• Nonlinear Functional Analysis and Applications
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• v.26 no.5
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• pp.917-933
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• 2021

In this paper, we investigate the behavior and sensitivity analysis of a solution set for a parametric generalized multi-valued nonlinear quasi-variational inclusion problem in a real Hilbert space. For this study, we utilize the technique of resolvent operator and the property of a fixed-point set of a multi-valued contractive mapping. We also examine Lipschitz continuity of the solution set with respect to the parameter under some appropriate conditions.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.1
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• pp.20-27
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• 2003

In this study, we designed and made Ultrasonic motor-digital multi controller(USM-DMC) using FPGA chip, A54SX72A made in Actel Corporation. By the minute, USM-DMC can adjust the frequency, duty ratio, and phase difference parameters of USM by digital input to be each 11bit from PC. Therefore, when we use this controller, it is possible to apply typical three parameters individually as well as multi-parameters simultaneously to control the speed and the torque. What is more, the strongest point is that it can trace frequency based on optimized frequency as compared with the phase difference because we can input optimized resonant frequency while in motoring. And we test the speed of USM with the adjustment of multi-parameters, the phase difference-frequency. As the result of the test, in the case of the multi-parameters of the phase difference and frequency, the speed characteristic is more linear and stable, and wider in the range of control than the single-parameter of the phase difference or the frequency.

• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.3133-3141
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• 2011

The next generation domestic high speed railway system is a power distributed type and uses vector control method for motor speed control. Nowadays, inverter driven induction motor system is widely used. However, recently PMSM drives are deeply considered as a alternative candidate instead of an induction motor drive system due to their advantages in efficiency, noise reduction and maintenance. The next-generation high speed train is composed of 2 converter units, 4 inverter units, and 4 Traction Motor units. Each motor is connected to the inverter directly. In this paper, the effect of IPMSM parameter variations to the system operation characteristics of the multi inverter drive high speed train system are investigated. The parallel connected inverter input-output characteristics are analyzed to the parameter mismatches of IPMSM using the 1C1M control simulator based on Matlab/Simulink.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.8 s.227
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• pp.984-988
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• 2004

This study presents the process of the solenoid parameter estimation of an common-rail injector fer HSDI(High Speed Direct Injection) diesel engines. The EMF(Electromotive Force) and solenoid inductance are the major parameters for presenting the injector dynamics, and also these parameters are estimated by using a multi-layer feedforward artificial neural networks(ANN). The performances of parameter estimators are verified by the simulation with injector model. The feasibility of this methodology is closely examined through the simulation in the various operating points of injector. The simulation results have revealed that estimated parameters show favorable agreements with the common-rail injector model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.20-24
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• 2008

A bid-based pool(BBP) model is representative of energy market structure in a number of restructured electricity markets. Supply function equilibrium(SFE) models of interaction better match what is explicitly required in the bid formats of typical BBP markets. Many of the results in the SFE literature involve restrictive parametrization of the bid cost functions. In the SFE models, two parameters, intercept and slope, are available for strategic bidding. This paper addresses the realistic competition format that players can choose both parameters arbitrarily. In a fixed demand function, equilibrium conditions for generation company's profit maximization have a degree of freedom, which induces multi-equilibrium. So it is hard to choose a convergent equilibrium. However, consideration of stochastic demand function makes the equilibrium conditions independent each other based on the amount of variance of stochastic demand function. This variance provides the bidding players with incentives to change the slope parameter from an equilibrium for a fixed demand function until the slope parameter equilibrium.

• Journal of Integrative Natural Science
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• v.13 no.3
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• pp.92-96
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• 2020

Taguchi's robust parameter design is an approach to reduce the performance variation of quality characteristics in products and processes. In robust design, the signal-to-noise ratio (SN ratio) was used to find the optimum condition to minimize the variation of quality characteristics as much as possible and bring the average of quality characteristics closer to the target value. In this paper, we propose a simultaneous optimization method based on a linear model of the SN ratio as a method to find the optimal condition of the control factor in case of multi-characteristics. In addition, the proposed method and the existing method were compared and studied by taking actual cases.

• ETRI Journal
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• v.35 no.6
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• pp.990-1000
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• 2013

This paper describes the scalable extension of High Efficiency Video Coding (HEVC) to provide flexible high-quality digital video content services. The proposed scalable codec is designed on multi-loop decoding architecture to support inter-layer sample prediction and inter-layer motion parameter prediction. Inter-layer sample prediction is enabled by inserting the reconstructed picture of the reference layer (RL) into the decoded picture buffer of the enhancement layer (EL). To reduce the motion parameter redundancies between layers, the motion parameter of the RL is used as one of the candidates in merge mode and motion vector prediction in the EL. The proposed scalable extension can support scalabilities with minimum changes to the HEVC and provide average Bj${\o}$ntegaard delta bitrate gains of about 24% for spatial scalability and of about 21% for SNR scalability compared to simulcast coding with HEVC.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.49-52
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• 2003

In this paper, we propose new speech feature parameter using NMf(Non-Negative Matrix Factorization). NMF can represent multi-dimensional data based on effective dimensional reduction through matrix factorization under the non-negativity constraint, and reduced data present parts-based features of input data. In this paper, we verify about usefulness of NMF algorithm for speech feature extraction applying feature parameter that is got using NMF in Mel-scaled filter bank output. According to recognition experiment result, we could confirm that proposal feature parameter is superior in recognition performance than MFCC(mel frequency cepstral coefficient) that is used generally.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.11a
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• pp.211-214
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• 2005

This research studied robust design of composite structure under combined loading of bending and torsion. DOE (Design of Experiment) technique was used to find important design factors. The results show that the beam height, beam width, layer thickness and stack angle of outer-layer are important design parameter. The $2^{nd}$ DOE and RSM (Response Surface Model) were conducted to obtain optimum design. Multi-island genetic algorithm was used to optimum design. An approximate value of 6.65 mm in deflection was expected under optimum condition. Six sigma robust design was conducted to find out guideline for control range of design parameter. To acquire six sigma level reliability, the sigma level reliability, the standard deviation of design parameter should be controlled within 2.5 % of average design value.