• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.88-93
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• 2020

Based on the capture-emission energy (CEE) maps of CMOS devices, a physics-informed machine learning model for the bias temperature instability (BTI)-induced threshold voltage shifts and low frequency noise is presented. In order to incorporate physics theories into the machine learning model, the integration of artificial neural network (IANN) is employed for the computation of the threshold voltage shifts and low frequency noise. The model combines the computational efficiency of IANN with the optimal estimation of Gaussian mixture model (GMM) with soft clustering. It enables full lifetime prediction of BTI under various stress and recovery conditions and provides accurate prediction of the dynamic behavior of the original measured data.

• Wind and Structures
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• v.25 no.5
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• pp.459-474
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• 2017

In this study an analytical expression is derived for the natural frequency of the wind turbine towers supported on flexible foundation. The derivation is based on a Euler-Bernoulli beam model where the foundation is represented by a stiffness matrix. Previously the natural frequency of such a model is obtained from numerical or empirical method. The new expression is based on pure physical parameters and thus can be used for a quick assessment of the natural frequencies of both the real turbines and the small-scale models. Furthermore, a relationship between the diagonal and non-diagonal element in the stiffness matrix is introduced, so that the foundation stiffness can be obtained from either the p-y analysis or the loading test. The results of the proposed expression are compared with the measured frequencies of six real or model turbines reported in the literature. The comparison shows that the proposed analytical expression predicts the natural frequency with reasonable accuracy. For two of the model turbines, some errors were observed which might be attributed to the difference between the dynamic and static modulus of saturated soils. The proposed analytical solution is quite simple to use, and it is shown to be more reasonable than the analytical and the empirical formulas available in the literature.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.786-791
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• 2005

This paper is concerned with the examination and evaluation concerning a tuning method of multivariable PID controllers based on partial model matching on frequency domain proposed by authors from practical view point. In this case, PID controller parameters are determined by minimizing the loss function defined by the difference between frequency response of ideal model transfer function and actual frequency response on several frequency points. The purpose of the paper is to examine and evaluate the performance of the method through actual experiments of MIMO liquid level experimental process control equipment.

• The Journal of the Acoustical Society of Korea
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• v.32 no.3
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• pp.252-261
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• 2013

The common speech recognition system displays higher recognition performance in a quiet environment, while its performance declines sharply in a real environment where there are noises. To implement a speech recognizer that is robust in different speech settings, this study suggests the method of Parallel Model Combination adaptation using frequency-variant based on environment-awareness (FV-PMC), which uses variants in frequency; acquires the environmental data for speech recognition; applies it to upgrading the speech recognition model; and promotes its performance enhancement. This FV-PMC performs the speech recognition with the recognition model which is generated as followings: i) calculating the average frequency variant in advance among the readily-classified noise groups and setting it as a threshold value; ii) recalculating the frequency variant among noise groups when speech with unknown noises are input; iii) regarding the speech higher than the threshold value of the relevant group as the speech including the noise of its group; and iv) using the speech that includes this noise group. When noises were classified with the proposed FV-PMC, the average accuracy of classification was 56%, and the results from the speech recognition experiments showed the average recognition rate of Set A was 79.05%, the rate of Set B 79.43%m, and the rate of Set C 83.37% respectively. The grand mean of recognition rate was 80.62%, which demonstrates 5.69% more improved effects than the recognition rate of 74.93% of the existing Parallel Model Combination with a clear model, meaning that the proposed method is effective.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.61-68
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• 2018

In this paper, we present an effective encryption algorithm for 3D printing models in the frequency domain of discrete cosine transform to prevent illegal copying, access in the secured storage and transmission. Facet data of 3D printing model is extracted to construct a three by three matrix that is then transformed to the frequency domain of discrete cosine transform. The proposed algorithm is based on encrypting the DC coefficients of matrixes of facets in the frequency domain of discrete cosine transform in order to generate the encrypted 3D printing model. Experimental results verified that the proposed algorithm is very effective for 3D printing models. The entire 3D printing model is altered after the encryption process. The proposed algorithm is provide a better method and more security than previous methods.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.22-29
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• 2015

