Abstract
First responders such as firefighters are exposed to extreme stress and fatigue situations during their work routines. It is thus desirable to monitor their health using wearable sensing but this is a complex and still unsolved research challenge that requires large amounts of properly annotated physiological signals data. In this paper we show that the information gathered by our Vital Analysis Framework can support the annotation of these vital signals with the stress levels perceived by the target user, confirmed by the analysis of more than 4600 hours of data collected from real firefighters in action, including 717 answers to event questionnaires from a total of 454 different events.

Abstract
Nowadays it's common to find the same place covered by multiple access networks. For that reason, mobile terminals are normally equipped with multiple network interfaces, which allow users to take advantage of the heterogeneity of those networks. This paper presents an architecture capable of using, in a simultaneous way, the multiple network interfaces existent in the mobile terminal for accessing a video streaming service. With this goal in mind, a solution on the session layer was developed, allowing the creation of an abstraction layer for the intervening applications. The purposed solution is composed by two modules, responsible for the division and aggregation of the transmitted data through multiple interfaces. The obtained results show that the developed architecture is not only capable of interconnecting two machines through multiple interfaces in a simultaneous way, but it is also capable of processing a video stream division in an intelligent way, accordingly to the network conditions. © 2012 University of Split.

Abstract

Abstract

Abstract
In the last few years the research community has witnessed significant progress in biometric technology, due to the availability of a wide variety of databases. However, the available databases that are currently available present significant setbacks in terms of restricted access to data, low-resolution and restrictions imposed on individuals during the acquisition phase. In this paper, two new public databases are described that have been created, with fingerprint and palm print images and their characteristics are compared with other databases available in the research community. The advantages of these databases are the great variety of individual characteristics, they have no restrictions during acquisition and they have manual ground truth annotation. They were presented in two different international competitions and have been used in research by different authors.

Abstract
First responders are professionals that are exposed to extreme stress and fatigue during extended periods of time. That is why it is necessary to research and develop technological solutions based on wearable sensors that can continuously monitor the health of these professionals in action, namely their stress and fatigue levels. In this paper we present the Vital Analysis smartphone-based framework, integrated into the broader Vital Responder project, that allows the annotation and contextualization of the signals collected during real action. After a contextual study we have implemented and deployed this framework in a firefighter team with 5 elements, from where we have collected over 3300 hours of annotations during 174 days, covering 382 different events. Results are analysed and discussed, validating the framework as a useful and usable tool for annotating biological signals of first responders in action.