• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.93-100
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• 2003

It is necessary to check the curvature of selected covariates in regression diagnostics. There are various graphical methods using residual plots based on least squares fitting. The sensitivity of LS fitting to outliers can distort their residuals, making the identification of the unknown function difficult to impossible. In this paper, we compare combining conditional expectation and residual plots(CERES Plots) between least square fit and robust fits using Huber M-estimator. Robust CERES will be far less distorted than their LS counterparts in the presence of outliers and hence, will be more useful in identifying the unknown function.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.5-12
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• 2000

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution and it is shown to be useful in such Bayesian meta-analysis. A general class of skewed elliptical distribution is reviewed and developed. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierarchical selection model and use Markov chain Monte Carlo methods to develop inference for the parameters of interest.

• Journal of Korean Society for Quality Management
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• v.31 no.2
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• pp.40-50
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• 2003

This study proposes Environmental Quality Deployment (EQD) by combining an instrument for measuring customer satisfaction (ENVIROQUAL) with a standard tool of product design in manufacturing called quality function deployment (QFD). The EQD presents the conceptual map of House of Environmental Quality as a means to implementation to help a company know what customers perceive as important in making environmentally friendly product and provide a framework for the translation of customer satisfaction into identifiable and measurable conformance specifications for environmentally friendly product design.

• Structural Engineering and Mechanics
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• v.56 no.1
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• pp.107-121
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• 2015

The main objective of this research is to present the procedures of combining topology, shape & sizing optimization for truss structure by employing strain energy as objective function under the constraints of volume fractions which yield more general solution than that of total weight approach. Genetic Algorithm (GA) is used as searching engine for the convergence solution. A number of algorithms from previous research are used for evaluating the feasibility and stability of candidate to accelerate convergence and reduce the computational effort. It is followed by solving problem for topology & shape optimization and topology, shape & sizing optimization of truss structure to illustrate the feasibility of applying the objective function of strain energy throughout optimization stages.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.3
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• pp.450-454
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• 2003

It is important to control the processing conditions to maximize the replication quality of UV-molded microstructure. In the present study, the tip radius anil surface roughness of V-groove structure were measured to quantify the replication quality. UV-curing dose and the applied pressure were experimentally selected as the governing Processing conditions that affect the replication quality of the UV-molded part. Finally. an experimental optimization technique combining central composite design and desirability function approach was used to maximize the replication quality of UV-molded structure.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.7
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• pp.649-658
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• 2000

Thermodynamic modeling of low-pressure scroll compressor was developed by combining continuity and energy conservation equation. Suction gas heating was considered using energy balance inside the low pressure shell. Pressure, temperature and mass of refrigerant-22 as a function of orbiting angle were calculated by solving the governing equations using fourth order Rung-Kutta scheme. Motor efficiency was taken by experiments with a variation of frequency. The developed model was applied to the analysis of an inverter driven scroll compressor with a variation of frequency, pressure ratio and operating conditions. The model was verified with the experimental results at the same operating conditions. The developed model was adequate to predict performance of the inverter driven scroll compressor as a function of operating conditions. Calculated parameters from the model were discharge temperature, mass flow rate, power input, COP, and thermodynamic properties with respect to orbiting angle. To enhance the performance of a scroll compressor, it is essential to diminish leakage at low frequency level and improve the mechanical efficiency at high frequency level.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.250-255
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• 2016

Steganography is the art and science of secure communication. It focuses on both security and camouflage. Steganographic techniques must produce the resultant stego-image with less distortion and high resistance to steganalysis attack. This paper is mainly concerned with two steganographic techniques-least significant bit (LSB)++ and the reversible histogram transformation function (RHTF). LSB++ is likely to produce less distortion in the output image to avoid suspicion, but it is vulnerable to steganalysis attacks. RHTF using a mod function technique is capable of resisting the most popular and efficient steganalysis attacks, such as the regular-singular pair attack and chi-squared detection steganalysis, but it produces a lot of distortion in the output image. In this paper, we propose a new steganographic technique by combining both methods. The experimental results show that the proposed technique overcomes the respective drawbacks of each method.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.338-342
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• 2000

In order to approximate a nonlinear function, wacelet neural networks combining wacelet theory and neural networks have been proposed as an alternative to conventional multi-layered neural networks. wacelet neural networks provide better approximating performance than conventional neural networks. In this paper, an effective method to construct an optimal wavelet neural network is proposed using genetic alogorithm. Genetic Algorithm is used to determine dilationa and translations of wavelet basic functions of wavelet neural networks. Then, these determined dilations dilations and translations, wavelet neural networks are funther trained by back propagation learning algorithm. The effectiveness of the final network is verified thrifigh the approximation result of a nonlinear function and comparison with conventional neural networks.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.413-424
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• 2010

Mixture experiments involve combining ingredients or components of a mixture and the response is a function of the proportions of ingredients which is independent of the total amount of a mixture. The purpose of the mixture experiments is to find the optimum blending at which responses such as the flavor and acceptability are maximized. We assume the quadratic or special cubic canonical polynomial model over the experimental region for a mixture since the current mixture is assumed to be located in the neighborhood of the optimal mixture. The cost of the mixture is proportional to the cost of the ingredients of the mixture and is the linear function of the proportions of the ingredients. In this paper, we propose mixture response surface methods to develop a mixture such that the cost is down more than ten percent as well as mean responses are as good as those from the current mixture. The proposed methods are illustrated with the well known the flare experimental data described by McLean and Anderson(1966).

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.425-448
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• 2003

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution proposed originally by Chen et al. (1999) and Branco and Dey (2001). These rich classes of models combine the information of independent studies, allowing investigation of variability both between and within studies, and incorporate weight function. Here, the testing for the skewness parameter is discussed. The score test statistic for such a test can be shown to be expressed as the posterior expectations. Also, we consider the detail computational scheme under skewed normal and skewed Student-t distribution using MCMC method. Finally, we introduce one example from Johnson (1993)'s real data and apply our proposed methodology. We investigate sensitivity of our results under different skewed errors and under different prior distributions.