21,324 research outputs found
Network conduciveness with application to the graph-coloring and independent-set optimization transitions
We introduce the notion of a network's conduciveness, a probabilistically
interpretable measure of how the network's structure allows it to be conducive
to roaming agents, in certain conditions, from one portion of the network to
another. We exemplify its use through an application to the two problems in
combinatorial optimization that, given an undirected graph, ask that its
so-called chromatic and independence numbers be found. Though NP-hard, when
solved on sequences of expanding random graphs there appear marked transitions
at which optimal solutions can be obtained substantially more easily than right
before them. We demonstrate that these phenomena can be understood by resorting
to the network that represents the solution space of the problems for each
graph and examining its conduciveness between the non-optimal solutions and the
optimal ones. At the said transitions, this network becomes strikingly more
conducive in the direction of the optimal solutions than it was just before
them, while at the same time becoming less conducive in the opposite direction.
We believe that, besides becoming useful also in other areas in which network
theory has a role to play, network conduciveness may become instrumental in
helping clarify further issues related to NP-hardness that remain poorly
understood
The Physical State of the Intergalactic Medium or Can We Measure Y?
We present an argument for a {\it lower limit} to the Compton- parameter
describing spectral distortions of the cosmic microwave background (CMB). The
absence of a detectable Gunn-Peterson signal in the spectra of high redshift
quasars demands a high ionization state of the intergalactic medium (IGM).
Given an ionizing flux at the lower end of the range indicated by the proximity
effect, an IGM representing a significant fraction of the
nucleosynthesis-predicted baryon density must be heated by sources other than
the photon flux to a temperature \go {\rm few} \times 10^5\, K. Such a gas at
the redshift of the highest observed quasars, , will produce a y\go
10^{-6}. This lower limit on rises if the Universe is open, if there is a
cosmological constant, or if one adopts an IGM with a density larger than the
prediction of standard Big Bang nucleosynthesis.Comment: Proceedings of `Unveiling the Cosmic Infrared Background', April
23-25, 1995, Maryland. Self-unpacking uuencoded, compressed tar file with two
figures include
On the use of machine learning algorithms in the measurement of stellar magnetic fields
Regression methods based in Machine Learning Algorithms (MLA) have become an
important tool for data analysis in many different disciplines.
In this work, we use MLA in an astrophysical context; our goal is to measure
the mean longitudinal magnetic field in stars (H_ eff) from polarized spectra
of high resolution, through the inversion of the so-called multi-line profiles.
Using synthetic data, we tested the performance of our technique considering
different noise levels: In an ideal scenario of noise-free multi-line profiles,
the inversion results are excellent; however, the accuracy of the inversions
diminish considerably when noise is taken into account. In consequence, we
propose a data pre-process in order to reduce the noise impact, which consists
in a denoising profile process combined with an iterative inversion
methodology.
Applying this data pre-process, we have found a considerable improvement of
the inversions results, allowing to estimate the errors associated to the
measurements of stellar magnetic fields at different noise levels.
We have successfully applied our data analysis technique to two different
stars, attaining by first time the measurement of H_eff from multi-line
profiles beyond the condition of line autosimilarity assumed by other
techniques.Comment: Accepted for publication in A&
A State-of-the-art Integrated Transportation Simulation Platform
Nowadays, universities and companies have a huge need for simulation and
modelling methodologies. In the particular case of traffic and transportation,
making physical modifications to the real traffic networks could be highly
expensive, dependent on political decisions and could be highly disruptive to
the environment. However, while studying a specific domain or problem,
analysing a problem through simulation may not be trivial and may need several
simulation tools, hence raising interoperability issues. To overcome these
problems, we propose an agent-directed transportation simulation platform,
through the cloud, by means of services. We intend to use the IEEE standard HLA
(High Level Architecture) for simulators interoperability and agents for
controlling and coordination. Our motivations are to allow multiresolution
analysis of complex domains, to allow experts to collaborate on the analysis of
a common problem and to allow co-simulation and synergy of different
application domains. This paper will start by presenting some preliminary
background concepts to help better understand the scope of this work. After
that, the results of a literature review is shown. Finally, the general
architecture of a transportation simulation platform is proposed
Densifying the sparse cloud SimSaaS: The need of a synergy among agent-directed simulation, SimSaaS and HLA
Modelling & Simulation (M&S) is broadly used in real scenarios where making
physical modifications could be highly expensive. With the so-called Simulation
Software-as-a-Service (SimSaaS), researchers could take advantage of the huge
amount of resource that cloud computing provides. Even so, studying and
analysing a problem through simulation may need several simulation tools, hence
raising interoperability issues. Having this in mind, IEEE developed a standard
for interoperability among simulators named High Level Architecture (HLA).
Moreover, the multi-agent system approach has become recognised as a convenient
approach for modelling and simulating complex systems. Despite all the recent
works and acceptance of these technologies, there is still a great lack of work
regarding synergies among them. This paper shows by means of a literature
review this lack of work or, in other words, the sparse Cloud SimSaaS. The
literature review and the resulting taxonomy are the main contributions of this
paper, as they provide a research agenda illustrating future research
opportunities and trends
New contention resolution schemes for WiMAX
AbstractâThe use of Broadband Wireless Access (BWA) technology is increasing due to the use of Internet and multimedia applications with strict requirements of endâtoâend delay and jitter, through wireless devices. The IEEE 802.16 standard, which defines the physical (PHY) and the medium access control (MAC) layers, is one of the BWA standards. Its MAC layer is centralized basis, where the Base Station (BS) is responsible for assigning the needed bandwidth for each Subscriber Station (SS), which requests bandwidth competing between all of them. The standard defines a contention resolution process to resolve the potential occurrence of collisions during the requesting process. In this paper, we propose to modify the contention resolution process to improve the network performance, including endâtoâend delay and throughput
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