• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.45-52
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• 2016

This paper suggests a new method of finding regularization parameter for image restoration problems. Wiener filter requires priori information such that power spectrums of original image and noise. Constrained least squares restoration also requires knowledge of the noise level. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, self-regularization method that connects bias term of augmented linear system and smoothing term of Tikhonov regularization is introduced in the frequency domain and applied to the image restoration problems. Experimental results show the effectiveness of the proposed method.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.39-74
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• 2018

Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi's philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.574-582
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• 1999

This paper discusses the multi-level optimization method in dynamic optimization problems through stiffened plate of ship structures. In structural optimization the computational cost increases rapidly as the number of design variables increases. And we need a great amount of cal-culation and time on problems of modified dynamic characteristics of large and complicated struc-tures. In this paper the multi-level optimization is proposed which decreases computational time and cost. the dynamic optimum designs of stiffened plate that control the natural frequency and minimize weight subjected to constraints condition are derived. The way to apply the multi-level optimization methods in this study follow: In the first step the dynamic characteristics is controlled for the two-dimensional model of stiffened plate by sensitivity analysis and quasi-least squares methods. In the second step the cross-section of the stiffener is decided so that the weight is minimized under needed constraints by the steepest descent or ascent method. In the third the three-dimensional model is made based on the results of the first step and the second step confirmation and finer tuning of the objective function are carried out. It is shown that the results are effective in the optimum modification for dynamic characteristics of the stiffened plate.

• The Journal of Engineering Geology
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• v.19 no.1
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• pp.71-79
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• 2009

Step-drawdown tests were conducted at four pumping Wells, two in porous media and two in fractured rocks, respectively. In general, P = 2.0 suggested by Jacob (1947) is applied to porous media and fractured rocks in terms of drawdowns of step-drawdown test. In an attempt to review problems of linear model (Jacob's graphic method) in interpreting the step-draw down test, the outcomes of well parameters (aquifer loss coefficient (B), well loss coefficient (C) and well loss exponent (P)) calculated from linear and nonlinear model (Labadie and Helweg's least-squares method) were compared and analyzed. The values of C and P calculated from linear and nonlinear models differed according to permeability of aquifer and the conditions of pumping well. The value C obtained from nonlinear models in porous media and fractured rocks is about $10^0{\sim}10^{-2}$ and $10^{-3}{\sim}10^{-6}$ times lower than in their linear models, respectively. The value P of porous media obtained from nonlinear model ranged from 2.123 to 2.775, while it ranged from 3.459 to 5.635 for fractured rocks. In case of nonlinear model, well loss highly depends on the value P. At this time, well efficiencies calculated from linear and nonlinear models were $1.56{\sim}14.89%$ for porous media and $8.73{\sim}24.71%$ for fractured rocks, showing a significant error according to chosen models. In nonlinear model, it was found that the regression analysis using the least squares method was very useful to interpret step-drawdown test in all aquifer.

• Journal of Ginseng Research
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• v.37 no.3
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• pp.371-378
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• 2013

Serum and liver metabolites in rats fed red ginseng (RG) were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. The mass data were analyzed by partial least squares-discriminant analysis (PLS-DA) to discriminate between control and RG groups and identify metabolites contributing to this discrimination. The RG group was clearly separated from the control group on PLS-DA scores plot for serum samples, but not liver samples. The major metabolites contributing to the discrimination included lipid metabolites (lysophosphatidylcholine, acyl-carnitine, and sphingosine), isoleucine, nicotinamide, and corticosterone in the serum; the blood levels of all but isoleucine were reduced by RG administration. Not all metabolites were positively correlated with the health benefits of RG. However, the blood levels of lysophosphatidylcholine, which stimulate various diseases, and long-chain acylcarnitines and corticosterone, which activate the stress response, were reduced by RG, suggesting long-term RG might relieve stress and prevent physiological and biological problems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.2062-2069
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.182-188
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.101-108
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• 2007

This paper presents an efficient meshless method for analyzing cracked piezoelectric structures subjected to mechanical and electrical loading. The method employs an element free Galerkin (EFG) formulation and an enriched basic function as well as special shape functions that contain discontinuous derivatives. Based on the moving least squares (MLS) interpolation approach, The EFG method is one of the promising methods for dealing with problems involving progressive crack growth. Since the method is meshless and no element connectivity data are needed, the burdensome remeshing procedure required in the conventional finite element method (FEM) is avoided. The numerical results show that the proposed method yields an accurate near-tip stress field in an infinite piezoelectric plate containing an interior hole. Another example is to study a ceramic multilayer actuator. The proposed model was found to be accurate in the simulation of stress and electric field concentrations due to the abrupt end of an internal electrode.

• Ocean and Polar Research
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• v.32 no.1
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• pp.23-40
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• 2010

This study investigated the effects of imported fisheries products on WTO/DDA tariff negotiations. To calculate the results, the study estimated the demand functions of imported fisheries products by using unit root and cointegration approaches. These approaches allowed us to solve spurious regression problems with macro-economic variables. In addition, this study surmised the effects of change by individually imported fish products from a tariff negotiation model using price elasticities of estimated import demand function. In a process of the analysis for estimating import effects, this study found out that 39 out of 128 imported fish products had positive (+) price elasticities or did not exhibit cointegrations. To cure this problem, this study suggested that the effects of these 39 imported products be estimated with the average variation rate of import volume, rather than by the Ordinary Least Squares approach. In this study, a case-study of tariff formula with coefficient 8 based on a 'Swiss formula' for priority duty rate of 2001 and 2008 was used by to analyze the effect of change in the 128 imported fish products of both years, respectively.