235 research outputs found
Gas-induced segregation in Pt-Rh alloy nanoparticles observed by in-situ Bragg coherent diffraction imaging
Bimetallic catalysts can undergo segregation or redistribution of the metals
driven by oxidizing and reducing environments. Bragg coherent diffraction
imaging (BCDI) was used to relate displacement fields to compositional
distributions in crystalline Pt-Rh alloy nanoparticles. 3D images of internal
composition showed that the radial distribution of compositions reverses
partially between the surface shell and the core when gas flow changes between
O2 and H2. Our observation suggests that the elemental segregation of
nanoparticle catalysts should be highly active during heterogeneous catalysis
and can be a controlling factor in synthesis of electrocatalysts. In addition,
our study exemplifies applications of BCDI for in situ 3D imaging of internal
equilibrium compositions in other bimetallic alloy nanoparticles
Ka-Band Multi-Gbps High Speed Downlink With Electrically Steerable Beam
With advances in sensor technology and data services, the latest earth observation missions tend to require substantial amounts of remote sensing data to be downlinked to earth stations with shorter delivery times. To meet these demands, AXELSPACE is developing a Ka-band downlink system (AxelLink-Ka) in cooperation with Tokyo Institute of Technology 1 that combines a broadband Ka-band transmitter and an active phased array antenna.2 The prototype of the AxelLink-Ka was found to achieve a data rate of up to 4.2 Gbps with using dual polarizaion of Right- and Left-Handed Circular Polarization (RHCP/LHCP) in the Ka-band (25.5—27.0 GHz) and electrical beam steering covering ±66-degree range with the small enough Size, Weight and Power (SWaP) to be installed on a microsatellite: the size ∼ 220 × 170 × 100 mm, the weight \u3c 2, 300g, and the power consumption \u3c 60 W. This paper provides an overview of the entire system, simulation results of link budgets, and design and measurement results of the hardware and software
A Riemann solver at a junction compatible with a homogenization limit
We consider a junction regulated by a traffic lights, with n incoming roads
and only one outgoing road. On each road the Phase Transition traffic model,
proposed in [6], describes the evolution of car traffic. Such model is an
extension of the classic Lighthill-Whitham-Richards one, obtained by assuming
that different drivers may have different maximal speed. By sending to infinity
the number of cycles of the traffic lights, we obtain a justification of the
Riemann solver introduced in [9] and in particular of the rule for determining
the maximal speed in the outgoing road.Comment: 19 page
Tracking Cyber Adversaries with Adaptive Indicators of Compromise
A forensics investigation after a breach often uncovers network and host
indicators of compromise (IOCs) that can be deployed to sensors to allow early
detection of the adversary in the future. Over time, the adversary will change
tactics, techniques, and procedures (TTPs), which will also change the data
generated. If the IOCs are not kept up-to-date with the adversary's new TTPs,
the adversary will no longer be detected once all of the IOCs become invalid.
Tracking the Known (TTK) is the problem of keeping IOCs, in this case regular
expressions (regexes), up-to-date with a dynamic adversary. Our framework
solves the TTK problem in an automated, cyclic fashion to bracket a previously
discovered adversary. This tracking is accomplished through a data-driven
approach of self-adapting a given model based on its own detection
capabilities.
In our initial experiments, we found that the true positive rate (TPR) of the
adaptive solution degrades much less significantly over time than the naive
solution, suggesting that self-updating the model allows the continued
detection of positives (i.e., adversaries). The cost for this performance is in
the false positive rate (FPR), which increases over time for the adaptive
solution, but remains constant for the naive solution. However, the difference
in overall detection performance, as measured by the area under the curve
(AUC), between the two methods is negligible. This result suggests that
self-updating the model over time should be done in practice to continue to
detect known, evolving adversaries.Comment: This was presented at the 4th Annual Conf. on Computational Science &
Computational Intelligence (CSCI'17) held Dec 14-16, 2017 in Las Vegas,
Nevada, US
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