• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.160-171
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• 2003

Criteria for the comparison of quality of asset portfolio management are risk and return. In this paper a method to use structural time-series model to determine an optimal portfolio for the improvement of quality of asset portfolio management is suggested. In traditional mean variance analysis expected return is assumed to be time-invariant. However, it is more realistic to assume that expected return is temporally dynamic and structural time-series model can be used to reflect time-varying nature of return. A data set from an insurance company was used to show validity of suggested method.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.11-23
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• 2003

This study Investigates the short and long-run dynamic relationships between the domestic and U.S. stock markets for the period of declining stock prices. It Is well known that the domestic stock market variations are largely caused by the U.S. stock market movements. Multivariate causal tty test Is utilized to examine the lead-lag relationships among four stock prices of KOSPI and KOSDAQ In the domestic part and DOWJONES and NASDAQ In the U.S. part. When the stock prices tend to decrease In the long run, It Is found that both KOSPI and KOSDAQ have closer relations with NASDAQ than DOWJONES. When both of domestic stock markets are severely fluctuate, bidirectional causal relationships appear to exist between NASDAQ and each of KOSPI and KOSDAQ. On the other hand. when the domestic stock markets are relatively stable, unidirectional causality Is found to exist between NASDAQ and each of KOSPI and KOSDAQ. which is explicitly validated by the analysis of variance decomposition.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.373-381
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• 2009

Evidence of linkage is expressed as a decreasing trend of the squared trait difference of two siblings with increasing identical by descent scores. In contrast to successes in the application of a parametric approach of Haseman-Elston regression, notably low powers are demonstrated in the nonparametric linkage analysis methods for complex traits and diseases with sib-pairs data. We report that the Genehunter nonparametric linkage statistic is biased and furthermore the variance formula that they used is an inflated one, and this is one reason for a low performance. Thus, we propose bias-corrected nonparametric linkage statistics. Simulation studies comparing our proposed nonparametric test statistics versus the existing test statistics suggest that the bias-corrected new nonparametric test statistics are more powerful and attains efficiencies close to that of Haseman-Elston regression.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.1
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• pp.1-12
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• 2006

In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation, each objective function is converted into the Expected Improvement (EI) and this value is used as fitness value in the multi-objective optimization instead of the objective function itself. Among the non-dominated solutions about EIs, additional sample points for the update of the Kriging model are selected. The present method was applied to a transonic airfoil design. Design results showed the validity of the present method. In order to obtain the information about design space, two data mining techniques are applied to design results: Analysis of Variance (ANOVA) and the Self-Organizing Map (SOM).

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.208-211
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• 2000

Processing parameters of filament winding were investigated by using design of experiment. To understand 4 main effects(fiber tension, impregnation pressure, processing rate, and temperature) and 3 interactions, $L_{27}(3^{13})$ orthogonal array table was adopted. The used materials were carbon fiber and epoxy resin. Split disk test and short-beam test, which are the general test methods for filament wound composite material, were selected as evaluation methods for a filament would part. The optimal processing parameters for the filament winding were easily found through the analysis of variance of the experimental results.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.489-497
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• 2000

The M/M/1 queue with impatient customers is studied. Impatient customers wait for service only for limited time K/0 and leave the system if their services do not start during that time. Notice that in the analysis of virtual waiting time, the impatient customer can be considered as the customer who enters the system only when his/her waiting time does not exceed K. In this paper, we apply martingale methods to the virtual waiting time and obtain the expected period from origin to the point where the virtual waiting time crosses over K or reaches 0, and the variance of this period. With this results, we obtain the expected busy period of the queue, the distribution, expectation and variance of the number of times the virtual waiting time exceeding level K during a busy period, and the probability of there being no impatient customers in a busy period.

• Journal of Hydrogen and New Energy
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• v.15 no.1
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• pp.72-81
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• 2004

Study on the analysis of sodium spray fire using Gaussian drop size distribution, which redistributes a droplet spectrum with given mean diameter if its size classes with critical diameter(D>8mm) occur, was carried out. In this case, the oversized droplets were reduced to a stable diameter. Results calculated by the code using Gaussian drop size distribution were in better agreement with AI experimental results than those of NACOM and SPRAY code. The effect of variance on pressure in the test cell appeared greatly by introducing Gaussian function, which could represent various sodium droplet size distribution. The increase of the variance with mean droplet size resulted had an important effect upon the pressure in the test cell.

• International Journal of Railway
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• v.6 no.2
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• pp.45-52
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• 2013

Railway construction needs vast soil investigation for its infrastructure foundation designs along the planned railway path to identify the design parameters for stability and serviceability checks. The soil investigation data are usually classified and grouped to decide design input parameters per each construction section and budget estimates. Deterministic design method which most civil engineer and practitioner are familiar with has a clear limitation in construction/maintenance budget control, and occasionally produced overdesigned or unsafe design problems. Instead of using a batch type analysis with predetermined input parameters, data population collected from site soil investigation and design load condition can be statistically estimated for the mean and variance to present the feature of data distribution and optimized with a best fitting probability function. Probabilistic approach using entire feature of design input data enables to predict the worst, best and most probable cases based on identified ranges of soil and load data, which will help railway designer select construction method to save the time and cost. This paper introduces two Monte Carlo simulations actually applied on estimation of retaining wall external stability and long term settlement of organic soil in soil investigation area for a recent high speed railway project.

• Journal of the Korea Society for Simulation
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• v.8 no.2
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• pp.1-11
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• 1999

Advanced information communication processing system mainly consists of network access subsystems and a switching system. This paper provides performance analysis of a typical network access subsystem. The network access subsystem is modeled as a queueing network including a server providing polling services. The arrival process of messages to an input buffer is regarded as a Poisson process. Performance measures such as mean input buffer length and mean waiting time of meassages are obtained through simulation, for it is impossible to calculate the performance measures using an analytical method. Hybrid simulation is used to reduce the variance of estimators. The variance reduction effect on the mean waiting time is reported.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.40-49
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• 2018

We propose a more stable robust recognition algorithm which detects faces reliably even in cases where there are changes in lighting and angle of view, as well it satisfies efficiency in calculation and detection performance. We propose detects the face area alone after normalization through pre-processing and obtains a feature vector using (PCA). The feature vector is applied to LDA and using Euclidean distance of intra-class variance and inter class variance in the 2nd dimension, the final analysis and matching is performed. Experimental results show that the proposed method has a wider distribution when the input image is rotated $45^{\circ}$ left / right. We can improve the recognition rate by applying this feature value to a single algorithm and complex algorithm, and it is possible to recognize in real time because it does not require much calculation amount due to dimensional reduction.