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

Detection of Black Holes01:10

Detection of Black Holes

2.6K
Although black holes were theoretically postulated in the 1920s, they remained outside the domain of observational astronomy until the 1970s.
Their closest cousins are neutron stars, which are composed almost entirely of neutrons packed against each other, making them extremely dense. A neutron star has the same mass as the Sun but its diameter is only a few kilometers. Therefore, the escape velocity from their surface is close to the speed of light.
Not until the 1960s, when the first neutron...
2.6K
Relative Strengths of Conjugate Acid-Base Pairs02:29

Relative Strengths of Conjugate Acid-Base Pairs

52.6K
Brønsted-Lowry acid-base chemistry is the transfer of protons; thus, logic suggests a relation between the relative strengths of conjugate acid-base pairs. The strength of an acid or base is quantified in its ionization constant, Ka or Kb, which represents the extent of the acid or base ionization reaction. For the conjugate acid-base pair HA / A−, the ionization equilibrium equations and ionization constant expressions are
52.6K
Acid and Bases: Ka, pKa, and Relative Strengths02:35

Acid and Bases: Ka, pKa, and Relative Strengths

33.6K
This lesson delves into a critical aspect of the relative strengths of acids and bases. The strength of an acid is evaluated by the acid dissociation into its conjugate base and a hydronium ion in water. The complete dissociation of a strong acid is confirmed with a very high concentration of hydronium ions. As a result, an incomplete dissociation process affirms a weak acid. Therefore, the equilibrium is in the forward direction for strong acids and backward for weak acids in these reactions.
33.6K
Nuclear Localization Signals and Import01:46

Nuclear Localization Signals and Import

7.8K
Proteins targeted to the nucleus carry short stretches of amino acid sequences called the nuclear localization signal or NLS. Classical nuclear localization signals are of two types: monopartite and bipartite NLS. Monopartite classical NLS (cNLS) consists of a single cluster of 4-8 amino acids. Bipartite cNLS consists of two clusters of  2-3 amino acids and a 9-12 residue long proline-rich linker bridging the two clusters. Signal clusters are rich in positively charged amino acids such as...
7.8K
Acid/Base Strengths and Dissociation Constants03:02

Acid/Base Strengths and Dissociation Constants

70.0K
The relative strength of an acid or base is the extent to which it ionizes when dissolved in water. If the ionization reaction is essentially complete, the acid or base is termed strong; if relatively little ionization occurs, the acid or base is weak. There are many more weak acids and bases than strong ones. The most common strong acids and bases are listed below:
70.0K
Self-Evaluation: Self-Enhancement and Self-Verification03:00

Self-Evaluation: Self-Enhancement and Self-Verification

5.8K
Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
5.8K

You might also read

Related Articles

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

Sort by
Same author

DUAL-Net: Joint Domain-Invariant and User-Adaptive Feature Learning for Gesture Recognition.

Sensors (Basel, Switzerland)·2026
Same author

Tree growth after a major hurricane reflects predisturbance vigor rather than canopy damage.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Taller Trees Experienced Less Crown Damage During a Severe Hurricane in a Tropical Forest.

Global change biology·2026
Same author

The Effects of FKBP12 Single-Dose Plasmid Oral Preparation on the Alkaline Phosphatase Activity, Mortality Rate, and Cocoon Quality of Bivoltine Jinqiu × Churi Silkworms.

International journal of molecular sciences·2026
Same author

Integrating Cross-Modal Semantic Learning with Generative Models for Gesture Recognition.

Sensors (Basel, Switzerland)·2025
Same author

The heterogeneous expression, extraction, and purification of recombinant Caldanaerobacter subterraneus subsp. tengcongensis apurine/apyrimidine endonuclease in Escherichia coli.

Protein expression and purification·2024

Related Experiment Video

Updated: Feb 8, 2026

Enhanced Oil Recovery using a Combination of Biosurfactants
13:19

Enhanced Oil Recovery using a Combination of Biosurfactants

Published on: June 3, 2022

6.0K

Enhancing Received Signal Strength-Based Localization through Coverage Hole Detection and Recovery.

Shuangjiao Zhai1, Zhanyong Tang2, Dajin Wang3

  • 1School of Information Science and Technology, Northwest University, Xi'an 710127, China. sjzhai@stumail.nwu.edu.cn.

Sensors (Basel, Switzerland)
|July 1, 2018
PubMed
Summary

This study introduces a novel algorithm for wireless sensor networks (WSNs) to fix coverage gaps in Radio Signal Strength Indicator (RSSI)-based localization. The method effectively recovers all coverage holes, ensuring up to 100% network coverage.

Keywords:
Delaunay triangulationRSSI-based localizationVoronoi tessellationcoverage holeswireless sensor networks

More Related Videos

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K
Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

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

Published on: August 27, 2021

6.1K

Related Experiment Videos

Last Updated: Feb 8, 2026

Enhanced Oil Recovery using a Combination of Biosurfactants
13:19

Enhanced Oil Recovery using a Combination of Biosurfactants

Published on: June 3, 2022

6.0K
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K
Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

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

Published on: August 27, 2021

6.1K

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) are crucial for applications like intrusion detection and monitoring.
  • Radio Signal Strength Indicator (RSSI)-based localization is a common technique in WSNs.
  • Existing coverage models (e.g., disk coverage) are often too simplistic for WSN localization, especially for non-disk models like ellipses.

Purpose of the Study:

  • To address the challenge of coverage holes in WSNs, specifically for RSSI-based localization techniques employing an elliptical coverage model.
  • To propose and evaluate an algorithm for detecting and recovering these coverage holes.

Main Methods:

  • The study proposes an algorithm inspired by Voronoi tessellation and Delaunay triangulation.
  • This algorithm is designed to identify and fill coverage gaps within the WSN.
  • The method specifically targets WSNs with elliptical coverage models.

Main Results:

  • The proposed algorithm successfully detects and recovers coverage holes in WSNs.
  • Simulation results demonstrate the algorithm's ability to achieve any desired coverage rate, including full 100% coverage.
  • The technique enhances the effectiveness of RSSI-based localization in WSNs.

Conclusions:

  • The developed algorithm effectively addresses coverage hole issues in WSNs with elliptical coverage models.
  • This approach significantly improves the reliability and performance of RSSI-based localization techniques.
  • The method offers a scalable solution for achieving comprehensive WSN coverage.