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

Self-Awareness and Its Effects01:21

Self-Awareness and Its Effects

308
Self-awareness is a psychological state in which the individual becomes the focal point of their attention. This inward focus transforms the self into an object of contemplation and assessment, influencing how individuals perceive their actions and their alignment with personal and societal standards.Triggers and Contexts for Self-AwarenessSelf-awareness can be activated by external stimuli that make individuals visually or audibly aware of themselves, such as mirrors, cameras, or recordings.
308
Altered States of Awareness01:06

Altered States of Awareness

1.1K
Altered states of consciousness represent significant deviations from one's normal mental state. These deviations can range from subtle changes in awareness to profound transformations in perception, thought processes, and sensory experiences. Altered states of consciousness can be triggered by various factors, including drug use, meditation, hypnosis, illness, or even intense fatigue.
The ingestion of substances like stimulants or hallucinogens leads to chemical alterations in the brain...
1.1K
Subconsciousness and No Awareness01:15

Subconsciousness and No Awareness

702
The concept of subconscious awareness refers to the processing of information below the level of conscious thought, which significantly influences both behaviors and decisions. It is also known as waking subconscious awareness. This complex level of cognition operates without the direct awareness of the individual, facilitating rapid and simultaneous handling of multiple information streams.
An illustrative example of subconscious processing is its role in problem-solving. Often, individuals...
702
Interference and Diffraction02:18

Interference and Diffraction

52.3K
Interference is a characteristic phenomenon exhibited by waves. When two electromagnetic waves interact with their peaks and troughs coinciding, a resulting wave with enhanced amplitude is produced. This is known as constructive interference. In this case, the two waves interacting are in phase with each other.
52.3K
RNA Interference01:23

RNA Interference

28.0K
RNA interference (RNAi) is a process in which a small non-coding RNA molecule blocks the post-transcriptional expression of a gene by binding to its messenger RNA (mRNA) and preventing the protein from being translated.
This process occurs naturally in cells, often through the activity of genomically-encoded microRNAs. Researchers can take advantage of this mechanism by introducing synthetic RNAs to deactivate specific genes for research or therapeutic purposes. For example, RNAi could be used...
28.0K
High-Level and Low-Level Awareness01:19

High-Level and Low-Level Awareness

693
Controlled processes in human consciousness represent high-alert mental states where individuals deliberately focus their attention on achieving specific goals. Controlled processes can be seen in situations like mastering new technology, where a person might become so absorbed that they ignore surrounding distractions. Such processes involve selective attention, requiring one to concentrate on particular elements of experience while disregarding others. These are governed by executive...
693

You might also read

Related Articles

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

Sort by
Same author

SecureEdge-MedChain: A Post-Quantum Blockchain and Federated Learning Framework for Real-Time Predictive Diagnostics in IoMT.

Sensors (Basel, Switzerland)·2025
Same author

STID-Net: Optimizing Intrusion Detection in IoT with Gradient Descent.

Sensors (Basel, Switzerland)·2025
Same author

Design and SAR Analysis of an AMC-Integrated Wearable Cavity-Backed SIW Antenna.

Micromachines·2025
Same author

Variational Autoencoders for Network Lifetime Enhancement in Wireless Sensors.

Sensors (Basel, Switzerland)·2024
Same author

Blockchain Enabled Anonymous Privacy-Preserving Authentication Scheme for Internet of Health Things.

Sensors (Basel, Switzerland)·2023
Same author

Interleaved Honeypot-Framing Model with Secure MAC Policies for Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

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

Related Experiment Video

Updated: Jan 29, 2026

Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines
10:46

Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines

Published on: June 2, 2018

9.8K

Multi-Factor Cost Function-Based Interference-Aware Clustering with Voronoi Cell Partitioning for Dense WSNs.

Soundrarajan Sam Peter1, Parimanam Jayarajan2, Rajagopal Maheswar3

  • 1Department of Artificial Intelligence and Data Science, Sri Eshwar College of Engineering, Coimbatore 641202, Tamil Nadu, India.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
Summary
This summary is machine-generated.

A new Density-Aware Adaptive Clustering (DAAC) protocol optimizes wireless sensor networks (WSNs) by improving cluster head selection and formation. This leads to significantly extended network lifetime and enhanced data delivery in dense environments.

Keywords:
density-aware clusteringdynamic clusteringlink qualityload balancingnode density

More Related Videos

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets
06:40

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Published on: February 23, 2024

1.8K
DNA Vector-based RNA Interference to Study Gene Function in Cancer
13:10

DNA Vector-based RNA Interference to Study Gene Function in Cancer

Published on: June 4, 2012

21.0K

Related Experiment Videos

Last Updated: Jan 29, 2026

Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines
10:46

Dissection of Enhancer Function Using Multiplex CRISPR-based Enhancer Interference in Cell Lines

Published on: June 2, 2018

9.8K
Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets
06:40

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Published on: February 23, 2024

1.8K
DNA Vector-based RNA Interference to Study Gene Function in Cancer
13:10

DNA Vector-based RNA Interference to Study Gene Function in Cancer

Published on: June 4, 2012

21.0K

Area of Science:

  • Computer Science
  • Network Engineering
  • Wireless Communication

Background:

  • Traditional clustering algorithms like LEACH and HEED struggle with dense wireless sensor networks (WSNs) due to unbalanced load distribution and high contention.
  • Existing methods often result in overloaded cluster heads (CHs) in dense areas and underutilized CHs in sparse regions, leading to frequent CH changes and reduced network efficiency.
  • This inefficiency is particularly problematic in dynamic, real-time environments requiring stable network operation.

Purpose of the Study:

  • To develop a Density-Aware Adaptive Clustering (DAAC) protocol for optimizing CH selection and cluster formation in dense WSNs.
  • To address the limitations of traditional algorithms by incorporating node density and link quality into CH selection metrics.
  • To enhance overall network lifetime, packet delivery ratio, and throughput in dense WSN deployments.

Main Methods:

  • Developed the DAAC protocol, utilizing residual energy, local node density, and link quality as a unified CH detection metric.
  • Implemented a minimum inter-CH distance constraint to prevent CH crowding and used a multi-factor cost function for cluster formation.
  • Incorporated dynamic re-clustering triggered by CH energy depletion or significant load density changes, and employed dynamic Voronoi cells (VCs) for interference-aware coverage.

Main Results:

  • DAAC demonstrated a network lifetime improvement of 20.53% over LEACH and 32.51% over HEED.
  • The protocol achieved an average increase in packet delivery ratio of 8.14% (vs. LEACH) and 25.68% (vs. HEED).
  • Total throughput packet saw significant enhancements: 140.15% over LEACH and 883.51% over HEED.

Conclusions:

  • DAAC effectively optimizes CH selection and cluster formation in dense WSNs, outperforming traditional algorithms like LEACH and HEED.
  • The protocol's adaptive nature and use of Voronoi cells contribute to improved network lifetime, data reliability, and overall performance.
  • DAAC offers a robust solution for dense WSNs, enabling efficient hierarchical extensions and secondary CHs in extremely dense scenarios.