963 resultados para Tangible interfaces


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El art??culo forma parte de la secci??n ???Discursos y contextos??? del monogr??fico ???Los contenidos???.

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Selenium (Se) is an element with important health implications that is emitted in significant amounts from volcanoes. Attracted by the fertility of volcanic soils, around 10% of the world population lives within 100 km of an active volcano. Nevertheless, the behaviour of Se in volcanic environments is poorly understood. Therefore, the main aim of this thesis is to investigate the role of soils in the Se cycling in volcanic environments. Prior to the geochemical studies, precise and accurate methods for the determination of Se contents, speciation and isotopic signatures were developed. Afterwards, a combination of field studies and lab controlled experiments were performed with soils from two contrasting European volcanic settings: Mount Etna in Sicily (Italy) and Mount Teide in Tenerife (Spain). The results showed a strong link between Se behaviour and soil development, indicating that Se mobility in volcanic soils is controlled by sorption processes and soil mineralogy.

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Abstract. Different types of mental activity are utilised as an input in Brain-Computer Interface (BCI) systems. One such activity type is based on Event-Related Potentials (ERPs). The characteristics of ERPs are not visible in single-trials, thus averaging over a number of trials is necessary before the signals become usable. An improvement in ERP-based BCI operation and system usability could be obtained if the use of single-trial ERP data was possible. The method of Independent Component Analysis (ICA) can be utilised to separate single-trial recordings of ERP data into components that correspond to ERP characteristics, background electroencephalogram (EEG) activity and other components with non- cerebral origin. Choice of specific components and their use to reconstruct “denoised” single-trial data could improve the signal quality, thus allowing the successful use of single-trial data without the need for averaging. This paper assesses single-trial ERP signals reconstructed using a selection of estimated components from the application of ICA on the raw ERP data. Signal improvement is measured using Contrast-To-Noise measures. It was found that such analysis improves the signal quality in all single-trials.