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Stress concentration is when stress intensifies near discontinuities such as holes or abrupt cross-sectional changes in a structural member. This localized stress can often surpass the average stress within the member. The stress distribution in flat bars, either with a circular hole or varying widths connected by fillets, can be determined experimentally using a photoelastic method. The results are based on ratios of geometric parameters like the ratio of the hole's radius to the smaller...
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Microtubules are hollow cylindrical filaments having a diameter of approximately 25 nm and a length that varies from 200 nm to 25 μm. GTP-bound tubulin subunits form αβ-heterodimers for microtubule assembly. These core building blocks interact longitudinally, polymerizing into protofilaments. The protofilaments then interact with one another through lateral bonding forces to form stable cylindrical microtubules. These cylindrical filaments are dynamic as they undergo repeated...
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基于结构和嵌入的中心性在超图中的网络脆弱性.

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此摘要是机器生成的。

在超图中识别关键节点是网络安全的关键. 结合结构和嵌入特征的新方法显著改善了网络脆弱性分析,性能优于现有的方法.

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科学领域:

  • 网络科学 网络科学
  • 数据挖掘 数据挖掘
  • 机器学习 机器学习

背景情况:

  • 识别关键节点对于网络安全和稳定性至关重要.
  • 在超图中识别重要节点的现有方法往往忽略了组合结构和嵌入信息.
  • 超图分析对于建模复杂系统越来越重要.

研究的目的:

  • 提出新的中心性措施,用于在超图中识别重要节点.
  • 调查将节点嵌入纳入结构中心性的措施的影响.
  • 评估这些新方法在评估网络脆弱性的有效性.

主要方法:

  • 研究了两个拓结构中心性,考虑了共同的节点和超边缘.
  • 开发了一种基于表示学习的嵌入中心性的超图.
  • 提出了四个改进的集中性,将节点嵌入与结构性质集成在一起.
  • 使用六个现实世界数据集评估网络脆弱性.

主要成果:

  • 建议的方法在六个超图中的五个中超过了基线方法.
  • 整合嵌入功能与结构中心性显著提高了性能.
  • 基于单一结构的中心系统在结合嵌入时表现出明显的改善.
  • 节点嵌入相似性分析提供了对结果的启发式理解.

结论:

  • 结合超图结构和节点嵌入,为重要的节点识别提供了一种卓越的方法.
  • 提出的中心性措施在分析网络脆弱性方面是有效的.
  • 嵌入增强的结构中心性代表了对超图分析未来研究的有希望的方向.