• Korean Journal of Optics and Photonics
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• v.10 no.1
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• pp.10-14
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• 1999

One dimensional inhomogeneous phase modulation effects on the MTF of optical system was investigated. The lens under test was a doublet made in Korea. It was 36 mm effective diameter, 128.04 mm effective focal length. The ray-fans and spot diagrams were calculated and presented on the picture for on-axis and off-axis (field of view, $1^{\circ}$ and $2^{\circ}$). Phase modulation was carried out by positioning a phase modulator close contacted with the lens under test. One was linear type that had linearly increasing phase retardation and the other was stepped type which had phase difference $\pi$ for each step. The MTFs were measured on the Gaussian image plane and were compared with one another. The MTFs of linear type phase modulated apertures had a little lower values than the MTF of unmodulated aperture for on-axis but most of all the MTFs of one dimensional phase modulated aperture are improved than the MTF of unmodulated aperture.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.3
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• pp.261-269
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• 2004

The existing concrete beams can be retrofitted or reinforced by attaching carbon fiber or glass fiber sheet beneath the beams. Although diverse design methods and application techniques of the retrofitting are studied and developed, the testing method of examining retrofitted beams have not been put into practice yet. In this study, a bond delamination has been modeled and studied to provide a basis for the development of actual testing equipments. For this purpose, Gaussian and sinusoidal waves with 3GHz and 5GHz center frequency are used as an incident wave and 1mm and 3mm bond delamination under the reinforcement are modeled. In the modeling, Finite Difference-Time Domain algorithm is used to investigate the behavior of electromagnetic waves in concrete. The results have shown that 5GHz waves are suitable for the detection of delamination.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1044-1053
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• 2010

Transmitting correct train control information is important in a train control system which demands safety. The train control information includes the maximum speed of trains, position of preceding trains, incline of tracks and curve sections etc. A radio frequency-communication based train control system is influenced by the noise and interference because the train control information is transmitted by wireless between a on-board system and wayside system. The radio frequency-communication based train control system is a mobile communication system due to moving trains. The inter symbol interference(ISI) occurs by the multipath fading in the mobile ommunication system. As signal-to-noise ratio(SNR) is decreased by the ISI, the train control information is not received correctly. In case of tunnel section, numerous reflected waves exist. Therefore, the power density of receiver is decreased by difference among the received times, magnitudes, phases through the multipath. So, the train suddenly is stopped by the fail-safe operation in the train control system on account of decreasing the power density of receiver. In this paper, a line of sight model-(Additive White Gaussian noise(AWGN) channel), rayleigh and rician fading model are presented. Probability density functions which are related to the SNR are derived from the models. The fading phenomenon severely occurs as a result of analyzing the probability density functions. So, the space diversity method is used in order to reduce the fading effect and it is demonstrated by using Matlab program.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.10A
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• pp.969-979
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• 2002

This paper proposes an novel method of minimizing Interference which causes data decision error in digital wireless communications. In this method, in order to suppress ISI which is caused by the phase difference between the transmitted and received signal phases, the transmitted and received signals are always kept orthogonal by compensating the transmitted signal for detecting the phase noise and the delay of the received signal was implemented by MOS circuits. To delay the phase of the signal, additive white Gaussian noise (AWGN) environment was used. The phase and delay of the signal transmitted through AWGN channel were compensated in the modulator of the transmitter and the compensated signal was demodulated using quasi-direct conversion receiver and QPSK demodulator. ISI suppression was achieved by keeping the orthogonality between the compensated transmitted signal and the receive signal. The error probability of data decision was compared. By simulation the proposed system was proved to be effective in minimizing the ISI.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.789-799
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• 2018

This article presents machine learning based approach on Big data to analyzing time series data for anomaly detection in such industrial complex system. Long Short-Term Memory (LSTM) network have been demonstrated to be improved version of RNN and have become a useful aid for many tasks. This LSTM based model learn the higher level temporal features as well as temporal pattern, then such predictor is used to prediction stage to estimate future data. The prediction error is the difference between predicted output made by predictor and actual in-coming values. An error-distribution estimation model is built using a Gaussian distribution to calculate the anomaly in the score of the observation. In this manner, we move from the concept of a single anomaly to the idea of the collective anomaly. This work can assist the monitoring and management of Smart Factory in minimizing failure and improving manufacturing quality.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.48-55
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• 2008

