• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.689-694
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• 2011

Objective: The aim of this study is to evaluate the fluctuation of signal amplitude during repetitive dynamic contraction based on surface electromyography(EMG). Background: The most previous studies were considered isometric muscle contraction and they were difference to smoothing window length by moving average filter. In practical, the human movement is dynamic state. Dynamic EMG signal which indicated as the nonstationary pattern should be analyzed differently compared with the static EMG signal. Method: Ten male subjects participated in this experiment, and EMG signal was recorded by biceps brachii, anterior/posterior deltoid, and upper/lower trapezius muscles. The subject was performed to repetitive right horizontal lifting task during ten cycles. This study was considered three independent variables(muscle, amplitude processing technique, and smoothing window length) as the within-subject experimental design. This study was estimated muscular activation by means of the linear envelope technique(LE). The dependent variable was set coefficient of variation(CV) of LE for each cycle. Results: The ANOVA results showed that the main and interaction effects between the amplitude processing technique and smoothing window length were significant difference. The CV value of peak LE was higher than mean LE. According to increase the smoothing window length, this study shows that the CV trend of peak LE was decreased. However, the CV of mean LE was analyzed constant fluctuation trend regardless of the smoothing window length. Conclusion: Based on these results, we expected that using the mean LE and 300ms window length increased reproducibility and signal noise ratio during repetitive dynamic muscle contraction. Application: These results can be used to provide fundamental information for repetitive dynamic EMG signal processing.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.84-89
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• 2014

Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.

• Journal of the Optical Society of Korea
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• v.12 no.3
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• pp.121-125
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• 2008

We address the problem of Blind Source Separation(BSS) of superimposed signals in situations where one signal has constant or slowly varying intensities at some consecutive locations and at the corresponding locations the other signal has highly varying intensities. Independent Component Analysis(ICA) is a major technique for Blind Source Separation and the existing ICA algorithms fail to estimate the original intensities in the stated situation. We combine the advantages of existing sparse methods and Kernel ICA in our technique, by proposing wavelet packet based sparse decomposition of signals prior to the application of Kernel ICA. Simulations and experimental results illustrate the effectiveness and accuracy of the proposed approach. The approach is general in the way that it can be tailored and applied to a wide range of BSS problems concerning one-dimensional signals and images(two-dimensional signals).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.575-583
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• 2000

Pulse oximetry is a well established non-invasive optical technique for monitoring the $SpO_2$ during anaesthesia, recovery and intensive care. Pulse oximeters determine the oxygen saturation level of blood by measuring the light absorption of arterial blood. In the measurement of the hemoglobin oxygen saturation, conventional method has required the technique of filtering of remove the noise, and of complex signal processing algorithm. So much time have been required to signal processing. In this research, we separate AC signal and DC signal in the stage of signal detection. Therefore we simplify the calculation algorithm for $SpO_2$. The implemented system have the high performance such an accuracy and a processing time than the traditional method.

• Journal of KSNVE
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• v.8 no.5
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• pp.957-963
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• 1998

A new signal processing technique, the directional harmonic wavelet map(dHWM), is presented to characterize the instantaneous planar motion of a measurement point in a structure from its transient complex-valued vibration signal. It is proven that the directional auto-HWM essentially tracks the shape and directively of the instantaneous planar motion, whereas the phase of the directional cross-HWM indicates its inclination angle. Finally, the technique is suessfully applied to an automobile engine for characterization of its transient motion during crank-on/idling/engine-off.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1305-1308
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• 1993

A novel digital signal processing technique based on fuzzy rules is proposed for estimating nonstationary signals, such as image signals, contaminated with additive random noises. In this filter, fuzzy rules are utilized to set the filter parameters, taking the local characteristics of the signal into consideration. The introduction of the fuzzy rules is effective, since the rules to set the filter parameters is usually expressed ambiguously. Computer simulations verify its high performance.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.868-871
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• 2002

Nowadays, zerotrees based digital watermarking techniques are considered to be an efficient watermarking technique used for multimedia data in a compressed form. This paper presents a technique for watermarking an image, by employing zerotrees derived from the wavelet packet coefficients of the transformed image to carry the watermark signal. By setting a proper threshold in zerotrees determining process, the watermark signal can be recovered without the need of original image. With our proposed technique, more amount of watermark signal can be embedded within the image, compared to ordinary wavelet transform based techniques. The experimental results show the improved performance in both qualities of the resultant watermarked image and robustness of the embedded watermark signal against common signal processing such as brightness/contrast enhancement, high-pass filtering, Gaussian noise adding and JPEG compression scheme

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.84-89
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• 2001

Ultrasonic pulse echo method comes to be difficult to apply to the multi-layered structure with very thin layer, because the echoes from the top and the bottom of the layer are overlapped. Conventionally method, deconvolution technique has been used for the decomposition of overlapped UT signals, however it has disabilities when the waveform of the transmitted signal is distorted according to the propagation. In this paper, the wavelet transform based deconvolution (WTBD) technique is proposed as a new signal processing method that can decompose the overlapped echo signals in A-Scan signal with superior performances compared to the conventional deconvolution technique. Performances of the proposed method are shown by through computer simulations using model signal with noise and are demonstrated by through experiments for the fabricated acryl rod with a thin steel plate bonded to it.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.217-225
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• 2000

Scanning Acoustic Microscope (SAM) is used as an important nondestructive test tool in semiconductor reliability evaluation and failure analysis. However, inspections of chip attach adhesive interface fer thin chip has proven difficulty as the reflected signals from the chip top and bottom are superimposed. In this paper, in order to overcome this difficulty, a new signal processing method based on the deconvolution technique combined with the wavelet transform is proposed. The wavelet transform complements a disability of deconvolution technique of which performance largely decreases when the waveform of target signal is not identical to that of reference signal. Performances of the proposed method are demonstrated by through computer simulations using model signal and experiments for the fabricated semiconductor samples, and satisfactory results are obtained.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.399-403
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• 2006

Software-based GNSS receivers have the great advantage in flexibility compared with conventional receivers. But it has some problems to processing IF level Signal RAW data, need long time to process long term data and TTFF is long because the process is too slow. So this time, we concentrated on the signal acquisition, and examined the speedup technique. Using this technique, the acquisition was speedup dramatically, and signal-to-noise ratio was improved.