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相关概念视频

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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...
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Short-distance Transport of Resources02:12

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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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Distributed Loads01:19

Distributed Loads

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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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Drift Velocity01:19

Drift Velocity

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The high speed of electrical signals results from the fact that the force between charges acts rapidly at a distance. Thus, when a free charge is forced into a wire, the incoming charge pushes other charges ahead due to the repulsive force between like charges. These moving charges move the charges farther down the line. The density of charge in a system cannot easily be increased, so the signal is passed on rapidly. The resulting electrical shock wave moves through the system at nearly the...
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Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
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Carrier Transport01:21

Carrier Transport

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The generation of electrical current in semiconductors is fundamentally driven by two mechanisms: drift and diffusion. These processes are essential for the functionality and performance of semiconductor-based devices.
Drift Current:
The drift of charge carriers is started by an external electric field (E). Charged particles, such as electrons and holes, experience an acceleration between collisions with lattice atoms. For electrons, this results in a drift velocity (vd) given by:
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Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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无人机支持的海上物联网D2D任务卸载:一个潜在的游戏加速框架

Baiyi Li1, Jian Zhao1, Tingting Yang1,2

  • 1Navigation College, Dalian Maritime University, Dalian 116026, China.

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概括
此摘要是机器生成的。

使用无人水面船 (USV) 的海洋物联网 (IoT) 从新的分布式框架中受益. 该系统通过优化无人飞行器 (UAV) 边缘计算来降低延迟时间,改善在具有挑战性的海上环境中做出决策.

关键词:
美国VS 美国VS设备对设备的通信.游戏理论的游戏理论.海上物联网系统的海洋物联网系统.任务卸载 任务卸载

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科学领域:

  • 海洋技术的海洋技术
  • 边缘计算是一种边缘计算.
  • 无线网络是无线网络.

背景情况:

  • 使用无人水面船 (USV) 的海洋物联网 (IoT) 部署面临重大挑战,原因是船上计算能力有限,无线连接不可靠.
  • 视觉和传感等计算密集型任务经常超过延迟值,阻碍了对海事运营至关重要的实时决策.

研究的目的:

  • 提出一个针对海上物联网场景量身定制的新型分布式计算卸载框架.
  • 通过整合设备对设备 (D2D) 和无人机 (UAV) 辅助边缘计算来解决基于USV的系统中的延迟问题.

主要方法:

  • 设计了一个基于广度优先搜索 (BFS) 的分布式计算卸载游戏,利用USV资源和无人机移动性.
  • 制定了一个全球延迟最小化问题,共同优化无人机悬浮坐标和到达时间.
  • 解决了优化问题,使用了乘数的交替方向方法 (ADMM) 和连续凸近似方法 (SCA) 的结合方法.

主要成果:

  • 拟议的框架有效地减少了海上物联网系统的延迟.
  • 模拟显示,与传统卸载方法相比,延迟时间显著减少,高达49.6%.
  • 无人机参数的联合优化在最大限度地减少整体系统延迟方面被证明是有效的.

结论:

  • 新的分布式计算卸载框架提高了海上物联网系统的效率.
  • 整合D2D和无人机辅助边缘计算为克服USV计算和连接限制提供了可行的解决方案.
  • 这种方法在复杂的海上环境中显著提高了及时决策能力.