• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.52-59
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• 2016

COSMOS system which was developed in Seoul for real-time signal control was designed to judge traffic condition for practicing signal operation. However, it occurs efficiency problem that stop line detection and queue length detection could not judge overflow saturation of street. For that reason, following research process GPS data of Seoul city's corporationowned taxi to calculate travel speed that excluded existing system of stop line detection and queue length detection. Also, "Research of calculating queue length by GPS data" which was progressed with following research expressed queue length. It is based on establishing algorithm of judging congestion situation. The algorithm was applied to a few areas where appeared congestion situation consistently to confirm real time traffic condition with established network. [Entrance of the National Sport Institute ${\rightarrow}$ Gangnam station Intersection, Yuksam station intersection ${\rightarrow}$ National Sport Institute.

• International Journal of Aeronautical and Space Sciences
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• v.4 no.1
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• pp.1-8
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• 2003

In this paper, a reconfigurable flight control system is designed by applying the sliding mode control scheme. The sliding mode control method is a nonlinear control method which has been widely used because of its merits such as robustness and flexibility. In the sliding mode controller design, the signum function is usually included, but it causes the undesirable chattering problem. The chattering phenomenon can be avoided by using the saturation function instead of signum function. However, the boundary layer of the sliding surface should be carefully treated because of the use of the saturation function. In contrast to the conventional approaches, the thickness of the boundary layer of our approach does not need to be small. The reachability to the boundary layer is guaranteed by the sliding mode controller. The fault detection and isolation process is operated based on a sliding mode observer. To evaluate the reconfiguration performance, a numerical simulation using six degree-of-freedom aircraft dynamics is performed.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.1-7
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• 2013

The present paper relates to a development of the Gear Detection Sensor for automotive manual transmission. To detect air gap from control finger to detecting zone of sensor based on non-contacted method, permanent magnet and linear type Hall IC are mounted in this sensor. Control finger is machined to 3 step heights to detect 3 gear stages such as In-Gear, Normal and Rear. After conducting actual experimentation based on exclusive Jig and FEM, it is described to consider possibility for automotive application of Gear Detection Sensor.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.621-632
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• 2013

The most important things for a forest fire detection system are the exact extraction of the smoke from image and being able to clearly distinguish the smoke from those with similar qualities, such as clouds and fog. This research presents an intelligent forest fire detection algorithm via image processing by using the Gaussian Mixture model (GMM), which can be applied to detect smoke at the earliest time possible in a forest. GMMs are usually addressed by making the model adaptive so that its parameters can track changing illuminations and by making the model more complex so that it can represent multimodal backgrounds more accurately for smoke plume segmentation in the forest. Also, in this paper, we suggest a way to classify the smoke plumes via a feature extraction using HSL(Hue, Saturation and Lightness or Luminanace) color space analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.1-11
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• 2021

This paper presents a procedure to extract lane line models using a set of proposed methods. Firstly, an image warping method based on homography is proposed to transform a target image into an image which is efficient to find lane pixels within a certain region in the image. Secondly, a method to use the combination of the results of edge detection and HSL (Hue, Saturation, and Lightness) transform is proposed to detect lane candidate pixels with reliability. Thirdly, erroneous candidate lane pixels are eliminated using a selection area method. Fourthly, a method to fit lane pixels to quadratic polynomials is proposed. In order to test the validity of the proposed procedure, a set of black-box images captured under varying illumination and noise conditions were used. The experimental results show that the proposed procedure could overcome the problems of color-only and edge-only based methods and extract lane pixels and model the lane line geometry effectively within less than 0.6 seconds per frame under a low-cost computing environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.1
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• pp.55-60
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• 2014

In this paper, we proposed a method for face region extraction by skin-color hue, saturation and facial feature extraction in natural images. The proposed algorithm is composed of lighting correction and face detection process. In the lighting correction step, performing correction function for a lighting change. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. Eye detection using C element in the CMY color model and mouth detection using Q element in the YIQ color model for extracted candidate areas. Face area detected based on human face knowledge for extracted candidate areas. When an experiment was conducted with 10 natural images of face as input images, the method showed a face detection rate of 100%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3671-3689
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• 2019

Software defined networking brings unique security risks such as control plane saturation attack while enhancing the performance of wireless sensor networks. The attack is a new type of distributed denial of service (DDoS) attack, which is easy to launch. However, it is difficult to detect and hard to defend. In response to this, the attack threat model is discussed firstly, and then a DDoS attack prevention extension, called FuzzyGuard, is proposed. In FuzzyGuard, a control network with both the protection of data flow and the convergence of attack flow is constructed in the data plane by using the idea of independent routing control flow. Then, the attack detection is implemented by fuzzy inference method to output the current security state of the network. Different probabilistic suppression modes are adopted subsequently to deal with the attack flow to cost-effectively reduce the impact of the attack on the network. The prototype is implemented on SDN-WISE and the simulation experiment is carried out. The evaluation results show that FuzzyGuard could effectively protect the normal forwarding of data flow in the attacked state and has a good defensive effect on the control plane saturation attack with lower resource requirements.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.117-120
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• 2000

Pulse oximetry is a well established non-invasive optical technique for monitoring the SpO$_2$ during anaesthesia, recovery and intensive care. Pulse oximeters determine the oxygen saturation level of blood by measuring the light absorption of arterial blood. The sensors consists of red and infrared light sources and photodetectors. In the measurement of the hemoglobin oxygen saturation, conventional method has required the technique of filtering of remove the noise, and of complex signal processing algorithm. So much time have required to signal processing. In this research, we separate AC signal and DC signal in the stage of signal detection. We filter the noise from each signal and convert A/D. We obtain the SpO$_2$ using the DSP algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1244-1253
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• 2018

The color of traffic light is sensitive to various illumination conditions. Especially it loses the hue information when oversaturation happens on the lighting area. This paper proposes a traffic light recognition method robust to these illumination variations. The method consists of two steps of traffic light detection and recognition. It just uses the intensity and saturation in the first step of traffic light detection. It delays the use of hue information until it reaches to the second step of recognizing the signal of traffic light. We utilized a deep learning technique in the second step. We designed a deep convolutional neural network(DCNN) which is composed of three convolutional networks and two fully connected networks. 12 video clips were used to evaluate the performance of the proposed method. Experimental results show the performance of traffic light detection reporting the precision of 93.9%, the recall of 91.6%, and the recognition accuracy of 89.4%. Considering that the maximum distance between the camera and traffic lights is 70m, the results shows that the proposed method is effective.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.4 s.119
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• pp.455-463
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• 2007

In this paper, it is proposed how to implement the object detection system which is able to apply to vehicular applications, unmanned facilities, automatic door and others with microwave. As the technology which detects an object with microwave is becoming more popular, it seems impossible to avoid mutual interference and jamming caused by limited frequency bandwidth. The system in this paper detects an object by correlating the code of TX and RX signals with the pseudo-random code having best quality in interference and jamming environment. In order to generate simulant doppler signal for detecting the distance of an fixed object where there is no doppler effect, the phase of TX signal is shifted continually. Also, the saturation of receiver was removed and the error of distance measurement was decreased by controlling the power of TX signal for getting constant RX signal. The proposed system detects a object which ranges from 0.5 m to 2.0 m and informs vocally whether there is the object within 1.0 m or not.