4,454 research outputs found

    On Optimization Modulo Theories, MaxSMT and Sorting Networks

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    Optimization Modulo Theories (OMT) is an extension of SMT which allows for finding models that optimize given objectives. (Partial weighted) MaxSMT --or equivalently OMT with Pseudo-Boolean objective functions, OMT+PB-- is a very-relevant strict subcase of OMT. We classify existing approaches for MaxSMT or OMT+PB in two groups: MaxSAT-based approaches exploit the efficiency of state-of-the-art MAXSAT solvers, but they are specific-purpose and not always applicable; OMT-based approaches are general-purpose, but they suffer from intrinsic inefficiencies on MaxSMT/OMT+PB problems. We identify a major source of such inefficiencies, and we address it by enhancing OMT by means of bidirectional sorting networks. We implemented this idea on top of the OptiMathSAT OMT solver. We run an extensive empirical evaluation on a variety of problems, comparing MaxSAT-based and OMT-based techniques, with and without sorting networks, implemented on top of OptiMathSAT and {\nu}Z. The results support the effectiveness of this idea, and provide interesting insights about the different approaches.Comment: 17 pages, submitted at Tacas 1

    Biohydrogen production from waste: experimental investigation and deployment prospect for transportation

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    Deriving the respiratory sinus arrhythmia from the heartbeat time series using Empirical Mode Decomposition

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    Heart rate variability (HRV) is a well-known phenomenon whose characteristics are of great clinical relevance in pathophysiologic investigations. In particular, respiration is a powerful modulator of HRV contributing to the oscillations at highest frequency. Like almost all natural phenomena, HRV is the result of many nonlinearly interacting processes; therefore any linear analysis has the potential risk of underestimating, or even missing, a great amount of information content. Recently the technique of Empirical Mode Decomposition (EMD) has been proposed as a new tool for the analysis of nonlinear and nonstationary data. We applied EMD analysis to decompose the heartbeat intervals series, derived from one electrocardiographic (ECG) signal of 13 subjects, into their components in order to identify the modes associated with breathing. After each decomposition the mode showing the highest frequency and the corresponding respiratory signal were Hilbert transformed and the instantaneous phases extracted were then compared. The results obtained indicate a synchronization of order 1:1 between the two series proving the existence of phase and frequency coupling between the component associated with breathing and the respiratory signal itself in all subjects.Comment: 12 pages, 6 figures. Will be published on "Chaos, Solitons and Fractals

    Syllabic quantity patterns as rhythmic features for Latin authorship attribution

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    It is well known that, within the Latin production of written text, peculiar metric schemes were followed not only in poetic compositions, but also in many prose works. Such metric patterns were based on so-called syllabic quantity, that is, on the length of the involved syllables, and there is substantial evidence suggesting that certain authors had a preference for certain metric patterns over others. In this research we investigate the possibility to employ syllabic quantity as a base for deriving rhythmic features for the task of computational authorship attribution of Latin prose texts. We test the impact of these features on the authorship attribution task when combined with other topic-agnostic features. Our experiments, carried out on three different datasets using support vector machines (SVMs) show that rhythmic features based on syllabic quantity are beneficial in discriminating among Latin prose authors

    El crecimiento económico argentino en perspectiva histórica

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    Nuevos enfoques en la historia económica de España y de América Latina. Homenaje a Robert W. Fogel y Douglas C. North, Premios Nobel de Economía 1993Editada en la Universidad Carlos IIIPublicad

    Fertility and well-being in the italian regions

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    We analyse the association between fertility rates and well-being in the Italian regions in the period 2012-2017. Well-being is measured by the indicators of Equitable and Sustainable Well-being (BES), collected by ISTAT since 2013 with the aim of evaluating the economic, social and environmental development of the society through measurement of citizens’ life quality. We expect that the regions performing better in terms of well-being conditions are also those with the highest levels of fertility. Both graphical and panel data regression analyses support our main hypothesis, but also reveal that in different clusters of regions the intensity and direction of the relationship significantly change. Our results also stress the need of taking the different domains of well-being into account while explaining reproductive behaviour of resident population at territorial level
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