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

33.6K
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...
33.6K
Entropy01:18

Entropy

3.2K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
3.2K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.0K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.0K
Entropy and Solvation02:05

Entropy and Solvation

7.9K
The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
7.9K
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

3.9K
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...
3.9K
Entropy within the Cell01:22

Entropy within the Cell

12.3K
A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that...
12.3K

You might also read

Related Articles

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

Sort by
Same author

A Deep Learning Framework for Synthesizing Longitudinal Infant Brain MRI during Early Development.

Radiology. Artificial intelligence·2025
Same author

Fine-Grained Semantics-Enhanced Graph Neural Network Model for Person-Job Fit.

Entropy (Basel, Switzerland)·2025
Same author

Enabling AI-Generated Content for Gadolinium-Free Contrast-Enhanced Breast Magnetic Resonance Imaging.

Journal of magnetic resonance imaging : JMRI·2024
Same author

Breast tumor segmentation via deep correlation analysis of multi-sequence MRI.

Medical & biological engineering & computing·2024
Same author

Do Gender or Major Influence the Performance in Programming Learning? Teaching Mode Decision Based on Exercise Series Analysis.

Computational intelligence and neuroscience·2022
Same author

Improving Arabic Sentiment Analysis Using CNN-Based Architectures and Text Preprocessing.

Computational intelligence and neuroscience·2021
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Nov 27, 2025

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

34.1K

Context-Aware Superpixel and Bilateral Entropy-Image Coherence Induces Less Entropy.

Feihong Liu1, Xiao Zhang1, Hongyu Wang2,3

  • 1School of Information Science and Technology, Northwest University, Xi'an 710027, China.

Entropy (Basel, Switzerland)
|December 8, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces context-aware superpixel (CASP) clustering, mimicking human perception for hierarchical image segmentation. CASP automatically adapts superpixel numbers and improves segmentation accuracy by evaluating image coherence with bilateral entropy.

Keywords:
Gestalt grouping rulescomputer visionimage entropyimage representationminimum entropy principlesuperpixel

More Related Videos

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

15.0K
Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

3.0K

Related Experiment Videos

Last Updated: Nov 27, 2025

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

34.1K
Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
08:08

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

Published on: May 10, 2017

15.0K
Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis
05:59

Author Spotlight: Unlocking New Insights in fNIRS Studies - A Novel Framework for Inter-Brain Synchrony Analysis

Published on: October 6, 2023

3.0K

Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Neuroscience

Background:

  • Superpixel clustering aggregates pixels into meaningful groups, inspired by Gestalt principles.
  • Current methods lack hierarchical structure and require manual superpixel number initialization.
  • Underlying neural mechanisms of perceptual grouping remain unclear.

Purpose of the Study:

  • To develop a context-aware superpixel (CASP) method that adheres to Gestalt rules and hierarchical principles.
  • To enable automatic adaptation of superpixel numbers to diverse images.
  • To introduce bilateral entropy for evaluating image coherence and encoding efficiency.

Main Methods:

  • Proposed Context-Aware Superpixel (CASP) algorithm incorporating Gestalt rules and top-down hierarchy.
  • Developed bilateral entropy (conditional intensity and spatial occupation entropy) for coherence evaluation.
  • Conducted extensive experiments comparing CASP with baseline methods.

Main Results:

  • CASP demonstrated superior superpixel segmentation performance compared to existing methods.
  • CASP achieved lower entropy values, indicating improved encoding efficiency.
  • A strong correlation was found between local image coherence and superpixel segmentation performance.

Conclusions:

  • CASP effectively mimics human hierarchical image perception and adapts superpixel numbers automatically.
  • Bilateral entropy serves as a reliable metric for image coherence and segmentation quality.
  • Findings support the validity of perceptual rules and suggest developing new entropy criteria for complex patterns.