• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.265-278
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• 1998

In this paper, we suggest two-phase adaptive cluster sampling schemes. The main feature of the two-phase sampling is that the information collected in the first phase sample is utilized in the selection of the second phase sample. The conventional two-phase sampling is, however, not sufficient to increase efficiency when the population of interest is rare and clustered. In the proposed sampling scheme, the first phase sample is selected with adaptive cluster sampling procedure and the second phase sample is selected by PPSWR and $\pi$PS sampling. We investigate unbiased estimators of population total and their variance for the proposed sampling schemes respectively. Finally we compare these suggested sampling schemes using numerical examples .

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.181-189
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• 2005

This paper suggest a method of inclusion probability proportional to size sampling that provides a non-negative and stable variance estimator. The sampling procedure is quite simple and flexible since a sampling design is easily obtained using mathematical programming. This scheme appears to be preferable to Nigam, Kumar and Gupta's (1984) method which uses a balanced incomplete block designs. A comparison is made with their method through an example in the literature.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.590-596
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• 2016

Biopsy is a typical needle type intervention procedure performed under radiographic image equipment such as computed tomography (CT) and cone-beam CT. This minimal invasive procedure is a simple and effective way for identifying cancerous condition of a suspicious tissue but radiation exposure for the patients and interventional radiologists is a critical problem. In order to overcome such trouble and improve accuracy in targeting of the needle, there have been various attempts using robot technology. Those devices and systems, however, are not for full procedure automation in biopsy without consideration for tissue sampling task. A robotic end-effector of a master-slave tele-operated needle type intervention robot system has been proposed to perform entire biopsy procedure by the authors. However, motorized sampling adopted in the device has different cutting speed from that of biopsy guns used in the conventional way. This paper presents the design of a novel robotic mechanism and protocol for the automation of biopsy procedure using spring-triggered biopsy gun mechanism. An experimental prototype has been successfully fabricated and shown its feasibility of the automated biopsy sequence.

• Structural Engineering and Mechanics
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• v.92 no.1
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• pp.111-120
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• 2024

Sampling methods are powerful approaches to solving the problems of structural reliability analysis and estimating the failure probability of structures. In this paper, a new sampling method is proposed offering lower variance and lower computational cost for complex and high-dimensional problems. The method is called Optimal Latinized partially stratified sampling (OLPSS) as it is based upon the Latinized Partially Stratified Sampling (LPSS) which itself is based on merging Stratified Sampling (SS) and Latin Hypercube Sampling (LHS) algorithms. While LPSS has a low variance, it may suffer from a lack of good space-filling of its generated samples in some cases. In the OLPSS, this issue has been resolved by employing a new columnwise-pairwise exchange optimization procedure for sample generation. The efficiency of the OLPSS has been tested and reported under several benchmark mathematical functions and structural examples including structures with a large number of variables (e.g., a structure with 67 variables). The proposed method provides highly accurate estimates of the failure probability of structures with a significantly lower variance relative to the Monte Carlo simulations, Latin Hypercube, and standard LPSS.

• Water for future
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• v.29 no.2
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• pp.129-141
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• 1996

A procedure for computing total suspended sediment load is presented based on a single point-integrated sample, a power velocity distribution, and Laursen's sediment concentration distribution equation. The procedure was tested with field data from the Rio Grande River. Computed concentrations agreed well with depth-integrated measurements corrected for unmeasured load using nominal values of $\beta$, $\kappa$ and w. Even better agreement was obtained when site-specific data were used to define the x and z exponents of the velocity and concentration distributions. The difference between total suspended load computed using a single measurement and this procedure and conventional computations based on depthintegrated measurements is well within sampling error. There are major advantages in estimating total suspended load using a single time-integrated suspended-sediment point sample. Less field time is required; sampling costs are greatly reduced; and sampling can be more frequent and better timed to measure the changing sediment load. Single-point sampling makes automatic sampling procedures more feasible.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.22-38
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• 1997

In a traditional sequential acceptance sampling plan, it is assumed that the sampled items are independent each other. In this paper, stochastically dependent sequential acceptance sampling plans are dealt when there exists dependency between sampled items. Monte-Calro algorithm is used to find the acceptance and rejection probabilities of a lot. The number of defectives for the test to be accepted and rejected in probability ratio sequential test can be found by using these probabilities. The formula for measures of performance of these sampling plans is developed. Type I and II error probabilities are estimated by simulation. This research can be a, pp.ied to sequential sampling procedures in place of control charts where there is a recognized and necessary dependency during the production processes. Also, dependent multiple acceptance sampling plans can be derived by extending this sequential sampling procedure. As a numerical example, a Markov dependent process model is given, and the characteristics of the sampling plans are examined according to the change of the dependency factor.

• ETRI Journal
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• v.23 no.3
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• pp.129-137
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• 2001

A random sampling or systematic sampling method is commonly used to assess the accuracy of classification results. In remote sensing, with these sampling methods, much time and tedious work are required to acquire sufficient ground truth data. So, a more effective sampling method that can represent the characteristics of the population is required. In this study, fractal analysis is adopted as an index for reference sampling. The fractal dimensions of the whole study area and the sub-regions are calculated to select sub-regions that have the most similar dimensionality to that of the whole area. Then the whole area's classification accuracy is compared with those of sub-regions, and it is verified that the accuracies of selected sub-regions are similar to that of whole area. A new kind of reference sampling method using the above procedure is proposed. The results show that it is possible to reduce sampling area and sample size, while keeping the same level of accuracy as the existing methods.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.22-32
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• 1992

This thesis compares life test acceptance sampling plans under lifetime has an exponential distribution. Various practical considerations may lead a user adopt a two-stage, or double sampling, test procedure. Hewett and Spurrier(1983) provided a survey of two-stage methods, as well as examples of experiments for which a two-stage procedure would be appropriate. The plans are compared in terms of the expected number of failures, and the expected time required to reach a dicision. Computational experiments are conducted and the results are tabulated to provide guidelines for selecting an appropriate plan for a given situation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.101-112
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• 1998

Recently, researchers show growing interest on product quality characteristic dependence and designing acceptance sampling plans under the quality dependence. This research intends to resolve a few theoretical and practical questions for better application of acceptance sampling when the quality characteristic of product items exhibits a statistical dependence and samples are inspected according to the production order. In this research, a mathematical programming model is developed for the economic modeling of sampling plans based on two evaluation criteria : the average outgoing quality(AOQ) and the average total inspection cost. An efficient solution procedure is then proposed using the functional structure of the two evaluation criteria and the procedure is numerically illustrated.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.761-770
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• 1999

A combination procedure of successive occasions sampling and randomized response method is investigated. Randomized response technique is very simple for use in a telephone survey of a sensitive subject. In the suggested randomized response method. the interviewee replies "yes" or "no" to a randomly selected question and the investigator can estimate the proportion of "yes" or "no" answer. When this procedure is used on successive occasions, not only the proportion supporting a candidate and the time change in this supporting proportion can be derived but also the voters' swing in the trend of voters' support can be estimated. A numerical example is given to show how the suggested sampling strategy can be applied to a practical telephone survey.