866 resultados para Test data


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Transport regulators consider that, with respect to pavement damage, heavy vehicles (HVs) are the riskiest vehicles on the road network. That HV suspension design contributes to road and bridge damage has been recognised for some decades. This thesis deals with some aspects of HV suspension characteristics, particularly (but not exclusively) air suspensions. This is in the areas of developing low-cost in-service heavy vehicle (HV) suspension testing, the effects of larger-than-industry-standard longitudinal air lines and the characteristics of on-board mass (OBM) systems for HVs. All these areas, whilst seemingly disparate, seek to inform the management of HVs, reduce of their impact on the network asset and/or provide a measurement mechanism for worn HV suspensions. A number of project management groups at the State and National level in Australia have been, and will be, presented with the results of the project that resulted in this thesis. This should serve to inform their activities applicable to this research. A number of HVs were tested for various characteristics. These tests were used to form a number of conclusions about HV suspension behaviours. Wheel forces from road test data were analysed. A “novel roughness” measure was developed and applied to the road test data to determine dynamic load sharing, amongst other research outcomes. Further, it was proposed that this approach could inform future development of pavement models incorporating roughness and peak wheel forces. Left/right variations in wheel forces and wheel force variations for different speeds were also presented. This led on to some conclusions regarding suspension and wheel force frequencies, their transmission to the pavement and repetitive wheel loads in the spatial domain. An improved method of determining dynamic load sharing was developed and presented. It used the correlation coefficient between two elements of a HV to determine dynamic load sharing. This was validated against a mature dynamic loadsharing metric, the dynamic load sharing coefficient (de Pont, 1997). This was the first time that the technique of measuring correlation between elements on a HV has been used for a test case vs. a control case for two different sized air lines. That dynamic load sharing was improved at the air springs was shown for the test case of the large longitudinal air lines. The statistically significant improvement in dynamic load sharing at the air springs from larger longitudinal air lines varied from approximately 30 percent to 80 percent. Dynamic load sharing at the wheels was improved only for low air line flow events for the test case of larger longitudinal air lines. Statistically significant improvements to some suspension metrics across the range of test speeds and “novel roughness” values were evident from the use of larger longitudinal air lines, but these were not uniform. Of note were improvements to suspension metrics involving peak dynamic forces ranging from below the error margin to approximately 24 percent. Abstract models of HV suspensions were developed from the results of some of the tests. Those models were used to propose further development of, and future directions of research into, further gains in HV dynamic load sharing. This was from alterations to currently available damping characteristics combined with implementation of large longitudinal air lines. In-service testing of HV suspensions was found to be possible within a documented range from below the error margin to an error of approximately 16 percent. These results were in comparison with either the manufacturer’s certified data or test results replicating the Australian standard for “road-friendly” HV suspensions, Vehicle Standards Bulletin 11. OBM accuracy testing and development of tamper evidence from OBM data were detailed for over 2000 individual data points across twelve test and control OBM systems from eight suppliers installed on eleven HVs. The results indicated that 95 percent of contemporary OBM systems available in Australia are accurate to +/- 500 kg. The total variation in OBM linearity, after three outliers in the data were removed, was 0.5 percent. A tamper indicator and other OBM metrics that could be used by jurisdictions to determine tamper events were developed and documented. That OBM systems could be used as one vector for in-service testing of HV suspensions was one of a number of synergies between the seemingly disparate streams of this project.

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The motivation for secondary school principals in Queensland, Australia, to investigate curriculum change coincided with the commencement in 2005 of the state government’s publication of school exit test results as a measure of accountability. Aligning the schools’ curriculum with the requirements of high-stakes testing is considered by many academics and teachers as negative outcome of accountability for reasons such as ‘teaching to the test’ and narrowing the curriculum. However, this article outlines empirical evidence that principals are instigating curriculum change to improve published high-stakes test results. Three principals in this study offered several reasons as to why they wished to implement changes to school curricula. One reason articulated by all three was the pressures of accountability, particularly through the publication of high-stakes test data which has now become commonplace in education systems of many Western Nations.

