• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.15 no.3
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• pp.277-281
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• 2005

Air-line mask is an important personal protective equipment for workers working under hazardous surroundings in which a fixed ventilation system is difficult to be installed. If the air-line mask make loud noise, works wearing the mask may be faced with health problems such as noise induced hearing loss(NIHL). The purpose of this study is to introduce a low noisy technology for workers using air-line mask. A traditional type air-line has been improved to an advanced air-line mask with lesser noise. In the mask, air suppling conduits consists of multi tubes are placed inside of the front of the safety helmet. The noise level reduced from 80dB(A) to less than 80dB(A) when measured by KS A 0701 method at Center for Safety Inspection, Testing and Certification for KOSHA. It is suitable for related regulation[Article 35 of the Industrial Safety and Health Act(Test of Personal Protective Equipment)]. While workers working in noise level of over 90dB(A), they may expose to 82dB(A) or less when they wear the advanced masks. This type masks can be an alternative for works suffering from loud noise generated by traditional air-line masks.

• Current Optics and Photonics
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• v.5 no.5
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• pp.562-575
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• 2021

As a new type of spectrometer, that based on filters with different transmittance features attracts a lot of attention for its advantages such as small-size, low cost, and simple optical structure. It uses post-processing algorithms to achieve target spectrum reconstruction; therefore, the performance of the spectrometer is severely affected by noise. The influence of noise on the spectral reconstruction results is studied in this paper, and suggestions for solving the spectral reconstruction problem under noisy conditions are given. We first list different spectral reconstruction methods, and through simulations demonstrate that these methods show unsatisfactory performance under noisy conditions. Then we propose to apply the gradient projection for sparse reconstruction (GRSR) algorithm to the spectral reconstruction method. Simulation results show that the proposed method can significantly reduce the influence of noise on the spectral reconstruction process. Meanwhile, the accuracy of the spectral reconstruction results is dramatically improved. Therefore, the practicality of the filter-based spectrometer will be enhanced.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.255-265
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• 2009

This paper presents the acoustic noise and mechanical vibration reduction of a coreless brushless DC motor with an air dynamic bearing used in a digital lightening processor. The coreless brushless DC motor does not have a stator yoke or stator slot to remove the unbalanced force caused by the interaction between the stator yoke and the rotor magnet. An unbalanced force makes slotless brushless DC motors vibrate and mechanically noisy, and the attractive force between the magnet and the stator yoke increases power consumption. Also, when a coreless brushless DC motor is driven by a $120^{\circ}$ conduction type inverter, high frequency acoustic noise occurs because of the peak components of the phase currents caused by small phase inductance and large phase resistance. In this paper, a core-less brushless DC motor with an air dynamic bearing to remove mechanical vibration and to reduce power consumption is applied to a digital lightening processor. A $180^{\circ}$ conduction type inverter drives it to reduce high frequency acoustic noise. The applied methods are simulated and tested using a manufactured prototype motor with an air dynamic bearing. The experimental results show that a coreless brushless DC motor has characteristics of low power consumption, low mechanical vibration, and low high frequency acoustic noise.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.137-146
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• 2019

This study proposed a new technique to control of mobile robot based on voice command for (Human-Robot Cooperative operation in manufacturing precess). High performance voice recognition and control system was designed In this paper for smart factory. robust voice recognition is essential for a robot to communicate with people. One of the main problems with voice recognition robots is that robots inevitably effects real environment including with noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we describe an robust voice recognition system which can robustly recognize voice by adults and students in noisy environments. It is illustrated by experiments the voice recognition performance of mobile robot placed in a real noisy environment.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1394-1397
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• 1987

It is difficult to detect edge segments from a noisy image since the image have a noise in piratical applications which utilize some type of visual input capability. Hence, the proposed algorithm consists of the modality tests based on parallel statistical tests without a noise removal preprocessing or postprocessing, and the edge detection technique With one-Pixel edge segments in this paper. The algorithm is very reliable and effective in the case of those situations where the Picture is poor quality and low resolution. And it does'nt require thinning operation and thresholding in hand. Experimental comparision With the more conventional techniques when applied to typical low-quality Pictures confirms good capabilities of the algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.205-213
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• 2011

The Long Term Evolution (LTE) system is designed to provide a high quality data service for fast moving mobile users. It is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the training samples which are systematically built within the transmitting data. Either a preamble or a lattice type is used for the distribution of training samples and the latter suits better for the multipath fading channel environment whose channel frequency response (CFR) fluctuates rapidly with time. In the lattice-type structure, the estimation of the CFR makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time-and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. All interpolation schemes should rely on the pilot estimates only, and thus, their performances are bounded by the quality of pilot estimates. However, the additive noise give rise to high fluctuation on the pilot estimates, especially in a communication environment with low signal-to-noise ratio. These high fluctuations could be monitored in the alternating high values of the first forward differences (FFD) between pilot estimates. In this paper, we analyzed statistically those FFD values and propose a postprocessing algorithm to suppress high fluctuations in the noisy pilot estimates. The proposed method is based on a localized adaptive moving-average filtering. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification. It is shown that the mean-squared error (MSE) between the actual CFR and pilot estimates could be reduced up to 68% from the noisy pilot estimates.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.432-438
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• 1994

This paper describes the measuring method of vibration mode shapes by the Electronic Shearography. Shearographic interferometer has many merits in practical use, that is low sensitive to the environmental noisy, liw limit of the coherent-length and simple optical configuration etc.. In this study, we developed Michelson-type shearing interferometer provided with a phase stepping mirror and with a bias modulation mirror to quantify the vibration gradient fields. As a results of application to a simple cantilever plate vibration amplitude fields were obtained by the proper integration technique, and their exprimental results were in good agreement with those of the ESPI experiment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.57-68
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• 2023

Because salt and pepper noise is a type of impulse, even a small amount of noise could cause a large image degradation. In this paper, we proposed a salt-and-pepper noise removal method using the convolutional neural network. It consists of four phases. In the first step, the proposed method reconstructs noisy image using a traditional salt-and-pepper noise reduction method, and in the second step, the result image of previous step is filtered with Gaussian low pass filter. After that, we reconstruct the filtered image using convolution neural network. In the last step, the pixels with salt-and-pepper noise are replaced with the result of previous phase. Simulation results show that the proposed method yields not only objective image qualities(PSNR, SSIM) but also subjective image qualities for all SAP noise ratios.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.3
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• pp.207-218
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• 1991

In this paper, the characteristics of MODEM with the low and medium transmission rate which are recommended by the international organization such as CCITT have been studied and the features of the telephone channel have been investigated. Then three kinds of classification algorithm for the modulated signals have been suggested and their performance have been researched through the computer simulation. In case that the channel is ideal, the modulated type such as FSK, PSK and QAM could be detected correctly. Moreover, when the modulated signals are received through the telpehone channel or noisy channel, it could be seen that the performance of the correlation algorithm is superior to that of other two algorithms because of the correlation being robust to the characteristics of telephone chanel and Gasussian noise, although the performances of the two classification algorithm using the peak and phase difference, signal constellation and so on decrease rapidly as the amplitude distortion, delay distortion and Gaussian noise increase.