Caracterización del aprendizaje en tres grupos de estudio de la Licenciatura de Etnoeducación y Desarrollo Comunitario de la U.T.P. a partir de una experiencia personal

El presente estudio, tuvo como objetivo caracterizar el aprendizaje en tres grupos de estudio de la Licenciatura de Etnoeducación y Desarrollo Comunitario de la U.T.P. a partir de una experiencia personal, en relación con autores como Henry Giroux (1992). Inicialmente se contextualizó la investigación, mediante la exposición de la teoría de este autor acerca de la resistencia en la educación, con apoyo de otros teóricos. Luego se establecieron las características de la población y se hizo finalmente una breve relación de la teoría del autor mencionado con las características de la población de estudio. En síntesis, se pudo determinar que independiente de que la carrera sea la misma para la población de estudio, los estudiantes poseen cada uno unas ideologías propias e intereses, y modos de recibir el aprendizaje, propios de la conciencia de cada quien y la forma como concibe el mundo, y por ello, su manifestación en cuanto a la resistencia en la educación, fue diferente en los tres grupos

Manizales City: A Smart City?

The use in the cities of Information and Communications Technologies (ICT) has increased, due to the political and economical control, that has favored their development. This new type of city (system) holds different names: Digital City and Smart City. The Smart City is a self-sustaining city. In the most innovative-technological dimension, there are included the factors for sustainable development. The Smart City uses the ICT, with the purpose of providing an infrastructure, that can guarantee: a sustainable development, an better life quality for its population, a higher efficiency when using the resources that are available and, a more active participation of the citizens. The focus of Smart City, is more popular among projects that imply transformation for this kind of cities. However, in researches that measure and classify some of the smart cities, there have been presented ideal models, where the main characteristics are based in the subsystems of these cities. The factor that allows establishing the level of intelligence that a city has achieved, is the analysis of a real city and then, comparing it to the features of a Smart City. This measurement model, can be adopted by the municipal government of the city, in order to carry out special improvement activities in their development plans. The case in this paper is the city of Manizales, which is considered to be the ICT city of Colombia. It was labeled as a Smart City by the adoption of intensive systems in ICT. Nevertheless, and according to a recent study in FEDESARROLLO, Manizales has the lowest usage rate of ICT in Colombia, based on the different components of urban intelligence. Therefore, this label is not based in a measurement that comprises all of the factors that define this type of cities. The project that is presented in this paper aims to set an assessment model, in order to measure the intelligence of Manizales as a Smart City. This paper is the final paper for graduation, in the Masters Program of Information Systems Management (Major)

Global versus local superintegrability of nonlinear oscillators

Liouville (super)integrability of a Hamiltonian system of differential equations is based on the existence of globally well-defined constants of the motion, while Lie point symmetries provide a local approach to conserved integrals. Therefore, it seems natural to investigate in which sense Lie point symmetries can be used to provide information concerning the superintegrability of a given Hamiltonian system. The two-dimensional oscillator and the central force problem are used as benchmark examples to show that the relationship between standard Lie point symmetries and superintegrability is neither straightforward nor universal. In general, it turns out that super-integrability is not related to either the size or the structure of the algebra of variational dynamical symmetries. Nevertheless, all of the first integrals for a given Hamiltonian system can be obtained through an extension of the standard point symmetry method, which is applied to a superintegrable nonlinear oscillator describing the motion of a particle on a space with non-constant curvature and spherical symmetry

Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks

Methods based on Deep Learning have recently been applied on astrophysical parameter recovery thanks to their ability to capture information from complex data. One of these methods is the approximate Bayesian Neural Networks (BNNs) which have demonstrated to yield consistent posterior distribution into the parameter space, helpful for uncertainty quantification. However, as any modern neural networks, they tend to produce overly confident uncertainty estimates and can introduce bias when BNNs are applied to data. In this work, we implement multiplicative normalizing flows (MNFs), a family of approximate posteriors for the parameters of BNNs with the purpose of enhancing the flexibility of the variational posterior distribution, to extract $\Omega_m$, $h$, and $\sigma_8$ from the QUIJOTE simulations. We have compared this method with respect to the standard BNNs, and the flipout estimator. We found that MNFs combined with BNNs outperform the other models obtaining predictive performance with almost one order of magnitude larger that standard BNNs, $\sigma_8$ extracted with high accuracy ($r^2=0.99$), and precise uncertainty estimates. The latter implies that MNFs provide more realistic predictive distribution closer to the true posterior mitigating the bias introduced by the variational approximation and allowing to work with well-calibrated networks.Comment: 15 pages, 4 figures, 3 tables, submitted. Comments welcom