Javad Roostaei
University of North Carolina at Chapel Hill
14 Papers
9 Citations
Javad Roostaei is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Computer science & Environmental science. The author has an hindex of 6, co-authored 10 publications. Previous affiliations of Javad Roostaei include Indiana University & Wayne State University.
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Papers
Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance
TL;DR: In this article, the authors evaluated the effect of seven different feature selection methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP influent flow.
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Mixotrophic Microalgae Biofilm: A Novel Algae Cultivation Strategy for Improved Productivity and Cost-efficiency of Biofuel Feedstock Production.
TL;DR: This work proved that microalgae biofilms under mixotrophic condition exhibited significantly higher productivity and quality of biofuel feedstock, and demonstrated the applicability of integrating this novel cultivation method with wastewater for maximum efficiency.
Spatially Explicit Life Cycle Assessment: Opportunities and challenges of wastewater-based algal biofuels in the United States
Javad Roostaei,Yongli Zhang +1 more
TL;DR: In this paper, a spatially-explicit high resolution life cycle assessment (SEHR-LCA) model for wastewater-based algal biofuel production, by integrating GIS analysis, and site-specific wastewater Treatment Plants (WWTPs) data analysis, is presented.
Predicting the risk of GenX contamination in private well water using a machine-learned Bayesian network model
TL;DR: In this paper, the authors used spatial location information to link PFAS measurements from 1207 private drinking water wells around a fluorochemical manufacturing facility to a mechanistic model of PFAS air deposition and publicly available data on soil, land use, topography, weather, and proximity to multiple PFAS sources.
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Real-Time Sensor Response Characteristics of 3 Commercial Metal Oxide Sensors for Detection of BTEX and Chlorinated Aliphatic Hydrocarbon Organic Vapors
Gabriel Yurko,Javad Roostaei,Timothy M. Dittrich,Lanyu Xu,Michael Ewing,Yongli Zhang,Gina Shreve +6 more
- 27 Aug 2019
TL;DR: In this article, the authors examined the sensor response characteristics of three commercial Internet of Things compatible metal oxide (MOx) sensors in preparation for the development of field-scale sensor networks for the real-time monitoring of volatile organic compounds (VOCs) in indoor environments located in proximity to brownfield sites.
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