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

Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower indicates...
Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...

You might also read

Related Articles

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

Sort by
Same author

Ambient Analytics: Calm Technology for Immersive Visualization and Sensemaking.

IEEE computer graphics and applications·2026
Same author

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

IEEE transactions on visualization and computer graphics·2026
Same author

A Large-Scale Quantitative Analysis of Avatars in VR and AR.

IEEE transactions on visualization and computer graphics·2026
Same author

Situated Brushing and Linking in Virtual and Augmented Reality.

IEEE transactions on visualization and computer graphics·2026
Same author

PerSiVal: deep neural networks for pervasive simulation of an activation-driven continuum-mechanical upper limb model.

Medical & biological engineering & computing·2026
Same author

Make the Unhearable Visible: Exploring Visualization for Musical Instrument Practice.

IEEE transactions on visualization and computer graphics·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 9, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

ParaGlide: interactive parameter space partitioning for computer simulations.

Steven Bergner1, Michael Sedlmair, Torsten Möller

  • 1Department of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada. sbergner@cs.sfu.ca

IEEE Transactions on Visualization and Computer Graphics
|July 13, 2013
PubMed
Summary
This summary is machine-generated.

ParaGlide is a new visualization system that helps model developers explore complex parameter spaces more efficiently. It systematically partitions parameter spaces to reveal distinct output behaviors, aiding in model development and comparison.

Related Experiment Videos

Last Updated: May 9, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Area of Science:

  • Computer Science
  • Scientific Visualization
  • Computational Modeling

Background:

  • Model developers often struggle with the iterative process of setting parameters and evaluating simulation outcomes.
  • Existing tools lack systematic approaches for exploring multidimensional parameter spaces, making informed decisions difficult and time-consuming.

Purpose of the Study:

  • Introduce ParaGlide, a visualization system for interactive exploration of parameter spaces in multidimensional simulation models.
  • Address the limitations of current tools by providing a systematic method for parameter space exploration and analysis.

Main Methods:

  • Developed ParaGlide with a region-based user interface for guided parameter sampling.
  • Implemented parameter space partitioning to group parameters by distinct output behaviors.
  • Collaborated with domain experts and conducted user-centered design and case studies.

Main Results:

  • Parameter space partitioning enhances understanding of qualitative differences in high-dimensional model outputs.
  • ParaGlide provides insights into parameter sensitivity and facilitates model comparison.
  • User-centered design and case studies demonstrated the system's usefulness in real-world applications.

Conclusions:

  • ParaGlide offers a systematic and efficient approach to exploring complex parameter spaces.
  • The system aids model developers in making informed decisions, understanding parameter sensitivity, and comparing models.
  • ParaGlide's user-centered design ensures practical utility across different scientific domains.