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ISA Transactions|October 28, 2025
Interpretable distance adaptive GCN-autoencoder for soft sensor validation and remote reconstruction in urban air quality monitoring networksUsama Ali, Shahzeb Tariq, Keugtae Kim, et al.Chemosphere|June 4, 2023
Smart solutions for urban health risk assessment: A PMRoberto Chang-Silva, Shahzeb Tariq, Jorge Loy-Benitez, et al.The Science of the Total Environment|October 13, 2018
An insight into nanocellulose as soft condensed matter: Challenge and future prospective toward environmental sustainabilityKhangWei Tan, SungKu Heo, MeiLing Foo, et al.Chemosphere|October 26, 2021
Missing data imputation and sensor self-validation towards a sustainable operation of wastewater treatment plants via deep variational residual autoencodersAbdulrahman H Ba-Alawi, Jorge Loy-Benitez, SangYun Kim, et al.Journal of Hazardous Materials|August 10, 2010
Predictive monitoring and diagnosis of periodic air pollution in a subway stationYongSu Kim, MinJung Kim, JungJin Lim, et al.Environmental Technology|June 6, 2015
Assessment of environmental data quality and its effect on modelling error of full-scale plants with a closed-loop mass balancingSeungchul Lee, Sankara Rao, MinJeong Kim, et al.Ecotoxicology and Environmental Safety|November 24, 2019
Population response modeling and habitat suitability of Cobitis choii fish species in South Korea for climate change adaptationPaulina Vilela, Gabriel Jácome, Sang Youn Kim, et al.Water Science and Technology : a Journal of the International Association on Water Pollution Research|July 10, 2020
An autonomous operational trajectory searching system for an economic and environmental membrane bioreactor plant using deep reinforcement learningKiJeon Nam, SungKu Heo, Jorge Loy-Benitez, et al.Sustainable Cities and Society|June 13, 2022
A machine learning-driven spatio-temporal vulnerability appraisal based on socio-economic data for COVID-19 impact prevention in the U.S. countiesMohammad Moosazadeh, Pouya Ifaei, Amir Saman Tayerani Charmchi, et al.Environmental Science and Pollution Research International|June 13, 2014
Improving nitrogen removal using a fuzzy neural network-based control system in the anoxic/oxic processMingzhi Huang, Yongwen Ma, Jinquan Wan, et al.Pageof 76