• International Journal of Reliability and Applications
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• 제15권2호
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• pp.77-84
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• 2014

In this paper, a optimal designing methodology is proposed to determine the parameters for skip-lot sampling plan of type SkSP-2 plan with double sampling plan as reference plan, when the lifetime of the product follows generalized exponential distribution. The two points on the operating characteristic curve approach are used to find the optimal parameters for the proposed plan. The plan parameters are determined so as to minimize the average sample number subject to satisfying simultaneously both producer and consumer risks at the acceptable and limiting quality levels respectively.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 춘계학술발표회논문집(3)
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• pp.193-198
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• 1996

The effect of dynamic strain aging (DSA) on the leak-before-break (LBB) analysis was estimated through the evaluation of leakage-size-crack and flaw stability in SA106 Gr.C piping steel. Also. the results were represented as a form of "LBB allowable load window". In the DSA temperature region. the leakage-size-crack length was smaller than that at other temperatures and it increased with increasing tensile strain rate. In the results of flaw stability analysis. the lowest instability load appeared at the temperature corresponding to minimum J- R curve which was caused by DSA. The instability load near the plant operating temperature depended on the loading rate of J-R data. and decreased with increasing tensile strain rate. These are due to the strain hardening characteristic and strain rate sensitivity of DSA. In the "LBB allowable load window". LBB allowable region was the narrowest at the temperature and loading conditions where DSA occurs.

• 품질경영학회지
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• 제19권2호
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• pp.63-77
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• 1991

Currently the problem of air pollution caused by the motor vehicle emission is one of the most serious problems to be solved. Thus we needed the inspection method and technical innovation constraining the motor vehicle emission. In order to establish the more reasonable certified test, the multivariate sequential rectifying inspection plan designed in this paper has been applied to the domestic vehicles by analyzing the statistic characteristics of the emission distribution. This inspection method is designed to satisfy the evaluation measure constraining domestic vehicle emission, and it serves the defect rectifying system and performance certification of catalytic converts. As the prior parameter for the domestic vehicles, we used the data for the catalytic converts which passed the certified test excuted by the EPK. For the case of engine test, we used those data which passed the certified test of domestic vehicles. The multivariate sequential rectifying inspection plan of the vector parameter is able to minimize the average sample number and increase the pass probability of operating characteristic curve.

• Communications for Statistical Applications and Methods
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• 제25권3호
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• pp.307-319
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• 2018

High-throughput technologies enable the simultaneous evaluation of thousands of genes that could discriminate different subclasses of complex diseases. Ranking genes according to differential expression is an important screening step for follow-up analysis. Many statistical measures have been proposed for this purpose. A good ranked list should provide a stable rank (at least for top-ranked gene), and the top ranked genes should have a high power in differentiating different disease status. However, there is a lack of emphasis in the literature on ranking genes based on these two criteria simultaneously. To achieve the above two criteria simultaneously, we proposed to apply a previously reported metric, the modified area under the receiver operating characteristic cure, to gene ranking. The proposed ranking method is found to be promising in leading to a stable ranking list and good prediction performances of top ranked genes. The findings are illustrated through studies on both synthesized data and real microarray gene expression data. The proposed method is recommended for ranking genes or other biomarkers for high-dimensional omics studies.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (2)
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• pp.622-624
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• 2002

생체인식 기술은 급속도로 발전하고 있지만 개개의 생체 정보를 이용한 단일 생체인식 기술은 생체 방식에 따라 각각의 문제점이 노출되고 있는 상황이다. 이에 두 가지 이상의 생체 정보를 결합하여 단일 생체인식 기술의 문제점을 극복하고 보다 좋은 인식률을 확보하기 위해 다중 생체인식 시스템(Multi-Modal Bio-metries System)이라는 복합 시스템이 제안 되었다. 이 논문에서는 생체인식 산업의 특성 및 개인 인증 방법으로 사용중인 단일 생체인식 시스템의 문제점을 알아보고 그 해결방안으로 다중 생체인식 시스템의 확률단계(Probability Level)에서 더 좋은 성능을 보여주기 위해 각각의 시스템에 가중치(Weight)를 부여 할 경우, EER(Equal Error Rate)이 단일 생체인식 시스템에 보다 가중치를 부여 했을 때 낮아짐과 동시에 ROC 커브도 (Receiver Operating Characteristic Curve) 좋아짐을 보였다.

• EDISON SW 활용 경진대회 논문집
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• 제4회(2015년)
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• pp.500-509
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• 2015

This paper presents the single objective design optimization of plate-fin heat sink equipped with fan cooling system using Genetic Algorithm. The proper heat sink and fan model are selected based on the previous studies. And the thermal resistance of heat sinks and fan efficiency during operation are calculated according to specific design parameters. The objective function is combination of thermal resistance and fan efficiency which have been taken to measure the performance of the heat sink. And Decision making procedure is suggested considering life time of semiconductor and Fan Operating cost. And also Analytical Model used for optimization is validated by Fluent, Ansys 13.0 and this model give a quite reasonable and reliable design.

• 한국CDE학회지
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• 제21권2호
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• pp.39-49
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• 2015

This paper presents the single objective design optimization of plate-fin heat sink equipped with fan cooling system using Genetic Algorithm. The proper heat sink and fan model are selected based on the previous studies. And the thermal resistance of heat sinks and fan efficiency during operation are calculated according to specific design parameters. The objective function is combination of thermal resistance and fan efficiency which have been taken to measure the performance of the heat sink. And Decision making procedure is suggested considering life time of semiconductor and Fan Operating cost. And also Analytical Model used for optimization is validated by Fluent, Ansys 13.0 and this model give a quite reasonable and reliable design.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• 한국유체기계학회 논문집
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• 제12권4호
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• pp.37-43
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• 2009

In the present study, the flow characteristics of a peristaltic micropump were numerically analyzed. A channel wall motion of the micropump was simulated using a moving mesh technique. A sine wave pattern was assumed to simulate the peristaltic motion of wall. The present numerical method was verified by comparing the result with the available numerical data. The effects of the operating conditions which include the maximum displacement and frequency of the channel wall and the phase difference between top and bottom walls on the flow characteristics were investigated. From these numerical results, the pressure-flowrate characteristic curve was obtained for various maximum displacement and frequencies.

• IEIE Transactions on Smart Processing and Computing
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• 제4권2호
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• pp.103-109
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• 2015

In this paper, a novel method for the classification of term and preterm birth is proposed based on time-frequency analysis of electrohysterogram (EHG) using multivariate empirical mode decomposition (MEMD). EHG is a promising study for preterm birth prediction, because it is low-cost and accurate compared to other preterm birth prediction methods, such as tocodynamometry (TOCO). Previous studies on preterm birth prediction applied prefilterings based on Fourier analysis of an EHG, followed by feature extraction and classification, even though Fourier analysis is suboptimal to biomedical signals, such as EHG, because of its nonlinearity and nonstationarity. Therefore, the proposed method applies prefiltering based on MEMD instead of Fourier-based prefilters before extracting the sample entropy feature and classifying the term and preterm birth groups. For the evaluation, the Physionet term-preterm EHG database was used where the proposed method and Fourier prefiltering-based method were adopted for comparative study. The result showed that the area under curve (AUC) of the receiver operating characteristic (ROC) was increased by 0.0351 when MEMD was used instead of the Fourier-based prefilter.