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

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

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...

Distributed Loads

Distributed Loads

Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...

Multimachine Stability

Multimachine Stability

Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:

Principle of Virtual Work: Problem Solving

Principle of Virtual Work: Problem Solving

The principle of virtual work is an essential concept in the field of mechanics and engineering. This is used to solve problems related to the equilibrium of a structure or system. It is based on the assumption that if a system is in equilibrium, the work done by all the forces during a virtual displacement is zero. This principle is applied by considering virtual displacements of the system and the corresponding work done by internal and external forces.
To apply the principle of virtual work,...

Virtual Work for a System of Connected Rigid Bodies

Virtual Work for a System of Connected Rigid Bodies

Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...

You might also read

Related Articles

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

Sort by

Same author

The Prognostic Role of Residual SYNTAX Score in the Recovery of Erectile Function Following Myocardial Infarction Treated with Percutaneous Coronary Intervention.

Andrology·2026

Same author

From body mass index to waist circumference: a paradigm shift in assessing access complexity in percutaneous nephrolithotomy- comparative study.

Urolithiasis·2025

Same author

Formation of Colchicine-incorporated Hybrid Nanoflower With an Intrinsic Peroxidase-Mimic and Enhanced Antimicrobial Activities.

Chemistry & biodiversity·2025

Same author

Is there a safe no radiation option for endoscopic kidney stone treatment in children? multicenter results of modified retrograde intrarenal surgery without fluoroscopy in pediatric patients.

Urolithiasis·2025

Same author

Correction: Changes in blood gas in supine and prone positions in percutaneous stone surgery: does position have any advantage for hemodynamics?

Urolithiasis·2024

Same author

Acute limb ischemia in a COVID-19 patient.

Thrombosis update·2024

Search research articles

Related Experiment Video

Updated: Jun 19, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

The virtual marathon: parallel computing supports crowd simulations.

Erdal Yilmaz¹, Veysi Isler, Yasemin Yardimci Cetin

¹Informatics Institute, Middle East Technical University. erdal@ii.metu.edu.tr

IEEE Computer Graphics and Applications

|October 6, 2009

Summary

This summary is machine-generated.

Researchers simulated a marathon with over a million participants using parallel computing. Fuzzy logic on a graphics processing unit (GPU) enabled real-time simulation of participant behavior for realistic urban modeling.

More Related Videos

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Related Experiment Videos

Last Updated: Jun 19, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Area of Science:

Computational modeling
Urban dynamics
Artificial intelligence

Background:

Realistic urban models require accurate simulation of dynamic entities like pedestrians and vehicles.
Previous models often lacked the computational power to handle large-scale, complex scenarios.

Purpose of the Study:

To develop a realistic urban simulation incorporating a large number of dynamic entities.
To demonstrate the feasibility of simulating complex crowd behavior in real-time.

Main Methods:

Utilized a parallel-computing architecture for high-performance simulation.
Employed fuzzy logic algorithms executed on a graphics processing unit (GPU).
Simulated a marathon event with over one million participants.

Main Results:

Successfully modeled the behavior of a million participants in a marathon simulation.
Achieved real-time performance for millions of inferences using GPU acceleration.
Demonstrated the effectiveness of fuzzy logic in capturing complex participant dynamics.

Conclusions:

Parallel computing and GPU-accelerated fuzzy logic are effective for large-scale urban simulations.
This approach enhances the realism of urban models by accurately representing dynamic entities.
The methodology provides a scalable solution for simulating complex crowd behaviors.