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Much research in ubiquitous computing assumes that a user's phone will be always on and at-hand, for collecting user context and for communicating with a user. Previous work with the previous generation of mobile phones has shown that such an assumption is false. Here, we investigate whether this assumption about users' proximity to their mobile phones(More)
With advances in physiological sensors, we are able to understand people's physiological status and recognize stress to provide beneficial services. Despite the great potential in physiological stress recognition, there are some critical issues that need to be addressed such as the sensitivity and variability of physiology to many factors other than stress(More)
In today's ubiquitous computing environment where the number of devices, applications and web services are ever increasing, human attention is the new bottleneck in computing. To minimize user cognitive load, we propose Attelia, a novel middleware that identifies breakpoints in user interaction and delivers notifications at these moments. Attelia works in(More)
In today's ubiquitous computing environment where users carry, manipulate, and interact with an increasing number of networked devices, applications and web services, human attention is the new bottleneck in computing. It is therefore important to minimize a user's mental effort due to notifications, especially in situations where users are mobile and using(More)
BACKGROUND Physicians of the Spanish Influenza Sentinel Surveillance System report and systematically swab patients attended to their practices for influenza-like illness (ILI). Within the surveillance system, some Spanish regions also participated in an observational study aiming at estimating influenza vaccine effectiveness (cycEVA study). During the(More)
In this paper we present a novel scheme for unstructured audio scene classification that possesses three highly desirable and powerful features: autonomy, scalability, and robustness. Our scheme is based on our recently introduced machine learning algorithm called Simultaneous Temporal And Contextual Splitting (STACS) that discovers the appropriate number(More)
BACKGROUND In Spain, the influenza vaccine effectiveness (VE) was estimated in the last three seasons using the observational study cycEVA conducted in the frame of the existing Spanish Influenza Sentinel Surveillance System. The objective of the study was to estimate influenza vaccine effectiveness (VE) against medically attended, laboratory-confirmed(More)