30 resultados para optimize

em Cambridge University Engineering Department Publications Database


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This work represents a contribution to the field of sustainable electricity system design by using an optimization tool to specify the final mix composition, subject to the constraints of: emissions that are within the biocapacity of the region; a diverse and robust electricity supply system; and supply that at least meets current demand. The 25-country European Union (EU-25) is used as a case study. All the goals, save diversity, can be met by re-structuring the current fuel mix, thus maintaining current consumption levels. The diversity target is only met when consumption is reduced by 10-15% and the constraint on maximum material throughput is relaxed. Re-structuring the mix and reducing consumption is insufficient to achieve a sustainable EU carbon footprint. However, the solution proposed singlehandedly allows the EU to meet its Kyoto emissions target as well as its 2007 policy of a reduction of 20% in greenhouse gas emissions by 2020. © 2007 Elsevier Ltd. All rights reserved.

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This paper investigates unsupervised test-time adaptation of language models (LM) using discriminative methods for a Mandarin broadcast speech transcription and translation task. A standard approach to adapt interpolated language models to is to optimize the component weights by minimizing the perplexity on supervision data. This is a widely made approximation for language modeling in automatic speech recognition (ASR) systems. For speech translation tasks, it is unclear whether a strong correlation still exists between perplexity and various forms of error cost functions in recognition and translation stages. The proposed minimum Bayes risk (MBR) based approach provides a flexible framework for unsupervised LM adaptation. It generalizes to a variety of forms of recognition and translation error metrics. LM adaptation is performed at the audio document level using either the character error rate (CER), or translation edit rate (TER) as the cost function. An efficient parameter estimation scheme using the extended Baum-Welch (EBW) algorithm is proposed. Experimental results on a state-of-the-art speech recognition and translation system are presented. The MBR adapted language models gave the best recognition and translation performance and reduced the TER score by up to 0.54% absolute. © 2007 IEEE.

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In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.

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A microstructure based acoustic model is introduced, which can be used to optimize the microstructure of cellular materials and thus to obtain their optimal acoustic property. This acoustic model is an unsteady one which is appropriate in the limit of low Reynolds numbers. The model involves three elements. This first involves the propagation of acoustic waves passing the cylinders whose axes are aligned parallel to the direction of propagation. The second model relates to the propagation of acoustic waves passing the cylinders whose axes are aligned perpendicular to the direction of propagation. In both cases the interaction between adjacent cylinders is taken into account by considering the effect of polygonal periodic boundary conditions. As these two models are linear they are combined to give the characteristics of propagation at arbitrary incidence. The third model involves propagation passing spheres in order to represent the joints. Heat transfer is also included. These three models are then used to expand the design space and calculate the optimum cell structure for desired acoustic performance in a number of different applications. Moreover, the application fields are also analyzed.

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Numerous psychophysical studies suggest that the sensorimotor system chooses actions that optimize the average cost associated with a movement. Recently, however, violations of this hypothesis have been reported in line with economic theories of decision-making that not only consider the mean payoff, but are also sensitive to risk, that is the variability of the payoff. Here, we examine the hypothesis that risk-sensitivity in sensorimotor control arises as a mean-variance trade-off in movement costs. We designed a motor task in which participants could choose between a sure motor action that resulted in a fixed amount of effort and a risky motor action that resulted in a variable amount of effort that could be either lower or higher than the fixed effort. By changing the mean effort of the risky action while experimentally fixing its variance, we determined indifference points at which participants chose equiprobably between the sure, fixed amount of effort option and the risky, variable effort option. Depending on whether participants accepted a variable effort with a mean that was higher, lower or equal to the fixed effort, they could be classified as risk-seeking, risk-averse or risk-neutral. Most subjects were risk-sensitive in our task consistent with a mean-variance trade-off in effort, thereby, underlining the importance of risk-sensitivity in computational models of sensorimotor control.

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We describe a novel constitutive model of lung parenchyma, which can be used for continuum mechanics based predictive simulations. To develop this model, we experimentally determined the nonlinear material behavior of rat lung parenchyma. This was achieved via uni-axial tension tests on living precision-cut rat lung slices. The resulting force-displacement curves were then used as inputs for an inverse analysis. The Levenberg-Marquardt algorithm was utilized to optimize the material parameters of combinations and recombinations of established strain-energy density functions (SEFs). Comparing the best-fits of the tested SEFs we found Wpar = 4.1 kPa(I1-3)2 + 20.7 kPa(I1 - 3)3 + 4.1 kPa(-2 ln J + J2 - 1) to be the optimal constitutive model. This SEF consists of three summands: the first can be interpreted as the contribution of the elastin fibers and the ground substance, the second as the contribution of the collagen fibers while the third controls the volumetric change. The presented approach will help to model the behavior of the pulmonary parenchyma and to quantify the strains and stresses during ventilation.

