AIMC Topic: Computer Simulation

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Comparing machine learning methods for predicting land development intensity.

PloS one
Land development intensity is a comprehensive indicator to measure the degree of saving and intensive land construction and economic production activities. It is also the result of the joint action of natural, social, economic, and ecological element...

The emerging role of artificial intelligence and digital twins in pre-clinical molecular imaging.

Nuclear medicine and biology
INTRODUCTION: Pre-clinical molecular imaging, particularly with mice, is an essential part of drug and radiopharmaceutical development. There remain ethical challenges to reduce, refine and replace animal imaging where possible.

High-efficient Bloch simulation of magnetic resonance imaging sequences based on deep learning.

Physics in medicine and biology
. Bloch simulation constitutes an essential part of magnetic resonance imaging (MRI) development. However, even with the graphics processing unit (GPU) acceleration, the heavy computational load remains a major challenge, especially in large-scale, h...

A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status.

CPT: pharmacometrics & systems pharmacology
Oncology treatments require continuous individual adjustment based on the measurement of multiple clinical parameters. Prediction tools exploiting the patterns present in the clinical data could be used to assist decision making and ease the burden a...

CSI-Based Human Activity Recognition Using Multi-Input Multi-Output Autoencoder and Fine-Tuning.

Sensors (Basel, Switzerland)
Wi-Fi-based human activity recognition (HAR) has gained considerable attention recently due to its ease of use and the availability of its infrastructures and sensors. Channel state information (CSI) captures how Wi-Fi signals are transmitted through...

Modular robot interface for a smart operating theater.

Journal of robotic surgery
This paper discusses the architecture and implementation of a modular component of the smart operating theater digital twin, designed to control robotic equipment-the robot interface module. This interface is designed to ensure equipment operation bo...

Fixed/prescribed-time synchronization of BAM memristive neural networks with time-varying delays via convex analysis.

Neural networks : the official journal of the International Neural Network Society
The synchronization problem of bidirectional associative memory memristive neural networks (BAMMNNs) with time-varying delays plays an essential role in the implementation and application of neural networks. Firstly, under the framework of the Filipp...

A method for real-time mechanical characterisation of microcapsules.

Biomechanics and modeling in mechanobiology
Characterising the mechanical properties of flowing microcapsules is important from both fundamental and applied points of view. In the present study, we develop a novel multilayer perceptron (MLP)-based machine learning (ML) approach, for real-time ...

A myoelectric digital twin for fast and realistic modelling in deep learning.

Nature communications
Muscle electrophysiology has emerged as a powerful tool to drive human machine interfaces, with many new recent applications outside the traditional clinical domains, such as robotics and virtual reality. However, more sophisticated, functional, and ...

CHARLES: A C++ fixed-point library for Photonic-Aware Neural Networks.

Neural networks : the official journal of the International Neural Network Society
In this paper we present CHARLES (C++ pHotonic Aware neuRaL nEtworkS), a C++ library aimed at providing a flexible tool to simulate the behavior of Photonic-Aware Neural Network (PANN). PANNs are neural network architectures aware of the constraints ...