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Applied Sciences (Switzerland)(2)
Frontiers in Big Data(2)
Sustainability (Switzerland)(2)
2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016(1)
2019 6th International Conference on eDemocracy and eGovernment, ICEDEG 2019(1)
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Otros problemas y servicios sociales(9)
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Assessing the COVID-19 Impact on Air Quality: A Machine Learning Approach
ArticleAbstract: The worldwide research initiatives on Corona Virus disease 2019 lockdown effect on air quality agreePalabras claves:air pollution, covid-19, quarantine measures, urban air qualityAutores:Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopusBiomonitoring of metal levels in urban areas with different vehicular traffic intensity by using Araucaria heterophylla needles
ArticleAbstract: For the first time, Araucaria heterophylla needles were used as a biomonitor to assess the concentraPalabras claves:air pollution, Andean, biomonitor, conifer, TrafficAutores:Fausto Viteri, Juan Ernesto Guevara Andino, Katiuska Alexandrino, Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopusA Traffic-based method to pbkp_redict and map urban air quality
ArticleAbstract: As global urbanization, industrialization, and motorization keep worsening air quality, a continuousPalabras claves:Machine-learning-based models, Pollution mapping, urban air qualityAutores:Adrian Buenaño, Marco G. Bastidas, Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:scopusContrasted effects of relative humidity and precipitation on urban PM<inf>2.5</inf> pollution in high elevation urban areas
ArticleAbstract: Levels of urban pollution can be influenced largely by meteorological conditions and the topographyPalabras claves:Combustion efficiency, precipitation, Relative humidity, Urban PM 2.5Autores:Jesús López-Villada, Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:scopusDeep Learning Approach for Assessing Air Quality During COVID-19 Lockdown in Quito
ArticleAbstract: Weather Normalized Models (WNMs) are modeling methods used for assessing air contaminants under a buPalabras claves:air pollution, covid-19, data-driven modeling and optimization, deep learning - artificial neural network (DL-ANN), Machine learningAutores:Chau P.N., Rasa Zalakeviciute, Rybarczyk Y.P., Thomas I.Fuentes:googlescopusAirQ2: Quito air quality monitoring and visualization tool
Conference ObjectAbstract: This work describes the AirQ2: Quito Air Quality Monitoring and Visualization Tool, which is a web aPalabras claves:data visualization, Pollution heatmap, R-Shiny, Temporal profilesAutores:Mario González-Rodríguez, Martín Almeida, Rasa Zalakeviciute, Rodrigo Narango, Rybarczyk Y.P.Fuentes:scopusEvaluation of the usability of a mobile application for public air quality information
Conference ObjectAbstract: This contribution summarizes the results achieved from a summative usability study considering the ePalabras claves:Air pollution mobile application, User experience, User Interfaces, user studyAutores:Jorge Luis Pérez Medina, Mario González-Rodríguez, Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:scopusEditorial: Statistical Learning for Pbkp_redicting Air Quality
OtherAbstract:Palabras claves:chemical transport model (CTM), deep learning, Forecast, Machine learning, urban pollutionAutores:Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopusMachine learning approach to forecasting urban pollution
Conference ObjectAbstract: This work addresses the question of how to pbkp_redict fine particulate matter given a combination oPalabras claves:decision tree, fine particulate matter, Machine learning, Pbkp_redictive model, urban pollutionAutores:Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopusMachine learning approaches for outdoor air quality modelling: A systematic review
ReviewAbstract: Current studies show that traditional deterministic models tend to struggle to capture the non-lineaPalabras claves:Atmospheric pollution, Data Mining, Multiple correspondence analysis, pbkp_redictive modelsAutores:Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopus