19 research outputs found

    Tune in to your emotions: a robust personalized affective music player

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    The emotional power of music is exploited in a personalized affective music player (AMP) that selects music for mood enhancement. A biosignal approach is used to measure listeners’ personal emotional reactions to their own music as input for affective user models. Regression and kernel density estimation are applied to model the physiological changes the music elicits. Using these models, personalized music selections based on an affective goal state can be made. The AMP was validated in real-world trials over the course of several weeks. Results show that our models can cope with noisy situations and handle large inter-individual differences in the music domain. The AMP augments music listening where its techniques enable automated affect guidance. Our approach provides valuable insights for affective computing and user modeling, for which the AMP is a suitable carrier application

    The Physics of the B Factories

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    The BaBar detector: Upgrades, operation and performance

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    Contains fulltext : 121729.pdf (preprint version ) (Open Access

    A Review of Factors Influencing Whole-Body Vibration Injuries in Forestry Mobile Machine Operators

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    Mobile machine operators in the forestry industry are subjected to long hours of whole-body vibration exposure while adopting static seated postures and performing repeated hand and foot movements to operate controls. These conditions have been found to put operators at increased risk for musculo-skeletal injuries and pain in the neck, shoulders, and back, as well as decreased productivity. This paper provides a review of the individual risk factors for these musculoskeletal problems and explores the possible interactions between risk factors and their effects on injury and productivity. Gaps in the literature and directions for future research are identified and discussed
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