• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.2
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• pp.75-82
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• 1985

Reorganization is essential part of data base maintenanc work and the reasonable reorganization points can be determined from the trade-off between reorganization cost and performance degradation. There has been many reorganization models so far, but none of these models have assumed nonlinear search cost function. This paper presents the existensions of two existing linear reorganization models for the case where the search cost function is quadratic. The higher performance of these extended models was shown in quadratic search cost function case.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.78-89
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• 2016

Purpose: In this paper, we investigate whether the endeavors for Six Sigma quality management by a firm have positive effects on its financial performance and the length of Six Sigma implemented period affects its financial status. We find a relationship between Six Sigma implemented period and several financial performance index using a smoothing spline function. Methods: A smoothing spline function is used in order to analyze the relationship between efforts for quality management and financial performance. Specifically, the return on assets, return on equity, sales cost and business fee are investigated as dependent variables and the efforts for quality management as independent variable. Results: As a result of the analysis, the indication is that companies that put effects into the Six Sigma quality management have a positive result in its financial status. In detail, the efforts for Six Sigma quality management have positive effects on total asset turnover ratio and Six Sigma implemented period on net income to net sales ratio. Additionally, companies with longer (shorter) period of Six Sigma program have more (less) improvement in its financial status. Conclusion: It can be concluded that the company's efforts for quality management positively influence financial performance.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1464-1473
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• 1990

Optimal design parameters are estimated from the sensitivity function and performance index variation. Suspension design modification for performance improvement and basic materials for practical applications are presented. The linear quarter model of a vehicle suspension is analyzed in order to represent the utilities of sensitivity analysis, and sensitivity function is determined in the frequency domain. The change of frequency response function is predicted, which depends on the design parameter variation and the property is verified by computer simulation. As an investigation results of sensitivity function for the vibrational amplitude of sprung mass to road profile input, it is shown that the most sensitive parameters are the suspension damping and the suspension stiffness. In order to identify the effects of these two parameters to the performance of suspension system, the performance index variation according to the changes of parameters is considered and then optimal design parameters are determined. It is verified that the system response is improved noticeably in the both of frequency and time domain after the design modification with the optimal parameters.

• Journal of the Korean Magnetics Society
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• v.25 no.6
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• pp.203-207
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• 2015

This paper introduces a probabilistic analysis method in order to analyze the effect of manufacturing tolerance on induction motor performance occurring in massive production. The univariate dimension reduction method is adapted to predict probabilistic characteristics of a performance function due to certain probabilistic distributions of design variables. Moreover, the sensitivity information on mean and variance of the performance function is estimated, and then the effect of randomness of individual design variables on the probability performance function is analyzed. The effectiveness and accuracy of the method is investigated with a mathematical model and an induction motor.

• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.143-161
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• 2015

This study presents a comparative analysis on mackerel distribution process and price formation process, and investigation of price and margin between traditional markets and Large-scale discount store distribution channel. Through this, the study investigated distribution efficiency of each channel, and examined whether a difference of distribution efficiency leads to a difference of performance through the investigation of a difference of function and role between members of a wholesale market and vendor of Large scale discount store. The following are the results of this study. As a consequence of investigating supply and sum by distribution channel of mackerel, it appeared that mackerels shipped from port market are distributed into 9 consumption sites(Wholesale market, Large scale discount store, Institutional Food Service, etc.). In the comparison of distribution efficiency between traditional retail store and Large scale discount store 52.0% margin is formed in traditional retail store distribution channel and 43.1% margin is formed in Large scale discount store, and a distribution cost rate consists of 19.4% cost in a traditional retail store for fishery products and 18.1% cost in a Large-scale discount store. To analyze a difference of performance, the study examine a difference of role and function between vendor and Wholesale market company, wholesaler and middleman. Wholesale market company and middleman of wholesale market for consumer have slightly high or similar score in collection function, sorting function, evaluation function and financial function which are traditional and original. However, it was confirmed that vendor has a better score in other functions, that is, newly-demanded functions(ex : market frontier function, product development function, Integral Distribution Function, etc.).

