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
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

6.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.1K
Outliers and Influential Points01:08

Outliers and Influential Points

4.1K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
4.1K
Methods of Obtaining Topography01:25

Methods of Obtaining Topography

67
Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
67
What Are Outliers?01:12

What Are Outliers?

3.9K
Outliers are observed data points that are far from the least squares line. They have unusual values and need to be examined carefully. Though an outlier may result from erroneous data, at other times, it may hold valuable information about the population under study and should be included in the data. Hence, it is crucial to examine what causes a data point to be an outlier.
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
3.9K
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

47
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
47

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

Insights into the fluid dynamics of bioaerosol formation in a model respiratory tract.

Biomicrofluidics·2024
Same author

A novel recurrence-based approach for investigating multiphase flow dynamics in bubble column reactors.

Chaos (Woodbury, N.Y.)·2024
Same author

Study of interaction and complete merging of binary cyclones using complex networks.

Chaos (Woodbury, N.Y.)·2023
Same author

Dynamics of a single-phase natural circulation system under harmonic excitation.

Chaos (Woodbury, N.Y.)·2023
Same author

Early detection of lean blowout using recurrence network for varying degrees of premixedness.

Chaos (Woodbury, N.Y.)·2022
Same author

Risk assessment of COVID infection by respiratory droplets from cough for various ventilation scenarios inside an elevator: An OpenFOAM-based computational fluid dynamics analysis.

Physics of fluids (Woodbury, N.Y. : 1994)·2022
Same journal

Multiscale dynamics of special memristive ion channels in a neural circuit.

Chaos (Woodbury, N.Y.)·2026
Same journal

Symmetry-protected delay spectroscopy in oscillator networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Mesoscale community organization governs epidemic onset and spread in metapopulations.

Chaos (Woodbury, N.Y.)·2026
Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
查看所有相关文章

相关实验视频

Updated: Jul 6, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.9K

通过拓数据分析来检测精益爆发.

Arijit Bhattacharya1,2, Sabyasachi Mondal2, Somnath De3

  • 1Department of Mechanical Engineering, Institute of Engineering and Management, Kolkata 700091, India.

Chaos (Woodbury, N.Y.)
|January 3, 2024
PubMed
概括
此摘要是机器生成的。

在超薄条件下,现代燃烧器可能会出现瘦身爆发 (LBO). 拓数据分析 (TDA) 提供了一种新的,计算上便宜的方法,用于在多燃烧器系统中实时预测LBO,即使使用低成本传感器.

更多相关视频

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images
12:45

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images

Published on: August 31, 2022

2.9K
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.6K

相关实验视频

Last Updated: Jul 6, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

42.9K
Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images
12:45

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images

Published on: August 31, 2022

2.9K
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.6K

科学领域:

  • 燃烧工程是指燃烧的工程.
  • 数据分析数据分析
  • 动态系统是动态系统.

背景情况:

  • 现代精益预混合燃烧器在超精益条件下运行,以满足排放标准.
  • 这种操作增加了对临界故障模式 - - 倾斜爆发 (LBO) 的易感性.
  • 现有的LBO预测技术主要是为单燃烧器系统开发的,对于多燃烧器配置来说效率较低.

研究的目的:

  • 为了应对在多燃烧器燃烧器中早期瘦爆 (LBO) 检测的挑战.
  • 引入和评估拓数据分析 (TDA) 作为实时LBO预测的新工具.
  • 为了证明TDA在各种燃烧器配置中的有效性.

主要方法:

  • 拓数据分析 (TDA) 对燃烧动态数据的应用.
  • 在过渡到倾斜爆发期间分析TDA指标.
  • 调查低采样率信号的下级设置TDA指标.

主要成果:

  • 已建立的LBO检测技术对于多燃烧器燃烧器来说效率较低.
  • 在计算上,TDA指标是廉价的,并且表现出接近LBO的单调趋势.
  • 亚级设置的TDA指标显示强大的单调变化,即使采样率低.

结论:

  • 拓数据分析 (TDA) 提供了一种计算效率高,可靠的方法,用于在多燃烧器燃烧器中实时预测LBO.
  • 通过TDA,可以微调LBO安全边际,从而提高运营安全.
  • TDA促进了简单,低成本传感器的使用,以有效监测燃烧.