• International Journal of CAD/CAM
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• v.12 no.1
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• pp.9-19
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• 2012

Generation of optimum planar B-spline curve in terms of minimum deviation and required fairness to approximate a target shape defined by a strip-shaped unorganized 2D point cloud is studied. It is proposed to use the location of control points as variables within the geometric optimization framework of point distance minimization. An adaptive simulated annealing heuristic optimization algorithm is developed to iteratively update an initial approximate curve towards the target shape. The new implementation comprises an adaptive cooling procedure in which the temperature change is adaptively dependent on the objective function evolution. It is shown that the proposed method results in an improved convergence speed when compared to the standard simulated annealing method. A couple of examples are included to show the applicability of the proposed method in the surface model reconstruction directly from point cloud data.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.10a
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• pp.193-198
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• 1993

This paper presents a systematic procedure to obtain shape functions of the infinite elements for soil-structure interaction analysis. The function spaces are derived from the analytical solutions and appropriate assumptions based on physical interpretation. The function spaces are complete for the surface wave components, but approximate for the body wave components. Three different infinite elements are developed by using the wave functions of the derived function spaces. Numerical example analysis is presented for demonstrating the effectiveness of the present infinite elements.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.645-655
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• 2011

Chandrasekar et al. (2004) introduced a generalized Type-II hybrid censoring. In this paper, we propose generalized doubly Type-II hybrid censoring. In addition, this paper presents the statistical inference on the scale parameter for the half logistic distribution when samples are generalized doubly Type-II hybrid censoring. The approximate maximum likelihood(AMLE) method is developed to estimate the unknown parameter. The scale parameter is estimated by the AMLE method using two di erent Taylor series expansion types. We compar the AMLEs in the sense of the mean square error(MSE). The simulation procedure is repeated 10,000 times for the sample size n = 20; 30; 40 and various censored samples. The $AMLE_I$ is better than $AMLE_{II}$ in the sense of the MSE.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.383-388
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• 2009

In this paper we propose a variance function estimation method based on kernel trick for replicated data or data consisted of sample variances. Newton-Raphson method is used to obtain associated parameter vector. Furthermore, the generalized approximate cross validation function is introduced to select the hyper-parameters which affect the performance of the proposed variance function estimation method. Experimental results are then presented which illustrate the performance of the proposed procedure.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.507-516
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• 2007

Multinomial logistic regression is probably the most popular representative of probabilistic discriminative classifiers for multiclass classification problems. In this paper, a kernel variant of multinomial logistic regression is proposed by combining a Newton's method with a bound optimization approach. This formulation allows us to apply highly efficient approximation methods that effectively overcomes conceptual and numerical problems of standard multiclass kernel classifiers. We also provide the approximate cross validation (ACV) method for choosing the hyperparameters which affect the performance of the proposed approach. Experimental results are then presented to indicate the performance of the proposed procedure.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.3
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• pp.256-264
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• 2012

A general procedure for the optimal design of a micro-channel heat exchanger for heat pump systems is presented. For this design, a performance analysis program that can reflect the various geometric variables of the micro-channel heat exchanger was developed. The deviation between simulated and experiment results of previous research was within 4% for the heat transfer rate. To prove the feasibility of the optimal design process, the performance of the reference heat exchanger was compared to that of the optimized heat exchanger. The $JF_{air}$ and PECv of the optimized heat exchanger were enhanced by 14% and 26%, respectively.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.457-465
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• 2004

Ramik[7] introduced a fuzzy goal programming (FGP)problem that generalizes a standard goal programming (GP) problem with fuzzy alternatives, fuzzy objective functions and fuzzy deviation functions for measuring the deviation between attained and desired goals being fuzzy. However, it is known that this FGP tends to produce an approximate solution since it uses an approximate fuzzy multiplication operation to solve the resultant fuzzy model. In this paper, we show that this FGP sometimes leads to the wrong decision. We also propose a procedure that gets the exact solution to overcome these problems. The method is based on $T_M$ (min norm)-based fuzzy operations using $\alpha-cut$ representations. We consider the same example as used in Ramik and investigate how our procedures are compared to Ramik's.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.47-52
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• 1999

In this paper we propose new approximate method for the performance analysis of closed-loop production system with unreliable machines and random processing times. The approximate method decomposes the production system consisting of K machines into a set of K subsystems, each subsystem consisting of two machines separated by a finite buffer. Then, each subsystem is analyzed by analyzing method n isolation. The population constraint of the closed-loop production system is taken into account by prescribing that the sum of average buffer level in the subsystems is equal to the number of customers in the closed-loop production system,. We establish a set of equations that characterizes unknown parameters of the servers in the subsystems. An iterative procedure is then used to determine the unknown parameters. Experimental results show that these methods provide a good estimation of the throughput.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.633-641
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• 2014

The exponential distibution is one of the most popular distributions in analyzing the lifetime data. In this paper, we propose multiply Type I hybrid censoring. And this paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply Type I hybrid censoring. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator (MLE) of the scale parameter ${\sigma}$ under the proposed multiply Type I hybrid censored samples. We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The $AMLE_{II}$ is better than $AMLE_I$ in the sense of the RMSE.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.240-253
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• 1999

In this paper we propose new approximate methods for the performance analysis of closed-loop production systems with unreliable machines and random processing times. Each approximate method decomposes the production system consisting of K machines into a set of K subsystems, each subsystem consisting of two machines separated by a finite buffer. Then, each subsystem is analyzed by three different analyzing methods in isolation. The population constraint of the closed-loop production system is taken into account by prescribing that the sum of average buffer levels in the subsystems is equal to the number of customers in the closed-loop production system. We establish a set of equations that characterize unknown parameters of the servers in the subsystems. An iterative procedure is then used to determine the unknown parameters. Experimental results show that these methods provide a good estimation of the throughput.