• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.489-499
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• 2000

We propose a new instrumental variable estimator of the complex parameter of a class of univariate complex-valued diffusion processes defined by the possibly non-stationary and/or nonlinear stochastic differential equations. On the basis of the exact finite sample distribution of the pivotal quantity, we construct the exact confidence intervals and the exact tests for the parameter. Monte-Carlo simulation suggests that the new estimator seems to provide a viable alternative to the maximum likelihood estimator (MLE) for nonlinear and/or non-stationary processes.

• The Korean Journal of Food And Nutrition
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• v.29 no.5
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• pp.605-609
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• 2016

This study aimed to find the optimum instrumental test conditions for the Texture Profile Analysis (TPA) of cooked rice in order to predict the sensory texture attributes (hardness, adhesiveness, chewiness). Sensory evaluation was performed for three kinds of instant cooked rice with university students in their twenties and the results of the sensory evaluation were compared to instrumental TPA patterns. Using partial least squares regression, the instrumental TPA results at a cross-head speed of 1.0 mm/sec and a compression ratio of 70% proved to be an excellent predictor of the sensory attributes of hardness ($R^2=0.99$) and chewiness ($R^2=0.99$). The results at a cross-head speed of 0.5 mm/sec and compression ratio of 30% provided an excellent model for the prediction of sensory adhesiveness ($R^2=0.83$). In this experimental range, sensory hardness and chewiness showed a high correlation with instrumental TPA parameters (hardness, cohesiveness, adhesiveness, springiness, chewiness) with a high cross-head speed and compression ratio, while sensory adhesiveness showed a high correlation with the TPA parameters with a low cross-head speed and compression ratio.

• Journal of KSNVE
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• v.6 no.5
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• pp.679-684
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• 1996

The Instrumental Variable Method(IVM), modified from least square algorithm, is applied to parameter identification of a noise contaminated bearing test rig. The signal to noise ratio included in Frequency Response Function(FRF) can cause significant errors in parameter identification. Therefore, among several candidates of parameter identification method, results of the applied IVM were compared with noise-contaminated least square method. This study shows that the noise-contaminated least square method can have indonsistent accuracy depending on the degree of noise level, while the IVM has robuster performance to signal to noise ratio than least square method.

• Korean Journal of Food Science and Technology
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• v.48 no.5
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• pp.521-524
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• 2016

This study aimed to examine variations in the texture profile analysis (TPA) of cooked rice in relation to the instrumental parameter conditions. The TPA of four types of ready-to-eat, white rice products was conducted in two levels of compression ratio (30 and 70%) and cross-head speed (0.5 and 1.0 mm/s). The properties of the four rice products significantly or non-significantly differed, depending on the instrumental parameter condition. Agglomerative hierarchical clustering, based on the five TPA properties such as hardness, adhesiveness, cohesiveness, chewiness, and springiness, revealed that clustering of the four rice products varied with the instrumental parameter condition. Additionally, the ratio of adhesiveness to hardness, an index of rice texture quality, showed a variation depending on the two instrumental parameter conditions. In conclusion, our findings demonstrate that the texture profile, texture-based sample clustering, and the ratio of adhesiveness to hardness vary with the compression ratio and cross-head speed in the TPA.

• Korean Journal of Food Science and Technology
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• v.25 no.6
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• pp.620-625
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• 1993

