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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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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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Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
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基于扩展的UNET-GWO-SVM算法的智能停车锁

Jianguo Shen1, Yu Xia1, Hao Ding1

  • 1College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua 321000, China.

Sensors (Basel, Switzerland)
|October 28, 2023
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概括
此摘要是机器生成的。

这项研究介绍了使用Raspberry Pi的智能停车锁系统以及用于准确识别车牌的UNET-GWO-SVM算法. 实地测试显示99.0%的解锁率,解决城市停车挑战.

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拉斯伯派 (Raspberry Pi) 是一款非常有价值的小米电脑.在U-net中,U-net是指U-net网络.自动识别车牌的自动识别灰狼优化优化 灰狼优化停车位锁 停车位锁 停车位锁支持矢量机器的支持矢量机器.

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科学领域:

  • 工程 工程师 工程师 工程师
  • 计算机科学 计算机科学
  • 城市规划 城市规划

背景情况:

  • 中国的快速城市化和私人汽车拥有量的增加加剧了停车场短缺和冲突.
  • 现有的停车锁缺乏智能,无法满足各种用户需求.
  • 智能停车解决方案对于高效的城市交通至关重要.

研究的目的:

  • 开发一个智能停车锁系统,以缓解停车冲突.
  • 在嵌入式系统中提高车牌识别准确度,用于自动化停车场访问.
  • 为停车锁控制提供一个用户友好的移动界面.

主要方法:

  • 使用Raspberry Pi作为智能停车锁的核心控制器.
  • 集成了用于车辆检测的超声波传感器和用于拍摄车牌图像的摄像机.
  • 开发了一种新的UNET-GWO-SVM算法,用于嵌入式系统上高精度的车牌识别.
  • 创建了一个微信小程序,用于无的用户交互和锁定控制.

主要成果:

  • 在两个车牌字符下实现了99.0%的有效解锁率,识别错误.
  • 保持了大约2秒的平均时间消耗,满足实时要求.
  • 通过在大学校园的实地测试来证明系统的可行性和性能.

结论:

  • 开发的智能停车锁系统有效解决了城市停车位冲突.
  • 在资源有限的环境中,UNET-GWO-SVM算法显著提高了车牌识别准确性.
  • 集成系统为智能停车管理提供了实用和高效的解决方案.