• Structural Engineering and Mechanics
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• v.65 no.4
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• pp.369-380
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• 2018

In this paper, a multi-layered finite element model for laminated glass plates is introduced. A layer-wise theory is applied to the analysis of laminated glass due to the combination of stiff and soft layers; the independent layers are connected via Lagrange multipliers. The von $K{\acute{a}}rm{\acute{a}}n$ large deflection plate theory and the constant Poisson ratio for constitutive equations are assumed to capture the possible effects of geometric nonlinearity and the time/temperature-dependent response of the plastic foil. The linear viscoelastic behavior of a polymer foil is included by the generalized Maxwell model. The proposed layer-wise model was implemented into the MATLAB code and verified against detailed three-dimensional models in ADINA solver using different hexahedral finite elements. The effects of temperature, load duration, and creep/relaxation are demonstrated by examples.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1871-1877
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• 2000

Longitudinal and lateral forces acting at tire are known to be closely related to the tractive ability, braking characteristics, handling stability and maneuverability of ground vehicles. However, it is not feasible in the operating vehicles to measure the tire forces directly because of high cost of sensors, limitations in sensor technology, interference with the tire rotation and harsh environment. In this paper, in order to develop tire force monitoring system, a new vehicle dynamics monitoring model is proposed including the roll motion. Based on the monitoring model, tire force monitoring system is designed to estimate the lateral tire force acting at each tire. A newly proposed SKFMEC (Scaled Kalman Filter with Model Emr Compensator) method is developed utilizing the conventional EKF (Extended Kalman Filter) method. Tire force estimation performance of the SKFMEC method is evaluated in the Matlab simulations where true tire force data is generated from a 14 DOF vehicle model with a combined-slip Magic Formula tire model.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.541-549
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• 2001

The term 'silent period(SP)' refers to a transitory, relative or absolute decrease electromyography(EMG) activity, evoked in the midst of an otherwise sustained contraction. Masseteric SP is elicited by a tap on the chin during isometric contraction of masseter muscle. In this paper, a new EMG signal generation model including SP in masseter muscle is proposed. This work is based on the anatomical structure of trigeminal nerve system that related on temporomandibular joint(TMJ) dysfunction. And it was verified by comparing the real EMG signals including SP in masseter muscle to the simulated signals by the proposed model. Through this studies, it was shown that SP has relation to variable neurophysiological phenomena. A proposed model is based on the control system theory and DSP(Digital Signal Processing) theory, and was simulated using MATLAB simulink. As a result, the proposed SP model generated EMG signals which are similar to real EMG signal including normal SP and an abnormal extended SP. This model can be applied to the diagnosis of TMJ dysfunction and can effectively explain the origin of extended SP.

• Journal of Power Electronics
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• v.13 no.3
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• pp.429-436
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• 2013

Online simulations are utilized to reduce time and cost in the development and performance optimization of plug-in hybrid electric vehicle (PHEV) and electric vehicles (EV) systems. One of the most important factors in an online simulation is the accuracy of the model. In particular, a model of a battery should accurately reflect the properties of an actual battery. However, precise dynamic modeling of high-capacity battery systems, which significantly affects the performance of a PHEV, is difficult because of its nonlinear electrochemical characteristics. In this study, a dynamic model of a high-capacity battery cell for a PHEV is developed through the extraction of the equivalent impedance parameters using electrochemical impedance spectroscopy (EIS). Based on the extracted parameters, a battery cell model is implemented using MATLAB/Simulink, and charging/discharging profiles are executed for comparative verification. Based on the obtained results, the model is optimized for a high-capacity battery cell for a PHEV. The simulation results show good agreement with the experimental results, thereby validating the developed model and verifying its accuracy.

• Journal of Power Electronics
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• v.13 no.6
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• pp.1080-1089
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• 2013

In this paper, the superposition principle of a heat sink temperature rise is verified based on the mathematical model of a plate-fin heat sink with two mounted heat sources. According to this, the distributed coupling thermal impedance matrix for a heat sink with multiple devices is present, and the equations for calculating the device transient junction temperatures are given. Then methods to extract the heat sink thermal impedance matrix and to measure the Epoxy Molding Compound (EMC) surface temperature of the power Metal Oxide Semiconductor Field Effect Transistor (MOSFET) instead of the junction temperature or device case temperature are proposed. The new thermal impedance model for the power converters in Switched Reluctance Motor (SRM) drivers is implemented in MATLAB/Simulink. The obtained simulation results are validated with experimental results. Compared with the Finite Element Method (FEM) thermal model and the traditional thermal impedance model, the proposed thermal model can provide a high simulation speed with a high accuracy. Finally, the temperature rise distributions of a power converter with two control strategies, the maximum junction temperature rise, the transient temperature rise characteristics, and the thermal coupling effect are discussed.

