• Journal of Korea Society of Industrial Information Systems
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• v.18 no.5
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• pp.45-50
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• 2013

Recently, as the market for SMART TV expands, the camera is embedded for providing various user experience. However, this leads to occurrence of camera failure due to TV power up sequence problem, which are usually not detectable in conventional test equipments. Although the failure-detection can be possible by re-generating control signals for audio interface with new equipment, it is expensive and also requires much time to test. In this paper, for SMART TV, FPGA(Field Programmable Gate Array)-based failure-detection system is proposed which can lead to reduction of both cost and time for test.

• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.214-221
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• 2003

In view of the fact that gas insulated switchgear (GIS) is an important piece of equipment in a substation, it is highly desirable to continuously monitor the state of equipment by measuring the partial discharge (PD) activity in a GIS, as PD is a symptom of an insulation weakness/breakdown. However, since the PD signal is relatively weak and the external noise makes detection of the PD signal difficult, it therefore requires careful attention in its detection. In this paper, the algorithm for detection of PD in the GIS using the wavelet transform (WT) is proposed. The WT provides a direct quantitative measure of the spectral content and dynamic spectrum in the time-frequency domain. The most appropriate mother wavelet for this application is the Daubechies 4 (db4) wavelet. 'db4', the most commonly applied mother wavelet in the power quality analysis, is very well suited to detecting high frequency signals of very short duration, such as those associated with the PD phenomenon. The proposed algorithm is based on utilizing the absolute sum value of coefficients, which are a combination of D1 (Detail 1) and D2 (Detail 2) in multiresolution signal decomposition (MSD) based on WT after noise elimination and normalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.5
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• pp.471-478
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• 2013

In this paper, we have designed and implemented an obstacle detecting device based laser radar. It is an alternative to solve through problem analysis of that are currently operated safety equipment and status research of domestic railway crossing. It is target to improve the safety and reliability of the rail traffic through effective obstacle detection at crossing account for a large proportion of train accidents. suggest a system to overcome the problems caused by aging and limitation of existing safety equipment. Design a crossing obstacle detection device that utilizes laser radar scanner, proved this through performance evaluation and testing of the prototype.

• JOURNAL OF ELECTRICAL WORLD
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• no.2 s.146
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• pp.11-18
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• 1989

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.27-33
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• 2020

Backward compatibility is one of the key issues for radio equipment supporting IEEE 802.11, the typical wireless local area networks (WLANs) communication protocol. For a successful packet decoding with the backward compatibility, the frame format detection is a core precondition. This paper presents a novel frame format detection method based on a deep learning procedure for WLANs affiliated with IEEE 802.11. Considering that the detection performance of conventional methods is degraded mainly due to the poor performances in the symbol synchronization and/or channel estimation in low signal-to-noise-ratio environments, we propose a novel detection method based on convolutional neural network (CNN) that replaces the entire conventional detection procedures. The proposed deep learning network provides a robust detection directly from the receive data. Through extensive computer simulations performed in the multipath fading channel environments (modeled by Project IEEE 802.11 Task Group ac), the proposed method exhibits superb improvement in the frame format detection compared to the conventional method.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.238-240
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• 2006

For the method of train position detection, ground-based train position estimation mainly has been applied so far. Ground-based position detection is the way to detect train current positions by installing train position equipments on railroad lines. However, the ground-based methods should install detection equipments on each section, and can only be able to detect train positions from main command center. So this method has several disadvantages such as an discontinuous position detection, an increment in cost of installation and maintenance. To make possible continuous train position detection, and to minimize amount of the cost, the vehicle-based position detection method should be chosen to determine train positions by loading position equipments on vehicles. In this paper, to realize the vehicle-based train position detection method, configuration scheme of train position detection equipment is suggested by using GPS, inertial sensor, speed sensor and its performance is verified by simulations.

• Convergence Security Journal
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• v.21 no.2
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• pp.11-18
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• 2021

To protect tangible and intangible assets, most of the companies are conducting information protection monitoring by using various security equipment in the IT service network. As the security equipment that needs to be protected increases in the process of upgrading and expanding the service network, it is difficult to monitor the possible exposure to the attack for the entire service network. As a countermeasure to this, various studies have been conducted to detect external attacks and illegal communication of equipment, but studies on effective monitoring of the open service ports and construction of illegal communication monitoring system for large-scale service networks are insufficient. In this study, we propose a framework that can monitor information leakage and illegal communication attempts in a wide range of service networks without large-scale investment by analyzing 'Netflow statistical information' of backbone network equipment, which is the gateway to the entire data flow of the IT service network. By using machine learning algorithms to the Netfllow data, we could obtain the high classification accuracy of 94% in identifying whether the Telnet service port of operating equipment is open or not, and we could track the illegal communication of the damaged equipment by using the illegal communication history of the damaged equipment.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.11
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• pp.1564-1570
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• 1998

In-situ particle monitors(ISPMs) are widely used for monitoring contaminant particles in vacuum-based semiconductor manufacturing equipment. In the present research, the performance of a Particle Measuring Systems(PMS) Vaculaz-2 ISPM at subatmospheric pressures has been studied. We created uniform upstream conditions of particle concentration and measured the detection efficiency, the lower detection limit, and the size response of the ISPM using uniform sized methylene blue aerosol particles. The effect of particle size, particle velocity, particle concentration, and system pressure on the detection efficiency was examined. Results show that the detection efficiency of the ISPM decreases with decreasing chamber pressure, and with increasing mass flow rate. The lower detection limit of the ISPM, determined at 50 % of the measured maximum detection efficiency, was found to be about $0.15{\sim}0.2{\mu}m$, which is similar to the minimum detectable size of $0.17{\mu}$ given by the manufacturer.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.425-428
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• 2001

In this paper, FMCW radar signal processing technique for the vehicle detection system are studied. And FMCW radar sensor is used as a equipment for vehicle detection. To test the performance of developed algorithm, the evaluation of the algorithm is done by simulation for signal processing technique of vehicle detection system. RADAR signal of a driving vehicle is generated by using the Matlab. Distance and velocity of vehicles are calculated with developed a1gorithm. Also the signal processing procedure is done for the virtual data with FM-AM converted noise.

• Proceedings of the KIEE Conference
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• summer
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• pp.301-303
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• 2004

This paper presents an islanding detection algorithm based on the second harmonic. When the DG(distributed Generator) was connected with utility supply, for maintenance and repair of equipment, an islanding occurred. So islanding detection algorithm must be developed for safety of human. Although the DG generating power is similar to power consumption. the proposed algorithm can detect the islanding condition very successfully.