• JSTS:Journal of Semiconductor Technology and Science
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• v.2 no.4
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• pp.280-287
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• 2002

We present technical issues involved in the development of actuators and sensors for applications to high-precision Micro Electro Mechanical System (MEMS). The technical issues include fabrication uncertainty and noise disturbance, causing major difficulties for MEMS to achieve high-precision actuation and detection functions. For nano-precision actuators, we solve the fabrication instability and electrical noise problems using digital actuators coupled with nonlinear mechanical modulators. For the high-precision capacitive sensors, we present a branched finger electrodes using high-amplitude anti-phase sensing signals. We also demonstrate the potential applications of the nanoactuators and nanodetectors to high-precision positioning MEMS.

• Journal of information and communication convergence engineering
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• v.19 no.1
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• pp.54-60
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• 2021

Various digital devices were supplied throughout the Fourth Industrial Revolution. Accordingly, the importance of data processing has increased. Data processing significantly affects equipment reliability. Thus, the importance of data processing has increased, and various studies have been conducted on this topic. This study proposes a modified Gaussian filter algorithm based on a fuzzy membership function. The proposed algorithm calculates the Gaussian filter weight considering the standard deviation of the filtering mask and computes an estimate according to the fuzzy membership function. The final output is calculated by adding or subtracting the Gaussian filter output and estimate. To evaluate the proposed algorithm, simulations were conducted using existing additive white Gaussian noise removal algorithms. The proposed algorithm was then analyzed by comparing the peak signal-to-noise ratio and differential image. The simulation results show that the proposed algorithm has superior noise reduction performance and improved performance compared to the existing method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.542-542
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• 2010

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.142-143
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• 2010

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.61-62
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• 2011

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.193-194
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• 2011

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.95-103
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• 2010

Raw files record luminance values corresponds to each pixel of a digital camera sensor. In digital imaging, controlling exposure to capture the first highlight stop is important on linear-distribution of raw file characteristic. This study sought to verify the efficiency of ETTR method and found the optimum over-exposure amount to maintain the first highlight stop to be the largest number of levels. This was achieved by over-exposing a scene with a raw file and converting it to under-exposure in a raw file converting software. Our paper verified the efficiency of ETTR by controlling the exposure range and ISOs. Throughout the results, if exposure increases gradually 6 steps, dynamic range is also increased. And it shows that the optimized exposure value is around + $1\frac{2}{3}$ stop over compared to the normal exposure with the high ISOs simultaneously. We compared visual noise value at $1\frac{2}{3}$ stop to the normal exposure visual noise. Based on the normal exposure's visual noise, we can confirm that visual noise decrement is increased by increasing ISOs. In this experimental result, we confirm that overexposure about + $1\frac{2}{3}$ stop is the optimum value to make the widest dynamic range and lower visual noise in high ISOs. Based on the study results, we can provide the effective ETTR information to consumers and manufacturers. This method will contribute to the optimum image performance in maximizing dynamic range and minimizing noise in a digital imaging.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.6 no.3
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• pp.36-54
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• 1995

The error performance of digital radio signals (i.e., M-ary PSK signal, DQPSK signal, MSK signal, GMSK signal) interfered by impulsive noise and electromagnetic interference (EMI) is analyzed and discussed. In analysis at first, the error rate equations have been derived in an electromagnetic interference plus impulsive noise environment. And then, the error performance has been evaluated and shown in figures as a function of carrier-to-noise ratio, carrier-to-interference ratio, impu- lsive index, gaussian noise to impulsive noise power ratio, and interference index to measure the amount of error degradation in digital radio signals. From the obtained results we have known that in the presence of m-distributed tone interference plus inpulsive noise, the more significant the electromagnetic interference amplitude varies, the more significant performance degradation is produced. The listing the digital radio signals from the most degraded to the least is that DQPSK, GMSK, QPSK and MSK signal. In the constant amplitude tone interference plus impulsive noise environment, the effect of in- terference nearly disappears over about 20dB in CIR. The effect of constant tone interference on error rate performance is reduced more remarkably in the region from 10dB to 15dB in CIR. In both enviroments of m-distributed tone interference and constant amplitude tone interference, the more electromagnetic interference amplitude varies and CIR increases, the more error perfor- mance is improved. But it is found out that the performance can not be improved significantly even the electromagnetic interference becomes weak. This describes that the impulsive noise affects dominantly to the performance degradation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.692-693
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• 2013

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.175-182
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• 2017

Noises are usually generated by various external causes and low quality devices in image data acquisition and recording as well as by channel interference in image transmission. Since these noise signals result in the loss of information, subsequent image processing is subject to the corruption of the original image. In general, image processing is performed in the mixed noise environment where common types of noise, known to be Gaussian and impulse, are present. This study proposes an iterative weighted mean filter for reducing mixed type of noise. Impulse noise pixels are first turned off in the input image, then $3{\times}3$ sliding window regions are processed by replacing center pixel with the result of weighted mean mask operation. This filtering processes are iterated until all the impulse noise pixels are replaced. Applied to images corrupted by Gaussian noise with ${\sigma}=10$ and different levels of impulse noise, the proposed filtering method improved the PSNR by up to 12.98 dB, 1.97 dB, 1.97 dB respectively, compared to SAWF, AWMF, MMF when impulse noise desities are less than 60%.