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Sökning: WFRF:(Arribas Bel D.)

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1.
  • Arribas-Bel, D., et al. (författare)
  • Cyber Cities : Social Media as a Tool for Understanding Cities
  • 2015
  • Ingår i: Applied Spatial Analysis and Policy. - : Springer Science+Business Media B.V.. - 1874-463X .- 1874-4621. ; 8:1, s. 231-247
  • Tidskriftsartikel (refereegranskat)abstract
    • ‘Big’ urban data are increasingly becoming accessible for scientific research and policy use. They may enhance the intelligence that is needed for understanding and mapping out social connectivity phenomena (in the sense of Jane Jacobs) in modern smart cities. The present paper aims to highlight and demonstrate the rich potential of information based on digital technology in modern cities. As a case study example of the power of social media data as a support tool in smart cities, we consider Twitter data in the municipality of Amsterdam. We use machine learning techniques to identify temporal patterns that we then relate back to their spatial dimension, effectively connecting the digital with physical aspect of cities. We also show that analysis of geo-referenced tweets can shed significant light on physical aspects of the city and on the spatial distribution of urban functions.
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2.
  • Thompson, Robin N., et al. (författare)
  • Key questions for modelling COVID-19 exit strategies
  • 2020
  • Ingår i: Proceedings of the Royal Society of London. Biological Sciences. - : The Royal Society. - 0962-8452 .- 1471-2954. ; 287:1932
  • Tidskriftsartikel (refereegranskat)abstract
    • Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.
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