• Proceedings of the KSME Conference
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• 2001.11a
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• pp.778-784
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• 2001

Injection molding is a very important industrial process for the manufacturing of plastics objects. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of weld-line parts in injection-molded products is assessed. And the effects of fiber content and injection molding conditions on the fiber orientation functions are also discussed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.1-7
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• 2006

Injection molding is a very important industrial process for the manufacturing of plastics objects. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of weld-line in injection-molded products is assessed. And the effects of fiber content and injection mold-gate conditions on the fiber orientation are also discussed.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.253-267
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• 2004

In some clinical trials, one may see that a significant fraction of patients are cured and their original disease does not recur even after termination of treatment and pro-longed follow-up. This situation occurs frequently in pediatric cancer trials where there are excellent therapeutic results. In such cases, interest concentrated on the difference of cure rates rather than other types of differences in failure distributions. Various authors have investigated the parametric and nonparametric methods for testing the difference of cure rates. In this study, we compare by simulation the power and size of a parametric test and five nonparametric tests in a various range of the alternatives, censoring rates and cure rates. Our objectives are to determine if any test was preferable on the basis of size and power in various situation, and to investigate the effect of the model misspecification.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.265-270
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• 2000

Injection molding is a very important industrial process for the manufacturing of plastics objects. During an injection molding process of composites, the fiber-matrix separation and fiber orientation are caused by the flow of molten polymer/fiber mixture. As a result, the product tends to be nonhomogeneous and anisotropic. Hence, it is very important to clarify the relations between separation· orientation and injection molding conditions. So far, there is no research on the measurement of fiber orientation using image processing. In this study, the effects of fiber content ratio and molding condition on the fiber orientation-angle distributions are studied experimentally. Using the image processing method, the fiber orientation distribution of weld-line parts in injection-molded products is assessed. And the effects of fiber content and injection molding conditions on the fiber orientation functions are also discussed

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.55 no.12
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• pp.601-605
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• 2006

The resistance-capacitance (RC) delay of signals through interconnection materials becomes a big hurdle for high speed operation of semiconductors which contain multi-layer interconnections in smaller scales with higher integration density. Low-k materials are applied to the inter-metal dielectric (IMD) materials in order to overcome the RC delay. Relaxation continuum (RCT) model that includes neutral-species transport model have developed to model the etching process in a capacitively coupled plasma (CCP) device. We present the parametric study of the modeling results of a two-frequency capacitively coupled plasma (2f-CCP) with $N_2/H_2$ gas mixture that is known as promising one for organic low-k materials etching. For the etching of low-k materials by $N_2/H_2$ plasma, N and H atoms have a big influence on the materials. Moreover the distributions of excited neutral species influence the plasma density and profile. We include the neutral transport model as well as plasma one in the calculation. The plasma and neutrals are calculated self-consistently by iterating the simulation of both species till a spatio-temporal steady state profile could be obtained.

• Journal of ILASS-Korea
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• v.4 no.2
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• pp.19-32
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• 1999

The present study investigated the forms and behaviors of fuel during intake and compression process, and the initial flame stability in a lean burn engine modified as a single cylinder engine equipped with quartz windows for visualization. PLIF(Planar Laser Induced Fluorescence) method with KrF Excimer laser was used for measuring the fuel distributions. The principal design concept of the lean burn nin in this study is the axial stratification in the fuel distribution via fuel injection during intake process and different shapes of intake ports; helical and straight. The experiments showed that fuel flowed in as a vapor state in the early part of intake process and lots of this mixture mated down along the intake valve side cylinder wall, but in the latter part, a lot of fuel flowed in as a liquid state and this fuel stayed in the upper part of cylinder, after that the dense fuel cloud moved upward in the early of part compression process. It became clear that the fuel flowed in via straight port had a important role in the axial fuel stratification.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.10
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• pp.1285-1293
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• 2000

In port fuel injection system of SI engines, injected fuel is impinged onto the surface of intake valves and port-wall, and then formed the wall flow under the cold start operation. Wall flows entrained into the cylinder result in the unsteady and nonuniform mixture formation. Therefore, the spray impingement to the wall is considered as having negative influences such as lowering combustion efficiency and causing unburned hydrocarbon emissions. This study investigates the spray characteristics of the wall impinging air-assist spray in suction air flow. A PDPA was used to analyze the flow characteristics under the different conditions such as impingement angle and supplied air. Experimental data concerning the impinging sprays has been obtained in the vicinity of the wall. Measured droplets divided into the pre-impinging droplets which denote as the positive normal velocities and post-impinging droplets that describe as the negative normal velocities for the suction flow. Their velocities, size distributions and SMD are comparatively analyzed before and after the impingement.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.975-989
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• 2014

Lasso (Tibshirani, 1996) and Elastic Net (Zou and Hastie, 2005) have been widely used in various fields for simultaneous variable selection and coefficient estimation. Bayesian methods using a conditional Laplace and a double Pareto prior specification have been discussed in the form of hierarchical specification. Full conditional posterior distributions with each priors have been derived. We compare the performance of Bayesian lassos with Laplace prior and the performance with double Pareto prior using simulations. We also apply the proposed Bayesian hierarchical models to real data sets to predict the collapse of governments in Asia.

• Speech Sciences
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• v.15 no.2
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• pp.55-65
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• 2008

Recently, the multi-model based speech recognizer has been used quite successfully for noisy speech recognition. For the selection of the reference HMM (hidden Markov model) which best matches the noise type and SNR (signal to noise ratio) of the input testing speech, the estimation of the SNR value using the VAD (voice activity detection) algorithm and the classification of the noise type based on the GMM (Gaussian mixture model) have been done separately in the multi-model framework. As the SNR estimation process is vulnerable to errors, we propose an efficient method which can classify simultaneously the SNR values and noise types. The KL (Kullback-Leibler) distance between the single Gaussian distributions for the noise signal during the training and testing is utilized for the classification. The recognition experiments have been done on the Aurora 2 database showing the usefulness of the model compensation method in the multi-model based speech recognizer. We could also see that further performance improvement was achievable by combining the probability density function of the MCT (multi-condition training) with that of the reference HMM compensated by the D-JA (data-driven Jacobian adaptation) in the multi-model based speech recognizer.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.489-498
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• 2004

In this paper, a new form of linear models referred to as generalized weighted linear models is proposed. The proposed models assume that the relationship between the response variable and explanatory variables can be modelled by a distribution function of the response mean and a weighted linear combination of distribution functions of covariates. This form addresses a structural problem of the link function in the generalized linear models in which the parameter space may not be consistent with the space derived from linear predictors. The maximum likelihood estimation with Lagrange's undetermined multipliers is used to estimate the parameters and resampling method is applied to compute confidence intervals and to test hypotheses.