• Structural Engineering and Mechanics
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• v.71 no.6
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• pp.683-697
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• 2019

The reinforced concrete (RC) structures usually suffer large residual displacements under strong motions. The large residual displacements may substantially reduce the anti-seismic capacity of structures during the aftershock and increase the difficulty and cost of structural repair after an earthquake. To reduce the adverse residual displacement, several self-centering energy dissipation braces (SCEBs) have been proposed to be installed to the RC structures. To investigate the seismic responses of the RC structures with SCEBs under the earthquake excitation, an extended Bouc-Wen model with degradation and self-centering effects is developed in this study. The extended model realized by MATLAB/Simulink program is able to capture the hysteretic characteristics of the RC structures with SCEBs, such as the energy dissipation and the degradation, especially the self-centering effect. The predicted hysteretic behavior of the RC structures with SCEBs based on the extended model, which used the unscented Kalman filter (UKF) for parameter identification, is compared with the experimental results. Comparison results show that the predicted hysteretic curves can be in good agreement with the experimental results. The nonlinear dynamic analyses using the extended model are then carried out to explore the seismic performance of the RC structures with SCEBs. The analysis results demonstrate that the SCEB can effectively reduce the residual displacements of the RC structures, but slightly increase the acceleration.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.425-430
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• 2022

A pumped storage power station is an important means to solve the problem of peak load regulation and ensures the safety of power grid operation. The doubly fed variable-speed pumped storage (DFVSPS) system adopts a doubly fed induction machine (DFIM) to replace the synchronous machine used in traditional pumped storage. The stator of DFIM is connected to the power grid, and the three-phase excitation windings are symmetrically distributed on the rotor. Excitation current is supplied by the converter. The active and reactive power of the unit can be quickly adjusted by adjusting the amplitude, frequency, and phase of the rotor-side voltage or current through the converter. Compared with a conventional pumped storage hydropower station (C-PSH), DFVSPS power stations have various operating modes and frequent start-up and shutdown. This study introduces the structure and principle of the DFVSPS unit. Mathematical models of the unit, including a model of DFIM, a model of the pump-turbine, and a model of the converter and its control, are established. Fast power control strategies are proposed for the unit model. A 300 MW model of the DFVSPS unit is established in MATLAB/Simulink, and the response characteristics in generating mode are examined.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.163-178
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• 2023

GARCH-X(1, 1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo-Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCHX(1, 1) model. In general, based on the Akaike information criterion, the GARCH-X(1, 1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen's independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.156-157
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• 2022

The purpose of this study is to propose a 40MPa mortar mixed design model that applies the neural network theory to minimize wasted effort in trial and error. A mixed design model was applied to each of the 60 data using fly ash, blast furnace slag fine powder and thickened rice husk powder. And in the neural network model, the optimized connection weight was obtained by repeatedly applying it to the MATLAB. The completed mixed design model was demonstrated by analyzing and comparing the predicted values of the mixed design model with those measured in the actual compressive strength test. As a result of the mixed design verification experiment, the error rates of the double mixed non-cement mortar using blast furnace slag fine powder and rice husk powder at a height of 40MPa were 3.24% and 3.4%. Mixed with fly ash and rice husk powder had an error rate of 3.94% and 5.8%. The error rate of the triple mixed non-cement mortar of the rice husk powder, fly ash, and blast furnace slag fine powder was 2.5% and 5.1%.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.115-120
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• 2023

Plant leaf diseases and destructive insects are major challenges that affect the agriculture production of the country. Accurate and fast prediction of leaf diseases in crops could help to build-up a suitable treatment technique while considerably reducing the economic and crop losses. In this paper, Convolutional Neural Network based model is proposed to detect leaf diseases of a plant in an efficient manner. Convolutional Neural Network (CNN) is the key technique in Deep learning mainly used for object identification. This model includes an image classifier which is built using machine learning concepts. Tensor Flow runs in the backend and Python programming is used in this model. Previous methods are based on various image processing techniques which are implemented in MATLAB. These methods lack the flexibility of providing good level of accuracy. The proposed system can effectively identify different types of diseases with its ability to deal with complex scenarios from a plant's area. Predictor model is used to precise the disease and showcase the accurate problem which helps in enhancing the noble employment of the farmers. Experimental results indicate that an accuracy of around 93% can be achieved using this model on a prepared Data Set.