• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1927-1943
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• 2016

Jitterbug is a passive network covert timing channel supplying reliable stealthy transmission. It is also the basic manner of some improved covert timing channels designed for higher undetectability. The existing entropy-based detection scheme based on training sample binning may suffer from model mismatching, which results in detection performance deterioration. In this paper, a new detection method based on the feature of Jitterbug covert channel traffic is proposed. A fixed binning strategy without training samples is used to obtain bins distribution feature. Coefficient of variation (CV) is calculated for several sets of selected bins and the weighted mean is used to calculate the final CV value to distinguish Jitterbug from normal traffic. Furthermore, the timing window parameter of Jitterbug is estimated based on the detected traffic. Experimental results show that the proposed detection method can achieve high detection performance even with interference of network jitter, and the parameter estimation method can provide accurate values after accumulating plenty of detected samples.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.110-123
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• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.951-969
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• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.1-15
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• 1988

DS1 transmission systems use framing bit errors, bipolar violations and code-detected errors to estimate the bit error rate when determining errored and severely errored seconds. Using the coefficient of variation under the memoryless binary symmetric channel assumption, a basic framework to evaluate these estimation schemes is proposed to provide a practical guideline in determining errored and severely errored seconds which are fundamental in monitoring the real-ime error performance of DS1 transmission systems carrying live traffic. To evaluate the performance of the cyclic redundancy check code (CRC), a computer simulation model is used. Several drawbacks of the superframe format in association with real time error performance monitoring are discussed. A few recommendations are suggested in measuring errored and severely errored seconds, and determining service limit alarms through the use of the superframe format. Furthermore, we propose a new robust scheme for determining service limit alarms which take into consideration the limitations of some estimation schemes for the time interval of one second.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.63-74
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• 2010

Recently, there has been increasing demand from academic society in Korea for the improvement of current traffic congestion cost estimation methods. The purpose of this study is to suggest a better way to estimate congestion cost followed by in-depth review regarding traffic congestion. The key improvements proposed in this study include: 1) adding social externality to congestion cost, 2) integrating the green house and environmental pollution impacts with congestion costs, 3) taking non-recurrent traffic congestion costs into account for the assessment, 4) revising the criteria to determining the level of traffic congestion speed, and 5) deciding how to limit congestion measurement period. It is found meaningful that the improvements, notwithstanding difficulties in their real case application, provide invaluable insights in our efforts to change the meaning of congestion cost in an era of sustainable growth.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.83-93
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• 2002

To improve the performance of estimation, the research that uses additional information addition to traffic count and target OD with additional survey cost have been studied. The purpose of this paper is to improve the performance of OD estimation by reducing the feasible solutions with cost-efficiently additional information addition to traffic counts and target OD. For this purpose, we Propose the OD estimation method with sample link use proportion as additional information. That is, we obtain the relationship between OD trip and link flow from sample link use proportion that is high reliable information with roadside survey, not from the traffic assignment of target OD. Therefore, this paper proposes OD estimation algorithm in which the conservation of link flow rule under the path-based non-equilibrium traffic assignment concept. Numerical result with test network shows that it is possible to improve the performance of OD estimation where the precision of additional data is low, since sample link use Proportion represented the information showing the relationship between OD trip and link flow. And this method shows the robust performance of estimation where traffic count or OD trip be changed, since this method did not largely affected by the error of target OD and the one of traffic count. In addition to, we also propose that we must set the level of data precision by considering the level of other information precision, because "precision problem between information" is generated when we use additional information like sample link use proportion etc. And we Propose that the method using traffic count as basic information must obtain the link flow to certain level in order to high the applicability of additional information. Finally, we propose that additional information on link have a optimal counting location problem. Expecially by Precision of information side it is possible that optimal survey location problem of sample link use proportion have a much impact on the performance of OD estimation rather than optimal counting location problem of link flow.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1788-1796
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• 1997

In this paper, we propose a new connection admission control(CAC) algorithm for traffic control in ATM network in which traffic estimation is performed based on user-specified parameters at every moment of connection request or connection release by recursive formula which makes real-time calculation possible. And traffic estimation using cell flow measurement is carried out when the number of connectioned calls does not change during a measurement reflection period. Performance analysis of the proposed method is carried out using several aspects for homogeneous and heterogeneous bursty traffic. The results showed that the proposed CAC method revealed better performance, than conventional CAC method for burst model in both utilization and QoS point of view.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.396.1-396
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• 2002

The AVT under traffic-induced vibrations was carried out on Namhae Suspension bridge in Korea. Mode shapes as well as natural frequencies up to the 15th mode were acquired exactly, and the effect of traffic mass and temperature on measured natural frequencies was investigated. The results from the AVT are compared with those from forced vibration test(FVT) and FE analysis. (omitted)

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.1045-1049
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• 2001

Before building houses or apartments, we need to predict noise propagation to eliminate possible noise problems to residents. However, we do not try to predict noise propagation during estimation of noise effect for the developing area since we did not have a good mathematical model to predict noise level due to a traffic noise. In this article, an adequate mathematical model has been developed and proved to predict noise effect to living area due to a traffic noise.