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

Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
pV-Diagrams01:18

pV-Diagrams

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...
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
Graphs of Functions01:30

Graphs of Functions

Graphs of functions provide a visual representation of how output values change in response to varying inputs. Each point on the graph corresponds to an ordered pair, where the x-coordinate (independent variable) determines the horizontal position and the y-coordinate (dependent variable) determines the vertical position. Linear functions like y = x give a straight line, indicating a constant rate of change.Nonlinear functions display more complex behaviors. Even power functions generate...
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

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,...
Graphs of Polar Equations01:17

Graphs of Polar Equations

The polar coordinate system represents points using a distance from a central point (the pole) and an angle from a reference direction (the polar axis). Unlike rectangular coordinates, polar coordinates are ideal for graphing curves with radial symmetry or periodic behavior.Some general forms of graphs in polar coordinates include the following:Equation of a Circle (Centered at the Pole):A graph where the radius remains constant for all angles traces a circle centered at the pole:Equation of a...

You might also read

Related Articles

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

Sort by
Same author

CDKN1A promotes paclitaxel resistance through mediating formation of polyploid giant cancer cells and enhancing neosis in non-small cell lung cancer.

Translational lung cancer research·2026
Same author

Mamba2SVN: a Mamba2 and reconstruction-cooperative sensitivity refinement-based variational network for parallel MRI reconstruction.

Physics in medicine and biology·2026
Same author

<i>Planococcus dechangensis</i> NEAU-ST10-9<sup>T</sup> Promotes Maize Seedling Root Development: Evidence from Effective Fluorescence Tracking.

Microorganisms·2026
Same author

Effects of Dietary Squalene Supplementation on the Growth Performance and Disease Resistance of Largemouth Bass.

Veterinary sciences·2026
Same author

Cold plasma modification of natural polysaccharides: mechanisms, regulatory factors, and biological activity enhancement.

Food chemistry·2026
Same author

Synergistic utilization of steel slag and activated coke for microwave-induced simultaneous desulfurization and denitrification.

Environmental research·2026
Same journal

Blue Noise Dithering for Reservoir-based Spatio-temporal Importance Resampling.

IEEE transactions on visualization and computer graphics·2026
Same journal

ROS-GS: Relightable Outdoor Scenes With Gaussian Splatting.

IEEE transactions on visualization and computer graphics·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
See all related articles

Related Experiment Video

Updated: May 23, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

A space-filling visualization technique for multivariate small-world graphs.

Pak Chung Wong1, Harlan Foote, Patrick Mackey

  • 1Pacific Northwest National Laboratory, Richland, WA 99352, USA. pak.wong@pnl.gov

IEEE Transactions on Visualization and Computer Graphics
|March 24, 2012
PubMed
Summary
This summary is machine-generated.

GreenCurve visualizes complex graphs using fractals, eliminating links for a compact overview. This novel technique aids electric power grid operations by ensuring all nodes are visible.

More Related Videos

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Related Experiment Videos

Last Updated: May 23, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Area of Science:

  • Information Visualization
  • Graph Theory
  • Complex Systems

Background:

  • Large multivariate sparse graphs with small-world properties pose visualization challenges.
  • Existing methods struggle to provide a succinct overview while ensuring node visibility.

Purpose of the Study:

  • Introduce GreenCurve, a novel fractal-based information visualization technique.
  • Address the need for efficient visualization of large, sparse graphs in critical infrastructure like power grids.

Main Methods:

  • Developed a fractal-based design approach using spatial cues to represent node connections.
  • Employed an algorithm to order graph nodes using the Fiedler vector of the graph Laplacian.
  • Mapped ordered nodes onto a space-filling fractal curve for compact visualization.

Main Results:

  • Achieved a highly compact graph visualization with guaranteed visibility of every node.
  • Demonstrated the technique's applicability to power grid infrastructure challenges.
  • Evaluated design claims through a case study and usability testing.

Conclusions:

  • GreenCurve offers a unique solution for visualizing large, sparse, small-world graphs.
  • The technique shows promise for enhancing electric power grid operations and analysis.
  • Further integration with other visualization tools is recommended for comprehensive support.