AIMC Topic: Computer Simulation

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Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning.

IEEE transactions on medical imaging
Automated volumetric meshing of patient-specific heart geometry can help expedite various biomechanics studies, such as post-intervention stress estimation. Prior meshing techniques often neglect important modeling characteristics for successful down...

Deep residual networks for crystallography trained on synthetic data.

Acta crystallographica. Section D, Structural biology
The use of artificial intelligence to process diffraction images is challenged by the need to assemble large and precisely designed training data sets. To address this, a codebase called Resonet was developed for synthesizing diffraction data and tra...

A hybrid deep learning approach to improve real-time effluent quality prediction in wastewater treatment plant.

Water research
Wastewater treatment plant (WWTP) operation is usually intricate due to large variations in influent characteristics and nonlinear sewage treatment processes. Effective modeling of WWTP effluent water quality can provide valuable decision-making supp...

Effect of Feedback Modality on Simulated Surgical Skills Learning Using Automated Educational Systems- A Four-Arm Randomized Control Trial.

Journal of surgical education
OBJECTIVE: To explore optimal feedback methodologies to enhance trainee skill acquisition in simulated surgical bimanual skills learning during brain tumor resections.

Fixed-time synchronization of complex-valued neural networks for image protection and 3D point cloud information protection.

Neural networks : the official journal of the International Neural Network Society
This paper studies the fixed-time synchronization (FDTS) of complex-valued neural networks (CVNNs) based on quantized intermittent control (QIC) and applies it to image protection and 3D point cloud information protection. A new controller was design...

Novel criteria of sampled-data synchronization controller design for gated recurrent unit neural networks under mismatched parameters.

Neural networks : the official journal of the International Neural Network Society
Synchronization between neural networks (NNs) has been intensively investigated to analyze stability, convergence properties, neuronal behaviors and response to various inputs. However, synchronization techniques of NNs with gated recurrent units (GR...

A cellular automata model coupled with partitioning CNN-LSTM and PLUS models for urban land change simulation.

Journal of environmental management
Urbanisation is a key aspect of land use change (LUC), and accurately modelling of urban LUC is crucial for sustainable development. Cellular automata (CA) are widely used in LUC research. However, previous studies have overlooked the significant tem...

Modular hierarchical reinforcement learning for multi-destination navigation in hybrid crowds.

Neural networks : the official journal of the International Neural Network Society
Real-world robot applications usually require navigating agents to face multiple destinations. Besides, the real-world crowded environments usually contain dynamic and static crowds that implicitly interact with each other during navigation. To addre...

Structure-based approaches against COVID-19.

Journal of the Chinese Medical Association : JCMA
The coronavirus disease 2019 (COVID-19) pandemic has had a major impact on human life. This review highlights the versatile roles of both classical and modern structure-based approaches for COVID-19. X-ray crystallography, nuclear magnetic resonance ...

Simulation-based design optimization for statistical power: Utilizing machine learning.

Psychological methods
The planning of adequately powered research designs increasingly goes beyond determining a suitable sample size. More challenging scenarios demand simultaneous tuning of multiple design parameter dimensions and can only be addressed using Monte Carlo...