Journal of the Air & Waste Management Association (1995)
Aug 1, 2018
UNLABELLED: This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of ide...
OBJECTIVE: Predict the number of hospitalizations for asthma and pneumonia associated with exposure to air pollutants in the city of São José dos Campos, São Paulo State.
Water science and technology : a journal of the International Association on Water Pollution Research
Apr 1, 2017
Hydrothermal liquefaction is a promising technology to convert wet biomass into bio-oil. However, post-hydrothermal liquefaction wastewater (PHWW) is also produced during the process. This wastewater contains a high concentration of organic compounds...
Journal of applied oral science : revista FOB
Jan 1, 2016
OBJECTIVES: This study evaluated the antimicrobial efficacy of ozone therapy in teeth contaminated with Pseudomonas aeruginosa, Enterococcus faecalis, and Staphylococcus aureus using a mono-species biofilm model. Parallel to this, the study aimed to ...
Water science and technology : a journal of the International Association on Water Pollution Research
Jan 1, 2016
The present study deals with use of central composite design (CCD) and artificial neural network (ANN) in modeling and optimization of reactive blue 21 (RB21) removal from aqueous media under photo-ozonation process. Four effective operational parame...
Environmental monitoring and assessment
Jul 1, 2015
The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions...