29,913 research outputs found

    On-Body Channel Measurement Using Wireless Sensors

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    © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This post-acceptance version of the paper is essentially complete, but may differ from the official copy of record, which can be found at the following web location (subscription required to access full paper): http://dx.doi.org/10.1109/TAP.2012.219693

    A critique of scaling behaviour in non-linear structure formation scenarios

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    Moments of the BBGKY equations for spatial correlation functions of cosmological density perturbations are used to obtain a differential equation for the evolution of the dimensionless function, h=−(v/a˙x)h = - ({v/{\dot{a}x}}), where vv is the mean relative pair velocity. The BBGKY equations are closed using a hierarchical scaling ansatz for the 3-point correlation function. Scale-invariant solutions derived earlier by Davis and Peebles are then used in the non-linear regime, along with the generalised stable clustering hypothesis (h→h \to const.), to obtain an expression for the asymptotic value of hh, in terms of the power law index of clustering, γ\gamma,and the tangential and radial velocity dispersions. The Davis-Peebles solution is found to require that tangential dispersions are larger than radial ones, in the non-linear regime; this can be understood on physical grounds. Finally, stability analysis of the solution demonstrates that the allowed asymptotic values of hh, consistent with the stable clustering hypothesis, lie in the range 0≤h≤1/20 \leq h \leq 1/2. Thus, if the Davis-Peebles scale-invariant solution (and the hierarchical model for the 3-pt function) is correct, the standard stable clustering picture (h→1h \to 1 as ξˉ→∞\bar\xi \to \infty) is not allowed in the non-linear regime of structure formation.Comment: 14 pages, no figures. Scheduled to appear in ApJ, Mar 1 issue. Final version, contains added discussion to match the accepted versio

    Improved Relation Extraction with Feature-Rich Compositional Embedding Models

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    Compositional embedding models build a representation (or embedding) for a linguistic structure based on its component word embeddings. We propose a Feature-rich Compositional Embedding Model (FCM) for relation extraction that is expressive, generalizes to new domains, and is easy-to-implement. The key idea is to combine both (unlexicalized) hand-crafted features with learned word embeddings. The model is able to directly tackle the difficulties met by traditional compositional embeddings models, such as handling arbitrary types of sentence annotations and utilizing global information for composition. We test the proposed model on two relation extraction tasks, and demonstrate that our model outperforms both previous compositional models and traditional feature rich models on the ACE 2005 relation extraction task, and the SemEval 2010 relation classification task. The combination of our model and a log-linear classifier with hand-crafted features gives state-of-the-art results.Comment: 12 pages for EMNLP 201

    Accurate determination of the Lagrangian bias for the dark matter halos

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    We use a new method, the cross power spectrum between the linear density field and the halo number density field, to measure the Lagrangian bias for dark matter halos. The method has several important advantages over the conventional correlation function analysis. By applying this method to a set of high-resolution simulations of 256^3 particles, we have accurately determined the Lagrangian bias, over 4 magnitudes in halo mass, for four scale-free models with the index n=-0.5, -1.0, -1.5 and -2.0 and three typical CDM models. Our result for massive halos with M≥M∗M \ge M_* (M∗M_* is a characteristic non-linear mass) is in very good agreement with the analytical formula of Mo & White for the Lagrangian bias, but the analytical formula significantly underestimates the Lagrangian clustering for the less massive halos $M < M_*. Our simulation result however can be satisfactorily described, with an accuracy better than 15%, by the fitting formula of Jing for Eulerian bias under the assumption that the Lagrangian clustering and the Eulerian clustering are related with a linear mapping. It implies that it is the failure of the Press-Schechter theories for describing the formation of small halos that leads to the inaccuracy of the Mo & White formula for the Eulerian bias. The non-linear mapping between the Lagrangian clustering and the Eulerian clustering, which was speculated as another possible cause for the inaccuracy of the Mo & White formula, must at most have a second-order effect. Our result indicates that the halo formation model adopted by the Press-Schechter theories must be improved.Comment: Minor changes; accepted for publication in ApJ (Letters) ; 11 pages with 2 figures include

    Modelling, simulation and proportional integral control of a pneumatic motor

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    Researchers have shown a considerable amount of interest in the control of pneumatic drives over the past decade, for two main reasons, firstly, the response of the system is very slow and it is difficult to attain set points due to hysteresis and secondly, the dynamic model of the system is highly non-linear, which greatly complicates controller design and development. To address these problems, two streams of research effort have evolved and these are: (i) using conventional methods to develop a modelling and control strategy, (ii) adopting a strategy that does not require mathematical model of the system. This paper presents an investigation into the modelling and control of an air motor incorporating a pneumatic equivalent of the electric H-bridge. The pneumatic H-bridge has been devised for speed and direction control of the motor. The system characteristics are divided into three regions, namely low speed, medium speed and high speed. The system is highly nonlinear in the low speed region, for which neuro-modelling, simulation and control strategies are developed

    Calculations of microwave brightness temperature of rough soil surfaces: Bare field

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    A model for simulating the brightness temperatures of soils with rough surfaces is developed. The surface emissivity of the soil media is obtained by the integration of the bistatic scattering coefficients for rough surfaces. The roughness of a soil surface is characterized by two parameters, the surface height standard deviation sigma and its horizontal correlation length l. The model calculations are compared to the measured angular variations of the polarized brightness temperatures at both 1.4 GHz and 5 GHz frequences. A nonlinear least-squares fitting method is used to obtain the values of delta and l that best characterize the surface roughness. The effect of shadowing is incorporated by introducing a function S(theta), which represents the probability that a point on a rough surface is not shadowed by other parts of the surface. The model results for the horizontal polarization are in excellent agreement with the data. However, for the vertical polarization, some discrepancies exist between the calculations and data, particularly at the 1.4 GHz frequency. Possible causes of the discrepancy are discussed

    On the Spatial Correlations of Lyman Break Galaxies

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    Motivated by the observed discrepancy between the strong spatial correlations of Lyman break galaxies (LBGs) and their velocity dispersions, we consider a theoretical model in which these starbursting galaxies are associated with dark matter halos that experience appreciable infall of material. We show using numerical simulation that selecting halos that substantially increase in mass within a fixed time interval introduces a ``temporal bias'' which boosts their clustering above that of the underlying population. If time intervals consistent with the observed LBGs star formation rates of 50 solar masses per year are chosen, then spatial correlations are enhanced by up to a factor of two. These values roughly correspond to the geometrical bias of objects three times as massive. Thus, it is clear that temporal biasing must be taken into account when interpreting the properties of Lyman break galaxies.Comment: 5 Pages, 2 Figures, Accepted for Publication in ApJ Letter

    Angular separations of the lensed QSO images

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    We have analyzed the observed image separations of the gravitationally lensed images of QSOs for a possible correlation with the source redshift. Contrary to the previously noted anti-correlation based on a smaller data set, no correlation is found for the currently available data. We have calculated the average image separations of the lensed QSOs as a function of source redshifts, for isothermal spheres with cores in a flat universe, taking into account the amplification bias caused by lensing. The shape of the distribution of average image separation as a function of redshift is very robust and is insensitive to most model parameters. Observations are found to be roughly consistent with the theoretical results for models which assume the lens distribution to be (i) Schechter luminosity function which, however, can not produce images with large separation and (ii) the mass condensations in a cold dark matter universe, as given by the Press-Schechter theory if an upper limit of 1-7×1013\times 10^{13} M⊙\odot is assumed on the mass of the condensations.Comment: 20 pages, 7 postscript figures, accepted for publication in The Astrophysical Journa
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