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

Social Exchange Theory02:06

Social Exchange Theory

34.6K
We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
34.6K
Time-Series Graph00:54

Time-Series Graph

4.4K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.4K
Ogive Graph01:07

Ogive Graph

5.7K
An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
5.7K
Signal Flow Graphs01:18

Signal Flow Graphs

255
Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
255
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

12.2K
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...
12.2K
Protein Networks02:26

Protein Networks

2.4K
2.4K

You might also read

Related Articles

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

Sort by
Same author

An innovative fuzzy Revan index with CRITIC integration in multi-criterion decision-making.

Scientific reports·2026
Same author

An advanced hybrid intuitionistic fuzzy Z-number framework for IT impact analysis in E-learning systems.

Scientific reports·2026
Same author

A novel computational study of reverse degree topological indices and entropies for nanostar dendrimers.

Scientific reports·2026
Same author

QSAR analysis of drugs using graph based degree based topological indices and regression models.

Scientific reports·2026
Same author

Correction: A novel numerical investigation of fiber Bragg gratings with dispersive reflectivity having polynomial law of nonlinearity.

Scientific reports·2025
Same author

Nonlocal complex short pulse equation in [Formula: see text]-symmetry like symmetry breaking, breather-grammian interactions and soliton solutions.

Scientific reports·2025
Same journal

Sleep deprivation impairs gastric ulcer healing and induces anxiety-like behavior in rats.

BMC research notes·2026
Same journal

Caring across cultures: a qualitative exploration of Macedonian carers supporting community-dwelling older adults in a large regional city in Australia.

BMC research notes·2026
Same journal

Prevalence and determinants of dyslipidemia among residents of Kurdistan Region of Iraq; a community-based study.

BMC research notes·2026
Same journal

Modulation of brain-kidney crosstalk by olanzapine in aluminum chloride-induced memory impairment: a preclinical investigation.

BMC research notes·2026
Same journal

Tagged and untagged amyloid precursor protein E2 domain have comparable thermal stability and metal-ion binding propensity.

BMC research notes·2026
Same journal

Phenotypical and functional characterization of a HepG2 cell clone stably overexpressing cytochrome P450 (CYP) 2C9.

BMC research notes·2026
See all related articles

Related Experiment Video

Updated: Jul 19, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.2K

Social network analysis by Turiyam graphs.

Gamachu Adugna Ganati1, V N Srinivasa Rao Repalle2, Mamo Abebe Ashebo2

  • 1Department of Mathematics, Wallaga University, Nekemte, Ethiopia. gammeekoo@gmail.com.

BMC Research Notes
|August 14, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces Turiyam graphs, an extension of neutrosophic graphs, to represent complex uncertainties including refusal degrees. Turiyam graphs offer a more comprehensive framework for analyzing social networks and other real-world scenarios.

Keywords:
DegreeOrderSingle valued neutrosophic graphSizeSocial networkTuriyam graph

More Related Videos

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:50

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

265
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

1.1K

Related Experiment Videos

Last Updated: Jul 19, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.2K
Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:50

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

265
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

1.1K

Area of Science:

  • Graph Theory
  • Fuzzy Set Theory
  • Artificial Intelligence

Background:

  • Single valued neutrosophic sets handle uncertainty via membership, indeterminacy, and non-membership degrees.
  • Real-life situations often involve an additional refusal degree, not fully captured by traditional neutrosophic sets.

Purpose of the Study:

  • Introduce Turiyam graphs as an extension of single valued neutrosophic graphs to incorporate a refusal degree.
  • Define and examine the concepts of degree, order, and size within Turiyam graphs.
  • Apply Turiyam graphs to analyze social networks and demonstrate their utility.

Main Methods:

  • Developed the theoretical framework for Turiyam graphs, including definitions for degree, order, and size.
  • Utilized graphical representations to depict complex uncertain relationships.
  • Applied the Turiyam graph concept to model and analyze a social network.

Main Results:

  • The degree, order, and size of Turiyam graphs were formally defined and studied.
  • The feasibility and applicability of Turiyam graphs were demonstrated through their use in analyzing a social network.
  • Turiyam graphs were shown to provide a superior framework compared to existing graph theories for representing complex uncertainties.

Conclusions:

  • Turiyam graphs offer a more comprehensive approach to modeling uncertainty by including a refusal degree.
  • The application in social networks highlights the practical value of Turiyam graphs in knowledge processing.
  • Turiyam graphs present a significant advancement over existing graph theories for handling multifaceted uncertainty.