• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.772-776
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• 2005

To support abruptly increasing data traffic in these days, network management is needed. And also to maintain the steady infra, there is MPLS need which can support traffic engineering. It's necessary that MPLS doesn't only manage network to support recently booming data traffic, but has capacity to support traffic engineering to keep static infrastructure. Traffic engineering, method that a large-scale user shifts traffic to the beforehand designated routes that pass through specific nodes on network, is operation that is mapping traffic flow to the physical network topology. In this paper, we supplement the defect of the traditional RSVP traffic engineering and to construct far more steady infra, we suggest the way of its development of ERSVP signaling protocol.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.105-108
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• 2005

To support abruptly increasing data traffic in these days. network management is needed. And also to maintain the steady infra, there is MPLS need which can support traffic engineering. It's necessary that MPLS doesn't only manage network to support recently booming data traffic, but has capacity to support traffic engineering to keep static infrastructure. Traffic engineering, method that a large-scale user shifts traffic to the beforehand designated routes that pass through specific nodes on network, is operation that is mapping traffic flow to the physical network topology. In this paper, we supplement the defect of the traditional RSVP traffic engineering and to construct far more steady infra, we suggest the way of its development of ERSVP signaling protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3230-3253
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• 2017

Android malware steals users' private information, and embedded unsafe advertisement (ad) libraries, which execute unsafe code causing damage to users. The majority of such traffic is HTTP and is mixed with other normal traffic, which makes the detection of malware and unsafe ad libraries a challenging problem. To address this problem, this work describes a novel HTTP traffic flow mining approach to detect and categorize Android malware and unsafe ad library. This work designed AndroCollector, which can automatically execute the Android application (app) and collect the network traffic traces. From these traces, this work extracts HTTP traffic features along three important dimensions: quantitative, timing, and semantic and use these features for characterizing malware and unsafe ad libraries. Based on these HTTP traffic features, this work describes a supervised classification scheme for detecting malware and unsafe ad libraries. In addition, to help network operators, this work describes a fine-grained categorization method by generating fingerprints from HTTP request methods for each malware family and unsafe ad libraries. This work evaluated the scheme using HTTP traffic traces collected from 10778 Android apps. The experimental results show that the scheme can detect malware with 97% accuracy and unsafe ad libraries with 95% accuracy when tested on the popular third-party Android markets.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.230-237
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• 2018

Purpose: In Korea, traffic information is collected in real time as part of Intelligent Transportation System to enhance efficiency of road operation. However, traffic information based on real-time data is different from the traffic situation the driver will experience. Method: In this study, forecasts were made for future highway traffic by day and time period by adjusting the Archived data reference days to 3, 5 and 10 days based on existing traffic Archived data. Results: Fewer days of reference in the past showed smaller errors. The prediction of Monday based on five past histories showed greater errors than the 10 past histories, as the traffic flow on the sixth Monday of 2016 was somewhat different from the usual holiday. Conclution: This study shows that less of the reference days of the past history when estimating traffic volume, the more accurate the data of the traffic history of the event can be used on special days.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.86-99
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• 2021

One of the methods to alleviate traffic congestion is to increase the efficiency of the roads by providing traffic condition information on road user and distributing the traffic. For this, reliability must be guaranteed, and quantitative real-time traffic speed prediction is essential. In this study, and based on analysis of traffic speed related to traffic conditions, historical data correlated with traffic flow were used as input. We developed an LSTM model that predicts speed in response to normal traffic conditions, along with a CNN-LSTM model that predicts speed in response to incidents. Through these models, we try to predict traffic speeds during the hour in five-minute intervals. As a result, predictions had an average error rate of 7.43km/h for normal traffic flows, and an error rate of 7.66km/h for traffic incident flows when there was an incident.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.119-129
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• 2016

