• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.19-26
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• 2009

This paper presents an approach to classify normal and ventricular tachycardia/fibrillation(VT/VF) from the Creighton University Ventricular Tachyarrhythmia Database(CUDB) using the neural network with weighted fuzzy membership functions(NEWFM) and wavelet transforms. In the first step, wavelet transforms are used to obtain the detail coefficients at levels 3 and 4. In the second step, all of detail coefficients d3 and d4 are classified into four intervals, respectively, and then the standard deviations of the specific intervals are used as eight numbers of input features of NEWFM. NEWFM classifies normal and VT/VF beats using eight numbers of input features, and then the accuracy rate is 90.1%.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.1-11
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• 2017

With a given spring-mass-damper system, $H_{\infty}$ and ${\mu}$-synthesis control methods are used to build system controllers which minimize vibrations at two major natural frequencies in two cases; without uncertainty; with 20% uncertainty. In order to check the stability and performance of two controllers, those are examined using GM and PM values. The signal strength of output responses is compared using the concept of central numerical differentiation and then results are quantified using the RMS method. Lastly, 40 random samples of $H_{\infty}$ and ${\mu}$-synthesis controllers are obtained for three different $W_{per\;f1}$ weighting functions and drawn in the time domain in order to compare the stability. Overall, ${\mu}$-synthesis controller manages the vibrations much better than $H_{\infty}$ controller according to the robust stability and performance values obtained by simulating random samples of 40 plant models.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.6 s.237
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• pp.671-686
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• 2005

The transient nature and complex geometries of two-phase gas-liquid flows cause fundamental difficulties when measuring flow velocity using an electromagnetic flowmeter. Recently, a current-sensing flowmeter was introduced to obtain measurements with high temporal resolution (Ahn et al.). In this study, current-sensing flowmeter theory was applied to measure the fast velocity transients in slug flows. The velocity fields of axisymmetric gas-liquid slug flow in a vertical pipe were obtained using Volume-of-Fluid (VOF) method, and the virtual potential distributions for the electrodes of finite size were also computed using the finite volume method for simulating slug flow. The output signal prediction for slug flow was carried out from the velocity and virtual potential (or weight function) fields. The flowmeter was numerically calibrated to obtain the cross-sectional liquid mean velocity at an electrode plane from the predicted output signal. Two calibration parameters are proposed for this procedure: a flow pattern coefficient and a localization parameter. The flow pattern coefficient was defined by the ratio of the liquid resistance between the electrodes for two-phase flow with respect to that for single-phase flow, and the localization parameter was introduced to avoid errors in the flowmeter readings caused by liquid acceleration or deceleration around the electrodes. These parameters were also calculated from the computed velocity and virtual potential fields. The results can be used to obtain the liquid mean velocity from the slug flow signal measured by a current-sensing flowmeter.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.758-766
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• 2007

High peak-to-average power ratio(PAPR) is one of serious problems in the orthogonal frequency division multiplexing(OFDM) systems. This paper proposes a PAPR reduction technique for limited feedback multiple input multiple output(MIMO) OFDM systems. The proposed method is based on the null space of the MIMO channel where a dummy signal is made in the channel's null space and then, subtracted from the original signal to reduce the PAPR. First, we show that a problem occurs when the existing method is directly applied to limited feedback MIMO case. Then, a weight function for the dummy signal is proposed to mitigate the degradation of the receiver performance while still reducing PAPR significantly. The weight function is derived from a constrained nonlinear optimization problem to minimize the mean square error between the received signal and its ideal signal. Simulation results shows that the proposed technique provides about 2.5dB PAPR reduction with 0.2dB bit-error probability loss.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1951-1956
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• 2004

The transient nature and complex flow geometries of two-phase gas-liquid flows cause fundamental difficulties when measuring flow velocity using an electromagnetic flowmeter. Recently, a current-sensing flowmeter was introduced to obtain measurements with high temporal resolution (Ahn et $al.^{(1)}$). In this study, current-sensing flowmeter theory was applied to measure the fast velocity transients in slug flows. To do this, the velocity fields of axisymmetric gas-liquid slug flow in a vertical pipe were obtained using Volume-of-Fluid (VOF) method and the virtual potential distributions for the electrodes of finite size were also computed using the finite volume method for the simulated slug flow. The output signal prediction for slug flow was carried out from the velocity and virtual potential (or weight function) fields. The flowmeter was numerically calibrated to obtain the cross-sectional liquid mean velocity at an electrode plane from the predicted output signal. Two calibration parameters are required for this procedure: a flow pattern coefficient and a localization parameter. The flow pattern coefficient was defined by the ratio of the liquid resistance between the electrodes for two-phase flow with respect to that for single-phase flow, and the localization parameter was introduced to avoid errors in the flowmeter readings caused by liquid acceleration or deceleration around the electrodes. These parameters were also calculated from the computed velocity and virtual potential fields. The results can be used to obtain the liquid mean velocity from the slug flow signal measured by a current-sensing flowmeter.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.330-335
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• 2000

