• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1109-1115
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• 2010

In this paper, exact confidence interval of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the performance of exact confidence interval estimates of hypergeometric parameter in terms of actual coverage probability by small sample Monte Carlo simulation.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1103-1111
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• 2000

The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.783-792
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• 2007

We consider estimation of reliability P(Y

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2345-2352
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• 1998

The hyper-geometric distribution software reliability growth model was recently developed and successfully applied Due to mathematical difficultv of the maximum likclihmd method, the least squares method has hem suggested for parameter estimation by the previous studies. We first summarize and compare the minimization criteria adopted by the previous studies. It is theo shown that the weighted least squares method is more appropriate hecause of the nonhomogeneous variability of the number of newly detected faults. The adequacy of the weighted least squares method is illustrated by two numerical examples. Finally, we propose a new method fur predicting the number of faults newly discovered by next test instances. The new prediction method can be used for determining the time to stop testing.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.115-120
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• 2015

Evaluating product quality level is necessary before the manufactured items are delivered to the customer. When the amount of the items to be manufactured is limited and the product is of high price and should be evaluated by destructive testing, the number of samples to be tested should be as small as possible. This paper presents a small-sample inspection method using hyper-geometric distribution and Bayesian approach for finite small-sized population. A method of determining the minimum sample size is presented for given population size, allowable number of defectives, warranteed defective level, and confidence level which is the degree of confidence on the product quality level recognized by both the producer and the customer.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2343-2349
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• 1999

The hyper-geometric distribution software reliability growth model (HGDM) was recently developed and successfully applied to real data sets. The HGDM considers the sensitivity factor as a parameter to be estimated. In order to reflect the random behavior of the test-and-debug process, this paper generalizes the HGDM by assuming that the sensitivity factor is a binomial random variable. Such a generalization enables us to easily understand the statistical characteristics of the HGDM. It is shown that the least squares method produces the identical results for both the HGDM and the generalized HGDM. Methods for computing the maximum likelihood estimates and predicting the future outcomes are also presented.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1175-1182
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• 2011

In this paper, properties of exact confidence interval and some approximate confidence intervals of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the approximation of hypergeometirc distribution to the binomial and normal distribution respectively. Approximate confidence intervals based on these approximation are also adequately discussed. The performance of exact confidence interval estimates and approximate confidence intervals of hypergeometric parameter is compared in terms of actual coverage probability by small sample Monte Carlo simulation.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.205-212
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• 2003

This paper may provide a basic design data for the safer car seat mechanism and the quality of the material used by finding out the passenger's dynamic behavior when protected by seat belt during collision. A computer simulation with finite element method is used to accomplish this objective. At first, a detailed geometric model of the seat is constructed using CAD program. The formation of a finite element from a geometric data of the seat is carried out using Hyper-Mesh that is the commercial software for mesh generation and post processing. In addition to seat modeling, the finite element model of seat belt and dummy is formed using the same software. Rear impact analysis is accomplished using Pam-Crash with crash pulse. The part of the recliner and right frame is under big stress in rear crash analysis because the acceleration force is exerted on the back of the seat by dummy. The stress condition of the part of the bracket is checked as well because it is considered as an important variable on the seat design. Front impact model which including dummy and seal belt is analyzed. A Part of anchor buckle of seat frame has high stress distribution because of retraction force due to forward motion of dummy at the moment of collision. On the basis of the analysis result, remodeling and reanalysis works had been repeatedly done until a satisfactory result is obtained.

• The Journal of Korean Academy of Prosthodontics
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• v.43 no.6
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• pp.727-735
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• 2005

Statement of problem. Platform switching in implant prosthesis has been used for esthetic and biological purpose. But there are few reports for this concept. Purpose. The purpose of this study is evaluation of platform switching in wide implant by three dimensional finite element analysis. Materials and Methods. The single implant and prosthesis was modeled in accordance with the geometric designs for Osstem implant system. Three-dimensional finite element models were developed for (1) a wide diameter 3i type titanium implant 5 mm in diameter, 13 mm in length with wide cemented abutment, titanium alloy abutment screw, and prosthesis (2) a wide diameter 3i type titanium implant 5 mm in diameter, 13 mm in length with regular cemented abutment, titanium alloy abutment screw and prosthesis(platform switching) was made for finite element analysis. The abutment screws were subjected to a tightening torque of 30 Ncm. The amount of preload was hypothesized to 650N, and round and flat type prostheses were loaded to 200 N. Four loading offset point (0, 2, 4, 6 mm from the center of the implants) were evaluated. Models were processed by the software programs HyperMesh and ANSA. The PAM-CRASH 2G simulation software was used for analysis of stress. The PAM-VIEW and HyperView were used for post processing. Results. The results from experiment were as follows; 1. von Mises stress value is increased in order of bone, abutment, implant and abutment screw. 2. von Mises stress of abutment screw is lower when platform switching. 3. von Mises stress of implant is lower when platform switching until loading offset 4 mm. 4. von Mises stress of abutment is similar between each other. 5. von Mises stress of bone is slightly higher when platform switching. Conclusion. The von Mises stress pattern of implant components is favor when platform switch ing but slightly higher in bone stress distribution than use of wide abutment. The research about stress distribution is essential for investigation of the cortical bone loss.

• Survey Research
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• v.12 no.1
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• pp.141-152
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• 2011

During major elections, three terrestrial broadcasting stations in Korea have covered the progresses of election results by announcing the simple sum of ballot counts of all ballot counting stations. The current approach, however, does not properly reflect the actual ballot count differences by ballot counting location, leading to cause unnecessary but possible confusions. In addition, the current coverage approach restricts the broadcasters from using regional poll data gained through exit polls by letting them to use the significant information on a one-off purpose to announce the initial prediction of the poll results and to fully disregard the exit poll results during the ballot counting process. Based on the understanding, this paper is designed to suggest a Bayesian approach to consolidate the exit poll results with the progressive ballot counting results and announce them as such. The suggested consolidation approach is expected to mitigate or avoid the possible confusions that may arise in connection with the different ballot counting paces by ballot counting station.