Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes
ilustraciones
- Autores:
-
Cusgüen Gómez, Carlos Alberto
- Tipo de recurso:
- Fecha de publicación:
- 2022
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/83237
- Palabra clave:
- Mass media and public opinion
Psicología social
Medios de comunicación de masas y opinión pública
Social psychology
Dinámicas de opinión
Agentes persistentes
Redes jerárquicas
Redes sociales
Opinion Dynamics
Stubborn Agents
Hierarchical Networks
Social Networks
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
| id |
UNACIONAL2_3b897c16f1c923ee54686869e06fadb9 |
|---|---|
| oai_identifier_str |
oai:repositorio.unal.edu.co:unal/83237 |
| network_acronym_str |
UNACIONAL2 |
| network_name_str |
Universidad Nacional de Colombia |
| repository_id_str |
|
| dc.title.spa.fl_str_mv |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes |
| dc.title.translated.eng.fl_str_mv |
Definition of network indices to characterize opinion dynamics in the presence of persistent agents |
| title |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes |
| spellingShingle |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes Mass media and public opinion Psicología social Medios de comunicación de masas y opinión pública Social psychology Dinámicas de opinión Agentes persistentes Redes jerárquicas Redes sociales Opinion Dynamics Stubborn Agents Hierarchical Networks Social Networks |
| title_short |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes |
| title_full |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes |
| title_fullStr |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes |
| title_full_unstemmed |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes |
| title_sort |
Definición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentes |
| dc.creator.fl_str_mv |
Cusgüen Gómez, Carlos Alberto |
| dc.contributor.advisor.none.fl_str_mv |
Mojica Nava, Eduardo Alirio |
| dc.contributor.author.none.fl_str_mv |
Cusgüen Gómez, Carlos Alberto |
| dc.contributor.researchgroup.spa.fl_str_mv |
Programa de Investigacion sobre Adquisicion y Analisis de Señales Paas-Un |
| dc.contributor.cvlac.spa.fl_str_mv |
Cusgüen Gómez, Carlos Alberto |
| dc.contributor.researchgate.spa.fl_str_mv |
https://www.researchgate.net/profile/Carlos-Cusguen-2 |
| dc.contributor.googlescholar.spa.fl_str_mv |
Carlos cusguen |
| dc.subject.armarc.eng.fl_str_mv |
Mass media and public opinion |
| topic |
Mass media and public opinion Psicología social Medios de comunicación de masas y opinión pública Social psychology Dinámicas de opinión Agentes persistentes Redes jerárquicas Redes sociales Opinion Dynamics Stubborn Agents Hierarchical Networks Social Networks |
| dc.subject.lemb.spa.fl_str_mv |
Psicología social Medios de comunicación de masas y opinión pública |
| dc.subject.lemb.eng.fl_str_mv |
Social psychology |
| dc.subject.proposal.spa.fl_str_mv |
Dinámicas de opinión Agentes persistentes Redes jerárquicas Redes sociales |
| dc.subject.proposal.eng.fl_str_mv |
Opinion Dynamics Stubborn Agents Hierarchical Networks Social Networks |
| description |
ilustraciones |
| publishDate |
2022 |
| dc.date.issued.none.fl_str_mv |
2022 |
| dc.date.accessioned.none.fl_str_mv |
2023-02-02T14:02:41Z |
| dc.date.available.none.fl_str_mv |
2023-02-02T14:02:41Z |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
| dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
| dc.type.content.spa.fl_str_mv |
Text |
| dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
| status_str |
acceptedVersion |
| dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/83237 |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.identifier.reponame.spa.fl_str_mv |
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/83237 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 |
