A new battery modelling method based on simulation error minimization

A new battery modelling method is presented based on the simulation error minimization criterion rather than the conventional prediction error criterion. A new integrated optimization method to optimize the model parameters is proposed. This new method is validated on a set of Li ion battery test data, and the results confirm the advantages of the proposed method in terms of the model generalization performance and long-term prediction accuracy.

Dual-Diversity Combining for Constrained Resource Allocation and Throughput Maximization in OFDMA Networks

Al Rawi, Anas F., Emiliano Garcia-Palacios, Sonia Aissa, Charalampos C. Tsimenidis, and Bayan S. Sharif. "Dual-Diversity Combining for Constrained Resource Allocation and Throughput Maximization in OFDMA Networks." In Vehicular Technology Conference (VTC Spring), 2013 IEEE 77th, pp. 1-5. IEEE, 2013.

Exploiting Significance of Computations for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for environments with energy constraints, provided that applications are given the mechanisms to produce outputs of the highest possible quality within the available energy budget. This paper introduces a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows developers to structure the computation in different tasks, and to express the relative importance of these tasks for the quality of the end result. For non-significant tasks, the developer can also supply less costly, approximate versions. The target energy consumption for a given execution is specified when the application is launched. A significance-aware runtime system employs an application-specific analytical energy model to decide how many cores to use for the execution, the operating frequency for these cores, as well as the degree of task approximation, so as to maximize the quality of the output while meeting the user-specified energy constraints. Evaluation on a dual-socket 16-core Intel platform using 9 benchmark kernels shows that the proposed framework picks the optimal configuration with high accuracy. Also, a comparison with loop perforation (a well-known compile-time approximation technique), shows that the proposed framework results in significantly higher quality for the same energy budget.

A box in the field: modernity and the barn in twentieth-century Ireland

This paper argues that the modern barn in Ireland is a complex social and architectural phenomena that is without, or has yet to find, a satisfactory discourse. Emerging in the middle third of the twentieth century, the modern barn – replete with corrugated iron and I-sections – continues to represent a presence in the Irish landscape whose ubiquity is as emphatic as its flexibility. It is, however, its universal properties that begin to suggest connections with wider narratives. The modernising aspects of the barn that appear in the 1920s and 30s begin to conflate with a rhetoric of architectural modernism which was simultaneously appearing across Europe. But while the relationship between high modernism’s critique of what it divined as the inspirational qualities of utilitarian buildings – Walter Gropius on grain silos, Le Corbusier on aircraft hangers etc. – has been well-documented, in Ireland this relationship perhaps contains another layer of complexity.
The barn’s consolidation as a modern type coincided with the search for a nation’s cultural identity after centuries of colonial rule. This tended to be an introspective vision that prioritised rural space over urban space, agriculture over industry, and imagined the small farm as a central tenet in the construction of a new State. This paper suggests that the twentieth-century barn – as a product of the mechanisation of agriculture promoted by the new administrations – is an iconic structure, emblematic of attempts to reconcile the contradictory forces and imagery of modernity with the mores of a traditional society. Moreover, given a cultural purview that was often ambivalent or even hostile to the ideologies and forms of modernity, the barn in Ireland is, perhaps, not so much the inspiration but the realisation of an architectural modernism in that country at its most pervasive, enduring and unself-conscious.

Personalised and Precision Medicine in Cancer Clinical Trials: Panacea for Progress or Pandora's Box?

Cancer clinical trials have been one of the key foundations for significant advances in oncology. However, there is a clear recognition within the academic, care delivery and pharmaceutical/biotech communities that our current model of clinical trial discovery and development is no longer fit for purpose. Delivering transformative cancer care should increasingly be our mantra, rather than maintaining the status quo of, at best, the often miniscule incremental benefits that are observed with many current clinical trials. As we enter the era of precision medicine for personalised cancer care (precision and personalised medicine), it is important that we capture and utilise our greater understanding of the biology of disease to drive innovative approaches in clinical trial design and implementation that can lead to a step change in cancer care delivery. A number of advances have been practice changing (e.g. imatinib mesylate in chronic myeloid leukaemia, Herceptin in erb-B2-positive breast cancer), and increasingly we are seeing the promise of a number of newer approaches, particularly in diseases like lung cancer and melanoma. Targeting immune checkpoints has recently yielded some highly promising results. New algorithms that maximise the effectiveness of clinical trials, through for example a multi-stage, multi-arm type design are increasingly gaining traction. However, our enthusiasm for the undoubted advances that have been achieved are being tempered by a realisation that these new approaches may have significant cost implications. This article will address these competing issues, mainly from a European perspective, highlight the problems and challenges to healthcare systems and suggest potential solutions that will ensure that the cost/value rubicon is addressed in a way that allows stakeholders to work together to deliver optimal cost-effective cancer care, the benefits of which can be transferred directly to our patients.

A Constrained Optimization Approach to Dynamic State Estimation for Power Systems Including PMU and Missing Measurements.

In this brief, a hybrid filter algorithm is developed to deal with the state estimation (SE) problem for power systems by taking into account the impact from the phasor measurement units (PMUs). Our aim is to include PMU measurements when designing the dynamic state estimators for power systems with traditional measurements. Also, as data dropouts inevitably occur in the transmission channels of traditional measurements from the meters to the control center, the missing measurement phenomenon is also tackled in the state estimator design. In the framework of extended Kalman filter (EKF) algorithm, the PMU measurements are treated as inequality constraints on the states with the aid of the statistical criterion, and then the addressed SE problem becomes a constrained optimization one based on the probability-maximization method. The resulting constrained optimization problem is then solved using the particle swarm optimization algorithm together with the penalty function approach. The proposed algorithm is applied to estimate the states of the power systems with both traditional and PMU measurements in the presence of probabilistic data missing phenomenon. Extensive simulations are carried out on the IEEE 14-bus test system and it is shown that the proposed algorithm gives much improved estimation performances over the traditional EKF method.