• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1980-1987
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• 1999

Restored image is always lower quality than original one due to distortion and noise. The purpose of image restoration is to improve the image quality by fixing the noise or distortion information. One category of spatial filters for image restoration is linear filter. This filter algorithm is easily implemented and can be suppressed the Gaussian noise effectively, but not so good performance for spot or impulse noise. In this paper, we propose the nonlinear spatial filter algorithm for image restoration called the optimal adaptive multistage filter(OAMF). The OAMF is used to reduce the filtering time, increases the noise suppression ratio and preserves the edge information. The OAMF optimizes the adaptive multistage filter(AMF) by using weight learning algorithm of back-propagation learning algorithm. Simulation results of this filter algorithm are presented and discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.798-801
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• 2014

Nowadays, the demand for multimedia services has grown with the rapid evolution in the digital era. But due to external causes in the process of processing, transmitting and storing image data, the images are damaged. One of the major causes of such damage is known to be noise. Some of the most commonly used methods for removing noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter). However, these filters all leave a bit to be desired in removing noise in a complex noise environment. Therefore this paper suggest an image restoration filter algorithm that first judges the noise and sets a adjustment weight based on the median value and distance of the mask to remove the complex noise. For an objective analysis, the results were compared against existing methods and the PSNR(peak signal to noise ratio) was used as a reference.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.1
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• pp.103-109
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• 2016

The performance of a multi-head, computerized combination scaling system to automatically identify a group of agricultural products having a total weight within the target range has been optimized to reduce the package cycle time of the merchandise. First, the structure of the scale was modified to enable faster measurement by enhancing the dynamic stability during the process. Second, the high frequency noise in the measured signal was eliminated by a high frequency filter to provide more accurate weight data. Finally, the algorithm to identify a group of products with a total weight within the target range was modified to enable a user to select an optimal number of scales. According to the experimental verifications, this modified system reduced the package cycle time significantly and also was accurate in measuring the total weight of the selected products.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.97-104
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• 2009

Recently, simultaneous localization and mapping (SLAM) approaches employing Rao-Blackwellized particle filter (RBPF) have shown good results. However, due to the usage of the accurate sensors, distinct particles which compensate one another are attenuated as the RBPF-SLAM continues. To avoid this particle depletion, we propose the strategic games to assign the particle's payoff which replaces the importance weight in the current RBPF-SLAM framework. From simulation works, we show that RBPF-SLAM with the strategic games is inconsistent in the pessimistic way, which is different from the existing optimistic RBPF-SLAM. In addition, first, the estimation errors with applying the strategic games are much less than those of the standard RBPF-SLAM, and second, the particle depletion is alleviated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.5
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• pp.416-425
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• 2013

A hybrid PN code phase acquisition system based on a least-mean-square adaptive filter, interpreted as a channel estimator is proposed and analyzed for direct-sequence spread-spectrum systems under frequency selective Rayleigh fading channels. Closed form expressions are derived for the filter tap weights and detection/false alarm probabilities. Compared to previously proposed systems, the proposed system achieves smaller mean acquisition times, is more robust to the operating signal-to-noise ratio and allows for multiplication free tap weight updates.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.1
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• pp.18-22
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• 2012

In this paper, we propose an equivalent Wiener-Hopf equation. The proposed algorithm can obtain the weight vector of a TDL(tapped-delay-line) filter and the error simultaneously if the inputs are orthogonal to each other. The equivalent Wiener-Hopf equation was analyzed theoretically based on the MMSE(minimum mean square error) method. The results present that the proposed algorithm is equivalent to original Wiener-Hopf equation. In conclusion, our method can find the coefficient of the TDL (tapped-delay-line) filter where a lattice filter is used, and also when the process of Gram-Schmidt orthogonalization is used. Furthermore, a new cost function is suggested which may facilitate research in the adaptive signal processing area.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1677-1688
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• 1993

Two dimensional amplitude scrambling algorithm using the hopping filter, which improve the drawback of conventional speech encryption scheme, is powerful encryption scheme in analog sppech signal. In this paper, we proposed the variable delay weight algorithm using hopping filter in order to solve the synchronization problem of two dimensional amplitude scrambling. Futhermore, analyzing the distortion of received signal which is transmitted in the gaussian noise channel, we determined the optimal encryption algorithm and optimal SNR using the simulation.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.E
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• pp.325-331
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• 1994

Organic extracts of diesel- exhaust particulates were analyzed for mutagenicity using Ames Salmonella typhimurium assay system. An experimental diesel microbus used was drived on the chassis dynamometer according to CVS-75 mode. The samples were taken from the mixed gases in a dilution tunnel. With a high-volume air sampler equipped with double filter holders, particulate matters were collected on a teflon-coated glass fiber filter placed behind a activated carbon filter. After ultrasonic extraction with benzene- ethanol and evaporation to dryness, the residue was dissolved in dimethylsulfoxide. Each sample was tested toward 2 strains, TA100 and TA98 by the pre-incubation method in the absence and presence of S-9mix. Average concentration of diesel- exhaust particulates was about 116.6mg/m$^3$, and 44.1~62.2 ％ to the total weight of particulates, consisted of organic matters. The mutagenicities of diesel- exhaust particulate organic matters were 4,512 and 2,205 revertants/m$^3$ toward TA100 without and with S-9mix, respectively. Those toward TA98 were 13,367 and 3,715 revertants/m$^3$, respectively.

• Journal of environmental and Sanitary engineering
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• v.16 no.1
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• pp.40-46
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• 2001

Conventional membrane systems was difficult to treatment for pulp and paper mills waste warter. Technological advances in membrane filtration systems have created opportunity for pulp and paper mills to treat effluent streams in order to meet stricter environmental constraints. "Vibratory Shear Enhanced Processing(VSEP)" developed by new logic international makes if possible to filter effluent streams without the fouling problems exhibited by conventional membrane systems. Various kinds of waste water occurred to and paper mills experiment with "VSEP" set up conventional membrane. The results were as followes : Excepting ultra filter($0.1{\mu}\textrm{m}$ Teflon, C-100, G-50), Nano filter(NTR-7450, DS-5, PVD-1) and reverse osmosis(ACM-4) was treated with very excellent weight of treatment, electric conductivity, removal COD, TDS, turbidity.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.255-263
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• 2012

This paper presents the smart interacting multiple model (SIMM) using the concept of predicted point and maximum noise level. Maximum noise level means the largest value of the mere noises. We utilize the positional difference between measured point and predicted point as acceleration. Comparing this acceleration with the maximum noise level, we extract the acceleration to recognize the characteristics of the target. To estimate the acceleration, we propose an optional algorithm utilizing the proposed method and the Kalman filter (KF) selectively. Also, for increasing the effect of estimation, the weight given at each sub-filter of the interacting multiple model (IMM) structure is varying according to the rate of noise scale. All the procedures of the proposed algorithm can be implemented by an on-line system. Finally, an example is provided to show the effectiveness of the proposed algorithm.