HEGSELMANN, Rainer, et al. Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of artificial societies and social simulation,2002,vol.5,no3. MIRTABATABAEI, Anahita; BULLO, Francesco. On opinion dynamics in heterogeneous networks. En Proceedings of the 2011 American Control Conference. IEEE, 2011. p. 2807- 2812. LORENZ, Jan. Continuous opinion dynamics under bounded confidence: A survey. International Journal of Modern Physics C, 2007, vol. 18, no 12, p. 1819-1838. A. V Proskurnikov and R. Tempo, “A Tutorial on Modeling and Analysis of Dynamic Social Networks. Part I.,” 2017. A. V. Proskurnikov and R. Tempo, “A tutorial on modeling and analysis of dynamic social networks. Part II,” Annu. Rev. Control, vol. 45, pp. 166–190, 2018 CASTELLANO, Claudio; FORTUNATO, Santo; LORETO, Vittorio. Statistical physics of social dynamics. Reviews of modern physics, 2009, vol. 81, no 2, p. 591. FRIEDKIN, Noah E. The problem of social control and coordination of complex systems in sociology: A look at the community cleavage problem. IEEE Control Systems Magazine, 2015, vol. 35, no 3, p. 40-51. MIRTABATABAEI, Anahita, et al. On the reflected appraisals dynamics of influence networks with stubborn agents. En 2014 American Control Conference. IEEE, 2014. p. 3978-3983. FRIEDKIN, Noah E. A structural theory of social influence. Cambridge University Press, 2006. WASSERMAN, Stanley; FAUST, Katherine. Social network analysis: Methods and applications. Cambridge university press, 1994. NEWMAN, Mark. Networks. Oxford university press, 2018. ACEMOGLU, Daron, et al. Opinion fluctuations and persistent disagreement in social networks. En 2011 50th IEEE Conference on Decision and Control and European Control Conference. IEEE, 2011. p. 2347-2352. H. Noorazar, K. R. Vixie, A. Talebanpour, and Y. Hu, “From classical to modern opinion dynamics,” Int. J. Mod. Phys. C, vol. 31, no. 7, pp. 1–63, 2020. Guillaume Deffuant, David Neau, Frederic Amblard, and Gérard Weisbuch. Mixing beliefs among interacting agents. Advances in Complex Systems, 03(01n04):87–98, 2000. IRFAN, Mohammad T.; ORTIZ, Luis E. On influence, stable behavior, and the most influential individuals in networks: A game-theoretic approach. Artificial Intelligence, 2014, vol. 215, p. 79-119. SHANG, Yilun. Deffuant model with general opinion distributions: First impression and critical confidence bound. Complexity, 2013, vol. 19, no 2, p. 38-49. YE, Mengbin, et al. Modification of social dominance in social networks by selective adjustment of interpersonal weights. En 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. p. 2906-2911 CHACOMA, Andres; ZANETTE, Damian H. Opinion formation by social influence: From experiments to modeling. PloS one, 2015, vol. 10, no 10, p. e0140406. CASTELLANO, Claudio; FORTUNATO, Santo; LORETO, Vittorio. Statistical physics of social dynamics. Reviews of modern physics, 2009, vol. 81, no 2, p. 591. FRIEDKIN, Noah E. The problem of social control and coordination of complex systems in sociology: A look at the community cleavage problem. IEEE Control Systems Magazine, 2015, vol. 35, no 3, p. 40-51. ORRELL, Shelley J.; RIDGEWAY, Cecilia L. Expectation states theory. En Handbook of social psychology. Springer, Boston, MA, 2006. p. 29-51. FRIEDKIN, Noah E. A formal theory of social power. Journal of Mathematical Sociology, 1986, vol. 12, no 2, p. 103-126. P. Frasca, C. Ravazzi, R. Tempo, and H. Ishii, Gossips and prejudices: Ergodic randomized dynamics in social networks, vol. 4, no. PART 1. IFAC, 2013. SMITH-LOVIN, Lynn; HEISE, David R. Analyzing social interaction: Advances in affect control theory. Routledge, 2016. DEGROOT, Morris H. Reaching a consensus. Journal of the American Statistical Association, 1974, vol. 69, no 345, p. 118-121. FRIEDKIN, Noah E.; JOHNSEN, Eugene C. Social influence and opinions. Journal of Mathematical Sociology, 1990, vol. 15, no 3-4, p. 193-206. FRIEDKIN, Noah E.; JOHNSEN, Eugene C. Attitude change, affect control, and expectation states in the formation of influence networks. En Power and Status. Emerald Group Publishing Limited, 2003. p. 1-29. CARRINGTON, Peter J.; SCOTT, John; WASSERMAN, Stanley (ed.). Models and methods in social network analysis. Cambridge university press, 2005. FRIEDKIN, Noah E.; JOHNSEN, Eugene C. Social influence network theory: A sociological examination of small group dynamics. Cambridge University Press, 2011. QUATTROCIOCCHI, Walter; CALDARELLI, Guido; SCALA, Antonio. Opinion dynamics on interacting networks: media competition and social influence. Scientific reports, 2014, vol. 4, p. 4938. FOTAKIS, Dimitris; PALYVOS-GIANNAS, Dimitris; SKOULAKIS, Stratis. Opinion Dynamics with Local Interactions. En IJCAI. 2016. p. 279-285. WEIDLICH, W., The statistical description of polarization phenomena in society, British Journal of Mathematical and Statistical Psychology,Vol. 24 (2), pp. 251-266, 1971. HANNEMAN,R. A., & Riddle, M. Introduction to social network methods. 2005 |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional |
| dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Atribución-NoComercial-SinDerivadas 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.extent.spa.fl_str_mv |
xiii, 93 páginas |
| dc.format.mimetype.spa.fl_str_mv |
application/pdf |
| dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia |
| dc.publisher.program.spa.fl_str_mv |
Bogotá - Ingeniería - Maestría en Ingeniería - Automatización Industrial |
| dc.publisher.faculty.spa.fl_str_mv |
Facultad de Ingeniería |
| dc.publisher.place.spa.fl_str_mv |
Bogotá - Colombia |
| dc.publisher.branch.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Bogotá |
| institution |
Universidad Nacional de Colombia |
| bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/83237/3/license.txt https://repositorio.unal.edu.co/bitstream/unal/83237/4/1032413496.2022.pdf https://repositorio.unal.edu.co/bitstream/unal/83237/5/1032413496.2022.pdf.jpg |
| bitstream.checksum.fl_str_mv |
eb34b1cf90b7e1103fc9dfd26be24b4a fe15ac98f15fa9802374af05285d75aa 7199012c757a222c0c1e575045d4843c |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
| repository.mail.fl_str_mv |
repositorio_nal@unal.edu.co |
| _version_ |
1814089389707362304 |
| spelling |
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_abf2Mojica Nava, Eduardo Alirio609c35fb4a7e288ee81a2ef0fb802397Cusgüen Gómez, Carlos Alberto7d001e6ddb713daed9ae8db0b53186d7Programa de Investigacion sobre Adquisicion y Analisis de Señales Paas-UnCusgüen Gómez, Carlos Albertohttps://www.researchgate.net/profile/Carlos-Cusguen-2Carlos cusguen2023-02-02T14:02:41Z2023-02-02T14:02:41Z2022https://repositorio.unal.edu.co/handle/unal/83237Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustracionesEl éxito de muchas de las sociedades modernas está directamente relacionado con el hecho de que la opinión de la mayoría de los individuos permita la toma de decisiones que generen acciones directas sobre el bienestar social, de esta manera se hace importante el análisis de las condiciones de influencia de las opiniones de líderes, sobre los agentes que constituyen las mayorías en los sistemas sociales, así pues, se entiende que las dinámicas de opinión pueden ser útiles y poderosas herramientas para diseñar mecanismos para la realización de acciones colectivas[1]. El propósito de este documento de tesis, es en primera medida presentar un análisis de los diferentes modelos propuestos para el estudio de las dinámicas de opinión, su clasificación y condiciones de uso, por otra parte busca establecer comparación entre modelos, que tengan en cuenta las características de los agentes, en la evolución de las opiniones, y por último plantear un modelo jerárquico de red, en el que se caracterice la dinámica de opinión de un conjunto de agentes dividido en dos grupos. El primero, de agente o agentes persistentes, los cuales típicamente no cambian su opinión a pesar de las interacciones sociales, además estos agentes difunden su opinión de manera pública, a los que se reconocerán como líderes de opinión; por otra parte, se establece un grupo de agentes regulares los cuales están dispuestos a cambiar sus opiniones y la comparten de manera semi-privada con un número específico de agentes, el modelo usado como referencia es una variación del modelo de Friedkin-Jhonsens [8], [13]. Se evalúan los efectos que los agentes persistentes tienen sobre el comportamiento del modelo de dinámica de opinión representado a través de grafos dirigidos, el modelo propuesto considera la actualización de las opiniones como una combinación convexa de la opinión actual de los vecinos y la opinión inicial del agente, además la disposición convexa de las variables es usada para introducir el peso de la difusión de las opiniones del grupo de los agentes persistentes y el valor de la información privada, más específicamente el mecanismo para la actualización de las opiniones afirma que el peso individual de las propias opiniones varia, los pesos relativos que se asignan a otros individuos y a otras hacen que la red cambie [8]. El modelo propuesto es validado por medio de simulación, donde se analizan algunos índices basadas en la centralidad, asociada a la red, de los agentes persistentes sobre los agentes regulares [10]. Además de los resultados de simulación, se presenta una propuesta para la recogida de datos para la validación del modelo, y un diseño de prueba sociométrica para caracterizar los grupos de agentes en un aplicación especifica. (Texto tomado de la fuente)ilustracionesThe success of many modern societies is directly related to the fact that the opinion of the majority individual allows to take decisions to generate direct actions for the social welfare. In this way, the analysis of the conditions of influence of the opinions of leaders, on the agents that constitute the majorities in the social systems is a fundamental issues. Thus, it is understood that the dynamic opinions can be a useful and powerful tools for designing mechanisms for carrying out collective actions [1]. The purpose of this thesis is first to present an analysis of the different models proposed for the study of the dynamics opinions, their classification and conditions of use,on the other hand, seeks to establish a comparison between models, which take into account the characteristics of agents in the evolution of the opinions, and finally to propose a hierarchical network model, in which the dynamic of opinion of a group of agents is divided into two groups. Stubborn agents,which typically do not change their opinion despite social interactions, and publicly disseminate their opinion to those who are recognized as opinion leaders. Otherwise group of regular agents is established who are willing to change their opinions and share it semi-privately with a specific number of agents. The model used as a reference is a variation of the Friedkin-Jhonsens model [2]. The effects that stubborn agents have on the behavior of the model of opinion dynamics represented through directed graphs are evaluated. The proposed model considers the updating of the opinions as a convex combination of the current opinion of the neighbors and the initial opinion of the agent, besides the convex disposition of the variables is used to introduce the weight of the diffusion of the opinions of the group of persistent agents, and the value of private information. More specifically the mechanism for the updating of opinions affirms that the individual weight of one’s opinions varies, the relative weights assigned to other individuals and others cause the network to change [3] The proposed model is validated by means of simulation, where some indexes are analyzed based on the centrality, associated to the network of the persistent agents on the regular agents [4]. In addition to the simulation results, a proposal is presented for data collection for model validation, anMaestríaModelación de dinámica de sistemasxiii, 93 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Automatización IndustrialFacultad de IngenieríaBogotá - ColombiaUniversidad Nacional de Colombia - Sede BogotáDefinición de índices de red para caracterizar la dinámica de opinión en presencia de agentes persistentesDefinition of network indices to characterize opinion dynamics in the presence of persistent agentsTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMHEGSELMANN, Rainer, et al. Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of artificial societies and social simulation,2002,vol.5,no3.MIRTABATABAEI, Anahita; BULLO, Francesco. On opinion dynamics in heterogeneous networks. En Proceedings of the 2011 American Control Conference. IEEE, 2011. p. 2807- 2812.LORENZ, Jan. Continuous opinion dynamics under bounded confidence: A survey. International Journal of Modern Physics C, 2007, vol. 18, no 12, p. 1819-1838.A. V Proskurnikov and R. Tempo, “A Tutorial on Modeling and Analysis of Dynamic Social Networks. Part I.,” 2017.A. V. Proskurnikov and R. Tempo, “A tutorial on modeling and analysis of dynamic social networks. Part II,” Annu. Rev. Control, vol. 45, pp. 166–190, 2018CASTELLANO, Claudio; FORTUNATO, Santo; LORETO, Vittorio. Statistical physics of social dynamics. Reviews of modern physics, 2009, vol. 81, no 2, p. 591.FRIEDKIN, Noah E. The problem of social control and coordination of complex systems in sociology: A look at the community cleavage problem. IEEE Control Systems Magazine, 2015, vol. 35, no 3, p. 40-51.MIRTABATABAEI, Anahita, et al. On the reflected appraisals dynamics of influence networks with stubborn agents. En 2014 American Control Conference. IEEE, 2014. p. 3978-3983.FRIEDKIN, Noah E. A structural theory of social influence. Cambridge University Press, 2006.WASSERMAN, Stanley; FAUST, Katherine. Social network analysis: Methods and applications. Cambridge university press, 1994.NEWMAN, Mark. Networks. Oxford university press, 2018.ACEMOGLU, Daron, et al. Opinion fluctuations and persistent disagreement in social networks. En 2011 50th IEEE Conference on Decision