• Steel and Composite Structures
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• 제25권5호
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• pp.603-615
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• 2017

This experimental research presents the seismic performance of steel reinforced high-strength concrete (SRHC) short columns. Eleven SRHC column specimens were tested under simulated earthquake loading conditions, including six short column specimens and five normal column specimens. The parameters studied included the axial load level, stirrup details and shear span ratio. The failure modes, critical region length, energy dissipation capacity and deformation capacity, stiffness and strength degradation and shear displacement of SRHC short columns were analyzed in detail. The effects of the parameters on seismic performance were discussed. The test results showed that SRHC short columns exhibited shear-flexure failure characteristics. The critical region length of SRHC short columns could be taken as the whole column height, regardless of axial load level. In comparison to SRHC normal columns, SRHC short columns had weaker energy dissipation capacity and deformation capacity, and experienced faster stiffness degradation and strength degradation. The decrease in energy dissipation and deformation capacity due to the decreasing shear span ratio was more serious when the axial load level was higher. However, SRHC short columns confined by multiple stirrups might possess good seismic behavior with enough deformation capacity (ultimate drift ratio ${\geq}2.5%$), even though a relative large axial load ratio (= 0.38) and relative small structural steel ratio (= 3.58%) were used, and were suitable to be used in tall buildings in earthquake regions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권7호
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• pp.1831-1853
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• 2012

By sending periodically short bursts of traffic to reduce legit transmission control protocol (TCP) traffic, the low-rate denial of service (LDoS) attacks are hard to be detected and may endanger covertly a network for a long period. Traditionally, LDoS detecting methods mainly concentrate on the attack stream with feature matching, and only a limited number of attack patterns can be detected off-line with high cost. Recent researches divert focus from the attack stream to the traffic anomalies induced by LDoS attacks, which can detect more kinds of attacks with higher efficiency. However, the limited number of abnormal characteristics and the inadequacy of judgment rules may cause wrong decision in some particular situations. In this paper, we address the problem of detecting LDoS attacks and present a scheme based on the fluctuant features of legit TCP and acknowledgment (ACK) traffic. In the scheme, we define judgment criteria which used to identify LDoS attacks in real time at an optimal detection cost. We evaluate the performance of our strategy in real-world network topologies. Simulations results clearly demonstrate the superiority of the method proposed in detecting LDoS attacks.

• 한국멀티미디어학회논문지
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• 제18권2호
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• pp.189-198
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• 2015

Despite the fact that traffic engineering techniques have been comprehensively utilized in the past to enhance the performance of communication networks, the distinctive characteristics of Software Defined Networking (SDN) demand new traffic engineering techniques for better traffic control and management. Considering the behavior of traffic, large flows normally carry out transfers of large blocks of data and are naturally packet latency insensitive. However, small flows are often latency-sensitive. Without intelligent traffic engineering, these small flows may be blocked in the same queue behind megabytes of file transfer traffic. So it is very important to identify large flows for different applications. In the scope of this paper, we present an approach to detect large flows in real-time without even a short delay. After the detection of large flows, the next problem is how to control these large flows effectively and prevent network jam. In order to address this issue, we propose an approach in which when the controller is enabled, the large flow is mitigated the moment it hits the predefined threshold value in the control application. This real-time detection, marking, and controlling of large flows will assure an optimize usage of an overall network.

• 디지털콘텐츠학회 논문지
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• 제5권1호
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• pp.7-11
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• 2004

차세대 고속 통신망을 구축하기 위해서는 해결해야 할 많은 문제들이 있는데, 이 중에서 기본적으로 고려해야 할 사항은 바로 망에 흐르는 트래픽의 특성 분석이다. 현재 제공되는 많은 인터넷 서비스들의 동작 특성은 자기 유사성(Self-similar)이라는 기존에 고려되던 트래픽 특성과는 완전히 다른 장기간 의존성의 성질들을 가진다는 것이 증명되었다 이러한 장기간 의존성 성질을 표현하기 위한 모델로는 자기유사 모델이 있는데, 이것은 단기간 의존성을 표현하는 기존의 모델인 포아송 모델과는 상반되는 개념이다. 따라서 차세대 통신망의 설계 및 디멘져닝을 위해서는 무엇보다도 데이터 트래픽의 주요 특성인 버스트성(Burstiness)과 자기유사성이 반영된 트래픽 모델이 요구된다. 여기서 자기유사성은 허스트 파라미터(Hurst Parameter)로 특성화 될 수 있다. 본 논문에서는 데이터 트래픽의 자기유사성 및 큐잉지연을 고려한 유효대역폭 산출식을 유도하여 시뮬레이션 결과와 비교 분석하였다.

