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Related Concept Videos

Transformers in Distribution System01:27

Transformers in Distribution System

Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the rated...
Types Of Transformers01:16

Types Of Transformers

Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
The Ideal Transformer01:26

The Ideal Transformer

In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's tangential component...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
Maximum Power Transfer01:16

Maximum Power Transfer

Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...

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Related Experiment Videos

An enhanced intelligent framework for 5G V2X communication using multi-objective optimization and mobility-aware

A Sangeetha1, R Santhana Krishnan2, T Sathya3

  • 1Department of Information Technology, PSNA College of Engineering and Technology, Dindigul, India. sangeetha@psnacet.edu.in.

Scientific Reports
|July 3, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces an intelligent framework for 5G Vehicle-to-Everything (V2X) communication, significantly improving routing efficiency. The new system reduces latency and energy use while boosting throughput for safer, more proficient road travel.

Keywords:
5G V2X networksBayesian optimizationIntelligent routingMAT TransformerMobility-aware Multi-Objective Harris Hawks OptimizationNetwork stabilitySpatiotemporal learning

Related Experiment Videos

Area of Science:

  • Telecommunications Engineering
  • Artificial Intelligence
  • Network Optimization

Background:

  • 5G-enabled Vehicle-to-Everything (V2X) communication faces challenges like high mobility, dynamic topologies, and strict Quality-of-Service (QoS) demands.
  • Latency-sensitive V2X applications suffer from link failures, routing overhead, and inefficient resource use.
  • Existing machine learning routing algorithms show limited adaptability and slow convergence.

Purpose of the Study:

  • To develop an enhanced intelligent framework for 5G V2X communication.
  • To address limitations in adaptability and convergence of current machine learning routing algorithms.
  • To optimize cluster formation, routing paths, and resource utilization for improved V2X performance.

Main Methods:

  • Proposed a novel Multi-Objective Harris Hawks Optimization (MO-HHO) algorithm.
  • Integrated MO-HHO with a Bayesian optimized Mobility-Aware Transformer Network (BMAT).
  • Utilized Tree-structured Parzen Estimator (TPE) for enhanced convergence in the BMAT model.

Main Results:

  • Achieved 20-30% reduced latency and 15-35% lower energy consumption.
  • Enhanced throughput by 18-28% compared to existing methods.
  • Demonstrated improved reliability and adaptability in urban and highway 5G V2X scenarios.

Conclusions:

  • The proposed MO-HHO and BMAT integrated framework significantly enhances 5G V2X communication performance.
  • The system effectively optimizes routing, cluster formation, and resource management.
  • Results indicate substantial improvements in latency, energy efficiency, and throughput for V2X networks.