53 resultados para Experimental algorithms


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This paper describes the trigger and offline reconstruction, identification and energy calibration algorithms for hadronic decays of tau leptons employed for the data collected from pp collisions in 2012 with the ATLAS detector at the LHC center-of-mass energy s√ = 8 TeV. The performance of these algorithms is measured in most cases with Z decays to tau leptons using the full 2012 dataset, corresponding to an integrated luminosity of 20.3 fb−1. An uncertainty on the offline reconstructed tau energy scale of 2% to 4%, depending on transverse energy and pseudorapidity, is achieved using two independent methods. The offline tau identification efficiency is measured with a precision of 2.5% for hadronically decaying tau leptons with one associated track, and of 4% for the case of three associated tracks, inclusive in pseudorapidity and for a visible transverse energy greater than 20 GeV. For hadronic tau lepton decays selected by offline algorithms, the tau trigger identification efficiency is measured with a precision of 2% to 8%, depending on the transverse energy. The performance of the tau algorithms, both offline and at the trigger level, is found to be stable with respect to the number of concurrent proton--proton interactions and has supported a variety of physics results using hadronically decaying tau leptons at ATLAS.

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This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

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This paper proposes a single-phase reconfigurable battery charger for Electric Vehicle (EV) that operates in three different modes: Grid-to-Vehicle (G2V) mode, in which the traction batteries are charged from the power grid; Vehicle-to-Grid (V2G) mode, in which the traction batteries deliver part of the stored energy back to the power grid; and in Traction-to-Auxiliary (T2A) mode, in which the auxiliary battery is charged from the traction batteries. When connected to the power grid, the battery charger works with sinusoidal current in the AC side, for both G2V and V2G modes, and also regulates the reactive power. When the EV is disconnected from the power grid, the control algorithms are modified and the full-bridge AC-DC bidirectional converter works as a full-bridge isolated DC-DC converter that is used to charge the auxiliary battery of the EV, avoiding the use of an additional charger to accomplish this task. To assess the behavior of the proposed reconfigurable battery charger under different operation scenarios, a 3.6 kW laboratory prototype has been developed and experimental results are presented.

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Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.

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Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

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In this contribution, original limit analysis numerical results are presented dealing with some reinforced masonry arches tested at the University of Minho-UMinho, PT. Twelve in-scale circular masonry arches were considered, reinforced in various ways at the intrados or at the extrados. GFRP reinforcements were applied either on undamaged or on previously damaged elements, in order to assess the role of external reinforcements even in repairing interventions. The experimental results were critically discussed at the light of limit analysis predictions, based on a 3D FE heterogeneous upper bound approach. Satisfactory agreement was found between experimental evidences and the numerical results, in terms of failure mechanisms and peak load.

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Many democratic decision making institutions involve quorum rules. Such rules are commonly motivated by concerns about the “legitimacy” or “representativeness” of decisions reached when only a subset of eligible voters participates. A prominent example of this can be found in the context of direct democracy mechanisms, such as referenda and initiatives. We conduct a laboratory experiment to investigate the consequences of the two most common types of quorum rules: a participation quorum and an approval quorum. We find that both types of quora lead to lower participation rates, dramatically increasing the likelihood of full-fledged electoral boycotts on the part of those who endorse the Status Quo. This discouraging effect is significantly larger under a participation quorum than under an approval quorum.

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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

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This paper proposes a methodology for improvement of energy efficiency in buildings through the innovative simultaneous incorporation of three distinct phase change materials (here termed as hybrid PCM) in plastering mortars for façade walls. The thermal performance of a hybrid PCM mortar was experimentally evaluated by comparing the behaviour of a prototype test cell (including hybrid PCM plastering mortar) subjected to realistic daily temperature profiles, with the behaviour of a similar prototype test cell, in which no PCM was added. A numerical simulation model was employed (using ANSYS-FLUENT) to validate the capacity of simulating temperature evolution within the prototype containing hybrid PCM, as well as to understand the contribution of hybrid PCM to energy efficiency. Incorporation of hybrid PCM into plastering mortars was found to have the potential to significantly reduce heating/cooling temperature demands for maintaining the interior temperature within comfort levels when compared to normal mortars (without PCM), or even mortars comprising a single type of PCM.

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High performance concrete (HPC) offers several advantages over normal-strength concrete, namely, high mechanical strength and high durability. Therefore, HPC allows for concrete structures with less steel reinforcement and a longer service life, both of which are crucial issues in the eco-efficiency of construction materials. Nevertheless international publications on the field of concrete containing nanoparticles are scarce when compared to Portland cement concrete (around 1%) of the total international publications. HPC nanoparticle-based publications are even scarcer. This article presents the results of an experimental investigation on the mechanical properties and durability of HPC based on nano-TiO2 and fly ash. The durability performance was assessed by means of water absorption by immersion, water absorption by capillarity, ultrasonic pulse velocity, electric resistivity, chloride diffusion and resistance to sulphuric acid attack. The results show that the concretes containing an increased content of nano-TiO2 show decreased durability performance. The results also show that concrete with 1% nano-TiO2 and 30% fly ash as Portland cement replacement show a high mechanical strength (C55/C67) and a high durability. However, it should be noted that the cost of nano-TiO2 is responsible for a severe increase in the cost of concrete mixtures.

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PhD thesis in Biomedical Engineering

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Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.

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Documento submetido para revisão pelos pares. A publicar em Journal of Parallel and Distributed Computing. ISSN 0743-7315