• Journal of the Korean Society of Radiology
• /
• v.8 no.5
• /
• pp.225-230
• /
• 2014

Assessments of medical image was improved in accordance with development of medical imaging systems. One of them is edge method to determining MTF(Modulation Transfer Function) based on the Fujita method. Fujita was reduced sampling interval used slightly angulated slit to the direction of pixel array and composited finely sampled LSF to determine presampling MTF. In this study, we investigate the effect of sampling interval on the MTF under a digital imaging system by changing wire angle. The wire method was equivalent to the slit method except signal appearance. A Simens's MAMMOMAT Inspiration with $0.085{\times}0.085mm^2$ pixel size made by amorphous selenium was used and 96% accuracy on MTF in twice sampling interval compared with Fujita was obtained. However, three times of sampling interval showed 93% accuracy on 50% of MTF and 85% accuracy on 10% of MTF.

• Journal of the Korean Data and Information Science Society
• /
• v.4
• /
• pp.31-44
• /
• 1993

Multivariate exponentially weighted moving average (EWMA) control charts for monitoring the variance-covariance matrix are investigated. A variable sampling interval (VSI) feature is considered in these charts. Multivariate EWMA control charts for monitoring the variance-covariance matrix are compared on the basis of their average time to signal (ATS) performances. The numerical results show that multivariate VSI EWMA control charts are more efficient than corrsponding multivariate fixed sampling interval (FSI) EWMA control charts.

• Journal of Korean Society for Quality Management
• /
• v.22 no.1
• /
• pp.66-81
• /
• 1994

Several sample statistics to simultaneously monitor both means and variances for multivariate quality characteristics under multivariate normal process are proposed. Performances of multivariate Shewhart schemes and cumulative sum(CUSUM) schemes are evaluated for matched fixed sampling interval(FSI) and variable sampling interval(VSI) feature. Numerical results show that multivariate CUSUM charts are more efficient than Shewhart charts for small or moderate shifts and VSI feature is more efficient than FSI feature.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.4
• /
• pp.819-829
• /
• 2010

Properties of multivariate variable sampling interval (VSI) Shewhart and CUSUM charts for monitoring mean vector of related quality variables are investigated. To evaluate average time to signal (ATS) and average number of switches (ANSW) of the proposed charts, Markov chain approaches and simulations are applied. Performances of the proposed charts are also investigated both when the process is in-control and when it is out-of-control.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.18 no.33
• /
• pp.143-151
• /
• 1995

In this design the sampling interval that each sampling time changes according to the valuse of the previous to sample statistics, sample mean and ranges. The VSI scheme uses large sample if the sample statistics appear near in side the control limits and smaller sample otherwise. The efficiency of the VSI scheme is compare to the FSI. It is shown that VSI control chart improves the confidence of the procedure and performens better than FSI control chart.

• Water Engineering Research
• /
• v.3 no.1
• /
• pp.31-44
• /
• 2002

The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

• Communications for Statistical Applications and Methods
• /
• v.10 no.3
• /
• pp.1069-1086
• /
• 2003

This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.34 no.2
• /
• pp.1-8
• /
• 2011

This paper proposes a variable sampling interval multivariate $T^2$ control chart with sampling at fixed times, where samples are taken at specified equally spaced fixed time points and additional samples are allowed between these fixed times when indicated by the preceding $T^2$ statistics. At fixed sampling points, the $T^2$ statistics are composed of all quality characteristics and a part of quality characteristics are selected to obtain $T^2$ statistics at additional sampling points. A Markov chain approach is used to evaluate the performance of the proposed chart. Numerical studies for the performance of the proposed chart show that the proposed chart reduces the observations obtained from a process and detects the assignable cause of a process with low correlated quality characteristics quickly.

• Journal of Biomedical Engineering Research
• /
• v.27 no.1
• /
• pp.6-13
• /
• 2006

Ultrasound visualization is a typical diagnosis method to examine organs, soft tissues and fetus data. It is difficult to visualize ultrasound data because the quality of the data might be degraded by artifact and speckle noise, and gathered with non-linear sampling. Rendering speed is too slow since we can not use additional data structures or procedures in rendering stage. In this paper, we use several visualization methods for fast rendering of ultrasound data. First method, denoted as adaptive ray sampling, is to reduce the number of samples by adjusting sampling interval in empty space. Secondly, we use early ray termination scheme with sufficiently wide sampling interval and low threshold value of opacity during color compositing. Lastly, we use bilinear interpolation instead of trilinear interpolation for sampling in transparent region. We conclude that our method reduces the rendering time without loss of image quality in comparison to the conventional methods.

• Journal of Korean Society for Quality Management
• /
• v.28 no.3
• /
• pp.18-30
• /
• 2000

Recent studies have shown that the $\bar{X}$ chart with variable sampling intervals(VSI) and the $\bar{X}$ chart with variable sample size(VSS) are much quicker than Shewhart $\bar{X}$ chart in detecting shiks in the process. Shewhart $\bar{X}$ chart has been beneficial to detect large shifts but it is hard to apply Shewhart $\bar{X}$ chart in detecting moderate shifts in the process mean. In this article the $\bar{X}$ chart using variable sample size(VSS) and variable sampling Intervals(VSI) has been proposed to supplement the weak point mentioned above. So the purpose of this paper is to consider finding the design parameters which minimize expected loss costs for unit process time and measure the performance of VSSI(variable sample size and sampling interval) $\bar{X}$ chart. It is important that assignable causes be detected to maintain the process controlled. This paper has been studied under the assumption that one cycle is from starting of the process to eliminating the assignable causes in the process. The other purpose of this article is to represent the expected loss costs in one cycle with three process parameters(sample size, sampling interval and control limits) function and find the three parameters.