Dynamic fator Models for bivariate Count Data: an application to fire activity

The study of forest re activity, in its several aspects, is essencial to understand the phenomenon and to prevent environmental public catastrophes. In this context the analysis of monthly number of res along several years is one aspect to have into account in order to better comprehend this tematic. The goal of this work is to analyze the monthly number of forest res in the neighboring districts of Aveiro and Coimbra, Portugal, through dynamic factor models for bivariate count series. We use a bayesian approach, through MCMC methods, to estimate the model parameters as well as to estimate the common latent factor to both series.

Forwarding and security in vehicular networks

The growing research in vehicular network solutions provided the rise of interaction in these highly dynamic environments in the market. The developed architectures do not usually focus, however, in security aspects. Common security strategies designed for the Internet require IP. Since nodes' addresses in a vehicular network are too dynamic, such solutions would require cumbersome negotiations, which would make them unsuitable to these environments. The objective of this dissertation is to develop, and test a scalable, lightweight, layer 3 security protocol for vehicular networks, in which nodes of the network are able to set up long-term security associations with a Home Network, avoiding session renegotiations due to lack of connectivity and reduce the protocol stacking. This protocol allows to provide security independent of the nodes (vehicles) position, of its addressing and of the established path to access the Internet, allowing the mobility of vehicles and of its active sessions seamlessly without communication failures.