Impact Analysis of Communication Network Reliability Based on Node Failure

2013 ◽  
Vol 347-350 ◽  
pp. 2100-2105
Author(s):  
Fei Zhao ◽  
Ning Huang ◽  
Jia Xi Chen
Keyword(s):  
Communication Network ◽  
Impact Analysis ◽  
Failure Modes ◽  
Network Reliability ◽  
Node Failure ◽  
Reliability Design ◽  
Complex Network Theory ◽  
And Performance ◽  
Network Reliability Design ◽  
Operation Cost

Node failure is an important factor causing network faults. Through research on node failures, mastering the effect laws of failure is a reasonable and effective method to improve network reliability. This paper summarized and classified the node failure modes of communication network. Meanwhile, combined with the classic BA network model in complex network theory, the effect laws of nodes function failure and performance failure on network reliability were investigated with the design of simulations using MATLAB and OPNET. The results have great guidance value for the simulation of network reliability and network reliability design under limited operation cost.

scholarly journals Percolation Analysis of Brain Structural Network

2021 ◽  
Vol 9 ◽  
Author(s):  
Shu Guo ◽  
Xiaoqi Chen ◽  
Yimeng Liu ◽  
Rui Kang ◽  
Tao Liu ◽  
...  
Keyword(s):  
Failure Modes ◽  
Critical Infrastructure ◽  
Network Reliability ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Structural Features ◽  
Brain Network ◽  
Structure Design ◽  
Reliability Design ◽  
The Brain

The brain network is one specific type of critical infrastructure networks, which supports the cognitive function of biological systems. With the importance of network reliability in system design, evaluation, operation, and maintenance, we use the percolation methods of network reliability on brain networks and study the network resistance to disturbances and relevant failure modes. In this paper, we compare the brain networks of different species, including cat, fly, human, mouse, and macaque. The differences in structural features reflect the requirements for varying levels of functional specialization and integration, which determine the reliability of brain networks. In the percolation process, we apply different forms of disturbances to the brain networks based on metrics that characterize the network structure. Our findings suggest that the brain networks are mostly reliable against random or k-core-based percolation with their structure design, yet becomes vulnerable under betweenness or degree-based percolation. Our results might be useful to identify and distinguish brain connectivity failures that have been shown to be related to brain disorders, as well as the reliability design of other technological networks.

scholarly journals The Implications of Regulatory Framework for Topical Semisolid Drug Products: From Critical Quality and Performance Attributes towards Establishing Bioequivalence

Pharmaceutics ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 710
Author(s):  
Tanja Ilić ◽  
Ivana Pantelić ◽  
Snežana Savić
Keyword(s):  
Statistical Power ◽  
Failure Modes ◽  
In Vitro Release ◽  
Optimal Number ◽  
Drug Products ◽  
Pharmaceutical Equivalence ◽  
And Performance ◽  
Low Sensitivity

Due to complex interdependent relationships affecting their microstructure, topical semisolid drug formulations face unique obstacles to the development of generics compared to other drug products. Traditionally, establishing bioequivalence is based on comparative clinical trials, which are expensive and often associated with high degrees of variability and low sensitivity in detecting formulation differences. To address this issue, leading regulatory agencies have aimed to advance guidelines relevant to topical generics, ultimately accepting different non-clinical, in vitro/in vivo surrogate methods for topical bioequivalence assessment. Unfortunately, according to both industry and academia stakeholders, these efforts are far from flawless, and often upsurge the potential for result variability and a number of other failure modes. This paper offers a comprehensive review of the literature focused on amending regulatory positions concerning the demonstration of (i) extended pharmaceutical equivalence and (ii) equivalence with respect to the efficacy of topical semisolids. The proposed corrective measures are disclosed and critically discussed, as they span from mere demands to widen the acceptance range (e.g., from ±10% to ±20%/±25% for rheology and in vitro release parameters highly prone to batch-to-batch variability) or reassess the optimal number of samples required to reach the desired statistical power, but also rely on specific data modeling or novel statistical approaches.

Grey Model Based Particle Swarm Optimization Algorithm for Anticorrosion Reliability Design of Underground Pipelines

2010 ◽  
Vol 118-120 ◽  
pp. 541-545
Author(s):  
Qin Ming Liu ◽  
Ming Dong
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Failure Modes ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Grey Model ◽  
Swarm Optimization ◽  
Reliability Design ◽  
Model Based ◽  
Underground Pipelines

This paper explores the grey model based PSO (particle swarm optimization) algorithm for anti-cauterization reliability design of underground pipelines. First, depending on underground pipelines’ corrosion status, failure modes such as leakage and breakage are studied. Then, a grey GM(1,1) model based PSO algorithm is employed to the reliability design of the pipelines. One important advantage of the proposed algorithm is that only fewer data is used for reliability design. Finally, applications are used to illustrate the effectiveness and efficiency of the proposed approach.

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