This experiment was carried out to predict the sensory properties of yogurt by instrumental methodology. Sensory attributes such as viscosity, mouth-feel, taste and quality were investigated. Instrumental parameters were measured with refractometer, viscometer, consistometer and rheometer. Sensory data showed that viscosity of peach yogurt was higher than that of strawberry and tropical-fruit-mixed (TFM) yogurts (p<.05). All instrumental parameters of peach yogurt were higher than those of strawberry and TFM yogurts, except cohesiveness and elasticity (p<.05). Viscosity measured by panelists was significantly correlated with instrumental viscosity, consistency, hardness, adhesiveness and gumminess in the fruit yogurts (p<.05). But mouth-feel and quality of yogurts showed poor relationships with instrumental parameters. The effective instrumental parameters for predicting sensory viscosity ($Y_{1}$) of yogurts were consistency ($X_{1}$), viscosity ($X_{2}$) and cohesiveness ($X_{3}$). And those for predicting mouth-feel ($Y_{2}$) were consistency. The estimated regression equations were as follows; $Y_{1}=4.968-0.0486X_{1}+0.00012X_{2}+0.0348X_{3},\;Y_{2}=5.701+0.0154X_{1}$.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1045-1050
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• 1988

The problem of applying the linear integral filter in analysis and parameter estimation of linear continuous systems is discussed. A discrete-time model, which is equivalent to that obtained using the bilinear z transformation, is derived and employed to predict system output. It is shown that the output error can be controlled through the sampling interval. In order to obtain unbiased estimates, an instrumental variable (IV) method is proposed, where the instrumental variables are constituted using adaptive filtering. Some problems on implementation of the recursive IV algorithm are discussed. Both theoretical analysis and simulation study are given to illustrate the proposed methods.

• Computational Structural Engineering
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• v.2 no.4
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• pp.111-116
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• 1989

Methods for the estimation of the coefficient matrices in the equation of motion for a linear multi-degree-of-freedom structure are studied. For this purpose, the equation of motion is transformed into an auto-regressive and moving average with auxiliary input(ARMAX) model. The ARMAX parameters are evaluated using several methods of parameter estimation : such as the least squares, the instrumental variable, the maximum likelihood and the limited information maximum likelihood methods. Then the parameters of the equation of motion are recovered therefrom. Numerical example is given for a 3-story building model subjected to an earthquake exitation.

• Nuclear Engineering and Technology
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• v.42 no.1
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• pp.55-64
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• 2010

The KIER's Korean historical earthquake catalog was revised for MMI${\geq}$VI events recorded from the years 27 A.D. to 1904. the magnitude of each event was directly determined from the criteria suggested by Seo. The criteria incorporated the damage phenomena of the Japanese historical earthquake catalog, recent seismological studies, and the results of tests performed on ancient structures in Korea. Thus, the uncertainty of the magnitudes of the Korean historical earthquakes can be reduced. Also, the Gutenberg-Richter parameter values were estimated based on the revised catalog of this study. It was determined that the magnitudes of a maximum inland and minimum offshore event were approximately 6.3 and 6.5, respectively. The Gutenberg-Richter parameter pairs of the historical earthquake catalog were estimated to be a=5.32${\pm}$0.21, b=0.95${\pm}$0.19, which were somewhat lower than those obtained from recent complete instrumental earthquakes. No apparent change in the Gutenberg-Richter parameter is observed for the $16^{th}-17^{th}$ centuries of the seismically active period.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.10a
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• pp.46-50
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• 1989

Methods for the estimation of the coefficient matrices in the equation of motion for a linear multi-degree-of-freedom structure arc studied. For this purpose, the equation of motion is transformed into an auto-regressive and moving average with auxiliary input (ARMAX) model. The ARMAX parameters are evaluated using several methods of parameter estimation; such as toe least squares, the instrumental variable, the maximum likelihood and the limited Information maximum likelihood methods. Then the parameters of the equation of motion are recovered therefrom. Numerical example is given for a 3-story building model subjected to an earthquake exitation.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.214-217
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• 1987

In this paper self tuning control of interconnected systems are dealt in view point of large scale system control. The plant model is given in multiple ARMA process. This process is simplified as independent SISO ARMA process having offset terms. This offset was considered as effects of interconnections. In each decentralized system, self tuning controller with instrumental variable method is adopted. As a result, this algorithm enables the parameter estimation to be unbiased and non-drift. This controller contains a new implicit offset rejection technique. Simulation results considers well with the analysis in case of linear interconnection.