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Advances in Intelligent Systems and Computing(5)
Quito: Universidad de las Américas, 2018(3)
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Heuristic method of evaluating accessibility of mobile in selected applications for air quality monitoring
Conference ObjectAbstract: At present, advances in technology, the use of smartphones and access to the Internet pose significaPalabras claves:accessibility, Air, Applications, Evaluation, Heuristic method, Mobile, Monitoring, Quality, WCAG 2.1Autores:Jorge Luis Pérez Medina, Luis Salvador-Ullauri, Patricia Acosta-Vargas, Rasa Zalakeviciute, Wilmar HernandezFuentes:scopusEvaluation of smart phone open source applications for air pollution
Conference ObjectAbstract: Global industrialization, urbanization and technological development have been rapidly changing thePalabras claves:air pollution, Evaluation, Mobile ApplicationsAutores:Jorge Luis Pérez Medina, Katiuska Alexandrino, Patricia Acosta-Vargas, Rasa Zalakeviciute, Wilmar HernandezFuentes:googlescopusEvaluation 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: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:googlescopusEddy covariance flux measurements of pollutant gases in urban Mexico City
ArticleAbstract: Eddy covariance (EC) flux measurements of the atmosphere/surface exchange of gases over an urban arePalabras claves:Autores:Allwine E., Coons T., Foster W., Francisco J.López Hernández, Jobson B.T., Lamb B.K., Molina L.T., Pressley S.N., Ramos R., Rasa Zalakeviciute, Velasco E., Westberg H.Fuentes:scopusEditorial: Statistical Learning for Predicting Air Quality
OtherAbstract:Palabras claves:chemical transport model (CTM), deep learning, Forecast, Machine learning, urban pollutionAutores:Rasa Zalakeviciute, Rybarczyk Y.P.Fuentes:googlescopusEfecto de los cambios de la cobertura forestal en la calidad del aire de la ciudad de Quito
Bachelor ThesisAbstract: Efecto de los cambios de la cobertura forestal en la calidad del aire de la ciudad de Quito La presePalabras claves:Calidad Del Aire, Contaminación Ambiental, CONTAMINACION DEL AIRE, DEFORESTACIÓN, RECURSOS FORESTALESAutores:Daniela Andrea Villacís Valle, Rasa ZalakeviciuteFuentes:rraaeContrasted 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:scopusA Traffic-based method to predict 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:scopusA global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions
ArticleAbstract: This global study, which has been coordinated by the World Meteorological Organization Global AtmospPalabras claves:Carbon monoxide, covid-19, Nitrogen dioxide, Ozone, particulate matter, sulphur dioxideAutores:Anand V., Andrade M.d.F., Arbilla G., Badali K., Baklanov A., Beig G., Belalcazar L.C., Bolignano A., Brimblecombe P., Camacho P., Carmichael G., Casallas A., Charland J.P., Choi J., Chourdakis E., Coll I., Collins M., Cyrys J., da Silva C.M., Di Giosa A.D., Di Leo A., Ferro C., Finardi S., Garland R.M., Gavidia-Calderon M., Gayen A., Ginzburg A., Godefroy F., Gonzalez Y.A., Guevara-Luna M., Haque S.M., Havenga H., Herod D., Hõrrak U., Hussein T., Ibarra S., Jaimes M., Kaasik M., Khaiwal R., Kim J., Kong S., Kousa A., Kukkonen J., Kulmala M., Kuula J., La Violette N., Lanzani G., Liu X., MacDougall S., Manseau P.M., Marchegiani G., Massagué J., McDonald B., Mishra S.V., Molina L.T., Mooibroek D., Mor S., Moussiopoulos N., Murena F., Niemi J.V., Noe S., Nogueira T., Norman M., Pavlovic R., Pérez-Camaño J.L., Petäjä T., Peuch V.H., Piketh S., Querol X., Rasa Zalakeviciute, Rathod A., Reid K., Ren L., Retama A., Rivera O., Rojas N.Y., Rojas-Quincho J.P., San José R., Sánchez-Ccoyllo O., Seguel R.J., Sillanpää S., Singh V., Sokhi R.S., Su Y., Tapper N., Tarasova O., Targino A.C., Terrazas A., Timonen H., Toscano D., Tsegas G., Velders G.J.M., Vlachokostas C., von Schneidemesser E., VPM R., Yadav R., Zavala M.Fuentes:googlescopus