• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권4호
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• pp.1307-1323
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• 2014

With the exhaustion of global IPv4 addresses, IPv6 technologies have attracted increasing attentions, and have been deployed widely. Meanwhile, new applications running over IPv6 networks will change the traditional traffic characteristics obtained from IPv4 networks. Traditional models obtained from IPv4 cannot be used for IPv6 network monitoring directly and there is a need to investigate those changes. In this paper, we explore the flow features of IPv6 traffic and compare its difference with that of IPv4 traffic from flow level. Firstly, we analyze the differences of the general flow statistical characteristics and users' behavior between IPv4 and IPv6 networks. We find that there are more elephant flows in IPv6, which is critical for traffic engineering. Secondly, we find that there exist many one-way flows both in the IPv4 and IPv6 traffic, which are important information sources for abnormal behavior detection. Finally, in light of the challenges of analyzing massive data of large-scale network monitoring, we propose a group flow model which can greatly reduce the number of flows while capturing the primary traffic features, and perform a comparative measurement analysis of group users' behavior dynamic characteristics. We find there are less sharp changes caused by abnormity compared with IPv4, which shows there are less large-scale malicious activities in IPv6 currently. All the evaluation experiments are carried out based on the traffic traces collected from the Northwest Regional Center of CERNET (China Education and Research Network), and the results reveal the detailed flow characteristics of IPv6, which are useful for traffic management and anomaly detection in IPv6.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1996년도 가을 학술발표회 논문집
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• pp.131-137
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• 1996

To perform condition monitoring of P.C. Box girder bridge under ambient traffic, dynamic characteristics were identified using the results of load test an analysis. It was found that natural frequencies obtained from the measured acceleration data for the forced vibration part and free vibration part were nearly identical. Thus it can be concluded that dynamic parameters are properly determined under ambient traffic condition. Finite element model for analysis was calibrated using measured frequencies. Change of dynamic characteristics were predicted through analysis of the established finite element model with anticipated change.

• 대한전자공학회논문지TC
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• 제43권9호
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• pp.69-79
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• 2006

영상 정보를 이용한 교통 모니터링 시스템에 관한 많은 연구가 이루어졌다. 대부분의 교통 모니터링 기술은 전체 영상을 분석하는 기법과 국부 영역을 검사하는 기법으로 구분된다. 하지만, 제안된 대부분의 기법들은 동작 환경이 변화할 경우 강건성의 결여로 인해 성능이 급격히 저하하는 문제점을 갖고 있다. 본 논문에서는 기존의 논문에서 제안되었던 다양한 기법들의 특성을 조사하고, 장점과 단점을 분석한다. 또한 각 응용 분야마다 영상 처리를 이용하는 기법들이 가지고 있는 문제점들을 해결 할 수 있는 적절한 방법을 고찰한다.

• 융합보안논문지
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• 제16권5호
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• pp.41-48
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• 2016

본 논문은 플로우 시각화 기반의 네트워크 보안 상황 감시 방법인 VisFlow를 제안하며, 기존 트래픽 플로우 시각화 기술의 단점인 대량 트래픽 발생 시의 직관성 상실 문제, 대칭적 주소 공간에 의한 반사현상 문제, 종단간 연결 의미의 상실 문제를 해결하고자 한다. VisFlow는 단순하고 효율적인 보안 시각화 인터페이스로써 플로우 시각화 기술을 활용하여 개별적인 트래픽 데이터들에서는 볼 수 없었던 다양한 네트워크 현상들을 패턴으로 형상화하고 관리 네트워크 내의 보안 상황을 실시간으로 분석 및 감시하는 방법이다. 트래픽 플로우의 포트 역할 분석 방법을 이용하여 노드 유형과 중요 정보를 식별 분류하고, 분류된 정보는 중요도에 따라 2D/3D 공간 상에 단순화 및 강조하여 표시함으로써 직관성과 실용성을 높인다. 또한, IP주소값에 기반한 비대칭적 노드 배치를 통해 반사현상 문제를 해결하고 노드간의 연결선을 활용하여 종단간의 세션 의미를 유지함으로써 정보성은 높인다. 관리자는 VisFlow를 통해 방대한 트래픽 데이터를 쉽게 탐색하고 전체 네트워크 상황을 직관적으로 파악함으로써 네트워크 보안 상황을 효과적으로 감시할 수 있다.

• 한국환경과학회지
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• 제15권8호
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• pp.737-744
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• 2006

Present study was designed to characterize the concentrations of major roadside air pollutants in Daegu and to compare with those of Seoul and Busan. Evaluated were the exceedance frequence of mean concentrations of target compounds(CO, NO$_2$, O$_3$, PM$_{10}$, SO$_2$) and the relationship for time variation. Two air pollution monitoring stations(one roadside station and one residential station) in Daegu were selected for this study. In addition, one roadside monitoring station from each of Seoul and Busan was chosen for the comparison of Daegu monitoring stations. The data analyzed in the current study were collected from 1998 to 2000 by Daegu Regional Environmental Management Office. The roadside concentrations of NO2 and PM to and the exceedance frequency of ambient air standard levels in Daegu were higher than those of Seoul and Busan. Except 03, the roadside concentrations of all target compounds showed following three distinguished patterns; first, possibly due to increased traffic density, the concentrations increased from 0500 to 0900(LST), second, the concentrations decreased from 0900 to 1700(LST) possibly due to the increased wind velocity and decreased traffic density, and finally, increased traffic density, the concentrations increased again from 1700 to 2100(LST). An implication was that major air pollution sources shifted from residential area to road-area during rush hours.

