A zero-stiffness elastic shell structure

A remarkable shell structure is described that, due to a particular combination of geometry and initial stress, has zero stiffness for any finite deformation along a twisting path; the shell is in a neutrally stable state of equilibrium. Initially the shell is straight in a longitudinal direction, but has a constant, nonzero curvature in the transverse direction. If residual stresses are induced in the shell by, for example, plastic deformation, to leave a particular resultant bending moment, then an analytical inextensional model of the shell shows it to have no change in energy along a path of twisted configurations. Real shells become closer to the inextensional idealization as their thickness is decreased; experimental thin-shell models have confirmed the neutrally stable configurations predicted by the inextensional theory. A simple model is described that shows that the resultant bending moment that leads to zero stiffness gives the shell a hidden symmetry, which explains this remarkable property.

Some measurements of the permeability of kaolin

The writers wish to present some additional data obtained independently and with different techniques that confirm the results published in the paper. For these tests, the speswhite kaolin clay was prepared as a slurry with a water content of 133 percent and was then consolidated one-dimensionally under an axial stress of 100 kPa in a 203 mm dia. tube. The results presented here show that the anisotropy of permeability is completely preserved (even after the sample is compressed isotropical) as long as the initial part of the stress path corresponds to one-dimensional compression. The data supports the speculation by the authors regarding permeability anisotropy for stress paths other than one-dimensional compression.

3D multi-car tracking based on monocular video

We propose a system that can reliably track multiple cars in congested traffic environments. Our system's key basis is the implementation of a sequential Monte Carlo algorithm, which introduces robustness against problems arising due to the proximity between vehicles. By directly modelling occlusions and collisions between cars we obtain promising results on an urban traffic dataset. Extensions to this initial framework are also suggested. © 2010 IEEE.

The performance of closed reactor grade plutonium-thorium fuel cycles in reduced-moderation pressurised water reactors

The production of long-lived transuranic (TRU) waste is a major disadvantage of fission-based nuclear power. Previous work has indicated that TRU waste can be virtually eliminated in a pressurised water reactor (PWR) fuelled with a mixture of thorium and TRU waste, when all actinides are returned to the reactor after reprocessing. However, the optimal configuration for a fuel assembly operating this fuel cycle is likely to differ from the current configuration. In this paper, the differences in performance obtained in a reduced-moderation PWR operating this fuel cycle were investigated using WIMS. The chosen configuration allowed an increase of at least 20% in attainable burn-up for a given TRU enrichment. This will be especially important if the practical limit on TRU enrichment is low. The moderator reactivity coefficients limit the enrichment possible in the reactor, and this limit is particularly severe if a negative void coefficient is required for a fully voided core. Several strategies have been identified to mitigate this. Specifically, the control system should be designed to avoid a detrimental effect on moderator reactivity coefficients. The economic viability of this concept is likely to be dependent on the achievable thermal-hydraulic operating conditions. © 2012 Elsevier Ltd. All rights reserved.

Making a shallow network deep: Conversion of a boosting classifier into a decision tree by boolean optimisation

This paper presents a novel way to speed up the evaluation time of a boosting classifier. We make a shallow (flat) network deep (hierarchical) by growing a tree from decision regions of a given boosting classifier. The tree provides many short paths for speeding up while preserving the reasonably smooth decision regions of the boosting classifier for good generalisation. For converting a boosting classifier into a decision tree, we formulate a Boolean optimization problem, which has been previously studied for circuit design but limited to a small number of binary variables. In this work, a novel optimisation method is proposed for, firstly, several tens of variables i.e. weak-learners of a boosting classifier, and then any larger number of weak-learners by using a two-stage cascade. Experiments on the synthetic and face image data sets show that the obtained tree achieves a significant speed up both over a standard boosting classifier and the Fast-exit-a previously described method for speeding-up boosting classification, at the same accuracy. The proposed method as a general meta-algorithm is also useful for a boosting cascade, where it speeds up individual stage classifiers by different gains. The proposed method is further demonstrated for fast-moving object tracking and segmentation problems. © 2011 Springer Science+Business Media, LLC.