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

Cluster Sampling Method01:20

Cluster Sampling Method

11.8K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.8K
Multiple Bar Graph01:07

Multiple Bar Graph

5.1K
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...
5.1K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

98
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
98
pV-Diagrams01:18

pV-Diagrams

4.1K
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...
4.1K
Ogive Graph01:07

Ogive Graph

5.6K
An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
5.6K
End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

308
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
308

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

Stable isotope dimethyl labeling combined with LTQ mass spectrometric detection, a quantitative proteomics technology used in liver cancer research.

Biomedical reports·2014
Same author

[Clinical application of micro transverse flap pedicled with superficial palmar branch of radial artery from palmar wrist to repair skin defect of finger].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery·2014
Same author

Biotransformations of racemic 2,3-allenenitriles in biphasic systems: synthesis and transformations of enantioenriched axially chiral 2,3-allenoic acids and their derivatives.

The Journal of organic chemistry·2014
Same author

The relationship between job performance and perceived organizational support in faculty members at Chinese universities: a questionnaire survey.

BMC medical education·2014
Same author

Preparation of hydrazine functionalized polymer brushes hybrid magnetic nanoparticles for highly specific enrichment of glycopeptides.

The Analyst·2014
Same author

Enantioseparation of new triadimenol antifungal active compounds by electrokinetic chromatography and molecular modeling study of chiral recognition mechanisms.

Electrophoresis·2014
Same journal

Granular Ball-Based Noise-Resistant Fuzzy Multineighborhood Feature Selection via Label Enhancement and Feature Graph.

IEEE transactions on neural networks and learning systems·2026
Same journal

Fighting Evolving Spam With ARTMAP Models: A Noise-Resilient Online Detection Framework.

IEEE transactions on neural networks and learning systems·2026
Same journal

HyperSAT: Unsupervised Hypergraph Neural Networks for Weighted MaxSAT Problems.

IEEE transactions on neural networks and learning systems·2026
Same journal

Negation of Basic Belief Assignment in Multisource Information Fusion on Dempster-Shafer Theory With Applications in Pattern Classification.

IEEE transactions on neural networks and learning systems·2026
Same journal

Intervention Feasible Region and Driver Risk Capacity Aware Human-Machine Collaborative Safe Trajectory Planning.

IEEE transactions on neural networks and learning systems·2026
Same journal

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug-Drug Interaction Prediction.

IEEE transactions on neural networks and learning systems·2026
查看所有相关文章

相关实验视频

Updated: Jun 19, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.4K

动态图指导渐进的部分视图对齐集群.

Liang Zhao, Qiongjie Xie, Zhengtao Li

    IEEE transactions on neural networks and learning systems
    |July 23, 2024
    PubMed
    概括
    此摘要是机器生成的。

    这项研究介绍了动态图形引导的渐进部分视图对齐聚类 (DGPPVC),这是一个用于不完整数据的多视图聚类的新方法. DGPPVC通过使用图形卷积网络逐步学习对应函数,有效地处理部分对齐的数据.

    更多相关视频

    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
    07:08

    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

    Published on: July 14, 2015

    7.3K
    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
    12:27

    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

    Published on: February 15, 2017

    7.0K

    相关实验视频

    Last Updated: Jun 19, 2025

    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
    05:12

    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

    Published on: January 16, 2019

    11.4K
    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
    07:08

    Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

    Published on: July 14, 2015

    7.3K
    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
    12:27

    Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

    Published on: February 15, 2017

    7.0K

    科学领域:

    • 机器学习 机器学习
    • 数据科学数据科学数据科学
    • 计算机视觉 计算机视觉

    背景情况:

    • 多视图数据提供了丰富的信息,以提高任务性能.
    • 现有的多视图集群 (MVC) 方法通常需要完整的数据对应,从而限制了它们的实际应用.
    • 部分视图对齐集群 (PVC) 解决了不完整数据对齐的挑战.

    研究的目的:

    • 提出一种新的方法,DGPPVC,用于部分视图对齐的集群.
    • 为了利用图形卷积网络 (GCNs) 在多视图数据中处理不可靠的对齐.
    • 逐步开发一个端到端的框架来学习特征表示和对齐关系.

    主要方法:

    • 使用带有动态相邻矩阵的图形卷积网络 (GCNs) 来进行强大的对齐学习.
    • 实施一个端到端的框架,集成图形构造,特征表示学习和对齐学习.
    • 使用渐进的对齐策略,从简单的对应开始,并使用Jaccard相似变体向复杂的对应推进.

    主要成果:

    • 通过使用动态图形结构,DGPPVC有效地减少了不可靠的对齐.
    • 逐步调整策略允许逐步获取未知对应的信息.
    • 实验表明,与现实PVC数据集上的最先进方法相比,DGPPVC的性能优越.

    结论:

    • DGPPVC提供了一种新且有效的方法,用于部分视图对齐的集群.
    • 集成GCN和渐进的调整学习解决了多视图数据分析的关键挑战.
    • 这种方法显示了在不完整的多视图数据下改善聚类性能的巨大潜力.