604 research outputs found

    Temperature dependence of volume and surface symmetry energy coefficients of nuclei

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    AbstractThe thermal evolution of the energies and free energies of a set of spherical and near-spherical nuclei spanning the whole periodic table are calculated in the subtracted finite-temperature Thomas–Fermi framework with the zero-range Skyrme-type KDE0 and the finite-range modified Seyler–Blanchard interaction. The calculated energies are subjected to a global fit in the spirit of the liquid-drop model. The extracted parameters in this model reflect the temperature dependence of the volume symmetry and surface symmetry coefficients of finite nuclei, in addition to that of the volume and surface energy coefficients. The temperature dependence of the surface symmetry energy is found to be very substantial whereas that of the volume symmetry energy turns out to be comparatively mild

    Moving towards a control technique to help small firms monitor and control key marketing parameters: a survival aid

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    This article considers that one way to help the small- and medium-sized enterprise (SME) to survive is to offer it a robust but simple monitoring and control technique that would help it manage the business effectively and this, in turn, should help to increase its chances of survival. This technique should also be of interest to all people involved with monitoring or advising a large number of small enterprises or business units within a larger organization. For example, a bank manager or a small business consultant responsible for a portfolio of firms. The authors utilize process control techniques more often used in production and inventory control systems to demonstrate how one might monitor the marketing ``health'' of small firms

    Neutrino hierarchy from CP-blind observables with high density magnetized detectors

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    High density magnetized detectors are well suited to exploit the outstanding purity and intensities of novel neutrino sources like Neutrino Factories and Beta Beams. They can also provide independent measurements of leptonic mixing parameters through the observation of atmospheric muon-neutrinos. In this paper, we discuss the combination of these observables from a multi-kton iron detector and a high energy Beta Beam; in particular, we demonstrate that even with moderate detector granularities the neutrino mass hierarchy can be determined for θ13\theta_{13} values greater than 4^\circ.Comment: 16 pages, 7 figures. Added a new section discussing systematic errors (sec 5.2); sec.5.1 and 4 have been extended. Version to appear in EPJ

    Predicting User-Cell Association in Cellular Networks from Tracked Data

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    We consider the problem of predicting user location in the form of user-cell association in a cellular wireless network. This is motivated by resource optimization, for example switching base transceiver stations on or off to save on network energy consumption. We use GSM traces obtained from an operator, and compare several prediction methods. First, we find that, on our trace data, user cell sector association can be correctly predicted in ca. 80% of the cases. Second, we propose a new method, called “MARPL”, which uses Market Basket Analysis to separate patterns where prediction by partial match (PPM) works well from those where repetition of the last known location (LAST) is best. Third, we propose that for network resource optimization, predicting the aggregate location of a user ensemble may be of more interest than separate predictions for all users; this motivates us to develop soft prediction methods, where the prediction is a spatial probability distribution rather than the most likely location. Last, we compare soft predictions methods to a classical time and space analysis (ISTAR). In terms of relative mean square error, MARPL with soft prediction and ISTAR perform better than all other methods, with a slight advantage to MARPL (but the numerical complexity of MARPL is much less than ISTAR)
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