and Control and European Control Conference. IEEE, 2011. p. 2347-2352.H. Noorazar, K. R. Vixie, A. Talebanpour, and Y. Hu, “From classical to modern opinion dynamics,” Int. J. Mod. Phys. C, vol. 31, no. 7, pp. 1–63, 2020.Guillaume Deffuant, David Neau, Frederic Amblard, and Gérard Weisbuch. Mixing beliefs among interacting agents. Advances in Complex Systems, 03(01n04):87–98, 2000.IRFAN, Mohammad T.; ORTIZ, Luis E. On influence, stable behavior, and the most influential individuals in networks: A game-theoretic approach. Artificial Intelligence, 2014, vol. 215, p. 79-119.SHANG, Yilun. Deffuant model with general opinion distributions: First impression and critical confidence bound. Complexity, 2013, vol. 19, no 2, p. 38-49.YE, Mengbin, et al. Modification of social dominance in social networks by selective adjustment of interpersonal weights. En 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. p. 2906-2911CHACOMA, Andres; ZANETTE, Damian H. Opinion formation by social influence: From experiments to modeling. PloS one, 2015, vol. 10, no 10, p. e0140406.CASTELLANO, Claudio; FORTUNATO, Santo; LORETO, Vittorio. Statistical physics of social dynamics. Reviews of modern physics, 2009, vol. 81, no 2, p. 591.FRIEDKIN, Noah E. The problem of social control and coordination of complex systems in sociology: A look at the community cleavage problem. IEEE Control Systems Magazine, 2015, vol. 35, no 3, p. 40-51.ORRELL, Shelley J.; RIDGEWAY, Cecilia L. Expectation states theory. En Handbook of social psychology. Springer, Boston, MA, 2006. p. 29-51.FRIEDKIN, Noah E. A formal theory of social power. Journal of Mathematical Sociology, 1986, vol. 12, no 2, p. 103-126.P. Frasca, C. Ravazzi, R. Tempo, and H. Ishii, Gossips and prejudices: Ergodic randomized dynamics in social networks, vol. 4, no. PART 1. IFAC, 2013.SMITH-LOVIN, Lynn; HEISE, David R. Analyzing social interaction: Advances in affect control theory. Routledge, 2016.DEGROOT, Morris H. Reaching a consensus. Journal of the American Statistical Association, 1974, vol. 69, no 345, p. 118-121.FRIEDKIN, Noah E.; JOHNSEN, Eugene C. Social influence and opinions. Journal of Mathematical Sociology, 1990, vol. 15, no 3-4, p. 193-206.FRIEDKIN, Noah E.; JOHNSEN, Eugene C. Attitude change, affect control, and expectation states in the formation of influence networks. En Power and Status. Emerald Group Publishing Limited, 2003. p. 1-29.CARRINGTON, Peter J.; SCOTT, John; WASSERMAN, Stanley (ed.). Models and methods in social network analysis. Cambridge university press, 2005.FRIEDKIN, Noah E.; JOHNSEN, Eugene C. Social influence network theory: A sociological examination of small group dynamics. Cambridge University Press, 2011.QUATTROCIOCCHI, Walter; CALDARELLI, Guido; SCALA, Antonio. Opinion dynamics on interacting networks: media competition and social influence. Scientific reports, 2014, vol. 4, p. 4938.FOTAKIS, Dimitris; PALYVOS-GIANNAS, Dimitris; SKOULAKIS, Stratis. Opinion Dynamics with Local Interactions. En IJCAI. 2016. p. 279-285.WEIDLICH, W., The statistical description of polarization phenomena in society, British Journal of Mathematical and Statistical Psychology,Vol. 24 (2), pp. 251-266, 1971.HANNEMAN,R. A., & Riddle, M. Introduction to social network methods. 2005Mass media and public opinionPsicología socialMedios de comunicación de masas y opinión públicaSocial psychologyDinámicas de opiniónAgentes persistentesRedes jerárquicasRedes socialesOpinion DynamicsStubborn AgentsHierarchical NetworksSocial NetworksIncremento en las estrategias sustentables en el uso del recurso de energía eléctrica para la población vulnerable en el depto. de CundinamarcaSistema General de Regalías- Departamento de CundinamarcaConsejerosLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83237/3/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD53ORIGINAL1032413496.2022.pdf1032413496.2022.pdfTesis de Maestría en Ingeniería - Automatización Industrialapplication/pdf2378125https://repositorio.unal.edu.co/bitstream/unal/83237/4/1032413496.2022.pdffe15ac98f15fa9802374af05285d75aaMD54THUMBNAIL1032413496.2022.pdf.jpg1032413496.2022.pdf.jpgGenerated Thumbnailimage/jpeg4731https://repositorio.unal.edu.co/bitstream/unal/83237/5/1032413496.2022.pdf.jpg7199012c757a222c0c1e575045d4843cMD55unal/83237oai:repositorio.unal.edu.co:unal/832372024-08-15 23:15:23.613Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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 |