The use of digital filters as the Wavelet Transform is widely recognized in signal processing; however, for the analysis of an electroencephalographic (EEG) signal, the most optimal filter to be used has not been definitively determined. This work presents a comparison between the results obtained by filtering an EEG signal recorded during an 8 minute foreign language class on 69 asymptomatic volunteers using Wavelet Symlets (sym2 - sym10) and Daubechies (db2 - db10). The EEG signals were divided into four sub-bands and an energy, frequency and time analysis was performed. The results obtained show that the filters respond in a different but not significant way. For the identification of the appropriate mother Wavelet for each scope of analysis, its similarity was considered with the average value of Symlets (sym2 - sym10) and this process was replicated for db Wavelets. Considering the energy of the EEG signals, the db4 filter had a higher presence in 5 electrodes in the Alpha and Delta frequency bands. In the frequency domain, the db5 family has a presence in 12 electrodes in the Beta, Alpha and Delta frequency bands. Regarding time, the sym9 filter has a higher presence in 4 electrodes in the Beta, Theta and Delta frequency bands. The purpose of this work is to provide more information for the proper choice of a mother Wavelet in the EEG signal analysis in asymptomatic volunteers.

The advent of the autonomous car is paving the road to the realization of ideas that will help optimize traffic flows, increase safety and reduce fuel consumption, among other advantages. We present one proposal to bring together Virtual Traffics Lights (VTLs) and platooning in urban scenarios, leaning on vehicle-to-vehicle (V2V) communication protocols that turn intersections into virtual containers of data. Newly-introduced protocols for the combined management of VTLs and platoons are validated by simulation, comparing a range of routing protocols for the vehicular networks with the baseline given by common deployments of traditional traffic lights ruled by state-of-the-art policies. The simulation results show that the combination of VTLs and platoons can achieve significant reductions in travel times and fuel consumption, provided that proper algorithms are used to handle the V2V communications.

Vehicular ad hoc networks (VANETs) face challenges related to the reliability of the data exchanged and the unstability of the communication links. These shortcomings have hampered the development of the long-awaited applications that would turn roads into a smart environment. We present a framework to deploy such services, in which a virtualization layer ensures means to efficiently deliver messages between vehicles and roadside units (RSUs) and, on top of that, blockchain technology is used to enable features of data integrity, traceability, and reliability that cannot be furnished by existing consensus and reputation mechanisms. A simulation experiment is included to determine the optimal number of RSUs to be installed as supporting infrastructure in a city.

The scenarios envisaged for the paradigm of vehicular cloud computing (VCC) have been limited by the challenges derived from the mobility of the vehicles, to the point that most of the proposals in the literature merely deal with vehicles in parking lots, stuck in traffic jams or moving as a flock for a long time. We present an approach to overcome those limitations by engaging the vehicles in collaboration to emulate an infrastructure of stationary virtual nodes, which can be made responsible for computing, sensing, storage and communication tasks. We present the architecture and the main procedures of the proposal, along with the results of simulations of the VCC service model known as Network as a Service (NaaS).

We present the OPPIA platform, a ubiquitous and smart learning environment, that deploys sporadic learning networks (SLNs) among people (students, teachers and experts) who happen to be in a common place or in a remote place but connected to the platform through the Internet. The idea is to establish dynamic learning networks that encourage their members to work together and create a learning environment with proper resources and activities to satisfy their learning needs. This paper describes the design of the platform from the lowest levels of establishing connections among members of the SLNs, up to the highest level of smart learning services.