• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.931-936
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• 1993

Optimal model following control scheme is to design the controller which makes the response of real system follow that of desirable model. This kind of design scheme is developed for first order system. We extends the scheme for second order system regarding the characteristics of mechanical second order system for vibration suppression of flexible structures. The model of mechanical second order system is obtained using suitable damping ratios and natural frequencies. Using this scheme, we can design the good controller which uses the characteristic of second order system. Numerical examples are presented which were used optimal model following control scheme.

• Journal of Distribution Research
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• v.1 no.1
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• pp.239-258
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• 1996

This study deals with the measurement of relational norms, a safeguard for sustained exchange relationshipsim marketing channel systems. Here, the relational norm items are hypothesized to have a second-order factor model, in which mine observed items originate from the three first-order factors and the first order factors in turn originate from a second-order factor. The three first order construe comprising a higher order norm are mutuality(equity in the distribution of benefits and burdens over the course of the exchange on a long term basis), flexibility(expectation of friendly adaption for possible circumstance changes), and solidarity (the degree to which the preservation of the unique and continuing relationship is internalized by the exchange partners as being important in and of itself). 113 research questionnaires are obtained from four industries such as construction, telecommunication, iron, and electric ＆ electronic industries, Reliability and nomological. discriminant validity are tested, and in using the confirmatory factor analysis of Lisrel 7.16, and the chi-square difference test it is tested which has a better satisfactory fit to the data, the first-order model or the second-order one. The results of this study indicates that relational norms have a second order construct. In the electric and electronic industry the model as a while has a satisfactory fit to the data and the relevant first- and second-order factor loading to the mutuality is not significant. Same Results are happened to the flexibility in the telecommunication industry and to the mutuality and flexibility in the inn industry. In sum, the model lends support to our construct, but it is difficult to apply the measurement model to all kinds of industries.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.71-80
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• 2001

Logistic regression model is one of the most popular linear models for a binary response variable and used for the estimation of probability function. In many practical situations, the probability function can be expressed by a bell shaped curve and such a function can be estimated by a second order logistic regression model. However, when the probability curve is asymmetric, the estimation results using a second order logistic regression model may not be precise because a second order logistic regression model is a symmetric function. In addition, even if a second order logistic regression model is used, the interpretation for the effect of second order term may not be easy. In this paper, in order to alleviate such problems, an estimation method for asymmetric probabiity curve based on a first order logistic regression model and iterative bi-section method is proposed and its performance is compared with that of a second order logistic regression model by a simulation study.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.4
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• pp.27-38
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• 1994

In this paper, a simplified model of a hydraulic actuator system for a low-band type active suspension system is derived. To reduce the order of model, time constants of each chamber in hydraulic system are neglected except that of an accumulator. And the dynamics of a spool in the pressure control valve is regarded as a first-order system. The step response and the frequency response of the simplified second-order simulation model exhibit a good agreement with those of the actual system as well as those of the tenth-order simulation model. It is possible to simplify the tenth-order model to the second-order one. The low-band type active suspension model is built up by combining of a quarter car model test rig to testify the validity of the simplified model. The experimental results of suspension characteristics show that the simplified second-order hydraulic actuator model is reasonable to describe the dynamics of the actual hydraulic actuator system for a low-band type active suspension system.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.595-610
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• 2021

Recently a few articles have derived robust first-order rotatable and D-optimal designs for the lifetime response having distributions gamma, lognormal, Weibull, exponential assuming errors that are correlated with different correlation structures such as autocorrelated, intra-class, inter-class, tri-diagonal, compound symmetry. Practically, a first-order model is an adequate approximation to the true surface in a small region of the explanatory variables. A second-order model is always appropriate for an unknown region, or if there is any curvature in the system. The current article aims to extend the ideas of these articles for second-order models. Invariant (free of the above four distributions) robust (free of correlation parameter values) second-order rotatable designs have been derived for the intra-class and inter-class correlated error structures. Second-order rotatability conditions have been derived herein assuming the response follows non-normal distribution (any one of the above four distributions) and errors have a general correlated error structure. These conditions are further simplified under intra-class and inter-class correlated error structures, and second-order rotatable designs are developed under these two structures for the response having anyone of the above four distributions. It is derived herein that robust second-order rotatable designs depend on the respective error variance covariance structure but they are independent of the correlation parameter values, as well as the considered four response lifetime distributions.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.6
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• pp.971-979
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• 2011

Palm Oil Mill Effluent (POME) is the mixed organic wastewater generated from palm oil industry. In this study, kinetic analysis with treating POME in an anaerobic hybrid reactor (AHR) was performed. Therefore, the AHR was monitored for its performances with respect to the changes of COD concentrations and hydraulic retention time (HRT). Batch tests were performed to find out the substrate removal kinetics by granular sludge from POME. Modified Stover Kincannon, First-order, Monod, Grau second-order kinetic models were used to analyze the performance of reactor. The results from the batch test indicate that the substrate removal kinetics of granular sludge is corresponds to follow Monod's theory. However, Grau second-order model were the most appropriate models for the continuous test in the AHR. The second order kinetic constant, saturation value constant, maximum substrate removal rate, and first-order kinetic constant were 2.60/day, 41.905 g/L-day, 39.683 g/L-day, and 1.25/day respectively. And the most appropriate model was Grau second-order kinetic model comparing the model prediction values and measured COD concentrations of effluent, whereas modified Stover-Kincannon model showed the lowest correlation.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.76-81
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• 2010

In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the second-order conditional maximum a posteriori (CMAP). In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the current observation and the speech activity decisions in the pervious two frames. Experimental results show that the proposed approach yields better results compared to the statistical model-based and the CMAP-based VAD using the LR test.

• Food Science of Animal Resources
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• v.43 no.2
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• pp.374-381
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• 2023

In a previous study, 'response surface methodology (RSM) using a fullest balanced model' was proposed to improve the optimization of food processing when a standard second-order model has a significant lack of fit. However, that methodology can be used when each factor of the experimental design has five levels. In response surface experiments for optimization, not only five-level designs, but also three-level designs are used. Therefore, the present study aimed to improve the optimization of food processing when the experimental factors have three levels through a new approach to RSM. This approach employs three-step modeling based on a second-order model, a balanced higher-order model, and a balanced highest-order model. The dataset from the experimental data in a three-level, two-factor central composite design in a previous research was used to illustrate three-step modeling and the subsequent optimization. The proposed approach to RSM predicted improved results of optimization, which are different from the predicted optimization results in the previous research.

• Bulletin of the Korean Chemical Society
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• v.16 no.11
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• pp.1119-1121
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• 1995

The method for the Schlo"gl model with the first order transition is extended to the Scho;gl model with the second order transition for a photochemical reaction. We obtain the explicit results of the time-dependent average and the time correlation function at the unstable steady state of the model in the neighborhood of the Gaussian white noise and then discuss the effect of noise on the dynamic properties.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.585-595
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• 2001

A second-order response surface model is often used to approximate the relationship between a response factor and a set of explanatory factors. In this article, we deal with canonical analysis in response surface models. For the interpretation of the geometry of second-order response surface model, standard errors and confidence intervals for the eigenvalues of the second-order coefficient matrix play an important role. If the confidence interval for some eigenvalue includes 0 or the estimate of some eigenvalue is very small (near to 0) with respect to other eigenvalues, then we are able to delete the corresponding canonical factor. We propose a formulation of criterion which can be used to select canonical factors. This criterion is based on the IMSE(=Integrated Mean Squared Error). As a result of this method, we may approximately write the canonical factors as a set of some important explanatory factors.