Jove
Visualize
Contact Us

Related Concept Videos

Design Example: Automobile Ignition System01:14

Design Example: Automobile Ignition System

245
The automobile's ignition system plays a vital role by ensuring the timely ignition of the fuel-air mixture in each cylinder. This ignition is facilitated by a spark plug, which is composed of two electrodes separated by an air gap. A spark forms across this air gap when a substantial voltage is generated between the electrodes, leading to the ignition of the fuel.
One can generate a large voltage using a car battery of 12 volts with the help of inductors. Inductors are known for opposing...
245
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

122
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...
122
Gas Chromatography: Types of Detectors-II01:19

Gas Chromatography: Types of Detectors-II

413
In gas chromatography, different detectors are employed to meet specific analytical needs. These detectors are often categorized based on their detection mechanisms and the types of compounds they are best suited to analyze. Thermal Conductivity Detectors (TCD), Flame Ionization Detectors (FID), and Electron Capture Detectors (ECD) represent common categories, each with unique operating principles and applications. However, beyond these, several other detectors are designed for more specialized...
413
Gas Chromatography: Types of Detectors-I01:21

Gas Chromatography: Types of Detectors-I

470
There are different types of detectors used in gas chromatography, each with its own specific properties that make it suitable for detecting certain types of analytes. The most commonly used detectors in GC are thermal conductivity detector (TCD), flame ionization detector (FID), and electron capture detector (ECD).
TCD is the earliest and most widely used detector that operates by measuring the changes in the thermal conductivity of the carrier gas. When a sample compound enters the detector,...
470
Pilot and Numeric Relaying01:21

Pilot and Numeric Relaying

98
Pilot relaying is a type of differential protection used in power systems. It compares electrical quantities at the terminals of equipment via a communication channel instead of direct relay interconnection. This method is essential for transmission lines where the terminals are far apart, typically up to 80 km for lines with 69 to 115 kV ratings. Four types of communication channels are used for pilot relaying:
98
High-Performance Liquid Chromatography: Types of Detectors01:15

High-Performance Liquid Chromatography: Types of Detectors

611
The role of the detectors in High-Performance Liquid Chromatography (HPLC) is to analyze the solutes as they exit from the chromatographic column. The detector recognizes the solute's property and generates corresponding electrical signals, which are converted into a readable graph of the detector's response versus elution time called a chromatogram at the computer. There are several types of HPLC detectors, each with its own advantages and limitations, depending on the analyte...
611

You might also read

Related Articles

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

Sort by
Same author

Acne Detection Based on Reconstructed Hyperspectral Images.

Journal of imaging·2024
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
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 Experiment Video

Updated: Jul 15, 2025

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.3K

Detecting Cyber Attacks In-Vehicle Diagnostics Using an Intelligent Multistage Framework.

Tasneem A Awaad1,2, Mohamed Watheq El-Kharashi1,3, Mohamed Taher1

  • 1Department of Computer and Systems Engineering, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt.

Sensors (Basel, Switzerland)
|September 28, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new multistage intrusion detection system (IDS) for vehicles. The novel framework effectively detects anomalies in vehicle diagnostic data with high accuracy and a low false acceptance rate.

Keywords:
anomaly detectioncyber-physical securityintrusion detectionmachine learningvehicle diagnosticsvehicular security

More Related Videos

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K

Related Experiment Videos

Last Updated: Jul 15, 2025

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
06:32

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring

Published on: July 14, 2023

1.3K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.7K
Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.7K

Area of Science:

  • Cybersecurity
  • Automotive Engineering
  • Machine Learning

Background:

  • Modern vehicles are increasingly vulnerable to cyber threats due to advanced technology.
  • Existing Intrusion Detection Systems (IDS) face challenges with high false acceptance rates and network infrastructure modifications.
  • Electronic Control Unit (ECU) limitations and placement concerns impact IDS effectiveness.

Purpose of the Study:

  • To propose a novel multistage framework for detecting abnormalities in vehicle diagnostic data.
  • To enhance vehicle security without significant changes to existing network infrastructure.
  • To achieve high detection accuracy and a low false acceptance rate for vehicle intrusion detection.

Main Methods:

  • Developed a multistage framework utilizing diagnostic specifications.
  • Employed a stacking ensemble of various machine learning models for anomaly detection.
  • Validated the framework against KIA SOUL and Seat Leon 2018 datasets.
  • Evaluated performance against unseen point and period anomaly attacks.

Main Results:

  • Achieved high accuracy: 99.21% for Seat Leon 2018 and 99.22% for KIA SOUL.
  • Demonstrated a low false acceptance rate: 0.003% for Seat Leon 2018 and 0.005% for KIA SOUL.
  • Reported a high detection rate (DR): 99.63% for Seat Leon 2018 and 98.59% for KIA SOUL.

Conclusions:

  • The proposed multistage IDS framework is superior and robust in detecting vehicle network anomalies.
  • The system effectively identifies various anomaly types with excellent performance metrics.
  • This approach offers a promising solution for enhancing automotive cybersecurity.