Results 31 to 40 of about 914,936 (268)
Policy-Compliant Maximum Network Flows
Applied Sciences, 2019 Computer network administrators are often interested in the maximal bandwidth that can be achieved between two nodes in the network, or how many edges can fail before the network gets disconnected.
Pieter Audenaert +2 more
doaj +1 more source
PLoS ONE, 2023 The networks of factor flows in rural areas are the main support for rural revitalization, which has become one of the research trends in rural geography.
Zhi Li
doaj +1 more source
Detection of Malicious Network Flows with Low Preprocessing Overhead
Network, 2022 Machine learning (ML) is frequently used to identify malicious traffic flows on a network. However, the requirement of complex preprocessing of network data to extract features or attributes of interest before applying the ML models restricts their use ...
Garett Fox, Rajendra V. Boppana
doaj +1 more source
Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate [PDF]
, 2016 With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers.
Amor, B +5 more
core +1 more source
IEEE Access, 2019 Network attack behavior detection using deep learning is an important research topic in the field of network security. Currently, there are still many challenges in detecting multi-class imbalanced abnormal traffic data.
Yong Zhang +5 more
doaj +1 more source
Analysis of Multiple Flows using Different High Speed TCP protocols on a General Network
, 2016 We develop analytical tools for performance analysis of multiple TCP flows (which could be using TCP CUBIC, TCP Compound, TCP New Reno) passing through a multi-hop network.
Poojary, Sudheer, Sharma, Vinod
core +1 more source
On Network Science and Mutual Information for Explaining Deep Neural Networks
, 2020 In this paper, we present a new approach to interpret deep learning models. By coupling mutual information with network science, we explore how information flows through feedforward networks.
Bhardwaj, Kartikeya +4 more
core +1 more source
Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling
IEEE Open Journal of Signal ProcessingAnomaly detection (AD) is increasingly recognized as a key component for ensuring the resilience of future communication systems. While deep learning has shown state-of-the-art AD performance, its application in critical systems is hindered by concerns ...
Lukas Schynol, Marius Pesavento
doaj +1 more source
Hop-Based dynamic fair scheduler for wireless Ad-Hoc networks [PDF]
, 2014 In a typical multihop Ad-Hoc network, interference and contention increase when flows transit each node towards destination, particularly in the presence of cross-traffic.
Ghita, B., Lancaster, D., Marchang, Jims
core +1 more source
Network flows for functions [PDF]
2011 IEEE International Symposium on Information Theory Proceedings, 2011 16 pages, 4 ...
Shah, Virag +2 more
openaire +2 more sources