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Publications

Publications by Mafalda Rodrigues Castro

2022

Digital Twin for Monitoring Containerized Hazmat Cargo in Port Areas

Authors
Oliveira, L; Castro, M; Ramos, R; Santos, J; Silva, J; Dias, L;

Publication
2022 17TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)

Abstract
The complexity of the number of stakeholders, information systems used, and port operations evoke new challenges to port security when it comes to the total knowledge and control of the overall operations of transport and parking of containerized freight, namely hazmat ones. The rising interest and the port authorities' awareness of the relevance of security concerns involved in this complex ecosystem has led to the search for new technological solutions that allow, in an integrated manner, the smart and automatic control of operations of transport and hazardous freight parking in all the areas of its jurisdiction, without third-party dependencies. Despite its importance and criticality, port authorities tend to have limited real-time knowledge of the location of hazmat containers, whether moving within the port (entering and leaving), or in its parking, having a direct impact on the port security. This article presents a Digital Twin platform for 3D and real-time georeferenced visualization of container parks and the location of hazardous containerized freight. This tool combines different modules that further allow to visualize information associated to a container, its movement, as well as its surrounding area, including a realistic and dynamic 3D representation of what is the area encircling the port.

2023

TweetStream2Story: Narrative Extraction from Tweets in Real Time

Authors
Castro, M; Jorge, A; Campos, R;

Publication
ADVANCES IN INFORMATION RETRIEVAL, ECIR 2023, PT III

Abstract
The rise of social media has brought a great transformation to the way news are discovered and shared. Unlike traditional news sources, social media allows anyone to cover a story. Therefore, sometimes an event is already discussed by people before a journalist turns it into a news article. Twitter is a particularly appealing social network for discussing events, since its posts are very compact and, therefore, contain colloquial language and abbreviations. However, its large volume of tweets also makes it impossible for a user to keep up with an event. In this work, we present TweetStream2Story, a web app for extracting narratives from tweets posted in real time, about a topic of choice. This framework can be used to provide new information to journalists or be of interest to any user who wishes to stay up-to-date on a certain topic or ongoing event. As a contribution to the research community, we provide a live version of the demo, as well as its source code.