Aitzol Ezeiza

Electric vehicles (EVs) are emerging as one of the pillars for achieving climate neutrality. They represent both a threat and an opportunity for the operation of the network. Used as flexible loads, they can favor the self-consumption of photovoltaic (PV) energy. This paper presents three EV charging tariff systems (TSs) based on the self-consumption of excess PV energy. The TS objectives are to increase the self-consumption rate (SCR) and thus indirectly decrease the charging cost of the EV users. Two of the proposed TSs correspond to an indirect control of EV charging. The third TS is a hybrid system where the charging power is controlled. The TS is designed using a series of rules that consider the momentary PV surplus and the charging power of each EV. The influence of the TS is simulated by considering real data from a PV collective self-consumption project in the Basque Country (Spain). The TS simulations performed with 6 months of data show a 13.1% increase in the SCR when applying the third TS, reaching an average of 93.09% for the SCR. In addition, the cost of EV charging is reduced by 25%.

Information about the paper titled "HOW TO ENCOURAGE STUDENTS TO LEARN INDUSTRIAL INFORMATION TECHNOLOGY ON THEIR OWN. ONLINE RESOURCES AND ENTICING EXERCISES" at IATED Digital Library

Information about the paper titled "“CONGRATULATIONS! YOU HAVE EARNED A BADGE”: HOW TO ENGAGE STUDENTS WITH GAMIFICATION AND DIGITAL BADGES" at IATED Digital Library

This paper proposes a multilingual audio information management system based on semantic knowledge in complex environments. The complex environment is defined by the limited resources (financial, material, human, and audio resources); the poor quality of the audio signal taken from an internet radio channel; the multilingual context (Spanish, French, and Basque that is in under-resourced situation in some areas); and the regular appearance of cross-lingual elements between the three languages. In addition to this, the system is also constrained by the requirements of the local multilingual industrial sector. We present the first evolutionary system based on a scalable architecture that is able to fulfill these specifications with automatic adaptation based on automatic semantic speech recognition, folksonomies, automatic configuration selection, machine learning, neural computing methodologies, and collaborative networks. As a result, it can be said that the initial goals have been accomplished and the usability of the final application has been tested successfully, even with non-experienced users.

The present work describes the development of an LID system suited for handling security tasks in the Internet. The development context was the Infozazpi Internet digital radio, and the task presented substantial complexity due to the trilingual environment and the scarcity of language resources for Basque. In order to overcome previous difficulties, we propose a hybrid system based on the selection of subword units by SVMs, MLP classifiers, and discriminant analysis improved with robust regularized covariance matrix estimation methods and stochastic methods for ASR tasks (SC-HMM and n-grams). Our new subword unit proposals and the use of triphones and cross-lingual approaches considerably improve the system performance, achieving an optimal and stable LID recognition rate despite the complexity of the problem.

Alzheimer's disease (AD) is the most prevalent form of progressive degenerative dementia. Its diagnosis made by analyzing many biomarkers and test but nowadays a definitive confirmation requires a post-mortem examination of the patients' brain tissue. The purpose of this paper is to examine the potential of applying intelligent algorithms to the results obtained from non-invasive analysis methods on suspected patients in order to contribute to the improvement of both early diagnosis of AD and its degree of severity. This work deals with Emotional Response Automatic Analysis (ERAA) based on classical and new speech features: Emotional Temperature (ET) and Higuchi Fractal Dimension (FD). The method has the great advantage of being, in addition to non-invasive, of low cost and without any side effects. This is a pre-clinic studio oriented to validate future diagnosis tests and biomarkers. ERAA showed very satisfactory and promising results for the definition of features oriented to early diagnosis of AD.

The conservation and preservation of biodiversity, its global and fair use, ensures the survival of the planet and ultimately ours. Taken into account the tools provided by scientific and technological developments and increasing concern for environmental conservation, it is of great relevance to identify appropriate technological tools for environmental sustainability. Moreover it is essential establishing certain protocols for their implementation and use. For this reason specialists in intelligent automatic systems, in biology and engineers have been working together for several years in this issue. This paper presents the first steps towards the development of a biometric system based on ultrasound for identification of bat calls in the Basque Country. They have been carried out three different kind of identification with regard to: specie, individual and behaviour.