358 resultados para KAM curve
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Fusionless scoliosis surgery is an emerging treatment for idiopathic scoliosis as it offers theoretical advantages over current forms of treatment. Currently the treatment options for idiopathic scoliosis are observation, bracing and fusion. While brace treatment is non-invasive, and preserves the growth, motion, and function of the spine, it does not correct deformity and is only modestly successful in preventing curve progression. In adolescents who fail brace treatment, surgical treatment with an instrumented spinal fusion usually results in better deformity correction but is associated with substantially greater risk. Furthermore in younger patients requiring surgical treatment, fusion procedures are known to adversely effect the future growth of the chest and spine. Fusionless treatments have been developed to allow effective surgical treatment of patients with idiopathic scoliosis who are too young for fusion procedures. Anterior vertebral stapling is one such fusionless treatment which aims to modulate the growth of vertebra to allow correction of scoliosis whilst maintaining normal spinal motion The Mater Misericordiae Hospital in Brisbane has begun to use anterior vertebral stapling to treat patients with idiopathic scoliosis who are too young for fusion procedures. Currently the only staple approved for clinical use is manufactured by Medtronic Sofamor Danek (Memphis, TN). This thesis explains the biomechanical and anatomical changes that occur following anterior vertebral staple insertion using in vitro experiments performed on an immature bovine model. Currently there is a paucity of published information about anterior vertebral stapling so it is hoped that this project will provide information that will aid in our understanding of the clinical effects of staple insertion. The aims of this experimental study were threefold. The first phase was designed to determine the changes in the bending stiffness of the spine following staple insertion. The second phase was designed to measure the forces experienced by the staple during spinal movements. The third and final phase of testing was designed to describe the structural changes that occur to a vertebra as a consequence of staple insertion. The first phase of testing utilised a displacement controlled testing robot to compare the change in stiffness of a single spinal motion segment following staple insertion for the three basic spinal motions of flexion-extension, lateral bending, and axial rotation. For the second phase of testing strain gauges were attached to staples and used to measure staple forces during spinal movement. In the third and final phase the staples were removed and a testing specimen underwent micro-computed tomography (CT) scanning to describe the anatomical changes that occur following staple insertion. The displacement controlled testing showed that there was a significant decrease in bending stiffness in flexion, extension, lateral bending away from the staple, and axial rotation away from the staple following staple insertion. The strain gauge measurements showed that the greatest staple forces occurred in flexion and the least in extension. In addition, a reduction in the baseline staple compressive force was seen with successive loading cycles. Micro-CT scanning demonstrated that significant damage to the vertebral body and endplate occurred as a consequence of staple insertion. The clinical implications of this study are significant. Based on the findings of this project it is likely that the clinical effect of the anterior vertebral staple evaluated in this project is a consequence of growth plate damage (also called hemiepiphysiodesis) causing a partial growth arrest of the vertebra rather than simply compression of the growth plate. The surgical creation of a unilateral growth arrest is a well established treatment used in the management of congenital scoliosis but has not previously been considered for use in idiopathic scoliosis.
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An extensive literature examines the dynamics of interest rates, with particular attention given to the positive relationship between interest-rate volatility and the level of interest rates—the so-called level effect. This paper examines the interaction between the estimated level effect and competing parameterisations of interest-rate volatility for the Australian yield curve. We adopt a new methodology that estimates elasticity in a multivariate setting that explicitly accommodates the correlations that exist between various yield factors. Results show that significant correlations exist between the residuals of yield factors and that such correlations do indeed impact on model estimates. Within the multivariate setting, the level of the short rate is shown to be a crucial determinant of the conditional volatility of all three yield factors. Measures of model fit suggest that, in addition to the usual level effect, the incorporation of GARCH effects and possible regime shifts is important
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The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.
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Bayer hydrotalcites prepared using the seawater neutralisation (SWN) process of Bayer liquors are characterised using X-ray diffraction and thermal analysis techniques. The Bayer hydrotalcites are synthesised at four different temperatures (0, 25, 55, 75 °C) to determine the effect on the thermal stability of the hydrotalcite structure, and to identify other precipitates that form at these temperatures. The interlayer distance increased with increasing synthesis temperature, up to 55 °C, and then decreased by 0.14 Å for Bayer hydrotalcites prepared at 75 °C. The three mineralogical phases identified in this investigation are; 1) Bayer hydrotalcite, 2), calcium carbonate species, and 3) hydromagnesite. The DTG curve can be separated into four decomposition steps; 1) the removal of adsorbed water and free interlayer water in hydrotalcite (30 – 230 °C), 2) the dehydroxylation of hydrotalcite and the decarbonation of hydrotalcite (250 – 400 °C), 3) the decarbonation of hydromagnesite (400 – 550 °C), and 4) the decarbonation of aragonite (550 – 650 °C).
