Privacy-Friendly Mobility Analytics using Aggregate Location Data

Location data can be extremely useful to study commuting patterns and disruptions, as well as to predict real-time traffic volumes. At the same time, however, the fine-grained collection of user locations raises serious privacy concerns, as this can reveal sensitive information about the users, such as, life style, political and religious inclinations, or even identities. In this paper, we study the feasibility of crowd-sourced mobility analytics over aggregate location information: users periodically report their location, using a privacy-preserving aggregation protocol, so that the server can only recover aggregates -- i.e., how many, but not which, users are in a region at a given time. We experiment with real-world mobility datasets obtained from the Transport For London authority and the San Francisco Cabs network, and present a novel methodology based on time series modeling that is geared to forecast traffic volumes in regions of interest and to detect mobility anomalies in them. In the presence of anomalies, we also make enhanced traffic volume predictions by feeding our model with additional information from correlated regions. Finally, we present and evaluate a mobile app prototype, called Mobility Data Donors (MDD), in terms of computation, communication, and energy overhead, demonstrating the real-world deployability of our techniques.Comment: Published at ACM SIGSPATIAL 201

Alcohol approach tendencies in heavy drinkers: comparison of effects in a relevant stimulus-response compatibility task and an approach/avoidance Simon task

Several recent studies suggest that alcohol-related cues elicit automatic approach tendencies in heavy drinkers. A variety of tasks have been used to demonstrate these effects, including Relevant Stimulus-Response Compatibility (R-SRC) tasks and variants of Simon tasks. Previous work with normative stimuli suggests that the R-SRC task may be more sensitive than Simon tasks because the activation of approach tendencies may depend on encoding of the stimuli as alcohol-related, which occurs in the R-SRC task but not in Simon tasks. Our aim was to directly compare these tasks for the first time in the context of alcohol use. We administered alcohol versions of an R-SRC task and a Simon task to 62 social drinkers, who were designated as heavy or light drinkers based on a median split of their weekly alcohol consumption. Results indicated that, compared to light drinkers, heavy drinkers were faster to approach, rather than avoid, alcohol-related pictures in the R-SRC task but not in the Simon task. Theoretical implications and methodological issues are discussed

Using image-based modelling (SfM-MVS) to produce a 1935 ortho-mosaic of the Ethiopian highlands

Approximately 34,000 aerial photographs covering large parts of Ethiopia and dating back to 1935-1941 have been recently recovered. These allow investigating environmental dynamics for a past period that until now is only accessible from terrestrial photographs or narratives. As the archive consists of both oblique and vertical aerial photographs that cover rather small areas, methods of image-based modelling were used to orthorectify the images. In this study, 9 vertical and 18 low oblique aerial photographs were processed as an ortho-mosaic, covering an area of 25 km(2), west of Wukro town in northern Ethiopia. Using 15 control points (derived from Google Earth), a Root Means Square Error of 28.5 m in X 35.4 m in Y were achieved. These values can be viewed as optimal, given the relatively low resolution and poor quality of the imagery, the lack of metadata, the geometric quality of the Google Earth imagery and the recording characteristics. Land use remained largely similar since 1936, with large parts of the land being used as cropland or extensive grazing areas. Most remarkable changes are the strong expansion of the settlements as well as land management improvements. In a larger effort, ortho-mosaics covering large parts of Ethiopia in 1935-1941 will be produced