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

14.0K
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...
14.0K
Skewness01:06

Skewness

17.6K
The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency...
17.6K
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.6K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.6K
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
4.6K
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

5.3K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
5.3K
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

6.5K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
6.5K

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

ISilDR: Isometric Seriation-Based Dimensionality Reduction for Visual Cluster Analysis.

IEEE transactions on visualization and computer graphics·2026
Same author

Phase I trial of CJRB-101 plus pembrolizumab in patients with metastatic non-small cell lung cancer, head and neck squamous cell carcinoma and melanoma.

Journal for immunotherapy of cancer·2026
Same author

Polyethylene and polystyrene oxidation by host and microbial oxidoreductases in Zophobas atratus.

Journal of advanced research·2026
Same author

Trends in Cardiac Rehabilitation Participation in Patients With Acute Myocardial Infarction: A 5-Year Nationwide Study in Korea.

Journal of Korean medical science·2026
Same author

A Muribaculaceae-enriched microbiota exacerbates TLR4-dependent Acinetobacter baumannii-induced hyperinflammatory sepsis.

Nature communications·2026
Same author

Purification and Characterization of His-Tagged Recombinant <i>Bacteroides fragilis</i> Toxin-2 Variants In Vitro and In Vivo.

Toxins·2026
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
查看所有相关文章

相关实验视频

Updated: Jan 16, 2026

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

7.3K

在多维投影中进行可靠的集群分析的扭曲感知刷毛.

Hyeon Jeon, Michael Aupetit, Soohyun Lee

    IEEE transactions on visualization and computer graphics
    |September 29, 2025
    PubMed
    概括
    此摘要是机器生成的。

    扭曲感知刷毛通过纠正投影扭曲来增强多维投影 (MDP) 分析. 这种新的技术提高了刷多维 (MD) 数据集群的精度,从而获得更可靠的见解.

    更多相关视频

    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

    43.6K
    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
    08:12

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

    Published on: March 1, 2022

    2.9K

    相关实验视频

    Last Updated: Jan 16, 2026

    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

    7.3K
    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

    43.6K
    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
    08:12

    A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

    Published on: March 1, 2022

    2.9K

    科学领域:

    • 计算机科学 计算机科学
    • 数据可视化 数据可视化
    • 人与计算机的交互

    背景情况:

    • 刷子是选择二维散射图中的数据集群的关键交互.
    • 在多维投影 (MDP) 上的传统刷毛是不可靠的,因为投影扭曲.
    • 在MDPs中的扭曲可以误解原始的多维 (MD) 数据集群结构.

    研究的目的:

    • 介绍扭曲感知刷,这是MDPs的一种新技术.
    • 提高刷MD数据集群的准确性和可靠性.
    • 实现更有效的集群分析和MDP标签.

    主要方法:

    • 开发了用于MDPs的扭曲感知刷毛.
    • 在刷牙过程中动态移动点以纠正扭曲.
    • 将附近的MD点拉近并将远处的点推开在投影中.

    主要成果:

    • 与24名参与者进行的用户研究显示了显著的改善.
    • 扭曲感知刷毛精确地将投影空间中的MD集群分开.
    • 该技术对MDP诱导的扭曲具有稳定性.

    结论:

    • 扭曲感知刷刷增强了MDP上的集群分析.
    • 该技术可促进与多维数据的更可靠的交互.
    • 对于地理空间数据分析和交互式MD集群标签有效.