• International Journal of Highway Engineering
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• v.16 no.2
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• pp.1-9
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• 2014

PURPOSES : This study aims to evaluate the performance of interlocking block pavement system for low speed highway. METHODS : Through on-site monitoring, environmental impact assessment of interlocking block pavement such as heat island reduction, traffic safety, noise pollution were evaluated as compared with asphalt pavement. Also the pavement condition and roughness were evaluated according to performance period. RESULTS : Surface temperature of interlocking block pavement was about 7 degree lower than asphalt pavement in midsummer. Compared to asphalt pavement, vehicle speed reduction effect of interlocking block pavement was about 2kph. For low speed driving, the noise pollution was measured at a similar level for both asphalt and interlocking block pavement. After 42month service period, the breakage of block was only 0.24% for the whole surveyed area. IRI of interlock block pavement was estimated within the range of 5~8m/km. CONCLUSIONS : Depending on the performance monitoring results such as heat island reduction, providing traffic safety and keeping a good pavement condition for a long service period, it assures that interlocking block pavement was applicable for low speed road.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.360-367
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• 2002

In this paper, genetic algorithm based adaptive image enhancement filtering scheme is proposed and Implemented on FPGA board. Conventional filtering methods require a priori noise information for image enhancement. In general, if a priori information of noise is not available, heuristic intuition or time consuming recursive calculations are required for image enhancement. Contrary to the conventional filtering methods, the proposed filter system can find optimal combination of filters as well as their sequent order and parameter values adaptively to unknown noise types using structured genetic algorithms. The proposed image enhancement filter system is mainly composed of two blocks. The first block consists of genetic algorithm part and fitness evaluation part. And the second block consists of four types of filters. The first block (genetic algorithms and fitness evaluation blocks) is implemented on host computer using C code, and the second block is implemented on re-configurabe FPGA board. For gray scale control, smoothing and deblurring, four types of filters(median filter, histogram equalization filter, local enhancement filter, and 2D FIR filter) are implemented on FPGA. For evaluation, three types of noises are used and experimental results show that the Proposed scheme can generate optimal set of filters adaptively without a pioi noise information.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.898-901
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• 2000

A new 2-D block Kalman filtering method which uses a nonlinear function is presented to generate a more accurate filtered estimate of a range image that has been corrupted by additive noise. Novel 2-D block Kalman filtering method is constructed of the conventional method and nonlinear function which utilizes to control estimation error. We show that novel 2-D Kalman filtering method using a nonlinear function is effective at reducing the additive noise, not distorting shape edges.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1513-1525
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• 2016

Rapid and accurate phase synchronization is critical for the reliable control of grid-tied inverters. However, the commonly used software phase-locked loop methods do not always satisfy the need for high-speed and accurate phase synchronization under severe grid imbalance conditions. To address this problem, this study develops a novel open-loop phase locking scheme based on a synchronous reference frame. The proposed scheme is characterized by remarkable response speed, high accuracy, and easy implementation. It comprises three functional cascaded blocks: fast orthogonal signal generation block, fast fundamental-frequency positive sequence component construction block, and fast phase calculation block. The developed virtual orthogonal signal generation method in the first block, which is characterized by noise immunity and high accuracy, can effectively avoid approximation errors and noise amplification in a wide range of sampling frequencies. In the second block, which is the foundation for achieving fast phase synchronization within 3 ms, the fundamental-frequency positive sequence components of unsymmetrical grid voltages can be achieved with the developed orthogonal signal construction strategy and the symmetrical component method. The real-time grid phase can be consequently obtained in the third block, which is free from self-tuning closed-loop control and thus improves the dynamic performance of the proposed scheme. The proposed scheme is adaptive to severe unsymmetrical grid voltages with sudden changes in magnitude, phase, and/or frequency. Moreover, this scheme is able to eliminate phase errors induced by harmonics and random noise. The validity and utility of the proposed scheme are verified by the experimental results.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.3
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• pp.177-183
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• 2003

