Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES
ilustraciones, diagramas
- Autores:
-
Moreno Roballo, Nestor Ivan
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/85024
- Palabra clave:
- 520 - Astronomía y ciencias afines
Actividad solar
Radiación solar
Solar activity
Solar radiation
Sol calmo, Sol activo, ciclo solar, manchas solares, fulguracion solar, Satelite GOES, Satelite SORCE, aprendizaje automatico, correlacion de datos.
Sol calmo
Sol activo
Ciclo solar
Manchas solares
Fulguracion solar
Satelite GOES
Satelite SORCE
Aprendizaje automatico
Correlacion de datos
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
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| dc.title.spa.fl_str_mv |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES |
| dc.title.translated.eng.fl_str_mv |
Multispectral radiation study solar included in the period 2003 – 2020 according to satellite data SORCE and GOES |
| title |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES |
| spellingShingle |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES 520 - Astronomía y ciencias afines Actividad solar Radiación solar Solar activity Solar radiation Sol calmo, Sol activo, ciclo solar, manchas solares, fulguracion solar, Satelite GOES, Satelite SORCE, aprendizaje automatico, correlacion de datos. Sol calmo Sol activo Ciclo solar Manchas solares Fulguracion solar Satelite GOES Satelite SORCE Aprendizaje automatico Correlacion de datos |
| title_short |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES |
| title_full |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES |
| title_fullStr |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES |
| title_full_unstemmed |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES |
| title_sort |
Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOES |
| dc.creator.fl_str_mv |
Moreno Roballo, Nestor Ivan |
| dc.contributor.advisor.none.fl_str_mv |
Calvo Mozo, Benjamin |
| dc.contributor.author.none.fl_str_mv |
Moreno Roballo, Nestor Ivan |
| dc.contributor.educationalvalidator.none.fl_str_mv |
Martinez Oliveros Juan Carlos |
| dc.contributor.researchgroup.spa.fl_str_mv |
Astronomía, Astrofísica y Cosmologia |
| dc.subject.ddc.spa.fl_str_mv |
520 - Astronomía y ciencias afines |
| topic |
520 - Astronomía y ciencias afines Actividad solar Radiación solar Solar activity Solar radiation Sol calmo, Sol activo, ciclo solar, manchas solares, fulguracion solar, Satelite GOES, Satelite SORCE, aprendizaje automatico, correlacion de datos. Sol calmo Sol activo Ciclo solar Manchas solares Fulguracion solar Satelite GOES Satelite SORCE Aprendizaje automatico Correlacion de datos |
| dc.subject.armarc.none.fl_str_mv |
Actividad solar |
| dc.subject.lemb.spa.fl_str_mv |
Radiación solar Solar activity |
| dc.subject.lemb.eng.fl_str_mv |
Solar radiation |
| dc.subject.proposal.spa.fl_str_mv |
Sol calmo, Sol activo, ciclo solar, manchas solares, fulguracion solar, Satelite GOES, Satelite SORCE, aprendizaje automatico, correlacion de datos. Sol calmo Sol activo Ciclo solar Manchas solares Fulguracion solar Satelite GOES Satelite SORCE Aprendizaje automatico Correlacion de datos |
| description |
ilustraciones, diagramas |
| publishDate |
2023 |
| dc.date.accessioned.none.fl_str_mv |
2023-11-30T14:02:50Z |
| dc.date.available.none.fl_str_mv |
2023-11-30T14:02:50Z |
| dc.date.issued.none.fl_str_mv |
2023-11-29 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
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info:eu-repo/semantics/masterThesis |
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info:eu-repo/semantics/acceptedVersion |
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Text |
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http://purl.org/redcol/resource_type/TM |
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acceptedVersion |
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https://repositorio.unal.edu.co/handle/unal/85024 |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
| dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
| url |
https://repositorio.unal.edu.co/handle/unal/85024 https://repositorio.unal.edu.co/ |
| identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.relation.references.spa.fl_str_mv |
Abhyankar, K. D. (mar. de 1977). “A Survey of the Solar Atmospheric Models”. En: Bulletin of the Astronomical Society of India 5, pag. 40. Ali, Aatiya et al. (mar. de 2023). “Predicting Solar Proton Events of Solar Cycles 22-24 using GOES Proton & Soft X-Ray Flux Statistics”. En: arXiv e-prints, arXiv:2303.05446, arXiv:2303.05446. doi: 10.48550/arXiv.2303.05446. arXiv: 2303.05446 [astro-ph.SR]. Athay, R. Grant (1976). “Introduction”. En: The Solar Chromosphere and Corona: Quiet Sun. Dordrecht: Springer Netherlands, pags. 1-30. isbn: 978-94-010-1715-2. doi: 10.1007/978-94-010-1715-2_1. url: https://doi.org/10.1007/978-94-010-1715- 2_1. Benson, B. et al. (mayo de 2020). “Forecasting Solar Cycle 25 Using Deep Neural Networks”.En: Solar Phys. 295.5, 65, pag. 65. doi: 10 . 1007 / s11207 - 020 - 01634 - y. arXiv:2005.12406 [astro-ph.SR]. Benz, Arnold O. (dic. de 2017). “Flare Observations”. En: Living Reviews in Solar Physics 14.1, 2, pag. 2. doi: 10.1007/s41116-016-0004-3. Chamberlin, P. C., F. G. Eparvier et al. (dic. de 2020). “The Flare Irradiance Spectral Model-Version 2 (FISM2)”. En: Space Weather 18.12, e02588, e02588. doi: 10.1029/2020SW002588. Chamberlin, P. C., G. Lu et al. (abr. de 2009). “Using the Flare Irradiance Spectral Model (FISM) to study the response of the Earth, Mars and Moon to Solar Flares”. En: EGU General Assembly Conference Abstracts. EGU General Assembly Conference Abstracts, p ag. 5970. Clette, Frederic et al. (dic. de 2014). “Revisiting the Sunspot Number. A 400-Year Perspective on the Solar Cycle”. En: Space Sci. Rev. 186.1-4, pags. 35-103. doi: 10.1007/ s11214-014-0074-2. arXiv: 1407.3231 [astro-ph.SR]. Darnel, Jonathan M. et al. (2022). “The GOES-R Solar UltraViolet Imager”. En: Space Weather 20.4. e2022SW003044 2022SW003044, e2022SW003044. doi: https://doi.org/10.1029/2022SW003044. eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2022SW003044. url: https://agupubs.onlinelibrary.wiley. com/doi/abs/10.1029/2022SW003044. Engebretson, M. J. et al. (2018). “MMS, Van Allen Probes, GOES 13, and Ground-Based Magnetometer Observations of EMIC Wave Events Before, During, and After a Modest Interplanetary Shock”. En: Journal of Geophysical Research: Space Physics 123.10,pags. 8331-8357. doi: https : / / doi . org / 10 . 1029 / 2018JA025984. eprint: https :/ / agupubs . onlinelibrary . wiley . com / doi / pdf / 10 . 1029 / 2018JA025984. url:https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018JA025984. Goodman, Steven J. (2020). “Chapter 1 - GOES-R Series Introduction”. En: The GOES-R Series. Ed. por Steven J. Goodman et al. Elsevier, pags. 1-3. isbn: 978-0-12-814327-8.doi: https://doi.org/10.1016/B978- 0- 12- 814327- 8.00001- 9. url: https: //www.sciencedirect.com/science/article/pii/B9780128143278000019. Goupil, M J et al. (ene. de 2011). “Open issues in probing interiors of solar-like oscillating main sequence stars 1. From the Sun to nearly suns”. En: Journal of Physics: Conference Series 271.1, pag. 012031. doi: 10.1088/1742- 6596/271/1/012031. url: https://dx.doi.org/10.1088/1742-6596/271/1/012031. Gunshor, Mathew M. et al. (jul. de 2020). “GOES-R series ABI Imagery artifacts”. En:Journal of Applied Remote Sensing 14, 032411, pag. 032411. doi: 10.1117/1.JRS.14.032411. Hanslmeier, Arnold (2010). The sun and space weather. Vol. 18. Springer. Harder, J. et al. (ene. de 2005). “Solar spectral irradiance variability comparisons of the SORCE SIM instrument with monitors of solar activity and spectral synthesis”. En:Mem. Societa Astronomica Italiana 76, pag. 735. Hathaway, David (dic. de 2010). “The Solar Cycle”. En: Living Reviews in Solar Physics 7.doi: 10.12942/lrsp-2010-1. Kopp, Greg y George Lawrence (ago. de 2005). “The Total Irradiance Monitor (TIM): Instrument Design”. En: Solar Phys. 230.1-2, pags. 91-109. doi: 10.1007/s11207-005-7446-4. Kress, Brian T., Juan V. Rodriguez y Terrance G. Onsager (2020). “Chapter 20 - The GOES-R Space Environment In Situ Suite (SEISS): Measurement of Energetic Particles in Geospace”. En: The GOES-R Series. Ed. por Steven J. Goodman et al. Elsevier, pags. 