Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

121
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
121
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

14.9K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
14.9K
Vector Components in the Cartesian Coordinate System01:29

Vector Components in the Cartesian Coordinate System

21.6K
Vectors are usually described in terms of their components in a coordinate system. Even in everyday life, we naturally invoke the concept of orthogonal projections in a rectangular coordinate system. For example, if someone gives you directions for a particular location, you will be told to go a few km in a direction like east, west, north, or south, along with the angle in which you are supposed to move. In a rectangular (Cartesian) xy-coordinate system in a plane, a point in a plane is...
21.6K
Vector Representation of Complex Numbers01:16

Vector Representation of Complex Numbers

199
Complex numbers, represented in Cartesian coordinates, can also be visualized as vectors. These vectors can be expressed in polar form, emphasizing their magnitude and angle. When a complex number is input into a function, the output is another complex number, highlighting the function's zero point from which the vector representation can originate.
Consider a function defined as the product of the complex factors in the numerator divided by the product of the complex factors in the...
199
Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

844
The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse....
844
Dot Product: Problem Solving01:21

Dot Product: Problem Solving

427
The dot product is a powerful tool in problem-solving involving vectors, given that the dot product of two vectors is the product of their magnitudes and the cosine of the angle between them measured anti-clockwise. Solving problems involving the dot product requires understanding its properties and developing a step-by-step process to solve them. Here are the main steps to follow when solving any general problem involving the dot product:
Identify the problem: Start by reading the problem and...
427

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Simultaneous Formation of Interphases on both Positive and Negative Electrodes in High-Voltage Aqueous Lithium-Ion Batteries.

Small (Weinheim an der Bergstrasse, Germany)·2021
Same author

The effect of co-pyrolysis temperature for iron-biochar composites on their adsorption behavior of antimonite and antimonate in aqueous solution.

Bioresource technology·2021
Same author

MoS<sub>2</sub> nanosheets loaded on collapsed structure zeolite as a hydrophilic and efficient photocatalyst for tetracycline degradation and synergistic mechanism.

Chemosphere·2021
Same author

Potential Implications of Citrulline and Quercetin on Gut Functioning of Monogastric Animals and Humans: A Comprehensive Review.

Nutrients·2021
Same author

Circular RNA Expression Profiles and Bioinformatic Analysis in Mouse Models of Obstructive Sleep Apnea-Induced Cardiac Injury: Novel Insights Into Pathogenesis.

Frontiers in cell and developmental biology·2021
Same author

[Airway obstruction after anterior long-segment fusion surgery for tracheotomy:a case report].

Zhongguo gu shang = China journal of orthopaedics and traumatology·2021
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
See all related articles

Related Experiment Video

Updated: Sep 5, 2025

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
11:38

Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

Published on: August 23, 2017

9.9K

voxel2vec: A Natural Language Processing Approach to Learning Distributed Representations for Scientific Data.

Xiangyang He, Yubo Tao, Shuoliu Yang

    IEEE Transactions on Visualization and Computer Graphics
    |July 7, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces voxel2vec, a new unsupervised model for learning data representations. It uncovers complex relationships in scientific data, improving feature classification and association analysis.

    More Related Videos

    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

    24.7K
    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    676

    Related Experiment Videos

    Last Updated: Sep 5, 2025

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
    11:38

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

    Published on: August 23, 2017

    9.9K
    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

    24.7K
    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
    03:14

    Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

    Published on: December 6, 2024

    676

    Area of Science:

    • Data Science
    • Scientific Visualization
    • Machine Learning

    Background:

    • Scientific data analysis involves understanding intricate relationships within univariate, multivariate, and time-varying datasets.
    • Existing methods struggle to capture complex spatial and scalar value associations effectively.

    Purpose of the Study:

    • To introduce voxel2vec, a novel unsupervised representation learning model.
    • To learn low-dimensional vector representations of scalar values and their combinations.
    • To explore complex data associations through learned representations.

    Main Methods:

    • Developed voxel2vec, an unsupervised representation learning model based on contextual similarity.
    • Represented scalar values/combinations as symbols to learn spatial distribution similarities.
    • Utilized transfer prediction for exploring volume associations.

    Main Results:

    • Demonstrated voxel2vec's effectiveness by comparing it with isosurface similarity maps for univariate data.
    • Applied learned representations to enhance feature classification in multivariate data.
    • Successfully used voxel2vec for association analysis in time-varying and ensemble data.

    Conclusions:

    • voxel2vec effectively learns distributed representations of scalar values from scientific data.
    • The model facilitates the exploration of complex data relationships and improves downstream analytical tasks.
    • voxel2vec offers a powerful new tool for scientific data analysis and visualization.