1,948 research outputs found

    Enhanced Trellis Coded Multiple Access (ETCMA)

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    We propose an enhanced version of trellis coded multiple access (TCMA), an overloaded multiple access scheme that outperforms the original TCMA in terms of achieved spectral efficiency. Enhanced TCMA (ETCMA) performs simultaneous transmission of multiple data streams intended for users experiencing similar signal-to-noise ratios and can be employed both in the uplink and in the downlink of wireless systems, thus overcoming one of the main limitations of TCMA. Thanks to a new receiver algorithm, ETCMA is capable of delivering a significantly higher spectral efficiency. We show that ETCMA approaches the capacity of the Additive White Gaussian Noise channel for a wide range of signal-to-noise ratios.Comment: 5 pages, 5 figure

    Distress propagation in complex networks: The case of non-linear DebtRank

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    We consider a dynamical model of distress propagation on complex networks, which we apply to the study of financial contagion in networks of banks connected to each other by direct exposures. The model that we consider is an extension of the DebtRank algorithm, recently introduced in the literature. The mechanics of distress propagation is very simple: When a bank suffers a loss, distress propagates to its creditors, who in turn suffer losses, and so on. The original DebtRank assumes that losses are propagated linearly between connected banks. Here we relax this assumption and introduce a one-parameter family of non-linear propagation functions. As a case study, we apply this algorithm to a data-set of 183 European banks, and we study how the stability of the system depends on the non-linearity parameter under different stress-test scenarios. We find that the system is characterized by a transition between a regime where small shocks can be amplified and a regime where shocks do not propagate, and that the overall stability of the system increases between 2008 and 2013

    Streamlining models with explanations in the learning loop

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    Several explainable AI methods allow a Machine Learning user to get insights on the classification process of a black-box model in the form of local linear explanations. With such information, the user can judge which features are locally relevant for the classification outcome, and get an understanding of how the model reasons. Standard supervised learning processes are purely driven by the original features and target labels, without any feedback loop informed by the local relevance of the features identified by the post-hoc explanations. In this paper, we exploit this newly obtained information to design a feature engineering phase, where we combine explanations with feature values. To do so, we develop two different strategies, named Iterative Dataset Weighting and Targeted Replacement Values, which generate streamlined models that better mimic the explanation process presented to the user. We show how these streamlined models compare to the original black-box classifiers, in terms of accuracy and compactness of the newly produced explanations.Comment: 16 pages, 10 figures, available repositor

    Using the Sound Card as a Timer

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    Experiments in mechanics can often be timed by the sounds they produce. In such cases, digital audio recordings provide a simple way of measuring time intervals with an accuracy comparable to that of photogate timers. We illustrate this with an experiment in the physics of sports: to measure the speed of a hard-kicked soccer ball.Comment: 3 pages, 4 figures, Late

    Urban geomorphology of Genoa old city (Italy)

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    A multi-year geomorphological surveys of the city of Genoa allowed the creation of an original geomorphological map of the urban environment. The city of Genoa is internationally known for the importance of its port and for the presence of a historic city center recognized as an UNESCO World Heritage since 2006. The research methodology was based on the structuring and analysis of a multi-source geodatabase consisting of information acquired from scientific literature and technical reports, historical and recent photographs and maps, geological and environmental data related to land planning plans, original data from field surveys. Work phases of data elaboration included: 1) a multi-temporal cartographic comparison from the eighteenth-century to year 2016; 2) an analysis of aerial photographs in the period 1936-2016; 3) the interpretation of boreholes data; 4) both surface and underground geomorphological observations within the city centre, by means of field surveys and speleological techniques. The recognition of the former geomorphological setting on which the historical nucleus of Genoa has developed, and the interpretation of its paleogeographic, geological and tectonic conditions, are not an easy task: since the High Middle Ages of the Maritime Republic of Genoa, the superposition of multiple phases of urban sprawl has obliterated original geomorphic conditions. However, interpretation of the rich geodatabase allowed to classify landforms, processes and surficial deposits with respect to their original environment and morphogenesis, i.e due to: running waters, gravity, karst, action of the sea; but, above all, due to human activities. In fact, the entire study area has undergone continuous modifications by man through the all considered time interval, as shown by artificial land fillings at the seaside, alteration of the river network, excavations and fills on the slopes, with the highlighting of significant anthropogenic urban landforms. The geomorphological map support both a morpho-evolutionary and a functional approach to the geomorphological landscape the of Genoa old city: therefore, it can be a useful tool for land planning, also aimed at reducing the geo-hydrological risk that characterizes the urban area
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