243-250. isbn: 978-0-12-814327-8. doi: https://doi.org/10.1016/B978-0-12-814327-8.00020-2. url: https://www.sciencedirect.com/science/article/pii/B9780128143278000202. Lin, Rong et al. (abr. de 2023). “Prediction of solar wind speed by applying convolutional neural network to potential field source surface (PFSS) magnetograms”. En: arXiv eprints, arXiv:2304.01234, arXiv:2304.01234. doi: 10.48550/arXiv.2304.01234. arXiv:2304.01234 [astro-ph.SR]. Paluszek, M. y S. Thomas (2016). MATLAB Machine Learning. Apress. isbn: 9781484222492.url: https://books.google.com.co/books?id=jy75vQAACAAJ. Pearlman, Aaron et al. (jul. de 2022). “Geostationary operational environmental satellite-R advanced baseline imager reflective solar band absolute validation using Sonoran desert scenes”. En: Journal of Applied Remote Sensing 16, 034530, pag. 034530. doi: 10.1117/1.JRS.16.034530. Raschka, Sebastian y Vahid Mirjalili (2019). Python Machine Learning, 3rd Ed. 3.a ed. Birmingham, UK: Packt Publishing. isbn: 978-1789955750. Rottman, Gary (2002). SORCE: Solar Radiation and Climate Experiment. Goddard Space Flight Center. Rouhiainen, L. (2018). Artificial Intelligence: 101 Things You Must Know Today About Our Future. CreateSpace Independent Publishing Platform. isbn: 9781982048808. url:https://books.google.com.co/books?id=P3fSDwAAQBAJ. Sadykov, V. M. (dic. de 2019). “Predicting Solar Flares Using Machine Learning: Advances and Challenges”. En: AGU Fall Meeting Abstracts. Vol. 2019, SH34B-05, SH34B-05. Schwenn, Rainer (ago. de 2006). “SpaceWeather: The Solar Perspective”. En: Living Reviews in Solar Physics 3.1, 2, pag. 2. doi: 10.12942/lrsp-2006-2. Snow, Martin et al. (jul. de 2022). “SORCE SOLSTICE: Validation of Seventeen Years of UV Solar Spectral Irradiance Observations”. En: 44th COSPAR Scientific Assembly. Held 16-24 July. Vol. 44, pag. 1555. Spiegel, E. A. y J. -P. Zahn (nov. de 1992). “The solar tachocline.” En: Astron. Astrophys.265, pags. 106-114. Vaquero, J.M. y M. Vazquez (2009). The Sun Recorded Through History. Astrophysics and Space Science Library. Springer New York. isbn: 9780387929514. url: https://books. google.com.co/books?id=lmj4sgEACAAJ. Woods, Thomas N. y Joshua Elliott (mayo de 2022). “Solar Radiation and Climate Experiment (SORCE) X-Ray Photometer System (XPS): Final Data-Processing Algorithms”.En: Solar Phys. 297.5, 64, pag. 64. doi: 10.1007/s11207-022-01997-4. Woods, Thomas N. y John W. Leibacher (feb. de 2023). “The Solar Radiation and Climate Experiment (SORCE) Mission: Final Calibrations and Data Products”. En: Solar Phys.298.2, 25, pag. 25. doi: 10.1007/s11207-023-02125-6. |
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xi, 53 páginas |
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application/pdf |
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2003-2020 2003 – 2020 |
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Universidad Nacional de Colombia |
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Bogotá - Ciencias - Maestría en Ciencias - Astronomía |
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Facultad de Ciencias |
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Bogotá, Colombia |
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Universidad Nacional de Colombia - Sede Bogotá |
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Universidad Nacional de Colombia |
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Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Calvo Mozo, Benjamin44b2a2692053c7edeff57050fd587062Moreno Roballo, Nestor Ivan4cfa615999a17f2e40e79f4fde6a48f7Martinez Oliveros Juan CarlosAstronomía, Astrofísica y Cosmologia2003-20202003 – 20202023-11-30T14:02:50Z2023-11-30T14:02:50Z2023-11-29https://repositorio.unal.edu.co/handle/unal/85024Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasEl presente estudio se centró en analizar la radiacion solar en un periodo de tiempo que abarca desde 2003 hasta 2020, utilizando datos diarios satelitales proporcionados por SORCE (Solar Radiation and Climate Experiment) en diferentes bandas y GOES (Geostationary Operational Environmental Satellite) en rayos X; junto con los registros de numero de manchas