Jove
Visualize
联系我们

相关概念视频

Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

686
Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
This behavior occurs due to the magnetic flux produced by the short-circuit armature currents. Initially, these currents follow high-reluctance paths but eventually shift to...
686
Phase Transitions02:31

Phase Transitions

23.1K
Whether solid, liquid, or gas, a substance's state depends on the order and arrangement of its particles (atoms, molecules, or ions). Particles in the solid pack closely together, generally in a pattern. The particles vibrate about their fixed positions but do not move or squeeze past their neighbors. In liquids, although the particles are closely spaced, they are randomly arranged. The position of the particles are not fixed—that is, they are free to move past their neighbors to...
23.1K
Machines01:19

Machines

576
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
576
What is Energy?04:10

What is Energy?

58.9K
The universe is composed of matter in different forms, and all forms of matter contain energy.  The different forms of energy on Earth originate from the Sun — the ultimate energy source. Plants capture light energy from the Sun, and, via the process of photosynthesis, convert it into chemical energy. This stored energy from plants can be harnessed in many ways. For example, eating plant products as food provides energy for our body to function, and burning wood or coal (fossilized...
58.9K
Free Energy01:21

Free Energy

52.0K
Free energy—abbreviated as G for the scientist Gibbs who discovered it—is a measurement of useful energy that can be extracted from a reaction to do work. It is the energy in a chemical reaction that is available after entropy is accounted for. Reactions that take in energy are considered endergonic and reactions that release energy are exergonic. Plants carry out endergonic reactions by taking in sunlight and carbon dioxide to produce glucose and oxygen. Animals, in turn, break...
52.0K
Phase Transitions: Sublimation and Deposition02:33

Phase Transitions: Sublimation and Deposition

20.0K
Some solids can transition directly into the gaseous state, bypassing the liquid state, via a process known as sublimation. At room temperature and standard pressure, a piece of dry ice (solid CO2) sublimes, appearing to gradually disappear without ever forming any liquid. Snow and ice sublimate at temperatures below the melting point of water, a slow process that may be accelerated by winds and the reduced atmospheric pressures at high altitudes. When solid iodine is warmed, the solid sublimes...
20.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Enhanced Distributed Energy-Efficient Clustering (DEEC) Protocol for Wireless Sensor Networks: A Modular Implementation and Performance Analysis.

Sensors (Basel, Switzerland)·2025
Same author

Enhancing Clustering Efficiency in Heterogeneous Wireless Sensor Network Protocols Using the K-Nearest Neighbours Algorithm.

Sensors (Basel, Switzerland)·2025
Same author

Improving Performance of Cluster Heads Selection in DEC Protocol Using K-Means Algorithm for WSN.

Sensors (Basel, Switzerland)·2024
查看所有相关文章
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jan 29, 2026

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

13.0K

埃莫-佩加西斯:一种双相机器学习协议,用于优化WSN中的能量延迟.

Abdulla Juwaied1

  • 1Institute of Applied Computer Science, Lodz University of Technology, ul. Stefanowskiego 18, 90-537 Lodz, Poland.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
概括
此摘要是机器生成的。

增强多目标PEGASIS (EMO-PEGASIS) 通过使用机器学习来改进无线传感器网络,以提高能源效率和减少延迟. 该协议显著提高了网络的寿命和稳定性.

关键词:
K-最近的邻居 (K-NN)K-意味着K的意思是K.佩加西斯 (PEGASIS) 是一个传奇.能源效率是指能效的能源效率.机器学习是机器学习.多目标优化多目标优化延迟传输延迟传输时间无线传感器网络 (WSN) 是指无线传感器网络.

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.4K
An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
07:42

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents

Published on: August 2, 2018

14.4K

相关实验视频

Last Updated: Jan 29, 2026

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
08:58

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

Published on: November 19, 2018

13.0K
Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.4K
An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
07:42

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents

Published on: August 2, 2018

14.4K

科学领域:

  • 计算机科学 计算机科学
  • 电气工程 电气工程
  • 网络工程 网络工程

背景情况:

  • 无线传感器网络 (WSN) 在节能和数据传输延迟之间面临着关键的权衡.
  • 像PEGASIS这样的现有协议提供了能源效率,但受到高延迟和负载分布不平衡的影响.
  • 在传统的WSN协议中,低于最佳的集群形成限制了整体网络性能.

研究的目的:

  • 为WSNs引入一个增强的多目标PEGASIS (EMO-PEGASIS) 协议.
  • 解决现有协议在管理能源消耗和数据传输延迟方面的局限性.
  • 利用机器学习优化WSN在能源,延迟和网络寿命方面的性能.

主要方法:

  • 在协议设计和实施中采用了双相机器学习策略.
  • 使用K-means集群来实现网络的强大空间分区.
  • 适应性和智能路由使用K-最近邻居 (K-NN) 分类.

主要成果:

  • 与PEGASIS相比,EMO-PEGASIS实现了平均能源消耗的45%降低.
  • 端到端延迟减少了38%,网络寿命增加了67%.
  • 该协议显示了增强的稳定性,有效的负载平衡,以及96.8%的数据包交付比率.

结论:

  • 在EMO-PEGASIS协议有效地解决了多目标优化问题在WSNs.
  • 整合机器学习技术显著提高了WSN的性能.
  • 对于能源和延迟受限制的WSN环境,EMO-PEGASIS提供可靠的多目标优化.