quality, it is the most crucial factor for the strategy of sensibility engineering to investigate vital signal according to the sensibility. In this perspective, it is necessary to design and merchandise the products in cope with each sensibility and needs as well as its functional aspects. In this paper, we proposed the correlation between the visual sensibility and the vital signal using the wearable based electrocardiogram sensing clothes. We measured the electrocardiogram (ECG) signal by wearing the electrocardiogram sensing clothes. The heart rate variability (HRV) is calculated form the acquired ECG signal by wearing the electrocardiogram sensing clothes. And the power spectrum analysis using the Fast Fourier Transform (FFT) is evaluated the correlation between the visual sensibility and the vital signal. we plan to conduct empirical applications to verify the adequacy and the validity of the proposed method.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.48-54
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• 2013

With the development of IT convergence technology and the construction of infrastructure for water leakage detection, the detection technology of damaged pileline's location and size is being spotlighted. The exhaustion of water resource due to the leakage of water supply facilities renders it urgent to detect water leakage effectively. In this paper, we proposed the water leakage detection monitoring simulation using the power spectrum analysis. We measured the reflected wave signal by the proposed water leakage detection monitoring simulation. The rate variability is calculated form the acquired reflected wave signal. And the power spectrum analysis using the Fast Fourier Transform is evaluated the correlation between the water leakage's size and the reflected wave. Ultimately, this paper suggests empirical simulation to verify the adequacy and the validity. Accordingly, the satisfaction and the quality of services will be improved the efficient management by supporting the real-time water leakage detection.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.253-263
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• 2013

Frequency Scanning Interferometry(FSI) system, one of the most promising optical surface measurement techniques, generally results in superior optical performance comparing with other 3-dimensional measuring methods as its hardware structure is fixed in operation and only the light frequency is scanned in a specific spectral band without vertical scanning of the target surface or the objective lens. FSI system collects a set of images of interference fringe by changing the frequency of light source. After that, it transforms intensity data of acquired image into frequency information, and calculates the height profile of target objects with the help of frequency analysis based on Fast Fourier Transform(FFT). However, it still suffers from optical noise on target surfaces and relatively long processing time due to the number of images acquired in frequency scanning phase. 1) a Polarization-based Frequency Scanning Interferometry(PFSI) is proposed for optical noise robustness. It consists of tunable laser for light source, ${\lambda}/4$ plate in front of reference mirror, ${\lambda}/4$ plate in front of target object, polarizing beam splitter, polarizer in front of image sensor, polarizer in front of the fiber coupled light source, ${\lambda}/2$ plate between PBS and polarizer of the light source. Using the proposed system, we can solve the problem of fringe image with low contrast by using polarization technique. Also, we can control light distribution of object beam and reference beam. 2) the signal processing acceleration method is proposed for PFSI, based on parallel processing architecture, which consists of parallel processing hardware and software such as Graphic Processing Unit(GPU) and Compute Unified Device Architecture(CUDA). As a result, the processing time reaches into tact time level of real-time processing. Finally, the proposed system is evaluated in terms of accuracy and processing speed through a series of experiment and the obtained results show the effectiveness of the proposed system and method.

• Journal of the Korean Recycled Construction Resources Institute
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• v.2 no.3
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• pp.209-216
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• 2014

One of the widely used NDT(Non-destructive techniques) is the ultrasonic pulse velocity (USPV) method, which determines the travel time of the ultrasonic pulse through the tested materials and most studies were focused on the results expressed in time domain. However, the signal of ultrasonic pulse in time domain can be transformed into frequency domain, through Fast fourier transform(FFT) to give more useful informations. This paper shows a comparison of changes in the pulse velocity and frequency domain signals of concrete for various load histories using lightweight fine aggregates. The strength prediction equation for normal concrete using USPV cannot be used to estimate lightweight fine aggregate concrete strength. The signals in frequency domain of ultrasonic pulse of lightweight fine aggregate concrete does not show any significant difference comparing with those of normal concrete. The increases in stress levels of concrete change the pulse velocities and maximum frequencies, however the apparent relationship between themselves can not be found in this experiment.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.2
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• pp.46-54
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• 2012

We propose a continuously varying contact pressure(CVCP)-adaptive feature extraction algorithm for pulse diagnostic analysis. The CVCP method measures the pulse waveform with continuously increasing contact pressure(CP). This method offer a high resolution signal of the pulse waveform amplitude(PWA) as a function of the contact pressure. Therefore it enables us to overcome the limitation of commercially available pulse-taking devices whose analysis rely on a few number of PWA-CP pairs. We show that an efficient feature extraction algorithm which covers the features of the CVCP-method can be developed by sequentially applying Fast Fourier Transform, peak detection by center-to-edges method, baseline drift removal, detection of the percussion wave upstroke by intersecting tangent method and detection of the analysis region. Finally, by a clinical study with 30 subjects, we show that our CVCP-adaptive feature extraction algorithm detected the upstroke with accuracy of 99.46% and sensitivity of 99.51%, which were about 4.82% and 2.46% increases respectively, compared to a conventional feature extraction method. The proposed CVCP method and the CVCP-adaptive feature extraction algorithm are expected to improve the accuracy in the pulse diagnostic algorithms such as floating/sunken pulse qualities and deficient/excess pulse qualities.

• Journal of The Korean Association For Science Education
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• v.21 no.3
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• pp.516-528
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• 2001

In the educational study, the measure of EEG(brain waves) can be useful method to study the functioning state of brain during learning behaviour. This study investigated the changes of neuronal response according to four times repetition of audio-visual learning. EEG data at the prefrontal$(Fp_{1},Fp_{2})$ were obtained from twenty subjects at the 8th grade, and analysed quantitatively using FFT(fast Fourier transform) program. The results were as follows: 1) In the first audio-visual learning, the activities of $\beta_{2}(20-30Hz)$ and $\beta_{1}(14-19Hz)$ waves increased highly, but the activities of $\theta(4-7Hz)$ and $\alpha$ (8-13Hz) waves decreased compared with the base lines. 2). According to the repetitive audio-visual learning, the activities of $\beta_{2}$ and $\beta_{1}$ waves decreased gradually after the 1st repetitive learning. And, the activity of $\beta_{2}$ wave had the higher change than that of $\beta_{1}$ wave. 3). The activity of $\alpha$ wave decreased smoothly according to the repetitive audio-visual learning, and the activity of $\theta$ wave decreased radically after twice repetitive learning. 4). $\beta$ and $\theta$ waves together showed high activities in the 2nd audio-visual learning(once repetition), and the learning achievement increased highly after the 2nd learning. 5). The right prefrontal$(Fp_{2})$ showed higher activation than the left$(Fp_{1})$ in the first audio-visual learning. However, there were not significant differences between the right and the left prefrontal EEG activities in the repetitive audio-visual learning. Based on these findings, we can conclude that the habituation of neuronal response shows up in the repetitive audio-visual learning and brain hemisphericity can be changed by learning experiences. In addition, it is suggested once repetition of audio-visual learning be effective on the improvement of the learning achievement and on the activation of the brain function.