solares y eventos clase C, M y X. Se realiza una comparacion analıtica para entender los posibles factores que producen la variabilidad del ciclo solar y otra con la ayuda de inteligencia artificial mas precisamente aprendizaje automatico con redes neuronales de clasificacion. Los datos se compilaron con una matriz de datos de entrada de 24 × 6075 y se etiquetan respecto a tres salidas binarias, A Sol calmo, B Sol con actividad moderada y C Sol con actividad fuerte. Los resultados obtenidos muestran una correlacion de 90.3% de concordancia de la totalidad de los datos. El 48.1% de los datos tienen un comportamiento de Sol calmo, 41.3% presentan una actividad solar moderada y el 1.0% con actividad solar fuerte. (Texto tomado de la fuente)he present study was focused on the analysis of the solar radiation in a period from 2003 to 2020, using daily satellite data provided by SORCE (Solar Radiation and Climate Expe- riment) in different bands and GOES (Geostationary Operational Environmental Satellite) in X-rays; together with the records of the number of sunspots and class C, M and X events. An analytical comparison is performed to understand the possible factors that produce the variability of the solar cycle and another with the help of artificial intelligence more preci- sely automatic learning with classification neural networks. The data were compiled with an input data matrix of 24 × 6075 and labeled with respect to three binary outputs, A quiet Sun, B Sun with moderate activity and C Sun with strong activity. The results obtained show a correlation of 90.3 % agreement of all the data. The 48.1 % of the data have a behavior of quiet Sun, 41.3 % present a moderate solar activity and 1.0 % sun with strong activity.MaestríaMagíster en Ciencias - AstronomíaAstrofısica Solarxi, 53 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias - Maestría en Ciencias - AstronomíaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá520 - Astronomía y ciencias afinesActividad solarRadiación solarSolar activitySolar radiationSol calmo, Sol activo, ciclo solar, manchas solares, fulguracion solar, Satelite GOES, Satelite SORCE, aprendizaje automatico, correlacion de datos.Sol calmoSol activoCiclo solarManchas solaresFulguracion solarSatelite GOESSatelite SORCEAprendizaje automaticoCorrelacion de datosEstudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOESMultispectral radiation study solar included in the period 2003 – 2020 according to satellite data SORCE and GOESTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAbhyankar, K. D. (mar. de 1977). “A Survey of the Solar Atmospheric Models”. En: Bulletin of the Astronomical Society of India 5, pag. 40.Ali, Aatiya et al. (mar. de 2023). “Predicting Solar Proton Events of Solar Cycles 22-24 using GOES Proton & Soft X-Ray Flux Statistics”. En: arXiv e-prints, arXiv:2303.05446, arXiv:2303.05446. doi: 10.48550/arXiv.2303.05446. arXiv: 2303.05446 [astro-ph.SR].Athay, R. Grant (1976). “Introduction”. En: The Solar Chromosphere and Corona: Quiet Sun. Dordrecht: Springer Netherlands, pags. 1-30. isbn: 978-94-010-1715-2. doi: 10.1007/978-94-010-1715-2_1. url: https://doi.org/10.1007/978-94-010-1715- 2_1.Benson, B. et al. (mayo de 2020). “Forecasting Solar Cycle 25 Using Deep Neural Networks”.En: Solar Phys. 295.5, 65, pag. 65. doi: 10 . 1007 / s11207 - 020 - 01634 - y. arXiv:2005.12406 [astro-ph.SR].Benz, Arnold O. (dic. de 2017). “Flare Observations”. En: Living Reviews in Solar Physics 14.1, 2, pag. 2. doi: 10.1007/s41116-016-0004-3.Chamberlin, P. C., F. G. Eparvier et al. (dic. de 2020). “The Flare Irradiance Spectral Model-Version 2 (FISM2)”. En: Space Weather 18.12, e02588, e02588. doi: 10.1029/2020SW002588.Chamberlin, P. C., G. Lu et al. (abr. de 2009). “Using the Flare Irradiance Spectral Model (FISM) to study the response of the Earth, Mars and Moon to Solar Flares”. En: EGU General Assembly Conference Abstracts. EGU General Assembly Conference Abstracts, p ag. 5970.Clette, Frederic et al. (dic. de 2014). “Revisiting the Sunspot Number. A 400-Year Perspective on the Solar Cycle”. En: Space Sci. Rev. 186.1-4, pags. 35-103. doi: 10.1007/ s11214-014-0074-2. arXiv: 1407.3231 [astro-ph.SR].Darnel, Jonathan M. et al. (2022). “The GOES-R Solar UltraViolet Imager”. En: Space Weather 20.4. e2022SW003044 2022SW003044, e2022SW003044. doi: https://doi.org/10.1029/2022SW003044. eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2022SW003044. url: https://agupubs.onlinelibrary.wiley. com/doi/abs/10.1029/2022SW003044.Engebretson, M. J. et al. (2018). “MMS, Van Allen Probes, GOES 13, and Ground-Based Magnetometer Observations of EMIC Wave Events Before, During, and After a Modest Interplanetary Shock”. En: Journal of Geophysical Research: Space Physics 123.10,pags. 8331-8357. doi: https : / / doi . org / 10 . 1029 / 2018JA025984. eprint: https :/ / agupubs . onlinelibrary . wiley . com / doi / pdf / 10 . 1029 / 2018JA025984. url:https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018JA025984.Goodman, Steven J. (2020). “Chapter 1 - GOES-R Series Introduction”. En: The GOES-R Series. Ed. por Steven J. Goodman et al. Elsevier, pags. 1-3. isbn: 978-0-12-814327-8.doi: https://doi.org/10.1016/B978- 0- 12- 814327- 8.00001- 9. url: https: //www.sciencedirect.com/science/article/pii/B9780128143278000019.Goupil, M J et al. (ene. de 2011). “Open issues in probing interiors of solar-like oscillating main sequence stars 1. From the Sun to nearly suns”. En: Journal of Physics: Conference Series 271.1, pag. 012031. doi: 10.1088/1742- 6596/271/1/012031. url: https://dx.doi.org/10.1088/1742-6596/271/1/012031.Gunshor, Mathew M. et al. (jul. de 2020). “GOES-R series ABI Imagery artifacts”. En:Journal of Applied Remote Sensing 14, 032411, pag. 032411. doi: 10.1117/1.JRS.14.032411.Hanslmeier, Arnold (2010). The sun and space weather. Vol. 18. Springer.Harder, J. et al. (ene. de 2005). “Solar spectral irradiance variability comparisons of the SORCE SIM instrument with monitors of solar activity and spectral synthesis”. En:Mem. Societa Astronomica Italiana 76, pag. 735.Hathaway, David (dic. de 2010). “The Solar Cycle”. En: Living Reviews in Solar Physics 7.doi: 10.12942/lrsp-2010-1.Kopp, Greg y George Lawrence (ago. de 2005). “The Total Irradiance Monitor (TIM): Instrument Design”. En: Solar Phys. 230.1-2, pags. 91-109. doi: 10.1007/s11207-005-7446-4.Kress, Brian T., Juan V. Rodriguez y Terrance G. Onsager (2020). “Chapter 20 - The GOES-R Space Environment In Situ Suite (SEISS): Measurement of Energetic Particles in Geospace”. En: The GOES-R Series. Ed. por Steven J. Goodman et al. Elsevier, pags. 243-250. isbn: 978-0-12-814327-8. doi: https://doi.org/10.1016/B978-0-12-814327-8.00020-2. url: https://www.sciencedirect.com/science/article/pii/B9780128143278000202.Lin, Rong et al. (abr. de 2023). “Prediction of solar wind speed by applying convolutional neural network to potential field source surface (PFSS) magnetograms”. En: arXiv eprints, arXiv:2304.01234, arXiv:2304.01234. doi: 10.48550/arXiv.2304.01234. arXiv:2304.01234 [astro-ph.SR].Paluszek, M. y S. Thomas (2016). MATLAB Machine Learning. Apress. isbn: 9781484222492.url: https://books.google.com.co/books?id=jy75vQAACAAJ.Pearlman, Aaron et al. (jul. de 2022). “Geostationary operational environmental satellite-R advanced baseline imager reflective solar band absolute validation using Sonoran desert scenes”. 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En: Solar Phys.298.2, 25, pag. 25. doi: 10.1007/s11207-023-02125-6.Estudio multiespectral de radiacion solar comprendido en el periodo 2003 – 2020 segun datos satelitales de SORCE y GOESEstudiantesInvestigadoresMaestrosLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/85024/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL80215819.2023.pdf80215819.2023.pdfTesis de Maestría en Ciencias - Astronomíaapplication/pdf6802402https://repositorio.unal.edu.co/bitstream/unal/85024/2/80215819.2023.pdf24fe2a498c2b199df7e92871b1566486MD52THUMBNAIL80215819.2023.pdf.jpg80215819.2023.pdf.jpgGenerated Thumbnailimage/jpeg4773https://repositorio.unal.edu.co/bitstream/unal/85024/3/80215819.2023.pdf.jpg643d43a3ab035c6eb0e92ef4140e0193MD53unal/85024oai:repositorio.unal.edu.co:unal/850242023-12-01 23:03:43.267Repositorio Institucional Universidad Nacional de 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