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

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...

Absolute Motion Analysis- General Plane Motion

Absolute Motion Analysis- General Plane Motion

Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...

You might also read

Related Articles

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

Sort by

Same author

PUFA-rich oil supplement improves hair condition of cats and dogs.

Open veterinary journal·2026

Same author

Berberine from Tibetan Medicine <i>Dracocephalum tanguticum</i> Maxim Suppresses Colorectal Tumor Growth and Inhibits CD8⁺ T Cells Ferroptosis via the NRF2-SLC7A11-GPX4 Axis.

Cancer management and research·2026

Same author

Confinement-Driven Redox Inversion and Predicted Ferromagnetism in One-Dimensional Sc<sub>3</sub>Cl<sub>8</sub> within Single-Walled Carbon Nanotubes.

Nano letters·2026

Same author

From weak but broad to potent and universal: A trispecific antibody against conserved SARS-CoV-2 spike epitopes.

Molecular therapy : the journal of the American Society of Gene Therapy·2026

Same author

Association between patient-reported outcomes and pathological response in neoadjuvant chemoimmunotherapy-a post hoc analysis of the TD-FOREKNOW trial.

Translational lung cancer research·2026

Same author

Pseudo Sentences Evaluation and Quality-Aware Robust Learning for Unsupervised Text-Based Person Search.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

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

Search research articles

Related Experiment Video

Updated: Jul 23, 2025

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning

Published on: June 2, 2014

Task-Incremental Learning for Drone Pilot Identification Scheme.

Liyao Han¹, Xiangping Zhong¹, Yanning Zhang¹

¹School of Cybersecurity, Northwestern Polytechnical University, Xi'an 710072, China.

Sensors (Basel, Switzerland)

|July 14, 2023

Summary

This summary is machine-generated.

This study introduces an incremental learning drone pilot identification system to prevent impersonation attacks. The new system effectively identifies pilots and adapts to new users, ensuring drone security.

Keywords:

Internet of Things UAV security deep learning drone pilot identification incremental learning

More Related Videos

Operant Learning of Drosophila at the Torque Meter

Operant Learning of Drosophila at the Torque Meter

Published on: June 16, 2008

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: Jul 23, 2025

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning

Recording Single Neurons' Action Potentials from Freely Moving Pigeons Across Three Stages of Learning

Published on: June 2, 2014

Operant Learning of Drosophila at the Torque Meter

Operant Learning of Drosophila at the Torque Meter

Published on: June 16, 2008

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
Aerospace Engineering
Cybersecurity

Background:

Unmanned Aerial Vehicle (UAV) technology is crucial for intelligent transportation systems.
Commercial drones face impersonation attacks due to a lack of effective identification.
Existing pilot identification schemes lack extensibility for dynamic membership management.

Purpose of the Study:

To propose an incremental learning-based drone pilot identification scheme.
To protect drones from impersonation attacks.
To enable dynamic pilot membership management.

Main Methods:

Utilizing pilot temporal operational behavioral traits for identification.
Implementing an incremental learning approach for dynamic adaptation.
Systemic experiments on P450 and S500 drone platforms.

Main Results:

Achieved high average identification accuracy: 95.71% on P450 and 94.23% on S500.
Maintained identification performance with increasing numbers of registered pilots.
Demonstrated minimal system overhead.

Conclusions:

The proposed scheme effectively validates pilot legal status and protects against impersonation attacks.
The system supports dynamic pilot membership management with high accuracy and extensibility.
The identification scheme shows significant potential for enhancing drone security in intelligent transportation systems.