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

Entropy02:39

Entropy

32.1K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
32.1K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

112
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...
112
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

3.4K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
3.4K
Probability Laws01:49

Probability Laws

42.3K
Overview
42.3K
Deindividuation00:57

Deindividuation

28.3K
Deindividuation is a form of social influence on an individual’s behavior such that the individual engages in unusual or non-normal behavior while in a group setting. Why? Because in these group settings, the individual no longer sees themselves as an individual anymore, disinhibiting their behavior and personal restraint.
28.3K
Probability Histograms01:17

Probability Histograms

12.4K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
12.4K

You might also read

Related Articles

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

Sort by
Same author

Reclamation of wastewater organics via two-stage growth of bacteria-then-oleaginous phagotrophic algae.

Bioprocess and biosystems engineering·2018
Same author

Anti-endometriosis Mechanism of <i>Jiawei Foshou San</i> Based on Network Pharmacology.

Frontiers in pharmacology·2018
Same author

Remote in situ laser-induced breakdown spectroscopic approach for diagnosis of the plasma facing components on experimental advanced superconducting tokamak.

The Review of scientific instruments·2018
Same author

Peptide-Functionalized Nanoinhibitor Restrains Brain Tumor Growth by Abrogating Mesenchymal-Epithelial Transition Factor (MET) Signaling.

Nano letters·2018
Same author

Reticuloendothelial System Pre-Block Strategy to Improve Tumor Targeting Efficacy for Hyaluronic Acid Related Drug Delivery System.

Journal of biomedical nanotechnology·2018
Same author

First-Principles Study on the Adsorption and Dissociation of Impurities on Copper Current Collector in Electrolyte for Lithium-Ion Batteries.

Materials (Basel, Switzerland)·2018
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Oct 21, 2025

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

2.7K

A high-density crowd state judgment model based on entropy theory.

Guomin Zhao1, Cong Li1, Guangji Xu1

  • 1School of Energy and Safety Engineering, Tianjin Chengjian University, Tianjin, PR China.

Plos One
|September 2, 2021
PubMed
Summary
This summary is machine-generated.

Predicting crowd density using entropy theory helps prevent stampedes. This model assesses crowd states to inform safety and evacuation strategies, enhancing public security.

More Related Videos

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.0K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.0K

Related Experiment Videos

Last Updated: Oct 21, 2025

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

2.7K
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.0K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

34.0K

Area of Science:

  • Complex Systems Science
  • Public Safety Analytics
  • Statistical Mechanics

Background:

  • High-density crowds pose significant risks, leading to dangerous stampede events.
  • Accurate prediction of crowd behavior is crucial for preventing accidents and ensuring safety.
  • Existing methods may lack the precision needed for real-time crowd management.

Purpose of the Study:

  • To introduce a novel method for characterizing crowd states using entropy theory.
  • To develop a predictive model for identifying high-risk crowd congestion scenarios.
  • To provide a basis for effective crowd management and evacuation strategies.

Main Methods:

  • Application of entropy theory to quantify the state of a crowded system.
  • Calculation of theoretical entropy (Sr) and actual entropy (S) based on crowd distribution.
  • Comparison of maximum entropy values with actual entropy under varying conditions.

Main Results:

  • The entropy-based model effectively characterizes different crowd density states.
  • The model demonstrates practical applicability in assessing crowd congestion levels.
  • A clear correlation between entropy values and crowd states was established.

Conclusions:

  • The developed entropy model is a practical and effective tool for crowd state assessment.
  • Findings support the implementation of targeted management and evacuation plans.
  • This approach enhances the ability to prevent large-scale crowd-related accidents.