Earticle

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for parameter design to solve the dual response problems without resorting to SN.

The purpose of this study is to explore the effects of Chamaecyparis obtusa essential oil on the activity of autonomic nervous system. Heart rate variability (HRV), as an indicator of autonomic nervous system activity and blood pressure were measured before and after inhalation of Chamaecyparis obtusa essential oil. The systolic blood pressure was decreased by inhalation of Chamaecyparis obtusa essential oil (p<0.05). The diastolic blood pressure was not changed significantly by Chamaecyparis obtusa. High frequency (HF) power level was not changed but High frequency/Low frequency (HF/LF) ratio was decreased by Chamaecyparis obtusa essential oil (p<0.05), meaning that parasympathetic nervous system activity was not affected but sympathetic nervous system activity was decreased. These results indicate that Chamaecyparis obtusa essential oil has a modulatory effect on the autonomic nervous system activity.

In many cases, the quality of a product is determined by several correlated quality variables. Control charts have been used for a long time widely to control the production process and to quickly detect the assignable causes that may produce any deterioration in the quality of a product. Numerical switching performances of multivariate cumulative sum control chart for simultaneous monitoring all components in the dispersion matrix Σ under multivariate normal process Np( μ , Σ ) are considered. Numerical performances were evaluated for various shifts of the values of variances and/or correlation coefficients in Σ . Our computational results show that if one wants to quick detect the small shifts in a process, CUSUM control chart with small reference value 􀆉 is more efficient than large k in terms of average run length (ARL), average time to signal (ATS), average number of switches (ANSW).

The reaction of 1,1-dichloro-2,3,4,5-tetraphenyl-1-silacyclopentadiene (1) with magnesium-amalgam in THF gave octaphenyl-1,1′-spirobisilole (2), so it was suggested that octaphenyl-1,1′-spirobisilole (2) was produced via the corresponding silolylene species

Many researchers in various study fields use the two sample t - test to confirm their treatment effects. The two sample t - test is generally used for small samples, and assumes that two independent random samples are selected from normal populations, and the population variances are unknown. Researchers often conduct t - test, the test of equality of variances, before testing the treatment effects, and the test statistic or confidence interval for the two sample t - test has two formats according to whether the variances are equal or not. Researchers using the two sample t - test often want to know how large sample sizes they need to get reliable test results. This research gives some guidelines for sample sizes to them through simulation works. The simulation had run for normal populations with the different ratios of two variances for different sample sizes ( ≤ 30 ). The simulation results are as follows. First, if one has no idea equality of variances but he/she can assume the difference is moderate, it is safe to use sample size at least 20 in terms of the nominal level of significance. Second, the power of t - test for the equality of variances is very low when the sample sizes are small (＜ 30 ) even though the ratio of two variances is equal to 2. Third, the sample sizes at least 10 for the two sample t - test are recommendable in terms of the nominal level of significance and the error limit.