• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.241-246
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• 2010

This study is to estimate the link travel time of road networks in urban areas utilizing traffic information which is collected throughout the operation of Bus Information System (BIS). BIS, which applies the hightech information technology to an existing bus system, has been developing and operating in many bodies including the local self-government entities. However, a study to consider the technology trend is relatively rare. Even though some useful traffic informations have been collected throughout the operation of an existing BIS, which set limits to the development of a future service of integrated analysis. Accordingly, in this study, a fundamental research is performed for traffic controls in urban areas and providing a traffic information for driver throughout the estimation of link travel time of road networks. The study is proceeded throughout the data collected from the operation of BIS (Bus Information System). The result showed that the patterns of going through traffic were divided up to 2 in the bus travel time in BIS then estimate two link travel time.

• Journal of the Korea Society of Computer and Information
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• v.6 no.3
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• pp.64-71
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• 2001

In this paper we propose the network traffic monitoring system that can supported network and system operation, management, expansion, and design using network analysis and diagnosis to a network administrator. The proposed system consists of two parts: analysis server for collection and analysis of the network information. and supports real-time monitoring of network traffic, and client system shows user a graphical data that analyzed a returned result from the server This system implements web-based technology using java and contributes to enhance the effectiveness of network administrator's management.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.127-135
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• 2007

As the Internet is used widely, criminal offense that use computer is increasing, and an information security technology to remove this crime is becoming competitive power of the country. In this paper, we suggest network-based intrusion detection system that use fuzzy expert system. This system can decide quick intrusion decision from attack pattern applying fuzzy rule through the packet classification method that is done similarity of protocol and fixed time interval. Proposed system uses fuzzy logic to detect attack from network traffic, and gets analysis result that is automated through fuzzy reasoning. In present network environment that must handle mass traffic, this system can reduce time and expense of security

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.21-40
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• 2003

A traffic accident analysis method was developed and tested based on the highway alignment risk indices using geographic information systems(GIS). Impacts of the highway alignment on traffic accidents have been identified by examining accidents occurred on different alignment conditions and by investigating traffic accident risk indices(TARI). Evaluative criteria are suggested using geometric design elements as an independent variable. Traffic accident rates were forecasted more realistically and objectively by considering the interaction between highway alignment factors and the design consistency. And traffic accident risk indices and risk ratings were suggested based on model estimation results and accident data. Finally, forecasting traffic accident rates, evaluating the level of risk and then visualizing information graphically were combined into one system called risk assessment system by means of GIS. This risk assessment system is expected to play a major role in designing four-lane highways and developing remedies for highway sections susceptible to traffic accidents.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.995-999
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• 2010

Every year, traffic accidents and traffic congestion have been rapidly increasing, Although the roadway design and signal system have been improved to relieve traffic accidents, traffic casualties and property damage do not decrease. This paper develops a real-time traffic accident detection and analysis system (RTADAS): In the proposed system, we aim to precisely detect traffic accidents at different design and flow of intersections, However, because the data collected from intersections have uncertainty and complicated causal dependency between them, we construct probability-based networks for correct accident detection.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.281-291
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• 2017

Nowadays, as traffic jams are a daily elementary problem in both developed and developing countries, systems to monitor, predict, and detect traffic conditions are playing an important role in research fields. Comparing them, researchers have been trying to solve problems by applying many kinds of technologies, especially roadside sensors, which still have some issues, and for that reason, any one particular method by itself could not generate sufficient traffic prediction results. However, these sensors have some issues that are not useful for research. Therefore, it may not be best to use them as stand-alone methods for a traffic prediction system. On that note, this paper mainly focuses on predicting traffic conditions based on a hybrid prediction approach, which stands on accuracy comparison of three prediction models: multinomial logistic regression, decision trees, and support vector machine (SVM) classifiers. This is aimed at selecting the most suitable approach by means of integrating proficiencies from these approaches. It was also experimentally confirmed, with test cases and simulations that showed the performance of this hybrid method is more effective than individual methods.

• Journal of the Korean Institute of Navigation
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• v.20 no.2
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• pp.51-58
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• 1996

For the smooth flow of traffic vehicles and its effective management, it is necessary to have an exact information on traffic condition, i.e., the volume of traffic, velocity, occupancy and classification of vehicles. In particular, for classification of vehicles, there has been only image processing method using camera, where the method can obtain much information but rather expensive. In this paper, an algorithm for the measurement of velocity and total length of vehicles has been proposed to develop a general traffic management system, which is necessary to discriminate the class of vehicles. In order to realize the proposed algorithm, we have developed an ultrasonic spatial filtering method, which has better performance than that of using the traditional vehicle detector. To have this system to be constructed, we have introduced three sets of ultrasonic devices where each has one transmitter and two receivers which are arranged to obtain the spatial difference of objects. The velocity of vehicles can be measured by analyzing the occurrence time of pulses and their time differences. The total length of vehicles can be given by multiplying velocity with time interval of pulses sequence. To confirm the effectiveness of this measuring system, the experiment by the spatial filtering method using the ultrasonic sensors has been carried out. As the results, it is found that the proposed method can be used as one of measurement tools in the general traffic management system.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.89-95
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• 2008

In this paper, we propose an integrated techniques for managing data quality in traffic data warehousing environments. We describe how to collect and construct the traffic data warehouses from the operational databases, such as FTMS and ARTIS. We explain how to configure the traffic data warehouses efficiently. Also, we propose a quality management techniques to provide high quality traffic data for various analytical transactions. Proposed techniques can contribute in providing high quality traffic data to the traffic related users and researcher, thus reducing data preprocessing and evaluation cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2355-2373
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• 2011

Vision-based vehicle detector systems are becoming increasingly important in ITS applications. Real-time operation, robustness, precision, accurate estimation of traffic parameters, and ease of setup are important features to be considered in developing such systems. Further, accurate vehicle detection is difficult in varied complex traffic environments. These environments include changes in weather as well as challenging traffic conditions, such as shadow effects and jams. To meet real-time requirements, the proposed system first applies a color background to extract moving objects, which are then tracked by considering their relative distances and directions. To achieve robustness and precision, the color background is regularly updated by the proposed algorithm to overcome luminance variations. This paper also proposes a scheme of feedback compensation to resolve background convergence errors, which occur when vehicles temporarily park on the roadside while the background image is being converged. Next, vehicle occlusion is resolved using the proposed prior split approach and through reasoning for rule-based tracking. This approach can automatically detect straight lanes. Following this step, trajectories are applied to derive traffic parameters; finally, to facilitate easy setup, we propose a means to automate the setting of the system parameters. Experimental results show that the system can operate well under various complex traffic conditions in real time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.3
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• pp.579-589
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• 2017

The cloud environment is hypervisor-based, and many virtual machines are interconnected, which makes propagation of malicious code easier than other environments. Accordingly, this paper proposes a malicious traffic dynamic analysis system for secure cloud environment. The proposed system continuously monitors and analyzes malicious activity in an isolated virtual network environment by distinguishing malicious traffic that occurs in a cloud environment. In addition, the analyzed results are reflected in the distinguishment and analysis of malicious traffic that occurs in the future. The goal of this research is secure and efficient malicious traffic dynamic analysis by constructing the malicious traffic analysis environment in the cloud environment for detecting and responding to the new and variant malicious traffic generated in the cloud environment.