Directional algebraic reconstruction technique for electrical impedance tomography

We assume that the resistance matrix can be found in electrical impedance tomography from the assumption of linear dependence between the voltages and the currents and with the help of the resistance matrix and the transfer impedance between the electrodes, a directional algebraic reconstruction technique is proposed. The goal is to reconstruct the resistivity distribution by weighting the matrices that are obtained by calculating the orthogonal distance of the underlying mesh elements from the neighbouring port resistivity lines. These weighting matrices, which only depend on the topology of the underlying mesh, can be calculated offline and result in a computationally efficient online procedure with a reasonable image reconstruction performance. Simulation results are provided to validate this approach.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.

Options for achieving a 50% cut in industrial carbon emissions by 2050.

Carbon emissions from industry are dominated by production of goods in steel, cement plastic, paper, and aluminum. Demand for these materials is anticipated to double at least by 2050, by which time global carbon emissions must be reduced by at least 50%. To evaluate the challenge of meeting this target the global flows of these materials and their associated emissions are projected to 2050 under five technical scenarios. A reference scenario includes all existing and emerging efficiency measures but cannot provide sufficient reduction. The application of carbon sequestration to primary production proves to be sufficient only for cement The emissions target can always be met by reducing demand, for instance through product life extension, material substitution, or "light-weighting". Reusing components shows significant potential particularly within construction. Radical process innovation may also be possible. The results show that the first two strategies, based on increasing primary production, cannot achieve the required emissions reductions, so should be balanced by the vigorous pursuit of material efficiency to allow provision of increased material services with reduced primary production.

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty

Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller) or as an added value (risk-seeking controller) to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models. © 2010 Nagengast et al.

The technical potential for reducing metal requirements through lightweight product design

Metal production consumes around 10% of all global energy, so is a significant driver of climate change and other concerns about sustainability. Demand for metal is rising and forecast to double by 2050 through a combination of growing total demand from developing countries, and ongoing replacement demand in developed economies. Metal production is already extremely efficient, so the major opportunities for emissions abatement in the sector are likely to arise from material efficiency - using less new metal to meet demand for services. Therefore this paper examines the opportunity to reduce requirements for steel and aluminium by lightweight design. A set of general principles for lightweight design are proposed by way of a simple analytical example, and are then applied to five case study products which cumulatively account for 30% of global steel product output. It is shown that exploiting lightweight design opportunities for these five products alone could reduce global steel requirements by 5%, and similar savings in aluminium products could reduce global aluminium requirements by 7%. If similar savings to those in the design case studies were possible in all steel and aluminium products, total material requirements could be reduced by 25-30%. However, many of these light-weighting measures are, at present, economically unattractive, and may take many years to implement. © 2011 Elsevier B.V. All rights reserved.

Use of contexts in language model interpolation and adaptation

Language models (LMs) are often constructed by building multiple individual component models that are combined using context independent interpolation weights. By tuning these weights, using either perplexity or discriminative approaches, it is possible to adapt LMs to a particular task. This paper investigates the use of context dependent weighting in both interpolation and test-time adaptation of language models. Depending on the previous word contexts, a discrete history weighting function is used to adjust the contribution from each component model. As this dramatically increases the number of parameters to estimate, robust weight estimation schemes are required. Several approaches are described in this paper. The first approach is based on MAP estimation where interpolation weights of lower order contexts are used as smoothing priors. The second approach uses training data to ensure robust estimation of LM interpolation weights. This can also serve as a smoothing prior for MAP adaptation. A normalized perplexity metric is proposed to handle the bias of the standard perplexity criterion to corpus size. A range of schemes to combine weight information obtained from training data and test data hypotheses are also proposed to improve robustness during context dependent LM adaptation. In addition, a minimum Bayes' risk (MBR) based discriminative training scheme is also proposed. An efficient weighted finite state transducer (WFST) decoding algorithm for context dependent interpolation is also presented. The proposed technique was evaluated using a state-of-the-art Mandarin Chinese broadcast speech transcription task. Character error rate (CER) reductions up to 7.3 relative were obtained as well as consistent perplexity improvements. © 2012 Elsevier Ltd. All rights reserved.

A Novel Passive UHF RFID Real Time Location Sensing System

Ubiquitous in-building Real Time Location Systems (RTLS) today are limited by costly active radio frequency identification (RFID) tags and short range portal readers of low cost passive RFID tags. We, however, present a novel technology locates RFID tags using a new approach based on (a) minimising RFID fading using antenna diversity, frequency dithering, phase dithering and narrow beam-width antennas, (b) measuring a combination of RSSI and phase shift in the coherent received tag backscatter signals and (c) being selective of use of information from the system by, applying weighting techniques to minimise error. These techniques make it possible to locate tags to an accuracy of less than one metre. This breakthrough will enable, for the first time, the low-cost tagging of items and the possibility of locating them at relatively high precision.

From subspace learning to distance learning: A geometrical optimization approach

In this paper, we adopt a differential-geometry viewpoint to tackle the problem of learning a distance online. As this problem can be cast into the estimation of a fixed-rank positive semidefinite (PSD) matrix, we develop algorithms that exploits the rich geometry structure of the set of fixed-rank PSD matrices. We propose a method which separately updates the subspace of the matrix and its projection onto that subspace. A proper weighting of the two iterations enables to continuously interpolate between the problem of learning a subspace and learning a distance when the subspace is fixed. © 2009 IEEE.

Effect of95 241Am(n, γ) reaction branching ratio on fuel cycle and reactor design characteristics

The growing interest in innovative reactors and advanced fuel cycle designs requires more accurate prediction of various transuranic actinide concentrations during irradiation or following discharge because of their effect on reactivity or spent-fuel emissions, such as gamma and neutron activity and decay heat. In this respect, many of the important actinides originate from the 241Am(n,γ) reaction, which leads to either the ground or the metastable state of 242Am. The branching ratio for this reaction depends on the incident neutron energy and has very large uncertainty in the current evaluated nuclear data files. This study examines the effect of accounting for the energy dependence of the 241Am(n,γ) reaction branching ratio calculated from different evaluated data files for different reactor and fuel types on the reactivity and concentrations of some important actinides. The results of the study confirm that the uncertainty in knowing the 241Am(n,γ) reaction branching ratio has a negligible effect on the characteristics of conventional light water reactor fuel. However, in advanced reactors with large loadings of actinides in general, and 241Am in particular, the branching ratio data calculated from the different data files may lead to significant differences in the prediction of the fuel criticality and isotopic composition. Moreover, it was found that neutron energy spectrum weighting of the branching ratio in each analyzed case is particularly important and may result in up to a factor of 2 difference in the branching ratio value. Currently, most of the neutronic codes have a single branching ratio value in their data libraries, which is sometimes difficult or impossible to update in accordance with the neutron spectrum shape for the analyzed system.

Reconfigurable predictive control for redundantly actuated systems with parameterised input constraints

A method is proposed for on-line reconfiguration of the terminal constraint used to provide theoretical nominal stability guarantees in linear model predictive control (MPC). By parameterising the terminal constraint, its complete reconstruction is avoided when input constraints are modified to accommodate faults. To enlarge the region of feasibility of the terminal control law for a certain class of input faults with redundantly actuated plants, the linear terminal controller is defined in terms of virtual commands. A suitable terminal cost weighting for the reconfigurable MPC is obtained by means of an upper bound on the cost for all feasible realisations of the virtual commands from the terminal controller. Conditions are proposed that guarantee feasibility recovery for a defined subset of faults. The proposed method is demonstrated by means of a numerical example. © 2013 Elsevier B.V. All rights reserved.