Resilience of Hierarchical Critical Infrastructure Networks

Concern over the resilience of critical infrastructure networks has increased dramatically over the last decade due to a number of well documented failures and the significant disruption associated with these. This has led to a large body of research that has adopted graph-theoretic based analysis in order to try and improve our understanding of infrastructure network resilience. Many studies have asserted that infrastructure networks possess a scale-free topology which is robust to random failures but sensitive to targeted attacks at highly connected hubs. However, many studies have ignored that many networks in addition to their topological connectivity may be organised either logically or spatially in a hierarchical system which may significantly change their response to perturbations. In this paper we explore if hierarchical network models exhibit significantly different higher-order topological characteristics compared to other network structures and how this impacts on their resilience to a number of different failure types. This is achieved by investigating a suite of synthetic networks as well as a suite of ‘real world’ spatial infrastructure networks

An investigation into the relationship between preceding break crops and weed populations in barley crops in organic ley/arable rotations

This report was presented at the UK Organic Research 2002 Conference. The relationship between weed populations and cereal crops following nine organic break crops was investigated in field trials in Warwickshire, Aberdeenshire and Ceredigion in 2001. Weed biodiversity was high on all sites and varied between sites in terms of species present. Severity of weed infestation differed significantly between sites and between cereals following different break crops. The impact of break crop species on the incidence and severity of the weed burden in the following cereal is discussed in relation to the field trials at the three sites

Mammographic image restoration using maximum entropy deconvolution

An image restoration approach based on a Bayesian maximum entropy method (MEM) has been applied to a radiological image deconvolution problem, that of reduction of geometric blurring in magnification mammography. The aim of the work is to demonstrate an improvement in image spatial resolution in realistic noisy radiological images with no associated penalty in terms of reduction in the signal-to-noise ratio perceived by the observer. Images of the TORMAM mammographic image quality phantom were recorded using the standard magnification settings of 1.8 magnification/fine focus and also at 1.8 magnification/broad focus and 3.0 magnification/fine focus; the latter two arrangements would normally give rise to unacceptable geometric blurring. Measured point-spread functions were used in conjunction with the MEM image processing to de-blur these images. The results are presented as comparative images of phantom test features and as observer scores for the raw and processed images. Visualization of high resolution features and the total image scores for the test phantom were improved by the application of the MEM processing. It is argued that this successful demonstration of image de-blurring in noisy radiological images offers the possibility of weakening the link between focal spot size and geometric blurring in radiology, thus opening up new approaches to system optimization.Comment: 18 pages, 10 figure

Activity Recognition based on a Magnitude-Orientation Stream Network

The temporal component of videos provides an important clue for activity recognition, as a number of activities can be reliably recognized based on the motion information. In view of that, this work proposes a novel temporal stream for two-stream convolutional networks based on images computed from the optical flow magnitude and orientation, named Magnitude-Orientation Stream (MOS), to learn the motion in a better and richer manner. Our method applies simple nonlinear transformations on the vertical and horizontal components of the optical flow to generate input images for the temporal stream. Experimental results, carried on two well-known datasets (HMDB51 and UCF101), demonstrate that using our proposed temporal stream as input to existing neural network architectures can improve their performance for activity recognition. Results demonstrate that our temporal stream provides complementary information able to improve the classical two-stream methods, indicating the suitability of our approach to be used as a temporal video representation.Comment: 8 pages, SIBGRAPI 201

Response to comment on "solid recovered fuel: Materials flow analysis and fuel property development during the mechanical processing of biodried waste"

Laner and Cencic1 comment on Velis et al. (2013)2 clarifying certain points on the use of the material flow analysis (MFA) software STAN3. We welcome the correspondence and the opportunity this exchange provides to discuss optimal approaches to using STAN. In keeping with Velis et al.2 these physically impossible, and otherwise insignificant, negative flows have enabled improvements to STAN. Here, we elaborate on the practicalities of using STAN in our research and on the correctness and validation of our results, notwithstanding the inclusion of negative flows. We explain the contribution of our approach to solid waste management and resource recovery

A historic jet-emission minimum reveals hidden spectral features in 3C 273

Aims. The aim of this work is to identify and study spectral features in the quasar 3C 273 usually blended by its strong jet emission. Method. A historic minimum in the sub-millimetre emission of 3C 273 triggered coordinated multi-wavelength observations in June 2004. X-ray observations from the INTEGRAL, XMM-Newton and RXTE satellites are complemented by ground-based optical, infrared, millimetre and radio observations. The overall spectrum is used to model the infrared and X-ray spectral components. Results. Three thermal dust emission components are identified in the infrared. The dust emission on scales from 1 pc to several kpc is comparable to that of other quasars, as expected by AGN unification schemes. The observed weakness of the X-ray emission supports the hypothesis of a synchrotron self-Compton origin for the jet component. There is a clear soft-excess and we find evidence for a very broad iron line which could be emitted in a disk around a Kerr black hole. Other signatures of a Seyfert-like X-ray component are not detected.Comment: 4 pages. Accepted for publication in A&A Letter

The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development

With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions. However, few studies have looked into the practitioners view of DDDM, in particular for agile organizations. In this paper we investigated the experiences of using DDDM, and how data can improve decision making. An emailed questionnaire was sent out to 124 industry practitioners in agile software developing companies, of which 84 answered. The results show that few practitioners indicated a widespread use of DDDM in their current decision making practices. The practitioners were more positive to its future use for higher-level and more general decision making, fairly positive to its use for requirements elicitation and prioritization decisions, while being less positive to its future use at the team level. The practitioners do see a lot of potential for DDDM in an agile context; however, currently unfulfilled