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.111-128
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• 2014

The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.

• Women's Health Nursing
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• v.6 no.4
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• pp.606-618
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• 2000

The purpose of this study was to provide basic data for developing a nursing intervention for climacteric women by describing a health promoting lifestyle. Also this study identified the relationship between self-efficacy and family function which are factors affecting the health promoting behaviors. The subjects of this study were 143 women from 40 to 59 years of age. The data was analyzed using SPSS program for t-test, ANOVA, and Pearson's correlation coefficients. The results of the study are as follows; 1. The average score of performance in the health promoting lifestyle was 2.82. The variable with the highest degree of performance was the sanitary environment and reconciliatory relationship(3.31), whereas the one with the lowest degree was the professional health maintenance(2.27). The average score of self-efficacy was 71.44, family function was 68.50, and menopausal symptoms was 60.30. 2. There was a statistically significant difference in performance in health promoting lifestyle according to satisfaction of marital life. Also there was a significant difference between self-efficacy, religion, and family function. 3. Performance in the health promoting lifestyle was positively related to self-efficacy, and family function and negatively related to menopausal symptoms. Self-efficacy was positively related to family function. In conclusion, performance in health promoting lifestyle was related to self-efficacy, family function and menopausal symptoms. These factors were affected by religion, family type, and satisfaction of marital life. Therefore, health promoting programs to increase climacteric women's health should be a planed program based on results of this study.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.615-623
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• 2008

This paper proposes an $H_{\infty}$ controller design method for Takagi-Sugeno (T-S) fuzzy systems using a fuzzy basis-function-dependent Lyapunov function. Sufficient conditions for the guaranteed $H_{\infty}$ performance of the T-S fuzzy control system are given in terms of linear matrix inequalities (LMIs). These LMI conditions are further used for a convex optimization problem in which the $H_{\infty}-norm$ of the closed-loop system is to be minimized. To facilitate the basis-function-dependent Lyapunov function approach and thus improve the closed-loop system performance, additional decision variables are introduced in the optimization problem, which provide an additional degree-of-freedom and thus can enlarge the solution space of the problem. Numerical examples show the effectiveness of the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1537-1545
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• 2015

Support vector quantile regression (SVQR) can be obtained by applying support vector machine with a check function instead of an e-insensitive loss function into the quantile regression, which still requires to solve a quadratic program (QP) problem which is time and memory expensive. In this paper we propose an SVQR whose objective function is composed of an asymmetric quadratic loss function. The proposed method overcomes the weak point of the SVQR with the check function. We use the iterative procedure to solve the objective problem. Furthermore, we introduce the generalized cross validation function to select the hyper-parameters which affect the performance of SVQR. Experimental results are then presented, which illustrate the performance of proposed SVQR.

• International Journal of Contents
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• v.13 no.4
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• pp.23-28
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• 2017

Of the total economic loss caused by disasters, 40% are due to floods and floods have a severe impact on human health and life. So, it is important to monitor the water level of a river and to issue a flood warning during unfavorable circumstances. In this paper, we propose a modified error function to improve a hydrological modeling using a multi-layer perceptron (MLP) neural network. When MLP's are trained to minimize the conventional mean-squared error function, the prediction performance is poor because MLP's are highly tunned to training data. Our goal is achieved by preventing overspecialization to training data, which is the main reason for performance degradation for rare or test data. Based on the modified error function, an MLP is trained to predict the water level with rainfall data at upper reaches. Through simulations to predict the water level of Nakdong River near a UNESCO World Heritage Site "Hahoe Village," we verified that the prediction performance of MLP with the modified error function is superior to that with the conventional mean-squared error function, especially maximum error of 40.85cm vs. 55.51cm.