In this paper we propose a novel method for image retrieval system using image segmentation and salient points. The proposed method consists of four steps. In the first step, images are segmented into several regions by JSEG algorithm. In the second step, for the segmented regions, dominant colors and the corresponding color histogram are constructed. By using dominant colors and color histogram, we identify candidate regions where objects may exist. In the third step, real object regions are detected from candidate regions by SIFT matching. In the final step, we measure the similarity between the query image and DB image by using the color correlogram technique. Color correlogram is computed in the query image and object region of DB image. By experimental results, it has been shown that the proposed method detects multi-object very well and it provides better retrieval performance compared with object-based retrieval systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.231-241
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• 2013

In this paper, we propose an average approximation filter which can effectively remove the noises of the images. The noises include impulse noises, gaussian noises and mixed noises. The algorithm is as follows. First, as a step of noise detection, we find whether the difference between the pixel value and the average value is greater than the threshold value or not after getting the average value that removed the minimum and maximum values in the applied mask. If the pixel value is greater than the threshold value, the pixel value is processed as noise. If it is less than or equal to the threshold value, it is processed as non-noise. Next, as the noise reduction step, we output the approximate value in mask as the pixel value and the average value except the minimum and maximum values of the pixel including the noise. As the result of applying this average approximation filter to the mixed noise images, the approximation filter can reduce the noises effectively more than 0.4[dB] as compared with applying the median filter and the average filter, respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.70-76
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• 2012

In this paper, an automatic extraction method of glomerulus region from human renal tissue image is presented. The important information reflecting the state of kidneys richly included in the glomeruli, so it should be the first step to extract the glomerulus region from the renal tissue image for the further quantitative analysis of the renal condition. Especially, there is no clear difference between the glomerulus and other tissues, so the glomerulus region can not be easily extracted from its background by the existing segmentation methods. The outer edge of a glomerulus region is regarded as a common property for the regions of this kind ; a two- dimensional Gaussian distribution is used to convolve with an original image first and then the image is thresholded at this blurred image ; a closed curve corresponding to the outer edge can be obtained by usual pattern processing skills like thinning, branch-cutting, hole-filling etc., Finally, the glomerulus region can be obtained by extracting the area in the original image surrounded by the closed curve. The glomerulus regions are correctly extracted by 85 percentages and experimental results show the proposed method is effective.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1165-1172
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• 2008

In this paper, the scattering parameters of the metamaterial slab are obtained using the 2D FDTD(Finite-Difference Time-Domain) method. FDTD method is one of strongest electromagnetic numerical method which is widely used to analyze the metamaterial structure because of its simplicity. But it is very difficult to obtain frequency response of metamaterial itself because frequency dispersive model such as Lorentz, Drude model are used in FDTD. We used the well-known m-n-m cycle sine pulse to obtain the frequency response of the metamaterials. Comparisons between the wideband Gaussian input pulse and band-limited m-n-m cycle sine pulse are performed in this paper also. From the results, we concluded that the scattering parameters in frequency domain can be obtained using specific input pulse in FDTD even if the response has valid only for limited bandwidth.

• Korean Journal of Remote Sensing
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• v.16 no.1
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• pp.65-72
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• 2000

Scattering coefficients of randomly rough lossy dielectric surfaces were computed by using the FDTD(Finite-Difference Time-Domain) method and the Monte Carlo method in this paper. The FDTD method was applied to compute electromagnetic wave scattering characteristics at any incident angles, any linear polarizations by dividing the computation region into the total-field region and the scattered-field region. The radar cross sections(RCS) of conducting cylinders have been computed and compared with theoretical results, measurement data and the results from the method of moment(MoM) to verify the FDTD algorithm. Then, to apply the algorithm to compute scattering coefficients of distributed targets, a two-dimensionally rough surface was generated numerically for given roughness characteristics. The far-zone scattered fields of 50 statistically independent dielectric rough surfaces were computed and the scattering coefficient of the surface was calculated from the scattered fields by using the Monte Carlo method. It was found that these scattering coefficients agree well with the SPM(Small Pertubation Method) model in its validity region.