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Physical Sciences and Mathematics Commons™
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- Airborne bacteria (1)
- Biological risks (1)
- Boltzmann method (1)
- Computational pulsatile flows (1)
- GRACEnet (1)
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- Gradient boosted regression (1)
- Greenhouse gases fluxes (1)
- Hazard quotient (1)
- Health risk assessment (1)
- Indoor/outdoor bacteria (1)
- KNN regression (1)
- Paper and cardboard (1)
- Prediction (1)
- Random forest regression (1)
- Support vector regression (1)
- Volumetric lattice (1)
- Wall stresses (1)
- Waste sorting plant (1)
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Characteristics And Assessing Biological Risks Of Airborne Bacteria In Waste Sorting Plant, Abbas Norouzian Baghani, Somayeh Golbaz, Gholamreza Ebrahimzadeh, Marcelo I. Guzman, Mahdieh Delikhoon, Mehdi Jamshidi Rastani, Abdullah Barkhordari, Ramin Nabizadeh
Characteristics And Assessing Biological Risks Of Airborne Bacteria In Waste Sorting Plant, Abbas Norouzian Baghani, Somayeh Golbaz, Gholamreza Ebrahimzadeh, Marcelo I. Guzman, Mahdieh Delikhoon, Mehdi Jamshidi Rastani, Abdullah Barkhordari, Ramin Nabizadeh
Chemistry Faculty Publications
Examining the concentration and types of airborne bacteria in waste paper and cardboard sorting plants (WPCSP) is an urgent matter to inform policy makers about the health impacts on exposed workers. Herein, we collected 20 samples at 9 points of a WPCSP every 6 winter days, and found that the most abundant airborne bacteria were positively and negatively correlated to relative humidity and temperature, respectively. The most abundant airborne bacteria (in units of CFU m−3) were: Staphylococcus sp. (72.4) > Micrococcus sp. (52.2) > Bacillus sp. (30.3) > Enterococcus sp. (24.0) > Serratia marcescens (20.1) > E. coli (19.1) > Pseudomonas sp. (16.0) > Nocardia …
Volumetric Lattice Boltzmann Method For Wall Stresses Of Image-Based Pulsatile Flows, Xiaoyu Zhang, Joan Gomez-Paz, Xi Chen, James M. Mcdonough, Md Mahfuzul Islam, Yiannis Andreopoulos, Luoding Zhu, Huidan Yu
Volumetric Lattice Boltzmann Method For Wall Stresses Of Image-Based Pulsatile Flows, Xiaoyu Zhang, Joan Gomez-Paz, Xi Chen, James M. Mcdonough, Md Mahfuzul Islam, Yiannis Andreopoulos, Luoding Zhu, Huidan Yu
Mechanical Engineering Faculty Publications
Image-based computational fluid dynamics (CFD) has become a new capability for determining wall stresses of pulsatile flows. However, a computational platform that directly connects image information to pulsatile wall stresses is lacking. Prevailing methods rely on manual crafting of a hodgepodge of multidisciplinary software packages, which is usually laborious and error-prone. We present a new computational platform, to compute wall stresses in image-based pulsatile flows using the volumetric lattice Boltzmann method (VLBM). The novelty includes: (1) a unique image processing to extract flow domain and local wall normality, (2) a seamless connection between image extraction and VLBM, (3) an en-route …
Machine Learning Approach To Simulate Soil Co2 Fluxes Under Cropping Systems, Toby A. Adjuik, Sarah C. Davis
Machine Learning Approach To Simulate Soil Co2 Fluxes Under Cropping Systems, Toby A. Adjuik, Sarah C. Davis
Biosystems and Agricultural Engineering Graduate Research
With the growing number of datasets to describe greenhouse gas (GHG) emissions, there is an opportunity to develop novel predictive models that require neither the expense nor time required to make direct field measurements. This study evaluates the potential for machine learning (ML) approaches to predict soil GHG emissions without the biogeochemical expertise that is required to use many current models for simulating soil GHGs. There are ample data from field measurements now publicly available to test new modeling approaches. The objective of this paper was to develop and evaluate machine learning (ML) models using field data (soil temperature, soil …