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Educational Technologies (EdTech) are based on the use of Information and Communication Technologies (ICT) to improve the quality of teaching and learning. EdTech is experiencing great development at different educational levels worldwide, especially since the appearance of Covid-19. The recent publication of a study by the ICT Sectorial of CRUE Universidades Españolas, the Spanish University Association, is the first report on the implementation of such technologies within Spain´s University System. This paper presents two different maps based on the data from that report. Together, they illustrate the penetration of different types of EdTech in our university system and shed light on the strategic interest behind their adoption. Our goal is to produce self-explanatory maps that can be easily and directly interpreted. The first map reflects wide granularity in terms of the global importance of technologies, while the second points to relevant conclusions given the spatial position of Spain´s universities, and the size of the nodes that represent them (directly related with their strategic interests on EdTech), as well as with the local relationships existing among them (identifying similarities on those strategic interests).

Abstract  Different tasks in forensics require the use of 3D models of forensic objects (skulls, bones, corpses, etc.) captured by 3D range scanners. Since a whole object cannot be completely scanned in a single image using a range scanner, multiple acquisitions from different views are needed to supply the information to construct the 3D model by a range image registration method. There is an increasing interest in adopting evolutionary algorithms as the optimization technique for image registration methods. However, the image registration community tends to separate global and local searches in two different stages, named sequential hybridization approach, which is opposite to the scheme adopted by the memetic framework. In this work, we aim to analyze the capabilities of memetic algorithms (Moscato in On evolution, search, optimization, genetic algorithms and martial arts: towards memeticalgorithms. Report 826, Caltech Concurrent Computation Program, Pasadena, 1989) for tackling a really complex and challenging real-world problem as the 3D reconstruction of forensic objects. Our intention is threefold: firstly, designing new memetic-based methods for tackling a real-world problem and subsequently carrying out a performance and behavioral analysis of the results; secondly, comparing their performance with the one achieved by other methods based on the classical sequential hybridization approach; and thirdly, concluding the experimental study by highlighting the outcomes achieved by the best method in tackling the real-world problem. Several real-world 3D reconstruction problems from the Physical Anthropology Lab at the University of Granada, Spain, were used to support the evaluation study. [ABSTRACT FROM AUTHOR]

The morphological assessment of facial features using photographs has played an important role in forensic anthropology. The analysis of anthropometric landmarks for determining facial dimensions and angles has been considered in diverse forensic areas. Hence, the quantification of the error associated to the location of facial landmarks seems to be necessary when photographs become a key element of the forensic procedure. In this work, we statistically evaluate the inter- and intra-observer dispersions related to the facial landmark identification on photographs. In the inter-observer experiment, a set of 18 facial landmarks was provided to 39 operators. They were requested to mark only those that they could precisely place on 10 photographs with different poses (frontal, oblique, and lateral views). The frequency of landmark location was studied together with their dispersion. Regarding the intra-observer evaluation, three participants identified 13 facial points on five photographs classified in the frontal and oblique views. Each landmark location was repeated five times at intervals of at least 24 h. The frequency results reveal that glabella, nasion, subnasale, labiale superius, and pogonion obtained the highest location frequency in the three image categories. On the contrary, the lowest rate corresponds to labiale inferius and menton. Meanwhile, zygia, gonia, and gnathion were significantly more difficult to locate than other facial landmarks. They produced a significant effect on the dispersion depending on the pose of the image where they were placed, regardless of the type of observer that positioned them. In particular, zygia and gonia presented a statistically greater variation in the three image poses, while the location of gnathion is less precise in oblique view photographs. Hence, our findings suggest that the latter landmarks tend to be highly variable when determining their exact position.

Craniofacial superimposition can provide evidence to support that some human skeletal remains belong or not to a missing person. It involves the process of overlaying a skull with a number of ante mortem images of an individual and the analysis of their morphological correspondence. Within the craniofacial superimposition process, the skull-face overlay stage just focuses on achieving the best possible overlay of the skull and a single ante mortem image of the suspect. Although craniofacial superimposition has been in use for over a century, skull-face overlay is still applied by means of a trial-and-error approach without an automatic method. Practitioners finish the process once they consider that a good enough overlay has been attained. Hence, skull-face overlay is a very challenging, subjective, error prone, and time consuming part of the whole process. Though the numerical assessment of the method quality has not been achieved yet, computer vision and soft computing arise as powerful tools to automate it, dramatically reducing the time taken by the expert and obtaining an unbiased overlay result. In this manuscript, we justify and analyze the use of these techniques to properly model the skull-face overlay problem. We also present the automatic technical procedure we have developed using these computational methods and show the four overlays obtained in two craniofacial superimposition cases. This automatic procedure can be thus considered as a tool to aid forensic anthropologists to develop the skull-face overlay, automating and avoiding subjectivity of the most tedious task within craniofacial superimposition., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)