• Proceedings of the PSK Conference
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• 2003.10a
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• pp.100-101
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• 2003

Cell-cell and cell-matrix interaction is clearly required for metazoans not only to hold their cells together but also to conduct more sophisticated biological processes. Each cell has adhesion molecules on its cell membrane to link extracellular matrix and adjacent cells to the intracellular cytoskeleton, and also to transduce signals. In complex metazoans, information is transmitted from one cell to another by mechanisms such as direct intercellular communication, soluble signal molecules among distant cells, and local cellular environments formed by highly specialized extracellular matrix. (omitted)

• Journal of KSNVE
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• v.8 no.6
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• pp.1103-1112
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• 1998

A new time series method, directional ARMAX (dARMAX) model-based approach. is proposed for rotor dynamics identification. The dARMAX processes complex-valued signals, utilizing the complex modal testing theory which enables the separation of the backward and forward modes in the two-sided frequency domain and makes effective modal parameter identification possible, to account for the dynamic characteristics inherent in rotating machinery. This paper is divided into two parts : The dARMAX modeling, analysis. and fitting strategy are presented in the first part. whereas a evaluation of its performance characteristics based on both simulated and experimental data is presented in the second.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.213-216
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• 1996

In this research we would like to develop an exercise ECG signal analysis algorithm using the wavelet transform, which is possible to analyze the time and the frequency simultaneously. Wavelet transform has an advantage of dividing the nonstationary signals into the high frequency and low frequency band successively. Thus, it can separates the unnecessary noises from the frequency band of QRS complex and then using the selected frequency band we could detect the QRS complex and ST segment.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.217-220
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• 2000

This paper describes the application of a neural network based adaptive line enhancer (ALE) for enhancement of the weak QRS complex corrupted with background noise. Modified fully-connected recurrent neural network is used as a nonlinear adaptive filter in the ALE. The connecting weights between network nodes as well as the parameters of the node activation function are updated at each iteration using the gradient descent algorithm. The real ECG signal buried with moderate and severe background noise is applied to the ALE. Simulation results show that the neural network based ALE performs well the enhancement of the QRS complex from noisy ECG signals.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.818-825
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• 2016

The existing R-peak detection research suggests improving the distortion of the signal such as baseline variations in ECG signals by using preprocessing techniques such as a bandpass filtering. However, preprocessing can introduce another distortion, as it can generate a false detection in the R-wave detection. In this paper, we propose an R-peak detection algorithm in ECG signal, based on primitive signal in order to detect reliably an R-peak in baseline variation. First, the proposed algorithm decides the primitive signal to represent the QRS complex in ECG signal, and by scaling the time axis and voltage axis, extracts multiple primitive signals. Second, the algorithm detects the candidates of the R-peak using the value of the voltage. Third, the algorithm measures the similarity between multiple primitive signals and the R-peak candidates. Finally, the algorithm detects the R-peak using the mean and the standard deviation of similarity. Throughout the experiment, we confirmed that the algorithm detected reliably a QRS group similar to multiple primitive signals. Specifically, the algorithm can achieve an R-peak detection rate greater than an average rate of 99.9%, based on eight records of MIT-BIH ADB used in this experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1063-1071
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• 2008

This paper proposes a prior maximum likelihood (ML) detection verifier which has an ability to verify if the zero forcing (ZF) detection results are identical to the ML detection results. Since more than 90% of ZF detection results are identical to ML detection results, the proposed verifier makes it possible to omit the computationally complex ML detection in 90% cases of MIMO signal detections. The proposed verifier is designed by using the diversity gain obtained from converting MIMO signal into single input multiple output (SIMO) signals. In the proposed method, single input multiple output (SIMO) signals for each transmit antenna are separated from MIMO signals after the MIMO signals are detected by ZF method. Computer simulations show that the true alarm probability of the proposed verifier is more than 80% and the false alarm probability is less than $10^{-4}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1917-1922
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• 2017

WPS(Wifi Positioning System) conducts positioning using wireless signals scattered in real world. This process is divided into two stages: Construction Stage that collects information on wireless signals for determining location and constructs a radio map and Positioning Stage that compares the constructed information with the collected information on wireless signals. WPS lowers the accuracy of positioning if changes occur to the collected signals during positioning. PDR have recently been studied. IPS is a system designed to find out the final destination by analyzing pedestrian's no. of gait, travel range, and direction through inertial sensors. If the positioning results of WPS appear in more than two locations, it can be thought as the problem of positioning accuracy. In some cases, problems occur. In this respect, this study analyzes the situations in which the problem as mentioned above occurs and proposes a system to solve this problem through PDR.

• Korean Journal of Optics and Photonics
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• v.19 no.3
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• pp.175-181
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• 2008

We develop a fiber optic acceleration sensor with LED, PD, POF, and a cantilever beam, having film grating at the edge of the beam. Light is transmitted from LED to PD through the film grating. When the cantilever beam moves by external vibration, output light is modulated as sinusoidal signals. The characteristics of output signals are dominated by the spacing of the film grating and also by the size and the elasticity of the beam. Two output signals, having constant initial phase difference, are obtained by two gratings with 90 degree phase difference. Those two signals are used to determine phase angle, which is proportional to the displacement of the beam. Finally, the acceleration is determined from conversion equation between displacement and acceleration. This sensor is designed for monitoring the vibration of large and complex building in the low frequency range of below 7 Hz, and is particularly suitable to measure acceleration in electromagnetic environments.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.27-34
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• 2002

There is much interest on information communications owing to the rapid development of network and IT(Information Technology). Analog signals are converted into digital signals for information communications. However, it is very difficult to completely erase the distortion induced during the conversion of analog signals such as voices and images into digital signals. Existing audio graphic equalizer requires very complex processes to calculate the gain and coefficients of the higher-order filter which is required to generate natural sound and to satisfy the need of each person. Unfortunately it is uneconomical and very difficult to embed the existing digital audio equalizer in the system because of the complexity of the existing digital audio equalizer for high quality sound. This paper discusses the design of a new digital audio graphic equalizer(DAGEQ) which can improve system performance and the quality of audio sound, and can be embedded in the system. This new DAGEQ is designed so that the gain can be controlled automatically. The automatic control of coefficients and gain empowers real time processing and the improvement of audio quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.86-97
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• 2021

As mechatronic systems have various, complex functions and require high performance, automatic fault detection is necessary for secure operation in manufacturing processes. For conducting automatic and real-time fault detection in modern mechatronic systems, multiple sensor signals are collected by internet of things technologies. Since traditional statistical control charts or machine learning approaches show significant results with unified and solid density models under normal operating states but they have limitations with scattered signal models under normal states, many pattern extraction and matching approaches have been paid attention. Signal discretization-based pattern extraction methods are one of popular signal analyses, which reduce the size of the given datasets as much as possible as well as highlight significant and inherent signal behaviors. Since general pattern extraction methods are usually conducted with a fixed size of time segmentation, they can easily cut off significant behaviors, and consequently the performance of the extracted fault patterns will be reduced. In this regard, adjustable time segmentation is proposed to extract much meaningful fault patterns in multiple sensor signals. By considering inflection points of signals, we determine the optimal cut-points of time segments in each sensor signal. In addition, to clarify the inflection points, we apply Savitzky-golay filter to the original datasets. To validate and verify the performance of the proposed segmentation, the dataset collected from an aircraft engine (provided by NASA prognostics center) is used to fault pattern extraction. As a result, the proposed adjustable time segmentation shows better performance in fault pattern extraction.