Accurate air quality forecasting is critical for systematic pollution control as well as public
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …

Deep learning has remarkably impacted several different scientific disciplines over the last
few years. For example, in image processing and analysis, deep learning algorithms were …

Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich
science. Protein sequences and structures are comprehensively catalogued in online …

Objective Easy access bio-signals are useful to alleviate the shortcomings and difficulties of
cuff-based and invasive blood pressure (BP) measuring techniques. This study proposes a …

In this research, the effect of CO 2 (0%, 20%, 60%, and 100%) on the spoilage potential of
Shewanella putrefaciens (S. putrefaciens) during 4° C cold storage was evaluated. Results …

The recent emergence of deep learning to characterize complex patterns of protein big data
reveals its potential to address the classic challenges in the field of protein data mining …

The study aimed to assess the impact of different packaging methods on the moisture state,
quality, and microbial composition of grouper fillets. The grouper fillets were packaged …

This study presents a comprehensive and systematic review of the data mining (DM)
techniques used to predict employee turnover in the past decade. A total of 36 relevant peer …

Proteins are some of the most fascinating and challenging molecules in the universe, and
they pose a big challenge for artificial intelligence. The implementation of machine …

Predicting protein function and structure from sequence remains an unsolved problem in
bioinformatics. The best performing methods rely heavily on evolutionary information from …