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

15.1K
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...
15.1K
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

233
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
233
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

115
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...
115
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

804
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
804
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

323
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
323
Cluster Sampling Method01:20

Cluster Sampling Method

13.0K
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...
13.0K

You might also read

Related Articles

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

Sort by
Same author

Network security situation prediction method based on KG and Parsimonious memory unit.

Scientific reports·2026
Same author

Dual regulation of metabolism and immune contact by a self-reinforcing hydrogel enhances CAR-T-mediated residual tumor clearance and surveillance.

Journal of controlled release : official journal of the Controlled Release Society·2026
Same author

Video-Assisted Thoracoscopic Repair of an Iatrogenic Innominate Arterial Injury.

Interdisciplinary cardiovascular and thoracic surgery·2026
Same author

Event-triggered multi-agent coordination in directed graphs: An intermittent control approach.

ISA transactions·2025
Same author

Single-cell transcriptomic analysis of the heterogeneity of mesenchymal and stromal cells and their regulon alteration during airway remodeling in asthma.

Scientific reports·2025
Same author

A machine learning-driven robotic system for autonomous nucleic acid extraction and library preparation.

SLAS technology·2025
Same journal

Robust Semiglobal and Global Stabilization for Nonlinear Normal Form Systems by Time-Varying Feedback.

IEEE transactions on cybernetics·2026
Same journal

Adaptive Global Asymptotic Output Stabilization of Uncertain Nonlinear Systems Under Dynamic State/Input Quantization.

IEEE transactions on cybernetics·2026
Same journal

Accelerated Distributed Gradient Tracking for Constrained Aggregative Optimization Over Time-Varying Digraphs.

IEEE transactions on cybernetics·2026
Same journal

Small-Gain-Based Plug-and-Play Distributed Control Framework for DC Microgrids With Decentralized Reconfiguration.

IEEE transactions on cybernetics·2026
Same journal

Prescribed-Time Impulsive Control of High-Order Integrator Systems.

IEEE transactions on cybernetics·2026
Same journal

Relaxed Stability Conditions for Model Predictive Control of Hybrid Dynamical Systems Using Hybrid Recurrent Neural Networks.

IEEE transactions on cybernetics·2026
See all related articles

Related Experiment Video

Updated: Oct 5, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.6K

Distributed Optimization for Graph Matching.

Quoc Van Tran, Zhiyong Sun, Brian D O Anderson

    IEEE Transactions on Cybernetics
    |January 26, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a distributed optimization method for graph matching (GM) between isomorphic graphs in multiagent networks. The novel approach ensures agents converge to the correct vertex correspondences, enhancing distributed computation for complex graph problems.

    More Related Videos

    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria
    08:33

    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

    Published on: July 28, 2023

    708
    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
    07:35

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

    Published on: October 11, 2018

    7.7K

    Related Experiment Videos

    Last Updated: Oct 5, 2025

    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
    05:12

    ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

    Published on: January 16, 2019

    11.6K
    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria
    08:33

    Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

    Published on: July 28, 2023

    708
    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
    07:35

    Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

    Published on: October 11, 2018

    7.7K

    Area of Science:

    • Computer Science
    • Network Science
    • Optimization Theory

    Background:

    • Graph matching (GM) is vital for comparing graph structures across scientific and engineering fields.
    • Existing methods often require centralized processing, limiting scalability in distributed environments.

    Purpose of the Study:

    • To develop a distributed optimization framework for graph matching between isomorphic graphs.
    • To address GM in multiagent networks where agents have localized information.

    Main Methods:

    • Formulated GM as a distributed convex optimization problem over a multiagent network.
    • Utilized a convex relaxation by replacing permutation matrices with pseudostochastic matrices for asymmetric graphs.
    • Developed a projected primal-dual gradient method for solving the constrained optimization problem.

    Main Results:

    • Achieved globally exponential convergence of agents' states to the optimal permutation.
    • Demonstrated the algorithm's effectiveness through simulation examples.
    • Enabled distributed graph matching with only local vertex and neighborhood information.

    Conclusions:

    • The proposed distributed optimization approach effectively solves graph matching for isomorphic graphs in multiagent systems.
    • The projected primal-dual gradient method ensures robust convergence even with decentralized information.
    • This work advances distributed algorithms for critical graph comparison tasks.