• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.33-40
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• 2010

In this paper, we consider three macroscopic traffic flow monitoring indices, Travel Time Index(TTI), Acceleration Noise(AN) and Two Fluid(TF) and investigate how to determine a proper rate of probe cars for producing reliable values of these indices. For the analysis, we use classical sampling theories and provide numbers of probe rates using simulation data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.546-548
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• 2011

Various technologies for resource monitoring such as network traffic, IP resource usages have been developed. PING protocol message is one of the most simple, powerful way to monitor the network resources. In this paper we describe the efficient way to serves a real-time traffic information reports such as IP usage statistics by using saved database information. And we serve web-based traffic information services, so it can monitor a traffics more efficiently.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1017-1021
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• 2013

The traffic signal has been widely used in the transport system with a fixed time interval currently. This kind of setting time was determined based on experience for vehicles to generate a waiting time while allowing pedestrians crossing the street. However, this strict setting causes inefficient problems in terms of economic and safety crossing. In this research, we propose a monitoring algorithm to detect, track and check pedestrian crossing the crosswalk by the patterns of behavior. This monitoring system ensures the safety for pedestrian and keeps the traffic flow in efficient. In this algorithm, pedestrians are detected by using HOG feature which is robust to illumination changes in outdoor environment. According to a complex computation, the parallel process with the GPU as well as CPU is adopted for real-time processing. Therefore, pedestrians are tracked by the relationship of hue channel in image sequence according to the predefined pedestrian zone. Finally, the system checks the pedestrians' crossing on the crosswalk by its HOG based behavior patterns. In experiments, the parallel processing by both GPU and CPU was performed so that the result reaches 16 FPS (Frame Per Second). The accuracy of detection and tracking was 93.7% and 91.2%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3946-3965
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• 2018

Network anomaly detection in Software Defined Networking, especially the detection of DDoS attack, has been given great attention in recent years. It is convenient to build the Traffic Matrix from a global view in SDN. However, the monitoring and management of high-volume feature-rich traffic in large networks brings significant challenges. In this paper, we propose a moving window Principal Components Analysis based anomaly detection and mitigation approach to map data onto a low-dimensional subspace and keep monitoring the network state in real-time. Once the anomaly is detected, the controller will install the defense flow table rules onto the corresponding data plane switches to mitigate the attack. Furthermore, we evaluate our approach with experiments. The Receiver Operating Characteristic curves show that our approach performs well in both detection probability and false alarm probability compared with the entropy-based approach. In addition, the mitigation effect is impressive that our approach can prevent most of the attacking traffic. At last, we evaluate the overhead of the system, including the detection delay and utilization of CPU, which is not excessive. Our anomaly detection approach is lightweight and effective.

• Asian Journal of Atmospheric Environment
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• v.6 no.2
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• pp.96-103
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• 2012

Ambient particulate matter (PM) and particle-bound polycyclic aromatic hydrocarbon (PAH) concentrations were measured continuously for 70 days at a Korean elementary school located near a highway. The $PM_{10}$, $PM_{2.5}$, and $PM_1$ values were measured with a light-scattering, multi-channel, aerosol spectrometer (Grimm, Model 1.107). The number concentrations of the particles were measured using a scanning mobility particle sizer and counter (SMPS+C) which counted particles from 11.1 to 1083.3 nm classified in 44 channels. Particle-bound PAHs were measured with a direct reading, photoelectric aerosol sensor. The daily $NO_2$, $SO_2$, and CO concentrations were obtained from a national air-monitoring station located near the school. The average concentrations of $PM_{10}$, $PM_{2.5}$, and $PM_1$ were 75.3, 59.3, and $52.1{\mu}g/m^3$, respectively. The average number concentration of the ultrafine particles (UFPs) was $46,307/cm^3$, and the averaged particle-bound PAHs concentration was $17.9ng/cm^3$ during the study period. The ambient UFP variation was strongly associated with traffic intensity, particularly peak concentrations during the traffic rush hours. Particles <100 nm corresponded to traffic-related pollutants, including PAHs. Additional longterm monitoring of ambient UFPs and high-resolution traffic measurements should be carried out in future studies. In addition, transient variations in the ambient particle concentration should be taken into consideration in epidemiology studies in order to examine the short-term health effects of urban UFPs.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.369-381
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• 2019

