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相关概念视频

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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Velocity and position can be calculated from the known function of acceleration as a function of time. The total area under the acceleration-time graph and the velocity-time graph gives the change in velocity and position, respectively. In the case of an airplane, its acceleration is tracked using the inertial navigation system. The pilot provides the input of the airplane's initial position and velocity before takeoff. The inertial navigation system then uses the acceleration data to...
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Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
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相关实验视频

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Swimming Performance Assessment in Fishes
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在划船运动中使用图形匹配网络进行智能性能评估.

Chien-Chang Chen1, Cheng-Shian Lin1, Yen-Ting Chen1

  • 1Department of Computer Science and Information Engineering, Tamkang University, New Taipei City 25137, Taiwan.

Journal of imaging
|September 27, 2023
PubMed
概括

本研究介绍了一个基于视频的系统,使用图形匹配网络来分析划船姿势相似性. 它通过分析联合点数据,准确地将划船者配对,以提高团队表现.

关键词:
打开Pose,可以使用Pose.图表神经网络的神经网络

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科学领域:

  • 运动科学 运动科学 运动科学
  • 计算机视觉 计算机视觉
  • 生物力学 生物力学

背景情况:

  • 在划船比赛中,一致的划船冲击对于最佳的团队表现至关重要.
  • 目前的运动分析方法通常依赖于可穿戴传感器,对运动员造成不便.

研究的目的:

  • 开发一种新的基于视频的系统,用于分析双对划船者之间的划船姿势相似性.
  • 通过基于同步运动有效配对划船员来提高团队表现.

主要方法:

  • 利用OpenPose系统从视频录像中检测人类关节点.
  • 应用图形嵌入模型 (GEM) 和图形匹配网络来分析姿势相似性.
  • 集成的时间段相似性处理,以提高配对的准确性.

主要成果:

  • 拟议的系统成功地分析了两对运动员在划船姿势中的相似性.
  • 通过检测划船姿势中的一致起始点来实现准确的配对.
  • 2D图形嵌入模型 (GEM) 与时间周期相似性处理产生了最好的配对结果.

结论:

  • 一个新的基于视频的系统有效地分析了使用图形匹配网络的划船姿势同步.
  • 这种方法为性能分析提供了可穿戴传感器的非侵入性替代方案.
  • 该系统展示了优化划船者配对和提高团队表现的潜力.