Study of coded ALOHA with multi-user detection under heavy-tailed and correlated arrivals

In this paper, we study via simulation the performance of irregular repetition slotted ALOHA under multi-packet detection and different patterns of the load process. On the one hand, we model the arrival process with a version of the M/G/∞ process able to exhibit a correlation structure decaying slowly in time. Given the independence among frames in frame-synchronous coded-slotted ALOHA (CSA), this variation should only take effect on frame-asynchronous CSA. On the other hand, we vary the marginal distribution of the arrival process using discrete versions of the Lognormal and Pareto distributions, with the objective of investigating the influence of the right tail. In this case, both techniques should be affected by the change, albeit to a different degree. Our results confirm these hypotheses and show that these factors must be taken into account when designing and analyzing these systems. In frameless operations, both the shape of the packet arrivals tail distribution and the existence of short-range and long-range correlations strongly impact the packet loss ratio and the average delay. Nevertheless, these effects emerge only weakly in the case of frame-aligned operations, because this enforces the system to introduce a delay in the newly arrived packets (until the beginning of the next frame), and implies that the backlog of accumulated packets is the key quantity for calculating the performance.Ministerio de Ciencia e Innovación | Ref. PID2020-113240RB-I00Ministerio de Ciencia e Innovación | Ref. PID2020-113795RB-C3

Study of the impact of social learning and gamification methodologies on learning results in higher education

In this work, as the last step of a longitudinal study of the impact of so- cial learning and gamification methodologies on learning results in higher education, we have recorded the activity in a software platform based on Moodle, especially built for encouraging online participation of the stu- dents to design, carry out and evaluate a set of learning tasks and games, during two consecutive editions of an undergraduate course. Our aim is to confirm the relationships of the patterns of accomplishment of the gam- ified activities and the network structure of the social graphs associated to the online forums with knowledge adquisition and final outcomes. For this purpose we have offered two learning paths, traditional and novel, to our students. We have identified course variables that quantitatively explain the improvements reported when using the innovative methodolo- gies integrated in the course design, and we have applied techniques from the social network analysis (SNA) and the machine learning/deep learn- ing (ML/DL) domains to conduct success/failure classification methods finding that, generally, very good results are obtained when an ensemble approach is used, that is, when we blend the predictions made by different classifiers. The proposed methodology can be used over reduced datasets and variable time windows for having early estimates that allow pedagog- ical interventions. Finally, we have applied other statistical tests to our datasets, that confirm the influence of learning path on learning results

Design, development and use of a digital badges system in higher education

Badges are non fungible tokens used to document or certify achievements in academics or in any other domain. Besides their utility as proof of achievement, badges are of interest in higher education as pure incentives to push the students and learners in general toward pursuing well-defined goals and skills. In this respect, badges can be naturally incorporated into digital learning platforms also as part of informal learning activities, and stimulate participation, merit, and visibility for the students. However, the level of engagement of learners into these learning activities depends crucially on how the system of badges and rewards has been designed and on how it is applied, if it is to be used effectively. In this paper, we report on the design and implementation of a smart badges system, and an example of its use inside a gamification methodology for informal learning in a master level course, and discuss the benefits and the observed gains in learning performance that can be obtained

Current trends on green wireless sensor networks

The issue of energy balancing in Wireless Sensor Networks is a pivotal one, crucial in their deployment. This problem can be subdivided in three areas: (i) energy conservation techniques, usually implying minimizing the cost of communication at the nodes since it is known that the radio is the biggest consumer of the available energy; (ii) energy-harvesting techniques, converting energy from not full-time available environmental sources and usually storing it; and (iii) energy transfer techniques, sharing energy resources from one node (either specialized or not) to another one. In this article, we survey the main contributions in these three areas and identify the main trending topics in recent research. A discussion and some future directions are also included.Ministerio de Ciencia, Innovación y Universidades | Ref. RED2018-102585-TMinisterio de Ciencia, Innovación y Universidades | Ref. PID2020-113240RB-I0