844 resultados para System Performance Measures.


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Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

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Discrete time control systems require sample- and-hold circuits to perform the conversion from digital to analog. Fractional-Order Holds (FROHs) are an interpolation between the classical zero and first order holds and can be tuned to produce better system performance. However, the model of the FROH is somewhat hermetic and the design of the system becomes unnecessarily complicated. This paper addresses the modelling of the FROHs using the concepts of Fractional Calculus (FC). For this purpose, two simple fractional-order approximations are proposed whose parameters are estimated by a genetic algorithm. The results are simple to interpret, demonstrating that FC is a useful tool for the analysis of these devices.

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This paper studies fractional variable structure controllers. Two cases are considered namely, the sliding reference model and the control action, that are generalized from integer into fractional orders. The test bed consists in a mechanical manipulator and the effect of the fractional approach upon the system performance is evaluated. The results show that fractional dynamics, both in the switching surface and the control law are important design algorithms in variable structure controllers.

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This paper presents a comparison between proportional integral control approaches for variable speed wind turbines. Integer and fractional-order controllers are designed using linearized wind turbine model whilst fuzzy controller also takes into account system nonlinearities. These controllers operate in the full load region and the main objective is to extract maximum power from the wind turbine while ensuring the performance and reliability required to be integrated into an electric grid. The main contribution focuses on the use of fractional-order proportional integral (FOPI) controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. A comparison between proposed control approaches for the variable speed wind turbines is presented using a wind turbine benchmark model in the Matlab/Simulink environment. Results show that FOPI has improved system performance when compared with classical PI and fuzzy PI controller outperforms the integer and fractional-order control due to its capability to deal with system nonlinearities and uncertainties. © 2014 IEEE.

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The trajectory planning of redundant robots through the pseudoinverse control leads to undesirable drift in the joint space. This paper presents a new technique to solve the inverse kinematics problem of redundant manipulators, which uses a fractional differential of order α to control the joint positions. Two performance measures are defined to examine the strength and weakness of the proposed method. The positional error index measures the precision of the manipulator's end-effector at the target position. The repeatability performance index is adopted to evaluate if the joint positions are repetitive when the manipulator execute repetitive trajectories in the operational workspace. Redundant and hyper-redundant planar manipulators reveal that it is possible to choose in a large range of possible values of α in order to get repetitive trajectories in the joint space.

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Dynamically reconfigurable SRAM-based field-programmable gate arrays (FPGAs) enable the implementation of reconfigurable computing systems where several applications may be run simultaneously, sharing the available resources according to their own immediate functional requirements. To exclude malfunctioning due to faulty elements, the reliability of all FPGA resources must be guaranteed. Since resource allocation takes place asynchronously, an online structural test scheme is the only way of ensuring reliable system operation. On the other hand, this test scheme should not disturb the operation of the circuit, otherwise availability would be compromised. System performance is also influenced by the efficiency of the management strategies that must be able to dynamically allocate enough resources when requested by each application. As those resources are allocated and later released, many small free resource blocks are created, which are left unused due to performance and routing restrictions. To avoid wasting logic resources, the FPGA logic space must be defragmented regularly. This paper presents a non-intrusive active replication procedure that supports the proposed test methodology and the implementation of defragmentation strategies, assuring both the availability of resources and their perfect working condition, without disturbing system operation.

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Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

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Atualmente, existe uma constante necessidade de inovação tecnológica e organizacional das empresas, face às exigências do mercado e ao aumento constante da competitividade. No contexto da economia atual, e para contrariar a falta de investimento dos últimos anos, as empresas concentram-se no desenvolvimento de negócios bem estruturados e organizados, que satisfaçam as exigências de cada cliente. Revela-se, assim, muito importante a avaliação de desempenho para o alcance do seu sucesso, permitindo alinhar as atividades operacionais com a visão organizacional, fomentar a comunicação da estratégia e gerir o seu desempenho. É neste contexto que ganha importância o Balanced Scorecard, um instrumento que permite avaliar o desempenho organizacional, funcionando também como uma ferramenta de gestão. Tem, portanto, como principais objetivos definir claramente uma estratégia, definir objetivos, indicadores e medidas estratégicas, planear e estabelecer metas e melhorar continuamente os resultados obtidos. Esta ferramenta analisa a organização em quatro diferentes perspetivas: financeira, clientes, processos internos e apendizagem e crescimento. Cada uma delas deve estrututrar os seus próprios objetivos, indicadores, metas e iniciativas de forma a contribuir para o desenvolvimento da estratégia da organização e avaliar o seu desempenho. O desafio deste relatório é adaptar esta metodologia durante a realização de um estágio curricular na empresa Bysteel, que tem por base a implementação de um processo de gestão estratégica nas suas empreitadas, através do Balanced Scorecard. Este planemamento surge como um dos principais requisitos para uma gestão eficaz de custos e de tempo planeados para cada empreitada da Bysteel. Este processo torna-se bastante complexo dado que cada obra apresenta diferentes particularidades. A implementação desta metodologia numa empresa desta dimensão é um fator muito motivador, tornando-se ainda mais interessante pelo facto de se tratar de uma implementação numa nova vertente.

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In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

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Mutual fund managers increasingly lend their holdings and/or use short sales to generate higher returns for their funds. This project presents a first look into the impact these practices on performance using the performance measures: i) Characteristic Selectivity (CS), the ability of the fund's managers to choose stocks that outperform their benchmarks; ii) Characteristic Timing (CT), the ability of the manager to time the market; iii) and Average Style (AS), the returns from funds systematically holding stocks with certain characteristics. These returns are computed through the DGTW benchmarks. The effect of other variables that have also been shown to impact fund’s returns – total net assets under management, investment styles, turnover and expense ratios – will also be analyzed. I find that managers who use short-sales do not exhibit better stock picking abilities than those who do not, while mutual funds that lend do present higher CS returns. In addition, while lending is not significant for the total performance of a fund, the employment of short-sales and of both short-sales and lending has a negative impact on the fund’s performance.

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Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

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The implementation of imagery and video feedback programs has become an important tool for aiding athletes in achieving peak performance (Halliwell, 1990). The purpose of the study was to determine the effect of strategic imagery training and video feedback on immediate performance. Participants were two university goaltenders. An alternating treatment design (ATD; Barlow & Hayes, 1979; Tawney & Gast, 1984) was employed. The strategies were investigated using three plays originating from the right side by a right-handed shooting defenceman from the blueline. The baseline condition consisted of six practices and was used to establish a stable and "ideal" measure of performance. The intervention conditions included alternating the use of strategic imagery (Cognitive general; Paivio, 1985) and video feedback. Both participants demonstrated an increase in the frequency of Cognitive general use. Specific and global performance measures were assessed to determine the relative effectiveness of the interventions. Poor inter-rater reliability resulted in the elimination of specific performance measures. Consequently, only the global measure (i.e., save percentage) was used in subsequent analyses. Visual inspection of participant save percentage was conducted to determine the benefits of the intervention. Strategic imagery training resulted in performance improvements for both participants. Video feedback facilitated performance for Participant 2, but not Participant 1. Results are discussed with respect to imagery and video interventions and the challenges associated with applied research. KEYWORDS: imagery, video, goaltenders, alternating treatment design.