• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.105-112
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• 1998

In this paper, several bandwidth sampling methods were compared using experimental result in which contains "multi-order sampling", which was proposed for envelope detections in RF ultrasonic signals. A "Quadrature sampling method" and "Second-order sampling method" were compared with it. The resultant image of second-order sampling method introduces too much error as compared with the result of quadrature sampling. But Multi-order sampling method, specialy 5-th sampling method showed quite good envelope detection property. This means that more economical and quite good performance digital beamforming system can be built by adopting this multi-order sampling method.s multi-order sampling method.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.161-168
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• 1996

This paper describes a sampling method, which can be used instead of the simple random sampling without replacement(SRSWOR). This method, circular sampling, assumes that the sampling units of the population are arranged in circular format, and randomly selects as many as samples of contiguous units. Therefore this method gathers information quicker and easier than STSWOR. In certain circumstances, the reliability of this method is better than that of STSWOR. And of circular sampling would be applied to nonprobability could be determined. methods, the reliability of the sample results in terms of probability could be determined.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.459-469
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• 1998

Balanced half sample method is a simple variance estimation method for complex sampling designs. Since it is simple and flexible, it has been widely used in large scale sample surveys. However, the usual BHS method overestimate the true variance in without replacement sampling and two-stage cluster sampling. Focusing on this point , we proposed an unbiased BHS variance estimator in a stratified two-stage cluster sampling and then described an implementation method of the proposed estimator. Finally, partially BHS design is explained as a tool of reducing the number of replications of the proposed estimator.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.563-566
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• 1997

In this paper, several bandwidth sampling methods were compared in which contains "multi-order sampling", which was proposed or envelope detections in RF ultrasonic signals by a computer simulation and on experiment quadrature sampling method. The second-order sampling method were compared with it. As a conclusion, a multi-order sampling method, especially 5th order sampling method showed quite good envelope detection property. This means that more economical and quite good performance digital beamforming system can be built by adopting this new bandwidth sampling method.

• Journal of Korean Society of Forest Science
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• v.18 no.1
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• pp.1-7
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• 1973

This survey was estimated under the ratio estimate such as single class method, simple random sampling method, compound ratio sampling method, separate ratio sampling method and average tree sampling method artificial forest pitch pine volume. The following results were realized by the ratio estimates. At the above table simple random sampling method and compound ratio sampling method are the only ones which is included the actual stand volume in the ratio estimatedstand volume. It is thought that the sampling was in a such good result was because of stand structual stands were simple forest. The most simple measurement and calcuation on the stand volume estimates, in order, would be (1) single class method, (2) simple random sampling method (3) average tree method (4) separate ratio sampling method and compound ratio sampling method, and at the planted evenaged forest the method has realized the best results in obtaining good accuracy and the measure stand volume with least time, expenses and labor in considerably.

• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.179-187
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• 2024

In the Quality Control and inspection processes, the use of attribute sampling strategies is crucial. In this study, we incorporate the neutrosophic fuzzy acceptance sampling plan method to present a fresh approach to attribute sampling plans. Utilizing the benefits of neutrosophic fuzzy sets, the proposed sampling plan method models and assesses the acceptance standards for attribute sampling. We compare the suggested method to already-in-use attribute sampling techniques plans with new attribute six sigma sampling techniques plan is proposed in order to verified its efficacy. The outcomes show the neutrosophic fuzzy acceptance sampling plan's superiority in terms of its capacity to manage uncertainties, account for ambiguity, and produce more precise quality evaluation outputs.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.291-299
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• 2020

The purpose of this study was to propose the most cost-effective sampling method, by analyzing the cost of forest resource investigation per sampling method for the planned harvesting area of in Chunyang-myeon, Byeonghwa-gun, Gyeongsangbuk-do, Korea. For this study, three sampling methods were selected: random sampling method, systematic sampling method, and line transect method. For each method, sample size, hourly wage, number of sample points, survey time, travel time, the sample error rate of the estimated average volume, and the desired sampling error rate were used to calculate the cost of forest resource inventories. Thus, 10 sampling points were extracted for each sampling method, and the factors required for cost analysis were calculated via a field survey. As a result, the field survey cost per ha using the random sampling method was found to be have the lowest cost, regardless of the desired sampling error rate, followed by the systematic sampling method, and the line transect method.

• International Journal of Concrete Structures and Materials
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• v.18 no.2E
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• pp.89-95
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• 2006

This paper proposes a modified method of Latin Hypercube sampling to reduce the variance of statistical parameters in uncertainty analysis of concrete structures. The proposed method is a modification of Latin Hypercube sampling method. This analysis method uses specifically modified tables of random permutations of ranked numbers. In addition, the Spearman coefficient is used to make modified tables. Numerical analysis is carried out to predict the uncertainty of axial shortening in prestressed concrete bridge. Statistical parameters obtained from modified Latin Hypercube sampling method and conventional Latin Hypercube sampling method are compared and evaluated by a numeric analysis. The results show that the proposed method results in a decrease in the variance of statistical parameters. This indicates the method is efficient and effective in the uncertainty analysis of complex structural system such as prestressed concrete bridges.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.818-825
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• 2016

Network management and anomaly detection are challenges in high-speed networks due to the high volume of packets that has to be analysed. Flow-based analysis is a scalable method which reduces the high volume of network traffic by dividing it into flows. As sampling methods are extensively used in flow generators such as NetFlow, the impact of sampling on the performance of flow-based analysis needs to be investigated. Monitoring using sampled traffic is a well-studied research area, however, the impact of sampling on flow-based anomaly detection is a poorly researched area. This paper investigates flow sampling methods and shows that these methods have negative impact on flow-based anomaly detection. Therefore, we propose an efficient probabilistic flow sampling method that can preserve flow traffic distribution. The proposed sampling method takes into account two flow features: Destination IP address and octet. The destination IP addresses are sampled based on the number of received bytes. Our method provides efficient sampled traffic which has the required traffic features for both flow-based anomaly detection and monitoring. The proposed sampling method is evaluated using a number of generated flow-based datasets. The results show improvement in preserved malicious flows.

• 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.