• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1483-1486
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• 2003

Injection mold is a manufacturing process used to produce the various parts of complicated shape at a low cost. Many factors such as, section shape, resin and mold temperature, filling time, etc, affect on the quality of injection part during injection molding process. The precent study, was carried out the shrinkage analysis of shoes injection mold to optimize runner shape based on filling and packing pressure with MoldFlow. Taguchi design and analysis of variance are used to optimize injection mold design.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.708-713
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• 2000

The design of experiment(DOE) is getting more attention in the engineering community since it is easy to understand and apply. Recently, engineering designers are adopting DOE with orthogonal arrays when they want to design products in a discrete design space. In this research, a design flow with orthogonal arrays is defined fur structural design according to the general DOE. The design problem is defined as a general structural optimization problem. Sensitivity information is evaluated by the analysis of variance(ANOVA), and an optimum design is determined from analysis of means(ANOM). Interactions between design variables are investigated to achieve additivity which should be valid in DOE. When strong interactions exit, a method is proposed. Some methods to consider the problem are suggested.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.245-251
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• 2008

The research proposes three ANOVA(Analysis of Variance) tests using expected mean square(EMS) algorithms in various split-plot designs. The variance tests consist of Never-Pool test, Sometimes-Pool test and Always-Pool test. This paper also presents two EMS algorithms such as standard method and easy method. These algorithms are useful to make a decision rule for pooling. Numerical examples are illustrated for various split-plot designs such as split-plot designs, split-split-plot designs, repetition split-plot designs, and nested designs. Pragmatically, the results are summarized and compared with popular ANOVA spreadsheets and data model equations.

• Journal of Information Technology Services
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• v.16 no.1
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• pp.119-138
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• 2017

Mobile easy payment is a term for using mobile devices to facilitate financial transactions. Mobile easy payment is a quickly emerging practice, supported by the dramatic increase of mobile phone or device users around the world. The purpose of this study is to classify user's group of the mobile easy payment service by their lifestyle based on I-VALS type and to investigate differences in usage behavior among the user groups. For empirical study, a questionnaire survey was carried out with users of mobile easy payment services using the Internet from June 7 to 10 in 2016. We conducted factor analysis for I-VALS, usage factors, satisfaction factors. We also performed cluster analysis for group classification, and analysis of variance, cross analysis to compare the different usage behavior among the user groups. In analysis results, first three cluster appeared including "ICT task-oriented group", ICT positive and socialities oriented group", "ICT leader-oriented group". Second, it was found significant differences among the clusters about factor of "easy of use", "securities", "universality", "satisfaction". Third, we showed that there were significant differences in time first used the service. Based on these findings, we provide practical implications. Results of our study can be expected to provide the basis of differentiated marketing strategy of mobile easy payment services.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.305-309
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• 2000

In this paper, we presents a new methodology for face recognition after analysing conventional ICA(Independent Component Analysis) based approach. In the literature we found that ICA based methods have followed the same procedure without any exception, first PCA(Principal Component Analysis) has been used for feature extraction, next ICA learning method has been applied for feature enhancement in the reduced dimension. However, it is contradiction that features are extracted using higher order moments depend on variance, the second order statistics. It is not considered that a necessary component can be located in the discarded feature space. In the new methodology, features are extracted using the magnitude of kurtosis(4-th order central moment or cumulant). This corresponds to the PCA based feature extraction using eigenvalue(2nd order central moment or variance). The synergy effect of PCA and ICA can be achieved if PCA is used for noise reduction filter. ICA methodology is analysed using SVD(Singular Value Decomposition). PCA does whitening and noise reduction. ICA performs the feature extraction. Simulation results show the effectiveness of the methodology compared to the conventional ICA approach.

• Korean Management Science Review
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• v.33 no.4
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• pp.51-64
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• 2016

The maximum weight of single stock in mutual fund is limited by regulations to enforce diversification. Under incomplete information with added constraints on portfolio weights, enhanced performance had been reported in previous researches. We analyze a weight vector to examine the effects of additional constraints on the portfolio's performance by computing the Euclidean distance from the in-sample tangency portfolio, as opposed to previous researches which analyzed ex-post return only. Empirical experiment was performed on Mean-variance and Minimum-variance model with Fama French's 30 industry portfolio and 10 industry portfolio for the last 1,000 months from August 1932 to November 2015. We find that diversification-constrained portfolios have 7% to 26% smaller Euclidean distances with the benchmark portfolio compared to those of unconstrained portfolios and 3% to 11% greater Sharpe Ratio.

• Journal of the Korean Statistical Society
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• v.2 no.1
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• pp.47-51
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• 1973

No Abstract, See Full Text

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.2
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• pp.151-161
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• 2007

Statistical characteristic analysis was carried out using the non-tidal components computed by the harmonic analysis of the tidal elevation data in East coast. The tide gauging stations included in this study are the Sokcho, Mukho, Hupo, Pohang, Ulsan and Ulreungdo stations. In this study, the variance and skewness coefficient (SC) information changes, i.e., the max. value, min. value, mean and standard deviation of the variance and SC, are compared and analysed in detail by the various analysis periods increased from one year to the maximum available period. Based on the result of the statistical information (SI) range analysis, the minimum analysis period required in order to satisfy the confidence interval of the ${\pm}5%$ range of the variance and the ${\pm}0.1$ range of the SC is suggested as the 12 years, except the Ulreungdo stations. The auto-correlation and spectral density change patterns show the very similar shapes in every stations even though the absolute values are a little bit different each other.

• Bulletin of the Korean Mathematical Society
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• v.13 no.1
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• pp.21-26
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• 1976

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.189-212
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• 2005

This study examines the interactions between KTB spot and futures markets using the daily prices from March 4, 2002 to January 31, 2005. We use Granger causality test, impulse Response Analysis and Variance Decomposition through vector autoregressive analysis (VAR). However, considering the long-term relationships between the level variables of KTB spot and futures, we introduced Vector Error Correction Model. The main results are as follows. According to the results of Granger-causality test and impulse response analysis, we find that the yields of KTB forward have a great influence on the change of KTB spot but not vice versa. In terms of volatility analysis, there is no inter-dependence between KTB forward and spot markets. In the variance decomposition analysis we find that the short-term KTB forward has much more impact on the KTB spot market than the long-term KTB forward does. We think these results are meaningful for bond investors who are in charge of capital asset pricing valuation, risk management and international portfolio management.