7 resultados para Listen

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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INTRODUCTION: Experience-based adaptation of emotional responses is an important faculty for cognitive and emotional functioning. Professional musicians represent an ideal model in which to elicit experience-driven changes in the emotional processing domain. The changes of the central representation of emotional arousal due to musical expertise are still largely unknown. The aim of the present study was to investigate the electroencephalogram (EEG) correlates of experience-driven changes in the domain of emotional arousal. Therefore, the differences in perceived (subjective arousal via ratings) and physiologically measured (EEG) arousal between amateur and professional musicians were examined. PROCEDURE: A total of 15 professional and 19 amateur musicians listened to the first movement of Ludwig van Beethoven's 5th symphony (duration=∼7.4min), during which a continuous 76-channel EEG was recorded. In a second session, the participants evaluated their emotional arousal during listening. In a tonic analysis, we examined the average EEG data over the time course of the music piece. For a phasic analysis, a fast Fourier transform was performed and covariance maps of spectral power were computed in association with the subjective arousal ratings. RESULTS: The subjective arousal ratings of the professional musicians were more consistent than those of the amateur musicians. In the tonic EEG analysis, a mid-frontal theta activity was observed in the professionals. In the phasic EEG, the professionals exhibited an increase of posterior alpha, central delta, and beta rhythm during high arousal. DISCUSSION: Professionals exhibited different and/or more intense patterns of emotional activation when they listened to the music. The results of the present study underscore the impact of music experience on emotional reactions.

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Contention-based MAC protocols follow periodic listen/sleep cycles. These protocols face the problem of virtual clustering if different unsynchronized listen/sleep schedules occur in the network, which has been shown to happen in wireless sensor networks. To interconnect these virtual clusters, border nodes maintaining all respective listen/sleep schedules are required. However, this is a waste of energy, if locally a common schedule can be determined. We propose to achieve local synchronization with a mechanism that is similar to gravitation. Clusters represent the mass, whereas synchronization messages sent by each cluster represent the gravitation force of the according cluster. Due to the mutual attraction caused by the clusters, all clusters merge finally. The exchange of synchronization messages itself is not altered by LACAS. Accordingly, LACAS introduces no overhead. Only a not yet used property of synchronization mechanisms is exploited.

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Do you pronounce the /r/ in 'arm'? Do you call a shelf a 'sheuf'? And what on earth is a 'hoddy-doddy'? There is extensive variation in English dialects: this is why your answers to such questions will allow this app to localize your broader dialect region on a map of England. Did your home dialect change over time? Our algorithm is based on historical data from the Survey of English Dialects. If it guesses where you are from correctly, your home dialect has probably remained stable over the past decades. If the guess is far off, however, it is probably because of dialect change. - Can we localize your dialect based on your pronunciation of 26 words? - Record your dialect and listen to recordings of other users and to historical dialect recordings! - Choose a pronunciation variant, e.g. 'sheuf', and discover where in England it is used...or choose a place and explore its dialect!

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In every conversation you have, there is an unspoken code – a set of social rules that guide you. When to stop talking, where to look, when to listen and when to talk…