• Korean journal of applied entomology
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• v.54 no.3
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• pp.159-167
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• 2015

In order to establish B. tabaci control in paprika greenhouses a fixed-precision-level sampling plan was developed. The sampling plan consisted of spatial distribution analysis, a sampling stop line, and decision making. Sampling was conducted simultaneously in two independent greenhouses (GH 1, GH 2). GH 1 and 2 were surveyed every week for 22 consecutive weeks, using 19 sampling locations in GH 1 and 9 sampling locations in GH 2. The plant in both greenhouses were divided into top (180-220 cm from the ground), middle (80-120 cm from the ground) and bottom (30-70 cm from the ground) sections and B. tabaci adults and pupae were observed on three paprika leaves at each position and recorded separately. GH 2 data were used to validate the fixed-precision sampling plan, which was developed using GH 1 data. In this study, spatial distribution analysis was performed using Taylor's power law with the pooled data of the top and bottom position (B. tabaci adults), and the middle and bottom positions (B. tabaci pupae), based on a 1-leaf sampling unit. Decision making was undertaken using the maximum of action threshold in accordance with previously published method, and the value was decided by the price of the plants. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated a reasonable level of precision.

• Journal of Korean Society for Quality Management
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• v.7 no.2
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• pp.17-21
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• 1979

There are many kinds of the mathematical models which are developed for choosing the economic inspection plan. The aim of this paper is to classify these mathematical models, and to examine their characteristics. The mathematical models for choosing the economic inspection plan can be classified into three groups. The first of it is the break-even analysis, the second group of the model is to choose the inspection plan so as to minimize total sampling inspection cost function, and the third group of it is the model to choose the inspection plan which maximize the profit function of the sampling inspection. As a result of examining the characteristics of this classified group of the models the model to choose the inspection plan which minimize total sampling inspection cost is more economical than the other models.

• Journal of Korean Society for Quality Management
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• v.8 no.2
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• pp.15-22
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• 1980

This paper deals with the problem of determining a minimum cost sampling inspection plan for a single destructive testing by attribute. The cost for inspection lot is constructed by following three cost factors: (1) cost of inspection, (2) cost of accepted defective, (3) cost of rejected lot Using Hald's Bayesian approach in a single non-destructive testing, procedure's for finding the minimum cost single destructive sampling inspection plan by attribute are given. Assuming the uniform distribution as a prior-distribution and using numerical analysis by computer, a minimum cost single destructive sampling inspection plan by attribute for several lot sizes, unit cost, destructive testing cost, and salvage cost is given.

• Korean Journal of Environmental Biology
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• v.35 no.4
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• pp.427-436
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• 2017

A fixed-precision-level sampling plan was developed to establish control of the two-spotted spider mite, Tetranychus urticae, in two strawberry greenhouses (conventional plot, natural enemy plot). T. urticae was sampled by taking a three-leaflet leaf (1 stalk) from each plant (3 three-leaflet leaves) from each sampling position. Each leaflet was divided into three different units (1-leaflet, 2-leaflet, and 3-leaflet units) to compare relative net precision (RNP) values for selection of the appropriate sampling unit. The relative net precision values indicated that a 1-leaflet unit was more precise and cost-efficient than other units. The spatial distribution analysis was performed using Taylor's power law (TPL). Homogeneity of the TPL parameters in each greenhouse was evaluated by using the analysis of covariance (ANCOVA). A fixed-precision-level sequential sampling plan was developed using the parameters of TPL generated from the combined data of the conventional plot and natural enemy plot in a 1-leaflet sampling unit. Sequential classification sampling plans were also developed using the action threshold of 3 and 10 mites for pooled data. Using the results obtained in the independent data, simulated validation of the developed sampling plan by Resampling validation for sampling plan (RVSP) indicated a reasonable level of precision.

• Korean journal of applied entomology
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• v.62 no.4
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• pp.299-305
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• 2023

Bemisia tabaci is one of polyphagous insect pests that transmits Tomato Yellow Leaf Curl Virus (TYLCV) and Cassava Brown Streak Disease (CBSD). Insecticides are primarily applied to control B. tabaci, but it has limits due to the development of resistance. As a result, a fixed precision sampling plan was developed for its integrated pest management (IPM). The tomato plants were divided into top (more than 130cm from the ground), middle (70 cm to 100 cm above the ground), and bottom (50 cm or less above the ground) strata, before visual sampling of the larvae of B. tabaci. The spatial distribution analysis was conducted using Taylor's power law coefficients with pooled data of top, middle, bottom strata. Fixed precision sampling plan and control decision-making were developed with precision levels and action threshold recommended from published scientific papers. To assess the validation of the developed sampling plans, independent data not used in the analysis were evaluated using the Resampling Validation for Sampling Plan (RVSP) program.

