AI deciphers long-range DNA signals behind RNA splicing

Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...
GitHub

MATLAB and Simulink Challenge Projects

Contribute to the progress of engineering and science by solving key industry challenges! Are you looking for a design or research project idea with real industry relevance and societal impact?
Frontiers

Prediction and prevention of concrete chloride penetration: machine learning and MICP techniques

The chloride migration coefficient (CMC) of concrete is crucial for evaluating its durability. This study develops ensemble models to predict the CMC of concrete, addressing the limitations of ...
IEEE

Research on Power Load Forecasting Based on VMD-LSTM

Abstract: In order to more effectively exploit the latent features and hidden information in power load data, a combined prediction model based on variational modal decomposition (VMD) and long ...
Frontiers

Grey Wolf Optimization–Based Deep Echo State Network for Time Series Prediction

The Echo State Network (ESN) is a unique type of recurrent neural network. It is built atop a reservoir, which is a sparse, random, and enormous hidden infrastructure. ESN has been successful in ...
InfoWorld

The best open source software of 2021

Money may not grow on trees, but it does grow in GitHub repos. Open source projects produce the most valuable and sophisticated software on the planet, free for the taking, dramatically lowering the ...
C&EN

Machine Learning Models for Equivalent Circulating Density Prediction from Drilling Data

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Equivalent circulating density (ECD) is an important parameter ...
GitHub

Explainable AI: interpreting the classification performed by deep learning with LIME

This demo shows how to interpret the classification by CNN using LIME (Local Interpretable Model-agnostic Explanations) [1]. This demo was created based on [1], but the implementation might be a ...
PNAS

Deep learning predicts path-dependent plasticity

We show that material plasticity can be precisely and efficiently predicted by deep-learning methods. This approach is fundamentally different from the century-old theory of continuum plasticity ...