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

Manipulation and Analysis01:21

Manipulation and Analysis

23
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
23
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

42
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...
42
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

121
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
121
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

65
Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
65

You might also read

Related Articles

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

Sort by
Same author

Optimising the resilience of shipping networks to climate vulnerability.

Maritime policy and management·2025
Same author

Maritime cybersecurity: are onboard systems ready?

Maritime policy and management·2024
Same author

Use of evidential reasoning and AHP to assess regional industrial safety.

PloS one·2018
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: Jun 20, 2025

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

13.3K

Enhancing maritime transportation security: A data-driven Bayesian network analysis of terrorist attack risks.

Massoud Mohsendokht1, Huanhuan Li1, Christos Kontovas1

  • 1Faculty of Engineering and Technology, Liverpool Logistics, Offshore and Marine (LOOM) Research Institute, Liverpool John Moores University, Liverpool, Merseyside, UK.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|July 21, 2024
PubMed
Summary
This summary is machine-generated.

Maritime terrorism poses low-frequency, high-consequence risks. This study introduces a data-driven Bayesian network (DDBN) model using accident data to analyze maritime security risks and identify contributing factors.

Keywords:
Bayesian networkGlobal Terrorism Databasemaritime terrorismsecurity risk assessment

More Related Videos

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.0K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

530

Related Experiment Videos

Last Updated: Jun 20, 2025

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

13.3K
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.0K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

530

Area of Science:

  • Maritime Security
  • Risk Analysis
  • Terrorism Studies

Background:

  • Maritime terrorist accidents are infrequent but severe, demanding novel analytical approaches.
  • Existing research on maritime terrorism risk is limited, highlighting a critical knowledge gap.
  • Understanding the uncertainty and interdependencies in maritime security threats is crucial.

Purpose of the Study:

  • To develop and validate a novel data-driven Bayesian network (DDBN) model for maritime security risk analysis.
  • To identify key factors contributing to maritime terrorist incidents and their interrelationships.
  • To assess the probability and impact of various maritime terrorism scenarios.

Main Methods:

  • Utilized historical maritime terrorist accident data from the past two decades.
  • Developed a data-driven Bayesian network (DDBN) model for risk assessment.
  • Employed sensitivity, metrics, and comparative analyses for model verification and validation.
  • Tested the model against recent real-world cases for retrospective and prospective analysis.

Main Results:

  • The DDBN model effectively identifies critical contributing factors and their complex interdependencies.
  • Probabilities of different terrorist scenarios and their impacts on maritime operations were ascertained.
  • The model demonstrated strong diagnostic and predictive capabilities in risk propagation.
  • Validation against real-world incidents confirmed the model's effectiveness.

Conclusions:

  • The developed DDBN model offers a robust framework for understanding and managing maritime terrorism risks.
  • Findings provide actionable insights for companies and government bodies to enhance maritime security.
  • The study contributes to fortifying preventive measures and emergency management strategies against maritime terrorism.