73 research outputs found

    Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

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    Potential crowd flow prediction for new planned transportation sites is a fundamental task for urban planners and administrators. Intuitively, the potential crowd flow of the new coming site can be implied by exploring the nearby sites. However, the transportation modes of nearby sites (e.g. bus stations, bicycle stations) might be different from the target site (e.g. subway station), which results in severe data scarcity issues. To this end, we propose a data driven approach, named MOHER, to predict the potential crowd flow in a certain mode for a new planned site. Specifically, we first identify the neighbor regions of the target site by examining the geographical proximity as well as the urban function similarity. Then, to aggregate these heterogeneous relations, we devise a cross-mode relational GCN, a novel relation-specific transformation model, which can learn not only the correlations but also the differences between different transportation modes. Afterward, we design an aggregator for inductive potential flow representation. Finally, an LTSM module is used for sequential flow prediction. Extensive experiments on real-world data sets demonstrate the superiority of the MOHER framework compared with the state-of-the-art algorithms.Comment: Accepted by the 35th AAAI Conference on Artificial Intelligence (AAAI 2021

    Search for light dark matter from atmosphere in PandaX-4T

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    We report a search for light dark matter produced through the cascading decay of η\eta mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne⋅\cdotyear exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at 5.9×10−37cm25.9 \times 10^{-37}{\rm cm^2} for dark matter mass of 0.10.1 MeV/c2/c^2 and mediator mass of 300 MeV/c2/c^2. The lowest upper limit of η\eta to dark matter decay branching ratio is 1.6×10−71.6 \times 10^{-7}
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