As tactical networks are gradually shifting toward IP-based flexible operation for diversified battlefield services, QoS(Quality-of-Service) coordination for service differentiation becomes essential to overcome the heterogeneous and scarce networking resources limitations. QoS coordination for tactical network traffic should be able to monitor and react the dynamic changes in underlying network topology and service priorities. In this paper, by adopting the emerging cloud-native service mesh concept into tactical network context, we study the feasibility of intelligent QoS coordination by employing tactical service mesh(TSM) as an additional layer to support enhanced traffic quality monitoring and control. The additional TSM layer can leverage distributed service-mesh proxies at tactical mesh WAN(Wide Area Network) nodes so that service-aware differentiated QoS coordination can be effectively designed and integrated with TSM-assisted traffic monitoring and control. Also, by validating the feasibility of TSM layer for QoS coordination with miniaturized experimental setup, we show the potential of the proposed approach with several approximated battlefield traffics over a simulated TSM-enabled tactical network.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.6
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• pp.575-582
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• 2016

Seoul city has high population density as well as high traffic congestion, which are vulnerable to exposure of environmental pollutions caused by car traffic. However, recent studies are only on local regions about road traffic and air pollution or health effect of road traffic on residents. Thus, comprehensive study data are needed in terms of overall Seoul regions. In this study utilized the nitrogen dioxide concentration through the national air pollution monitoring network data, 2012 to 2013. It also divided regions into high and low exposure districts via the Origin destination data developed by the Korea transport institute to quantify and evaluate the effect of transport policies and analyzed a correlation of asthma symptoms with high and low exposure districts through raw data of community health survey from the Korea centers for disease control and prevention. Based on the collected data, the pearson's correlation analysis was conducted between air pollution substance concentration and high exposure district and multiple logistic regression analysis was conducted to determine the effect of traffic environment and factors on asthma symptoms of residents. Accordingly, the following results were derived. First, the high exposure district was higher concentrations of nitrogen dioxide ($NO_2$) as per time compared to those of the low exposure district (p<0.01). Second, analysis on correlation between average daily environmental concentration in the air pollution monitoring network and road traffic showed that nitrogen dioxide had a significant positive correlation (p<0.01) with car traffic and total traffic as well as with truck traffic (p<0.05) statistically. Third, an adjusted odds ratio about asthma doctor's diagnosis in the high and low exposure districts was analyzed through the logistic regression analysis. With regard to an adjusted model 2 (adjusted gender, age, health behavior characteristics, and demographic characteristics) odds ratio of asthma doctor's diagnosis in the high exposure district was 1.624 (95% CI: 1.269~2.077) compared to that of the low exposure district, which was significant statistically (p<0.001).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.1-6
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• 2012

In this paper, we propose a HMM(Hidden Markov Model)-based segmentation method to model shadows as well as foreground and background regions. The shadow of moving objects often keeps from visual tracking. We propose an HMM-based segmentation method which classifies each object in real time. In the case of traffic monitoring movies, the effectiveness of the proposed method was proved by experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.528-533
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• 2000

This paper is concerned to remote monitoring It management system on the bring up house of agricultural, lomestic animal, aquatic products. That is necessary for traffic network and monitoring unit for transmission the environment data of temperature, humidity and electric etc.. This study is executed the experimental research for structure of system. which are composed sensing interface, multi-processing, traffic network and algorithm. Result, that is respected the effective management, increase of produce and prevent of calamity on the bring up house by low cost of set & remain.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.16-22
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• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.