• Communications for Statistical Applications and Methods
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• v.31 no.4
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• pp.427-440
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• 2024

The problem addressed is that of sequentially estimating the difference between the means of two populations with respect to the squared error loss, where each population distribution is a member of the one-parameter exponential family. A Bayesian approach is adopted in which the population means are estimated by the posterior means at each stage of the sampling process and the prior distributions are not specified but have twice continuously differentiable density functions. The main result determines an asymptotic second-order lower bound, as t → ∞, for the Bayes risk of a sequential procedure that takes M observations from the first population and t - M from the second population, where M is determined according to a sequential design, and t denotes the total number of observations sampled from both populations.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.139-147
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• 2014

We address the problem of corrective control for two asynchronous sequential machines in parallel connection. Each asynchronous machine receives the same external input and shows independent state transition characteristics. We propose a novel control scheme in which only one corrective controller is employed so as to make the closed-loop system of each machine match the behavior of the corresponding reference model. Compared with the former method utilizing two corrective controllers, our scheme can reduce the controller size and computational load in controller design. We present the existence condition and design procedure for a state-feedback corrective controller under the assumption that the controlled machines are of input/state type. The design procedure for the proposed controller is described in an illustrative example.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.699-706
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• 2016

Outlier detection methods without performing a test often do not succeed in detecting multiple outliers because they are structurally vulnerable to a masking effect or a swamping effect. This paper considers testing procedures supplemented to a clustering-based method of identifying the group with a minority of the observations as outliers. One of general steps is performing a variety of t-test on individual outlier-candidates. This paper proposes a sequential procedure for searching for outliers by changing cutoff values on a cluster tree and performing a test on a set of outlier-candidates. The proposed method is illustrated and compared to existing methods by an example and Monte Carlo studies.

• Korea-Australia Rheology Journal
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• v.12 no.1
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• pp.83-92
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• 2000

In resin transfer molding (RTM) process, preplaced fiber mat is set up in a mold and thermoset resin is injected into the mold. An important interest in RTM process is to minimize cycle time without sacrificing part quality or increasing cost. In this study, the numerical simulation and optimization process in filling stage were conducted in order to determine the optimum gate locations. Control volume finite element method (CVFEM) was used in this numerical analysis with the coordinate transformation method to analyze the complex 3-dimensional structure. Experiments were performed to monitor the flow front to validate simulation results. The results of numerical simulation predicted well the experimental results with every single, simultaneous and sequential injection procedure. We performed the optimization analysis for the sequential injection procedure to minimize fill time. The complex geometry of an automobile bumper core was chosen. Genetic algorithm was used in order to determine the optimum gate locations with regard to 3-step sequential injection case. These results could provide the information of the optimum gate locations in each injection step and could predict fill time and flow front.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.193-201
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• 2023

In this paper, we consider the maximum scatter traveling salesman problem (MSTSP), a travelling salesman problem (TSP) variant. The problem aims to maximize the minimum length edge in a salesman's tour that travels each city only once in a network. It is a very complicated NP-hard problem, and hence, exact solutions can be found for small sized problems only. For large-sized problems, heuristic algorithms must be applied, and genetic algorithms (GAs) are found to be very successfully to deal with such problems. So, this paper develops a hybrid GA (HGA) for solving the problem. Our proposed HGA uses sequential sampling algorithm along with 2-opt search for initial population generation, sequential constructive crossover, adaptive mutation, randomly selected one of three local search approaches, and the partially mapped crossover along with swap mutation for perturbation procedure to find better quality solution to the MSTSP. Finally, the suggested HGA is compared with a state-of-art algorithm by solving some TSPLIB symmetric instances of many sizes. Our computational experience reveals that the suggested HGA is better. Further, we provide solutions to some asymmetric TSPLIB instances of many sizes.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.14-14
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• 2003

Given a sequence ｛ $X_{n}$｝ of independent and identically distributed random variables with F, a sequential procedure for the p-th quantile ξ$_{P}$= $F^{-1}$ (P), 0$\beta$-protection. Some asymptotic properties for the proposed procedure and of an involved stopping time are proved: asymptotic consistency, asymptotic efficiency and asymptotic normality. From one of the results an effect of smoothing based on kernel functions is discussed. The results are also extended to the contaminated case.e.e.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.8-20
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• 1999

In this paper, a design and estimation procedure for the stochastically dependent nonstationary multiple acceptance sampling plans is developed. At first, the rough-cut acceptance and rejection numbers are given as an initial solution from the corresponding sequential sampling plan. A Monte-Carlo algorithm is used to find the acceptance and rejection probabilities of a lot. The conditional probability formula for a sample path is found. The acceptance and rejection probabilities are found when a decision boundary is given. Several decision criteria and the design procedure to select optimal plans are suggested. The formula for measuring performance of these sampling plans is developed. Type I and II error probabilities are also estimated. As a special case, by setting the stage size as 1 in a dependent sampling plan, a sequential sampling plan satisfying type I and II error probabilities is more accurate and a smaller average sample number can be found. In a numerical example, a Polya dependent process is examined. The sampling performances are shown to compare the selection scheme and the effect of the change of the dependency factor.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.673-685
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• 2003

In this paper we consider the problem of identifying and testing outliers in linear regression. First we consider the problem for testing the null hypothesis of no outliers. A test based on the ratio of two residual scale estimates is proposed. We show the asymptotic distribution of the test statistics by Monte Carlo simulation and investigate its properties. Next we consider the problem of identifying the outliers. A forward sequential procedure using the suggested test is proposed and shown to perform fairly well. Unlike other forward procedures, the present one is unaffected by masking and swamping effects because the test statistic is based on robust scale estimate.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.3
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• pp.213-223
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• 2001

This paper presents an analytical procedure for the time-dependent analysis of the multi-story prestressed concrete structure under the construction stage. To account for the actual structural behavior, the procedure considers the effects due to the construction interval and the time-dependent losses of prestress at every construction step on the entire structural response. A numerical study is performed to demonstrate the general validity of the approach and to quantitatively evaluate the effects resulted from the time-dependent behaviors during construction. Recommendations and conclusions are developed by comparisons with structural responses using the present and conventional methods of analysis. The comparative results show that both effects of sequential construction and time-dependent prestress losses should be considered for the construction stage analysis.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.334-337
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• 2006

This paper considers the problem of selecting the most profitable process mean for production processes where measurement errors exist in inspection systems. For such situations, a sequential inspection procedure is proposed to reduce measurement errors. The decision to accept, reject, or take an additional inspection of an item is made at every measurement point until the number of repeated measurements reaches its upper bound. An expected profit model is constructed and the optimal process mean, the cut-off values, and the upper bound of the number of repeated measurements are obtained when accepted(rejected) items are sold at regular(reduced) price. A numerical study is performed to investigate the performance of the proposed procedure.