Jove
Visualize
Contact Us
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 Concept Videos

Classification of Systems-II01:31

Classification of Systems-II

585
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
585
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

384
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
384
Classification of Systems-I01:26

Classification of Systems-I

712
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
712
Aggregates Classification01:29

Aggregates Classification

1.2K
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
1.2K
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

1.9K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
1.9K
Survival Tree01:19

Survival Tree

504
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
504

You might also read

Related Articles

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

Sort by
Same author

A proof-of-concept study of the challenges of assessing the impact of crime scene units' accreditation: Lessons from a difference-in-differences analysis on police finalisation rates in Australia.

Forensic science international·2026
Same author

Event-Triggered Multiple Leaders Formation Tracking for Networked Swarm System With Resilience to Noncooperative Nodes.

IEEE transactions on cybernetics·2025
Same author

Forensic DNA Phenotyping: Examining knowledge and operational view from police officers.

Forensic science international. Synergy·2025
Same author

Do future police officers want to pursue a crime scene examiner career? Exploring stability and change in police recruits' interest in crime scene investigation.

Science & justice : journal of the Forensic Science Society·2025
Same author

A framework for resilience assessment of transportation networks exposed to geohazard threats.

Risk analysis : an official publication of the Society for Risk Analysis·2025
Same author

A modelling framework to analyze climate change effects on radionuclide aquifer contamination.

Journal of contaminant hydrology·2024
Same journal

Competition and Collaboration in the AI Race: Country-LevelDirectional Evidence for Risk Monitoring and Policy.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Cyber Resilience: Management With Cybersecurity Controls.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Jack Fowle: Combining Values, Experience, and Teamwork to Improve Risk Analysis.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

A Hybrid FMEA-AHP Framework for Risk Prioritization in Nontransparent Artificial Intelligence Systems.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Trust-Building Communication for Extreme Heat Preparedness.

Risk analysis : an official publication of the Society for Risk Analysis·2026
Same journal

Spring Broken: A Risk Analysis of Fatal and Nonfatal Traffic Injuries in Florida.

Risk analysis : an official publication of the Society for Risk Analysis·2026
See all related articles

Related Experiment Video

Updated: Apr 19, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

14.0K

Assessing the Performance of a Classification-Based Vulnerability Analysis Model.

Tai-ran Wang1, Vincent Mousseau2, Nicola Pedroni1

  • 1Chair on Systems Science and the Energy Challenge, European Foundation for New Energy-Electricité de France, Ecole Centrale Paris and Supélec, Chatenay Malabry Cedex, France.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|December 10, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a novel classification model using majority rule sorting (MR-Sort) to assess safety-critical system vulnerability to malevolent acts. Quantitative performance assessment methods were explored to ensure reliable vulnerability analysis.

Keywords:
Classification modelMR-Sortconfidence estimationnuclear power plantsvulnerability analysis

More Related Videos

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.9K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.8K

Related Experiment Videos

Last Updated: Apr 19, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

14.0K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

2.9K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.8K

Area of Science:

  • System safety engineering
  • Risk assessment methodologies
  • Computational intelligence

Background:

  • Safety-critical systems require robust vulnerability assessment against intentional threats.
  • Empirical classification models, while useful, introduce uncertainty that must be quantified.
  • Nuclear power plants serve as a relevant case study for such analyses.

Purpose of the Study:

  • To develop and evaluate a classification model for system vulnerability to malevolent acts.
  • To quantitatively assess the performance and confidence of the developed vulnerability classification model.
  • To explore different methods for uncertainty quantification in vulnerability analysis.

Main Methods:

  • Majority Rule Sorting (MR-Sort) method for classification model construction.
  • Utilizing a limited dataset of known vulnerability classifications.
  • Employing model-retrieval, bootstrap, and leave-one-out cross-validation for performance assessment.

Main Results:

  • The MR-Sort model provides a framework for vulnerability classification.
  • Quantitative assessment revealed varying levels of accuracy and confidence in model assignments.
  • Comparative analysis of the three performance assessment techniques was conducted.

Conclusions:

  • The MR-Sort approach offers a structured method for evaluating system vulnerability.
  • Quantifying model performance is crucial for reliable safety-critical system analysis.
  • The chosen methods provide valuable insights into the reliability of vulnerability assessments.