• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.183-191
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• 2018

In this study a traffic volume dependent displacement estimation model for Gwangan Bridge was developed using bridge monitoring big data. Traffic volume data for four different vehicle types and the vertical displacement data in the central position of the Gwangan Bridge were used to develop and validate the estimation model. Two statistical estimation models were developed using multiple regression analysis (MRA) and principal component analysis (PCA). Estimation performance of those two models were compared with actual values. The results show that both the MRA and the PCA based models are successfully estimating the vertical displacement of Gwangan Bridge. Based on the results, it is concluded that the developed model can effectively be used to predict the traffic volume dependent displacement behavior of Gwangan Bridge.

• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.41-45
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• 2006

From the 1978 Seasat synthetic aperture radar(SAR) to present systems, spaceborne SAR has demonstrated the capability to image the Earth's ocean and land features over broad areas, day and night, and under most weather conditions. The application of SAR for surveillance of commercial fishing grounds can did in the detection of illegal fishing activities and provides more efficient use cf limited aircraft or patron craft resources. In the area of vessel traffic monitoring for commercial vessels, Vessel Traffic Service (VTS) which uses the ground-based radar system has some difficulties in detecting moving ships due to the limited detection range cf about 10 miles. This paper introduces the field testing results of ship detection by RADARSAT SAR imagery, and proposes a new approach for a Vessel Monitoring System(VMS), including VTS, and SAR combination service.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.11-16
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• 2009

Better understanding of in-situ mechanical behavior of pavement foundations is very important to predict long-term effects on the system performance of transport infrastructure. In order to do that, resilient stiffness characterization of geomaterals is needed to properly adopt such mechanistic analysis under both traffic and environmental loadings. In this paper, in situ monitoring data from KHC test road was used to analyze the non-linearity of stress conditions under traffic and moisture loadings. Then, the predicted non-linear response using finite element method with a selected constitutive model of foundation geomaterials are verified with the field data.

• ETRI Journal
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• v.35 no.2
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• pp.253-258
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• 2013

We propose and demonstrate an efficient power-saving optical network unit (ONU) based on upstream traffic monitoring for 10-Gb/s wavelength division multiplexed passive optical networks (WDM-PONs). The power-saving mode controller uses a ${\mu}$-processor and traffic monitoring modules followed by the proposed power-saving processes to operate the sleep mode ONU. The power consumption of the ONU is effectively reduced from 19.3 W to 6.4 W when no traffic from the users is detected. In addition, we design a power-saving mechanism based on a cyclic sleep mode operation to allow a connectivity check between the optical line terminal and ONU. Our calculation results show that the WDM-PON ONU reduces the power consumption by around 60% using the proposed mechanism.

• Proceedings of KOSOMES biannual meeting
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• 2007.05a
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• pp.127-132
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• 2007

From the 1978 Seasat synthetic aperture radar(SAR) to present systems, spaceborne SAR has demonstrated the capability to image the Earth's ocean and land features over broad areas, day and night, and under most weather conditions. The application of SAR for surveillance of commercial fishing grounds can aid in the detection of illegal fishing activities and provides more efficient use of limited aircraft or patrol craft resources. In the area of vessel traffic monitoring for commercial vessels, Vessel Traffic Service (VTS) which uses the ground-based radar system has some difficulties in detecting moving ships due to the limited detection range of about 10 miles. This paper introduces the field testing results of ship detection by RADARSAT SAR imagery, and proposes a new approach for a Vessel Monitoring System(VMS), including VTS, and SAR combination service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.587-590
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• 2004

In this paper proposed a HMM(Hidden Martov Model)-based segmentation method which is able to model shadows as well as foreground and background regions. Shadow of moving objects often obstruct visual tracking. We propose an HMM-based segmentation method which classifies in real time oath objects. In the case of traffic monitoring movies, the effectiveness of the proposed method has been proven through experimental results

• Structural Engineering and Mechanics
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• v.17 no.5
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• pp.655-670
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• 2004

This paper aims to evaluate the effect of typhoons on fatigue damage accumulation in steel decks of long-span suspension bridges. The strain-time histories at critical locations of deck sections of long-span bridges during different typhoons passing the bridge area are investigated by using on-line strain data acquired from the structural health monitoring system installed on the bridge. The fatigue damage models based on Miner's Law and Continuum Damage Mechanics (CDM) are applied to calculate the increment of fatigue damage due to the action of a typhoon. Accumulated fatigue damage during the typhoon is also calculated and compared between Miner's Law and the CDM method. It is found that for the Tsing Ma Bridge case, the stress spectrum generated by a typhoon is significantly different than that generated by normal traffic and its histogram shapes can be described approximately as a Rayleigh distribution. The influence of typhoon loading on accumulative fatigue damage is more significant than that due to normal traffic loading. The increment of fatigue damage generated by hourly stress spectrum for the maximum typhoon loading may be much greater than those for normal traffic loading. It is, therefore, concluded that it is necessary to evaluate typhoon induced fatigue damage for the purpose of accurately evaluating accumulative fatigue damage for long-span bridges located within typhoon prone regions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• Journal of KIISE:Information Networking
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• v.34 no.2
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• pp.81-87
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• 2007

This paper proposes architecture of Linux-based Network Traffic Control Test-bed (NTCT) that easily implements reconfigurable network environment. The proposed NTCT consists of traffic generator that uses the simulation results of NS2 simulator, traffic controller using Linux kernel, and traffic monitor. This paper also includes the analysis example using the proposed NTCT.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.105-110
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• 2022

Traffic sign recognition plays an important role in solving traffic-related problems. Traffic sign recognition and classification systems are key components for traffic safety, traffic monitoring, autonomous driving services, and autonomous vehicles. A lightweight model, applicable to portable devices, is an essential aspect of the design agenda. We suggest a lightweight convolutional neural network model with residual blocks for traffic sign recognition systems. The proposed model shows very competitive results on publicly available benchmark data.