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A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.
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Muscle coordination is a complex and finely tuned process essential for smooth and purposeful movements like flexion, extension, adduction, abduction, and rotation. The human body orchestrates the actions of various muscles working in concert, each with a specific role. Four functional types describe how muscles work together: agonist, antagonist, synergist, and fixator.
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The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
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持续无线行动识别与扩张压缩协调 (CAREC)

Tingting Zhang1,2, Qunhang Fu1, Han Ding3

  • 1School of Software Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

Sensors (Basel, Switzerland)
|August 14, 2025
PubMed
概括

本研究介绍了CAREC,这是基于Wi-Fi的动作识别框架,可以防止在学习新动作时忘记旧动作. 在保持高精度的同时,CAREC有效地压缩模型.

关键词:
持续的学习,持续的学习.人类行动承认承认增量学习是一种增量学习.无线传感无线传感

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科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 现实世界的应用需要适应性系统,这些系统可以学习新的功能,而无需完全重新培训.
  • 阶级增量学习 (CIL) 对不断发展的系统至关重要,但基于Wi-Fi的动作识别面临着灾难性遗忘和模型扩展等挑战.
  • 现有的方法在增量学习场景中扎于性能退化和不受控制的参数增长.

研究的目的:

  • 提出CAREC,一个基于Wi-Fi的室内动作识别的新型类增量框架.
  • 为了解决灾难性遗忘和不受控制的模型扩展在CIL的行动识别.
  • 为适应性和可扩展系统平衡动态模型扩展与高效压缩.

主要方法:

  • 实施了多分支架构,以整合新的行动类,而不会降低现有类的性能.
  • 使用平衡知识蒸来实现显著的模型压缩 (80%),同时保持准确性.
  • 采用数据重播策略来保留旧的类信息和超级特征提取器来改善歧视.

主要成果:

  • 在XRF55数据集上的四个增量学习阶段中,CAREC显示了51.82%的绩效下降.
  • 仅用2108万个参数实现了67.84%的准确性,与传统方法相比,这意味着大幅减少.
  • 该框架有效地压缩了模型,同时在增量学习中保持了强大的性能.

结论:

  • 在基于Wi-Fi的动作识别中,CAREC为课堂增量学习提供了一个有效的解决方案.
  • 拟议的框架成功地减轻了灾难性遗忘,并在增量更新期间管理模型大小.
  • 通过CAREC,可以开发出更具适应性,可扩展性和高效的室内动作识别系统.