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

Optimal Foraging00:48

Optimal Foraging

13.8K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
13.8K
Optimization Problems01:26

Optimization Problems

62
Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
62
Basic Postulates of Kinetic Molecular Theory: Particle Size, Energy, and Collision02:43

Basic Postulates of Kinetic Molecular Theory: Particle Size, Energy, and Collision

37.6K
The ideal-gas equation, which is empirical, describes the behavior of gases by establishing relationships between their macroscopic properties. For example, Charles’ law states that volume and temperature are directly related. Gases, therefore, expand when heated at constant pressure. Although gas laws explain how the macroscopic properties change relative to one another, it does not explain the rationale behind it.
37.6K
Optimal Arousal Theory01:23

Optimal Arousal Theory

820
The optimal arousal theory suggests that performance is maximized when an individual experiences a moderate level of arousal. This theory is closely tied to the Yerkes-Dodson law, which illustrates an inverted U-shaped relationship between arousal and performance. The law, formulated by psychologists Robert Yerkes and John Dodson, implies an ideal arousal level for optimal performance, and deviations from this level can lead to declines in effectiveness.
Inverted U-Shaped Performance Curve
The...
820
Unrealistic Optimism Bias01:30

Unrealistic Optimism Bias

219
Unrealistic optimism bias is the tendency to overestimate the likelihood of positive outcomes. This cognitive bias makes individuals believe they are less likely to experience failures, setbacks, or risks and more likely to succeed than others. For example, people may assume they are less prone to health issues, accidents, or financial struggles than their peers, even when they share similar risk factors.One key component of this bias is the above-average effect, where individuals perceive...
219
Optimizing Chromatographic Separations01:15

Optimizing Chromatographic Separations

988
Optimizing chromatographic separations is crucial for obtaining clean separations in a minimum amount of time. Optimization is required for several factors, including kinetic effects related to band broadening, plate height, capacity factor, and separation factor.
Band broadening refers to spreading solute bands as they travel through the column. This broadening can impact resolution. Plate height (H) represents the length required for one theoretical plate. A lower plate height corresponds to...
988

You might also read

Related Articles

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

Sort by
Same author

Gut microbiota-induced elevation of succinate exacerbates diabetic myocardial ischemia/reperfusion injury by promoting macrophage polarization.

Frontiers in immunology·2026
Same author

Deciphering the microbial and physicochemical pathways of biochar-based fertilizer in driving resource-use efficiency: A comparative study of two contrasting acidic soils.

Journal of environmental management·2026
Same author

Evaluation of fetal brain development in growth restriction subtypes using brain MRI volume measurement.

BMC pregnancy and childbirth·2026
Same author

MRI and MDCT Findings of Kaposiform Hemangioendothelioma in the Oral Cavity of a Neonate: A Case Report and Literature Review.

Current medical imaging·2026
Same author

Prenatal detection and multimodality imaging of a retroperitoneal fetus-in-fetu in a neonate: a case description.

Quantitative imaging in medicine and surgery·2026
Same author

Multi-Omics Analysis Reveals Age-Related Enhancements in Gut Morphology, Microbiome, and Metabolism of Tibetan Pigs.

Microorganisms·2026

Related Experiment Video

Updated: Jan 28, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K

An Area Coverage and Energy Consumption Optimization Approach Based on Improved Adaptive Particle Swarm Optimization

Song Peng1,2, Yonghua Xiong3,4

  • 1School of Automation, China University of Geosciences, Wuhan 430074, China. pengsong0916@163.com.

Sensors (Basel, Switzerland)
|March 13, 2019
PubMed
Summary

This study introduces an improved adaptive particle swarm optimization (IAPSO) for directional sensor networks (DSNs). The approach enhances area coverage and balances energy consumption, improving overall network performance and longevity.

Keywords:
area coverageclusterdirectional sensor networkenergy consumption balanceparticle swarm optimization

More Related Videos

Optimization of Renal Organoid and Organotypic Culture for Vascularization, Extended Development, and Improved Microscopy Imaging
12:49

Optimization of Renal Organoid and Organotypic Culture for Vascularization, Extended Development, and Improved Microscopy Imaging

Published on: March 28, 2020

8.3K
Dispersion of Nanomaterials in Aqueous Media: Towards Protocol Optimization
09:35

Dispersion of Nanomaterials in Aqueous Media: Towards Protocol Optimization

Published on: December 25, 2017

29.2K

Related Experiment Videos

Last Updated: Jan 28, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

1.1K
Optimization of Renal Organoid and Organotypic Culture for Vascularization, Extended Development, and Improved Microscopy Imaging
12:49

Optimization of Renal Organoid and Organotypic Culture for Vascularization, Extended Development, and Improved Microscopy Imaging

Published on: March 28, 2020

8.3K
Dispersion of Nanomaterials in Aqueous Media: Towards Protocol Optimization
09:35

Dispersion of Nanomaterials in Aqueous Media: Towards Protocol Optimization

Published on: December 25, 2017

29.2K

Area of Science:

  • Computer Science
  • Wireless Sensor Networks
  • Optimization Algorithms

Background:

  • Directional sensor networks (DSNs) face challenges with random node deployment, leading to coverage blind spots and overlaps.
  • Limited node energy and premature node death significantly degrade DSN service quality.

Purpose of the Study:

  • To propose an optimized approach for area coverage and energy consumption in DSNs.
  • To enhance coverage ratio and minimize redundancy using sensing direction rotation.
  • To achieve balanced energy consumption across sensor nodes through effective clustering.

Main Methods:

  • Developed a multi-objective optimization model for area coverage, focusing on coverage and redundancy ratios.
  • Implemented a clustering network strategy for even energy distribution.
  • Designed a cluster head selection model considering residual energy and balance.
  • Proposed a node-centric cluster formation algorithm using a weight function.
  • Utilized an improved adaptive particle swarm optimization (IAPSO) to solve the optimization models.

Main Results:

  • The proposed IAPSO approach effectively improves the coverage ratio.
  • Redundancy in coverage areas is significantly reduced.
  • Energy consumption is balanced across the sensor nodes, extending network lifetime.
  • Simulation results confirm superior performance compared to existing methods.

Conclusions:

  • The IAPSO-based approach offers a robust solution for optimizing coverage and energy consumption in DSNs.
  • This method addresses key limitations of random deployment and energy depletion in sensor networks.
  • The findings indicate a significant advancement in DSN performance and reliability.