The temporal association dynamics between Global mobility and COVID-19 cases highlighted the significance of high-page rank centrality countries in mobility networks as a key intervention target in controlling infection spread.
Our analysis revealed that movement embeddings accurately represented the movement patterns of countries, with geographically proximate countries exhibiting similar movement patterns.
Our methodology utilizes Meta’s “Travel Patterns” dataset to capture the daily number of individuals traveling between countries from March 2020 to April 2022.
Exciting news! 🎉 Our paper (under guidance of Prof @Tavpritesh ) on developing effective pandemic surveillance systems by extracting scalable graph features from mobility networks is now available on pre-print. Here's a quick summary of our findings: (a🧵)
Prepare to learn new tools that every developer needs to manage and maintain their projects. In conjunction with GDSC IIIT Bhopal, GNU/Linux Users Club IIIT Bhopal offers Intro to GIT & GITHUB.
#guc#gdsc#iiit#iiitbhopal#linux#github#git
On this International Women's Day, let's celebrate the brilliant minds of women in tech who have shattered glass ceilings and made groundbreaking contributions to the world of Linux. They inspire future generations to break barriers and pursue their dreams.
#WomensDay#Linux