Carlos Gomez

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In embedded systems, non-functional and functional aspects are closely related and cannot be considered independently. However, the high complexity of systems requires a large domain of competencies and experts in various domains have to work concurrently on different aspects of the same systems. This is why we propose a multi-view model where each view(More)
Electrification structures design for railway systems is a crucial and complex process, since it compounds plenty of infrastructure elements, design decisions, and calculation conditions. In this paper, an ontologydriven decision support system for designing complex railway portal frames is presented and developed. A knowledge-rules database has been also(More)
Non-functional properties take an important place in real-time systems. Power consumption, time performance and temperature are non-functional properties that are individually analyzed using specialized tools. Nevertheless, non-functional properties are interrelated, and changes on one property may affect the other ones, but also may impact the system(More)
A crucial challenge for scientific workflow management systems is to support the efficient and scalable storage and querying of large provenance datasets that record the history of in silico experiments. As new provenance management systems are being developed, it is important to have benchmarks that can evaluate these systems and provide an unbiased(More)
Our research team has spent the last few years studying the cognitive processes involved in simultaneous interpreting. The results of this research have shown that professional interpreters develop specific ways of using their working memory, due to their work in simultaneous interpreting; this allows them to perform the processes of linguistic input,(More)
To deal with the high complexity of embedded systems, engineers rely on high-level heterogeneous models that combine functional and non-functional aspects, hardware/software artifacts, structural and behavioral descriptions. PRISMSYS is a system-level multi-view modeling framework, which provides a means to specify functional and non-functional aspects in(More)
The aim of this study was to examine the magnetoencephalography (MEG) background activity in Alzheimer's disease (AD) using three embedding entropies: approximate entropy (ApEn), sample entropy (SampEn), and fuzzy entropy (FuzzyEn). These three methods measure the time series regularity. Five minutes of recording were acquired with a 148-channel whole-head(More)
This work presents the design, implementation, and evaluation of a learning platform that addresses two main objectives: first it provides and on-line quiz tool for students which can be used as a complementary learning approach to the classroom courses. Secondly, this tool performs a detailed analysis of learners use, considering not only the number of(More)