In this article, we propose the use of the optimization algorithm based on improved pattern search (IPSM), applying it to the estimation of the model parameters of a single diode of a photovoltaic cell. The parameters to be estimated are the photovoltaic current, the saturation current of the diode, the series resistance, the resistance in parallel, and the ideality factor of the diode. The estimation is made from the data obtained from a known curve, that is to say, that a photovoltaic cell could be characterized and from the data of the curve the parameters are extracted. The results are the identification of the parameters and the accuracy of the model concerning the reference at the point of maximum power (MPP). Additionally, a comparison is made with the model obtained with three estimations made with the particle swarm optimization algorithm (PSO), under the same conditions in the number of particles and iterations. The error found shows the similarity of the model with the reference obtained using the IPSM algorithm. 

The GIS smart campuses have been constituted as an efficient system that allows the integration of information from different agencies inside universities, with the use of geographic applications developed for different types of users. This research describes general considerations to begin implementation of a smart GIS at the Nueva Granada Campus, in Cajicá. This phase was developed based on the generation of a campus base map, which is used as a spatial reference for the elaboration of all applications that require associated geographic information, as well as the implementation of a Gisweb system for the monitoring, verification, and updating of the campus trees. The result of the work provides the basis for subsequent systems and applications of location, mobility and efficacy management related with the academic and administrative activities in the university campus. 

Currently, there is an interest within the scientific community in thin-film solar cells with a Kesterite (Cu2ZnSnS4) type absorber layer, since they report a theoretical efficiency greater than 32 %. The synthesis of Kesterites by evaporation has allowed for efficiencies at the laboratory level of 11.6 %. Although these are good results, the design of the evaporation chamber and the distribution of the electrodes is essential to control synthesis parameters and evaporate each precursor in the corresponding stage. This project seeks to design an evaporation chamber that can achieve a vacuum of 10-5 mbar, increase the deposition surface and avoid each precursor evaporation in a non-corresponding stage. This last objective was studied using Comsol multiphysics R. (licensed product) software, with the adequate disposition of metallic precursors (zinc, copper, and tin) determined by analyzing heat distribution. It was concluded that the lower the evaporation temperature of the precursor, the smaller the height of the copper electrode in the system. This is because, with a lower height the concentration of heat in the container is lower.

There are several techniques to select a set of traffic features for traffic classification. However, most studies ignore the domain knowledge where traffic analysis or classification is performed and do not consider the always moving information carried in the networks. This paper describes a selection process of online network-traffic discriminators. We obtained 24 traffic features that can be processed on the fly and propose them as a base attribute set for future domain-aware online analysis, processing, or classification. For the selection of a set of traffic discriminators, and to avoid the inconveniences mentioned, we carried out three steps. The first step is a context knowledge-based manual selection of traffic features that meet the condition of being obtained on the fly from the flow. The second step is focused on the quality analysis of previously selected attributes to ensure the relevance of each one when performing a traffic classification. In the third step, the implementation of several incremental learning algorithms verified the usefulness of such attributes in online traffic classification processes. 

The Massive Open Online Courses (MOOC) are courses available to the general public without restrictions that are offered to hundreds or thousands of students and in recent years have been presented as a revolution in online education. They are presented as an alternative to the great demand in higher education for the characteristic of being open and massive because they allow access to education to a huge number of students. They have become an ideal environment for data collection and through the application of learning analytics techniques they have allowed a better understanding of how students learn. However, access to the data from thecurrent open-source MOOC platforms is limited and often difficult to collect and process. This paper presents a proposal for collecting and processing the data from students’ interaction with the Open edX platform through Scripts and a Collector based on Java code. 

Vulnerability studies can identify critical elements in electric power systems in order to take protective measures against possible scenarios that may result in load shedding, which can be caused by natural events or deliberate attacks. This article is a literature review on the latter kind, i.e., the interdiction problem, which assumes there is a disruptive agent whose objective is to maximize the damage to the system, while the network operator acts as a defensive agent. The non-simultaneous interaction of these two agents creates a multilevel optimization problem, and the literature has reported several interdiction models and solution methods to address it. The main contribution of this paper is presenting the considerations that should be taken into account to analyze, model, and solve the interdiction problem, including the most common solution techniques, applied methodologies, and future studies. This literature review found that most research in this area is focused on the analysis of transmission systems considering linear approximations of the network, and a few interdiction studies use an AC model of the network or directly treat distribution networks from a multilevel standpoint. Future challenges in this field include modeling and incorporating new defense options for the network operator, such as distributed generation, demand response, and the topological reconfiguration of the system.f the system.

