AIMC Topic: Computer Simulation

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Learning reduced-order models for cardiovascular simulations with graph neural networks.

Computers in biology and medicine
Reduced-order models based on physics are a popular choice in cardiovascular modeling due to their efficiency, but they may experience loss in accuracy when working with anatomies that contain numerous junctions or pathological conditions. We develop...

A spatio-temporal deep learning approach to simulating conflict risk propagation on freeways with trajectory data.

Accident; analysis and prevention
On freeways, sudden deceleration or lane-changing by vehicles can trigger conflict risk that propagates backward in a specific pattern. Simulating this pattern of conflict risk propagation can not only help prevent crashes but is also vital for the d...

Environmental force sensing helps robots traverse cluttered large obstacles.

Bioinspiration & biomimetics
Robots can traverse sparse obstacles by sensing environmental geometry and avoiding contact with obstacles. However, for search and rescue in rubble, environmental monitoring through dense vegetation, and planetary exploration over Martian and lunar ...

Intelligent diagnosis and prediction of turbine digital electro-hydraulic control system faults: Design and experimentation.

PloS one
A physical modeling approach was adopted to build a Digital Electro-Hydraulic Control (DEH) system simulation model and the fault models using the SIMULINK tool. This research combined the advantages of the gray system and neural network to build a m...

Deep learning precipitation prediction models combined with feature analysis.

Environmental science and pollution research international
Precise rainfall forecasting modeling assumes a pivotal role in water resource planning and management. Conducting a comprehensive analysis of the rainfall time series and making appropriate adjustments to the forecast model settings based on the cha...

The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease.

Med (New York, N.Y.)
BACKGROUND: Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical proc...

Enabling AI in synthetic biology through Construction File specification.

PloS one
The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects...

Neurodynamic approaches for multi-agent distributed optimization.

Neural networks : the official journal of the International Neural Network Society
This paper considers a class of multi-agent distributed convex optimization with a common set of constraints and provides several continuous-time neurodynamic approaches. In problem transformation, l and l penalty methods are used respectively to cas...

Sample size and predictive performance of machine learning methods with survival data: A simulation study.

Statistics in medicine
Prediction models are increasingly developed and used in diagnostic and prognostic studies, where the use of machine learning (ML) methods is becoming more and more popular over traditional regression techniques. For survival outcomes the Cox proport...

SIMPLEX: Multiple phase-cycled bSSFP quantitative magnetization transfer imaging with physic-guided simulation learning of neural network.

NeuroImage
Most quantitative magnetization transfer (qMT) imaging methods require acquiring additional quantitative maps (such as T) for data fitting. A method based on multiple phase-cycled bSSFP was recently proposed to enable high-resolution 3D qMT imaging b...