• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12C
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• pp.1208-1215
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• 2009

In OFDM systems, mobile channel degrades the system performance seriously. Therefore, channel estimation technique is required to compensate for the degradation from the channel effects. However, conventional channel estimations in frequency domain induce ICI which is induced from Doppler frequency. In addition, a linear interpolation method causes inaccurate channel estimation. In order to minimize the effect of the interference and interpolation error, the proposed method combines LS method and Kalman filtering algorithm. Channel impulse response is adaptively tracked by Kalman filtering based on the information from LS estimator. Simulation results are presented to verify the performance of the proposed channel estimation over mobile channel environment. Simulation results show that the proposed method can effectively compensate for channel degradation.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.3
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• pp.174-178
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• 2015

This paper describes a signal processing technique for identifying signals from defects by using an electromagnetic-ultrasonic guided waves method based on a magnetostrictive sensor that generates a torsional mode (T(0, 1)). Because this technique is based on the digital filtering, the filtered signals provide information on the relationship between the cutoff frequency of band-pass filter and the characteristic of defect signals in heat exchange tubes. To verify the performance of the technique, artificial defects with various thickness reduction ration and shape were machined in titanium tubes, and digital filtering results are reported. The results show that digital filtering provides information to the identify shape of defects and the contact condition between the tube and support ring. Therefore, the proposed technique has good potential as a tool for evaluating the integrity of heat exchange tubes.

• ETRI Journal
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• v.45 no.2
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• pp.338-345
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• 2023

A filtering power divider based on air-filled substrate-integrated waveguide (AFSIW) technology is proposed in this study. The AFSIW structure is used in the proposed filtering power divider for substantially reducing the transmission losses. This structure occupies a large area because of the use of air as a dielectric instead of typical dielectric materials. A filtering power divider provides power division and frequency selectivity simultaneously in a single device. The proposed filtering power divider comprises three AFSIW cavities. The filtering function is achieved using symmetrical inductive posts. The input and output ports of the proposed circuit are realized by directly connecting coaxial lines to the AFSIW cavities. This transition from the coaxial line to the AFSIW cavity eliminates the additional transitions, such as AFSIW-SIW and SIW-conductor-backed coplanar waveguide, applied in existing AFSIW circuits. The proposed power divider with a second-order bandpass filtering response is fabricated and measured at 5.5 GHz. The measurement results show that this circuit has a minimum insertion loss of 1 dB, 3-dB fractional bandwidth of 11.2%, and return loss exceeding 11 dB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.752-758
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• 2012

SNS(Social Networking Services) is oneline service that enable users to construct human network through their relation on web, such as following relation, friend relation, and etc. Recently, owing to the advent of digital devices (smart phone, tablet PC) which embedded GPS some applications which provide services with spatial relevance and social relevance have been released. Such an online service is called LBSNS. It is required to use spatial filtering so as to build the LBSNS system that enable users to subscribe information of interesting area. For spatial filtering, user and tweet attaches location information which divide into static property presenting fixed area and dynamic property presenting user's area changed along the moving user. In the case of using a location information including dynamic property, Continuous query occurred from the moving user causes the problem in server. In this paper, we propose spatial filtering algorithm using Virtual Grid for reducing frequency of query, and conclude that frequency of query on using Virtual Grid is 93% decreased than frequency of query on not using Virtual Grid.

• 전자공학회논문지 IE
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• v.48 no.1
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• pp.51-56
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• 2011

In this paper, a variety of digital image processing technique was applied to improve the quality of medical images which is a chest CR image. And the image quality was performed. On the other hand, the high-frequency emphasis filtering and the histogram equalization were realized by MATLAB programs to better the contrast of the chest CR image. As a result of simulation, the sharpness of the original image was elevated by the high-frequency emphasis filtering and the histogram equalization. To evaluate the degree which is improved the image quality by the digital image processing, the subjective evaluation is used by the observation of the image. The sensitivity which is the probability to find a signal or a lesion is calculated. The sensitivity of the image performed the high-frequency emphasis filtering and the histogram equalization became more improved than that of the original and the digital image processing performed in the medical image improved the quality of the image.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1004-1019
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• 2021

To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image's high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high- and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.143-151
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• 2012

A new data-driven method for the design of a blind modulation frequency filter that suppresses the slow-varying noise components is proposed. The proposed method is based on the temporal local decorrelation of the feature vector sequence, and is done on an utterance-by-utterance basis. Although the conventional modulation frequency filtering approaches the same form regardless of the task and environment conditions, the proposed method can provide an adaptive modulation frequency filter that outperforms conventional methods for each utterance. In addition, the method ultimately performs channel normalization in a feature domain with applications to log-spectral parameters. The performance was evaluated by speaker-independent isolated-word recognition experiments under additive noise environments. The proposed method achieved outstanding improvement for speech recognition in environments with significant noise and was also effective in a range of feature representations.

• Journal of IKEEE
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• v.22 no.4
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• pp.1242-1245
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• 2018

In this paper, we have implemented a network that overcomes the over-blurring phenomenon that occurs when removing Gaussian noise. In the conventional filtering method, blurring of the original image is performed to remove noise, thereby eliminating high frequency components such as edges and corners. We propose a network that reducing over blurring while maintaining denoising performance by adding denoised high frequency components to denoisers based on CNN.

• Journal of Mechanical Science and Technology
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• v.18 no.2
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• pp.253-261
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• 2004

A simple and effective filtering method to control the member size of an optimized structure is proposed for topology optimization. In the present approach, the original objective sensitivities are replaced with their relative values evaluated within a filtering area. By adjusting the size of the filtering area, the member size of an optimized structure or the level of its topological complexity can be controlled even within a given finite element mesh. In contrast to the checkerboard-free filter, the present filter focuses on high-frequency components of the sensitivities. Since the present filtering method does not add a penalty term to the objective function nor require additional constraints, it is not only efficient but also simple to implement. Mean compliance minimization and eigenfrequency maximization problems are considered to verify the effectiveness of the present approach.

• Journal of KIISE
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• v.44 no.6
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• pp.621-627
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• 2017

Collaborative filtering is a technique that effectively recommends unrated items for users. Collaborative filtering is based on the similarity of the items evaluated by users. The existing top-N recommendation methods are based on pair-wise and list-wise preference models. However, these methods do not effectively represent the relative preference of items that are evaluated by users, and can not reflect the importance of each item. In this paper, we propose a new method to represent user's latent preference by combining an existing preference model and the notion of inverse user frequency. The proposed method improves the accuracy of existing methods by up to two times.