Analysing the Impact of Learning Inputs - Application to Terrain Traversability Estimation

Data-driven approaches such as Gaussian Process (GP) regression have been used extensively in recent robotics literature to achieve estimation by learning from experience. To ensure satisfactory performance, in most cases, multiple learning inputs are required. Intuitively, adding new inputs can often contribute to better estimation accuracy, however, it may come at the cost of a new sensor, larger training dataset and/or more complex learning, some- times for limited benefits. Therefore, it is crucial to have a systematic procedure to determine the actual impact each input has on the estimation performance. To address this issue, in this paper we propose to analyse the impact of each input on the estimate using a variance-based sensitivity analysis method. We propose an approach built on Analysis of Variance (ANOVA) decomposition, which can characterise how the prediction changes as one or more of the input changes, and also quantify the prediction uncertainty as attributed from each of the inputs in the framework of dependent inputs. We apply the proposed approach to a terrain-traversability estimation method we proposed in prior work, which is based on multi-task GP regression, and we validate this implementation experimentally using a rover on a Mars-analogue terrain.

Prediction of masonry compressive behaviour using a damage mechanics inspired modelling method

Masonry under compression is affected by the properties of its constituents and their interfaces. In spite of extensive investigations of the behaviour of masonry under compression, the information in the literature cannot be regarded as comprehensive due to ongoing inventions of new generation products – for example, polymer modified thin layer mortared masonry and drystack masonry. As comprehensive experimental studies are very expensive, an analytical model inspired by damage mechanics is developed and applied to the prediction of the compressive behaviour of masonry in this paper. The model incorporates a parabolic progressively softening stress-strain curve for the units and a progressively stiffening stress-strain curve until a threshold strain for the combined mortar and the unit-mortar interfaces is reached. The model simulates the mutual constraints imposed by each of these constituents through their respective tensile and compressive behaviour and volumetric changes. The advantage of the model is that it requires only the properties of the constituents and considers masonry as a continuum and computes the average properties of the composite masonry prisms/wallettes; it does not require discretisation of prism or wallette similar to the finite element methods. The capability of the model in capturing the phenomenological behaviour of masonry with appropriate elastic response, stiffness degradation and post peak softening is presented through numerical examples. The fitting of the experimental data to the model parameters is demonstrated through calibration of some selected test data on units and mortar from the literature; the calibrated model is shown to predict the responses of the experimentally determined masonry built using the corresponding units and mortar quite well. Through a series of sensitivity studies, the model is also shown to predict the masonry strength appropriately for changes to the properties of the units and mortar, the mortar joint thickness and the ratio of the height of unit to mortar joint thickness. The unit strength is shown to affect the masonry strength significantly. Although the mortar strength has only a marginal effect, reduction in mortar joint thickness is shown to have a profound effect on the masonry strength. The results obtained from the model are compared with the various provisions in the Australian Masonry Structures Standard AS3700 (2011) and Eurocode 6.

Sustainable building envelope design by considering energy cost and occupant satisfaction

The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

Cost-effectiveness of a national initiative to improve hand hygiene compliance using the outcome of healthcare associated staphylococcus aureus bacteraemia

Background The objective is to estimate the incremental cost-effectiveness of the Australian National Hand Hygiene Inititiave implemented between 2009 and 2012 using healthcare associated Staphylococcus aureus bacteraemia as the outcome. Baseline comparators are the eight existing state and territory hand hygiene programmes. The setting is the Australian public healthcare system and 1,294,656 admissions from the 50 largest Australian hospitals are included. Methods The design is a cost-effectiveness modelling study using a before and after quasi-experimental design. The primary outcome is cost per life year saved from reduced cases of healthcare associated Staphylococcus aureus bacteraemia, with cost estimated by the annual on-going maintenance costs less the costs saved from fewer infections. Data were harvested from existing sources or were collected prospectively and the time horizon for the model was 12 months, 2011–2012. Findings No useable pre-implementation Staphylococcus aureus bacteraemia data were made available from the 11 study hospitals in Victoria or the single hospital in Northern Territory leaving 38 hospitals among six states and territories available for cost-effectiveness analyses. Total annual costs increased by $2,851,475 for a return of 96 years of life giving an incremental cost-effectiveness ratio (ICER) of $29,700 per life year gained. Probabilistic sensitivity analysis revealed a 100% chance the initiative was cost effective in the Australian Capital Territory and Queensland, with ICERs of $1,030 and $8,988 respectively. There was an 81% chance it was cost effective in New South Wales with an ICER of $33,353, a 26% chance for South Australia with an ICER of $64,729 and a 1% chance for Tasmania and Western Australia. The 12 hospitals in Victoria and the Northern Territory incur annual on-going maintenance costs of $1.51M; no information was available to describe cost savings or health benefits. Conclusions The Australian National Hand Hygiene Initiative was cost-effective against an Australian threshold of $42,000 per life year gained. The return on investment varied among the states and territories of Australia.

