44,968 research outputs found
On the Perturbation of Self-Organized Urban Street Networks
We investigate urban street networks as a whole within the frameworks of
information physics and statistical physics. Urban street networks are
envisaged as evolving social systems subject to a Boltzmann-mesoscopic entropy
conservation. For self-organized urban street networks, our paradigm has
already allowed us to recover the effectively observed scale-free distribution
of roads and to foresee the distribution of junctions. The entropy conservation
is interpreted as the conservation of the surprisal of the city-dwellers for
their urban street network. In view to extend our investigations to other urban
street networks, we consider to perturb our model for self-organized urban
street networks by adding an external surprisal drift. We obtain the statistics
for slightly drifted self-organized urban street networks. Besides being
practical and manageable, this statistics separates the macroscopic evolution
scale parameter from the mesoscopic social parameters. This opens the door to
observational investigations on the universality of the evolution scale
parameter. Ultimately, we argue that the strength of the external surprisal
drift might be an indicator for the disengagement of the city-dwellers for
their city.Comment: 22 pages, 4 figures + 1 table, LaTeX2e+BMCArt+AmSLaTeX+enote
A New Approach for Computing the Bandwidth Statistics of Avalanche Photodiodes
A new approach for characterizing the avalanche-buildup-time-limited bandwidth of avalanche photodiodes (APDs) is introduced which relies on the direct knowledge of the statistics of the random response time. The random response time is the actual duration of the APD’s finite buildup-limited random impulse response function. A theory is developed characterizing the probability distribution function (PDF) of the random response time. Recurrence equations are derived and numerically solved to yield the PDF of the random response time. The PDF is then used to compute the mean and the standard deviation of the bandwidth. The dependence of the mean and the standard deviation of the bandwidth on the APD mean gain and the ionization coefficient ratio is investigated. Exact asymptotics of the tail of the PDF of the response time are also developed to aid the computation efficiency. The technique can be readily applied to multiplication models which incorporate dead space and can be extended to cases for which the carrier ionization coefficient is position dependent
Dynamic Analysis of Executables to Detect and Characterize Malware
It is needed to ensure the integrity of systems that process sensitive
information and control many aspects of everyday life. We examine the use of
machine learning algorithms to detect malware using the system calls generated
by executables-alleviating attempts at obfuscation as the behavior is monitored
rather than the bytes of an executable. We examine several machine learning
techniques for detecting malware including random forests, deep learning
techniques, and liquid state machines. The experiments examine the effects of
concept drift on each algorithm to understand how well the algorithms
generalize to novel malware samples by testing them on data that was collected
after the training data. The results suggest that each of the examined machine
learning algorithms is a viable solution to detect malware-achieving between
90% and 95% class-averaged accuracy (CAA). In real-world scenarios, the
performance evaluation on an operational network may not match the performance
achieved in training. Namely, the CAA may be about the same, but the values for
precision and recall over the malware can change significantly. We structure
experiments to highlight these caveats and offer insights into expected
performance in operational environments. In addition, we use the induced models
to gain a better understanding about what differentiates the malware samples
from the goodware, which can further be used as a forensics tool to understand
what the malware (or goodware) was doing to provide directions for
investigation and remediation.Comment: 9 pages, 6 Tables, 4 Figure
HARPO: a TPC as a gamma-ray telescope and polarimeter
A gas Time Projection Chamber can be used for gamma-ray astronomy with
excellent angular-precision and sensitivity to faint sources, and for
polarimetry, through the measurement of photon conversion to pairs. We
present the expected performance in simulations and the recent development of a
demonstrator for tests in a polarized photon beam.Comment: SPIE Astronomical Telescopes + Instrumentation, Ultraviolet to gamma
ray, Montr\'eal, Canada 2014. v2: note added in proof. Copyright 2014 SPIE.
One print or electronic copy may be made for personal use only. Systematic
reproduction and distribution, duplication of any material in this paper for
a fee or for commercial purposes, or modification of the content of the paper
are prohibite
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