• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.108-112
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• 2000

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD (an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• Journal of Astronomy and Space Sciences
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• v.31 no.3
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• pp.277-283
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• 2014

Next Generation Small Satellite-1 (NEXTSat-1) is scheduled to launch in 2017 and Instruments for the Study of Space Storm (ISSS) is planned to be onboard the NEXTSat-1. High Energy Particle Detector (HEPD) is one of the equipment comprising ISSS and the main objective of HEPD is to measure the high energy particles streaming into the Earth radiation belt during the event of a space storm, especially, electrons and protons, to obtain the flux information of those particles. For the design of HEPD, the Geometrical Factor was calculated to be 0.05 to be consistent with the targets of measurement and the structure of telescope with field of view of $33.4^{\circ}$ was designed using this factor. In order to decide the thickness of the detector sensor and the classification of the detection channels, a simulation was performed using GEANT4. Based on the simulation results, two silicon detectors with 1 mm thickness were selected and the aluminum foil of 0.05 mm is placed right in front of the silicon detectors to shield low energy particles. The detection channels are divided into an electron channel and two proton channels based on the measured LET of the particle. If the measured LET is less than 0.8 MeV, the particle belongs to the electron channel, otherwise it belongs to proton channels. HEPD is installed in the direction of $0^{\circ}$, $45^{\circ}$, $90^{\circ}$ against the along-track of a satellite to enable the efficient measurement of high energy particles. HEPD detects electrons with the energy of 0.1 MeV to several MeV and protons with the energy of more than a few MeV. Thus, the study on the dynamic mechanism of these particles in the Earth radiation belt will be performed.

• Journal of Environmental Health Sciences
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• v.45 no.6
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• pp.658-667
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• 2019

Objective: This study was designed to compare construction types and seasonal radon concentrations in dwellings in Jeollabuk-do Province in Korea. Methods: The measurement of indoor radon concentrations in 79 dwellings using alpha-track detectors was performed every three months (seasonally) over one year between 2015 and 2016. Also, Radon concentrations in soil were measured in spring to investigate the correlations between the concentrations in soil and indoor air. Results: The annual average concentration of indoor radon for dwellings was 89.7±72.1(GM: 72.4) Bq/㎥, with a range (min-max) of 17.2 to 505.4 Bq/㎥. The highest indoor radon concentration was measured in winter and the lowest was shown in summer. The geometric mean of radon concentration in winter was 1.03-2.58 times higher than other seasons. Radon concentrations in soil were investigated at the depth of 1 m, and the concentrations ranged from 1,780 Bq/㎥ to 123,264 Bq/㎥. This showed low correlations with indoor radon concentrations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.813-827
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• 2017

Surveillance cameras installed in tunnels capture the various video frames effected by dynamic and variable factors. In addition, localizing and managing the cameras in tunnel is not affordable, and quality of capturing frame is effected by time. In this paper, we introduce a new method to detect and track the vehicles in tunnel by using surveillance cameras installed in a tunnel. It is difficult to detect the video frames directly from surveillance cameras due to the motion blur effect and blurring effect on lens by dirt. In order to overcome this difficulties, two new methods such as Differential Frame/Non-Maxima Suppression (DFNMS) and Haar Cascade Detector to track cars are proposed and investigated for their feasibilities. In the study, it was shown that high precision and recall values could be achieved by the two methods, which then be capable of providing practical data and key information to an automatic accident detection system in tunnels.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.123-128
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• 2012

In this paper, we propose a landmark-detection system of object for more accurate object recognition. The landmark-detection system of object becomes divided into a learning stage and a detection stage. A learning stage is created an interest-region model to set up a search region of each landmark as pre-information necessary for a detection stage and is created a detector by each landmark to detect a landmark in a search region. A detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. The proposed system uses Fast Fourier Transform to detect landmark, because the landmark-detection is fast. In addition, the system fails to track objects less likely. After we developed the proposed method was applied to environment video. As a result, the system that you want to track objects moving at an irregular rate, even if it was found that stable tracking. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.2
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• pp.83-92
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• 2018