Measuring cost and affordability of healthy and less healthy diet globally

The INFORMAS food prices module proposes a step-wise framework to measure the cost and affordability of population diets. The price differential and the tax component of healthy and less healthy foods, food groups, meals and diets will be benchmarked and monitored over time. Results can be used to model or assess the impact of fiscal policies, such as ‘fat taxes’ or subsidies. Key methodological challenges include: defining healthy and less healthy foods, meals, diets and commonly consumed items; including costs of alcohol, takeaways, convenience foods and time; selecting the price metric; sampling frameworks; and standardizing collection and analysis protocols. The minimal approach uses three complementary methods to measure the price differential between pairs of healthy and less healthy foods. Specific challenges include choosing policy relevant pairs and defining an anchor for the lists. The expanded approach measures the cost of a healthy diet compared to the current (less healthy) diet for a reference household. It requires dietary principles to guide the development of the healthy diet pricing instrument and sufficient information about the population’s current intake to inform the current (less healthy) diet tool. The optimal approach includes measures of affordability and requires a standardised measure of household income that can be used for different countries. The feasibility of implementing the protocol in different countries is being tested in New Zealand, Australia and Fiji. The impact of different decision points to address challenges will be investigated in a systematic manner. We will present early insights and results from this work.

Developing standardized methods to assess cost of healthy and unhealthy (current) diets in Australia

Unhealthy diets contribute at least 14% to Australia's disease burden and are driven by ‘obesogenic’ food environments. Compliance with dietary recommendations is particularly poor amongst disadvantaged populations including low socioeconomic groups, those living in rural/remote areas and Aboriginal and Torres Strait Islanders. The perception that healthy foods are expensive is a key barrier to healthy choices and a major determinant of diet-related health inequities. Available state/regional/local data (limited and non-comparable) suggests that, despite basic healthy foods not incurring GST, the cost of healthy food is higher and has increased more rapidly than unhealthy food over the last 15 years in Australia. However, there were no nationally standardised tools or protocols to benchmark, compare or monitor food prices and affordability in Australia. Globally, we are leading work to develop and test approaches to assess the price differential of healthy and less-healthy (current) diets under the food price module of the International Network for Food and Obesity/non-communicable diseases (NCDs) Research, Monitoring and Action Support (INFORMAS). This presentation describes contextualization of the INFORMAS approach to develop standardised Australian tools, survey protocols and data collection and analysis systems. The ‘healthy diet basket’ was based on the Australian Foundation Diet, 1 The ‘current diet basket’ and specific items included in each basket, were based on recent national dietary survey data.2 Data collection methods were piloted. The final tools and protocols were then applied to measure the price and affordability of healthy and less healthy (current) diets of different household groups in diverse communities across the nation. We have compared results for different geographical locations/population subgroups in Australia and assessed these against international INFORMAS benchmarks. The results inform the development of policy and practice, including those relevant to mooted changes to the GST base, to promote nutrition and healthy weight and prevent chronic disease in Australia.

Cost-effectiveness of a nonpharmacological intervention in pediatric burn care

OBJECTIVE To report the cost-effectiveness of a tailored handheld computerized procedural preparation and distraction intervention (Ditto) used during pediatric burn wound care in comparison to standard practice. METHODS An economic evaluation was performed alongside a randomized controlled trial of 75 children aged 4 to 13 years who presented with a burn to the Royal Children's Hospital, Brisbane, Australia. Participants were randomized to either the Ditto intervention (n = 35) or standard practice (n = 40) to measure the effect of the intervention on days taken for burns to re-epithelialize. Direct medical, direct nonmedical, and indirect cost data during burn re-epithelialization were extracted from the randomized controlled trial data and combined with scar management cost data obtained retrospectively from medical charts. Nonparametric bootstrapping was used to estimate statistical uncertainty in cost and effect differences and cost-effectiveness ratios. RESULTS On average, the Ditto intervention reduced the time to re-epithelialize by 3 days at AU$194 less cost for each patient compared with standard practice. The incremental cost-effectiveness plane showed that 78% of the simulated results were within the more effective and less costly quadrant and 22% were in the more effective and more costly quadrant, suggesting a 78% probability that the Ditto intervention dominates standard practice (i.e., cost-saving). At a willingness-to-pay threshold of AU$120, there is a 95% probability that the Ditto intervention is cost-effective (or cost-saving) against standard care. CONCLUSIONS This economic evaluation showed the Ditto intervention to be highly cost-effective against standard practice at a minimal cost for the significant benefits gained, supporting the implementation of the Ditto intervention during burn wound care.