This article presents the design experience of the “Folk dance as cultural heritage” course, which is offered to undergraduate students from University of Cauca the “massive online course” modality. It shows the main challenges faced in the exercise of the integration of two in-person courses, one practical and one theoretical, and its process of transformation into a MOOC. The course was designed for two academic credits with six hours of dedication per week and is offered as an elective (non-mandatory) class of the Integral Social and Human Formation (FISH) component, through a space in the MOOC Open edX platform. The integration process of the two in-person courses and their transformation into a MOOC, brought with it several challenges related to the adjustment of contents, academic activities and evaluation. This article presents how these challenges were faced in this experience. It is worth mentioning that one of the results obtained in this research is associated with the contribution of the research to the first folk dance course in MOOC modality in Latin America, what makes it an innovative educational proposal that allows the rescue of culture through the adaptation of traditional educational contents.

Massive open online courses (MOOCs) are a key strategy for digital education. The MOOCs contribute significantly to people’s knowledge about a wide range of topics. Nowadays, several web platforms as Coursera and edX offer MOOCs in different domains, however the platforms mentioned do not offer MOOCs focused on crop management through monitoring of climate elements and factors. In this paper, we present an overview of the MOOC titled: “agroclimatic tools for crop protection” for agricultural-sector Spanish speakers. We show a first MOOC evaluation based on a survey applied to 13 people of rural areas located in Cauca (Colombia) for one video of the “Temperature” MOOC unit. The results indicated that 100 % of the respondents understood clearly the video content and 53, 84 % of the surveyed learners understood all the words used in the video.

In recent years, new trends and methodologies have emerged that greatly favor the education sector. E-learning as an alternative to regular teaching and learning processes has transformed the educational dynamics thanks to the inclusion of MOOCs, personal learning environments, allowing the educational process to be carried out at a personalized level where the focus is on learning styles and the profile of the student. This article presents a review of current works around machine learning mechanisms to make recommendations in the educational environment, where it is found that besides the discovery of the student’s learning style, it is important to know their level of knowledge and learning speed, in addition to the tools used by the student to carry out their studies. Finally, the opportunity for implementation and research of these issues in Colombia is highlighted. 

In recent years, serious games have been applied in different contexts of application, highlighting their contribution in the educational context. This original type article presents the design, construction and evaluation of the Coffee Fun video game. Coffee Fun is a video serious game aimed at children aged 8 to 12 years old; the game has as a theme the growing of coffee beans in a simulation environment in which each player helps the growth of this plant by a few tools provided at each level of the game; in the game, different scenarios related to coffee growing environments are presented for each of its stages in a series of levels that the player must overcome to complete the game through a process of learning and entertainment.

This paper proposes a hybrid heuristic that combines Variable Neighborhood Search (VNS) with Ant Colony Optimization (ACO) to solve the scheduling problem of nonrelated parallel machines with sequence dependent setup times in order to minimize the makespan. The Variable Neighborhood Search is proposed to solve the scheduling problem with a descending scheme in a first phase, with an ACO algorithm, which successively reorder the jobs in the machine with the largest makespan in a second phase. An experimental study was performed using test problems from the literature showing that the second phase of the algorithm improves the solution obtained in the first phase. The results obtained are also compared with other methods in the literature proving to be a competitive method.

In this work, the academic performance of a tenth-grade physics course of high school is analyzed over three consecutive years, a b-learning educational context is configured in a rural area based on a framework that integrates Open Educational Resources (OER) to a Learning Management System (LMS). The performance of students who used b-learning is compared to other groups that received the same classes in a traditional way.

This article shows the different stages used for the design and production of a MOOC for biodegradable packing, the planning tools and methodologies used for the development of the themes and contents. Likewise, is shown the technological framework used making a surveillance technology to identify which stage the MOOC e-learning tech is and the search of terms related to biodegradable packing to identify potential topics. Finally, the software architecture for SELENE is explained and how is deployed in open edX platform.