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Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
Maximum Size of Aggregate01:12

Maximum Size of Aggregate

The maximum size of aggregate is defined as the aperture of the sieve retaining 15 percent or more of the particles present in the aggregate sample. The aggregate's maximum size impacts the concrete's water requirement, workability, and strength. Larger aggregates reduce the surface area needing cement paste coverage, which can lower water needs, thereby allowing a decrease in the water-to-cement ratio when the desired workability and richness of the mix are to be maintained, which can result...
Distributed Loads01:19

Distributed Loads

Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...

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Related Experiment Videos

SSDBFAN: Scalable and Secure Cluster-Based Data Aggregation with Blockchain for Flying Ad Hoc Networks.

Sufian Al Majmaie1, Ghazal Ghajari1, Niraj Prasad Bhatta2

  • 1Department of Computer Science and Engineering, Wright State University, Dayton, OH 45435, USA.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces SSDBFAN, a secure framework for Flying Ad Hoc Networks (FANETs). It enhances data aggregation efficiency and privacy using advanced cryptography and optimization algorithms for mobile UAVs.

Keywords:
FANETblockchaincryptographydata aggregationoptimization algorithms

Related Experiment Videos

Area of Science:

  • Computer Science
  • Network Security
  • Artificial Intelligence

Background:

  • Flying Ad Hoc Networks (FANETs) using mobile Unmanned Aerial Vehicles (UAVs) face security and privacy challenges in data aggregation due to dynamic structures and limited resources.
  • Traditional cluster-based data aggregation in FANETs can compromise data privacy, necessitating advanced security measures.

Purpose of the Study:

  • To propose SSDBFAN, a scalable and secure cluster-based data aggregation framework for FANETs.
  • To enhance data privacy and security in FANETs through integration of novel optimization and cryptographic techniques.

Main Methods:

  • Integration of the Frilled Lizard Optimization Algorithm (FLOA) for efficient Cluster Head (CH) selection.
  • Implementation of blockchain technology with post-quantum cryptography (lattice-based homomorphic encryption, Chinese Remainder Theorem) for privacy-preserving aggregation.
  • Utilizing a hybrid online/offline signature mechanism for secure and efficient authentication.

Main Results:

  • SSDBFAN demonstrates significant improvements in communication efficiency, reduced computational cost, and enhanced network stability compared to existing schemes.
  • Scalability analysis up to 500 UAV nodes shows effective control of blockchain overhead (bandwidth, latency, storage).
  • FLOA outperforms existing algorithms in cluster stability, delay, and throughput.

Conclusions:

  • SSDBFAN provides a scalable and security-aware solution for data aggregation in large-scale FANET environments.
  • The framework effectively addresses privacy concerns and enhances the overall performance and security of FANETs.