2,294 research outputs found

    A BDD proposal for Probabilistic Switching Activity Estimation

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    Switching activity computation is a essential stage for dynamic power estimation. Binary decision diagrams (BDD) are widely used in probabilistic activity estimation. However, the BDD size used for switching activity increases significantly in respect to the logic function BDDs. In this paper we propose a new BDD structure for activity computations in which important size reductions are achieved with no accuracy loss. The proposal includes the definition of a BDD activity operator. This operator has been implemented in a BDD package and then, in an automated tool. This implementation has permitted the analysis of several circuits and has corroborated the size reductions and the accuracy of the result

    Pure single photons from a trapped atom source

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    Single atoms or atom-like emitters are the purest source of on-demand single photons, they are intrinsically incapable of multi-photon emission. To demonstrate this degree of purity we have realized a tunable, on-demand source of single photons using a single ion trapped at the common focus of high numerical aperture lenses. Our trapped-ion source produces single-photon pulses at a rate of 200 kHz with g2(0)=(1.9±0.2)×103^2(0) = (1.9 \pm 0.2) \times 10^{-3}, without any background subtraction. The corresponding residual background is accounted for exclusively by detector dark counts. We further characterize the performance of our source by measuring the violation of a non-Gaussian state witness and show that its output corresponds to ideal attenuated single photons. Combined with current efforts to enhance collection efficiency from single emitters, our results suggest that single trapped ions are not only ideal stationary qubits for quantum information processing, but promising sources of light for scalable optical quantum networks.Comment: 7 pages plus one page supplementary materia

    Optimal Control of Airport Operations with Gate Capacity Constraints

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    The mitigation of airport surface congestion is an important step towards increasing the efficiency of the air transportation system, and decreasing flight delays. This paper proposes a strategy to control the release of departing flights from their gates with the specific objective of reducing their taxi times and fuel consumption, while limiting the impact on airport throughput. The proposed strategy also explicitly accounts for the practical constraints that arise due to limited gate resources at the airport. A stochastic network abstraction of the airport surface is used to model aircraft movement, and the optimal release time for each aircraft is calculated using dynamic programming. Simulations of operations at Boston's Logan International Airport in the US are used to illustrate the effects of the resultant policies.National Science Foundation (U.S.) (CAREER Award ECCS-0745237)National Science Foundation (U.S.) (Cyber-Physical Systems Award 0931843

    Sensors and Systems for Indoor Positioning

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    This reprint is a reprint of the articles that appeared in Sensors' (MDPI) Special Issue on “Sensors and Systems for Indoor Positioning". The published original contributions focused on systems and technologies to enable indoor applications

    Energy/power consumption model for an embedded processor board

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    This dissertation, whose research has been conducted at the Group of Electronic and Microelectronic Design (GDEM) within the framework of the project Power Consumption Control in Multimedia Terminals (PCCMUTE), focuses on the development of an energy estimation model for the battery-powered embedded processor board. The main objectives and contributions of the work are summarized as follows: A model is proposed to obtain the accurate energy estimation results based on the linear correlation between the performance monitoring counters (PMCs) and energy consumption. the uniqueness of the appropriate PMCs for each different system, the modeling methodology is improved to obtain stable accuracies with slight variations among multiple scenarios and to be repeatable in other systems. It includes two steps: the former, the PMC-filter, to identify the most proper set among the available PMCs of a system and the latter, the k-fold cross validation method, to avoid the bias during the model training stage. The methodology is implemented on a commercial embedded board running the 2.6.34 Linux kernel and the PAPI, a cross-platform interface to configure and access PMCs. The results show that the methodology is able to keep a good stability in different scenarios and provide robust estimation results with the average relative error being less than 5%. Este trabajo fin de máster, cuya investigación se ha desarrollado en el Grupo de Diseño Electrónico y Microelectrónico (GDEM) en el marco del proyecto PccMuTe, se centra en el desarrollo de un modelo de estimación de energía para un sistema empotrado alimentado por batería. Los objetivos principales y las contribuciones de esta tesis se resumen como sigue: Se propone un modelo para obtener estimaciones precisas del consumo de energía de un sistema empotrado. El modelo se basa en la correlación lineal entre los valores de los contadores de prestaciones y el consumo de energía. Considerando la particularidad de los contadores de prestaciones en cada sistema, la metodología de modelado se ha mejorado para obtener precisiones estables, con ligeras variaciones entre escenarios múltiples y para replicar los resultados en diferentes sistemas. La metodología incluye dos etapas: la primera, filtrado-PMC, que consiste en identificar el conjunto más apropiado de contadores de prestaciones de entre los disponibles en un sistema y la segunda, el método de validación cruzada de K iteraciones, cuyo fin es evitar los sesgos durante la fase de entrenamiento. La metodología se implementa en un sistema empotrado que ejecuta el kernel 2.6.34 de Linux y PAPI, un interfaz multiplataforma para configurar y acceder a los contadores. Los resultados muestran que esta metodología consigue una buena estabilidad en diferentes escenarios y proporciona unos resultados robustos de estimación con un error medio relativo inferior al 5%
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