• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.163-172
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• 2004

A fast, accurate model for calculating roll gap variables are critical to the implementation of computer based automation systems for cold rolling mills. Based on the work of Fleck and Johnson, rollgap simulator with non-circular arc model was developed using the influence function. This developed model is capable of predicting values of force, torque and slip which can be applied over the wide range of rolling conditions including cold rolling/DR/temper mill with high execution speed. Friction coefficient was obtained as a function of operation conditions through analyzing measured data. After combination of rollgap simulator with production strategy, draft schedule for No.3 RCM (Reversible Cold Rolling Mill) in Incheon works of Dongbu Steel was developed. This draft schedule will be installed in the setup computer of No.3 RCM replacing old Hitachi model.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.11-15
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• 1999

Monitoring of the cutting force signals in cutting process has been well emphasized in machine tool communities. Although the cutting force can be directly measured by a tool dynamometer, this method is not always feasible because of high cost and limitations in setup. In this paper an indirect cutting force monitoring system is developed so that the cutting force in turning process is estimated based on a AC spindle drive model. This monitoring system considers the cutting force as a disturbance input to the spindle drive and estimates the cutting force based on the inverse dynamic model. The inverse dynamic model represents the dynamic relation between the cutting force, the motor torque and the motor power. The proposed monitoring system is realized on a CNC lathe and its estimation performance is evaluated experimentally.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.566-567
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• 2013

In simulation model, when it's occurred model succession, the parent model is connected to child model. When the schoolzone system is constructed, it needs the module on networks. Hence, it is considerable about the zigbee based communication module so that this paper proposes the zigbee based schoolzone setup scheme.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.167-182
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• 1999

This article is concerned with the selection of subsets of predictor variables to be included in building the binary response probit regression model. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting promising subsets. This procedure reformulates the probit regression setup in a hierarchical normal mixture model by introducing a set of hyperparameters that will be used to identify subset choices. The appropriate posterior probability of each subset of predictor variables is obtained through the Gibbs sampler, which samples indirectly from the multinomial posterior distribution on the set of possible subset choices. Thus, in this procedure, the most promising subset of predictors can be identified as the one with highest posterior probability. To highlight the merit of this procedure a couple of illustrative numerical examples are given.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.1876-1878
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• 1998

For an analysis and simulation of the conducted EMI of switching converters, an accurate simulation model for MOSFET is needed. This paper presents a new modeling approach, which incorporates DC output characteristics and AC dynamics especially the parasitic capacitances. It uses Pspice ABM(Analog Behavioral Model) and the MOSFET parameters can be obtained from the Data sheet in the frequency range of interest for EMI analysis. The model verified with an experimental setup and the EMI for a test converter is analyzed with respect to the MOSFET switching waveforms.

• Journal of the Korea Society of Computer and Information
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• v.5 no.4
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• pp.69-75
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• 2000

This paper proposes a network intrusion detection model which can detect the insertion and evasion attacks. These attacks can be prevented when some kind of information are available in the network intrusion detection system. We classified these information with three categories and used each category at setup phase and executing Phase. Within the proposed model, all necessary information which are related with networks and operating systems are maintained in the database and created as a table. This table is used during intrusion detection. The overheads of database and table may be simple in this model.

• Journal of Welding and Joining
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• v.29 no.2
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• pp.94-101
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• 2011

A lumped mass damped vibratory model was proposed for quantitative understanding of welding machine characteristics. An experimental setup was developed to determine the mechanical parameters (moving mass m, equivalent stiffness k and damping c) which govern the dynamic mechanical response of the resistance spot welding machine. During the test, acceleration of the electrodes for each level of applied load was measured by accelerometer, filtered and numerically integrated to find the corresponding velocity and displacement. The machine dynamic parameters were determined by finding the unknowns of the proposed model with experimental data. A Simulink model was proposed to investigate the influence of these mechanical parameters on the welding process. The electrode response was simulated by changing values of stiffness and damping. It was observed that both of the machine parameters(c, k) have significant effect on the response of electrode head.

• Korean Management Science Review
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• v.31 no.3
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• pp.13-26
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• 2014

This paper considers an integrated one-vendor multi-buyer production-inventory model where the vendor manufactures multiple products in lot at their associated finite production rates. In the model, it is allowed for each product to be shipped in lot to the buyers even before the whole product production is not completed yet. Each product lot is dispatched to the associated buyer in a number of shipments. The buyers consume their products at fixed rates. The objective is to the production and shipment schedules in the integrated system, which minimizes the total cost per unit time. The total cost consists of production setup cost, inventory holding cost and shipment cost. For the model, an iterative optimal solution procedure with shipment consolidation policy incorporated. It is then tested through numerical experiments to show how efficient and effective the shipment consolidation policy is.

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.349-359
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• 2015

We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.513-532
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• 2022

In this paper, the use of Bayes factors and the deviance information criterion for model selection are compared in a Bayesian accelerated life testing setup. In Bayesian accelerated life testing, the most used tool for model comparison is the deviance information criterion. An alternative and more formal approach is to use Bayes factors to compare models. However, Bayesian accelerated life testing models with more than one stressor often have mathematically intractable posterior distributions and Markov chain Monte Carlo methods are employed to obtain posterior samples to base inference on. The computation of the marginal likelihood is challenging when working with such complex models. In this paper, methods for approximating the marginal likelihood and the application thereof in the accelerated life testing paradigm are explored for dual-stress models. A simulation study is also included, where Bayes factors using the different approximation methods and the deviance information are compared.