• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.825-836
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• 2019

One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.247-256
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• 2003

In this study, we systemize the theoretical validity for applying RRM to three-stage cluster sampling method and derive the estimate and it's variance of sensitive parameter. We derive the minimum variance form under the optimal values of the subsample sizes when the costs are fixed. Under the some given precision, we obtain the optimal values of the subsample sizes and derive the minimum cost form by using them. We apply the three-stage cluster RRM to field survey and suggest some necessary points for practical use.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.895-900
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• 2023

We study low-complexity graph sampling which selects a subset of nodes from graph nodes so as to reconstruct the original signal from the sampled one. To achieve complexity reduction, we propose a graph sampling algorithm with thresholding which selects a node with a cost lower than a given threshold at each step without fully searching all of the remaining nodes to find one with the minimum cost. Since it is important to find the threshold as close to a minimum cost as possible to avoid degradation of the reconstruction performance, we present a mathematical expression to compute the threshold at each step. We investigate the performance of the different sampling methods for various graphs, showing that the proposed algorithm runs 1.3 times faster than the previous method while maintaining the reconstruction performance.

• Geomechanics and Engineering
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• v.7 no.5
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• pp.525-537
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• 2014

The typical design of ground improvement with prefabricated vertical drains (PVD) and surcharge preloading involves a series of deterministic analyses using averaged or mean soil properties for the various combination of the PVD spacing and surcharge preloading height that would meet the criteria for minimum consolidation time and required degree of consolidation. The optimum design combination is then selected in which the total cost of ground improvement is a minimum. Considering the variability and uncertainties of the soil consolidation parameters, as well as considering the effects of soil disturbance (smear zone) and drain resistance in the analysis, this study presents a stochastic cost optimization of ground improvement with PVD and surcharge preloading. Direct Monte Carlo (MC) simulation and importance sampling (IS) technique is used in the stochastic analysis by limiting the sampled random soil parameters within the range from a minimum to maximum value while considering their statistical distribution. The method has been verified in a case study of PVD improved ground with preloading, in which average results of the stochastic analysis showed a good agreement with field monitoring data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2505-2510
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• 2009

Semiconductor processes need measurement to confirm where there are problems in quality after progresses manufacturing process. This paper suggests equipment and automatic measure sampling method that control monitoring ratio according to change point occurrence availability of process that is not measure method by the existent simple ratio rate. This paper defines measure section as ailment section, metastable section and stability section by change point standard and create statistical model of each section and developed suitable measure rate model by section. As a result, we have accomplished maximum throughput and minimum sampling number that needs to maintain constant level of quality. Proposed method minimizes load of measure process by brings production quality sophistication and decrease of process badness and lowers measure rate in stable section making perception about problem occurrence quick heightening measure rate at change point occurrence.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.41-48
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• 2016

In this manuscript, a modified single sampling plan is proposed for the inspection of products in which the nonconforming items can be classified in to two categories namely critical and non-critical; and explained with the help of industrial example. The operating procedure of this plan is also proposed and the performance measures such as the probability of acceptance, average sample number, average total inspection and average out going quality are also derived. The optimal parameters are determined which will have minimum sample size. The efficiency of the proposed plan is also discussed over the conventional single sampling plan. The extensive tables for selecting a modified single sampling plan based on AQL and LQL are provided for both Binomial and Poisson distributions and explained with the help of industrial data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.1097-1106
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• 1997

Most works on importance sampling (IS) as an efficient evaluation technique havd been done in an additibe white gaussian noise channel (Awgn). In this paper we propose a CQ(conventional importance sampling and quasi-translantion) IS technique for the mobile radio channel modeled as Rician fading, and analyze the IS estimator's variance to determine optimum IS parameters and the minimum number of run times. Reference showed that CIS technique has a poor performance for systems with meories, but it is shown that the CIS technique can be improved by combining with quasi-translation technique even for systems with memories. Here the CQ IS technique modifies the variance of additive noise and also performs quasi-translation for the fading distribution. We determine the optimum IS parameters of the proposed CQ IS estimator and whow that the simulation gains are about 10$^{3}$~10$^{6}$ for the mobile communication systems with memories in case of the expected BERs 10$^{-5}$ ~10$^{-8}$ .

• Journal of Radiation Protection and Research
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• v.40 no.3
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• pp.181-186
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• 2015

Measurement of xenon radioisotopes from nuclear fission is a key element for monitoring underground nuclear weapon tests. $^{131m}Xe$, $^{133}Xe$, $^{133}mXe$ and $^{135}Xe$ in the air can be detected via low background systems such as a beta-gamma coincidence counting system. Radioxenon monitoring is performed through air sampling, xenon extraction, measurement and spectrum analysis. The minimum detectable concentration of $^{135}Xe$ can be significantly variable depending on the sampling time, extraction time and data acquisition time due to its short half-life. In order to optimize the acquisition time with respect to certain experimental parameters such as sampling and xenon extraction, theoretical approach and experiment using SAUNA system were performed to determine the time to minimize the minimum detectable concentration, which the results were discussed.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.371-374
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• 1990

This paper presents the speed control of dc motor based on deadbeat response. The deadbeat response is that the output reaches the final value in the minimum possible settling time and stays there. This results demonstrate that the output reaches final value in one sampling time for the unsaturated region, and in one sampling time after getting free from the saturation state for the saturated region.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.147-156
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• 1997

This Study deals with the problem of determining a minimum cost sampling inspection plan for destructive testing by attribute. The linear cost model(LCM) is constructed under the assumption that unit cost, destructive testing cost, producer's risk cost, consumer's risk cost are given. For the solution from the LCM, we assumed the uniform distribution as a prior distribution.