Providing value to a business using a lightweight design system to support knowledge reuse by designers

This paper describes an alternative approach to knowledge based systems in engineering than traditional geometry or explicit knowledge focused systems. Past systems have supported product optimisation rather than creative solutions and provide little benefit to businesses for bespoke and low volume products or products which do not benefit from optimisation. The approach here addresses this by supporting the creativity of designers through codified tacit knowledge and encouraging knowledge reuse for bespoke product development, in particular for small to medium sized enterprises. The implementation and evaluation of the approach is described within a company producing bespoke fixtures and tooling in shorter than average lead times. The active support of knowledge management in the company is intended to add value to the business by further reducing the lead times of the designs and creating a positive impact to business processes. The evaluation demonstrates a viable alternative framework to the traditional management of knowledge in engineering, which could be implemented by other small to medium enterprises

Detection of osteoporosis from percussion responses using an electronic stethoscope and machine learning

Osteoporosis is an asymptomatic bone condition that affects a large proportion of the elderly population around the world, resulting in increased bone fragility and increased risk of fracture. Previous studies had shown that the vibroacoustic response of bone can indicate the quality of the bone condition. Therefore, the aim of the authors' project is to develop a new method to exploit this phenomenon to improve detection of osteoporosis in individuals. In this paper a method is described that uses a reflex hammer to exert testing stimuli on a patient's tibia and an electronic stethoscope to acquire the impulse responses. The signals are processed as mel frequency cepstrum coefficients and passed through an artificial neural network to determine the likelihood of osteoporosis from the tibia's impulse responses. Following some discussions of the mechanism and procedure, this paper details the signal acquisition using the stethoscope and the subsequent signal processing and the statistical machine learning algorithm. Pilot testing with 12 patients achieved over 80% sensitivity with a false positive rate below 30% and accuracies in the region of 70%. An extended dataset of 110 patients achieved an error rate of 30% with some room for improvement in the algorithm. By using common clinical apparatus and strategic machine learning, this method might be suitable as a large population screening test for the early diagnosis of osteoporosis, thus avoiding secondary complications

Scaling results up from a plot and paddock scale to a property - a case study from a long-term grazing experiment in northern Australia

Grazing experiments are usually used to quantify and demonstrate the biophysical impact of grazing strategies, with the Wambiana grazing experiment being one of the longest running such experiments in northern Australia. Previous economic analyses of this experiment suggest that there is a major advantage in stocking at a fixed, moderate stocking rate or in using decision rules allowing flexible stocking to match available feed supply. The present study developed and applied a modelling procedure to use data collected at the small plot, land type and paddock scales at the experimental site to simulate the property-level implications of a range of stocking rates for a breeding-finishing cattle enterprise. The greatest economic performance was achieved at a moderate stocking rate of 10.5 adult equivalents 100 ha(-1). For the same stocking rate over time, the fixed stocking strategy gave a greater economic performance than strategies that involved moderate changes to stocking rates each year in response to feed supply. Model outcomes were consistent with previous economic analyses using experimental data. Further modelling of the experimental data is warranted and similar analyses could be applied to other major grazing experiments to allow the scaling of results to greater scales

Machine learning and DSP algorithms for screening of possible osteoporosis using electronic stethoscopes

Osteoporosis is a prevalent but asymptomatic condition that affects a large population of the elderly, resulting in a high risk of fracture. Several methods have been developed and are available in general hospitals to indirectly assess the bone quality in terms of mineral material level and porosity. In this paper we describe a new method that uses a medical reflex hammer to exert testing stimuli, an electronic stethoscope to acquire impulse responses from tibia, and intelligent signal processing based on artificial neural network machine learning to determine the likelihood of osteoporosis. The proposed method makes decisions from the key components found in the time-frequency domain of impulse responses. Using two common pieces of clinical apparatus, this method might be suitable for the large population screening tests for the early diagnosis of osteoporosis, thus avoiding secondary complications. Following some discussions of the mechanism and procedure, this paper details the techniques of impulse response acquisition using a stethoscope and the subsequent signal processing and statistical machine learning algorithms for decision making. Pilot testing results achieved over 80% in detection sensitivity

Vitamin C Intravenous Treatment In the Setting of Atrial Fibrillation Ablation: Results From the Randomized, Double-Blinded, Placebo-Controlled CITRIS-AF Pilot Study