• International Journal of Concrete Structures and Materials
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• 제2권2호
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• pp.91-98
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• 2008

Curved bridges are important components of a highway transportation network for connecting local roads and highways, but very few data have been collected in terms of their field performance. This paper presents two-years monitoring and system identification results of a curved concrete box-girder bridge, the West St. On-Ramp, under ambient traffic excitations. The authors permanently installed accelerometers on the bridge from the beginning of the bridge life. From the ambient vibration data sets collected over the two years, the element stiffness correction factors for the columns, the girder, and boundary springs were identified using the back-propagation neural network. The results showed that the element stiffness values were nearly 10% different from the initial design values. It was also observed that the traffic conditions heavily influence the dynamic characteristics of this curved bridge. Furthermore, a probability distribution model of the element stiffness was established for long-term monitoring and analysis of the bridge stiffness change.

• 전기전자학회논문지
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• 제13권2호
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• pp.140-149
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• 2009

최근 인터넷을 통한 각종 침해사고 및 트래픽 폭주와 같은 현상이 급격하게 증가함에 따라 네트워크의 비정상적 상황을 조기에 탐지하기 위한 보다 능동적이고 진보적인 기술이 요구되고 있다. 본 논문에서는 캠퍼스 네트워크와 같이 트래픽이 주기적인 특성을 띠는 환경에서 Fisher 선형 분류법(FLD)을 사용하여 트래픽을 두 개의 그룹으로 분류하고, 네트워크에 유입되는 트래픽이 어떤 그룹에 속하는지를 판별하는 기법을 제안한다. 이를 위해 WISE-Mon이라 불리는 트래픽 분석 시스템을 개발하여 캠퍼스 네트워크의 트래픽을 수집하고 이를 모니터링해서 분석을 수행한다. 생성된 트래픽의 training set을 이용하여 비정상 트래픽의 범위를 판단하기 위한 chi-square distribution을 유도하고, FLD를 적용하여 유입되는 트래픽을 두 그룹으로 분리하기 위한 초평면 (hyperplane)을 만든다. 또한 네트워크 내의 트래픽 패턴이 시간이 지남에 따라 계속적으로 변하는 상황을 반영하기 위하여 self-learning 알고리즘을 적용한다. 캠퍼스 네트워크의 트래픽을 적용한 수학적 결과를 통하여 제안하는 기법의 정확성과 신뢰도를 보여준다.

• 한국도로학회논문집
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• 제17권4호
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• pp.135-141
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• 2015

PURPOSES: This study has been conducted to determine a homogeneous segment and integration to improve the efficiency of short-term traffic count. We have also attempted to reduce the traffic monitoring budget. METHODS: Based on the statistical approach, a homogeneous segment in the same road section is determined. Statistical analysis using t-test, mean difference, and correlation coefficient are carried out for 10-year-long (2004-2013) short-term count traffic data and the MAPE of fresh data (2014) are evaluated. The correlation coefficient represents a trend in traffic count, while the mean difference and t-score represent an average traffic count. RESULTS : The statistical analysis suggests that the number of target segments varies with the criteria. The correlation coefficient of more than 30% of the adjacent segment is higher than 0.8. A mean difference of 36.2% and t-score of 19.5% for adjacent segments are below 20% and 2.8, respectively. According to the effectiveness analysis, the integration criteria of the mean difference have a higher effect as compared to the t-score criteria. Thus, the mean difference represents a traffic volume similarity. CONCLUSIONS : The integration of 47 road segments from 882 adjacent road segments indicate 8.87% of MAPE, which is within an acceptable range. It can reduce the traffic monitoring budget and increase the count to improve an accuracy of traffic volume estimation.

• 한국도로학회논문집
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• 제18권3호
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• pp.109-114
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• 2016

PURPOSES : The demand for extending national highways is increasing, but traffic monitoring is hindered because of resource limitations. Hence, this study classified highway segments into 5 types to improve the efficiency of short-term traffic count planning. METHODS : The traffic volume trends of 880 highway segments were classified through R-squared and linear regression analyses; the steadiness of traffic volume trends was evaluated through coefficient of variance (COV), and the normality of the data were determined through the Shapiro-Wilk W-test. RESULTS : Of the 880 segments, 574 segments had relatively low COV and were classified as type 1 segments, and 123 and 64 segments with increasing and decreasing traffic volume trends were classified as type 2 and type 3 segments, respectively; 80 segments that failed the normality test were classified as type 4, and the remaining 39 were classified as type 5 segments. CONCLUSIONS : A theoretical basis for biennial count planning was established. Biennial count is recommended for types 1~4 because their mean absolute percentage errors (MAPEs) are approximately 10%. For type 5 (MAPE =19.26%), the conventional annual count can be continued. The results of this analysis can reduce the traffic monitoring budget.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.179-180
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• 2006

The real time monitoring of the power systems covering wide area are essential for the stable operation and control of the power system. Synchronized phasor measurement is a key for the precise monitoring and control of the power systems. In this paper, to suggest an appropriate network topology of Power Infrastructure Defense System(PIDS) and to estimate the maximum network bandwidth with using the network analyzer, we simulate a PIDS and analyze the network traffic.