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

Modified Boxplots00:57

Modified Boxplots

10.2K
A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...
10.2K
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

106
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
106
Boxplot01:12

Boxplot

11.4K
Box plots (also called box-and-whisker plots or box-whisker plots) give an excellent graphical image of the concentration of the data. They also show how far the extreme values are from most data. A box plot is constructed from five values: the minimum value, the first quartile, the median, the third quartile, and the maximum value. We use these values to compare how close other data values are to them. To construct a box plot, use a horizontal or vertical number line and a rectangular box. The...
11.4K
pV-Diagrams01:18

pV-Diagrams

4.5K
The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
4.5K
Survival Curves01:18

Survival Curves

336
Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
336
Multiple Bar Graph01:07

Multiple Bar Graph

7.9K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
7.9K

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

ICIRD: Information-Principled Deep Clustering for Invariant, Redundancy-Reduced and Discriminative Cluster Distributions.

Entropy (Basel, Switzerland)·2025
Same author

eXplainable Artificial Intelligence (XAI): A Systematic Review for Unveiling the Black Box Models and Their Relevance to Biomedical Imaging and Sensing.

Sensors (Basel, Switzerland)·2025
Same author

Comparative study of ten machine learning algorithms for short-term forecasting in gas warning systems.

Scientific reports·2024
Same author

BioChainReward: A Secure and Incentivised Blockchain Framework for Biomedical Data Sharing.

International journal of environmental research and public health·2023
Same author

Evaluating narrative visualization: a survey of practitioners.

International journal of data science and analytics·2023
Same author

An FSV analysis approach to verify the robustness of the triple-correlation analysis theoretical framework.

Scientific reports·2023
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
查看所有相关文章

相关实验视频

Updated: Sep 17, 2025

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.2K

泡墙图像作为动态分析处理可视化工具,用于开发视觉警告系统:一个案例研究

Robert M X Wu1, Huan Zhang2, Jie Liang3

  • 1School of Professional Practice and Leadership, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia.

PloS one
|July 1, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一个新的泡墙图形可视化工具,用于危险数据的动态分析处理 (DAP). 它解决了现有工具的局限性,为视觉预警系统提供了更简单,更直观的方法.

更多相关视频

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.3K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

相关实验视频

Last Updated: Sep 17, 2025

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.2K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.3K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.2K

科学领域:

  • 数据可视化 数据可视化
  • 信息科学 信息科学 信息科学
  • 危险分析 危险分析

背景情况:

  • 现有的数据可视化工具往往无法满足各种行业需求.
  • 自2017年以来对第一季度出版物的审查确定了23种可视化方法,其中7种用于异常数据.
  • 不同的研究人员如何感知和利用像Scatter Plots和Line Charts这样的可视化工具存在差异.

研究的目的:

  • 提出一种新的动态分析处理 (DAP) 可视化工具,即泡墙图.
  • 解决目前用于危险数据分析的数据可视化方法的局限性.
  • 为动态危险数据流程开发有效的视觉预警系统.

主要方法:

  • 对23种已识别的数据可视化方法和工具进行比较分析.
  • 一个案例研究,重点关注煤炭开采行业的危险数据.
  • 基于五个类别和26个子类别的衡量特征进行评估.

主要成果:

  • 没有一个现有的可视化工具能够充分满足行业的所有要求.
  • 拟议的泡墙图表表现出了显著的特点:简单,直截了当的视觉结果和直观性.
  • 泡墙图有效地可视化了危险数据的动态分析过程,如煤矿案例研究所示.

结论:

  • 泡墙图为可视化动态分析过程和开发危险预警系统提供了卓越的解决方案.
  • 提高用户对可视化工具功能的认识,对于有效应用至关重要.
  • 建议进行进一步的研究,以探索这种新的可视化方法的全部潜力.