21,324 research outputs found

    Network conduciveness with application to the graph-coloring and independent-set optimization transitions

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    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?

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    We present an argument for a {\it lower limit} to the Compton-yy 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, z∌5z\sim 5, will produce a y\go 10^{-6}. This lower limit on yy 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

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    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

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    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

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    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

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    Abstract—The use of Broadband Wireless Access (BWA) technology is increasing due to the use of Internet and multimedia applications with strict requirements of end–to–end 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 end–to–end delay and throughput
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