ORCID Profile
0000-0002-1953-1456
Current Organisation
Duy Tan University
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Publisher: Elsevier BV
Date: 06-2019
DOI: 10.1016/J.BIORTECH.2019.02.117
Abstract: In this study, three semi-pilot scale systems (vertical flow constructed wetland, multi-soil layering, and integrated hybrid systems) for treating real rice noodle wastewater were operated parallelly for the first time in a tropical climate at a loading rate of 50 L/(m
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier BV
Date: 10-2021
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier BV
Date: 10-2020
Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier BV
Date: 08-2021
Publisher: Elsevier BV
Date: 12-2020
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 04-2021
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 08-2022
DOI: 10.1016/J.SCITOTENV.2022.154930
Abstract: Water pollution generated from intensive anthropogenic activities has emerged as a critical issue concerning ecosystem balance and livelihoods worldwide. Although optimizing wastewater treatment efficiency is widely regarded as the foremost step to minimize pollutants released into the environment, this widespread application has encountered two major problems: firstly, the significant variation of influent wastewater constituents secondly, complex treatment processes within wastewater treatment plants (WWTPs). Based on the data collected hourly using real-time sensors in three different full-scale WWTPs (24 h × 365 days × 3 WWTPs × 10 wastewater parameters), this work introduced the potential application of Machine Learning (ML) to predict wastewater quality. In this work, six different ML algorithms were examined and compared, varying from shallow to deep learning architectures including Seasonal Autoregressive Integrated Moving Average (SARIMAX), Random Forest (RF), Support Vector Machine (SVM), Gradient Tree Boosting (GTB), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Long Short-Term Memory (LSTM). These models were developed to detect total phosphorus in the outlet (Outlet-TP), which served as an output variable due to the rising concerns about the eutrophication problem. Irrespective of WWTPs, SARIMAX consistently demonstrated the best performance for regression estimation as evidenced by the lowest values of Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and the highest coefficient of determination (R
Publisher: Springer Science and Business Media LLC
Date: 17-10-2020
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 10-2020
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 04-2020
Publisher: Elsevier BV
Date: 12-2022
DOI: 10.1016/J.SCITOTENV.2022.158203
Abstract: Sulfur (S) is a crucial component in the environment and living organisms. This work is the first attempt to provide an overview and critical discussion on the roles, mechanisms, and environmental applications of sulfur-oxidizing bacteria (SOB). The findings reveal that key enzymes of SOB embarked on oxidation of sulfide, sulfite, thiosulfate, and elemental S. Conversion of reduced S compounds was oxidatively catalyzed by various enzymes (e.g. sulfide: quinone oxidoreductase, flavocytochrome c-sulfide dehydrogenase, dissimilatory sulfite reductase, heterodisulfide reductase-like proteins). Environmental applications of SOB discussed include detoxifying hydrogen sulfide, soil bioremediation, and wastewater treatment. SOB producing S
No related grants have been discovered for Xuan Cuong Nguyen.