No abstract

Formative research is an essential component in the student's professional training; allows the development, management, generation of information and knowledge with the aim of achieving relevant skills and abilities. The present work consists in the validation of strategies developed in the course of RAII and the students manage to develop them by writing a research article with international standards and the evaluation of external-internal pairs to validate them.

The use of video games has increased exponentially worldwide, mainly among the youth population. The main objective of this article is to evaluate the consumption habits and motivations of engineering students to play video games. To this end, an instrument to measure the use of video games and a scale of motivations were administered to 633 students enrolled in different academic engineering programs at a Peruvian public university. It was found that 91.3% of students play video games, compared to 8.7% who have never played them; it was also found that their use is greater among male students (95%) than among female students (73.4%). Likewise, it was found that these students prefer strategy video games, and that they mostly play them for escape and entertainment, and for socioemotional activation. It is concluded that consumption habits and motivations are related, since the greater the consumption of video games, the greater the motivation is for young people to play them.

Cyberbullying is a growing problem in our society that can bring fatal consequences and can be presented in digital text for example at online social networks. Nowadays there is a wide variety of works focused on the detection of digital texts in the English language, however in the Spanish language there are few studies that address this issue. This paper aims to detect this cybernetic harassment in social networks, in Spanish language. Sentiment analysis techniques are used, such as bag of words, elimination of signs and numbers, tokenization and stemming, as well as a Bayesian classifier. The data used for the training of the Bayesian classifier were obtained from the Spanish Dictionary of Affect in Language (SDAL), which is a database formed by more than 2500 words manually evaluated in three affective dimensions: Pleasantness, activation and imagery, as well as same 595 words obtained following the same procedure of SDAL was used with the help of the members of the Research Center, Technology Transfer and Software Development. As a result, the software developed has 93% success in the validation tests carried out.

Mobile devices are powered by batteries whose capacities are limited by size, so efficient management of energy becomes a very important issue in such devices. Many solutions have been proposed seeking to extend mobile device's battery life, but there are only a few who takes the user as a decisive and determining factor. Only the user determines how to consume battery's energy. Therefore the proposed application aims to solve this issue by learning about user's context. By analyzing this information, automated actions are performed in order to optimize energy consumption.