• Journal of the Architectural Institute of Korea Structure & Construction
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• v.33 no.12
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• pp.53-62
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• 2017

Many gradient-based mathematical methods have been developed and are in use for structural size optimization problems, in which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. The main objective of this paper is to propose an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm that is derived using penalty function. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. In this paper, a discrete search strategy using the HS algorithm with a static penalty function is presented in detail and its applicability using several standard truss examples is discussed. The numerical results reveal that the HS algorithm with the static penalty function proposed in this study is a powerful search and design optimization technique for structures with discrete-sized members.

• Journal of Korea Trade
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• v.27 no.1
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• pp.176-191
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• 2023

Purpose - When recovered through arbitration a contractual penalty that is disproportionately high can become grounds for challenging an arbitral award or an obstacle to its enforcement within Russian jurisdiction. This article investigates how violation of the principle of proportionality can affect the enforcement and challenging of arbitral awards in Russia. Based on the examination of the current legislation, along with the analysis of recent court cases on the subject, the ultimate object of this article is to discern practical recommendations for Korean practitioners who are looking to challenge and/or enforce arbitral awards in Russian courts. Design/methodology - The research process included the reviewing of current Russian legislation conducted in concurrence with academic literature review, searching and analyzing recent court cases where the relevant legal provisions and concepts were applied, and formulating practical implications of the research at its final stage. Findings - Through its relation to the principle of fairness/justice the authors establish the connection between the principle of proportionality and the public policy of Russia. Analysis of recent court cases showed two conflicting trends of whether a disproportionate penalty can be considered a public policy violation. The authors offer practical recommendations on how to substantiate a relevant claim regarding contractual penalty reduction by the court, depending on the desired outcome. Originality/value - The article contains an up-to-date summary of the legal provisions on the principle of proportionality of civil liability in Russia and identifies the most recent trends in court practice on the issue that is not covered by existing studies.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.613-618
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• 2011

The proposed method is based on a penalized log partial likelihood of Cox proportional hazard model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log partial likelihood function of Cox proportional hazard model. It provide the ecient computation including variable selection and leads to the generalized cross validation function for the model selection. Experimental results are then presented to indicate the performance of the proposed procedure.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.655-662
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• 2012

Classification is an important research field in pattern recognition with high-dimensional predictors. The support vector machine(SVM) is a penalized feature selector and classifier. It is based on the hinge loss function, the non-convex penalty function, and the smoothly clipped absolute deviation(SCAD) suggested by Fan and Li (2001). We developed the algorithm for the multiclass SVM with the SCAD penalty function using the local quadratic approximation. For multiclass problems we compared the performance of the SVM with the $L_1$, $L_2$ penalty functions and the developed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.3-10
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• 1998

Optimization problems may be devided into geometry optimization problems and topology optimization problems. In this paper, a method using tile equivalent material properties prediction techniques of a particulate-reinforced composites is proposed for the topology optimization. This method makes use of penalty factor in order that regions with intermediate value of design variables can be penalized. The computational results being obtained from PLBA algorithm of some values of penalty factor are presented.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1653-1660
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• 2016

Smoothly clipped absolute deviation (SCAD) penalty is known to satisfy the desirable properties for penalty functions like as unbiasedness, sparsity and continuity. In this paper, we deal with the regression function estimation and variable selection based on SCAD penalized censored regression model. We use the local linear approximation and the iteratively reweighted least squares algorithm to solve SCAD penalized log likelihood function. The proposed method provides an efficient method for variable selection and regression function estimation. The generalized cross validation function is presented for the model selection. Applications of the proposed method are illustrated through the simulated and a real example.

• Bulletin of the Korean Mathematical Society
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• v.55 no.4
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• pp.1303-1315
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• 2018

For principal component analysis (PCA) to efficiently analyze large scale matrices, it is crucial to find a few singular vectors in cheaper computational cost and under lower memory requirement. To compute those in a fast and robust way, we propose a new stochastic method. Especially, we adopt the stochastic variance reduced gradient (SVRG) method [11] to avoid asymptotically slow convergence in stochastic gradient descent methods. For that purpose, we reformulate the PCA problem as a unconstrained optimization problem using a quadratic penalty. In general, increasing the penalty parameter to infinity is needed for the equivalence of the two problems. However, in this case, exact penalization is guaranteed by applying the analysis in [24]. We establish the convergence rate of the proposed method to a stationary point and numerical experiments illustrate the validity and efficiency of the proposed method.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1201-1210
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• 2002

A penalty frame method is proposed for the coupled analysis of finite elements with independently modeled substructures. Although previously reported hybrid interface method by Aminpour et al (IJNME, Vol 38, 1995) is accurate and reliable, it requires non-conventional special solution algorithm such as multifrontal solver. In present study, an alternative method has been developed using penalty frame constraints, which results in positive symmetric global stiffness matrices. Thus the conventional skyline solver or band solver can be utilized in the solution routine, which makes the present method applicable in the environment of conventional finite element commercial software. Numerical examples show applicability of the present method.

• Journal of the Korean Mathematical Society
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• v.57 no.5
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• pp.1267-1286
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• 2020

We pay attention to a coupled problem by a penalty term which is induced from non-overlapping domain decomposition methods based on augmented Lagrangian methodology. The coupled problem is composed by two parts mainly; one is a problem associated with local problems in non-overlapping subdomains and the other is a coupled part over all subdomains due to the penalty term. For the speedup of iterative solvers for the coupled problem, we propose two different types of preconditioners: a block-diagonal preconditioner and an additive Schwarz preconditioner as overlapping domain decomposition methods. We analyze the coupled problem and the preconditioned problems in terms of their condition numbers. Finally we present numerical results which show the performance of the proposed methods.

• Computers and Concrete
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• v.16 no.4
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• pp.587-604
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• 2015

The hybrid-type penalty method (HPM) is suitable for representing failure phenomena occurring during the transition from continua to discontinua in materials such as concrete. Initiation and propagation of dominant cracks and branching of cracks can easily be modeled as a discrete crack. The HPM represents a discrete crack by eliminating the penalty that represents the separation of the elements at the intersection boundary. This treatment is easy because no change in the degrees of freedom for the discrete crack is necessary. In addition, it is important to evaluate the correct deformation of the continua before the crack formation is initiated. To achieve this, we implemented a constitutive model of concrete for the HPM. In this paper, we explain the implemented constitutive model and describe the simulation of an anchor bolt pullout test using the HPM demonstrating its capability for evaluating progressive failure.