In a world increasingly torn by conflict, our proof of concept app OPENPORT is a digital lifeline for those navigating the asylum process. Whether you're a displaced refugee, an EU commissioner allocating aid, or a lawyer offering pro bono support, our platform delivers tailored insights from our extensive global asylum database.
Our app features 2 machine learning models, a logistic regression model for the asylum seeker persona, and a time series autoregression model under the EU commissioner persona. Both models used data from the Eurostat API. The only other page with real data is the "See Decision Stats per Capita" page under the EU Commissioner persona. It contains data from the Eurostat API and the World Bank. All other data shown on the app is mock data.
Mahika Modi, Alp Berrak, Jessica Poblete, Elianne Mejia
Before running the containers, make sure you create the following secret file in the secrets/ directory:
.env- Contains environment variables for MySQL database setup
- Example contents:
MYSQL_ROOT_PASSWORD=password MYSQL_DATABASE=rethread_db MYSQL_USER=rethread_user MYSQL_PASSWORD=rethread_pass
To start the backend, database, and frontend:
docker compose up -d
Inside the root folder, create a .env file with the following contents: DB_USER=root DB_HOST=db DB_PORT=3306 DB_NAME=openport_database
Start Docker Containers Use Docker Compose to start all containers: docker compose up -d
https://droidbait66.github.io/Team10/
Jessica Poblete: Logistic regression model and UI for the app Elianne Mejia: Asylum persona and the connections between the lawyer persona and asylum persona Alp Berrak: Commissioner persona and the connections between the lawyer persona and comissioner persona Mahika Modi: Time series autoregression model and preprocessing of the logistic regression model's data