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Towards Better Shale Gas Production Forecasting Using Transfer Learning
Deep neural networks can generate more accurate shale gas production forecasts in counties with a limited number of sample wells by utilizing transfer learning.
Applying physics-based loss functions to neural networks for improved generalizability in mechanics problems
Physics-Informed Machine Learning (PIML) has gained momentum in the last 5 years with scientists and researchers aiming to utilize the benefits afforded by advances in machine learning, particularly in deep learning.
BIG-bench Machine Learning
Physics-informed machine learning
Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics
A random forest classifier with spectral densities of linear acceleration and angular velocity was built to classify head impact types (e. g., football, car crash, mixed martial arts).
Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation
To better design brain injury criteria, the predictive power of rotational kinematics factors, which are different in 1) the derivative order (angular velocity, angular acceleration, angular jerk), 2) the direction and 3) the power (e. g., square-rooted, squared, cubic) of the angular velocity, were analyzed based on different datasets including laboratory impacts, American football, mixed martial arts (MMA), NHTSA automobile crashworthiness tests and NASCAR crash events.
Relationship between brain injury criteria and brain strain across different types of head impacts can be different
The results show a significant difference in the relationship between BIC and brain strain across datasets, indicating the same BIC value may suggest different brain strain in different head impact types.
Deep Learning Head Model for Real-time Estimation of Entire Brain Deformation in Concussion
Results: The proposed deep learning head model can calculate the maximum principal strain for every element in the entire brain in less than 0. 001s (with an average root mean squared error of 0. 025, and with a standard deviation of 0. 002 over twenty repeats with random data partition and model initialization).
A New Open-Access Platform for Measuring and Sharing mTBI Data
Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered.
