1,099 research outputs found

    Nonlinear Stochastic Resonance with subthreshold rectangular pulses

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    We analyze the phenomenon of nonlinear stochastic resonance (SR) in noisy bistable systems driven by pulsed time periodic forces. The driving force contains, within each period, two pulses of equal constant amplitude and duration but opposite signs. Each pulse starts every half-period and its duration is varied. For subthreshold amplitudes, we study the dependence of the output signal-to-noise ratio (SNR) and the SR gain on the noise strength and the relative duration of the pulses. We find that the SR gains can reach values larger than unity, with maximum values showing a nonmonotonic dependence on the duration of the pulses.Comment: 7 pages, 2 figure

    Modeling elastic wave propagation in fluid-filled boreholes drilled in nonhomogeneous media: BEM – MLPG versus BEM-FEM coupling

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    The efficiency of two coupling formulations, the boundary element method (BEM)-meshless local Petrov–Galerkin (MLPG) versus the BEM-finite element method (FEM), used to simulate the elastic wave propagation in fluid-filled boreholes generated by a blast load, is compared. The longitudinal geometry is assumed to be invariant in the axial direction (2.5D formulation). The material properties in the vicinity of the borehole are assumed to be nonhomogeneous as a result of the construction process and the ageing of the material. In both models, the BEM is used to tackle the propagation within the fluid domain inside the borehole and the unbounded homogeneous domain. The MLPG and the FEM are used to simulate the confined, damaged, nonhomogeneous, surrounding borehole, thus utilizing the advantages of these methods in modeling nonhomogeneous bounded media. In both numerical techniques the coupling is accomplished directly at the nodal points located at the common interfaces. Continuity of stresses and displacements is imposed at the solid–solid interface, while continuity of normal stresses and displacements and null shear stress are prescribed at the fluid–solid interface. The performance of each coupled BEM-MLPG and BEM-FEM approach is determined using referenced results provided by an analytical solution developed for a circular multi-layered subdomain. The comparison of the coupled techniques is evaluated for different excitation frequencies, axial wavenumbers and degrees of freedom (nodal points).Ministerio de Economía y Competitividad BIA2013-43085-PCentro Informático Científico de Andalucía (CICA

    Rule-based monitoring and error detecting for converged telecommunication processes

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    Convergent process may be defined as a composition of services which integrates functionalities from Web and Telecommunication domains. However, during execution of convergent processes some services may fail; in such cases a reconfiguration process must be triggered to recover normal behaviour of composite process. Previous works have developed mechanisms for reducing reconfiguration time while initial restrictions are maintained; this is achieved by replacing regions of services instead of individual services. The present work presents an approach for monitoring and error detecting in convergent processes using rule production systems based on ITIL model. The approach was tested in the monitoring module of the AUTO framework, whose architecture and performance are discussed to show that this approach can efficiently detect errors and repair convergent processes in telecom environments

    Coal mine ventilation air methane combustion in a catalytic reverse flow reactor: Influence of emission humidity

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    The role of the humidity content on the performance of catalytic reverse flow reactors (RFRs) for the abatement of methane emissions from coal mines is studied in this manuscript. It has been demonstrated that this technique is very useful for the abatement, and even upgrading, of these emissions. However, the effect of humidity on the reactor performance has not been addressed yet, in spite of being well known that water is an inhibitor in catalytic combustion. Experimental studies in a lab-scale isothermal fixed bed reactor demonstrated that water decreases the activity of a palladium on alumina catalyst for the combustion of methane, but this inhibition is entirely reversible, results fitting well to a Langmuir–Hinshelwood kinetic model. Then, the influence of water was studied in a bench-scale RFR operating at near adiabatic conditions at different switching times (100–600 s) and methane feed concentrations (2700–7200 ppm). Finally, a mathematical model for the reverse flow reactor, including the kinetic model with water inhibition, has been validated using the experimental results. This model is of key importance for designing this type of reactors for the treatment of mine ventilation emissions

    The Palaeozoic basement of the Andean Frontal Cordillera at 34º S (Cordón del Carrizalito, Mendoza Province, Argentina): Geotectonic implications

