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

Compartment Models: Two-Compartment Model01:20

Compartment Models: Two-Compartment Model

7.5K
The two-compartment model divides the body into central and peripheral compartments to account for varying blood perfusion rates among organs and tissues, affecting drug distribution. The central compartment includes blood and highly perfused tissues with rapid drug distribution, while the peripheral compartment contains tissues with slower drug distribution. After a single IV bolus dose, the drug concentration is high in plasma and low in tissues. The drug distribution between compartments...
7.5K
Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

3.5K
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...
3.5K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

377
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
377
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

314
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
314
Cartesian Vector Notation01:28

Cartesian Vector Notation

1.8K
Cartesian vector notation is a valuable tool in mechanical engineering for representing vectors in three-dimensional space, performing vector operations such as determining the gradient, divergence, and curl, and expressing physical quantities such as the displacement, velocity, acceleration, and force. By using Cartesian vector notation, engineers can more easily analyze and solve problems in various areas of mechanical engineering, including dynamics, kinematics, and fluid mechanics. This...
1.8K
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

307
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
307

You might also read

Related Articles

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

Sort by
Same author

Evaluating Visual Decision Support: How Does Preference Elicitation Shape Metric Sensitivity?

IEEE transactions on visualization and computer graphics·2026
Same author

Chat Modeling: Interaction-Enhanced Agent Framework for Visualizing Literature-Grounded Biological Structures.

IEEE transactions on visualization and computer graphics·2026
Same author

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results.

IEEE transactions on visualization and computer graphics·2026
Same author

Structural evolution of a fungal cell wall protein family for β-glucan-binding and cell separation.

mBio·2026
Same author

CrossSet: Unveiling the Complex Interplay of Two Set-typed Dimensions in Multivariate Data.

IEEE transactions on visualization and computer graphics·2025
Same author

MidSurfer: A Parameter-Free Approach for Mid-Surface Extraction From Segmented Volumetric Data.

IEEE computer graphics and applications·2025
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: Mar 11, 2026

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

3.0K

A Fractional Cartesian Composition Model for Semi-Spatial Comparative Visualization Design.

Ivan Kolesar, Stefan Bruckner, Ivan Viola

    IEEE Transactions on Visualization and Computer Graphics
    |November 23, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a model for comparative visualization to address challenges with spatial data ensembles. It automates visualization design, preserving key data characteristics for multiple ensemble members.

    More Related Videos

    A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
    09:01

    A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

    Published on: May 7, 2014

    10.6K
    Quantification of Orofacial Phenotypes in Xenopus
    09:26

    Quantification of Orofacial Phenotypes in Xenopus

    Published on: November 6, 2014

    10.3K

    Related Experiment Videos

    Last Updated: Mar 11, 2026

    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

    3.0K
    A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
    09:01

    A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

    Published on: May 7, 2014

    10.6K
    Quantification of Orofacial Phenotypes in Xenopus
    09:26

    Quantification of Orofacial Phenotypes in Xenopus

    Published on: November 6, 2014

    10.3K

    Area of Science:

    • Computer Science
    • Data Visualization
    • Scientific Computing

    Background:

    • Visualizing spatial data ensembles presents significant challenges.
    • Existing methods struggle to preserve crucial data characteristics when analyzing many ensemble members.

    Purpose of the Study:

    • To present a novel model for comparative visualization of spatial data ensembles.
    • To support the design of effective ensemble visualization solutions through partial automation.
    • To enable users to preserve essential spatial data characteristics during comparative analysis.

    Main Methods:

    • A model separating visualization design into user-specified parameters and automated optimization.
    • Formal description of the model with illustrated details.
    • Application examples across diverse domains to demonstrate generality.

    Main Results:

    • A framework for partially automated design of comparative visualization for spatial data ensembles.
    • Demonstrated ability to preserve selected spatial data characteristics.
    • Successful application in various domains, confirming model versatility.

    Conclusions:

    • The proposed model offers a systematic approach to tackle complex spatial data ensemble visualization.
    • Partial automation aids in designing effective comparative visualizations while retaining data integrity.
    • The approach is generalizable across different application domains requiring spatial data ensemble analysis.