• Journal of Radiation Industry
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• v.18 no.1
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• pp.15-21
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• 2024

The Non-Proliferation Treaty (NPT) is the basis of global efforts to prevent the spread of nuclear weapons. In Republic of Korea, safety measures are integrated with NPT approval through agreements with the International Atomic Energy Agency (IAEA) and the Safeguards Agreement. In contrast, Democratic People's Republic of Korea (DPRK), initially an NPT member, withdrew, refusing IAEA nuclear inspections. This inhibits the precise management of DPRK's nuclear facilities and limits access to related information. The Korean Peninsula, politically divided, sees DPRK in control of nuclear weapons. Although the IAEA periodically evaluates DPRK's nuclear facilities, there's a research gap in contamination and site management with nuclear activities. Recognizing the presence or absence of such activities is crucial for peaceful nuclear endeavors. This proposal suggests the number and locations for environmental sample collection using the Visual Sample Plan (VSP) software for nuclear activity analysis. VSP software is sample collection locations and quantities through statistical tests on collected data, ensuring reliability for decision-making. The proposal identifies sites and facilities for nuclear activity analysis based on IAEA safety reports, utilizing the software's embedded methods. Suggested sampling locations for undisclosed nuclear activities employ VSP's embedded techniques, including 'Show that at least some high % of the sampling area is acceptable' to confirm contamination and 'Estimate the Mean' to evaluate the average contamination level.

• Journal of Korean Society for Quality Management
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• v.13 no.2
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• pp.48-55
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• 1985

This paper intends to decide the optimum OC curves and to find the minimized ${\alpha}$, ${\beta}$-risk based upon the Linear Cost Model (L.C.M.) for the destructive or nondestructive acceptance sampling inspection plan. For the solution from the L.C.M., we assume the uniform distribution as a Prior-distribution and use numerical analysis by computer.

• Korean journal of applied entomology
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• v.40 no.2
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• pp.105-109
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• 2001

Dispersion pattern of the citrus red mite (CRM), Panonychus citri (McGregor) was determined to develop a monitoring method in the satsuma mandarin fields, Citrus unshiu L., in Jeju-do, during 1999 and 2000. CRM population was sampled by collecting leaves. Taylor's power law provided better description of mean-variance relationship for the dispersion indices compared to Iwao's patchiness regression. Slopes and intercepts of Taylor's power law from leaf samples did not differ among surveyed groves. Fixed-precision levels (D) of a sequential sampling plan were developed using Taylor's power law parameters generated from all motile stages of CRM in leaf sample. This sampling plan for leaf sample estimate was tested with resampling validation for sampling plan using 4 independent data sets. Resampling simulation analysis demonstrated that actual fixed-precision level values were better than desired D values of 0.20, 0.25 and 0.30. Required numbers for tree sampling at the density of more than 7 mites per tree were fewer than 18.

• IE interfaces
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• v.16 no.3
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• pp.344-351
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• 2003

Critical dimension is one of the most important characteristics of up-to-date integrated circuit devices. Hence, critical dimension control in a semiconductor wafer fabrication process is inevitable in order to achieve optimum device yield as well as electrically specified functions. Currently, in complex semiconductor wafer fabrication processes, statistical methodologies such as Shewhart-type control charts become crucial tools for practitioners. Meanwhile, given a critical dimension sampling plan, the analysis of variance technique can be more effective to investigating critical dimension variation, especially for on-chip and on-wafer variation. In this paper, relating to a typical sampling plan, linear statistical models are presented for the analysis of critical dimension variation. A case study is illustrated regarding a semiconductor wafer fabrication process.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.414-422
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• 2022

Presented in this paper is a methodology for combining a Bayesian statistical approach with Data Quality Objectives (a structured decision-making method) to provide increased levels of confidence in analytical data when approaching a waste boundary. Development of sampling and analysis plans for the characterisation of radioactive waste often use a simple, one pass statistical approach as underpinning for the sampling schedule. Using a Bayesian statistical approach introduces the concept of Prior information giving an adaptive sample strategy based on previous knowledge. This aligns more closely with the iterative approach demanded of the most commonly used structured decision-making tool in this area (Data Quality Objectives) and the potential to provide a more fully underpinned justification than the more traditional statistical approach. The approach described has been developed in a UK regulatory context but is translated to a waste stream from the Fukushima Daiichi Nuclear Power Station to demonstrate how the methodology can be applied in this context to support decision making regarding the ultimate disposal option for radioactive waste in a more global context.