• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.521-526
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• 2003

In this study the traffic noises were investigated for the subjective allowing limitation ion and the testified classes, 7 point scale was selected to evaluate the annoyance level with vocabularies. As a result, 'relatively annoying' is the most suitable expression for the allowing 1imitation, and the sound pressure levels for the traffic was 44.4㏈.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.473-494
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• 2020

To provide a guaranteed Quality of Service (QoS) to real-time traffic in High-Speed Downlink Packet Access (HSDPA) core network, we proposed an enhanced mechanism. For an enhanced QoS, a Class-Based Low Latency Fair Queueing (CBLLFQ) packet scheduling algorithm is introduced in this work. Packet classification, metering, queuing, and scheduling using differentiated services (DiffServ) environment was the points in focus. To classify different types of real-time voice and multimedia traffic, the QoS provisioning mechanisms use different DiffServ code points (DSCP).The proposed algorithm is based on traffic classes which efficiently require the guarantee of services and specified level of fairness. In CBLLFQ, a mapping criterion and an efficient queuing mechanism for voice, video and other traffic in separate queues are used. It is proved, that the algorithm enhances the throughput and fairness along with a reduction in the delay and packet loss factors for smooth and worst traffic conditions. The results calculated through simulation show that the proposed calculations meet the QoS prerequisites efficiently.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1534-1542
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• 2004

A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.19-33
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• 2011

The need for application traffic classification becomes important for the effective use of network resources. The header-based identification method uses the header signature {IP address, port number, transport layer protocol TCP/UDP)}extracted from Internet application server to overcome some limitations overhead, payload encryption, etc.) of previous methods. A lots signature is extracted because this method uses header information of server. So, we need a maintenance method to keep essential signatures. In this paper, we represent the signature maintenance method using properties of identified traffic and history of the signature. Also, we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.85-100
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• 2018

In this study, we formulated rational criteria to efficiently provide traffic information services via a crafted approach. By utilizing this, we presented a detailed traffic information service providing method that can overcome the limitations of existing link unit information provision system. Three methodologies such as user survey, data mining, and KHCM (Korea Highway Capacity Manual) utilization method were applied to formulate a rational expression standard for traffic information service. Each method was designed to establish a quantitative criterion for various traffic conditions and to enable user-oriented traffic information service in consideration of the traffic principal/compatibility. Considering the results of each methodological analysis in a comprehensive manner, the basic expression standards for traffic information service was formulated. Then we presented improvements such as traffic condition step by road, speed range of traffic condition, expression term of traffic condition and so on. In order to complement the problems of the information provision system of the existing link unit based on the derived improvement criterion, we presented the detailed traffic information service provision method by using the traffic speed data of the second order. And we applied this to the two links of Daegu city. The method presented in this research can improve the quality of traffic information service. Not only it can be used for various fields such as optimal route search, traffic safety service and so on.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.23-29
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• 2014

The advanced traffic management system of intelligent transport systems automates the related traffic tasks such as vehicle speed, traffic volume and traffic incidents through the improved infrastructures like high definition cameras, high-performance radar sensors. For the safety of road users, especially, the automated incident detection and secondary accident prevention system is required. Normally, CCTV based image object detection and radar based object detection is used in this system. In this paper, we proposed the algorithm for real time highway incident detection system using multi surveillance cameras to mosaic video and track accurately the moving object that taken from different angles by background modeling. We confirmed through experiments that the video detection can supplement the short-range shaded area and the long-range detection limit of radar. In addition, the video detection has better classification features in daytime detection excluding the bad weather condition.

• International Journal of Highway Engineering
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• v.7 no.3 s.25
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• pp.43-52
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• 2005

Highway classification is an essential part of defining design criteria of roads. This study is to classify highways by factor analysis. To accomplish the objectives, factor analysis is performed for classifying highways using the traffic data observed at the permanent traffic count points in 2004. A total off variables are applied : AADT, K factor, D factor, heavy vehicle proportion, day time traffic volume proportion, peak hour volume proportion, sunday factor, vacation factor and COV(Coefficient of Variation). The results of factor analysis show that variables are divided into two factors, which are the factor related to the fluctuational characteristics of traffic volume and the factor related to heavy vehicle and directional volume characteristics. According to the results of cluster analysis, 353 permanent traffic count points are categorized into such three groups as type I for urban highway, type II for rural highway, type III for recreational highway, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.1082-1089
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• 2012

Recent malicious attempts in Cyber space are intended to emerge national threats such as Suxnet as well as to get financial benefits through a large pool of comprised botnets. The evolved botnets use the Domain Name System(DNS) to communicate with the C&C server and zombies. DNS is one of the core and most important components of the Internet and DNS traffic are continually increased by the popular wireless Internet service. On the other hand, domain names are popular for malicious use. This paper studies on DNS-based cyber threats domain detection by data classification based on supervised learning. Furthermore, the developed cyber threats domain detection system using DNS traffic analysis provides collection, analysis, and normal/abnormal domain classification of huge amounts of DNS data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1D
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• pp.45-51
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• 2010

Traffic volume is essential data for traffic control or maintenance and rehabilitation planning. The volume especially with respect to the type of vehicles can facilitate to those road operations. In this research, a method for vehicle classification was developed using skewed sensors which can generate traffic signatures. In order to characterize vehicle types, the method investigates whether the second axle of each vehicle consists of dual tires. The presence of dual tire is determined by the discriminate function obtained from discriminant analysis. The validation using 1,878 vehicles recorded from a highway using a CCTV camera indicated significantly accurate results: 96.92% for class 1, 82.91% for class 3 and 79.13% for class 4.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.3
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• pp.48-54
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• 2016

This paper proposes a prediction model of air traffic controller's take-off clearance under mixed mode runway operations. The proposed model has its purpose on the better prediction of the air traffic controller's clearance on take-offs of departure aircraft by considering various factors. For this purpose, support vector machine classification algorithm is used for the proposed model. The proposed model is applied to real air traffic operations to demonstrate its performances.