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相关概念视频

Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

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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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Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
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Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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相关实验视频

Updated: Sep 12, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
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YOLO11-YX:一种高效的算法用于海洋垃圾目标检测.

Yuxin Wang1, Shuo Liu2, Yansong He1

  • 1School of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, Hebei, China.

Marine pollution bulletin
|August 8, 2025
PubMed
概括

这项研究介绍了YOLO11-YX,这是用于自动检测海洋碎片的先进算法. 它在复杂的环境中显著提高了准确性,为环境监测提供了强大的解决方案.

关键词:
功能融合的特点是:海洋碎片检测检测海洋碎片检测对象检测检测对象检测对象检测在YOLO11-YXX中,你会看到YOLO11-YX.

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科学领域:

  • 环境科学 环境科学
  • 计算机视觉 计算机视觉
  • 人工智能的人工智能

背景情况:

  • 海洋垃圾污染是一个日益严重的全球性问题.
  • 自动检测系统对于有效的监控和管理至关重要.
  • 现有的物体检测方法在复杂的海洋环境中难以获得准确性和稳定性,特别是对于小碎片.

研究的目的:

  • 开发一种增强的算法,用于更准确,更强大的海洋垃圾自动检测.
  • 解决复杂背景和小物体中传统物体检测方法的局限性.

主要方法:

  • 介绍了YOLO11-YX,这是基于YOLO11s.s.的增强算法.
  • 整合了三个新型模块:SDown (下方采样),C3SE (特征提取) 和FAN (特征融合).
  • SDown模块在维度缩小过程中保留了细节.
  • C3SE模块通过SENet改进了卷积结构,以改善复杂环境中的检测.
  • FAN模块增强了小目标的细节和上下文识别.

主要成果:

  • 与YOLO11s相比,YOLO11-YX在海洋碎片检测准确度上实现了2.44%的改进.
  • 新算法的整体准确率达到了62.32%.
  • 在处理复杂的背景和检测小型海洋碎片物体方面表现出增强的性能.

结论:

  • YOLO11-YX为自动化海洋垃圾检测提供了强大而可靠的解决方案.
  • 增强的算法在准确性和稳定性方面提供了显著的改进.
  • 开发的技术在环境监测和污染控制工作中具有广泛的应用.