The output of AraBERT is subsequently fed into a Long Short-Term Memory (LSTM) model, followed by feedforward neural networks and an output layer. AraBERT is used to capture rich contextual ...

Vikki Velasquez is a researcher and writer who has managed, coordinated, and directed various community and nonprofit organizations. She has conducted in-depth research on social and economic ...

The PK data focused on capturing the temporal profile of Ropeg plasma concentrations after administration, providing a dataset for subsequent analyses. A population PK (PopPK) model was used to ...

Thus, we propose end-to-end models combining Functional Brain Network (FBN) and Siamese Long Short-Term Memory model (Siam-LSTM) and apply them to a Virtual Reality Motion Sickness (VRMS) recognition ...

To address these problems, we propose the Improved AutoEncoder with LSTM module and Kullback-Leibler divergence (IAE-LSTM-KL) model in this paper. An LSTM network is added after the encoder to ...

Long short-term memory (LSTM) is a type of recurrent neural network (RNN) that can handle sequential data, such as time series, text, or speech. LSTM models are widely used for forecasting tasks ...

The aim of this project is to develop a machine learning model that can accurately classify whether an individual is experiencing stress based on their textual data.