Research group focused on the analysis of the changes and mutations caused by the digitalisation process in the contents and structures of the media and the public. The group arose from the activity of most of its researchers, since 2007, within the framework of the ‘Analysis Group of the Valencian Digital Media’ (since 2007), which has led to the achievement of three R&D projects (financed by the Generalitat Valenciana and the Universitat de València) and an annual congress (Digital Communication Congress in the Valencian Community), which began to be held in 2009. All this resulted in five monographs and an abundant number of partial publications in congresses, journals and book chapters.
In addition, the group has obtained a R&D project of the National R&D&I Plan, granted in the 2013 call, and which covers the period from 2014 to 2016. The title of the project is ‘Communication flows in political mobilisation processes: media, blogs and opinion leaders’ (reference CSO2013-43960-R). The research related to this project constitutes the critical point of the group's research. This group’s research mainly focuses on influence: who influences whom, in what way, and with what effects. We focus on the flows through which information circulates because they will allow us to see this process of translating messages and combining agendas, which all try to influence the public space. We seek to see which ones are more influential and in which direction, or directions, the flow of information transmission takes place.
The Digital Design and Processing Group of the Universitat de València focuses its research on digital signal processing and the application of digital processing techniques in fields such as Biomedical Engineering, industrial systems and hardware architectures for the implementation of real-time algorithms.
The team works in four main related and simultaneously complementary research lines:
- Pattern Recognition Techniques, Computer Vision and its applications for different problems, mainly content-based image search, distance learning and emotion detection from video sequences.
- Processing of different types of signals, particularly audio and video ones. Group works in this research line include capture, analysis and synthesis of acoustic signals, as well as analysis of video signals, all acting in coordination with the Computer Vision line.
- Design of Intelligent Tutoring Systems (ITSs) with affective capacities. Part of the results obtained from the first and second line of work are used to detect emotions from videos filmed with low-cost hardware by applying techniques specific to the fields of Signal Processing and Computer Vision.
- High-performance and high-availability computer systems offering a fundamental tool for all the previously mentioned fields (pattern recognition, intelligent systems and signal processing) by providing the necessary power in real time whenever required from application areas or in case of high system availability requirements. In this regard, the latest trends focus on distributed systems, the handling of Big Data and the so-called “cloud computing”: three fundamental aspects in the context of group investigation.
The ISP research group, http://isp.uv.es, has a long tradition in statistical analysis of data coming from imaging systems. These measurements depend on the properties of the scenes and the physics of the imaging process, and their relevance depends on the (natural or artificial) observer that will analyze the data. Our distinct approach to signal, image and vision processing combines machine learning theory with the understanding of the underlying physics and biological vision. Applications mainly focus on optical remote sensing and computational visual neuroscience. Empirical statistical inference, also known as machine learning, is a field of computer science interested in making predictions, and models from observations and sensory data. The information processing tools in machine learning are critical to understand the function of natural neural networks involved in biological vision, as well as to make inferences in complex dynamic network systems, such as the Earth biosphere, atmosphere, and ecosystems.
Problems in Visual Neuroscience and in Remote Sensing based geosciences require similar mathematical tools. For example, both scientific fields face model inversion and model understanding problems. In both cases, one has a complex forward model that is difficult to invert (to extract information from) either because it is not analytically invertible (undetermined) or because the measurements (or responses) are noisy in nature. In Remote Sensing, the forward model is the imaging process given certain state conditions in the surface and atmosphere. In Visual Neuroscience, the forward model includes what is known in the neural pathway from the retina to the different regions of the visual cortex. Inversion of such models is key to make quantitative and meaningful inferences about the underlying system that generated the observed data. Beyond such quantitative assessment, a qualitative interpretation of the proposed models is mandatory as well. Qualitative understanding is more challenging than prediction, and causal inference from empirical data is the common playground both in geoscience and neuroscience. Simultaneous observations and recordings from a phenomenon lead to multidimensional signals that may display strong statistical correlation between the components. However, correlation is not enough to establish cause-effect relationships. This is key when analyzing activation and inhibition in the communication between different brain regions, and it is also of paramount relevance when studying the causes, effects and confounders of essential climate variables for detection and attribution in climate science. Finally, another parallelism is the analysis of big visual data: hyperspectral imagery acquired by current and upcoming satellite sensors pose a big-data information processing problem in similar ways to that in the visual brain. Adaptation, pattern recognition, inference and decision making in the brain may be quite inspiring for remote sensing image analysis.
The group is therefore organized into a theoretical research branch (A) and a more applied research branch (B). The theoretical machine learning core tackles model inversion, interpretation, causal inference from empirical data and inclusion of physical constraints and prior knowledge in big visual data. The applied research lines are devoted to apply and adapt the theoretrical developments for remote sensing, geociences and visual neuroscience. For the sake of simplicity, we have grouped together these activities along five conceptual research lines: machine learning, visual neuroscience, image processing, remote sensing and big data processing.
The main purpose of IDAL is the study and application of intelligent methods of data analysis for pattern recognition, with applications that struggle with prediction, classification or trend determination.
Its members apply classic statistical methods and automatic learning techniques to large databases: statistical hypothesis testing, linear models, feature selection and extraction, neural networks, clustering algorithms, decision trees, support vector machines, probabilistic graphical models, manifold visualization, fuzzy logic, reinforcement learning, etc.
The ultimate goal of the application of these methods is to generate mathematical models which enable the optimization of processes and resources, as well as to reach the optimal decision making stage. A clear example of this is the area of health, where IDAL has developed clinical decision support application based on data analysis. These applications make it possible to improve the patient’s quality of life (establishing optimal clinical guidelines) while reducing healthcare costs.
Complementing this knowledge, the group has extensive experience in signal processing (spectral analysis, digital filter, adaptive process, etc.) due to their work of over 10 years in biosignal processing (mainly ECG and EEG). With all this background, IDAL is able to analyse a wide range of data and signals. This fact is backed up by the large number of both private and public contracts it has developed in different areas of knowledge. Furthermore, most of the practical work carried out has been displayed in important scientific publications with high impact parameters and in a large number of communications to international congresses within the area of data analysis.
Among the developed applications, (outside the health area already mentioned) are the following, i.a: web recommendations, models for optimal incentive management to gain customer loyalty, measurement-based shoe recommendations, and other data analysis consultancy works. In addition to its practical work IDAL, it develops new data analysis algorithms improving the performance of the existing ones. This research work is also reflected in a wide dissemination in the form of different publications in journals of impact and in congresses of data analysis relevant to the scientific community.
With regard to the motivations of this group for research into music teaching and learning processes, it should be noted that the practical music teaching institutions have been distanced from research into specific music teaching and learning processes. This has not been so much due to their own decision or to the lack of research training of Spanish conservatory teachers -which is a fact-, but rather to the scant importance given to music studies in the different reforms of the Spanish educational system until the LOGSE, as well as to the traditional separation between music practice and research, the former being relegated to music conservatories and the latter to the university. What is more, after the establishment of the so-called Higher Artistic Education within the European Higher Education Area, neither the LOE -and even less the LOMCE- have established effective mechanisms for the research training of music conservatory teachers. As a result, there is a lack of research in conservatories and, as a consequence, little knowledge of what really happens in the teaching and learning processes.
We believe that this is a very important area of expertise in the training of individuals, in addition to its importance in the training of musicians and music teachers. The members of this research group have a long-established track record in different fields of music. Thus, research has been carried out on training processes in music education; on the influence of the use of score editors on the formation of mental images of sound in students; on the effect of multimodal presentations of musical information versus unimodal presentations; on the effects of different modes of information presentation on the learning of musical parameters (texture, melody, rhythm.... ); on the creation of specific software for certain musical tasks and its effects on musical learning; on the influence of music in the media on the stereotypes of primary school pupils; on the use of technology as a mediator in the development of musical skills. All this is materialised in an extensive quality scientific production (publications in impact journals indexed in JCR and Scopus) in the sub-disciplines of music technology, music education, musical creativity, musical performativity and musical cognition. They have also executed European, American (Organización Estados Americanos, CONICYT), national (Plan Nacional i+d+i, FNEA, FONDEF-TIC-EDU (Chile), Fondo Nacional de la Cultura de Chile) and regional (C.Valenciana, Gobierno de La Rioja, Gobierno Vasco, Junta de Andalucía) projects. The members of the group have directed doctoral theses and works related to the aforementioned fields, including works derived from the training capacity of the groups executing R&D projects.
