Quantitative models and software architecture, facing student Desertion and Permanence
The development of multi-tier architecture based on knowledge and model driven for the competitiveness is discussed in Higher Education; the engine are Mathematical and Computational Models for dynamic and structural analysis of the academic governance given the student high dropout. The problem is characterized by the high social and economic costs; the layers mentioned, mainly are: Institution issues, Users (3-student levels, Faculty Teachers and Parents) and the data and knowledge, enabling management of multiple piece inter-connected environments, focusing on the governance with its sustainability impact into quality, productivity and competitiveness. Data architecture gives several figures on desertion, costs (families, institutions). The period of observation, the student's retention figures were increased significantly and the desertion control was also improved.
Application of Data Mining for the Detection of Variables that Cause University Desertion
College desertion is one of the problems currently addressed by most higher education institutions throughout Latin America. From different investigations, it is known that a large percentage of students do not complete their studies, with the consequent social cost associated with this phenomenon. Some countries have begun to design deep improvement processes to increase retention in the first years of university studies. The process considered for the improvement of the desertion is through the data mining, the use of its algorithms allows discovering patterns in the students that help to explain this effect. The algorithms also identify the independent variables that influence the desertion and analyze them according to a level of depth previously established by the interested parties. The purpose of this study is to determine a model that explains the desertion of undergraduate students at the university and design actions that tend towards the decrease of the desertion.
A bifunctional Cr/Yb/Tm:Ca3Ga2Ge3O12 phosphor with near-infrared long-lasting phosphorescence and upconversion luminescence.
Currently, upconversion nanocrystals and long-lasting phosphorescent particles have attracted extensive research interest for their possible applications as bioimaging probes. However, there are few reports concerning the achievement of both upconversion luminescence of lanthanide ions and long-lasting phosphorescence of transition metal ions in a sole host so far. Herein, we demonstrate a novel calcium gallium germanium garnet (Ca3Ga2Ge3O12) host where lanthanide ions such as Tm(3+)/Yb(3+) and transition metal ions such as Cr(3+) can be easily incorporated through substituting the Ca(2+) and Ga(3+) respectively. This Cr/Yb/Tm:Ca3Ga2Ge3O12 phosphor exhibits both broadband near-infrared long-lasting phosphorescence of Cr(3+) with an afterglow time of more than 7000 s and near-infrared to near-infrared upconversion luminescence of Tm(3+). Impressively, it is evidenced that the addition of Yb(3+)/Tm(3+) into Cr:Ca3Ga2Ge3O12 not only results in Tm(3+) upconversion luminescence but also greatly increases Cr(3+) afterglow time. Based on excitation/emission, three-dimensional thermoluminescence, and time-resolved luminescence spectra, the related long-lasting phosphorescence and upconversion luminescent mechanisms are systematically discussed as well.