Computational methods for the prediction of the structure and interactions of coiled-coil peptides

The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.

Prediction of heparin binding sites in bone morphogenetic proteins (BMPs)

Heparin is a glycosaminoglycan known to bind bone morphogenetic proteins (BMPs) and the growth and differentiation factors (GDFs) and has strong and variable effects on BMP osteogenic activity. In this paper we report our predictions of the likely heparin binding sites for BMP-2 and 14. The N-terminal sequences upstream of TGF-β-type cysteine-knot domains in BMP-2, 7 and 14 contain the basic residues arginine and lysine, which are key components of the heparin/HS-binding sites, with these residues being highly non-conserved. Importantly, evolutionary conserved surfaces on the beta sheets are required for interactions with receptors and antagonists. Furthermore, BMP-2 has electropositive surfaces on two sides compared to BMP-7 and BMP-14. Molecular docking simulations suggest the presence of high and low affinity binding sites in dimeric BMP-2. Histidines were found to play a role in the interactions of BMP-2 with heparin; however, a pKa analysis suggests that histidines are likely not protonated. This is indicative that interactions of BMP-2 with heparin do not require acidic pH. Taken together, non-conserved amino acid residues in the N-terminus and residues protruding from the beta sheet (not overlapping with the receptor binding sites and the dimeric interface) and not C-terminal are found to be important for heparin–BMP interactions.

Time-driven life cycle cost estimation system for product family design

This research develops a design support system, which is able to estimate the life cycle cost of different product families at the early stage of product development. By implementing the system, a designer is able to develop various cost effective product families in a shorter lead-time and minimise the destructive impact of the product family on the environment.

Counting the cost: Estimating the number of deaths among recently released prisoners in Australia

TO THE EDITOR: Kinner and colleagues described the high proportion of deaths among recently released prisoners in Australia...

Managing uncertainty to improve the cost performance of complex infrastructure projects

There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.

Cost-efficient virtual machine management in data centers

Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

Women’s Wellness after Cancer Program Study (WWACP)– A multi centre randomised controlled trial examining the benefits and cost effectiveness of an Evidenced Based, e-health intervention

Background Advances in cancer diagnosis and treatment have significantly improved survival rates, through their subsequent health needs are often not adequately addressed by current health services. National Health and Medical Research Council (NHMRC) Partnerships Project awarded a national collaborative project to develop, trial and evaluate clinical benefits and cost effectiveness of an e-health enabled structured health promotion intervention - The Women’s Wellness after Cancer Program (WWACP). The aim of this e-health enabled multimodal intervention is to improve health related quality of life in women previously treated for target cancers. Aim The WWACP is a 12-week web based, interactive, holistic program. Primary outcomes for this project are to promote a positive change in health-related quality of life (HRQoL) and reduction in Body Mass Index (BMI) in the women undertaking WWACP compared to women who receive usual care. Secondary outcomes include managing other side effects of cancer treatment through evidence-based nutrition and exercise practices, dealing with stress, sleep, menopause and sexuality issues. Methods The single-blinded multi-center randomized controlled trial recruited a toatl of 330 women within 24 months of completion of chemotherapy and /or radiotherapy. Women were randomly assigned to either a usual care or intervention group. Women provided with the intervention were provided with an interactive iBook and journal, web interface, and three virtual consultations by experienced cancer nurses. A variety of methods were utilized, to enable positive self- efficacy and lifestyle changes. These include online coaching with a registered nurse trained in the intervention, plus written educational and health promotional information. The program has been delivered through the e-health enabled interfaces, which enables virtual delivery via desktop and mobile computing devices. Importantly this enables accessibility for rural and regional women in Australia who are frequently geographically disadvantaged in terms of health care provision. Results Research focusing on alternative methods of delivering post treatment / or survivorship care in cancer utilizing web based interfaces is limited, but emerging evidence suggests that Internet interventions can increase psychological and physical wellbeing in cancer patients. The WWACP trial aims to establish the effectiveness of delivery of the program in terms of positive patient outcomes and cost effective, flexibility. The trial will be completed in September and results will be presented at the conference. Conclusions Women after acute hematological, breast and gynecological cancer treatments demonstrate good cancer survival rates and face residual health problems which are amenable to behavioral interventions. The conclusion of active treatment is a key 'teachable moment' in which sustainable positive lifestyle change can be achieved if patients receive education and psychological support which targets key treatment related health problems and known chronic disease risk factors.