Saowanit Sukparungsee

A study of VoIP quality evaluation: User perception of voice quality from G.729, G.711 and G.722

This paper presents new evidence about user perception of VoIP quality that is inconsistent with the general understanding of three codecs know as G.729, G.711 and G.722. The focus of the study is aimed at VoIP quality evaluation by Thai users that use the Thai language which is tonal. This study was conducted by using conversation-opinion tests. The results, called MOS-CQS, were then analyzed carefully. After the study and analysis, it has been found that the perception of subjects, who were Thai native speakers, to G.729, G.711 and G.722 is not significantly different.

VoIP Quality of Experience: A proposed subjective MOS estimation model based-on Thai users

To aid authenticity, accuracy and reliability of subjective measurement of VoIP quality measurements, this paper proposes a model that has been created from the subjective MOS, instead of using existing objective measurement methods for VoIP quality measurement. The proposed model of VoIP quality measurement method is based-on Thai users. The data has been gathered from conversation-opinion tests with 400 Thai subjects, referring to packet loss and packet delay effects. This model is called the Thai subjective VoIP Quality Evaluation model (ThaiVQE). It has been evaluated by testing with a test set of subjective MOS, then the results have been compared with the E-model results. Based-on Thai subjects, the evaluation result shows that ThaiVQE can provide better accuracy and reliability than the E-model with improvement of over 20%.

VoIP quality of experience: A study of perceptual voice quality from G.729, G.711 and G.722 with Thai users referring to delay effects

This paper presents the conduction of conversational tests with three codecs; G.729, G.711 and G.722 referring to different one-way delays of <;10 ms, 400 ms and 800 ms, to help investigate delay effects to perceived voice quality by Thai users. The result from this study is found that with the best condition of delay (<;10 ms delay), the delay of 400 ms and 800 ms, the observed difference among three codecs was not statistically significant. Also, it has been found that Thai users did not detect a statistically significant difference of perceived voice quality from the same codec (G.729, G.711 or G.722) among three delay conditions of <;10 ms, 400 ms and 800 ms. This result is not consistent with the ITU-T standard because ITU-T recommended that the delay of 400 ms and above is unacceptable. The possible reasons could be language and cultural effects, which should be investigated in future.

Bivariate copulas on the Hotelling's T2 control chart

ABSTRACT In this paper, we propose five types of copulas on the Hotellings T2 control chart when observations are from exponential distribution and use the Monte Carlo simulation to compare the performance of the control chart, which is based on the Average Run Length (ARL) for each copula. Five types of copulas function for specifying dependence between random variables are used and measured by Kendalls tau. The results show that the copula approach can be fitted the observation and we can use copula as an option for application on Hotellings T2 control chart.

Multivariate copulas on the MCUSUM control chart

Abstract The copula approach is a popular method for multivariate modeling applied in several fields; it defines non-parametric measures of dependence between random variables. In this paper, three families are proposed from elliptical and Archimedean copulas on the multivariate cumulative sum (MCUSUM) control chart when observations are draw from an exponential distribution. The performance of the control chart is based on the average run length (ARL)—via Monte Carlo simulations. A copula function for specifying the dependence between random variables is measured by Kendall’s tau. The numerical results indicate that the observations can be fitted and that the copula can be used on the MCUSUM for cases of small and large dependencies.

Explicit analytical solutions for ARL of CUSUM chart for a long-memory SARFIMA model

ABSTRACT This paper aims to derive explicit analytical solutions for Average Run Length (ARL) of CUSUM chart for the SARFIMA(P,D,Q)S process with exponential white noise. Measurement of performance was done with the ARL in terms of percentage error and CPU time. The results obtained from the explicit formulas were compared focusing on the performance using the numerical integral equation (NIE) method. Both methods had similarly excellent agreement with the percentage error at less than 0.25%. Meanwhile, the explicit formulas consumed less CPU time than the NIE method. It is clear that the explicit formulas are a good alternative in real applications.

Average run length of the long-memory autoregressive fractionally integrated moving average process of the exponential weighted moving average control chart

Abstract Measurement of control chart efficiency by comparison of average run length (ARL) is widely implemented in quality control. The aim of this study is to evaluate the ARL, which is a solution of the integral equation obtained from the Exponential Weighted Moving Average (EWMA) statistic with a long-memory Autoregressive Fractionally Integrated Moving Average (ARFIMA) process. The derivation of the analytical ARL of the EWMA control chart and proof of the existence and uniqueness of the analytical ARL by Fixed Point theory are shown. Moreover, the numerical ARL carried out by the Composite Midpoint Rule technique of the EWMA control chart is demonstrated. A comparison between the analytical and numerical ARL is also illustrated. The findings indicated that analytical ARL of the EWMA control chart is more quickly computational than the numerical ARL. Therefore, the analytical ARL is an alternative method for measuring the efficiency of the EWMA control chart with the long-memory ARFIMA process.

Odds Ratios Estimation of Rare Event in Binomial Distribution

We introduce the new estimator of odds ratios in rare events using Empirical Bayes method in two independent binomial distributions. We compare the proposed estimates of odds ratios with two estimators, modified maximum likelihood estimator (MMLE) and modified median unbiased estimator (MMUE), using the Estimated Relative Error (ERE) as a criterion of comparison. It is found that the new estimator is more efficient when compared to the other methods.

AN EXPLICIT EXPRESSION OF AVERAGE RUN LENGTH OF EXPONENTIALLY WEIGHTED MOVING AVERAGE CONTROL CHART WITH ARIMA(p, d, q)(P, D, Q)_L MODELS

In this paper we propose the explicit formulas of Average Run Length (ARL) of Exponentially Weighted Moving Average (EWMA) control chart for Autoregressive Integrated Moving Average: ARIMA (p,d,q) (P, D, Q)L process with exponential white noise. To check the accuracy, the ARL results were compared with numerical integral equations based on the Gauss-Legendre rule. There was an excellent agreement between the explicit formulas and the numerical solutions. Additionally, we compared the computational time between our explicit formulas for the ARL with the one obtained via Gauss-Legendre numerical scheme. The computational time for the explicit formulas was approximately one second that is much less than the numerical approximations. The explicit analytical formulas for evaluating ARL0 and ARL1 can produce a set of optimal parameters which depend on the smoothing parameter (λ) and the width of control limit (H), for designing an EWMA chart with a minimum ARL1.

Comparative the Performance of Control Charts Based on Copulas

Control charts are quality control procedures to detect a change of manufacturing product. They are used both univariate and multivariate quality characteristics which are random, independent and identically distributed (i.i.d.). Copulas approach can be applied to dependencies and non-normal variables with marginal distributions when the joint distribution could not be found in multivariate cases except normal distribution process. Therefore, the objective of this work is to compare three control charts from three copulas, when observations are exponential distribution via Average Run Length ( ARL ). For specifying dependence between random variables are proposed and measured by Kendall’s tau through Monte Carlo simulation . The numerical results show that the Normal copula of Multivariate Exponentially Weighted Moving Average (MEWMA ) control chart is inferior to other control charts for all magnitudes of shifts.