• Geomechanics and Engineering
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• 제32권1호
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• pp.35-47
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• 2023

Deformability of road pavements in the form of ruts represent a safety risk for road users. In the procedures for dimensioning the pavement structure, the requirement that such deformations do not occur is imperatively included, which results in the appropriate selection of elements (material, geometry) of the pavement structure. Deformability and functionality, will depend of the correct design of pavement structure during exploitation period. Nevertheless, there are many examples where deformations are observed on the pavement structure, in the form of rutting at parts of the road with relatively short length, realised in the same climatic and the same geoenvironmental conditions. The performed analysis of deformability led to the conclusion that the level of deformation is a function of the speed of traffic. This effect is observed on city roads, but also outside of urban areas at roads with speed limits are significant, due to the traffic management, traffic jams (intersections, etc.). Still, the lower speed cause greater deformations. The authors tried to describe the deformability of flexible pavement structures, from the aspects of geotechnical problems, as a function of driving speed. Outcome of the analysis is a traffic load correction coefficient, in terms of using the existing methods of flexible pavement structures design.

• 한국도로학회논문집
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• 제14권5호
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• pp.101-111
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• 2012

PURPOSES: Because expressway ramps are very complex segments where diverse roadway design elements dynamically change within relatively short length, drivers on ramps are required to drive their cars carefully for safety. Especially, ramps on expressways are designed to guarantee driving at high speed so that the risk and severity of traffic accidents on expressway ramps may be higher and more deadly than other facilities on expressways. Safe deceleration maneuvers are required on off-ramps, whereas safe acceleration maneuvers are necessary on onramps. This difference in required maneuvers may contribute to dissimilar patterns and severity of traffic accidents by ramp types. Therefore, this study was aimed at developing prediction models of the severity of traffic accidents on expressway on- and off-ramps separately in order to consider dissimilar patterns and severity of traffic accidents according to types of ramps. METHODS: Four-year-long traffic accident data between 2007 and 2010 were utilized to distinguish contributing design elements in conjunction with AADT and ramp length. The prediction models were built using the negative binomial regression model consisting of the severity of traffic accident as a dependent variable and contributing design elements as in independent variables. RESULTS: The developed regression models were evaluated using the traffic accident data of the ramps which was not used in building the models by comparing actual and estimated severity of traffic accidents. Conclusively, the average prediction error rates of on-ramps and offramps were 30.5% and 30.8% respectively. CONCLUSIONS: The prediction models for the severity of traffic accidents on expressway on- and off-ramps will be useful in enhancing the safety on expressway ramps as well as developing design guidelines for expressway ramps.

• 대한토목학회논문집
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• 제42권1호
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• pp.67-74
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• 2022

최근 높은 스마트폰 보급율과 ITS (intelligent transportation systems) 인프라 확충 등 정보통신기술(information and communications technology, ICT) 이용 활성화로 실시간 교통정보의 수집원이 증가하였다. 이렇게 다양하게 수집되는 실시간 교통정보의 정확도는 VDS(vehicle detection system), DSRC (dedicated short-range communications), GPS (global positioning system) probe와 같은 다양한 교통정보 수집원별 시공간 혹은 교통상황 등 다양한 환경에 따라 다르게 나타날 수 있다. 본 연구의 목적은 이질적 교통정보가 동시에 수집될 경우, 실시간 교통정보의 정확도를 향상시키기 위한 융합 전략의 제시에 있다. 이를 위해 고속국도(892.2 km, 227개 링크), 일반국도(937.0 km, 2,074개 링크)를 대상으로 주행 조사를 실시하였으며, 해당 링크 및 시간대에 probe 차량 5대의 평균 통행속도는 실시간 교통정보 수집원별(VDS or DSRC, GPS-based A, B) 정확도 평가의 기준 혹은 참값으로 활용되었다. 결과적으로 제시된 융합 전략에 대한 정확도 개선 효과는 일반국도에서 1개 수집원을 제외하고 모두 통계적으로 유의한 것으로 나타났으며, 향후 다양한 기관으로부터 서비스되는 실시간 교통정보가 동시에 연계되는 환경에서 보다 정확한 교통정보 서비스의 가능성을 확인하였다.