This paper deals with sensing ability of smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the two type of smart sensors for experiment. The first type of smart sensor is H2 type. The second type of smart sensor is HH type. The smart sensor was developed for recognition of material. And then we developed estimation method of sensing ability of smart sensors. The first method(Sensing Ability Index) is developed for H2 smart sensor. The second method($R_{SAI}$ Index) is developed for HH smart sensor. We estimated sensing ability of smart sensor with new SAI and $R_{SAI}$ method. This paper describes our primary study for a new method of estimate sensing ability of smart sensor, which is need for precision work system. This is a study of dynamic characteristics of smart sensor according to frequency and displacement changing with new SAI and $R_{SAI}$ method. Experiment and analysis are executed for proper dynamic sensing condition. First, we developed advanced smart sensors. Second, we develop new SAI and $R_{SAI}$ methods that have a sensing ability of distinguish materials. Dynamic characteristics of smart sensor are evaluated through new SAI and $R_{SAI}$ method relatively. We can use the new SAI and $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object(auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.151-155
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• 2019

Recently heart attack is 80% of the sudden death of elderly. The causes of a heart attack are complex and sudden, and it is difficult to predict the onset even if prevention or medical examination is performed. Therefore, early diagnosis and proper treatment are the most important. In this paper, we show the accuracy of normal and abnormal classification with neural network using weighted fuzzy function for accurate and rapid diagnosis of myocardial infarction. The data used in the experiment was data from the UCI Machine Learning Repository, which consists of 14 features and 303 sample data. The algorithm for feature selection uses the average of weight method. Two features were selected and removed. Heart attack was classified into normal and abnormal(1-normal, 2-abnormal) using the average of weight method. The test result for the diagnosis of heart attack using a weighted fuzzy neural network showed 87.66% accuracy.

• Computational Structural Engineering
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• v.8 no.1
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• pp.127-136
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• 1995

In this paper the stochastic FE analysis considering the material and geometrical property of the plate structure is performed by the weighted integral method. To consider the stochasity of the material and geometrical property, the stochastic field is assumed respectively. The mean value of the stochastic field is 0 and the value of variance is assumed as 0.1. The characteristics of the assumed stochastic field is represented by auto-correlation function. This auto-correlation function is used in evaluating the response variability of the plate structure. In this study a new auto-correlation function is derived to concern the uncertainty of the plate thickness. The newly derived auto-correlation function is a function of auto-correlation function and coefficient of variation of the assumed stochastic field. The two results, obtained by proposed Weighted Integral method and Monte Carlo Simulation method, are coincided with each other and these results are almost equal to the theoretical result that is derived in this study. In the case of considering the variability of plate thickness, the obtained result is well coincide with those of Lawrence and Monte Carlo simulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.1
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• pp.61-68
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• 1986

A set of the shape functions which perfectly satisfy the homogeneous Euler Equations has been proposed for deep beam problems. A finite element beam model using the proposed shape functions has been derived by the Galerkin weighted residual method and used to analyze the numerical examples without reduced shear integration, to show the accuracy and efficiency of the proposed shape functions. The result shows that the finite element model using the proposed shape functions gives very accurate solutions for both static and free vibration analyses. The concept of the proposed shape functions is thought to be applied for the finite element analysis of the elasto-static problems.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.7
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• pp.703-714
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• 2010

This paper describes the design optimization of a rotating rectangular channel with staggered arrays of pin-fins by Kriging metamodeling technique. Two non-dimensional variables, the ratio of the height to the diameter of the pin-fins and the ratio of the spacing between the pin-fins to the diameter of the pin-fins are chosen as the design variables. The objective function that is a linear combination of heat transfer and friction loss related terms with a weighting factor is selected for the optimization. To construct the Kriging model, objective function values at 20 training points generated by Latin hypercube sampling are evaluated by a three-dimensional Reynolds-averaged Navier-Stokes (RANS) analysis method with the SST turbulence model. The Kriging model predicts the objective function value that agrees well with the value calculated by the RANS analysis at the optimum point. The objective function is reduced by 11% by the optimization of the channel.