517 resultados para WII FIT
Development of multi-rotor localised surveillance using multi-spectral sensors for plant biosecurity
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This report describes a proof of concept for multi-rotor localised surveillance using a multi-spectral sensor for plant biosecurity applications. A literature review was conducted on previous applications using airborne multispectral imaging for plant biosecurity purposes. A ready built platform was purchased and modified in order to fit and provide suitable clearance for a Tetracam Mini-MCA multispectral camera. The appropriate risk management documents were developed allowing the platform and the multi-spectral camera to be tested extensively. However, due to technical difficulties with the platform the Mini- MCA was not mounted to the platform. Once a suitable platform is developed, future extensions can be conducted into the suitability of the Mini-MCA for airborne surveillance of Australian crops.
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Big Data and predictive analytics have received significant attention from the media and academic literature throughout the past few years, and it is likely that these emerging technologies will materially impact the mining sector. This short communication argues, however, that these technological forces will probably unfold differently in the mining industry than they have in many other sectors because of significant differences in the marginal cost of data capture and storage. To this end, we offer a brief overview of what Big Data and predictive analytics are, and explain how they are bringing about changes in a broad range of sectors. We discuss the “N=all” approach to data collection being promoted by many consultants and technology vendors in the marketplace but, by considering the economic and technical realities of data acquisition and storage, we then explain why a “n « all” data collection strategy probably makes more sense for the mining sector. Finally, towards shaping the industry’s policies with regards to technology-related investments in this area, we conclude by putting forward a conceptual model for leveraging Big Data tools and analytical techniques that is a more appropriate fit for the mining sector.
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Background Longer breastfeeding duration appears to have a protective effect against childhood obesity. This effect may be partially mediated by maternal feeding practices during the first years of life. However, the few studies that have examined links between breastfeeding duration and subsequent feeding practices have yielded conflicting results. Objective Using a large sample of first-time mothers and a newly validated, comprehensive measure of maternal feeding (the Feeding Practices and Structure Questionnaire1), this study examined associations between breastfeeding duration and maternal feeding practices at child age 24 months. Methods Mothers (n = 458) enrolled in the NOURISH trial2 provided data on breastfeeding at child age 4, 14 and 24 months, and on feeding practices at 24 months. Structural Equation Modelling was used to examine associations between breastfeeding duration and five non-responsive and four structure-related ‘authoritative’ feeding practices, adjusting for a range of maternal and child characteristics. Results The model showed acceptable fit (χ2/df = 1.68; RMSEA = .04, CFI = .91 and TLI = .89) and longer breastfeeding duration was negatively associated with four out of five non-responsive feeding practices and positively associated with three out of four structure-related feeding practices. Overall, these results suggest that mothers who breastfeed longer reported using more appropriate feeding practices. Conclusion These data demonstrate an association between longer breastfeeding duration and authoritative feeding practices characterised by responsiveness and structure, which may partly account for the apparent protective effect of breastfeeding on childhood obesity.
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When designed effectively dashboards are expected to reduce information overload and improve performance management. Hence, interest in dashboards has increased recently,which is also evident from the proliferation of dashboard solution providers in the market. Despite dashboards popularity, little is known about the extent of their effectiveness in organizations. Dashboards draw from multiple disciplines but ultimately use visualization to communicate important information to stakeholders. Thus,a better understanding of visualization can improve the design and use of dashboards. This paper reviews the foundations and roles of dashboards in performance management and proposes a framework for future research, which can enhance dashboard design and perceived usefulness depending on the fit between the features of the dashboard and the characteristics of the users.
