• Convergence Security Journal
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• v.12 no.3
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• pp.59-65
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• 2012

Clouding computing which is developing newly as IT and network technology develops become changed to internet and service environment of company. Especially, it can lend IT resource at low costs and no need to build up infra. Clouding computing environment become popular more and more because various computing environment using virtualization is provided. The attack threat range also becomes wider in proportion to broaden various connection ways and service supply range at these clouding computing. Therefore, intrusion detection system which can protect resource from various attack having malignant attempts is necessary. In this study, we analyzed about characteristic of intrusion detection system at cloud computing environment having big damage than other computing environment when intrusion happen by sharing of resource and virtualization.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.8
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• pp.99-105
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• 2011

This paper is about the design of 3-axis magnetic sensor module which detects parking and moving vehicle. For the sensor module, MR Sensor from Honeywell of which maximum measurement range is ${\pm}2$[G] is used. It also consisted of amplifier and sensor filter and fabricated $30{\times}50$[mm] PCB. Fabricated sensor module produced helmholtz coil of which the length is 1.2[m] of 3-axis to know the performance. It installed sensor module at the center and measured the detected magnetic field. In result, 3-axis were detected as 0.2~0.3[mG] and the drift of the fluctuation of magnetic field was stabilized at 0.03[mG] unit. For the performance evaluation of the vehicle detection, after the entry and parking of the vehicle, variation of magnetic field was measured as 0.323~0.695[G] which the average 0.5[G] of the earth magnetic field was the center and the range of variation was confirmed as 0.37[G]. Therefore, the designed magnetic sensor can be used as the vehicle detection sensor module.

• Analytical Science and Technology
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• v.19 no.3
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• pp.189-193
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• 2006

Chromatographic separation of glycerol monostearate, glycerol distearate and glycerol tristearate (GMS, GDS, and GTS) has been performed by normal phase HPLC method utilizing a Zorbax silica ($250{\times}4.6mm$, $5{\mu}m$) column and hexane-hexane, IPA and ethyl acetate mixtures as the eluent within 20 min. The observed reproducibility was less than 5% RSD, Suggesting that ELSD was an effective tool for detection of the glycerol stearates of low volatility without chromophore. The detection limits were in the concentration range of 0.3~2 mg/L, and the calibration curves (the log-log plots) were linear in the range of 4~1000 mg/L (with the slopes of 1.06~1.32). The application of the analytical procedure without pretreatment demonstrated that the proposed chromatographic method would be practical for a routine analysis of commercial products.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.213-221
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• 2024

Aircraft's operational effectiveness is reduced due to threats from enemy anti-aircraft weapons, which is a weak point. In particular, guided missiles, which pose a threat to aircraft, are rapidly developing due to technological advancements in seekers, and are classified as one of the important technologies in weapon systems. Missile approach warning equipment installed to ensure aircraft survivability detects guided missiles and provides relevant information to respond. Tests were conducted domestically to verify the detection level of missile approach warning equipment, and test results were presented under various test conditions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.

• Journal of the Society of Disaster Information
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• v.10 no.3
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• pp.452-457
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• 2014

The event of a Chemical disaster response personnel are causative events quickly Appearance & residual contaminant concentrations, should be identified accurately. In addition, the chemical disaster response procedure appropriate progress in the field of Chemical Composition and contaminant concentrations in order confirmation is essential. Use in the field to using the characteristics of each equipment. on-Site response equipment can not verify all the chemicals, materials detection, limited by each equipment. Detection range of equipment & specific materials should be considered complementary. In this study, using the equipment on-site detection of detection kit and detector tube, electronic detection equipment utilized for the rapid response procedure for helping a person to cope.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.895-901
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• 2016

Nowadays, the axle counter has been developed to the wide range of the track circuit blocks as well as the wheel detection device. The axle counter, as becoming an important device for the high speed railway, must be guaranteed in accordance with the safety. With considering the safety and the high speed, performance evaluation a wheel detection sensor is described in this paper. To increase the safety, digital proximity sensor instead of analog is employed in the wheel detection sensor. Therefor the wheel detection sensor can minimize noisy signals caused by the harsh railway environments. And, to meet the high speed railway requirements, the performance of the wheel detection sensor is also successfully verified using the speed simulator at the velocity 500Km/h.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.155-162
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• 2009

In walking guide robot, a guide vehicle detects an obstacle distribution in the walking space using range sensors, and generates a 3D grid map to map the obstacle information and the tactile display. And the obstacle information is transferred to a blind pedestrian using tactile feedback. Based on the obstacle information a user plans a walking route and controls the guide vehicle. The algorithm for 3D detection of an obstacle distribution and the method of mapping the generated obstacle map and the tactile display device are proposed in this paper. The experiment for the 3D detection of an obstacle distribution using ultrasonic sensors is performed and estimated. The experimental system consisted of ultrasonic sensors and control system. In the experiment, the detection of fixed obstacles on the ground, the moving obstacle, and the detection of down-step are performed. The performance for the 3D detection of an obstacle distribution and space mapping is verified through the experiment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.159-166
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• 2005

The pulse amplitude of a search radar signal received by an ES system is not constant pulse by pulse because of the radar's scan characteristics. The variation of the pulse amplitude causes the ES detection loss in the ES system. Therefore, the ES detection range equation should consider the ES detection loss caused by the search radar's scan characteristics. In this paper, we theoretically analyze the ES detection loss for the circular scar and propose the model to evaluate it quantitatively. The experiment results for the real search radar signals demonstrate that the proposed model is suitable for the evaluation model of the ES detection loss related to the circular scan of radars.