• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2005.04a
• /
• pp.203-206
• /
• 2005

The objective of study on composite cylinder for alternative fuel vehicle is to develop safe, efficient, and commercially viable, on-board fuel storage system for the fuel cell vehicle or natural gas vehicle that use highly compressed gaseous fuel such as hydrogen or natural gas. This study presents the whole procedure of development and certification of a type 3 composite cylinder of 207bar service pressure and 70 liter water capacity, which includes design/analysis, processing of filament winding, and validation through various testing and evaluation. Design methods of liner configuration and winding patterns are presented. Three dimensional, nonlinear finite element analysis techniques are used to predict burst pressure and failure mode. Design and analysis techniques are verified through burst and cycling tests. The full qualification test methods and results for validation and certification are presented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.05a
• /
• pp.738-742
• /
• 2005

Ground vibration at Gil-dong in Seoul induced by the 5th ling of Seoul Subway is predicted using various prediction methods and compared with measured vibration. Also, several issues on the improvement of prediction methods are discussed. Furthermore, as an alternative vibration source, measured vibration acceleration level(VAL) on the tunnel wall of the Bundang line of Seoul Subway is applied to the prediction of the VAL at the location mentioned previously. Then requirements accompanied to the suggestion of the new vibration source appropriate to the condition of Seoul Subway.

• Journal of the Korean Statistical Society
• /
• v.35 no.2
• /
• pp.167-177
• /
• 2006

An important role of statistical analysis in science is interpreting observed data as evidence, that is 'what do the data say?'. Although standard statistical methods (hypothesis testing, estimation, confidence intervals) are routinely used for this purpose, the theory behind those methods contains no defined concept of evidence and no answer to the basic question 'when is it correct to say that a given body of data represent evidence supporting one statistical hypothesis against another?' (Royall, 1997). In this article, we use likelihood ratios to measure evidence provided by record values in favor of a hypothesis and against an alternative. This hypothesis is concerned on mean of an exponential model and prediction of future record values.

• Transactions of Materials Processing
• /
• v.11 no.3
• /
• pp.223-230
• /
• 2002

Matched die forming technology has been used widely as a sheet metal forming method for a long time. This conventional method, however, needs a high cost and long delivery time to prepare a set of matched dies or, in many cases, several sets of dies. For more than ten years, some alternative methods using single die or non-matched dies have been developed and applied practically in various fields of industry. Elasto-forming, fluid forming, hydro-forming, and blow forming are some examples of these new methods. Recently, a dieless sheet forming technology using a reconfigurable matrix of punch elements has been developed, and started to be used in some industries such as aircraft and railroads. A new concept of dieless forming technology has also been proposed to overcome the drawback of the conventional dieless forming technology.

• The Korean Journal of Applied Statistics
• /
• v.24 no.2
• /
• pp.315-321
• /
• 2011

Gene expression microarray data often include multiple missing values. Most gene expression analysis (including gene clustering analysis); however, require a complete data matric as an input. In ordinary clustering methods, just a single missing value makes one abandon the whole data of a gene even if the rest of data for that gene was intact. The quality of analysis may decrease seriously as the missing rate is increased. In the opposite aspect, the imputation of missing value may result in an artifact that reduces the reliability of the analysis. To clarify this contradiction in microarray clustering analysis, this paper compared the accuracy of clustering with and without imputation over several microarray data having different missing rates. This paper also tested the clustering efficiency of several imputation methods including our propose algorithm. The results showed it is worthwhile to check the clustering result in this alternative way without any imputed data for the imperfect microarray data.

• IE interfaces
• /
• v.12 no.4
• /
• pp.496-505
• /
• 1999

Quality of Service(QoS) is the collective effect of service performances and has a direct impact on customer satisfaction. Although QoS is subjective, network performance parameters contributing to QoS can be measured physically. Therefore overall customer satisfaction for each test condition of the performance parameters is evaluated by asking respondents to indicate his or her opinion on a five-category rating scale i.e., excellent, good, fair, poor, and unsatisfactory. The opinion data resulting from the test can then be used to measure and analyze QoS from the customers' viewpoints. In this papaer, we consider two methods for analyzing the opinion data: MOS method and Cumulative Probability Curve method. The former evaluates an arithmetic mean of the opinion scores which quantify the surveyed opinions of respondents. The latter uses graphical and analytical models which are based on the distribution of the opinions rather than an arithmetic mean. The advantages, disadvantages, and an alternative of each method are discussed, together with future directions of research.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.33 no.2
• /
• pp.1-16
• /
• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• Journal of Korean Society for Quality Management
• /
• v.31 no.3
• /
• pp.98-113
• /
• 2003

Kano model distinguishes three types of customer requirements, namely, one-dimensional quality, must-be quality, and attractive quality. There are a few methods for classifying a given customer requirement into one of the Kano's quality elements. However, the existing methods have a common limitation in that they are based on Kano evaluation table. Kano evaluation table is not always effective for the classification task, and suffers from a significant information loss. This paper proposes an alternative to Kano's evaluation table and a new classification scheme based on fuzzy set concept. The proposed method is illustrated using a case study on the ADSL service.

• Communications for Statistical Applications and Methods
• /
• v.7 no.2
• /
• pp.481-487
• /
• 2000

When we construct an interval estimate of two independent proportions with rare events, the standard approach based on the normal approximation behaves badly in many cases. The problem becomes more severe when no success observations are observed on both groups. In this paper, we compare two alternative methods of constructing a confidence interval of the difference of two independent proportions by use of simulation. One is based on the profile likelihood and the other is the Bayesian probability interval. It is shown in this paper that the Bayesian interval estimator is easy to be implemented and performs almost identical to the best frequentist's method -the profile likelihood approach.

• Communications for Statistical Applications and Methods
• /
• v.13 no.3
• /
• pp.503-512
• /
• 2006

In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.