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    The Cordón del Carrizalito is located in the southern sector of the Andean Frontal Cordillera. In this area, the Andean basement is composed of meta-sedimentary rocks (Las Lagunitas Formation) of Ordovician age. In addition, no- or very low grade metamorphism and less deformed rocks also occur in the study area. We call these rocks Selerpe series, whose characteristics are comparable to other series, late Carboniferous in age, described in nearby areas. The Las Lagunitas Formation is affected by west-verging folds, developed under low-grade metamorphic conditions. These structures can be attributed to the Chanic orogeny (Late Devonian – early Carboniferous). The Selerpe series and Las Lagunitas Formation are deformed by east-verging thrusts and folds developed in narrow bands and generated in the absence or under very low metamorphic conditions. These structures always deform the Chanic structures, and are attributed to the Gondwanan deformation (San Rafael orogeny, late Carboniferous – Permian in age). The Chanic structures of the study area can be placed in the western branch and in the hinterland of the Chanic orogen, which was developed as a result of the accretion of the Chilenia terrane at the west Gondwana margin during Late Devonian and early Carboniferous. The eastern branch of this orogen is located in the Andean Precordillera. The Permo-Triassic cover, deformed by the Andean orogenic cycle (Mesozoic – Cenozoic), rests unconformably on the Palaeozoic basement rocks.En el Cordón del Carrizalito, situado en el sector meridional de la Cordillera Frontal de los Andes, afloran metasedimentos ordovícicos pertenecientes a la Formación Las Lagunitas y otro conjunto de rocas menos deformadas, en ausencia de metamorfismo o con metamorfis­mo de muy bajo grado, que hemos denominado serie de Selerpe. Esta última es litoestratigráficamente comparable a series del Carbonífero superior descritas en áreas próximas. La Formación Las Lagunitas está afectada por pliegues apretados, vergentes al oeste y desarrollados bajo condiciones de metamorfismo de bajo grado. Estas estructuras pueden ser atribuidas a la orogenia Chánica (Devónico Superior - Car­bonífero inferior). La deformación Gondwánica, atribuida a la orogenia San Rafael, (Carbonífero superior – Pérmico), afecta tanto a la serie de Selerpe como a la Formación Las Lagunitas y se caracteriza por cabalgamientos y pliegues vergentes al este y generados en ausencia de metamorfismo o bajo condiciones metamórficas de muy grado bajo. Las estructuras chánicas de la zona estudiada se encuentran en las zonas internas de la rama occidental del orógeno del mismo nombre. Estas estructuras se desarrollaron como resultado de la acreción del terreno de Chilenia al margen occidental del antiguo continente de Gondwana durante el Devónico Superior – Carbonífero inferior. La rama oriental del orógeno Chánico se sitúa en la Precordillera andina. La cobertera permo-triásica, deformada durante el Mesozoico y Cenozoico por el ciclo orogénico Andino, se apoya discordantemente sobre las rocas del basamento paleozoico

    ESC NN-Potentials in Momentum Space. II. Meson-Pair Exchange Potentials

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    The partial wave projection of the Nijmegen soft-core potential model for Meson-Pair-Exchange (MPE) for NN-scattering in momentum space is presented. Here, nucleon-nucleon momentum space MPE-potentials are NN-interactions where either one or both nucleons contains a meson-pair vertex. Dynamically, the meson-pair vertices can be viewed as describing in an effective way (part of) the effects of heavy-meson exchange and meson-nucleon resonances. From the point of view of ``duality,'' these two kinds of contribution are roughly equivalent. Part of the MPE-vertices can be found in the chiral-invariant phenomenological Lagrangians that have a basis in spontaneous broken chiral symmetry. It is shown that the MPE-interactions are a very important component of the nuclear force, which indeed enables a very succesful description of the low and medium energy NN-data. Here we present a precise fit to the NN-data with the extended-soft-core (ESC) model containing OBE-, PS-PS-, and MPE-potentials. An excellent description of the NN-data for TLab350T_{Lab} \leq 350 MeV is presented and discussed. Phase shifts are given and a χp.d.p.2=1.15\chi^2_{p.d.p.} = 1.15 is reached.Comment: 27 pages, 5 PostScript figures, revtex

    Detecting hate speech on twitter using a convolution-GRU based deep neural network

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    In recent years, the increasing propagation of hate speech on social media and the urgent need for effective counter-measures have drawn significant investment from governments, companies, as well as empirical research. Despite a large number of emerging scientific studies to address the problem, existing methods are limited in several ways, such as the lack of comparative evaluations which makes it difficult to assess the contribution of individual works. This paper introduces a new method based on a deep neural network combining convolutional and long short term memory networks, and conducts an extensive evaluation of the method against several baselines and state of the art on the largest collection of publicly available datasets to date. We show that our proposed method outperforms state of the art on 6 out of 7 datasets by between 0.2 and 13.8 points in F1. We also carry out further analysis using automatic feature selection to understand the impact of the conventional manual feature engineering process that distinguishes most methods in this field. Our findings challenge the existing perception of the importance of feature engineering, as we show that: the automatic feature selection algorithm drastically reduces the original feature space by over 90% and selects predominantly generic features from datasets; nevertheless, machine learning algorithms perform better using automatically selected features than the original features
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