• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.171-175
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• 1990

A diagnostic test for detecting nonconstant variance in mixed linear models based on the score statistic is derived through the technique of model expansion, and compared to the log likelihood ratio test.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.403-414
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• 2000

A diagnostic tool for testing homogeneity for random effects is proposed in unbalanced linear mixed model based on score statistic. The finite sample behavior of the test statistic is examined using Monte Carlo experiments examine the chi-square approximation of the test statistic under the null hypothesis.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.603-613
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• 2001

A test based on score statistic is derived for detecting homoscedasticity of errors in unbalanced random effects linear model. A small simulation study is performed to investigate the finite sample behaviour of the test statistic which is known to have an asymptotic chi-square distribution under the null hypothesis.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.463-469
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• 2016

This paper presents a compression-friendly low power test scheme in EDT environment. The proposed approach exploits scan slices reusing to reduce the switching activity during shifting for test scheme based on linear decompressor. To avoid the impact on encoding efficiency from resulting control data, a counter is utilized to generate control signals. Experimental results obtained for some larger ISCAS'89 and ITC'99 benchmark circuits illustrate that the proposed test application scheme can improve significantly the encoding efficiency of linear decompressor.

• Journal of the Korea Concrete Institute
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• v.17 no.3 s.87
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• pp.313-322
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• 2005

Recently, as the remodeling market gradually substitute for new construction market and safety diagnosis for reconstruction apartment become a matter of principal Interest, it is demanded that scientific diagnosis and evaluation for existing concrete structure state. And it is increasing that the significance for reliability of data which is used for estimating the concrete compressive strength by nondestructive test. As a result, it is found that different proposal to material age and hitting angle is good to improving the reliability of presumption of concrete compressive strength in the linear hitting rebound test hammer. And for the reason that mutual relation between the compressive strength and rebound degree is highest in linear hitting rebound test hammer 25mm in all portion according to early md middle material age and hitting angle except the early material age $-45^{\circ}$, analysis showed that linear hitting rebound test hammer is more reliable than existing schmidt hammer in presumption of concrete compressive strength.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.95-103
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• 1998

Azzalini and Bowman proposed the pseudo-likelihood ratio test for checking the linear relationship using kernel regression estimator when the error of the regression model follows the normal distribution. We modify their method with the bootstrap technique to construct a new test, and examine the power of our test through simulation. Our method can be applied to the case where the distribution of the error is not normal.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2006.05a
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• pp.230-233
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• 2006

In this study, the effects of residual stress induced by plastic injection molding process on the tensile behavior of plastic tensile test specimen were investigated. To manufacture plastic tensile test specimens, an injection mold based on the international standard system was designed and made. Cavity pressure and temperature sensors were installed inside of the presented mold to monitor pressure and temperature values during the cycle of injection molding. Injection molding simulation was performed with the same condition of experiment and linear structural tensile analysis was also performed with the initial condition of the residual stress. It was shown that the residual stress induced by injection molding has an effect on the experiment of tensile test and linear structural tensile simulation.

• The Journal of Information Systems
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• v.4
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• pp.27-39
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• 1995

This study tests the fuzzy linear regression model to see if there is a performance difference between it and the classical linear regression model. These results show that FLR was better as f forecasting technique when compared with CLR. Another important find in the test of the two different regression methods is that they generate two different predicted P/E ratios from expected value test, variance test and error test of two different regressions, though we can not see a significant difference between two regression models doing test in error measurements (GMRAE, MAPE, MSE, MAD). So, in this financial setting we can conclude that FLR is not superior to CLR, comparing and testing between the t재 different regression models. However, FLR is better than CLR in the error measurements.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.5 s.248
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• pp.609-614
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• 2006

Recently linear motor has been used mainly for high speed feeding performance of machine tools. The advantages of linear motor are not only high speed but high accuracy, because it is not required the coupling and ballscrew for converting rotary to liner motion. Before applying in different moving system, the dynamometer is necessary to test the performance. In Korea, the linear motor is producing in a couple of company However, the liner motor dynamometer is not commercialized yet, like as rotary motor dynamometer. In this paper, a linear motor dynamometer is designed and manufactured using a MR damper. The dynamometer system developed in this study could be used for testing the positioning accuracy fur different loading conditions, traction forces, dynamic performance and so on.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.305-315
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• 2014

In a simple linear regression, a linear relationship between an explanatory variable and a response variable can be easily recognized in the scatter plot of them. The lack of fit test for the replicated data is commonly used for testing the linearity but it is not easy to test the linearity when the explanatory variable is not replicated. In this paper, we propose three new test statistics for testing the linearity regardless of replication using the principle of average slope and validate them through several simulations and empirical studies.