Inexact-aware architecture design for ultra-low power bio-signal analysis

This study introduces an inexact, but ultra-low power, computing architecture devoted to the embedded analysis of bio-signals. The platform operates at extremely low voltage supply levels to minimise energy consumption. In this scenario, the reliability of static RAM (SRAM) memories cannot be guaranteed when using conventional 6-transistor implementations. While error correction codes and dedicated SRAM implementations can ensure correct operations in this near-threshold regime, they incur in significant area and energy overheads, and should therefore be employed judiciously. Herein, the authors propose a novel scheme to design inexact computing architectures that selectively protects memory regions based on their significance, i.e. their impact on the end-to-end quality of service, as dictated by the bio-signal application characteristics. The authors illustrate their scheme on an industrial benchmark application performing the power spectrum analysis of electrocardiograms. Experimental evidence showcases that a significance-based memory protection approach leads to a small degradation in the output quality with respect to an exact implementation, while resulting in substantial energy gains, both in the memory and the processing subsystem.

On the statistics of transverse permeability of randomly distributed fibers

An RVE–based stochastic numerical model is used to calculate the permeability of randomly generated porous media at different values of the fiber volume fraction for the case of transverse flow in a unidirectional ply. Analysis of the numerical results shows that the permeability is not normally distributed. With the aim of proposing a new understanding on this particular topic, permeability data are fitted using both a mixture model and a unimodal distribution. Our findings suggest that permeability can be fitted well using a mixture model based on the lognormal and power law distributions. In case of a unimodal distribution, it is found, using the maximum-likelihood estimation method (MLE), that the generalized extreme value (GEV) distribution represents the best fit. Finally, an expression of the permeability as a function of the fiber volume fraction based on the GEV distribution is discussed in light of the previous results.

Becoming private property: custom, law, and the geographies of ‘ownership’ in 18th- and 19th-century England

The making private of hitherto public goods is a central tenet of neoliberalism. From land in Africa, Asia, and South America to the assertion of property rights over genes and cells by corporations, the process(es) of making private property matters more than ever. And yet, despite this importance, we know remarkably little about the spatial plays through which things become private property. In this paper I seek to address this imbalance by focusing upon the formative context of 18th- and early-19th-century England. The specific lens is wood, that most critical of all ‘natural’ things other than land in the transition to market-driven economies. It is shown that the interplay between custom, law, and local practices rendered stable and aspatial definitions of property impossible. Whilst law was the key technology through which property was mediated, the cadence of particular places gave these mediations distinctive forms. I conclude that not only must we take property seriously, but we must also take the conditions and contexts of its making seriously too.

Ballistic Focusing of Polyenergetic Protons Driven by Petawatt Laser Pulses

By using a thick (250 mu m) target with 350 mu m radius of curvature, the intense proton beam driven by a petawatt laser is focused at a distance of similar to 1 mm from the target for all detectable energies up to similar to 25 MeV. The thickness of the foil facilitates beam focusing as it suppresses the dynamic evolution of the beam divergence caused by peaked electron flux distribution at the target rear side. In addition, reduction in inherent beam divergence due to the target thickness relaxes the curvature requirement for short-range focusing. Energy resolved mapping of the proton beam trajectories from mesh radiographs infers the focusing and the data agree with a simple geometrical modeling based on ballistic beam propagation. © 2011 American Physical Society