Using ground moving target indicators equipped with synthetic aperture radars for locating moving targets within a wide background clutter in a short time is an excellent method for monitoring traffic. Although the displaced phase center antenna (DPCA) technique and along track interferometry (ATI) are real time methods with low computational complexity, they are essential for reducing cases of false alarm that can result in poor performance. In this paper, we propose two detection methods using DPCA and ATI-the parallel fusion method and serial fusion method. Simulation results demonstrate that the proposed detection methods are characterized by low probability of false alarm along with good performance. In particular, the serial fusion method possesses high detection probability along with low probability of false alarm (1/5th of the false alarm probability of the DPCA technique).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.609-617
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• 2017

Railways are one of the safest and most important transportation systems in the world. On the other hand, due to the increasing complexity of the railway system and the running distance of rail vehicles, railway accidents occur continuously every year. In particular, in the case of high-speed trains and freight trains, if the function of the axle bearing is lost due to abnormal overheating of the axle box bearing, the load on the axle becomes uneven. Therefore, abnormal overheating in the train axle box bearings can cause serious accidents or derailments. For this purpose, a Hot Box Detector (HBD) was installed in the track side of a high speed line to detect abnormal overheating. This paper proposes an EWMA technique-based axle temperature monitoring method to detect abnormal overheating quickly and efficiently. A statistical design of the proposed method was also performed. The proposed method has better performance compared to the current method in the case of abnormal overheating and the performance is improved by approximately 170% at the maximum.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.28-38
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• 2001

Traffic information can be broadly categorized into point information and spatial information. Point information can be obtained by chocking only the presence of vehicles at prespecified points(small area), whereas spatial information can be obtained by monitoring large area of traffic scene. To obtain spatial information by image processing, we need to track vehicles in the whole area of traffic scene. Image detector system based on global tracking consists of video input, vehicle detection, vehicle tracking, and traffic information measurement. For video input, conventional approaches used auto iris which is very poor in adaptation for sudden brightness change. Conventional methods for background generation do not yield good results in intersections with heave traffic and most of the early studies measure only point information. In this paper, we propose user-controlled iris method to remedy the deficiency of auto iris and design flame difference-based background generation method which performs far better in complicated intersections. We also propose measurement method for spatial traffic information such as interval volume/lime/velocity, queue length, and turning/forward traffic flow. We obtain measurement accuracy of 95%∼100% when applying above mentioned new methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.1100-1112
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• 1998

In this paper, a novel method of minimizing the phase error is proposed. A DP-PLL system using this method is implemented and its performacnce is investigated, too. The DP-PLL system detects the phase error between reference clock and locally generated system clock. The phase difference is then reported as a PEV(Phase Error Variation), which is propoced from the delayted n-tap rising dege clock circuit with 5ns resolution in the phase detector. The algorithm is used to track the optimal DAC coefficients, which are adjusted from sample to sample in such a way as to minimize the PEV. The proposed method is found to have remarkable good potential for fast and accurate phase error tracking characteristic. The algorithm shows good performance to supress the low frequency jitter.-ending points, we design new basis functions based on the Legendre polynomial and then transform the error signals with them. When applied to synthetic images such as circles, ellipses and etc., the proposed method provides, in overall, outstanding results in respect to the transform coding gain compared with DCT and DST. And in the case when applied to natural images, the proposed method gives better image quality over DCT and comparable results with DST.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.1-9
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• 2008

In this paper, we proposed automatic face detection and tracking which is robustness in rotation. To detect a face image in complicated background and various illuminating conditions, we used face skin color detection. we used Harris corner detector for extract facial feature points. After that, we need to track these feature points. In traditional method, Lucas-Kanade feature tracker doesn't delete useless feature points by occlusion in current scene (face rotation or out of camera). So we proposed the estimation function, which delete useless feature points. The method of delete useless feature points is estimation value at each pyramidal level. When the face was occlusion, we deleted these feature points. This can be robustness to face rotation and out of camera. In experimental results, we assess that using estimation function is better than traditional feature tracker.