Jesus García

The main purpose of this study was to analyze the presence and current situation of the game of skittles throughout the northern route of the Camino de Santiago. Thus, we considered its current practice, modalities, where it is played, and its different manifestations as an informal and formal game, comparing it with other traditional games on this pilgrimage route. To do this, a mixed qualitative-quantitative study was designed with 89 participants, constituting an informant for each municipality through which the Northern Way passes. An ad hoc questionnaire was used for the data collection, which was processed through content analysis by expert judges and by using the IBM-SPSS statistical package. The results of the study show notable skittles activity on the Northern Camino, reflected in the number of skittles alleys, the number of clubs, associations, and peñas participating in federated leagues, and the wide range of varieties of skittles currently active on the Camino. The relationship between skittles and local culture, both symbols of identity in these northern Spanish regions, made it possible to preserve the traditional heritage in these places, keeping it alive today, despite the push toward new and more attractive leisure and sport trends.

La museografía escolar gana terreno en la virtualidad gracias a la tecnología. Entonces, es necesario establecer la ruta pedagógica para la creación de un museo virtual como espacio de divulgación artística de educación secundaria mediante el uso de las TIC. Por ello, desde la investigación creación, se propone un método teórico-práctico de técnicas artísticas para la generación de obras de arte escolar y las herramientas virtuales en línea para la construcción y montaje en red de la propuesta museográfica 2D y 3D. Como resultado se crea el Museo Virtual de Arte Salesiano con más de 1000 obras.

Ship-type identification in a maritime context can be critical to the authorities to control the activities being carried out. Although Automatic Identification Systems has been mandatory for certain vessels, if a vessel does not have them voluntarily or not, it can lead to a whole set of problems, which is why the use of tracking alternatives such as radar is fully complementary for a vessel monitoring systems. However, radars provide positions, but not what they are detecting. Having systems capable of adding categorical information to radar detections of vessels makes it possible to increase control of the activities being carried out, improve safety in maritime traffic, and optimize on-site inspection resources on the part of the authorities. This paper addresses the binary classification problem (fishing ships versus all other vessels) using unbalanced data from real vessel trajectories. It is performed from a deep learning approach comparing two of the main trends, Convolutional Neural Networks and Long Short-Term Memory. In this paper, it is proposed the weighted cross-entropy methodology and compared with classical data balancing strategies. Both networks show high performance when applying weighted cross-entropy compared with the classical machine learning approaches and classical balancing techniques. This work is shown to be a novel approach to the international problem of identifying fishing ships without context.