Delphi study for the design and validation of a questionnaire about digital competences in higher education

The study of digital competence remains an issue of interest for both the scientific community and the supranational political agenda. This study uses the Delphi method to validate the design of a questionnaire to determine the perceived importance of digital competence in higher education. The questionnaire was constructed from different framework documents in digital competence standards (NETS, ACLR, UNESCO). The triangulation of non-parametric techniques made it possible to consolidate the results obtained through the Delphi panel, the suitability of which was highlighted through the expert competence index (K). The resulting questionnaire emerges as a good tool for undertaking future national and international studies on digital competence in higher education.

Redes sociales en industrias culturales: opiniones desde la praxis

Tanto por el público al que se dirigen como por el tipo de «producto» que ofrecen, las industrias culturales pueden obtener múltiples ventajas con el uso de las redes sociales. En el presente estudio analizamos el papel que juegan las redes sociales online en las empresas culturales a través de la opinión de cualificados expertos en redes sociales y con el método Delphi. Las conclusiones revelan que, en el ámbito de las empresas culturales, existe una prevalencia de los usos utilitarios sobre los expresivos y de las motivaciones proactivas sobre las reactivas, con referencia a las redes sociales.

Social networks in cultural industries

Although cultural industries can benefit from social networks in many ways, few Spanish studies examine the extent to which firms within this economic sector actually use such networks. This study's objective is to investigate the role of online social networks in Spanish cultural firms. The study begins with a literature review on cultural industries and social networks. Then the study proceeds to a Delphi analysis that draws upon experts' opinions. Results reveal a predominance of utilitarian uses over expressive ones, as well as an overriding use of proactive motivations rather than reactive ones within the context of cultural firms' use of social networks. The study confirms the profitability of these networks and the transfer of influence or power from providers to the consumers of cultural goods and services.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

A connectionist computational method for face recognition

In this work, a modified version of the elastic bunch graph matching (EBGM) algorithm for face recognition is introduced. First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the fiducial points for the facial graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector defining each face. A self-organizing map (SOM) framework is shown afterwards. Thus, the calculation of the winning neuron and the recognition process are performed by using a similarity function that takes into account both the geometric and texture information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our proposal when compared with other state-of the-art methods.