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Applied Sciences (Switzerland)(2)
Frontiers in Big Data(2)
2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016(1)
2018 IEEE (SMC) International Conference on Innovations in Intelligent Systems and Applications, INISTA 2018(1)
Geophysical Research Letters(1)
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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:googlescopusDeep 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:googlescopusGradient boosting machine to assess the public protest impact on urban air quality
ArticleAbstract: Political and economic protests build-up due to the financial uncertainty and inequality spreading tPalabras claves:Machine learning, protests, urban pollutionAutores:DANILO MEJIA CORONEL, Katiuska Alexandrino, Marco G. Bastidas, Rasa Zalakeviciute, Rybarczyk Y.P., Santiago Bonilla-Bedoya, Valeria DíazFuentes:scopusEvaluation of Self-Rehabilitation Movements by Hidden Markov Model
Conference ObjectAbstract: This study aims to propose a statistical model to automatically assess the correctness of rehabilitaPalabras claves:Decision Support Systems, Health computing, Machine learning, movement recognition, Probabilistic modelAutores:Jan Kleine Deters, Rybarczyk Y.P.Fuentes:scopusENSEMBLE DEEP LEARNING FOR CLASSIFICATION OF POLLUTION PEAKS
Conference ObjectAbstract: The concentration peaks of atmospheric pollutants are the most challenging and important phenomena iPalabras claves:air pollution forecasting, data-driven modelling, deep learning, Machine learningAutores:Chau P.N., Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopusEditorial: 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:googlescopusHidden Markov model approach for the assessment of tele-rehabilitation exercises
ArticleAbstract: Two mandatory conditions in the development of tele-rehabilitation platforms are: (i) being based onPalabras claves:Hidden markov models, Real-time motion assessment, Rehabilitation exercisesAutores:Jan Kleine Deters, Rybarczyk Y.P.Fuentes:scopusMachine 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:googlescopusModeling PM<inf>2.5</inf> Urban Pollution Using Machine Learning and Selected Meteorological Parameters
ArticleAbstract: Outdoor air pollution costs millions of premature deaths annually, mostly due to anthropogenic finePalabras claves:Autores:Jan Kleine Deters, Mario González-Rodríguez, Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopus