Microplastics as emerging pollutants have been heavily accumulated in the waste activated
sludge (WAS) during biological wastewater treatment, which showed significantly diverse …

The indirect carbon emission from electrical consumption of wastewater treatment plants
(WWTPs) accounts for large proportions of their total carbon emissions, which deserves …

The effective control of total nitrogen (ETN) and total phosphorus (ETP) in effluent is
challenging for wastewater treatment plants (WWTPs). In this work, automated machine …

Globally, over 17 million people annually die from cardiovascular diseases, with heart
disease being the leading cause of mortality in the United States. The ever-increasing …

Determining the rural domestic water consumption (RDWS, L/person-day) and rural sewage
production (RSP, L/person-day) of rural residents at the county scale can provide decision …

With most technical fields, there exists a delay between fundamental academic research and
practical industrial uptake. Whilst some sciences have robust and well-established …

Background: We aimed to develop and validate an automated machine learning (autoML)
prediction model for cardiac surgery-associated acute kidney injury (CSA-AKI). Methods …

This study evaluates the diagnostic efficacy of automated machine learning (AutoGluon) with
automated feature engineering and selection (autofeat), focusing on clinical manifestations …

Risk Management is an integral part of every project. Risk management must estimate the
risks' significance, especially in the SDLC process, and mitigate those risks. Since 2016 …

Abstract Automated Machine Learning (AutoML) is revolutionizing how businesses utilize
data, but there seems to be a lack of clarity and a holistic view regarding all its advantages …