Modelling resilience in a water supply system : contrasting conditions of drought and flood

This paper presents an approach to modelling the resilience of a generic (potable) water supply system. The system is contextualized as a meta-system consisting of three subsystems to represent the natural catchment, the water treatment plant and the water distribution infrastructure for urban use. An abstract mathematical model of the meta-system is disaggregated progressively to form a cascade of equations forming a relational matrix of models. This allows the investigation of commonly implicit relationships between various operational components within the meta system, the in-depth understanding of specific system components and influential factors and the incorporation of explicit disturbances to explore system behaviour. Consequently, this will facilitate long-term decision making to achieve sustainable solutions for issues such as, meeting a growing demand or managing supply-side influences in the meta-system under diverse water availability regimes. This approach is based on the hypothesis that the means to achieve resilient supply of water may be better managed by modelling the effects of changes at specific levels that have a direct or in some cases indirect impact on higher-order outcomes. Additionally, the proposed strategy allows the definition of approaches to combine disparate data sets to synthesise previously missing or incomplete higher-order information, a scientifically robust means to define and carry out meta-analyses using knowledge from diverse yet relatable disciplines relevant to different levels of the system and for enhancing the understanding of dependencies and inter-dependencies of variable factors at various levels across the meta-system. The proposed concept introduces an approach for modelling a complex infrastructure system as a meta system which consists of a combination of bio-ecological, technical and socio-technical subsystems.

The flying doctors

This book is a reader for primary school students, stage 24-26 (fluent), incorporating mathematics themes. There is a fictional narrative, entitled "A Flying Visit", that describes Tess' and Alex's encounter with the Flying Doctor. A non-fiction recount, entitled "Fundraising for the Flying Doctors", describes the activities of a class group in raising money for the Flying Doctors. Accompanying the book is a "building comprehension card" to assist teachers in their classroom use of the reader.

Intended and actual avoidance of road use situations by older drivers and pedestrians, by gender and age

• The Queensland context • Rationale and aims • Method • Demographics and basic data • Avoidance of driving and walking situations • Success of intended avoidance • Further analyses (preliminary results) • Implications

Adaptive radiotherapy for virally mediated head and neck cancer

Purpose: Virally mediated head and neck cancers (VMHNC) often present with nodal involvement, and are generally considered radioresponsive, resulting in the need for a re-planning CT during radiotherapy (RT) in a subset of patients. We sought to identify a high-risk group based on nodal size to be evaluated in a future prospective adaptive RT trial. Methodology: Between 2005-2010, 121 patients with virally-mediated, node positive nasopharyngeal (EBV positive) or oropharyngeal (HPV positive) cancers, receiving curative intent RT were reviewed. Patients were analysed based on maximum size of the dominant node with a view to grouping them in varying risk categories for the need of re-planning. The frequency and timing of the re-planning scans were also evaluated. Results: Sixteen nasopharyngeal and 105 oropharyngeal tumours were reviewed. Twenty-five (21%) patients underwent a re-planning CT at a median of 22 (range, 0-29) fractions with 1 patient requiring re-planning prior to the commencement of treatment. Based on the analysis, patients were subsequently placed into 3 groups; ≤35mm (Group 1), 36-45mm (Group 2), ≥46mm (Group 3). Re-planning CT’s were performed in Group 1- 8/68 (11.8%), Group 2- 4/28 (14.3%), Group 3- 13/25 (52%). Sample size did not allow statistical analysis to detect a significant difference or exclusion of a lack of difference between the 3 groups. Conclusion: In this series, patients with VMHNC and nodal size > 46mm appear to be a high-risk group for the need of re-planning during a course of definitive radiotherapy. This finding will now be tested in a prospective adaptive RT study.

Future Information Communication Technology and Applications : ICFICE 2013

Focuses on the various aspects of advances in future information communication technology and its applications Presents the latest issues and progress in the area of future information communication technology Applicable to both researchers and professionals These proceedings are based on the 2013 International Conference on Future Information & Communication Engineering (ICFICE 2013), which will be held at Shenyang in China from June 24-26, 2013. The conference is open to all over the world, and participation from Asia-Pacific region is particularly encouraged. The focus of this conference is on all technical aspects of electronics, information, and communications ICFICE-13 will provide an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of FICE. In addition, the conference will publish high quality papers which are closely related to the various theories and practical applications in FICE. Furthermore, we expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject. "This work was supported by the NIPA (National IT Industry Promotion Agency) of Korea Grant funded by the Korean Government (Ministry of Science, ICT & Future Planning)."

