• Journal of Advanced Marine Engineering and Technology
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• v.31 no.4
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• pp.433-440
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• 2007

In this paper a new dynamoelectric winch system is introduced which is widely applied in shipping. building, architecture and so on. Generally in the winch system the squirrel cage induction motor is used as prime mover and line voltage is directly applied to the induction motor during operation. So it is difficult to obtain the smoothing revolution. because of variation of the weight of cargo and system operating method. Based on above reasons, the switched reluctance motor (SRM) is proposed to replace the induction motor because of more reliable mechanical structure, better traction characteristic and higher efficiency compared to induction motor. And in order to solve smoothing revolution problem, instantaneous torque control method based on torque sharing function (TSF) is used. Finally the validity of the proposed method is verified through the simulation and experimental results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.533-535
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• 2018

As the use frequency of electronic communication equipment increases due to the influence of the 4th industrial revolution, the importance of image and signal processing is increasing. However, due to noise caused by various causes, the reliability of the equipment is degraded and malfunctions are caused. In this paper, we propose an algorithm to remove AWGN in most environments. The existing methods show relatively poor performance due to the smoothing phenomenon at the boundary of the image. To overcome this problem, we proposed a filter algorithm that adapts to the boundary region using the Sobel edge detection to remove the noise. And using the PSNR compared with traditional methods, such as to demonstrate the performance of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.849-854
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• 2018

Radio base stations, which are widely distributed across large areas, have many difficulties in managing them. Unmanned radio base stations in remote mountains are having a hard time accessing them in case of emergencies. Major telephone service providers only remotely control incoming and outgoing information and local small business partners responsible for maintaining actual facilities do not possess such technologies, so they are each checked during field visits. In this study, in order to process the sensor raw data and smoothing, we apply the particle filters and confirmed that the performance of sensor data accuracy is increased. Integrated system using temperature, humidity, fire condition, and power operation at a wide range of radio base stations under the real-time monitoring status is operated well. It show that all of the status of base station are monitored at the remote office using the cloud server through internet networking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.4
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• pp.474-480
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• 2020

With the advent of the Fourth Industrial Revolution, many new technologies are being utilized. In particular, video signals are used in various fields. However, when transmitting and receiving video signals, salt and pepper noise and additive white Gaussian noise (AWGN) occur for multiple reasons. Failure to remove such noise when performing image processing can cause problems. Generally, filters such as CWMF, MF, and AMF remove noise. However, these filters perform somewhat poorly in the high-density noise domain and cause smoothing, resulting in slightly lower retention of the edge components. In this paper, we propose an algorithm by effectively eliminating salt and pepper noise using a modified weight filter using standard deviation. In order to prove the noise reduction performance of the proposed algorithm, we compared it with the existing algorithm using PSNR and magnified images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1846-1852
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• 2021

In modern society, various digital devices are being distributed in a wide range of fields due to the fourth industrial revolution and the development of IoT technology. However, noise is generated in the process of acquiring or transmitting an image, and not only damages the information, but also affects the system, causing errors and incorrect operation. AWGN is a representative noise among image noise. As a method for removing noise, prior research has been conducted, and among them, AF, A-TMF, and MF are the representative methods. Existing filters have a disadvantage that smoothing occurs in areas with high frequency components because it is difficult to consider the characteristics of images. Therefore, the proposed algorithm calculates the standard deviation distribution to effectively eliminate noise even in the high frequency domain, and then calculates the final output by applying the probability density function weight of the Laplace distribution using the curve fitting method.