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

Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

355
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
355
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

652
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
652
Routh-Hurwitz Criterion I01:15

Routh-Hurwitz Criterion I

422
Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
422
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
Moment-Area Theorems01:17

Moment-Area Theorems

514
The Moment-Area Theorem is crucial in structural engineering for analyzing beam bending, particularly in applications like building floor supports. This theorem utilizes the geometric properties of the elastic curve, which depicts how a beam deforms under load, to simplify the calculations of deflections and slopes.
The theorem is divided into two parts. The first part connects the angle between tangents at any two points on the beam's elastic curve to the area under a curve derived by...
514
Trimmed Mean01:10

Trimmed Mean

3.1K
While measuring the mean of a data set, care needs to be taken when associating the mean to its central tendency. The same goes for the arithmetic mean, the geometric mean, or the harmonic mean. This is because the presence of a single outlier data value can significantly affect the mean. That is, the mean is sensitive to fluctuations in the data set.
Although certain measures of central tendency are not sensitive to outliers, there are alternative versions of the mean that get around the...
3.1K

You might also read

Related Articles

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

Sort by
Same author

Determinants of Bird Richness in the Louzishan National Nature Reserve: Effects of Productivity and Habitat Heterogeneity Across Taxonomic and Functional Dimensions.

Ecology and evolution·2026
Same author

Upcycling of atmospheric CO<sub>2</sub> to self-healing recyclable polymers under ambient conditions.

Nature communications·2026
Same author

Lithium ions protected orbital symmetry enables reversible oxygen redox in layered manganese-based cathodes.

Science bulletin·2025
Same author

Development and evaluation of a deep learning system for screening real-world multiple abnormal findings based on ultra-widefield fundus images.

Frontiers in medicine·2025
Same author

A secure and scalable IoT access control framework with dynamic attribute updates and policy hiding.

Scientific reports·2025
Same author

Four-Point Refixation for In-the-Bag Intraocular Lens Dislocation Into Vitreous Cavity With Implantable Capsular Hooks.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)·2023
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

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.2K

An Attribute Reduction Method Using Neighborhood Entropy Measures in Neighborhood Rough Sets.

Lin Sun1,2, Xiaoyu Zhang1, Jiucheng Xu1,2

  • 1College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel attribute reduction method for neighborhood rough sets, effectively handling continuous data and improving classification performance. The new approach utilizes neighborhood entropy measures to select relevant attributes, enhancing data mining preprocessing.

Keywords:
attribute reductionclassificationneighborhood entropyneighborhood rough setsrough sets

More Related Videos

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.3K
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

34.2K

Related Experiment Videos

Last Updated: Nov 27, 2025

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.2K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.3K
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

34.2K

Area of Science:

  • Data Mining and Machine Learning
  • Rough Set Theory
  • Information Theory

Background:

  • Classical rough set theory may lose information during discretization of continuous data.
  • Neighborhood rough set theory offers an alternative for handling continuous data.
  • Attribute reduction is crucial for efficient data mining and improving classification performance.

Purpose of the Study:

  • To propose a novel attribute reduction method for neighborhood rough sets.
  • To enhance classification performance on complex and continuous data.
  • To integrate algebraic and informational views for attribute reduction.

Main Methods:

  • Developed a new average neighborhood entropy measure combining neighborhood approximate precision and neighborhood entropy.
  • Introduced decision neighborhood entropy to address uncertainty and noisiness in neighborhood decision systems.
  • Derived properties and relationships of these entropy measures.
  • Proposed a heuristic attribute reduction algorithm.

Main Results:

  • The proposed method effectively handles continuous data while preserving classification information.
  • New entropy measures provide a comprehensive analysis of knowledge content and uncertainty.
  • Experimental results demonstrate significant improvements in classification performance.
  • The method successfully identifies the most relevant attributes.

Conclusions:

  • The novel attribute reduction method based on neighborhood entropy measures is effective for complex data.
  • The integration of algebraic and informational views enhances attribute reduction capabilities.
  • The proposed approach offers a robust solution for data mining preprocessing with continuous data.