• Korea Trade Review
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• v.46 no.3
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• pp.185-201
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• 2021

This paper analyzes the penalty tax system under the Customs Act of Korea and examines whether the penalty tax provision violate the constitutional principle of proportionality when imposed on a person who does not made import declaration intentionally or travelers who has not been made an import declaration of their carry-on items. It examines the provisions that adopt a penalty tax as a means to secure the effectiveness of the customs law. In relation to penalty tax, the case studies of the Supreme Court and Constitutional Court of Korea are analyzed by major issues such as the legal nature of the penalty tax, whether the penalty tax is unconstitutional, and the reasons for exemption from the penalty tax. There is no reasonable basis for the high penalty tax imposed on travelers' carry-on items for which import declaration has not been made. It is necessary to unify the penalty tax imposed when an import declaration is not made and the penalty tax on traveler's carry-on items. It is necessary to establish a limit on penalty tax and to create new regulations to exempt or reduce penalty tax when punished by administrative punishment to avoid double jeopardy. It is necessary to effectively secure the effectiveness of the Customs Act by converting the penalty tax into civil penalty that does not presuppose the faithful and accurate performance of tax obligations by the taxpayer. The government revised the penalty tax system in the Customs Act in 2019, but there are still many types of penalty tax and there are elements that are unconstitutional. It seems that the Korean government should lower the burden on the people by improving the system for the penalty tax system.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1025-1036
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• 2003

Variable selection algorithm for principal component analysis using penalty function is proposed. We use the fact that usual principal component problem can be expressed as a maximization problem with appropriate constraints and we will add penalty function to this maximization problem. Simulated annealing algorithm is used in searching for optimal solutions with penalty functions. Comparisons between several well-known penalty functions through simulation reveals that the HARD penalty function should be suggested as the best one in several aspects. Illustrations with real and simulated examples are provided.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.916-921
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• 2004

The penalty method has been widely applied to analyses of incompressible fluid flow. However, we have not yet found any prior studies that employed penalty method to analyze compressible fluid flow. In this study, with an eye on the apparent similarity between the slight compressible formulation and the penalty formulation, we have proposed a new approximate approach that can analyze compressible packing process using the penalty parameter l. Based on the assumption of the isothermal flow, a set of reference solutions was obtained to verify the validity of the proposed scheme. Furthermore, we have applied the proposed scheme to the analysis of the packing process of different cases.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.41-54
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• 2015

In this article, we propose nonconcave penalties on a reduced-rank regression model to select variables and estimate coefficients simultaneously. We apply HARD (hard thresholding) and SCAD (smoothly clipped absolute deviation) symmetric penalty functions with singularities at the origin, and bounded by a constant to reduce bias. In our simulation study and real data analysis, the new method is compared with an existing variable selection method using $L_1$ penalty that exhibits competitive performance in prediction and variable selection. Instead of using only one type of penalty function, we use two or three penalty functions simultaneously and take advantages of various types of penalty functions together to select relevant predictors and estimation to improve the overall performance of model fitting.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.49-51
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• 2000

ln this paper, a method by which penalty factors of all generators including slack bus can be directly derived is presented. With a simple re-assignment of angle reference bus to a bus where no generation exists, penalty factors for slack bus is obtained without any physical assumption. While previous Jacobian-based techniques for generator penalty factor calculation have been derived with basis upon reference bus, proposed method are not dependent on reference bus and calculated penalty factors can be substituted directly into the general ELD equation to compute the economic dispatch. Equations for system loss sensitivity, penalty factors and optimal generation allocation are solved simultaneously in normal power flow computation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.30-35
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• 1996

Penalty technique perhaps is the most common technique used in the genetic algorithms for constrained optimization problems. In recent years, several techniques have been proposed in the area of evolutionary computation. However, there is no general guideline on designing penalty function and constructing an efficient penalty function is quite problem-dependent. The purpose of the paper is to give a tutorial survey of recent works on penalty techniques used in genetic algorithms and to give a better classification on exisitng works, which may be helpful for revealing the intrinsic relationship among them and for providing some hints for further studies on penalty techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.105-110
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• 2005

The penalty method has been widely applied to analyses of incompressible fluid flow. However, we have not yet found any prior studies that employed penalty method to analyze compressible fluid flow. In this study, with an eye on the apparent similarity between the slight compressible formulation and the penalty formulation, we have proposed a modified approximate approach that can analyze compressible packing process using the penalty parameter, which is an improvement on an earlier formulation (KSME, 2004B). Based on the assumption of the isothermal flow, a set of reference solutions was obtained to verify the validity of the proposed scheme. Furthermore, we have applied the proposed scheme to the analysis of the packing process of different cases.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.215-227
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• 2007

Variable selection algorithm for Sliced Inverse Regression using penalty function is proposed. We noted SIR models can be expressed as generalized eigenvalue decompositions and incorporated penalty functions on them. We found from small simulation that the HARD penalty function seems to be the best in preserving original directions compared with other well-known penalty functions. Also it turned out to be effective in forcing coefficient estimates zero for irrelevant predictors in regression analysis. Results from illustrative examples of simulated and real data sets will be provided.

• Journal of applied mathematics & informatics
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• v.33 no.3_4
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• pp.387-399
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• 2015

In this paper, a new smoothing approximation to the l₁ exact penalty function for constrained optimization problems (COP) is presented. It is shown that an optimal solution to the smoothing penalty optimization problem is an approximate optimal solution to the original optimization problem. Based on the smoothing penalty function, an algorithm is presented to solve COP, with its convergence under some conditions proved. Numerical examples illustrate that this algorithm is efficient in solving COP.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1477-1487
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• 2010

In this paper, we give a solving approach based on a logarithmic-exponential multiplier penalty function for the constrained minimization problem. It is proved exact in the sense that the local optimizers of a nonlinear problem are precisely the local optimizers of the logarithmic-exponential multiplier penalty problem.