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We present electro-optic characteristics of a transparent nanophotonic device fabricated on quartz substrate based on multiwall carbon nanotubes and nematic liquid crystals (LCs). The nanotube electrodes spawn a Gaussian electric field to three dimensionally address the LC molecules. The electro-optic characteristics of the device were investigated to optimize the device performance and it was found that lower driving voltages were suitable for microlens array and phase modulation applications, while higher driving voltages with a holding voltage can be used for display-related applications.

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In recent years a variety of experimental and theoretical work has been reported on the use of semiconductor optical amplifiers for high speed wavelength conversion. However little work has addressed the dynamic limitations of this conversion process in detail with a view to device optimization. In this paper, a detailed study of the conversion process is carried out in order to optimize device parameters and drive conditions for increased conversion speed and improved modulation index.

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Photoluminescence experiments have identified strain as the origin for polarization pinning in vertical cavity surface emitting lasers post-processed by focused ion beam etching. Theoretical models were applied to deduce the strain in devices. Post-annealing was used to optimize polarization pinning.

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Supply chain tracking information is one of the main levers for achieving operational efficiency. RFID technology and the EPC Network can deliver serial-level product information that was never before available. However, these technologies still fail to meet the managers' visibility requirements in full, since they provide information about product location at specific time instances only. This paper proposes a model that uses the data provided by the EPC Network to deliver enhanced tracking information to the final user. Following a Bayesian approach, the model produces realistic ongoing estimates about the current and future location of products across a supply network, taking into account the characteristics of the product behavior and the configuration of the data collection points. These estimates can then be used to optimize operational decisions that depend on product availability at different locations. The enhancement of tracking information quality is highlighted through an example. © 2009 IFAC.

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It is shown that reflective liquid crystal on silicon (LCOS) spatial light modulator (SLM) based interconnects or fiber switches that use defocus to reduce crosstalk can be evaluated and optimized using a fractional Fourier transform if certain optical symmetry conditions are met. Theoretically the maximum allowable linear hologram phase error compared to a Fourier switch is increased by a factor of six before the target crosstalk for telecom applications of -40 dB is exceeded. A Gerchberg-Saxton algorithm incorporating a fractional Fourier transform modified for use with a reflective LCOS SLM is used to optimize multi-casting holograms in a prototype telecom switch. Experiments are in close agreement to predicted performance. © 2012 Optical Society of America.

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With increasing demands on storage devices in the modern communication environment, the storage area network (SAN) has evolved to provide a direct connection allowing these storage devices to be accessed efficiently. To optimize the performance of a SAN, a three-stage hybrid electronic/optical switching node architecture based on the concept of a MPLS label switching mechanism, aimed at serving as a multi-protocol label switching (MPLS) ingress label edge router (LER) for a SAN-enabled application, has been designed. New shutter-based free-space multi-channel optical switching cores are employed as the core switch fabric to solve the packet contention and switching path conflict problems. The system-level node architecture design constraints are evaluated through self-similar traffic sourced from real gigabit Ethernet network traces and storage systems. The extension performance of a SAN over a proposed WDM ring network, aimed at serving as an MPLS-enabled transport network, is also presented and demonstrated. © 2012 OSA.

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Mixtures of two proprietary low molar mass organosiloxane liquid crystals were studied in order to improve their alignment and optimize their electro-optic properties for telecommunication applications. Over a certain concentration range, mixtures exhibited an isotropic-chiral smectic A-chiral smectic C (Iso-SmA*-SmC*) phase sequence leading to exceptionally good alignment. At room temperature, the spontaneous polarization of these samples was reduced from 225 nC cm -2 in the pure SmC* liquid crystal to as low as 75 nC cm -2 in the mixture. Within this concentration range, the ferroelectric tilt angle could be varied between 35° and 15°, while the rise time decreased by 69.4%. The rise times were < 45 μs for moderate electric fields of ± 10 V μm -1 in the SmC* phase and ∼ 4 μs, independent of electric field, in the SmA* phase. At λ = 1550 nm, these mixtures exhibited very large extinction ratios of {\sim} 60 dB for binary switching in the SmC* phase and ∼ 55 dB continuous variable attenuation in the SmA* phase. © 2012 IEEE.