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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

676
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...
676
Distributed Loads01:19

Distributed Loads

558
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...
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Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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RAPT: A Robust Attack Path Tracing Algorithm to Mitigate SYN-Flood DDoS Cyberattacks.

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Author Spotlight: Enhancing Cryo-Electron Microscopy by Automated Data Collection and Analysis Techniques
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在智能城市的多云节点之间复制文件段:机器学习方法

Nour Mostafa1, Yehia Kotb1, Zakwan Al-Arnaout1

  • 1College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait.

Sensors (Basel, Switzerland)
|July 11, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种新型模型,用于在多云和边缘计算环境中高效地复制数据,优化智能城市和物联网 (IoT) 的资源共享. 该模型最大限度地降低了成本,同时提高了数据可用性和访问速度.

关键词:
数据复制数据的复制.边缘服务器 边缘服务器正式的方法 正式的方法物联网 (IoT) 的物联网 (IoT) 的物联网.机器学习是机器学习.多云服务是多云服务.部分复制的部分复制.这是一个回归回归的回归.系统的健全性 系统的健全性

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科学领域:

  • 云计算 云计算 云计算
  • 边缘计算 边缘计算
  • 物联网 (IoT) 的物联网 (IoT) 的物联网.
  • 智慧城市管理 智慧城市管理
  • 大数据管理大数据管理

背景情况:

  • 智慧城市和物联网管理提出了复杂的,多维的挑战,特别是在云计算和边缘计算中.
  • 在这些分布式环境中,资源共享是提高整体系统性能的关键组成部分.
  • 在分布式应用程序中管理多petabyte数据集和增加用户/资源数量需要先进的解决方案.

研究的目的:

  • 解决异质多云系统中当前大数据管理方法的局限性.
  • 提出一种新的数据复制模型,在基于物联网的多云环境中优化数据访问,可用性和成本.
  • 在复杂的分布式系统中提高数据管理的可扩展性和可耗性.

主要方法:

  • 开发了一个数据复制模型,将成本函数最小化,考虑存储,主机访问和通信成本.
  • 采用基于历史数据的成本组件相对权重的学习机制,适应不同的云环境.
  • 数学验证了拟议的模型的稳定性和有效性.

主要成果:

  • 该模型确保数据复制提高了可用性,同时降低了总体数据存储和访问成本.
  • 它有效地平衡服务器负载,并改善数据访问时间.
  • 拟议的方法避免了与传统的完整数据复制技术相关的开销.

结论:

  • 开发的模型为在多云和边缘计算中高效的数据管理提供了数学上健全和有效的解决方案.
  • 它在物联网和智能城市环境中处理大型数据集的传统方法上提供了显著的改进.
  • 这项研究有助于更具可扩展性,成本效益和高性能的分布式数据管理系统.