PURPOSES : The purpose of this study is to develop a methodology for estimating additional carbon emissions due to freeway incidents. METHODS : As our country grows, our highway policy has mainly neglected the environmental and social sectors. However, with the formation of a national green growth keynote and an increase in the number of people interested in environmental and social issues, problems related to social issues, such as traffic accidents and congestion, and environmental issues, such as the impact of air pollution caused by exhaust gases that are emitted from highway vehicles, are beginning to be discussed. Accordingly, studies have been conducted on a variety of environmental aspects in the field of road transport, and for the quantitative calculation of greenhouse gas emissions, using various methods. However, in order to observe the effects of carbon emissions, microscopic simulations must use many difficult variables such as cost, analysis time, and ease of analysis process. In this study, additional greenhouse gas emissions that occur because of highway traffic accidents were classified by type (incident handling time, number of lanes blocked, freeway level of service), and the annual additional emissions based on incidents were calculated. According to the results, congestion length and emissions tend to increase with an increase in incident clearance time, number of occupied lanes, and worsening level of service. Using this data, we analyzed accident data on the Gyeong-bu Expressway (Yang-Jae IC - Osan IC) for a year. RESULTS : Additional greenhouse gas emissions that occur because of highway traffic accidents were classified by type (incident handling time, number of lanes blocked, freeway level of service) and annual additional emissions caused by accidents were calculated. CONCLUSIONS : In this study, a methodology for estimating carbon emissions due to freeway incidents was developed that incorporates macroscopic flow models. The results of the study are organized in the form of a look-Up table that calculates carbon emissions rather easily.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.133-144
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• 2009

In Korea, the ITS project has been progressed to improve traffic mobility and safety. Further, it is to relieve traffic jam by supply real time travel information for drivers and to promote traffic convenience and safety. It is important that the traffic information is provided accurately. This study was conducted outlier elimination and missing data adjustment to improve accuracy of raw data. A method for raise reliability of travel time prediction information was presented. We developed Historical Profile model and adjustment formula to reflect quality of interrupted flow. We predicted travel time by developed Historical Profile model and adjustment formula and verified by comparison between developed model and existing model such as Neural Network model and Kalman Filter model. The results of comparative analysis clarified that developed model and Karlman Filter model similarity predicted in general situation but developed model was more accurate than other models in incident situation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.79-90
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• 2019

This study aims to develop time headway distribution models of bicycle traffic flow in a uninterrupted bikeway. The sample data were collected and classified into two groups of traffic volume levels. The lower level traffic volume is defined to be under 8 bicycles per minute, and the higher one is greater or equal to 8 bicycles per minute. The data aggregation interval size was set to be 0.5-second. Four distribution models including normal distribution, negative exponential distribution, shifted negative exponential distribution, and Pearson III distribution were tested, and Chi-square test results shows that the negative exponential distribution and the shifted negative exponential distribution are well fitted to the sample data. Another test results with different sample data also shows the same conclusion.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.25-30
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• 2006

Marine traffics near Ulsan approaching waters are crossing and converged at the diverging point of No.1 route- No.2 route and No.1 route -No.3 route and are also concentrated at near No1. route approaching area and the headland of cape Gawnjeol. Because the number of berth will increase to 78 from 49 until 2011 due to additional developments, minor modification is expected for the water utilities. This study examined environmental conditions, marine accidental data, marine traffic capacity, traffic flow survery and fisheries zone status near Ulsan approaching water area. Finally, a questionaire survey was carried ou for experts and users to propose new plan.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.123-133
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• 2015

PURPOSES : This study aimed to develop a new highway capacity estimation method and provide comparative results among traditional capacity estimation methods and the recommended values in the latest version of KHCM. METHODS : The limitations of the existing methods, such as inconsistency and underestimation of the capacity value, are summarized through an extensive literature review. To overcome these limitations, a new method is introduced by adopting a definition of capacity and traffic flow characteristics at or near breakdown points. This method can produce the capacity value by searching a point corresponding to the maximum traffic flow through analysis of gradient changes (point of inflection) of the traffic flow and speed distribution. Comparative results of capacity values from each method are also presented to validate the new method by using data collected from detectors on freeways. RESULTS: From the analysis results, it is shown that a consistent capacity value can be estimated by applying the new method. In addition, the resulting capacity values are 3%-4% higher than those recommended in KHCM. CONCLUSIONS : The capacity values listed in the current KHCM tend to produce underestimated results. The new method presented in this paper may be included in the future edition of KHCM.