• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.223-232
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• 2005

In this paper, we propose a novel post-filtering algorithm with low computational complexity that improves the visual quality of decoded images using block boundary classification and simple adaptive filter (SAF). At first, each block boundary is classified into smooth or complex sub-region. And for smooth-smooth sub-regions, the existence of blocking artifacts is determined using blocky strength. And simple adaptive filtering is processed in each block boundary area. The proposed method processes adaptively, that is, a nonlinear 1-D 8-tap filter is applied to smooth-smooth sub-regions with blocking artifacts, and for smooth-complex or complex-smooth sub-regions, a nonlinear 1-D variant filter is applied to block boundary pixels so as to reduce the blocking and ringing artifacts. And for complex-complex sub-regions, a nonlinear 1-D 2-tap filter is only applied to adjust two block boundary pixels so as to preserve the image details. Experimental results show that the proposed algorithm produced better results than those of conventional algorithms both subjective and objective viewpoints.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.362-373
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• 2015

This study analysed the effectiveness of aluminium(Al) filter in the added compound filtration for the removal of characteristic radiation from high atomic number material by DQE and image evaluation. 1mm Al was applied to each 0.1, 0.2, 0.3 mm copper and befere and after use were evaluated. Beam quality and DQE were tested by IEC regulations and image quality was evaluated by PSNR, MAE, MSE, CNR, SNR and qualitative analysis was performed by 7 items for resolution and contrast from chest x-ray criteria of national cancer checkup. MTF 10 and 50% were the same by 4.6, 2.54 cycle/mm and NPS, DQE, PSNR MAE, MSE, CNR, SNR and qualitative analysis were all the same or slightly better when Al was not used. PSNR is over 30dB and all significant and at the qualitative analysis, the p-value of t-test was over 0.05. The DQE and image quality evaluation have little difference between before and after use of Al filter and it is effective to use the Al filter for the reduction of skin dose by removal of characteristic radiation.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.98-106
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• 2001

This paper presents external load disturbance compensation that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a dead beat observer that is well-known method. However it has disadvantage such as a noise amplification effect. To reduce of the effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. Although RLSM estimator is one of the most effective methods for online parameter identification, it is difficult to obtain unbiased result in this application. It is caused by disturbed dynamic model with external torque. The proposed RLSM estimator is combined with a high performance torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.188-195
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• 2004

This paper presents neural load torque observer that is used to deadbeat load torque observer and gain compensation by parameter estimator As a result, the response of the PMSM(permanent magnet synchronous motor) follows that nominal plant. The load torque compensation method is composed of a neural deadbeat observer To reduce the noise effect, the post-filter implemented by MA(moving average) process, is adopted. The parameter compensator with RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller The parameter estimator is combined with a high performance neural load torque observer to resolve the problems. The neural network is trained in on-line phases and it is composed by a feed forward recall and error back-propagation training. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against the load torque and the Parameter variation. A stability and usefulness are verified by computer simulation and experiment.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.E1
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• pp.17-24
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• 2001

For the purpose of collecting fog droplets as a function of size a new sampling method was developed in this study. Formation of 100$\pm$10㎛ thickness of polymeric water absorbent film (PWAF) on a nuclepore filter could be successfully realized. Also applicability of particle induced X-ray emission (PIXE) method to the chemical analysis of size-segregated fog droplets collected on PWAF was examined experimentally with synthetic fog droplets generated from a nebulizer. Absorption capacity of S-PAAS polymeric water absorbent shows marked decreases in the range less than 1 wt% and slight decrease between 1 and 3.5 wt% of every salt concentration. Dependency of absorption capacity on pH shows the maximum at pH 7. No apparent peak which can influence the quantitative analysis of elements dissolved and suspended in fog droplets was found at PIXE spectrum of PWAF blank. PWAF kept the original shape without rupture under the PIXE analytical conditions of beam intensity for 10 to 60 nA and irradiation time of 4∼5 min. It should be said that the proposed new technique in the work is helpful to get more detailed information of fog droplets, to clarify the fog formation processes, and to develop a model of acid deposition process.

• Journal of Environmental Science International
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• v.14 no.10
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• pp.937-944
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• 2005

Presently, aquatic plants are used for the water purification in inland water. This study was carried out to investigate the water purification effect of aquatic plants, Oenanthe javanica and Typha angustata, The experiment was conducted in outdoor flowing water was conducted for ten days, Water quality was measured in terms of water temperature, COD(chemical oxygen demand), SS(suspended solids), Total N, Total P. The results of field experimentation showed that hydraulic retention time was the earliest in July and August 2003, and there were not any particular changes of monthly water temperature in inflow water and outflow water. As we look at the changes taken place in inflow water and outflow water throughout the whole experiment period, the change of water quality in summer was salient, especially SS removal ratio showed distinguished change as $25\%$, when the pebble filter and aquatic were attached to it. The removal rate of COD, total N total P were $14,7\%,\;8\%\;and\;9\%$, respectively. In relating the length of water extension to the change in water quality, the water quality tended to get lower generally in proportion to hydraulic retention time.

• Journal of Power Electronics
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• v.8 no.4
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.92-95
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• 2001

This study presents neural load disturbance observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM fellows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. The proposed estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation, are shown in this paper.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.10
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• pp.573-580
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• 2002

This paper presents neural load disturbance observer that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a neural deadbeat observer. To reduce of the noise effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. The proposed estimator is combined with a high performance neural torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• Journal of Power Electronics
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• v.15 no.2
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• pp.399-410
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• 2015

A 6.5 V/50 kA high-frequency switching power supply (HSPS) system composed of 10 power modules is developed to meet the requirements of copper-foil electrolysis. The power module is composed of a two-leg pulse width modulation (PWM) rectifier and a DC/DC converter. The DC/DC converter adopts two full-wave rectifiers in parallel to enhance the output. For the two-leg PWM rectifier, the ripple of the DC-link voltage is derived. A composite control method with a ripple filter is then proposed to effectively improve the performance of the rectifier. To meet the process demand of copper-foil electrolysis, the virtual impedance-based current-sharing control method with load current full feedforward is proposed for n-parallel DC/DC converters. The roles of load current feedforward and virtual impedance are analyzed, and the current-sharing control model of the HSPS system is derived. Virtual impedance is used to adjust the current-sharing impedance without changing the equivalent output impedance, which can effectively reduce current-sharing errors. Finally, simulation and experimental results verify the structure and control method.