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

Distributed Loads: Problem Solving

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...

Observational Learning

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...

Reducing Line Loss

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...

Ampere-Maxwell's Law: Problem-Solving

Ampere-Maxwell's Law: Problem-Solving

A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...

Maximum Power Transfer

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...

You might also read

Related Articles

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

Sort by

Same author

Design of a 5G millimeter-wave wideband high-gain metamaterial-based antenna.

Scientific reports·2026

Same author

Fractional modeling of nonlinear dispersive systems: on the comparative study of Whitham-Broer-Kaup equations using various derivatives.

Scientific reports·2026

Same author

Vibrational Analysis of Thermoelastic Beams on Dual-Parameter Foundations via the Fractional Three-Phase-Lag Approach.

Micromachines·2026

Same author

Preoperative Mental Health, Sociodemographic, and Clinical Correlates of Baseline Pain and Function in Hallux Valgus Surgery Candidates.

Foot & ankle international·2026

Same author

Clinical significance of new suspicious enhancement on breast MRI during neoadjuvant chemotherapy.

Clinical imaging·2025

Same author

Response of nonlocal thermoelastic nanobeams supported by Pasternak foundations to the effect of generalized fractional theory with three-phase lags.

Scientific reports·2025

Search research articles

Related Experiment Video

Updated: Oct 2, 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

Re-Learning EXP3 Multi-Armed Bandit Algorithm for Enhancing the Massive IoT-LoRaWAN Network Performance.

Samar Adel Almarzoqi¹, Ahmed Yahya¹, Zaki Matar¹

¹Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11651, Egypt.

Sensors (Basel, Switzerland)

|February 26, 2022

Summary

This study enhances Long-Range Wide Area Network (LoRaWAN) performance using a decentralized Multi-Armed Bandit (MAB) approach. Combining expert advice in the EXP3 algorithm significantly boosts data throughput and optimizes power consumption for IoT devices.

Keywords:

IoT LPWAN LoRaWAN MAB wireless node

More Related Videos

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Oct 2, 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 Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Area of Science:

Computer Science
Electrical Engineering
Telecommunications

Background:

Long-Range Wide Area Network (LoRaWAN) is a key protocol for Internet of Things (IoT) Low Power Wide Area Networks (LPWAN).
Decentralized decision-making is crucial for optimizing IoT network performance.
Existing methods may not fully leverage historical data for adaptive parameter tuning.

Purpose of the Study:

To investigate the impact of the EXP3 Multi-Armed Bandit (MAB) algorithm, incorporating expert advice, on LoRaWAN network performance.
To propose and evaluate a novel approach using combined expert distributions for transmission parameter optimization.
To enhance successful packet transmission with minimized power consumption in LoRaWAN.

Main Methods:

Implementation of a self-managed EXP3 algorithm within LoRa smart nodes for adaptive transmission parameter selection and updates.
Development of a method to combine previous expert distribution advice for improved parameter confidence.
Simulation-based validation of the proposed approach on LoRaWAN network performance metrics.

Main Results:

The re-learning EXP3 MAB algorithm with expert advice demonstrated improved LoRaWAN network performance.
Combined expert distribution strategies led to significant enhancements in data throughput.
Optimized transmission parameters resulted in reduced power consumption for successful packet delivery.

Conclusions:

The integration of combined expert distribution within the EXP3 MAB algorithm is effective for LoRaWAN optimization.
This approach successfully balances data throughput and power efficiency in IoT networks.
The findings provide a pathway for more intelligent and efficient LPWAN management.