Recurrent neural networks (RNNs) have significantly advanced the field of machine learning
(ML) by enabling the effective processing of sequential data. This paper provides a …

Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …

With the innovation and advancement of artificial intelligence, more and more artificial
intelligence techniques are employed in drug research, biomedical frontier research, and …

This study presents a case focused on sustainable farming practices, specifically the
cultivation of tilapia (Mozambican and aureus species) in ponds with geothermal water. This …

Residential consumers can optimize their participation in demand response programs
(DRPs) using home energy management systems (HEMS). By automatically adjusting air …

Drones are a promising technology performing various functions, ranging from aerial
photography to emergency response, requiring swift fault diagnosis methods to sustain …

The reduction of the critical dimension (CD) usually improves the resolution of patterns and
performance of chips. In chip manufacturing, electron beam lithography (EBL) is a promising …

In recent years, the rapid development of deep learning has led to a wide range of
applications in the field of medical image classification. The variants of neural network …

This study introduces a novel deep learning-based approach for classifying poultry audio
signals, incorporating a custom Burn Layer to enhance model robustness. The methodology …

Abstract Structural Health Monitoring (SHM) systems provide extensive data on in-service
bridges, which is crucial for evaluating structural performance. However, data loss frequently …