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Computer Simulation

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Uncovering water conservation patterns in semi-arid regions through hydrological simulation and deep learning.

PloS one
Under the increasing pressure of global climate change, water conservation (WC) in semi-arid regions is experiencing unprecedented levels of stress. WC involves complex, nonlinear interactions among ecosystem components like vegetation, soil structur...

Leveraging Extended Windows in End-to-End Deep Learning for Improved Continuous Myoelectric Locomotion Prediction.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Current surface electromyography (sEMG) methods for locomotion mode prediction face limitations in anticipatory capability due to computation delays and constrained window lengths typically below 500 ms-a practice historically tied to stationarity re...

Transcranial adaptive aberration correction using deep learning for phased-array ultrasound therapy.

Ultrasonics
This study aims to explore the feasibility of a deep learning approach to correct the distortion caused by the skull, thereby developing a transcranial adaptive focusing method for safe ultrasonic treatment in opening of the blood-brain barrier (BBB)...

A deep learning approach to multi-fiber parameter estimation and uncertainty quantification in diffusion MRI.

Medical image analysis
Diffusion MRI (dMRI) is the primary imaging modality used to study brain microstructure in vivo. Reliable and computationally efficient parameter inference for common dMRI biophysical models is a challenging inverse problem, due to factors such as va...

A novel one-layer neural network for solving quadratic programming problems.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a novel one-layer neural network to solve quadratic programming problems in real time by using a control parameter and transforming the optimality conditions into a system of projection equations. The proposed network includes two...

EBM-WGF: Training energy-based models with Wasserstein gradient flow.

Neural networks : the official journal of the International Neural Network Society
Energy-based models (EBMs) show their efficiency in density estimation. However, MCMC sampling in traditional EBMs suffers from expensive computation. Although EBMs with minimax game avoid the above drawback, the energy estimation and generator's opt...

Turbulence control in memristive neural network via adaptive magnetic flux based on DLS-ADMM technique.

Neural networks : the official journal of the International Neural Network Society
High-voltage defibrillation for eliminating cardiac spiral waves has significant side effects, necessitating the pursuit of low-energy alternatives for a long time. Adaptive optimization techniques and machine learning methods provide promising solut...

Mechanical Structure Design and Motion Simulation Analysis of a Lower Limb Exoskeleton Rehabilitation Robot Based on Human-Machine Integration.

Sensors (Basel, Switzerland)
Population aging is an inevitable trend in contemporary society, and the application of technologies such as human-machine interaction, assistive healthcare, and robotics in daily service sectors continues to increase. The lower limb exoskeleton reha...

Distributed Synaptic Connection Strength Changes Dynamics in a Population Firing Rate Model in Response to Continuous External Stimuli.

Neural computation
Neural network complexity allows for diverse neuronal population dynamics and realizes higherorder brain functions such as cognition and memory. Complexity is enhanced through chemical synapses with exponentially decaying conductance and greater vari...

The value of simulation testing for the evaluation of ambient digital scribes: a case report.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: The objective of this work is to demonstrate the value of simulation testing for rapidly evaluating artificial intelligence (AI) products.