Quadrotor is widely used in variable application nowadays. Due to its inherent unstable characteristics, control system to augment the stability is essential for quadrotor operation. To design control system and verify its performance through simulation, accurate dynamic model is required. Quadrotor dynamic model is simply compared with conventional rotorcraft such as helicopter. However, the accurate dynamic model of quadrotor is not easy to develop because of the highly correlated aerodynamic effect of each rotor. In this paper, quadrotor dynamic model is identified from the flight data using frequency domain approach. Flight test of quadrotor is performed in closed loop configuration with stability augmentation system included. Frequency sweep input is applied in each of lateral, longitudinal, yaw and heave axis separately. The bare dynamic model is identified from the flight data of quadrotor responses and thrust measurement through Pulse Width Modulation(PWM) data. The frequency responses of identified model match well with those of flight data, and time responses of identified model for doublet input in each axis are also shown to agree with flight data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2166-2172
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• 2007

In this study a low-signal equivalent circuit based on the Double Schottky Barrier model is proposed for ZnO-based varistor. Since pin-lead inductance and stray capacitance are considered in pin-lead type ZnO varistor these inductance and capacitance could be removed from the experimental dielectric data of the varistor. According to the equivalent circuit simulation results the higher the varistor-voltage of varistor sample the capacitance of dielectric layer is larger, and the capacitances of semiconducting layer and depletion layer are smaller, while the parallel resistances of semiconducting layer and depletion layer are more larger values. Spectra of the dielectric loss factor $tan{\delta}$ show 2 peaks in low frequency and high frequency regions respectively. The low-frequency peak is due to the relaxation by deep donors and the high-frequency peak is due to the relaxation by shallow donors. Above results are well consistent with the theoretical mechanism of ZnO varistor.

• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.13-24
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• 2013

The main objective of this study was to develop a new regional frequency analysis model based on hierarchical Bayesian model that allows us to better estimate and quantify model parameters as well as their associated uncertainties. A Monte-carlo experiment procedure has been set up to verify the proposed regional frequency analysis. It was found that the proposed hierarchical Bayesian model based regional frequency analysis outperformed the existing L-moment based regional frequency analysis in terms of reducing biases associated with the model parameters. Especially, the bias is remarkably decreased with increasing return period. The proposed model was applied to six weather stations in Jeollabuk-do, and compared with the existing L-moment approach. This study also provided shrinkage process of the model parameters that is a typical behavior in hierarchical Bayes models. The results of case study show that the proposed model has the potential to obtain reliable estimates of the parameters and quantitatively provide their uncertainties.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.2
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• pp.153-163
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• 2010

In this paper a frequency response analysis using Krylov subspace-based model reduction and its design sensitivity analysis with respect to design variables are presented. Since the frequency response and its design sensitivity information are necessary for a gradient-based optimization, problems of high computational cost and resource may occur in the case that frequency response of a large sized finite element model is involved in the optimization iterations. In the suggested method model order reduction of finite element models are used to calculate both frequency response and frequency response sensitivity, therefore one can maximize the speed of numerical computation for the frequency response and its design sensitivity. As numerical examples, a semi-monocoque shell and an array-type $4{\times}4$ MEMS resonator are adopted to show the accuracy and efficiency of the suggested approach in calculating the FRF and its design sensitivity. The frequency response sensitivity through the model reduction shows a great time reduction in numerical computation and a good agreement with that from the initial full finite element model.

• Smart Structures and Systems
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• v.25 no.3
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• pp.265-277
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• 2020

Recently, the concept of "drive-by" bridge monitoring system using indirect measurements from a passing vehicle to extract key parameters of a bridge has been rapidly developed. As one of the most key parameters of a bridge, the natural frequency has been successfully extracted theoretically and in practice using indirect measurements. The frequency of bridge is generally calculated applying Fast Fourier Transform (FFT) directly. However, it has been demonstrated that with the increase in vehicle velocity, the estimated frequency resolution of FFT will be very low causing a great extracted error. Moreover, because of the low frequency resolution, it is hard to detect the frequency drop caused by any damages or degradation of the bridge structural integrity. This paper will introduce a new technique of bridge frequency extraction based on Hilbert Transform (HT) that is not restricted to frequency resolution and can, therefore, improve identification accuracy. In this paper, deriving from the vehicle response, the closed-form solution associated with bridge frequency removing the effect of vehicle velocity is discussed in the analytical study. Then a numerical Vehicle-Bridge Interaction (VBI) model with a quarter car model is adopted to demonstrate the proposed approach. Finally, factors that affect the proposed approach are studied, including vehicle velocity, signal noise, and road roughness profile.