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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

647
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
647
Distributed Loads01:19

Distributed Loads

538
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
538
Relation Between the Distributed Load and Shear01:23

Relation Between the Distributed Load and Shear

643
Understanding the relationship between the distributed load and shear force in structural analysis is crucial for analyzing beams subjected to various loading conditions. Consider the case of a beam experiencing a distributed load, two concentrated loads, and a couple moment.
643
Elastic Curve from the Load Distribution01:16

Elastic Curve from the Load Distribution

180
The structural behavior of beams under distributed loads is critical for engineering analysis, which focuses on predicting how beams bend and react under such conditions. Different types of beams (e.g., cantilever, supported, or overhanging) behave differently under distributed load conditions.
For all beams, the analysis of the beam's reaction to distributed loads begins by understanding the relationship between a beam's load and the resulting shear forces and bending moments.
180
Beams with Symmetric Loadings01:15

Beams with Symmetric Loadings

190
The moment-area method is an analytical tool used in structural engineering to determine the slope and deflection of beams under various loads. Consider a cantilever with a concentrated load and moment at the free end. The first step is constructing a free-body diagram to calculate the reactions at the fixed end. Next, the bending moment diagram is plotted to visualize how the bending moment varies along the beam's length, focusing on points where the bending moment equals zero.
The M/EI...
190
Beams with Unsymmetric Loadings01:17

Beams with Unsymmetric Loadings

122
Analyzing a supported beam under unsymmetrical loadings is essential in structural engineering to understand how beams respond to varied force distributions. This analysis involves calculating the deflection and identifying points where the slope of the beam is zero, which are crucial for ensuring structural stability and functionality.
The first moment-area theorem determines the slope at any point on the beam. This theorem indicates that the change in slope between two points on a beam...
122

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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一个基于云环境中区域之间负载平衡算法的安全解决方案.

Sarah Eljack1, Mahdi Jemmali1,2,3, Mohsen Denden4,5

  • 1Department of Computer Science and Information, College of Science at Zulfi, Majmaah University, Majmaah, Saudi Arabia.

PeerJ. Computer science
|December 11, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种新的云数据存储模型,通过优化区域和区域选择来最大限度地减少文件传输事件. 拟议的"调度器"组件和"分组方法"算法有效地平衡数据负载,提高敏感信息的安全性.

关键词:
算法算法是一种算法.云计算是一种云计算.云安全 云安全 云安全网络安全 网络安全建模建模模型是什么优化优化 优化优化

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科学领域:

  • 云计算和数据存储的数据存储.
  • 信息安全和数据管理信息安全和数据管理
  • 算法设计和优化 算法设计和优化

背景情况:

  • 在云中存储敏感数据会因为全球网络传输而带来风险,可能会增加安全漏洞.
  • 不高效的数据配置可能导致区域之间不必要的文件传输,增加运营成本和复杂性.
  • 尽量减少数据迁移对于维护安全和优化云环境中资源利用至关重要.

研究的目的:

  • 开发一种用于跨云区域调度文件的新型模型,平衡安全性和负载.
  • 通过优化对敏感数据存储的区域和区域选择来最大限度地减少文件传输事件的数量.
  • 解决分布式云环境中最佳文件放置的NP难题.

主要方法:

  • 提出了一种新的云数据存储模型,其中包括一个"调度器"组件.
  • 引入了一种"分组方法",有几种变体,用于生成用于文件调度的新算法.
  • 开发和评估了七个初始算法,其中三种组合产生了改进的结果,导致六个选择的算法用于性能分析.

主要成果:

  • 在四个类别中测试了1360个实例,使用三个指标来评估算法性能.
  • "四个算法的最佳值"表现出卓越的性能,在86.5%的案例中获得最佳结果.
  • 性能最好的算法平均间隙为0.021秒,平均运行时间为0.0018秒.

结论:

  • 提出的模型和算法有效地解决了云中安全和高效的敏感数据存储的挑战.
  • 优化的文件调度可以最大限度地减少数据传输事件,并提高整体云数据管理安全性.
  • "四个算法的最佳值"为云数据放置问题提供了强大而高效的解决方案.