Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Maxwell-Boltzmann Distribution: Problem Solving

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by

You might also read

Related Articles

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

Sort by

Same author

Can the two-point method based on peak and trough concentrations accurately estimate the area under the curve of polymyxin B? A Monte Carlo simulation study.

Frontiers in pharmacology·2026

Same author

Ginsenoside Rb1 mitigates senescence-associated hepatic steatosis in mice through enhanced lysine degradation.

Journal of ginseng research·2026

Same author

Intestinal Barrier Dysfunction and Stem Cell Impairment Following Cardiac Surgery in Pigs: A Porcine Model Study.

Biology·2026

Same author

Comparative efficacy and safety of extended versus continuous infusion of beta-lactam antibiotics for severe infection: a network meta-analysis of randomized trials.

Critical care (London, England)·2026

Same author

Whole-Genome Resequencing Reveals Deep Genomic Differentiation and Highly Differentiated Segments Between a Composite Domestic Cattle Population and Yak from the Ili River Valley and Other Xinjiang Regions.

Animals : an open access journal from MDPI·2026

Same author

Validation of qualitative and quantitative methods for 40 benzodiazepines and Z-drugs in hair by UPLC-MS/MS.

Journal of pharmaceutical and biomedical analysis·2026

Search research articles

Related Experiment Video

Updated: Aug 13, 2025

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

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

Published on: September 8, 2023

A Quantum Annealing Bat Algorithm for Node Localization in Wireless Sensor Networks.

Shujie Yu¹, Jianping Zhu¹, Chunfeng Lv¹

¹College of Engineering Science and Technology, Shanghai Ocean University, No. 999, Huchenghuan Rd., Nanhui New City, Shanghai 201306, China.

Sensors (Basel, Switzerland)

|January 21, 2023

Summary

A new Quantum Annealing Bat Algorithm (QABA) enhances wireless sensor network (WSN) node localization accuracy. This improved algorithm significantly reduces localization errors in both 2D and 3D spaces.

Keywords:

bat algorithm geometric features natural selection node localization quantum evolution tournament wireless sensor networks

More Related Videos

Author Spotlight: High-Quality Quantum Dot Nanobeads for Sensitive Fluorescent Lateral Flow Immunoassays

Author Spotlight: High-Quality Quantum Dot Nanobeads for Sensitive Fluorescent Lateral Flow Immunoassays

Published on: June 28, 2024

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

Related Experiment Videos

Last Updated: Aug 13, 2025

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

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

Published on: September 8, 2023

Author Spotlight: High-Quality Quantum Dot Nanobeads for Sensitive Fluorescent Lateral Flow Immunoassays

Author Spotlight: High-Quality Quantum Dot Nanobeads for Sensitive Fluorescent Lateral Flow Immunoassays

Published on: June 28, 2024

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

Area of Science:

Computer Science
Electrical Engineering
Artificial Intelligence

Background:

Node localization is crucial for wireless sensor networks (WSNs).
Existing localization methods face challenges in accuracy and applicability.
Improving localization performance is an active research area.

Purpose of the Study:

To propose a novel algorithm for enhanced node localization in WSNs.
To improve the accuracy and applicability of WSN node localization.
To introduce a Quantum Annealing Bat Algorithm (QABA) for this purpose.

Main Methods:

Developed a Quantum Annealing Bat Algorithm (QABA) integrating quantum evolution and annealing strategies.
Enhanced the bat algorithm's search capabilities for improved convergence.
Designed 2D (QABA-2D) and 3D (QABA-3D) localization algorithms using trilateral and geometric principles, optimized with QABA.

Main Results:

QABA demonstrated significantly improved convergence speed and solution accuracy compared to other heuristic algorithms.
QABA-2D achieved the highest average error reduction of 90.35% and the lowest of 17.22%.
QABA-3D achieved the highest average error reduction of 75.26% and the lowest of 7.79%.

Conclusions:

QABA offers superior performance in WSN node localization.
The proposed QABA-based algorithms provide substantial improvements in localization accuracy.
This research contributes a more effective solution for WSN localization challenges.