Traffic sign detection is an important task in traffic sign recognition systems. Chinese traffic signs have their unique features compared with traffic signs of other countries. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, we present a Chinese traffic sign detection algorithm base...

Reliable distinguishing DDOS flood traffic from aggregated traffic is desperately desired by reliable prevention of DDOS attacks. By reliable distinguishing, we mean that flood traffic can be distinguished from aggregated one for a predetermined probability. The basis to reliably distinguish flood traffic from aggregated one is reliable detection of signs of DDOS flood attacks. As is known, rel...

background: detection of best predictor of ovarian reserve in patients with temporarily or consistently elevated early follicular phase serum levels of fsh is one of the most important goals in assisted reproductive technique (art). objective: to evaluate whether high level of anti-mullerian hormone level is related to success of art in patients with temporarily or consistently elevated early f...

Hypotheses and some results of the three-phase traffic theory by the author are compared with results of the fundamental diagram approach to traffic flow theory. A critical discussion of model results about congested pattern features which have been derived within the fundamental diagram approach to traffic flow theory and modelling is made. The empirical basis of the three-phase traffic theory...

We have empirically observed that the average volume change across flows is close to zero in links carrying a large enough number of flows. This flow equilibrium property holds if the flows are nearly independent, and it is violated by traffic changes caused by several, potentially small, correlated flows. Many traffic anomalies fit this description, including scans, DDoS attacks, and routing s...

Anomaly Intrusion Detection System is used to identify a new attack in the network by identifying the deviations in the network traffic patterns. Though it identifies new attacks efficiently, the false alarm rate is usually high in this system. As there may be attack in the network at any time and as the input traffic varies over time, we need a model which efficiently identifies the change in ...

—Due to that the existing traffic facilities can hardly be extended, developing traffic signal control methods is the most important way to improve the traffic efficiency of modern roundabouts. This paper proposes a novel traffic signal controller with two fuzzy layers for signalizing the roundabout. The outer layer of the controller computes urgency degrees of all the phase subsets and then ac...

There is considerable interest in using entropy-based analysis of traffic feature distributions for anomaly detection. Entropy-based metrics are appealing since they provide more fine-grained insights into traffic structure than traditional traffic volume analysis. While previous work has demonstrated the benefits of using the entropy of different traffic distributions in isolation to detect an...

Effective traffic management in urban areas is done by adapting traffic signal times to current traffic conditions. At isolated intersections this task is usually realised by fixed time or by conventional vehicle actuated signal controllers. The fixed time signals use predefined green times, they are reliable and cost-efficient but offer no opportunity to adapt on-line. Especially with rapidly ...

Traffic conditions vary over time, and therefore, traffic behavior should be modeled as a stochastic process. In this study, a probabilistic approach utilizing Autocorrelation is proposed to model the stochastic variation of traffic conditions, and subsequently, predict the traffic conditions. Using autocorrelation of the time series samples of density and flow which are collected from segments...