• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1247-1252
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• 2004

The present paper is devoted to the modeling method based on an averaging approach for thermal analysis of microchannel heat sinks subjected to the uniform wall temperature condition. Solutions for velocity and temperature distributions are presented using the averaging approach. When the aspect ratio of the microchannel is higher than 1, these solutions accurately evaluate thermal resistances of heat sinks. Asymptotic solutions for velocity and temperature distributions at the high-aspect-ratio limit are alsopresented by using the scale analysis. Asymptotic solutions are simple, but shown to predict thermal resistances accurately when the aspect ratio is higher than 10. The effects of the aspect ratio and the porosity on the friction factor and the Nusselt number are presented. Characteristics of the thermal resistance of microchannel heat sinks are also discussed.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1430-1435
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• 2004

The present paper is devoted to the modeling based on an averaging approach for microchannel heat sinks. Firstly, analytic solutions for velocity and temperature distributions for low-aspect-ratio microchannel heat sinks are presented by using the averaging approach. When the aspect ratio of the microchannel is smaller than 1, analytic solutions accurately evaluate thermal resistances of heat sinks while the previous model cannot predict thermal resistances. Secondly, asymptotic solutions for velocity and temperature distributions at low-aspect-ratio limit and at high-aspect-ratio limit are presented by using the scale analysis. Asymptotic solutions are very simple, but shown to predict thermal resistances accurately.

• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.67-80
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• 2017

Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.589-598
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• 2018

To maintain safety and reliability of reactors, redundant sensors are usually used to measure critical variables and estimate their averaged time-dependency. Nonhealthy sensors can badly influence the estimation result of the process variable. Since online condition monitoring was introduced, the online cross-calibration method has been widely used to detect any anomaly of sensor readings among the redundant group. The cross-calibration method has four main averaging techniques: simple averaging, band averaging, weighted averaging, and parity space averaging (PSA). PSA is used to weigh redundant signals based on their error bounds and their band consistency. Using the consistency weighting factor (C), PSA assigns more weight to consistent signals that have shared bands, based on how many bands they share, and gives inconsistent signals of very low weight. In this article, three approaches are introduced for improving the PSA technique: the first is to add another consistency factor, so called trend consistency (TC), to include a consideration of the preserving of any characteristic edge that reflects the behavior of equipment/component measured by the process parameter; the second approach proposes replacing the error bound/accuracy based weighting factor ($W^a$) with a weighting factor based on the Euclidean distance ($W^d$), and the third approach proposes applying $W^d$, TC, and C, all together. Cold neutron source data sets of four redundant hydrogen pressure transmitters from a research reactor were used to perform the validation and verification. Results showed that the second and third modified approaches lead to reasonable improvement of the PSA technique. All approaches implemented in this study were similar in that they have the capability to (1) identify and isolate a drifted sensor that should undergo calibration, (2) identify a faulty sensor/s due to long and continuous missing data range, and (3) identify a healthy sensor.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09c
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• pp.61-65
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• 2010

The performance of slopes during earthquake is often accessed in terms of permanent deformation. In the assessment of permanent deformation, Newmark-type rigid block analysis is widely used. Original Newmark-type block approach, however, assumes the potential sliding mass to be rigid, and has been criticized to be potentially unconservative. The paper reviews analytically the impact of this noncompliance assumption on computed permanent deformations. The results indicate that there is a simple criterion that can be used to determine the level of conservativeness of the rigid block approach in cases of gently-sloping slip surfaces and retaining walls.

• Journal of Power Electronics
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• v.10 no.1
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• pp.1-8
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• 2010

A new scheme for sliding-mode control (SMC) of DC-DC converters with a constant switching frequency is proposed. The scheme is based on the averaging model and the output signal of the controller is $d^+$ or $d^-$ instead of the on or off signal of a direct sliding-mode (SM) controller or the continuous signal d = $u_{eq}$ of an indirect SM controller. Two approaches using the new scheme are also proposed and the design procedures for a buck converter are given in detail. The first approach called constant $d^+$ and $d^-$ SMC is simple, cost effective and dynamically fast. In order to improve the dynamic characteristics of the reaching phase and to alleviate chattering, the second approach called reaching law SMC is also presented. Analyses and simulation results demonstrate the feasibility of the proposed scheme.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2315-2325
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• 2015

Induction motors are widely used in industrial processes since they offer a very high degree of reliability. But like any other machine, they are vulnerable to faults, which if left unmonitored, might lead to an unexpected interruption at the industrial plant. Therefore, the condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault features selection. However, in induction-motor drives, rotor defects are the most complex in terms of detection since they interact with the supply frequency within a restricted band around this frequency, especially in the no-loaded case. To overcome this drawback, this paper deals with an efficient and new method to diagnose the induction-motor rotor fault based on the digital implementation of the monitoring algorithm based on the association of the Time Synchronous Averaging technique and Discrete Wavelet Transform. Experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the combined “Time Synchronous Averaging – Discrete Wavelet Transform” approach.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.256-261
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• 2008

In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the conditional maximum a posteriori criterion. A crucial component of a practical speech enhancement system is the estimation of the noise power spectrum. One state-of-the-art approach is the minima controlled recursive averaging (MCRA) technique. The noise estimate in the MCRA technique is obtained by averaging past spectral power values based on a smoothing parameter that is adjusted by the signal presence probability in frequency subbands. We improve the MCRA using the speech presence probability which is the a posteriori probability conditioned on both the current observation the speech presence or absence of the previous frame. With the performance criteria of the ITU-T P.862 perceptual evaluation of speech quality (PESQ) and subjective evaluation of speech quality, we show that the proposed algorithm yields better results compared to the conventional MCRA-based scheme.

• Interaction and multiscale mechanics
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• v.3 no.1
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• pp.1-22
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• 2010

In this paper one introduces a method of multiscale modelling called collection of dynamical systems with dimensional reduction. The method is suggested to be an appropriate approach to theoretical modelling of phenomena in mechanics of materials having in mind especially dynamics of processes. Within this method one formalizes scale of averaging of processes during modelling. To this end a collection of dynamical systems is distinguished within an elementary dynamical system. One introduces a dimensional reduction procedure which is designed to be a method of transition between various scales. In order to consider continuum models as obtained by means of the dimensional reduction one introduces continuum with finite-dimensional fields. Owing to geometrical elements associated with the elementary dynamical system we can formalize scale of averaging within continuum mechanics approach. In general presented here approach is viewed as a continuation of the rational mechanics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.223-229
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• 2005

In this paper, we proposed an extended edge-based line averaging method for deinterlacing with restricted search range. Conversion from interlaced signal to non-interlaced signal is one of important issues. Conventional deinterlacing algorithms usually utilize edge-based line average algorithm(ELA) within pixel-by-pixel approach. However, it is very sensitive to noise and variation of intensity. To reduce the sensitivity, the proposed method adopts a block-by-block approach and provides reliable direction of edge. Simulation results show that it provides a better performance than other pixel-by-pixel ELA-based methods.