19,352 research outputs found
On Mitigation of Side-Channel Attacks in 3D ICs: Decorrelating Thermal Patterns from Power and Activity
Various side-channel attacks (SCAs) on ICs have been successfully
demonstrated and also mitigated to some degree. In the context of 3D ICs,
however, prior art has mainly focused on efficient implementations of classical
SCA countermeasures. That is, SCAs tailored for up-and-coming 3D ICs have been
overlooked so far. In this paper, we conduct such a novel study and focus on
one of the most accessible and critical side channels: thermal leakage of
activity and power patterns. We address the thermal leakage in 3D ICs early on
during floorplanning, along with tailored extensions for power and thermal
management. Our key idea is to carefully exploit the specifics of material and
structural properties in 3D ICs, thereby decorrelating the thermal behaviour
from underlying power and activity patterns. Most importantly, we discuss
powerful SCAs and demonstrate how our open-source tool helps to mitigate them.Comment: Published in Proc. Design Automation Conference, 201
Physics-based large-signal sensitivity analysis of microwave circuits using technological parametric sensitivity from multidimensional semiconductor device models
The authors present an efficient approach to evaluate the large-signal (LS) parametric sensitivity of active semiconductor devices under quasi-periodic operation through accurate, multidimensional physics-based models. The proposed technique exploits efficient intermediate mathematical models to perform the link between physics-based analysis and circuit-oriented simulations, and only requires the evaluation of dc and ac small-signal (dc charge) sensitivities under general quasi-static conditions. To illustrate the technique, the authors discuss examples of sensitivity evaluation, statistical analysis, and doping profile optimization of an implanted MESFET to minimize intermodulation which makes use of LS parametric sensitivities under two-tone excitatio
Fast, scalable, Bayesian spike identification for multi-electrode arrays
We present an algorithm to identify individual neural spikes observed on
high-density multi-electrode arrays (MEAs). Our method can distinguish large
numbers of distinct neural units, even when spikes overlap, and accounts for
intrinsic variability of spikes from each unit. As MEAs grow larger, it is
important to find spike-identification methods that are scalable, that is, the
computational cost of spike fitting should scale well with the number of units
observed. Our algorithm accomplishes this goal, and is fast, because it
exploits the spatial locality of each unit and the basic biophysics of
extracellular signal propagation. Human intervention is minimized and
streamlined via a graphical interface. We illustrate our method on data from a
mammalian retina preparation and document its performance on simulated data
consisting of spikes added to experimentally measured background noise. The
algorithm is highly accurate
Ionization Electron Signal Processing in Single Phase LArTPCs I. Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation
We describe the concept and procedure of drifted-charge extraction developed
in the MicroBooNE experiment, a single-phase liquid argon time projection
chamber (LArTPC). This technique converts the raw digitized TPC waveform to the
number of ionization electrons passing through a wire plane at a given time. A
robust recovery of the number of ionization electrons from both induction and
collection anode wire planes will augment the 3D reconstruction, and is
particularly important for tomographic reconstruction algorithms. A number of
building blocks of the overall procedure are described. The performance of the
signal processing is quantitatively evaluated by comparing extracted charge
with the true charge through a detailed TPC detector simulation taking into
account position-dependent induced current inside a single wire region and
across multiple wires. Some areas for further improvement of the performance of
the charge extraction procedure are also discussed.Comment: 60 pages, 36 figures. The second part of this work can be found at
arXiv:1804.0258
Optimized digital filtering techniques for radiation detection with HPGe detectors
This paper describes state-of-the-art digital filtering techniques that are
part of GEANA, an automatic data analysis software used for the GERDA
experiment. The discussed filters include a novel, nonlinear correction method
for ballistic deficits, which is combined with one of three shaping filters: a
pseudo-Gaussian, a modified trapezoidal, or a modified cusp filter. The
performance of the filters is demonstrated with a 762 g Broad Energy Germanium
(BEGe) detector, produced by Canberra, that measures {\gamma}-ray lines from
radioactive sources in an energy range between 59.5 and 2614.5 keV. At 1332.5
keV, together with the ballistic deficit correction method, all filters produce
a comparable energy resolution of ~1.61 keV FWHM. This value is superior to
those measured by the manufacturer and those found in publications with
detectors of a similar design and mass. At 59.5 keV, the modified cusp filter
without a ballistic deficit correction produced the best result, with an energy
resolution of 0.46 keV. It is observed that the loss in resolution by using a
constant shaping time over the entire energy range is small when using the
ballistic deficit correction method
Stability of the Submillimeter Brightness of the Atmosphere Above Mauna Kea, Chajnantor and the South Pole
The summit of Mauna Kea in Hawaii, the area near Cerro Chajnantor in Chile,
and the South Pole are sites of large millimeter or submillimeter wavelength
telescopes. We have placed 860 GHz sky brightness monitors at all three sites
and present a comparative study of the measured submillimeter brightness due to
atmospheric thermal emission. We report the stability of that quantity at each
site.Comment: 6 figure
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