36 resultados para Compactness Compensated

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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BACKGROUND AND PURPOSE: To describe the clinical implementation of dynamic multileaf collimation (DMLC). Custom compensated four-field treatments of carcinoma of the bladder have been used as a simple test site for the introduction of intensity modulated radiotherapy.MATERIALS AND METHODS: Compensating intensity modulations are calculated from computed tomography (CT) data, accounting for scattered, as well as primary radiation. Modulations are converted to multileaf collimator (MLC) leaf and jaw settings for dynamic delivery on a linear accelerator. A full dose calculation is carried out, accounting for dynamic leaf and jaw motion and transmission through these components. Before treatment, a test run of the delivery is performed and an absolute dose measurement made in a water or solid water phantom. Treatments are verified by in vivo diode measurements and real-time electronic portal imaging. RESULTS: Seven patients have been treated using DMLC. The technique improves dose homogeneity within the target volume, reducing high dose areas and compensating for loss of scatter at the beam edge. A typical total treatment time is 20 min. CONCLUSIONS: Compensated bladder treatments have proven an effective test site for DMLC in an extremely busy clinic.

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We continue the study of multidimensional operator multipliers initiated in~cite{jtt}. We introduce the notion of the symbol of an operator multiplier. We characterise completely compact operator multipliers in terms of their symbol as well as in terms of approximation by finite rank multipliers. We give sufficient conditions for the sets of compact and completely compact multipliers to coincide and characterise the cases where an operator multiplier in the minimal tensor product of two C*-algebras is automatically compact. We give a description of multilinear modular completely compact completely bounded maps defined on the direct product of finitely many copies of the C*-algebra of compact operators in terms of tensor products, generalising results of Saar

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This paper presents the design and implementation of a novel optical fiber temperature compensated relative humidity (RH) sensor device, based on fiber Bragg gratings (FBGs) and developed specifically for monitoring water ingress leading to the deterioration of building stone. The performance of the sensor thus created, together with that of conventional sensors, was first assessed in the laboratory where they were characterized under experimental conditions of controlled wetting and drying cycles of limestone blocks, before being employed “in-the-field” to monitor actual building stone in a specially built wall. Although a new construction, this was built specifically using conservation methods similar to those employed in past centuries, to allow an accurate simulation of processes occurring with wetting and drying in the historic walls in the University of Oxford.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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The paper outlines the effects of polymer conditioning on alum sludge properties, such as floc size, density, fractal dimension (DF) and rheological properties. Experimental results demonstrate that polymer conditioning of alum sludge leads to: larger floc size with a plateau reached in higher doses; higher densities associated with higher doses; increased degree of compactness; and an initial decrease followed by an increase of supernatant viscosity with continued increase in polymer dose. The secondary focus of this paper dwells on a comparison of the estimates of optimum dose using different criteria that emanate from established dewatering tests such as CST, SRF, liquid phase viscosity and modified SRF as well as a simple settlement test in terms of CML30. Alum sludge was derived from a water works treating coloured, low-turbidity raw waters.

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This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.

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Using first principles electronic structure methods, we calculate the effects of boron impurities in bulk copper and at surfaces and grain boundaries. We find that boron segregation to the Sigma5(310)[001] grain boundary should strengthen the boundary up to 1.5 ML coverage (15.24 at./nm2). The maximal effect is observed at 0.5 ML and corresponds to boron atoms filling exclusively grain boundary interstices. In copper bulk, B causes significant distortion both in interstitial and regular lattice sites, for which boron atoms are either too big or too small. The distortion is compensated to a large extent when the interstitial and substitutional boron combine together to form a strongly bound dumbbell. Our prediction is that bound boron impurities should appear in a sizable proportion if not dominate in most experimental conditions. A large discrepancy between calculated heats of solution and experimental terminal solubility of B in Cu is found, indicating either a significant failure of the density functional approach or, more likely, strongly overestimated solubility limits in the existing B-Cu phase diagram.

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Two electrical techniques that are frequently used to characterize radio frequency plasmas are described: current-voltage probes for plasma power input and compensated Langmuir probes for electron energy probability functions and other parameters. The following examples of the use of these techniques, sometimes in conjunction with other diagnostic methods, are presented: plasma source standardization, plasma system comparison, power efficiency, plasma modelling and complex processing plasma mechanisms.