• La Universidad
    • Historia
    • Rectoría
    • Autoridades
    • Secretaría General
    • Pastoral UC
    • Organización
    • Hechos y cifras
    • Noticias UC
  • 2011-03-15-13-28-09
  • Facultades
    • Agronomía e Ingeniería Forestal
    • Arquitectura, Diseño y Estudios Urbanos
    • Artes
    • Ciencias Biológicas
    • Ciencias Económicas y Administrativas
    • Ciencias Sociales
    • College
    • Comunicaciones
    • Derecho
    • Educación
    • Filosofía
    • Física
    • Historia, Geografía y Ciencia Política
    • Ingeniería
    • Letras
    • Matemáticas
    • Medicina
    • Química
    • Teología
    • Sede regional Villarrica
  • 2011-03-15-13-28-09
  • Organizaciones vinculadas
  • 2011-03-15-13-28-09
  • Bibliotecas
  • 2011-03-15-13-28-09
  • Mi Portal UC
  • 2011-03-15-13-28-09
  • Correo UC
- Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log in
    Log in
    Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log in
    Log in
    Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Gutiérrez González, Felipe Iván"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Identifying outbreaks in sewer networks: An adaptive sampling scheme under network's uncertainty
    (2024) Baboun Larach, José; Beaudry, Isabelle S.; Castro Cepero, Luis Mauricio; Gutiérrez González, Felipe Iván; Jara Vallejos, Alejandro Antonio; Rubio Orellana, Benjamín Eduardo; Verschae, José
    Motivated by the implementation of a SARS-Cov-2 sewer surveillance system in Chile during the COVID-19 pandemic, we propose a set of mathematical and algorithmic tools that aim to identify the location of an outbreak under uncertainty in the network structure. Given an upper bound on the number of samples we can take on any given day, our framework allows us to detect an unknown infected node by adaptively sampling different network nodes on different days. Crucially, despite the uncertainty of the network, the method allows univocal detection of the infected node, albeit at an extra cost in time. This framework relies on a specific and well-chosen strategy that defines new nodes to test sequentially, with a heuristic that balances the granularity of the information obtained from the samples. We extensively tested our model in real and synthetic networks, showing that the uncertainty of the underlying graph only incurs a limited increase in the number of iterations, indicating that the methodology is applicable in practice.

Bibliotecas - Pontificia Universidad Católica de Chile- Dirección oficinas centrales: Av. Vicuña Mackenna 4860. Santiago de Chile.

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback