Participatory privacy: Enabling privacy in participatory sensing

Abstract Participatory Sensing is an emerging computing paradigm that enables the distributed collection of data by self-selected participants. It allows the increasing number of mobile phone users to share local knowledge acquired by their sensor-equipped devices, e.g., to monitor temperature, pollution level or consumer pricing information. While research initiatives and prototypes proliferate, their real-world impact is often bounded to comprehensive user participation. If users have no incentive, or feel that their privacy might be endangered, it is likely that they will not participate. In this article, we focus on privacy protection in Participatory Sensing and introduce a suitable privacy-enhanced infrastructure. First, we provide a set of definitions of privacy requirements for both data producers (i.e., users providing sensed information) and consumers (i.e., applications accessing the data). Then, we propose an efficient solution designed for mobile phone users, which incurs very low overhead. Finally, we discuss a number of open problems and possible research directions

Combining lanekeeping and vehicle following with hazard maps

Abstract This paper addresses the issues involved with including moving obstacles in a hazard map or potential field framework for driver assistance systems. Under such a framework, control forces must consist of either conservative forces obtained from the gradient of a potential or artificial damping. By treating vehicle following as a combination of a safety distance and a hazard or potential function, common following strategies, such as constant time headway and guaranteed collision avoidance, can be incorporated into this framework without modification. When combining these fields with lateral potential fields for lanekeeping, however, challenges arise due to the natural asymmetry between the longitudinal and lateral velocity of a vehicle. For instance, a decision to change lanes while approaching a slow moving vehicle results in a large amount of undesirable energy transfer into the lateral dynamics. By treating the lateral and longitudinal hazards -described in road-fixed coordinates -as decoupled, however, such transfers can be eliminated. Because of the manner in which the lateral and longitudinal dynamics couple, control with decoupled hazard maps resembles the coupled case when following or lanekeeping while eliminating the problems associated with energy transfer. The paper concludes by discussing the characteristics of the dynamic equations that lead to this result and outlining future work in obtaining rigorous hazard bounds for the decoupled controller

Coresets for Nonparametric Estimation -the Case of DP-Means

Abstract Scalable training of Bayesian nonparametric models is a notoriously difficult challenge. We explore the use of coresets -a data summarization technique originating from computational geometry -for this task. Coresets are weighted subsets of the data such that models trained on these coresets are provably competitive with models trained on the full dataset. Coresets sublinear in the dataset size allow for fast approximate inference with provable guarantees. Existing constructions, however, are limited to parametric problems. Using novel techniques in coreset construction we show the existence of coresets for DP-Means -a prototypical nonparametric clustering problem -and provide a practical construction algorithm. We empirically demonstrate that our algorithm allows us to efficiently trade off computation time and approximation error and thus scale DP-Means to large datasets. For instance, with coresets we can obtain a computational speedup of 45× at an approximation error of only 2.4% compared to solving on the full data set. In contrast, for the same subsample size, the "naive" approach of uniformly subsampling the data incurs an approximation error of 22.5%

The potential of high-rate GPS for strong ground motion assessment

We show that high-rate GPS can have a vital role to play in near real-time monitoring of potentially destructive earthquakes. We do this by investigating the potential of GPS in recording strong ground motions from earthquakes in Switzerland and Japan. The study uses finite-fault stochastic ground motion simulation based on Fourier amplitude spectra and duration models previously developed for both countries, allowing comparisons in terms of both Fourier and time domain characteristics (here the Peak Ground Velocity, PGV). We find that earthquakes of magnitude Mw>5.8 can be expected to be recorded by GPS in real-time at 10 km distance, i.e. their Fourier spectrum exceeds the noise of the instruments enough to be used in strong motion seismology. Post-processing of GPS time series lowers the noise and can improve the minimum observable magnitude by 0.1-0.2. As GPS receivers can record at higher rates (> 10 sps), we investigate which sampling rate is sufficient to optimally record earthquake signals and conclude that a minimum sampling rate of 5 sps is recommended. This is driven by recording events at short distances (below 10 km for magnitude 6 events and below 30 km for magnitude 7 events). Furthermore, the Maximum Ground Velocity derived from GPS is compared to the actual PGV for synthetic signals from the stochastic simulations and the 2008 Mw=6.9 Iwate earthquake. The proposed model, confirmed by synthetic and empirical data, shows that a reliable estimate of PGV for events of about magnitude 7 and greater can be basically retrieved by GPS in real-time and could be included for instance in ShakeMaps for aiding post-event disaster management

Mechanical Properties of Advanced Gas-Cooled Reactor Stainless Steel Cladding After Irradiation

The production of helium bubbles in advanced gas-cooled reactor (AGR) cladding could represent a significant hazard for both the mechanical stability and long-term storage of such materials. However, the high radioactivity of AGR cladding after operation presents a significant barrier to the scientific study of the mechanical properties of helium incorporation, said cladding typically being analyzed in industrial hot cells. An alternative non-active approach is to implant He2+ into unused AGR cladding material via an accelerator. Here, a feasibility study of such a process, using sequential implantations of helium in AGR cladding steel with decreasing energy is carried out to mimic the buildup of He (e.g., 50 appm) that would occur for in-reactor AGR clad in layers of the order of 10 lm in depth, is described. The implanted sample is subsequently analyzed by scanning electron microscopy, nanoindentation, atomic force and ultrasonic force microscopies. As expected, the irradiated zones were affected by implantation damage (<1 dpa). Nonetheless, such zones undergo only nanoscopic swelling and a small hardness increase (10%), with no appreciable decrease in fracture strength. Thus, for this fluence and applied conditions, the integrity of the steel cladding is retained despite He2+ implantation