Lucio Naranjo José Francisco
Departamento de Informática y Ciencias de la Computación
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Oficina: Decanato
Ext: 4700
iD orcid.org/0000-0003-2578-1950
Estudios
  1. Ingeniero en Sistemas y Computación en Pontificia Universidad Católica del Ecuador
  2. Mestre em Modelagem Computacional, Master in Sciences (M.Sc.) en la Universidade do Estado do Rio de Janeiro 
  3. Doutor em Modelagem Computacional, Doctor in Sciences (D.Sc.) en la Universidade do Estado do Rio de Janeiro
Líneas de investigación
  1. DICC-A1-L1 Inteligencia Artificial
  2. DICC-A1-L2 Machine learning
  3. DICC-A1-L3 Modelado y simulación
Publicaciones
  1. Tinizaray, P., Aguilar, W., & Lucio, J. (2022). Fast segmentation of point clouds using a convolutional neural network for helping visually impaired people find the closest traversable region. Inteligencia Artificial, An international open access journal., 25(70). doi: https://doi.org/10.4114/intartif.vol25iss70pp50-63 
  2. Bravo-Moncayo, L., Mosquera, R., Puyana-Romero, V., Romero, M., Lucio-Naranjo, J., & Suárez, E. (2023). Traffic noise and property values: an instrumental variable strategy for hedonic valuation. Journal of Environmental Planning and Management, 2556-2575. doi: https://doi.org/10.1080/09640568.2022.2079079 
  3. Bravo-Moncayo, L., Chávez, M., Puyana, V., Lucio-Naranjo, J., Garzón, C., & Pavón-García, I. (2019). A cost-effective approach to the evaluation of traffic noise exposure in the city of Quito, Ecuador. Case Studies on Transport Policy, 128–137. https://doi.org/10.1016/j.cstp.2018.12.006
  4. Bravo-Moncayo, L., Lucio Naranjo, J., Pavón García, I., & Mosquera, R. (2017). Neural based contingent valuation of road traffic noise. Transportation Research Part D: Transport and Environment, 26–39. https://doi.org/10.1016/j.trd.2016.10.020
  5. Bravo-Moncayo, L., Lucio-Naranjo, J., Chávez, M., Pavón-García, I., & Garzón, C. (2019). A machine learning approach for traffic-noise annoyance assessment. Applied Acoustics, 262–270. https://doi.org/10.1016/j.apacoust.2019.07.010
  6. Bravo-Moncayo, L., Mosquera, R., Puyana-Romero, V., Romero, M., Lucio-Naranjo, J., & Suárez, E. (2022). Traffic noise and property values: an instrumental variable strategy for hedonic valuation. Journal of Environmental Planning and Management. https://doi.org/10.1080/09640568.2022.2079079
  7. Bravo-Moncayo, L., Pavón-García, I., Lucio-Naranjo, J., & Mosquera, R. (2017). Contingent valuation of road traffic noise: A case study in the urban area of Quito, Ecuador. Case Studies on Transport Policy, 722–730. https://doi.org/10.1016/j.cstp.2017.08.003
  8. Lucio-Naranjo, J., Torres, J., & Tenenbaum, R. A. (2017). Optimum ANN architecture for HRIR interpolation. En Horizons in Computer Science Research (págs. 121–143).
  9. Sanaguano, D., Lucio-Naranjo, J., & Tenenbaum, R. (2020). A Conceptual Model for real-time Binaural-Room Impulse Responses generation using ANNs in Virtual Environments: State of the Art. Proceedings - 2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020, (págs. 572–578).
  10. Tenenbaum, R. A., Melo, V., Lucio-Naranjo, J., & Santos, L. (2015). Articulation index used as a metrics to validate acoustic virtual reality. 22nd International Congress on Sound and Vibration, ICSV 2015.
  11. Tenenbaum, R., Melo, V., & Lucio-Naranjo, J. (2014). Virtual Reality: A New Approach To Validate Computer Modeling Auralizations By Using Articulation Indexes. En Virtual Reality: Technologies, Medical Applications and Challenges (págs. 55–71).

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