Vibration analysis using component mode synthesis method was carried out to identify that to some extent each component contributed to the whole vibration of a powertrain consisting of several components. This analysis helped decide the component to be modified to reduce the powertrain weight, without degrading its current vibration characteristics. As a result, a cylinder block was chosen as a redesign object. Topology optimization analysis was performed to design the topology of the cylinder block whose flange connected with the transmission was chosen to be the design domain. After all, a new prototype of cylinder block was manufactured based on the analysis results for the verification experiment. It was confirmed from the analytical and experimental results that u optimally designed cylinder block had an advantage over the current one in the powertrain weight, with the powertrain vibration characteristics improved slightly.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.225-235
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• 2012

Noise reduction is an important issue in the field of image processing because image noise worsens the quality of the input image. The basic difficulty is that the noise and the signal are not easy to distinguish. Simple moothing is one of the most basic and important procedures to remove the noise, however, it does not consider the level of noise. This method effectively reduces the noise but the feature area is simultaneously blurred. This paper considers the block approach to detect noise and image features of the input image so that noise reduction could be adaptively applied. Simulation results show that the proposed algorithm improves the overall quality of the image by removing the noise according to the noise level.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.244-250
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• 2007

The electric train in the first line subway runs faster in the block from Suwon to Cheonan than the general block. The faster run results in the deterioration of ride quality due to the increase of noise and vibration. To reduce the noise and vibration of the electric train, a running test of the electric train was performed in the block from Suwon to Cheonan. The experimental results show that the sources of the noise and vibration basically comes from the irregularity of the railroad track and the connection part between car body and bogie. The possible countermeasure of the high speed electric train can be the reinforcement of the center pivot to have more flexibility and the frequent maintenance of electric train.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.155-158
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• 2000

In this paper, the quantization noise in block-based video coding is analyzed, and a post-processing method based on the analysis is presented for reducing the quantization noise by using a wavelet transform(WT). In the proposed method, the quantization noise is considered as the sum of a blocking noise expressed as a deterministic profile and the random remainder noise. Each noise is removed in a viewpoint of image restoration using a 1-D WT, which yields a regularized differentiation. The blocking noise first is reduced by weakening the strength of each blocking noise component that appears as an impulse in the first scale wavelet domain. The impulse strength estimation is performed using median filter, quantization parameter(QP), and local activity. The remainder noise, which is considered as a white noise at non-edge pixels, then is reduced by soft-thresholding. The experimental results show that the proposed method yields better performance in terms if subjective quality as well as PSNR performance over VM post-filter in MPEG-4 for all test sequences of various compression ratios. We also present a fast post-processing in spatial domain equivalent to that in wavelet domain for real-time application.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.11
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• pp.72-82
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• 1996

In this paper, newly developed algorithm for enhancing images corrupted by white gaussian noise is proposed. In the method proposed here, image is subdivided into a number of subblocks, and each block is separated into cimponents corresponding to signal and noise subspaces, respectively through the signal subspace method. A clean signal is then estimated form the signal subspace by the adaptive wiener filtering. The decomposition of noisy signal into noise and signal subspaces in is implemented by eigendecomposition of covariance matrix for noisy image, and by performing blockwise KLT (karhunen loeve transformation) using eigenvector. To reduce the perceptual noise level and distortion, wiener filtering is implementd by adaptively adjusting noise level according to activity characteristics of given block. Simulation results show the effectiveness of proposed method. In particular, edge bluring effects are reduced compared to the previous methods.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.87-94
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• 1985

In this paper, enhancement of speech corrupted by additive white or colored noise is stuided. The nuconstrained frequency-domain block least-mean-square (UFBLMS) adaptation algorithm and its frequency-weighted version are newly applied to speech enhancement. For enhancement of speech degraded by white noise, the performance of the UFBLMS algorithm is superior to the spectral subtraction method or Wiener filtering technique by more than 3 dB in segmented frequency-weighted signal-to-noise ratio(FWSNERSEG) when SNR of speech is in the range of 0 to 10 dB. As for enhancement of noisy speech corrupted by colored noise, the UFBLMS algorithm is superior to that of the spectral subtraction method by about 3 to 5 dB in FWSNRSEG. Also, it yields better performance by about 2 dB in FWSNR and FWSNRSEG than that of time-domain least-mean-square (TLMS) adaptive prediction filter(APF). In view of the computational complexity and performance improvement in speech quality and intelligibility, the frequency-weighted UFBLMS algorithm appears to yield the best performance among various algorithms in enhancing noisy speech corrupted by white or colored noise.