899 resultados para Recall campaigns.


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This paper describes the first five SEALS Evaluation Campaigns over the semantic technologies covered by the SEALS project (ontology engineering tools, ontology reasoning tools, ontology matching tools, semantic search tools, and semantic web service tools). It presents the evaluations and test data used in these campaigns and the tools that participated in them along with a comparative analysis of their results. It also presents some lessons learnt after the execution of the evaluation campaigns and draws some final conclusions.

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The aim of this contribution is to present a theoretical approach and two experimental campaigns (on wind tunnel and on the track) concerning the research work about the ballast train-induced-wind erosion (BTIWE) phenomenon. When a high speed train overpasses the critical speed, it produces a wind speed close to the track large enough to start the motion of the ballast elements, eventually leading to the rolling of the stones (Kwon and Park, 2006) and, if these stones get enough energy, they can jump and then initiate a saltation-like chain reaction, as found in the saltation processes of soil eolian erosion (Bagnold, 1941). The expelled stones can reach a height which is larger than the lowest parts of the train, striking them (and the track surroundings) producing considerable damage that should be avoided. There is not much published work about this phenomenon, in spite of the great interest that exists due to its relevant applications in increasing the maximum operative train speed. Particularly, the initiation of flight of ballast due to the pass of a high speed train has been studied by Kwon and Park (2006) by performing field and wind tunnel experiments.

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The impact of disruptions in JET became even more important with the replacement of the previous Carbon Fiber Composite (CFC) wall with a more fragile full metal ITER-like wall (ILW). The development of robust disruption mitigation systems is crucial for JET (and also for ITER). Moreover, a reliable real-time (RT) disruption predictor is a pre-requisite to any mitigation method. The Advance Predictor Of DISruptions (APODIS) has been installed in the JET Real-Time Data Network (RTDN) for the RT recognition of disruptions. The predictor operates with the new ILW but it has been trained only with discharges belonging to campaigns with the CFC wall. 7 realtime signals are used to characterize the plasma status (disruptive or non-disruptive) at regular intervals of 1 ms. After the first 3 JET ILW campaigns (991 discharges), the success rate of the predictor is 98.36% (alarms are triggered in average 426 ms before the disruptions). The false alarm and missed alarm rates are 0.92% and 1.64%.

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