• 한국재난정보학회 논문집
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• 제14권2호
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• pp.230-237
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• 2018

연구목적: 현재 국내에서는 지능형 교통체계(Intelligent transport system)의 일환으로 실시간 교통정보를 수집하여 도로운영의 효율성을 높이고 있다. 하지만 실시간 자료를 기반으로 한 교통정보는 운전자가 경험하게 될 교통상황과는 차이가 존재한다. 연구방법: 본 연구에서는 기존 교통량 이력자료 바탕으로 이력자료의 과거참조일수를 3일, 5일, 10일로 조정하여 요일별, 시간대별로 장래의 고속도로 교통량 예측을 수행하였다. 연구결과: 과거 참조일수가 적을수록 예측오차가 작게 나타나는 것을 알 수 있었다. 5번의 과거이력을 참조하여 월요일을 예측한 결과는 10번의 과거이력을 참조했을 때보다 오차가 크게 나타났는데 이는 분석대상 기간인 2016년의 6번째 월요일이 명절이기 때문에 평소의 월요일 교통흐름과는 다소 차이가 있었기 때문으로 판단된다. 결론: 본 연구를 통해 교통량예측 시 과거이력의 참조일수가 적을수록 비교적 오차가 적은 것을 알 수 있었으며 특수한 날에는 해당 이벤트의 교통량이력의 자료를 사용하면 보다 정확도 높은 결과를 나타낼 수 있을 것으로 판단된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.240-259
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• 2020

Analyzing network traffic is the basis of dealing with network security issues. Most of the network security systems depend on the feature selection of network traffic data and the detection ability of malicious traffic in network can be improved by the correct method of feature selection. An FAFS method, which is short for Fuzzy Association Feature Selection method, is proposed in this paper for network malicious traffic detection. Association rules, which can reflect the relationship among different characteristic attributes of network traffic data, are mined by association analysis. The membership value of association rules are obtained by the calculation of fuzzy reasoning. The data features with the highest correlation intensity in network data sets are calculated by comparing the membership values in association rules. The dimension of data features are reduced and the detection ability of malicious traffic detection algorithm in network is improved by FAFS method. To verify the effect of malicious traffic feature selection by FAFS method, FAFS method is used to select data features of different dataset in this paper. Then, K-Nearest Neighbor algorithm, C4.5 Decision Tree algorithm and Naïve Bayes algorithm are used to test on the dataset above. Moreover, FAFS method is also compared with classical feature selection methods. The analysis of experimental results show that the precision and recall rate of malicious traffic detection in the network can be significantly improved by FAFS method, which provides a valuable reference for the establishment of network security system.

• 한국ITS학회 논문지
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• 제13권2호
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• pp.12-26
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• 2014

이 연구에서는 교통사고 영향요인 중 야간의 시인성 저하가 교통사고 발생에 미치는 영향을 진단하였다. 연구를 위해 경기지역의 경부선, 서해안선, 영동선, 서울외곽순환고속도로의 기본구간을 58개의 소구간으로 분할하였고, 2009년에서 2012년 상반기까지 소구간에서 발생한 교통사고 410건을 이용하여 야간의 어두움으로 인한 시인성 저하가 교통사고에 미치는 영향을 진단하였다. 실험방법은 준실험설계를 준용하여 시인성 외 교통사고에 영향을 주는 변인을 통제하고 음이항 회귀분석을 활용하였다. 조사 결과, 맑음 기상조건에서의 LOS A 상태 등 특정조건에서 주간과 야간의 시인성 차이가 교통사고 발생에 유의한 영향을 미치는 것으로 진단되었다. 그리고 진단 결과를 이용하여 교통사고의 유형과 원인에 대하여 다양한 분석을 시도하였다.