4,121 research outputs found
Beyond Counting: New Perspectives on the Active IPv4 Address Space
In this study, we report on techniques and analyses that enable us to capture
Internet-wide activity at individual IP address-level granularity by relying on
server logs of a large commercial content delivery network (CDN) that serves
close to 3 trillion HTTP requests on a daily basis. Across the whole of 2015,
these logs recorded client activity involving 1.2 billion unique IPv4
addresses, the highest ever measured, in agreement with recent estimates.
Monthly client IPv4 address counts showed constant growth for years prior, but
since 2014, the IPv4 count has stagnated while IPv6 counts have grown. Thus, it
seems we have entered an era marked by increased complexity, one in which the
sole enumeration of active IPv4 addresses is of little use to characterize
recent growth of the Internet as a whole.
With this observation in mind, we consider new points of view in the study of
global IPv4 address activity. Our analysis shows significant churn in active
IPv4 addresses: the set of active IPv4 addresses varies by as much as 25% over
the course of a year. Second, by looking across the active addresses in a
prefix, we are able to identify and attribute activity patterns to network
restructurings, user behaviors, and, in particular, various address assignment
practices. Third, by combining spatio-temporal measures of address utilization
with measures of traffic volume, and sampling-based estimates of relative host
counts, we present novel perspectives on worldwide IPv4 address activity,
including empirical observation of under-utilization in some areas, and
complete utilization, or exhaustion, in others.Comment: in Proceedings of ACM IMC 201
Scattering map for two black holes
We study the motion of light in the gravitational field of two Schwarzschild
black holes, making the approximation that they are far apart, so that the
motion of light rays in the neighborhood of one black hole can be considered to
be the result of the action of each black hole separately. Using this
approximation, the dynamics is reduced to a 2-dimensional map, which we study
both numerically and analytically. The map is found to be chaotic, with a
fractal basin boundary separating the possible outcomes of the orbits (escape
or falling into one of the black holes). In the limit of large separation
distances, the basin boundary becomes a self-similar Cantor set, and we find
that the box-counting dimension decays slowly with the separation distance,
following a logarithmic decay law.Comment: 20 pages, 5 figures, uses REVTE
Proving Safety with Trace Automata and Bounded Model Checking
Loop under-approximation is a technique that enriches C programs with
additional branches that represent the effect of a (limited) range of loop
iterations. While this technique can speed up the detection of bugs
significantly, it introduces redundant execution traces which may complicate
the verification of the program. This holds particularly true for verification
tools based on Bounded Model Checking, which incorporate simplistic heuristics
to determine whether all feasible iterations of a loop have been considered.
We present a technique that uses \emph{trace automata} to eliminate redundant
executions after performing loop acceleration. The method reduces the diameter
of the program under analysis, which is in certain cases sufficient to allow a
safety proof using Bounded Model Checking. Our transformation is precise---it
does not introduce false positives, nor does it mask any errors. We have
implemented the analysis as a source-to-source transformation, and present
experimental results showing the applicability of the technique
Caracterização físico-química de mirtilos submetidos a diferentes coberturas de solo.
bitstream/item/79717/1/comunicado-266.pd
Uso da torta de mamona como alternativa à adubação química para morangueiro.
bitstream/item/72405/1/16121.pd
Identification of duplicates of cassava accessions sampled on the North Region of Brazil using microsatellite markers.
Duplicatas costumam ocorrer em bancos de germoplasma e a sua identificação é necessária para facilitar o manejo dos bancos ativos de germoplasma (BAGs) e diminuir custos de manutenção. O objetivo deste trabalho foi identificar duplicatas de mandioca determinadas previamente pela caracterização morfo-agronômica, em um BAG da Amazônia Oriental. Foram selecionados 36 acessos que se agrupavam em 13 grupos de similaridade morfo-agronômica para serem genotipados com 15 locos microssatélites. Todos os locos foram polimórficos, sendo obtidos 75 alelos, com média de cinco alelos por loco e HE = 0,66. Foram encontrados 34 pares de genótipos que apresentaram perfis multilocos idênticos e a probabilidade de identidade genética foi de 1,1x10-12 com probabilidade de exclusão de 99,9999%. Entre essas duplicatas, estão materiais coletados em épocas e locais diferentes, e com diferentes denominações e acessos com o mesmo nome coletados em diferentes locais e anos. O estudo identificou genótipos que vem sendo cultivados em diferentes locais e que vêm sendo mantidos pelos agricultores ao longo dos anos
On multigraded generalizations of Kirillov-Reshetikhin modules
We study the category of Z^l-graded modules with finite-dimensional graded
pieces for certain Z+^l-graded Lie algebras. We also consider certain Serre
subcategories with finitely many isomorphism classes of simple objects. We
construct projective resolutions for the simple modules in these categories and
compute the Ext groups between simple modules. We show that the projective
covers of the simple modules in these Serre subcategories can be regarded as
multigraded generalizations of Kirillov-Reshetikhin modules and give a
recursive formula for computing their graded characters
Microstructure identification via detrended fluctuation analysis of ultrasound signals
We describe an algorithm for simulating ultrasound propagation in random
one-dimensional media, mimicking different microstructures by choosing physical
properties such as domain sizes and mass densities from probability
distributions. By combining a detrended fluctuation analysis (DFA) of the
simulated ultrasound signals with tools from the pattern-recognition
literature, we build a Gaussian classifier which is able to associate each
ultrasound signal with its corresponding microstructure with a very high
success rate. Furthermore, we also show that DFA data can be used to train a
multilayer perceptron which estimates numerical values of physical properties
associated with distinct microstructures.Comment: Submitted to Phys. Rev.
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