Results 21 to 30 of about 1,193,865 (259)
Egyptian Informatics Journal, 2022 the drivers that enable a view of traffic flow and the volume of vehicles available on the road remotely, intending to avoid traffic jams. The proposed model improves traffic flow and decreases congestion. The proposed system provides an accuracy of 95% and a
Muhammad Saleem +5 more
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Traffic engineering with elastic traffic [PDF]
2013 IEEE Global Communications Conference (GLOBECOM), 2013 In the network layer, an internet service provider controls the traffic across an autonomous system by load balancing via traffic engineering and by varying the offered traffic of the users via feedback signals. In the transport layer, users send traffic into the network using the TCP protocol, which adjusts offered traffic according to the received ...
null Chiun Lin Lim, null Ao Tang
openaire +1 more source
Traffic and related self-driven many-particle systems [PDF]
, 2000 Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by “phantom traffic jams ...
D. Helbing
semanticscholar +1 more source
Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction [PDF]
Italian National Conference on Sensors, 2017 This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and
Xiaolei Ma +5 more
semanticscholar +1 more source
Deep packet: a novel approach for encrypted traffic classification using deep learning [PDF]
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2017 Network traffic classification has become more important with the rapid growth of Internet and online applications. Numerous studies have been done on this topic which have led to many different approaches.
M. Lotfollahi +3 more
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IEEE transactions on intelligent transportation systems (Print), 2021 Accurate short-time traffic flow prediction has gained gradually increasing importance for traffic plan and management with the deployment of intelligent transportation systems (ITSs).
Haifeng Zheng +3 more
semanticscholar +1 more source
Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions
IEEE transactions on intelligent transportation systems (Print), 2021 Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic prediction can assist route planing, guide vehicle dispatching, and mitigate traffic congestion.
Xueyan Yin +5 more
semanticscholar +1 more source
Reciprocal control of viral infection and phosphoinositide dynamics
FEBS Letters, EarlyView.Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source
Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control [PDF]
IEEE transactions on intelligent transportation systems (Print), 2019 Reinforcement learning (RL) is a promising data-driven approach for adaptive traffic signal control (ATSC) in complex urban traffic networks, and deep neural networks further enhance its learning power. However, the centralized RL is infeasible for large-
Tianshu Chu +3 more
semanticscholar +1 more source
IEEE Internet of Things Journal, 2021 Identification of anomaly and malicious traffic in the Internet-of-Things (IoT) network is essential for the IoT security to keep eyes and block unwanted traffic flows in the IoT network.
M. Shafiq +4 more
semanticscholar +1 more source