BackgroundCatheter ablation is an effective treatment for atrial fibrillation (AF), but high levels of post-procedure inflammation predict adverse clinical events. Ascorbic acid (AA) has shown promise in reducing inflammation but is untested in this population. We sought to test the feasibility, safety, and preliminary effects on inflammatory biomarkers in the CITRIS-AF (Vitamin C Intravenous Treatment In the Setting of Atrial Fibrillation Ablation) pilot study. Methods and ResultsPatients scheduled to undergo AF ablation (N=20) were randomized 1:1 to double-blinded treatment with AA (200 mg/kg divided over 24 hours) or placebo. C-reactive protein and interleukin-6 levels were obtained before the first infusion and repeated at 24 hours and 30 days. Pain levels within 24 hours and early recurrence of AF within 90 days were recorded. Median and interquartile range were aged 63 (56–70) years, 13 (65%) men, and 18 (90%) white. Baseline data were similar between the 2 groups except ejection fraction. Baseline C-reactive protein levels were 2.56 (1.47–5.87) mg/L and similar between groups (P=0.48). Change in C-reactive protein from baseline to 24 hours was +10.79 (+6.56–23.19) mg/L in the placebo group and +3.01 (+0.40–5.43) mg/L in the AA group (P=0.02). Conversely, change in interleukin-6 was numerically higher in the AA group, though not statistically significant (P=0.32). One patient in each arm developed pericarditis; no adverse events related to the infusions were seen. There were no significant differences between aggregated post-procedure pain levels within 24 hours or early recurrence of AF (both P\u3e0.05). ConclusionsHigh-dose AA is safe and well tolerated at the time of AF ablation and may be associated with a blunted rise in C-reactive protein, although consistent findings were not seen in interleukin-6 levels. Further studies are needed to validate these findings and explore the potential benefit in improving clinically relevant outcomes

Survival of Hendra Virus in the Environment: Modelling the Effect of Temperature

Hendra virus (HeV), a highly pathogenic zoonotic paramyxovirus recently emerged from bats, is a major concern to the horse industry in Australia. Previous research has shown that higher temperatures led to lower virus survival rates in the laboratory. We develop a model of survival of HeV in the environment as influenced by temperature. We used 20 years of daily temperature at six locations spanning the geographic range of reported HeV incidents to simulate the temporal and spatial impacts of temperature on HeV survival. At any location, simulated virus survival was greater in winter than in summer, and in any month of the year, survival was higher in higher latitudes. At any location, year-to-year variation in virus survival 24 h post-excretion was substantial and was as large as the difference between locations. Survival was higher in microhabitats with lower than ambient temperature, and when environmental exposure was shorter. The within-year pattern of virus survival mirrored the cumulative within-year occurrence of reported HeV cases, although there were no overall differences in survival in HeV case years and non-case years. The model examines the effect of temperature in isolation; actual virus survivability will reflect the effect of additional environmental factor

Survival of Hendra Virus in the Environment: Modelling the Effect of Temperature

Hendra virus (HeV), a highly pathogenic zoonotic paramyxovirus recently emerged from bats, is a major concern to the horse industry in Australia. Previous research has shown that higher temperatures led to lower virus survival rates in the laboratory. We develop a model of survival of HeV in the environment as influenced by temperature. We used 20 years of daily temperature at six locations spanning the geographic range of reported HeV incidents to simulate the temporal and spatial impacts of temperature on HeV survival. At any location, simulated virus survival was greater in winter than in summer, and in any month of the year, survival was higher in higher latitudes. At any location, year-to-year variation in virus survival 24 h post-excretion was substantial and was as large as the difference between locations. Survival was higher in microhabitats with lower than ambient temperature, and when environmental exposure was shorter. The within-year pattern of virus survival mirrored the cumulative within-year occurrence of reported HeV cases, although there were no overall differences in survival in HeV case years and non-case years. The model examines the effect of temperature in isolation; actual virus survivability will reflect the effect of additional environmental factor

Systematic management of stocking rates improves performance of northern Australian cattle properties in a variable climate

The risks for extensive cattle properties in the rangelands of northern Australia arising from high inter-annual rainfall variability are predominantly managed through adjustments in stocking rates (SR). This modeling study compared the performance of SR strategies that varied considerably in the extent that they adjusted SR annually at 3 locations in northern Australia. At all locations, land types and pasture condition states, the SR strategies that achieved the best pasture condition were those that least increased and most decreased SR annually in response to changes in forage avail-ability. At Donors Hill (Qld), these conservative strategies also achieved the highest cattle liveweight gains per hectare (LWG/ha). While conservative strategies produced the highest percent perennial pasture species at Fitzroy Crossing (WA), strategies which allowed larger increases and decreases in SR also performed well, enabling them to also achieve high LWG/ha with little deterioration of pasture condition. A similar trend occurred at Alice Springs (NT), although at this location the strategies with even larger annual increases and decreases in SR achieved relatively high percent peren-nials and the highest LWG/ha. While systematic management of SR appears to perform better than a constant SR strategy when rainfall variability is high, it is unclear if the magnitude of annual adjustments in SR needs to increase with increasing rainfall variability. © 2013