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Current graduates in education are entering a very different profession to the one in which most of their “baby-boomer” colleagues started. It is a profession in which accountability and national high-stakes testing (e.g. NAPLAN) have become catch-cries, and where the interpretation and use of educational data is an additional challenge. This has led to schools focusing on performance, and teachers now have to analyse test data and apply the findings to their teaching.

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My oldest daughter recently secured a position as a Science/Geography teacher in a P-12 Catholic College in regional Queensland. This paper looks at the teaching world into which she has graduated. Specifically, the paper will outline and discuss findings from a survey of graduating early childhood student teachers in relation to their knowledge and skills of the current regime of high-stakes testing in Australia. The paper argues that understanding accountability and possessing skills to scrutinise test data are essential for the new teacher as s/he enters a profession in which governments world-wide are demanding a return for their investment in education. The paper will examine literature on accountability and surveillance in the form of high-stakes testing from global, school and classroom perspectives. It makes the claim that it is imperative for beginning teachers to be able to interpret high-stakes test data and considers the skills required to do this. The paper also draws on local research to comment on the readiness of graduates to meet this comparatively new professional demand.

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We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical VC dimension, empirical VC entropy, and margin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

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Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

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Many ageing road bridges, particularly timber bridges, require urgent improvement due to the demand imposed by the recent version of the Australian bridge loading code, AS 5100. As traffic volume plays a key role in the decision of budget allocations for bridge refurbishment/ replacement, many bridges in low volume traffic network remain in poor condition with axle load and/ or speed restrictions, thus disadvantaging many rural communities. This thesis examines an economical and environmentally sensible option of incorporating disused flat rail wagons (FRW) in the construction of bridges in low volume, high axle load road network. The constructability, economy and structural adequacy of the FRW road bridge is reported in the thesis with particular focus of a demonstration bridge commissioned in regional Queensland. The demonstration bridge comprises of a reinforced concrete slab (RCS) pavement resting on two FRWs with custom designed connection brackets at regular intervals along the span of the bridge. The FRW-RC bridge deck assembly is supported on elastomeric rubber pads resting on the abutment. As this type of bridge replacement technology is new and its structural design is not covered in the design standards, the in-service structural performance of the FRW bridge subjected to the high axle loadings prescribed in AS 5100 is examined through performance load testing. Both the static and the moving load tests are carried out using a fully laden commonly available three-axle tandem truck. The bridge deck is extensively strain gauged and displacement at several key locations is measured using linear variable displacement transducers (LVDTs). A high speed camera is used in the performance test and the digital image data are analysed using proprietary software to capture the locations of the wheel positions on the bridge span accurately. The wheel location is thus synchronised with the displacement and strain time series to infer the structural response of the FRW bridge. Field test data are used to calibrate a grillage model, developed for further analysis of the FRW bridge to various sets of high axle loads stipulated in the bridge design standard. Bridge behaviour predicted by the grillage model has exemplified that the live load stresses of the FRW bridge is significantly lower than the yield strength of steel and the deflections are well below the serviceability limit state set out in AS 5100. Based on the results reported in this thesis, it is concluded that the disused FRWs are competent to resist high axle loading prescribed in AS 5100 and are a viable alternative structural solution of bridge deck in the context of the low volume road networks.

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A road bridge containing disused flatbed rail wagons as the primary deck superstructure was performance tested in a low volume, high axle load traffic road in Queensland, Australia; some key results are presented in this paper. A fully laden truck of total weight 28.88 % of the serviceability design load prescribed in the Australian bridge code was used; its wheel positions were accurately captured using a high speed camera and synchronised with the real‐time deflections and strains measured at the critical members of the flat rail wagons. The strains remained well below the yield and narrated the existence of composite action between the reinforced concrete slab pavement and the wagon deck. A three dimensional grillage model was developed and calibrated using the test data, which established the structural adequacy of the rail wagons and the positive contribution of the reinforced concrete slab pavement to resist high axle traffic loads on a single lane bridge in the low volume roads network.

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In this paper, three metaheuristics are proposed for solving a class of job shop, open shop, and mixed shop scheduling problems. We evaluate the performance of the proposed algorithms by means of a set of Lawrence’s benchmark instances for the job shop problem, a set of randomly generated instances for the open shop problem, and a combined job shop and open shop test data for the mixed shop problem. The computational results show that the proposed algorithms perform extremely well on all these three types of shop scheduling problems. The results also reveal that the mixed shop problem is relatively easier to solve than the job shop problem due to the fact that the scheduling procedure becomes more flexible by the inclusion of more open shop jobs in the mixed shop.

