Parametric Multiroute Flow and Its Application to Robust Network with $$k$$ Edge Failures

2014 ◽  
pp. 26-37
Author(s):  
Jean-François Baffier ◽  
Vorapong Suppakitpaisarn ◽  
Hidefumi Hiraishi ◽  
Hiroshi Imai
Keyword(s):  
Robust Network

scholarly journals Learning Region-Based Attention Network for Traffic Sign Recognition

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 686
Author(s):  
Ke Zhou ◽  
Yufei Zhan ◽  
Dongmei Fu
Keyword(s):  
High Resolution ◽  
Traffic Sign Recognition ◽  
Traffic Sign ◽  
Attention Network ◽  
Sign Recognition ◽  
Learning Region ◽  
Robust Network ◽  
Traffic Sign Classification

Traffic sign recognition in poor environments has always been a challenge in self-driving. Although a few works have achieved good results in the field of traffic sign recognition, there is currently a lack of traffic sign benchmarks containing many complex factors and a robust network. In this paper, we propose an ice environment traffic sign recognition benchmark (ITSRB) and detection benchmark (ITSDB), marked in the COCO2017 format. The benchmarks include 5806 images with 43,290 traffic sign instances with different climate, light, time, and occlusion conditions. Second, we tested the robustness of the Libra-RCNN and HRNetv2p on the ITSDB compared with Faster-RCNN. The Libra-RCNN performed well and proved that our ITSDB dataset did increase the challenge in this task. Third, we propose an attention network based on high-resolution traffic sign classification (PFANet), and conduct ablation research on the design parallel fusion attention module. Experiments show that our representation reached 93.57% accuracy in ITSRB, and performed as well as the newest and most effective networks in the German traffic sign recognition dataset (GTSRB).

scholarly journals An approach to robust network design in telecommunications

2007 ◽  
Vol 41 (4) ◽  
pp. 411-426 ◽  
Author(s):  
Georgios Petrou ◽  
Claude Lemaréchal ◽  
Adam Ouorou
Keyword(s):  
Network Design ◽  
Robust Network Design ◽  
Robust Network

scholarly journals Neural and genetic degeneracy underlies Caenorhabditis elegans feeding behavior

2014 ◽  
Vol 112 (4) ◽  
pp. 951-961 ◽  
Author(s):  
Nicholas F. Trojanowski ◽  
Olivia Padovan-Merhar ◽  
David M. Raizen ◽  
Christopher Fang-Yen
Keyword(s):  
Caenorhabditis Elegans ◽  
Neural Circuit ◽  
Dependent Manner ◽  
State Dependent ◽  
Excitatory Pathways ◽  
Genetic Mechanisms ◽  
Genetic Level ◽  
Pharyngeal Pumping ◽  
Robust Network

Degenerate networks, in which structurally distinct elements can perform the same function or yield the same output, are ubiquitous in biology. Degeneracy contributes to the robustness and adaptability of networks in varied environmental and evolutionary contexts. However, how degenerate neural networks regulate behavior in vivo is poorly understood, especially at the genetic level. Here, we identify degenerate neural and genetic mechanisms that underlie excitation of the pharynx (feeding organ) in the nematode Caenorhabditis elegans using cell-specific optogenetic excitation and inhibition. We show that the pharyngeal neurons MC, M2, M4, and I1 form multiple direct and indirect excitatory pathways in a robust network for control of pharyngeal pumping. I1 excites pumping via MC and M2 in a state-dependent manner. We identify nicotinic and muscarinic receptors through which the pharyngeal network regulates feeding rate. These results identify two different mechanisms by which degeneracy is manifest in a neural circuit in vivo.

scholarly journals Application of Grounded Theory in Determining Required Elements for IPv6 Risk Assessment Equation

2018 ◽  
Vol 150 ◽  
pp. 06005
Author(s):  
Athirah Rosli ◽  
Abidah Mat Taib ◽  
Wan Nor Ashiqin Wan Ali ◽  
Ros Syamsul Hamid
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Grounded Theory ◽  
Network Security ◽  
Strategic Planning ◽  
Internet Protocol ◽  
Network Environment ◽  
Ipv6 Network ◽  
Robust Network ◽  
Network Administrators

The deployment of Internet Protocol version 6 (IPv6) has raised security concerns among the network administrators. Thus, in strengthening the network security, administrator requires an appropriate method to assess the possible risks that occur in their networks. Aware of the needs to calculate risk in IPv6 network, it is essential to an organization to have an equation that is flexible and consider the requirements of the network. However, the existing risk assessment equations do not consider the requirement of the network. Therefore, this paper presents the adaptation of grounded theory to search for elements that are needed to develop IPv6 risk assessment (IRA6) equation. The attack scenarios’ experiments; UDP Flooding, TCP Flooding and Multicast attacks were carried out in different network environment to show how the IPv6 risk assessment equation being used. The result shows that the IRA6 equation is more flexible to be used regardless the network sizes and easier to calculate the risk value compared to the existing risk assessment equations. Hence, network administrators can have a proper decision making and strategic planning for a robust network security.

scholarly journals Constraint Generation for Two-Stage Robust Network Flow Problems

2019 ◽  
Vol 1 (1) ◽  
pp. 49-70 ◽  
Author(s):  
David Simchi-Levi ◽  
He Wang ◽  
Yehua Wei
Keyword(s):  
Network Flow ◽  
Network Flow Problems ◽  
Two Stage ◽  
Constraint Generation ◽  
Flow Problems ◽  
Robust Network
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