• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2184-2196
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• 1998

Admission control is one of the most important congestion control mechanism to be executed at the call set up phase by regulating traffic into a network in a preventive way. An efficient QOS evaluation or bandwidth estimation method is required for call admission to be decided in real time. In this paper, we spropose a computtionally simple approximation method of estimating cell loss probability and mean cell delay for admission control of both delay sensitive and loss sensitive calls. Mixed input queueing system, where a new call combines with the existing traffic, is used as a queueing model for QOS estimation. Also traffic parameters are suggested to characterize both a new call and existing traffic. Aggregate traffic is approximated by a renewal process with these traffic parameters and then mean delay and cell loss probability are detemined using appropriate approximation formulas. The accuracy of this approximation approach is examined by comparing their results with exact analysis or simulation results of vrious mixed unput queueing systems. Based on this QOS estimation method, call admission control scheme which is traffic independent and computable in yeal time are proposed.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.375-386
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• 2024

Autonomous weapon systems act according to artificial intelligence-based judgement based on recognition through various sensors. Test and evaluation for various scenarios is required depending on the characteristics that artificial intelligence-based judgement is made. As a part of this approach, this paper proposed a LiDAR point cloud augmentation method for mixed-reality based test and evaluation. The augmentation process is achieved by mixing real and virtual LiDAR signals based on the virtual LiDAR synchronized with the pose of the autonomous weapon system. For realistic augmentation of test and evaluation purposes, appropriate intensity values were inserted when generating a point cloud of a virtual object and its validity was verified. In addition, when mixing the generated point cloud of the virtual object with the real point cloud, the proposed method enhances realism by considering the occlusion phenomenon caused by the insertion of the virtual object.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1095-1102
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• 2011

The classical two-period, two-sequence crossover design is no longer sufficient to assess various demands in a bioequivalence study. For instance, to estimate the within-subject and between-subject variances of test and reference formulations separately, it is necessary to use a replicate design in which each subject receives at least the reference formulation in two periods. Several designs were studied to satisfy the demands. It is provided a unified Bayesian approach applicable to those study designs. The benefit of the method in the bioequivalence study is discussed.

• East Asian mathematical journal
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• v.31 no.5
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• pp.627-634
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• 2015

In this paper, we investigate the following orthogonally additive-quadratic functional equation f(2x + y) - f(x + 2y) - f(x + y) - f(y - x) - f(x) + f(y) + f(2y) = 0. and prove the generalized Hyers-Ulam stability for it in orthogonality spaces by using the fixed point method.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.1
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• pp.43-49
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• 2012

In this paper, we investigate the stability of a functional equation $$f(x+y+z)-f(x+y)-f(y+z)-f(x+z)+f(x)+f(y)+f(z)=0$$ by using the fixed point theory in the sense of L. $C\breve{a}dariu$ and V. Radu.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.3
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.197-202
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• 1992

In this paper, we consider the synthesis of mixed H$_{2}$/H$_{\infty}$ controllers such that the closed-loop poles are located in a specified region in the complex plane. Using solution to a generalized Riccati equation and a change of variable technique, it is shown that this synthesis problem can be reduced to a convex optimization problem over a bounded subset of matrices. This convex programming can be further reduced to Generalized Eigenvalue Minimization Problem where Interior Point method has been recently developed to efficiently solve this problem..

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.41-50
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• 2000

Cell formation(CF) Is to group parts with similar geometry, function, material and process into part families, and the corresponding machines into machine cells. Cell formation solutions often contain exceptional elements(EEs). Also, the following objective functions - minimizing the total costs of dealing with exceptional elements and maximizing total similarity coefficients between parts - have been used in CF modeling. Thus, multiobjective programming approach can be developed to model cell formation problems with two conflicting objective functions. This paper presents an effective cell formation method with fuzzy multiobjective nonlinear mixed-integer programming simultaneously to form machine cells and to minimize the cost of eliminating EEs.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.971-978
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• 2009

Poisson generalized linear mixed models(GLMMs) have been widely used for the analysis of clustered or correlated count data. For the inference marginal likelihood, which is obtained by integrating out random effects is often used. It gives maximum likelihood(ML) estimator, but the integration is usually intractable. In this paper, we propose how to obtain the ML estimator via Laplace approximation based on hierarchical-likelihood (h-likelihood) approach under the Poisson GLMMs. In particular, the h-likelihood avoids the integration itself and gives a statistically efficient procedure for various random-effect models including GLMMs. The proposed method is illustrated using two practical examples and simulation studies.

• Transactions of Materials Processing
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• v.8 no.5
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• pp.507-519
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• 1999

An approach using the energy method has veen proposed for the analysis of cone spinning having the complicated deformation modes mixed by shear and normal deformation. In the proposed method, the corresponding solution is found through optimization of the total energy dissipation with respect to the parameters assumed by the velocity field defined as the variation of the length in longitudinal direction. The sheet blank is divided into three layers to consider the bending effect and the energy dissipated by shear deformation is superposed to the energy consumption due to normal deformation related with the shrinking deformation is superposed to the energy consumption due to normal deformation related with the shrinking deformation of axi-symmetric sheet element for the evaluation of total deformation energy. In order to check the validity of the proposed method, the complex spinning for making the conical cup is analyzed and the computed results are compared with the experimental results. In comparison of the computed results with existing experimental results,, the good agreement is obtained for the variation of outer radius and the distribution of thickness, and it has thus been shown that the present approach is applicable to the analysis of complex spinning.