Jove
Visualize
联系我们
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

相关概念视频

Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

1.6K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.6K
Load along a Single Axis01:29

Load along a Single Axis

304
In structural engineering, the analysis of beams subjected to varying loads is a critical aspect of understanding the behavior and performance of these structural elements. A common scenario involves a beam subjected to a combination of different load distributions.
Consider a beam of length L subjected to a varying load, which is a combination of parabolic and trapezoidal load distribution along the x-axis. In this case, it is essential to determine the resultant loads, their locations, and...
304
Improving Translational Accuracy02:07

Improving Translational Accuracy

10.4K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
10.4K
Machines: Problem Solving II01:30

Machines: Problem Solving II

310
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.
310
Beams with Unsymmetric Loadings01:17

Beams with Unsymmetric Loadings

120
Analyzing a supported beam under unsymmetrical loadings is essential in structural engineering to understand how beams respond to varied force distributions. This analysis involves calculating the deflection and identifying points where the slope of the beam is zero, which are crucial for ensuring structural stability and functionality.
The first moment-area theorem determines the slope at any point on the beam. This theorem indicates that the change in slope between two points on a beam...
120
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

8.3K
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
8.3K

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

Association of phthalate exposure during early pregnancy with fetal growth and the effect modification by gestational stress.

International journal of hygiene and environmental health·2026
Same author

Association Between Urinary Phthalate Metabolites and Early Spontaneous Abortion.

Toxics·2026
Same author

Chronic (180-day) and sub-chronic (90-Day) oral toxicity studies of a novel polyethyleneglycol (PEG)-carbohydrate-lipid conjugate in Wistar rats and beagle dogs.

Toxicology reports·2026
Same author

Robust orthogonal NMF with label propagation for image clustering.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Changes of physician-patient communication skills among general practitioners after intervention of targeted SEGUE training.

BMC medical education·2025
Same author

An Integrated Experimental System for Unmanned Underwater Vehicle Swarm Control.

Sensors (Basel, Switzerland)·2025

相关实验视频

Updated: Jul 3, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.1K

数学改进的XGBoost算法用于在集装箱卸载中检测卡车升降.

Nian Wu1, Wenshan Hu1, Guo-Ping Liu2

  • 1School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China.

Sensors (Basel, Switzerland)
|February 10, 2024
PubMed
概括

这项研究引入了一种新的,非侵入性的方法,用于检测港口的卡车升降,使用数学模型和极端梯度增强 (XGBoost). 这种方法显著提高了准确性,并降低了港口安全操作的成本.

关键词:
一个XGBoost模型.检测异常检测异常的检测非侵入性测量是一种非侵入性测量.卡车提升检测检测 卡车提升检测

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

539
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

6.8K

相关实验视频

Last Updated: Jul 3, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
08:27

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

1.1K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

539
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

6.8K

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
  • 安全系统安全系统

背景情况:

  • 传统的卡车提升检测方法在港口面临高成本,天气敏感性和低准确度的挑战.
  • 需要改进,非侵入性的解决方案,以确保有效的港口安全和集装箱处理.

研究的目的:

  • 提出和评估一种新的,非侵入性的方法来检测卡车升降.
  • 提高在港口环境中检测异常集装箱提升器的准确性和降低成本.

主要方法:

  • 使用霍尔传感器收集来自卡车提升操作的电信号 (电压和电流).
  • 开发了一个数学模型来处理和增强来自电信号的物理信息.
  • 采用极端梯度提升 (XGBoost) 模型,在处理数据上进行训练,用于异常的升降机识别.

主要成果:

  • 拟议的方法在多个站点的实验试验中表现出色.
  • 实现了不超过0.7%的错误阳性率和零个错误阴性.
  • XGBoost模型在识别异常提升器方面表现得更好.

结论:

  • 非侵入式检测方法有效降低了成本,并提高了检测集装箱提升的准确性.
  • 这种方法为提高港口安全和运营效率提供了可行的解决方案.