Anomalies of the omnipresent earth magnetic (i.e., geomagnetic) field in an indoor environment, caused by local disturbances due to construction materials, give rise to noisy direction sensing that hinders any dead reckoning system. In this paper, we turn this unpalatable phenomenon into a favorable one. We present Magicol, an indoor localization and tracking system that embraces the local disturbances of the geomagnetic field. We tackle the low discernibility of the magnetic field by vectorizing consecutive magnetic signals on a per-step basis, and use vectors to shape the particle distribution in the estimation process. Magicol can also incorporate WiFi signals to achieve much improved positioning accuracy for indoor environments with WiFi infrastructure. We perform an in-depth study on the fusion of magnetic and WiFi signals. We design a two-pass, bidirectional particle filtering process for maximum accuracy, and propose an on-demand WiFi scan strategy for energy savings. We further propose a compliant-walking method for location database construction that drastically simplifies the site survey effort. We conduct extensive experiments at representative indoor environments, including an office building, an underground parking garage, and a supermarket in which Magicol achieved a 90 percentile localization accuracy of 5m, 1m, and 8m, respectively, using the magnetic field alone. The fusion with WiFi leads to 90 percentile accuracy of 3.5m for localization and 0.9m for tracking in the office environment. When using only the magnetism, Magicol consumes 9× less energy in tracking compared to WiFibased tracking.
With the increased popularity of smartphones, various security threats and privacy leakages targeting them are discovered and investigated. In this work, we present SilentSense, a framework to authenticate users silently and transparently by exploiting dynamics mined from the user touch behavior biometrics and the micro-movement of the device caused by user's screen-touch actions. We build a "touch-based biometrics" model of the owner by extracting some principle features, and then verify whether the current user is the owner or guest/attacker. When using the smartphone, some unique operating dynamics of the user is detected and learnt by collecting the sensor data and touch events silently. When users are mobile, the micro-movement of mobile devices caused by touch is suppressed by that due to the large scale user-movement which will render the touch-based biometrics ineffective. To address this, we integrate a movementbased biometrics for each user with previous touch-based biometrics. We conduct extensive evaluations of our approaches on the Android smartphone, we show that the user identification accuracy is over 99%.
Ultrathin Pd nanosheets (NSs) coated with submonolayered Ru, referred to as Pd@Ru NSs, are synthesized via a seed-mediated growth method. The underpotential deposition can be the driving force for the formation of Pd@Ru NSs. The Pd@Ru NSs exhibit superior catalytic properties in the reduction of 4-nitrophenol and the semihydrogenation of 1-octyne, compared to the pure Pd NSs and Ru NSs.
This article reports on a novel methodology for preparing a new class of core/shell nanoparticles. The nanoparticles consist of a unique core (composed of an optically active helical-substituted polyacetylene) and a shell (composed of a vinyl polymer) and thus exhibit optical activities. Such nanoparticles were synthesized by combining aqueous catalytic microemulsion polymerization and free radical polymerization in one specific system. The shells could be further cross-linked for improving the properties of particles. The investigations are of high importance not only in polymer chemistry due to the combination of catalytic polymerization and free radical polymerization in one system but also in materials due to the integration of “chirality” and “nano” concepts in one single material.
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