25 research outputs found

    Interactivity : Using Expressy to Demonstrate Expressiveness in Touch-based Interactions

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    We present an interactivity demonstration of Expressy. A system that augments existing touchscreen devices with a variety of continuous expressive interaction capabilities, using movement data from a wrist-worn IMU. Our demonstration comprises a set of applications that show how the expressive touch interaction capabilities, offered by Expressy, can enable intuitive and meaningful interactions, in contexts including productivity, entertainment and lifestyle apps. This demo submission accompanies a full paper, describing a conceptual model of expressive touch interaction and the implementation and evaluation of Expressy. © 2016 Authors

    Optoelectronic analogue signal transfer for LHC detectors, 1991

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    We propose to study and develop opto-electronic analogue front-ends based on electro-optic intensity modulators. These devices translate the detector electrical analogue signals into optical signals which are then transferred via optical fibres to photodetector receivers at the remote readout. In comparison with conventional solutions based on copper cables, this technique offers the advantages of high speed, very low power dissipation and transmission losses, compactness and immunity to electromagnetic interference. The linearity and dynamic range that can be obtained are more than adequate for central tracking detectors, and the proposed devices have considerable radiation- hardness capabilities. The large bandwidth and short transit times offer possibilities for improved triggering schemes. The proposed R&D programme is aimed at producing multi-channel "demonstrator" units for evaluation both in laboratory and beam tests. This will allow the choice of the most effective technology. A detailed study will also be carried out on packaging and interconnection to large arrays of fibres, as well as on the optimization of the processes for the production of large quantities

    Spokespeople: Exploring Routes to Action through Citizen-Generated Data

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