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Foot morphology and function has received increasing attention from both biomechanics researchers and footwear manufacturers. In this study, 168 habitually unshod runners (90 males whose age, weight & height were 23 +/- 2.4years, 66 +/- 7.1kg & 1.68 +/- 0.13m and 78 females whose age, weight & height were 22 +/- 1.8years, 55 +/- 4.7kg & 1.6 +/- 0.11m) (Indians) and 196 shod runners (130 males whose age, weight & height were 24 +/- 2.6years, 66 +/- 8.2kg & 1.72 +/- 0.18m and 66 females whose age, weight & height were 23 +/- 1.5years, 54 +/- 5.6kg & 1.62 +/- 0.15m)(Chinese) participated in a foot scanning test using the easy-foot-scan (a three-dimensional foot scanning system) to obtain 3D foot surface data and 2D footprint imaging. Foot length, foot width, hallux angle and minimal distance from hallux to second toe were calculated to analyze foot morphological differences. This study found that significant differences exist between groups (shod Chinese and unshod Indians) for foot length (female p = 0.001), width (female p = 0.001), hallux angle (male and female p = 0.001) and the minimal distance (male and female p = 0.001) from hallux to second toe. This study suggests that significant differences in morphology between different ethnicities could be considered for future investigation of locomotion biomechanics characteristics between ethnicities and inform last shape and design so as to reduce injury risks and poor performance from mal-fit shoes.
Experimental measurement of the mechanical properties of carotid atherothrombotic plaque fibrous cap
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Eleven carotid atherothrombotic plaque samples were harvested from patients. Three samples that were highly calcified were discarded, while eight yielded results. The elastic properties of the material were estimated by fitting the measured indentation response to finite element simulations. The methodology was refined and its accuracy quantified using a synthetic rubber. The neo-Hookean form of the material model gave a good fit to the measured response of the tissue. The inferred shear modulus μ was found to be in the range 7-100 kPa, with a median value of 11 kPa. A review of published materials data showed a wide range of material properties for human atherothrombotic tissue. The effects of anisotropy and time dependency in these published results were highlighted. The present measurements were comparable to the static radial compression tests of Lee et al, 1991 [Structure-dependent dynamic behaviour of fibrous caps from human atherosclerotic plaques. Circulation 83, 1764-1770].
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We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.
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A flexible and simple Bayesian decision-theoretic design for dose-finding trials is proposed in this paper. In order to reduce the computational burden, we adopt a working model with conjugate priors, which is flexible to fit all monotonic dose-toxicity curves and produces analytic posterior distributions. We also discuss how to use a proper utility function to reflect the interest of the trial. Patients are allocated based on not only the utility function but also the chosen dose selection rule. The most popular dose selection rule is the one-step-look-ahead (OSLA), which selects the best-so-far dose. A more complicated rule, such as the two-step-look-ahead, is theoretically more efficient than the OSLA only when the required distributional assumptions are met, which is, however, often not the case in practice. We carried out extensive simulation studies to evaluate these two dose selection rules and found that OSLA was often more efficient than two-step-look-ahead under the proposed Bayesian structure. Moreover, our simulation results show that the proposed Bayesian method's performance is superior to several popular Bayesian methods and that the negative impact of prior misspecification can be managed in the design stage.
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We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.
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Previous studies have shown that the external growth records of the posterior adductor muscle scar (PAMS) of the bivalve Pinna nobilis are incomplete and do not produce accurate age estimations. We have developed a new methodology to study age and growth using the inner record of the PAMS, which avoids the necessity of costly in situ shell measurements or isotopic studies. Using the inner record we identified the positions of PAMS previously obscured by nacre and estimated the number of missing records in adult specimens with strong abrasion of the calcite layer in the anterior portion of the shell. The study of the PAMS and inner record of two shells that were 6 years old when collected showed that only 2 and 3 PAMS were observed, while 6 inner records could be counted, thus confirming our working methodology. Growth parameters of a P. nobilis population located in Moraira, Spain (western Mediterranean) were estimated with the new methodology and compared to those obtained using PAMS data and in situ measurements. For the comparisons, we applied different models considering the data alternatively as length-at-age (LA) and tag-recapture (TR). Among every method we tested to fit the Von Bertalanffy growth model, we observed that LA data from inner record fitted to the model using non-linear mixed effects and the estimation of missing records using the calcite width was the most appropriate. The equation obtained with this method, L = 573*(1 - e(-0.16(t-0.02))), is very similar to that calculated previously from in situ measurements for the same population.
