17 research outputs found

    Applications of Machine Learning to Automated Reasoning

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    Sensitivity of NEXT-100 detector to neutrinoless double beta decay

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    Nesta tese estúdiase a sensibilidade do detector NEXT-100 á desintegración dobre beta sen neutrinos. Existe un gran interese na busca desta desintegración xa que podería respostar preguntas fundamentais en física de neutrinos. O detector constitúe a terceira fase do experimento NEXT, colaboración na que se desenrolou esta tese. A continuación inclúese un resumo de cada un dos capítulos nos que se divide a tese. Comézase introducindo o marco teórico e experimental nas seccións Física de neutrinos, A busca da desintegración dobre beta sen neutrinos e O experimento NEXT. Posteriormente descríbense a parte principal do análise da tese en Simulación do detector, Procesamento de datos e Sensibilidade do detector NEXT-100

    Formal Linguistic Models and Knowledge Processing. A Structuralist Approach to Rule-Based Ontology Learning and Population

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    2013 - 2014The main aim of this research is to propose a structuralist approach for knowledge processing by means of ontology learning and population, achieved starting from unstructured and structured texts. The method suggested includes distributional semantic approaches and NL formalization theories, in order to develop a framework, which relies upon deep linguistic analysis... [edited by author]XIII n.s

    ATEE Spring Conference 2020-2021

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    This book collects some of the works presented at ATEE Florence Spring Conference 2020-2021. The Conference, originally planned for May 2020, was forcefully postponed due to the dramatic insurgence of the pandemic. Despite the difficulties in this period, the Organising Committee decided anyway to keep it, although online and more than one year later, not to disperse the huge work of authors, mainly teachers, who had to face one of the hardest challenges in the last decades, in a historic period where the promotion of social justice and equal opportunities – through digital technologies and beyond – is a key factor for democratic citizenship in our societies. The Organising Committee, the University of Florence, and ATEE wish to warmly thank all the authors for their commitment and understanding, which ensured the success of the Conference. We hope this book could be, not only a witness of these pandemic times, but a hopeful sign for an equal and inclusive education in all countries

    Modelling motorcycles driving cycles and emissions in Edinburgh

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    The level of ownership and use of motorcycling has increased rapidly in Edinburgh and the UK in the last ten years. In this study, motorcycle driving cycles (rural and urban) were developed for Edinburgh (Edinburgh Motorcycle Driving cycle-EMDC). The analysis of EMDC demonstrates that motorcycles‘ driving behaviour differs between urban and rural areas. EMDC shows a typical transient nature of speed, acceleration and deceleration, which is also different from regulatory driving cycles (Economic Commission for Europe-ECE and World Motorcycle Test Cycle-WMTC) and examples from Asia (Taiwan, Bangkok and China). This research underlines the need for detailed investigations of driving cycles in any local condition. It is not generally feasible for a driving cycle developed in one area to be applicable in another area, even with some similar characteristics.Emission factors were also estimated using onboard, laboratory and micro simulation measurements along the test corridor (Air Quality Management Area-AQMA). Laboratory measurements were carried out by applying a numberof standard driving cycles (ECE and WMTC) and the derived EMDCs.Results show that the emission factors (EFs) calculated in the laboratory for carbon monoxide (CO) and Hydrocarbons (HC) are higher for the urban EMDC cycle compared to the standard regulatory factors than they are for the rural (except Nitrogen Oxide-NOx). Laboratory emission factors for CO and HC for the urban EMDC were found to be higher than the micro-simulation and onboard methods. EFs obtained from micro-simulation and onboard emissions using the National Atmospheric Emission Inventory (NAEI) emission coefficients were not very different with the exception of NOx, which were relatively higher than those of EMDC.Micro simulation models were mainly developed for private cars and therefore special care should be taken when using them for modelling other conditions (e.g. motorcycles driving characteristics). This study illustrates the extent to which micro-simulation may be utilised to accurately model emissions and discusses the refinements required to model motorcycle motion (hence emission) accurately in micro simulation.The study provides a platform for a large number of potential future applications for the evaluation of emissions and for developing various policy scenarios of pollution reduction and reducing health impacts at local levels
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