Sex-based comparisons of myofibrillar protein synthesis after resistance exercise in the fed state

Sex-based comparisons of myofibrillar protein synthesis after resistance exercise in the fed state. J Appl Physiol 112: 1805-1813, 2012. First published March 1, 2012; doi:10.1152/japplphysiol.00170.2012.- We made sex-based comparisons of rates of myofibrillar protein synthesis (MPS) and anabolic signaling after a single bout of high-intensity resistance exercise. Eight men (20 ± 10 yr, BMI = 24.3 ± 2.4) and eight women (22 ± 1.8 yr, BMI = 23.0 ± 1.9) underwent primed constant infusions of L-[ring-13C6]phenylalanine on consecutive days with serial muscle biopsies. Biopsies were taken from the vastus lateralis at rest and 1, 3, 5, 24, 26, and 28 h after exercise. Twenty-five grams of whey protein was ingested immediately and 26 h after exercise. We also measured exercise-induced serum testosterone because it is purported to contribute to increases in myofibrillar protein synthesis (MPS) postexercise and its absence has been hypothesized to attenuate adaptative responses to resistance exercise in women. The exercise-induced area under the testosterone curve was 45-fold greater in men than women in the early (1 h) recovery period following exercise (P < 0.001). MPS was elevated similarly in men and women (2.3- and 2.7-fold, respectively) 1-5 h postexercise and after protein ingestion following 24 h recovery. Phosphorylation of mTORSer2448 was elevated to a greater extent in men than women acutely after exercise (P = 0.003), whereas increased phosphorylation of p70S6K1Thr389 was not different between sexes. Androgen receptor content was greater in men (main effect for sex, P = 0.049). Atrogin-1 mRNA abundance was decreased after 5 h recovery in both men and women (P < 0.001), and MuRF-1 expression was elevated in men after protein ingestion following 24 h recovery (P = 0.003). These results demonstrate minor sex-based differences in signaling responses and no difference in the MPS response to resistance exercise in the fed state. Interestingly, our data demonstrate that exerciseinduced increases in MPS are dissociated from postexercise testosteronemia and that stimulation of MPS occurs effectively with low systemic testosterone concentrations in women.

Rethinking emergency management and climate adaptation policies

Emergency management and climate change adaptation will increasingly challenge all levels of government because of three main factors. First, Australia is extremely vulnerable to the impacts of climate change, particularly through the increasing frequency and/or intensity of disasters such as floods and bushfires. Second, the system of government that divides powers by function and level can often act as a barrier to a well-integrated response. Third, policymaking processes struggle to cope with such complex inter-jurisdictional issues. This paper discusses these factors and explores the nature of the challenge for Australian governments. Investigations into the 2009 Victorian bushfires, the 2011 Perth Hills bushfires, and the 2011 Brisbane floods offer an indication of the challenges ahead and it is argued that there is a need to: improve community engagement and communication; refocus attention on resilience; improve interagency communication and collaboration; and, develop institutional arrangements that support continual improvement and policy learning. These findings offer an opportunity for improving responses as well as a starting point for integrating disaster risk management and climate change adaptation policies. The paper is based on the preliminary findings of an NCCARF funded research project: The Right Tool for the Job – Achieving climate change adaptation outcomes through improved disaster management policies, planning and risk management strategies involving Griffith University and RMIT.

Local inter-session variability modelling for object classification

Object classification is plagued by the issue of session variation. Session variation describes any variation that makes one instance of an object look different to another, for instance due to pose or illumination variation. Recent work in the challenging task of face verification has shown that session variability modelling provides a mechanism to overcome some of these limitations. However, for computer vision purposes, it has only been applied in the limited setting of face verification. In this paper we propose a local region based intersession variability (ISV) modelling approach, and apply it to challenging real-world data. We propose a region based session variability modelling approach so that local session variations can be modelled, termed Local ISV. We then demonstrate the efficacy of this technique on a challenging real-world fish image database which includes images taken underwater, providing significant real-world session variations. This Local ISV approach provides a relative performance improvement of, on average, 23% on the challenging MOBIO, Multi-PIE and SCface face databases. It also provides a relative performance improvement of 35% on our challenging fish image dataset.

Object tracking via non-Euclidean geometry : a Grassmann approach

A robust visual tracking system requires an object appearance model that is able to handle occlusion, pose, and illumination variations in the video stream. This can be difficult to accomplish when the model is trained using only a single image. In this paper, we first propose a tracking approach based on affine subspaces (constructed from several images) which are able to accommodate the abovementioned variations. We use affine subspaces not only to represent the object, but also the candidate areas that the object may occupy. We furthermore propose a novel approach to measure affine subspace-to-subspace distance via the use of non-Euclidean geometry of Grassmann manifolds. The tracking problem is then considered as an inference task in a Markov Chain Monte Carlo framework via particle filtering. Quantitative evaluation on challenging video sequences indicates that the proposed approach obtains considerably better performance than several recent state-of-the-art methods such as Tracking-Learning-Detection and MILtrack.

Random projections on manifolds of symmetric positive definite matrices for image classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

Summarisation of short-term and long-term videos using texture and colour

We present a novel approach to video summarisation that makes use of a Bag-of-visual-Textures (BoT) approach. Two systems are proposed, one based solely on the BoT approach and another which exploits both colour information and BoT features. On 50 short-term videos from the Open Video Project we show that our BoT and fusion systems both achieve state-of-the-art performance, obtaining an average F-measure of 0.83 and 0.86 respectively, a relative improvement of 9% and 13% when compared to the previous state-of-the-art. When applied to a new underwater surveillance dataset containing 33 long-term videos, the proposed system reduces the amount of footage by a factor of 27, with only minor degradation in the information content. This order of magnitude reduction in video data represents significant savings in terms of time and potential labour cost when manually reviewing such footage.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.