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Gene-targeted disruption of Grg5, a mouse homologue of Drosophila groucho (gro), results in postnatal growth retardation in mice. The growth defect, most striking in approximately half of the Grg5 null mice, occurs during the first 4-5 weeks of age, but most mice recover retarded growth later. We used the nonlinear mixed-effects model to fit the growth data of wild-type, heterozygous, and Grg5 null mice. On the basis of preliminary evidence suggesting an interaction between Grg5 and the transcription factor Cbfa1/Runx2, critical for skeletal development, we further investigated the skeleton in the mice. A long bone growth plate defect was identified, which included shorter zones of proliferative and hypertrophic chondrocytes and decreased trabecular bone formation. This decreased trabecular bone formation is likely caused by a reduced recruitment of osteoblasts into the growth plate region of Grg5 null mice. Like the growth defect, the growth plate and trabecular bone abnormality improved as the mice grew older. The growth plate defect was associated with reduced Indian hedgehog expression and signaling. We suggest that Grg5, a transcriptional coregulator, modulates the activities of transcription factors, such as Cbfa1/Runx2 in vivo to affect Ihh expression and the function of long bone growth plates.
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Background It is often believed that by ensuring the ongoing completion of competency documents and life-long learning in nursing practice guarantees quality patient care. This is probably true in most cases where it provides reassurances that the nursing team is maintaining a safe “generalised” level of practice. However, competency does not always promise quality performance. There are a number of studies that have reported differences in what practitioners know and what they actually do despite being deemed competent. Aim The aim of this study was to assess whether our current competency documentation is fit for purpose and to ascertain whether performance assessment needs to be a key component in determining competence. Method 15 nurses within a General ICU who had been on the unit <4 years agreed to participate in this project. Using participant observation and assessing performance against key indicators of the Benner Novice to Expert5 model the participants were supported and assessed over the course of a ‘normal’ nursing shift. Results The results were surprising both positively and negatively. First, the nurses felt more empowered in their clinical decision making skills; second, it identified individual learning needs and milestones in educational development. There were some key challenges identified which included 5 nurses over estimating their level of competence, practice was still very much focused on task acquisition and skill and surprisingly some nurses still felt dominated by the other health professionals within the unit. Conclusion We found that the capacity and capabilities of our nursing workforce needs continual ongoing support especially if we want to move our staff from capable task-doer to competent performers. Using the key novice to expert indicators identified the way forward for us in how we assess performance and competence in practice particularly where promotion to higher grades is based on existing documentation.
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The power of projects has been demonstrated by the growth in their use across an increasing range of industries and workplaces in recent years. Not only has the number of people involved in project management increased, but the qualifications and backgrounds of those people have also broadened, with engineering no longer being the only path to project management (PM). Predicting the career trajectories in Project Management has become more important for both organisations employing project managers and project managers building career portfolios. Our research involved interviewing more than 75 project officers and project managers across a range of industries to explore their career journey. We used Wittgenstein’s family resemblance theory is to analyse the information from the transcripts to identify the extent to which the roles of participants fit with the commonly accepted definition of project management. Findings demonstrate diversity of project manager backgrounds and experiences and relational competencies across these backgrounds that form and shape PM careers.
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Inspiration for this work came from my recent experience of living in Beijing, China. Having a massive population of over 21 million people, one cannot feel but just another number within the crowd of this hectic megalopolis. Society is conditioned to obey, to conform, with some cultures being more hard lined with their citizens than others. However, there is a desire within each of us to have freedom of expression… to project an identity, to be an individual… nevertheless a desire not to be different… to follow trends and fads… a desire to fit in and connect. Within the pack there is also the outcast… the one who is different… the one who does not fit in. Pack has been created to be absorbed and interpreted openly by each individual. Driven by repetition and cycles, I have used this choreographic approach as a metaphor for the daily routine inherent in one’s life.
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Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.