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0000-0002-4983-7202
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Predicting nitrification status in aerobic membrane bioreactors by interpretable machine learning models : proof of concept for advancing greywater reuse through process monitoring with cross-scenario model validation
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- Journal Article
- A1
- open access
Enhancing hydrogen sulfide control in urban sewer systems using machine learning models : development of a new predictive simulation approach by using boosting algorithm
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- Journal Article
- A1
- open access
Assessment of hydrogen peroxide, persulfate, and peroxymonosulfate as oxidizing agents in electrochemical oxidation of pyridine
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- Journal Article
- A2
- open access
Enhancing sulfate reduction efficiency in microbial electrolysis cells : the impact of mixing conditions and heavy metal concentrations on functional genes, cell activity, and community structure in sulfate-laden wastewater treatment
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Real-time diagnosis and monitoring of biofilm and corrosion layer formation on different water pipe materials using non-invasive imaging methods
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- Journal Article
- A1
- open access
A rapid and multi-endpoint ecotoxicological test using Mychonastes afer for efficient screening of metals and herbicides
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Harnessing iron materials for enhanced decolorization of azo dye wastewater : a comprehensive review
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Super-hydrophilic and positive charged pressure retarded osmosis membrane for efficient ammonia recovery and energy production
(2024) FRONTIERS IN MEMBRANE TECHNOLOGY, IWA-RMTC 2024. In Lecture notes in civil engineering (LNCE) 525. p.127-132 -
Current developments in machine learning models with boosting algorithms for the prediction of water quality
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Assessing industrial wastewater effluent toxicity using boosting algorithms in machine learning : a case study on ecotoxicity prediction and control strategy development