• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.451-459
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• 2017

There are many researches showing that when a process change has occurred, variable sampling intervals (VSI) control chart is better than the fixed sampling interval (FSI) control chart in terms of reducing the required time to signal. When the process engineers use VSI control procedure, frequent switching between different sampling intervals can be a complicating factor. However, average number of samples to signal (ANSS), which is the amount of required samples to signal, and average time to signal (ATS) do not provide any control statistics about switching performances of VSI charts. In this study, we evaluate numerical switching performances of multivariate VSI EWMA chart including average number of switches to signal (ANSW) and average switching rate (ASWR). In addition, numerical study has been carried out to examine how to improve the performance of considered chart with accumulate-combine approach under several different smoothing constant and sample size. In conclusion, process engineers, who want to manage the correlation coefficients of related quality variables, are recommended to make sample size as large and smoothing constant as small as possible under permission of process conditions.

• Journal of Digital Contents Society
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• v.8 no.1
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• pp.9-15
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• 2007

Smoothing is a transmission plan where variable rate video data is converted to a constant bit rate stream. Among them are CBA, MCBA, MVBA, e-PCRTT and others. e-PCRTT algorithm, which was improved from PCRTT, restricts the number of rate changes with fixed-size run. This causes unnecessary rate changes when run size is small and buffer size is large. In this paper, to overcome a shortcoming of e-PCRTT algorithm, a smoothing algorithm is proposed, which is improved from e-PCRTT, where a transmission rate transmits more intervalsl as possible. Experiments demonstrated that the proposed algorithm outperformed e-PCRTT algorithm. In order to show the performance, various evaluation factors were used such as the number of transmission rate changes, peak rate, transmission rate variability and so on.

• 한국전산유체공학회:학술대회논문집
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• 2001.10a
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• pp.11-19
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• 2001

An adaptive nonlinear artificial dissipation model is presented for performing aeroacoustic computations by the high-order and high-resolution numerical schemes based on the central finite differences. An effective formalism of it is devised by combining a selective background smoothing term and a well-established nonlinear shock-capturing term which is for the temporal accuracy as well as the numerical stability. A conservative form of the selective background smoothing term is presented to keep accurate phase speeds of the propagating nonlinear waves. The nonlinear shock-capturing term that has been modeled by the second-order derivative term is combined with it to improve the resolution of discontinuities and stabilize the strong nonlinear waves. It is shown that the improved artificial dissipation model with an adaptive control constant which is independent of problem types reproduces the correct profiles and speeds of nonlinear waves, suppresses numerical oscillations near discontinuity and avoids unnecessary damping on the smooth linear acoustic waves. The feasibility and performance of the adaptive nonlinear artificial dissipation model are investigated by the applications to actual computational aeroacoustics problems.

• Journal of KIISE:Information Networking
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• v.29 no.5
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• pp.495-500
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• 2002

We propose a new estimation method for rate adjustment in the face of a packet loss in the TFRC protocol, a TCP-Friendly congestion control protocol for UDP flows. Previous methods respond in a sensitive way to a single packet loss, resulting in oscillatory transmission behavior. This is an undesirable for multimedia services demanding constant bandwidth. The proposed TFRC provides more smooth and fair (against TCP flows) transmission through collective response based on multiple packets loss events. We show our "Exponential smoothing method" performs better than known "Weight smoothing method" in terms of smoothness and fairness.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.5
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• pp.193-198
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• 1986

In this paper, 1-168 hours ahead load prediction algorithm is developed for power system economic weekly operation. Total load is composed of three components, which are base load, week load and weather-sensitive load. Base load and week load are predicted by moving average and exponential smoothing method, respectively. The days of moving average and smoothing constant are optimally determined. Weather-sensitive load is modeled by linear form. The paramiters of weather load model are estimated by exponentially weighted recursive least square method. The load prediction of special day is very tedious, difficult and remains many problems which should be improved. Test results are given for the day of different types using the actual load data of KEPCO.

• The KIPS Transactions:PartC
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• v.11C no.7 s.96
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• pp.1009-1022
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• 2004

Smoothing is a transmission plan where variable rate video data is converted to a constant bit rate stream. Among them are CHA, MCBA. MVBA, e-PCRTT and others. E-PCRTT algorithm, which was improved from PCRTT, restricts the number of rate changes with fixed-size run. This causes unnecessary rate changes and may not guarantee QoS when buffer size is small. In this paper. a smoothing algorithm is pro-posed, where the number of rate changes are not limited and the size of run can be flexible, in order to overcome the shortcomings of e-PCRTT. Experiments demonstrated that the proposed algorithm such as e-PCRTT. In order to show the performance, var-ious evaluation factors were used such as the nember of rate changes, buffer size to maintain QoS, and so on.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.579-585
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• 2012

Many different semi-supervised learning algorithms have been proposed for use wit unlabeled data. However, most of them focus on classification problems. In this paper we propose a semi-supervised regression algorithm called the semi-supervised local constant estimator (SSLCE), based on the local constant estimator (LCE), and reveal the asymptotic properties of SSLCE. We also show that the SSLCE has a faster convergence rate than that of the LCE when a well chosen weighting factor is employed. Our experiment with synthetic data shows that the SSLCE can improve performance with unlabeled data, and we recommend its use with the proper size of unlabeled data.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.413-422
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• 1999

Multivariate EWMA control charts to simultaneously monitor correlation coefficients of correlated quality characteristics under multivariate normal process are proposed. Performances of the proposed charts are measured in terms of average run length(ARL). Numerical results show that smalle values for smoothing constant with accumulate-combine approach are preferred for detecting smalle shifts.

• Journal of Korean Society for Quality Management
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• v.26 no.2
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• pp.51-60
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• 1998

Exponetially weighted moving average(EWMA) control chart to simultaneously monitor correlation coefficients of several correlated quality variables under multivariate normal process are proposed. Performances of the proposed control charts are measured in terms of average run length(ARL) by simulation. Numerical results show that smaller values of smoothing constant are more efficient in terms of ARL.

• Journal of electromagnetic engineering and science
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• v.4 no.1
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• pp.23-29
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• 2004

In this paper we analyze convergence constraints and time constant of IT-LMS algorithm and derive a method of making it's time constant independent of signal power by using input variance estimation. The method for estimating the input variance is to use a single-pole low-pass filter(LPF) with common smoothing parameter value, θ. The estimator is with narrow bandwidth for large θ but with wide bandwidth for small θ. This small θ gives long term average estimation(low frequency) of the fluctuating input variance well as short term variations (high frequency) of the input power. In our simulations of multipath communication channel equalization environments, the method with large θ has shown not as much improved convergence speed as the speed of the original IT-LMS algorithm. The proposed method with small θ=0.01 reach its minimum MSE in 100 samples whereas the IT-LMS converges in 200 samples. This shows the proposed, tap-power normalized IT-LMS algorithm can be applied more effectively to digital wireless communication systems.