5 resultados para Trinity College (Dublin, Ireland)

em Universidad Politécnica de Madrid


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This paper introduces a novel technique for identifying logically related sections of the heap such as recursive data structures, objects that are part of the same multi-component structure, and related groups of objects stored in the same collection/array. When combined withthe lifetime properties of these structures, this information can be used to drive a range of program optimizations including pool allocation, object co-location, static deallocation, and region-based garbage collection. The technique outlined in this paper also improves the efficiency of the static analysis by providing a normal form for the abstract models (speeding the convergence of the static analysis). We focus on two techniques for grouping parts of the heap. The first is a technique for precisely identifying recursive data structures in object-oriented programs based on the types declared in the program. The second technique is a novel method for grouping objects that make up the same composite structure and that allows us to partition the objects stored in a collection/array into groups based on a similarity relation. We provide a parametric component in the similarity relation in order to support specific analysis applications (such as a numeric analysis which would need to partition the objects based on numeric properties of the fields). Using the Barnes-Hut benchmark from the JOlden suite we show how these grouping methods can be used to identify various types of logical structures allowing the application of many region-based program optimizations.

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Renewable energy sources are believed to reduce drastically greenhouse gas emissions that would otherwise be generated from fossil fuels used to generate electricity. This implies that a unit of renewable energy will replace a unit of fossil-fuel, with its CO2 emissions, on an equivalent basis (with no other effects on the grid). But, the fuel economy and emissions in the existing power systems are not proportional with the electricity production of intermittent sources due to cycling of the fossil fuel plants that make up the balance of the grid (i.e. changing the power output makes thermal units to operate less efficiently). This study focuses in the interactions between wind generation and thermal plants cycling, by establishing the levels of extra fuel use caused by decreased efficiencies of fossil back-up for wind electricity in Spain. We analyze the production of all thermal plants in 2011, studying different scenarios where wind penetration causes major deviations in programming, while we define a procedure for quantifying the carbon reductions by using emission factors and efficiency curves from the existing installations. The objectives are to discuss the real contributions of renewable energies to the environmental targets as well as suggest alternatives that would improve the reliability of future power systems.

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The recent continuous development of Cooperative ITS has resulted in several initiatives which focus on different parts of the Cooperative environment landscape. The FOTsis project focuses on the infrastructure side of the Cooperative environment and will deploy and test 7 services designed to maximise the benefits of the integration of the road operator and infrastructure-based information providers into the ITS environment. This integration can take place in any of the stages of data collection, processing and actuations of the services, but also support and trigger external tasks such as operations of the emergency response entities, etc. This paper describes the current status of the project and focuses on the specification of the supporting architecture to the services tested: references, a brief outline of the requirements’ definition, and the FOTsis architecture proposal, with some conclusions about the architecture tests conducted. The outlook on the project’s next steps is given in the last section of the paper.

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This paper describes our participation at SemEval- 2014 sentiment analysis task, in both contextual and message polarity classification. Our idea was to com- pare two different techniques for sentiment analysis. First, a machine learning classifier specifically built for the task using the provided training corpus. On the other hand, a lexicon-based approach using natural language processing techniques, developed for a ge- neric sentiment analysis task with no adaptation to the provided training corpus. Results, though far from the best runs, prove that the generic model is more robust as it achieves a more balanced evaluation for message polarity along the different test sets.

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El gen AtbZIP44 se expresa en el endospermo micropilar y en la radícula de semillas en germinación. El mRNA del gen AtbZIP9 se localiza también en la radícula. Se realizan experimentos de interacción proteína-proteína entre los correspondientes factores transcripcionales.