Recent advances in artificial intelligence (AI) and data analytics (DA) could provide
opportunities for the fault management and the decision-making of the urban wastewater …

Abstract Machine learning (ML), a branch of artificial intelligence (AI), has been increasingly
used in environmental engineering due to the ability to analyze complex nonlinear problems …

Abstract Study region Cork City, Ireland. Study focus Reconstruction of precipitation
timeseries is gaining increasing attention for monitoring and prediction studies. To address …

Herein, machine learning approaches were employed to predict the kinetic constant of the
organic pollutant degradation process in a peroxymonosulfate environment with a typical Fe …

As an essential environmental property, the aqueous solubility quantifies the hydrophobicity
of a compound. It could be further utilized to evaluate the ecological risk and toxicity of …

To increase the efficiency of managing backup water resources, it is critical to identify and
allocate pollution sources. Source apportionment of dissolved organic matter (DOM) was …

Since depression often results in suicidal thoughts and leaves a person severely disabled
daily, there is an elevated risk of premature mortality due to mental problems caused by …

Sentiment Analysis provides an opportunity to understand the subject (s), especially in the
digital age, due to an abundance of public data and effective algorithms. Cybersecurity is a …

Data annotation interfaces predominantly leverage ground truth labels to guide annotators
toward accurate responses. With the growing adoption of Artificial Intelligence (AI) in domain …

Nutritional epidemiology employs observational data to discover associations between diet
and disease risk. However, existing analytic methods of dietary data are often sub-optimal …