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Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

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Cold-formed steel stud walls are an important component of Light Steel Framing (LSF) building systems used in commercial, industrial and residential buildings. In the conventional LSF stud wall systems, thin-walled steel studs are protected from fire by placing one or two layers of plasterboard on both sides with or without cavity insulation. However, there is very limited data about the structural and thermal performance of these wall systems while past research showed contradicting results about the benefits of cavity insulation. This research proposed a new LSF stud wall system in which a composite panel made of two plasterboards with insulation between them was used to improve the fire rating of walls. Full scale fire tests were conducted using both conventional steel stud walls with and without the use of cavity insulation and the new composite panel system. Eleven full scale load bearing wall specimens were tested to study the thermal and structural performances of the load bearing wall assemblies under standard fire conditions. These tests showed that the use of cavity insulation led to inferior fire performance of walls while also providing good explanations and supporting test data to overcome the incorrect industry assumptions about cavity insulation. Tests demonstrated that the use of external insulation in a composite panel form enhanced the thermal and structural performances of stud walls and increased their fire resistance rating significantly. This paper presents the details of the full scale fire tests of load-bearing wall assemblies lined with plasterboards and different types of insulation under varying load ratios. Test results including the temperature and deflection profiles of walls measured during the fire tests will be presented along with their failure modes and failure times.

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Background: Nurse practitioner education and practice has been guided by generic competency standards in Australia since 2006. Development of specialist competencies has been less structured and there are no formal standards to guide education and continuing professional development for specialty fields. There is limited international research and no Australian research into development of specialist nurse practitioner competencies. This pilot study aimed to test data collection methods, tools and processes in preparation for a larger national study to investigate specialist competency standards for emergency nurse practitioners. Research into specialist emergency nurse practitioner competencies has not been conducted in Australia. Methods: Mixed methods research was conducted with a sample of experienced emergency nurse practitioners. Deductive analysis of data from a focus group workshop informed development of a draft specialty competency framework. The framework was subsequently subjected to systematic scrutiny for consensus validation through a two round Delphi Study. Results: The Delphi study first round had a 100% response rate; the second round 75% response rate. The scoring for all items in both rounds was above the 80% cut off mark with the lowest mean score being 4.1 (82%) from the first round. Conclusion: The authors collaborated with emergency nurse practitioners to produce preliminary data on the formation of specialty competencies as a first step in developing an Australian framework.

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This thesis studies the water resources of Laidley Creek catchment within the Lockyer Valley where groundwater is used for intensive irrigation of crops. A holistic approach was used to consider groundwater within the total water cycle. The project mapped the geology, measured stream flows and groundwater levels, and analysed the chemistry of the waters. These data were integrated within a catchment-wide conceptual model, including historic and rainfall records. From this a numerical simulation was produced to test data validity and develop predictions of behaviour, which can support management decisions, particularly in times of variable climate.

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Background & aim To understand whether any change in gastric emptying (GE) is physiologically relevant, it is important to identify its variability. Information regarding the variability of GE in overweight and obese individuals is lacking. The aim of this study was to determine the reproducibility of GE in overweight and obese males. Methods Fifteen overweight and obese males [body mass index 30.3 (4.9) kg/m2] completed two identical GE tests 7 days apart. GE of a standard pancake breakfast was assessed by 13C-octanoic acid breath test. Data are presented as mean (±SD). Results There were no significant differences in GE between test days (half time (t1/2): 179 (15) and 176 (19 min), p = 0.56; lag time (tlag): 108 (14) and 104 (8) min, p = 0.26). Mean intra-individual coefficient of variation for t1/2 was 7.9% and tlag 7.5%. Based on these findings, to detect a treatment effect in a paired design with a power of 80% and α = 0.05, minimum mean effect sizes for t1/2 would need to be ≥14.4 min and tlag ≥ 8.1 min. Conclusions These data show that GE is reproducible in overweight and obese males and provide minimum mean effect sizes required to detect a hypothetical treatment effect in this population.