• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.1
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• pp.1-11
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• 2000

An accurate technique to retrieve HEMT modeling parameters with measurements of S-parameters and DC characteristics of HEMT is proposed. The extrinsic series resistances among HEMT modeling parameters are determined by the FUKUI method using the measured DC characteristics. And other parameters are determined by the measured S-parameters by HP 8510C Network Analyzer with various values of DC bias. The transconductance retrieved from the measured S-parameters, however, shows only 0.078% error comparing with the measured gm values. Therefore, the S-parameters measured directly for an individual transistor should be used for an accurate determination of the model parameters. The procedure for the retrieval of the circuit modeling parameters redescribed in detail in this thesis.

• ETRI Journal
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• v.28 no.2
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• pp.182-190
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• 2006

The circuit modeling of interdigitated capacitors fabricated by high-k low-temperature co-fired ceramic (LTCC) sheets was investigated. The s-parameters of each test structure were measured from 50 MHz to 10 GHz, and the modeling was performed using these measured sparameters up to the first resonant frequency. Each test structure was divided into appropriate building blocks. The equivalent circuit of each building block was composed based on the partial element equivalent circuit (PEEC) method. Modeling was executed to optimize the parameters in the equivalent circuit of each building block. The validity of the extracted parameters was verified by the predictive modeling for the test structures with different geometry. After that, Monte Carlo analysis and sensitivity analysis were performed based on the extracted parameters. The modeling methodology can allow a device designer to improve the yield and to save time and cost for the design and manufacturing of devices.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2546-2550
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• 2003

We propose a new method of robot manipulator modeling. Different from existing modelers, our modeler provides a convenient robot modeling configured from modules from module library or module modeling. In addition, a way of using D-H parameters to configure a robot is proposed. These additional functions of robot modeling can be a powerful and flexible tool for various needs of robot modeling. We show an example of modeling with our approach.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.893-898
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• 1994

In this paper, the influence of voice source estimation and modeling on speech synthesis and coding is examined and then their new estimation and modeling techniques are proposed and verified by computer simulation. It is known that the existing speech synthesizer produced the speech which is dull and inanimated. These problems are arised from the fact that existing estimation and modeling techniques can not give more accurate voice parameters. Therefore, in this paper we propose a new voice source estimation algorithm and modeling techniques which can not give more accurate voice parameters. Therefore, in this paper we propose a new voice source estimation algorithm and modeling techniques which can represent a variety of source characteristics. First, we divide speech samples in one pitch region into four parts having different characteristics. Second, the vocal-tract parameters and voice source waveforms are estimated in each regions differently using sequential SVD. Third, we propose composite source model as a new voice source model which is represented by weighted sum of pre-defined basis functions. And finally, the weights and time-shift parameters of the proposed composite source model are estimeted uning EM(estimate maximize) algorithm. Experimental results indicate that the proposed estimation and modeling methods can estimate more accurate voice source waveforms and represent various source characteristics.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.3
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• pp.383-388
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• 2014

This paper describes a wave modeling method using low-cost sensors. Wave modeling is applied to the wave monitoring system for accurate measurement of ocean wave parameters. The observation of ocean wave parameters is necessary to improve the accuracy of forecast of ocean wave condition. However, the ocean wave parameters measured by a low-cost wave monitoring system suffer from several errors. Therefore we introduce a wave modeling method to compensate the ocean wave parameters corrupted by errors. The proposed method is analyzed using experiments within controlled environment. It is verified that the accuracy of low-cost wave monitoring system can be increased by the proposed method.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.601-610
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• 2008

This paper deals with a new geometrical surface modeling method of forebody's hull form which is fully defined by form parameters. The complex hull form in the forebody can be modeled by the combination of three parts: bare hull, bulbous bow and blending part which connects a bare hull and a bulbous bow. All these subdomain parts are characterized by each own form parameters and constructed with simple surface model. For this, we need only 2-dimensional hull form data and then the form parameters are calculated automatically from these data. Finally, the smooth hull form surfaces are generated by parametric design and fair-skinning. In the practical point of view, we show that this new method can be useful and efficient modeling tool by applying to the hull form surface modeling of Panamax container's forebody.

• Smart Structures and Systems
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• v.15 no.3
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• pp.717-733
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• 2015

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.519-522
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• 2006

Accurate modeling of a dynamic system from experimental data is the bases for the model updating or heath monitoring of the system. Modal analysis or modal test is a routine process to get the modal parameters of a dynamic system. The modal parameters include the natural frequencies, damping ratios and mode shapes. This paper presents a new method that can derive the equations of motion for a dynamic system from the modal parameters obtained by the modal analysis or modal test. The present method based on the relation between the eigenvalues and eigenvectors of the state space equation derives the mass, damping and stiffness matrices of the system. The modeling of a cantilevered beam from modal parameters is an example to prove the efficiency and accuracy of the present method. Using the lateral displacements only, not the rotations, gives limited information for the system. The numerical verification up to now gives reasonable results and the verification with the test data is scheduled.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.410-419
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• 2018

Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.3
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• pp.227-234
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• 2020

This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.