• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.205-208
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• 2001

A lumped electrical circuit is an approximate representation of the field within a curtain frequency range. The finite element modelling is a synonym of the equivalent circuit. The electric conduction field and electric potential wave field have been modelled by an admittance network and an LC low-pass filter network. Here in the present paper, the equivalent magnetic circuit representation is created for a magnetostatic field by the finite element modelling in two dimension.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.62-71
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• 2006

Development of an artificial reverberation algorithm with low memory requirements has been an issue of importance in applications such as mobile multimedia devices. One possible solution to this problem is to embed a time-varying all-pass filter to the feedback loop of the comb filter. In this paper, theoretical and perceptual analyses of reverberators embedding time-varying all-pass filters are presented. The analyses are to iud a perceptually acceptable degree of phase variation by the all-pass filter. Based on the analyses, we propose a new methodology of designing reverberators embedding time-varying all-pass filters. Through the subjective tests, we showed that, even with smaller memory, the proposed method is capable of providing perceptually comparable sound quality to the conventional methods involving time-invariant parameters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.59-66
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• 2010

Around a toll plaza, vehicles do such maneuvers as slow down, stop, and speed up to pay their tolls when they use ordinary toll gates. They can be expected more fuel consumptions compared to the vehicles which use the Hi-pass, a Korean type of Electronic Toll Collection System(ETCS). To measure the exact amount of difference between the two gas consumptions, we equipped a test vehicle with a measurement system and constructed a model toll gate on our test field. Through the field tests on fuel consumptions, we could confirm a 36.7 % of energy saving when the test car used the Hi-pass. Then we projected the result on the total traffic volumes which had used national expressway network for five months from January 2009. Projected to the whole traffic, potential cost savings reached 5.34 billion won. We expect this result be frequently mentioned of to prove the fuel efficiency of the Hi-pass system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.9
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• pp.904-911
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• 2011

This paper deals with transmission characteristics of a new dual resonant structure for designing waveguide band-pass filter. The structure which has a pass-band between two adjacent stop-bands in a single body consists of circular ridged aperture and four armed conducting patch. The dual resonant behavior of the structure can be represented by a combination of LC series and parallel resonant circuits. Also these resonant properties can be easily controlled by varying the geometry of the aperture and four armed conducting patch. Actually, the structure is fabricated on the microstrip substrate by use of etching technique so that it is formed an iris type resonator which can be easily put into the transverse plane of the waveguide. We use WR-90 standard waveguide, adapters, and VNA(vector network analyzer) to measure the resonant characteristics of the structure. It is very useful to design and to improve the cutoff skirts characteristics in the waveguide band-pass filter design area.

• The KSFM Journal of Fluid Machinery
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• v.13 no.5
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• pp.43-53
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• 2010

This study investigates a design optimization of a rotating two-pass rectangular cooling channel with staggered arrays of pin-fins. The radial basis neural network method is used as an optimization technique with Reynolds-averaged Navier-Stokes analysis of fluid flow and heat transfer with shear stress transport turbulent model. The ratio of the diameter to height of the pin-fins and the ratio of the streamwise spacing between the pin-fins to height of the pin-fin are selected as design variables. The optimization problem has been defined as a minimization of the objective function, which is defined as a linear combination of heat transfer related term and friction loss related term with a weighting factor. Results are presented for streamlines, velocity vector fields, and contours of Nusselt numbers, friction coefficients, and turbulent kinetic energy. These results show how fluid flow in a two-pass square cooling channel evolves a converted secondary flows due to Coriolis force, staggered arrays of pin-fins, and a $180^{\circ}$ turn region. These results describe how the fluid flow affects surface heat transfer. The Coriolis force induces heat transfer discrepancy between leading and trailing surfaces, having higher Nusselt number on the leading surface in the second pass while having lower Nusselt number on the trailing surface. Dean vortices generated in $180^{\circ}$ turn region augment heat transfer in the turning region and in the upstream region of the second pass. As the result of optimization, in comparison with the reference geometry, thermal performance of the optimum geometry shows the improvement by 30.5%. Through the optimization, the diameter of pin-fin increased by 14.9% and the streamwise distance between pin-fins increased by 32.1%. And, the value of objective function decreased by 18.1%.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2004.04a
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• pp.86-96
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• 2004

Identification of dynamics of short circulation during grade change operations in paper mills is very important for the effective plant operation. In the present study a prediction method of One Pass Retention(OPR) is proposed based on the neural network. The present method is used to analyze the dynamics of short circulation during grade change. Properties of the product paper largely depend upon the change in the OPR. In the present study the OPR is predicted from the training of the network by using grade change operation data. The results of the prediction are applied to the modeling equation to give flow rates and consistencies of short circulation.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.313-317
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• 2001

The approach to predict time series without neglecting the fluctuation in a short period is tried by using a digital FIR filter and a neural network. The differential waveform of the Nikkei average closing price is filtered by the FIR band-pass filter of 101 length. It is filtered into the five frequency bands of 0-1Hz, 1-2Hz, 2-3Hz, 3-4Hz and 4-5Hz by setting the sampling frequency 10Hz. The each filtered waveform is learned and forecasted by the neural network. The neural network of the back propagation method is adopted in the learning the waveform. By inputting the data of 20 days in the past, the prediction of 10 days ahead is carried out. After learning the time series of each frequency band by the neural network, the predicted data far each frequency band are obtained. The predicted waveforms of each frequency band are synthesized to obtain a final forecast. The waveform can be forecasted well as a whole.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1000-1002
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• 2005

In the Bluetooth piconet in which up to 7 slave devices can be connected simultaneously at one network instance, the wireless data expected to be sent over to the RF interface should be sliced by the unit of 1 micrometer, which is a requirement in the specification of the Bluetooth version 1.1. In this contribution, we have designed a digital low-pass filter which is able to slice the unstable analog signal fed from the RF interface to the Baseband, by the uniform unit of 1 micrometer, and is also capable of removing the possible noise which can be caused by the analog circuit system. The low-pass filter operated well in the various modes of the Bluetooth RF embedded Baseband chip such as sleep mode, normal mode, and high-speed mode at 12MHz, 24MHz, and 48MHz respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.286-293
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• 1999

A new control scheme using a torsional torque estimator based on a neural network is proposed and investigated for improving control characteristics of the high-performance motion control system. This control method presents better performance in the corresponding speed vibration response, compared with the disturbance observer-based control method. This result comes from the fact that the proposed neural network estimator keeps the self-learning capability, whereas the disturbance observer-based torque estimator with low pass filter should dbjust the time constant of the adopted filter according to the natural resonance frequency detemined by considering the system parameters varied. The simulation results shows the validity of the proposed control scheme.