The integration of multiomics data with detailed phenotypic insights from electronic health
records marks a paradigm shift in biomedical research, offering unparalleled holistic views …

Fault detection and localization in electrical power lines has long been a crucial challenge
for electrical engineers as it allows the detected fault to be isolated and recovered promptly …

Identifying accident patterns is one of the most vital research foci of driving analysis.
Environmental or safety applications and the growing area of fleet management all benefit …

This paper proposes a neural architecture search algorithm for obtaining an optimum
Transformer model to detect and localize different power system faults and uncertain …

Long short-term memory (LSTM), especially vanilla LSTM (VLSTM), has been widely used in
air quality prediction field. However, VLSTM has many more parameters, thereby making …

Stock forecasting has always been challenging as the stock market is affected by a
combination of factors. Temporal Convolutional Network (TCN) based on convolutional …

The energy consumption caused by battery thermal management of electric vehicles can be
reduced using predictive control. A predictive controller needs a prediction model of the …

As shipping continues to play an increasingly important role in world trade, there are
consequently a large number of ships at sea at any given time, posing a risk to maritime …

Though the forearm is the focus of the prostheses, myoelectric control with the electrodes on
the wrist is more comfortable for general consumers because of its unobtrusiveness and …

Methods A triple thresholding method was proposed to segment the WBCs; meanwhile, a
convolutional neural network (CNN)-based binary classification model that adopts transfer …