The lines of the group are related to training processes for music education teachers; music education processes in non-formal contexts; dynamisation processes in socio-educational projects through music; technology in music education; software design for music education; science-art interaction; musical performativity and creation.
The master's degrees and postgraduate and doctoral programmes in which members of this group have participated are: Postgraduate course of musical specialisation: ENSENYAMENT MUSICAL MIJANÇANT L'ORDINADOR (UPV-GVA); Postgraduate course of musical specialisation: INFORMÁTICA MUSICAL (Xunta Galicia-U. de A Coruña); Postgraduate course of musical specialisation: LENGUAJE MUSICAL Y EDUCACIÓN AUDITIVA (Gobierno de La Rioja-U. de La Rioja); university postgraduate course of musical specialisation: TEACHING MUSICAL EXPRESSION (Diputación Gral. de Aragón); doctorate course: RESOURCES FOR TRAINING AND CHANGE. TEACHING AND INNOVATIVE STRATEGIES within the Doctorate Programme of the Department of Human Sciences of the University of La Rioja; I University Expert in DESIGN AND CREATION OF VIRTUAL TRAINING ENVIRONMENTS (2004-05. U. of Malaga); II University Expert in Design and Creation of Virtual Training Environments (2005-06. U. of Malaga); II University Expert in Design and Creation of Virtual Training Environments (2005-06. U. of Malaga); III University Expert Course in Design and Creation of Virtual Training Environments (2005-06. U. of Malaga); III University Expert Course in Design and Creation of Virtual Training Environments (2005-06. de Málaga); III University Expert Course on Methods and Resources in Music Education (2005. u. de La Laguna); Doctorate Programme on Methods of Educational Research and Innovation (2005. u. de Málaga); I Master's Degree in New Technologies Applied to Education (U. de Málaga); IV University Expert Course on Methods and Resources in Music Education (2006. u. de La Laguna); II Master's Degree in New Technologies Applied to Education (U. de Málaga); IV Expert Course in Virtual E-learning Environments (U. de Málaga); Master's Degree in Musical Pedagogy (2009. U. de Valencia); Master's Degree in Research in Specific Didactics (University of Valencia. 2010 editions to date); Doctorate in Specific Didactics (U. de Valencia. From 2010 to the present); Master of Research in Musical Skills Development (2010. U. Pública de Navarra); Doctorate Course in Technology and Musical Learning Processes (U. Nacional Autónoma de México. 2011); Master of Research in Musical Skills Development (2011. U. Pública de Navarra); Master and Doctorate Programme in Music. Course on Technology and Musical Learning Processes. (U. Nacional Autónoma de México. 2012); Master of Research in Musical Skills Development (2012. U. Pública de Navarra); Master in Secondary Education Teaching (U. de Valencia. Several editions to date).
Application of work and recovery techniques for musculoskeletal injuries through the use of scientific methodology and modern and up-to-date technological and statistical management. This group includes experts from the fields of physiotherapy, physical education, electronic engineering, physicists and public health experts. Tendon and muscle behaviour will be studied by means of anthropometric assessment, blood and genetic studies, ultrasound scanning and dynamometry by statistical analysis of neural networks and organised maps.
The group's research activity focuses on the design of instrumentation and measurement for radiation detector systems. Specifically, the group applies research in two scientific-technical fields: experimental nuclear physics (AGATA, NEDA and TRACE experiments corresponding to European collaborations) and hospital medical physics (collaborations with the La Fe Hospital, Radiophysics Service, and companies in the sector, specifically in radiotherapy and dosimetry).
As regards experimental nuclear physics (the main activity of the group), the group has extensive experience in the design of electronic instrumentation for nuclear physics experiments (originally in experimental particle physics experiments at CERN, specifically in the DELPHI / LEP and ATLAS / LHC experiments) and participates continuously in the National Programme for Particle Physics and Accelerators.
In terms of activity in medical physics (most recent activity), the group is currently collaborating with the La Fe hospital centre (through the IRIMED IIS La Fe-UV Joint Research Unit), as well as with leading European companies in intraoperative radiotherapy and dosimetry. In parallel to these two research activities, the group has transferred technology to the Valencian productive sector, through collaborations with companies.
As a result of the research carried out within the group, some of its members are co-authors of more than 100 indexed articles, as well as co-authors of 2 working patents and have published several book chapters in major North American publishers.