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Road and highway infrastructure provides the backbone for a nation’s economic growth. The versatile dispersion of population in Australia and its resource boom, coupled with improved living standards and growing societal expectations, calls for continuing development and improvement of road infrastructure under the current local, state and federal governments’ policies and strategic plans. As road infrastructure projects involve huge resources and mechanisms, achieving sustainability not only on economic scales but also through environmental and social responsibility becomes a crucial issue. While sustainability is a logical link to infrastructure development, literature study and consultation with the industry found that there is a lack of common understanding on what constitutes sustainability in the infrastructure context. Its priorities are often interpreted differently among multiple stakeholders. For road infrastructure projects which typically span over long periods of time, achieving tangible sustainability outcomes during the lifecycle of development remains a formidable task. Sustainable development initiatives often remain ideological as in macro-level policies and broad-based concepts. There were little elaboration and exemplar cases on how these policies and concepts can be translated into practical decision-making during project implementation. In contrast, there seemed to be over commitment on research and development of sustainability assessment methods and tools. Between the two positions, there is a perception-reality gap and mismatch, specifically on how to enhance sustainability deliverables during infrastructure project delivery. Review on past research in this industry sector also found that little has been done to promote sustainable road infrastructure development; this has wide and varied potential impacts. This research identified the common perceptions and expectations by different stakeholders towards achieving sustainability in road and highway infrastructure projects. Face to face interviews on selected representatives of these stakeholders were carried out in order to select and categorize, confirm and prioritize a list of sustainability performance targets identified through literature and past research. A Delphi study was conducted with the assistance of a panel of senior industry professionals and academic experts, which further considered the interrelationship and influence of the sustainability indicators, and identified critical sustainability indicators under ten critical sustainability criteria (e.g. Environmental, Health & Safety, Resource Utilization & Management, Social & Cultural, Economic, Public Governance & Community Engagement, Relations Management, Engineering, Institutional and Project Management). This presented critical sustainability issues that needed to be addressed at the project level. Accordingly, exemplar highway development projects were used as case studies to elicit solutions for the critical issues. Through the identification and integration of different perceptions and priority needs of the stakeholders, as well as key sustainability indicators and solutions for critical issues, a set of decision-making guidelines was developed to promote and drive consistent sustainability deliverables in road infrastructure projects.
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Severe spinal deformity in young children is a formidable challenge for optimal treatment. Standard interventions for adolescents, such as spinal deformity correction and fusion, may not be appropriate for young patients with considerable growth remaining. Alternative surgical options that provide deformity correction and protect the growth remaining in the spine are needed to treat this group of patients 1, 2. One such method is the use of shape memory alloy staples. We report our experience to date using video-assisted thoracoscopic insertion of shape memory alloy staples. A retrospective review was conducted of 13 patients with scoliosis, aged 7 to 13 years, who underwent video-assisted thoracoscopic insertion of shape memory staples. In our experience, video-assisted thoracoscopic insertion of shape memory alloy staples is a safe procedure with no complications noted. It is a reliable method of providing curve stability, however the follow up results to date indicate that the effectiveness of the procedure is greater in younger patients.
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The LiteSteel Beam (LSB) is a new hollow flange section developed by OneSteel Australian Tube Mills using their patented dual electric resistance welding and automated continuous roll-forming technologies. It has a unique geometry consisting of torsionally rigid rectangular hollow flanges and a relatively slender web. It has found increasing popularity in residential, industrial and commercial buildings as flexural members. The LSB is considerably lighter than traditional hot-rolled steel beams and provides both structural and construction efficiencies. However, the LSB flexural members are subjected to a relatively new lateral distortional buckling mode, which reduces their member moment capacities. Unlike the commonly observed lateral torsional buckling of steel beams, the lateral distortional buckling of LSBs is characterised by simultaneous lateral defection, twist and cross sectional change due to web distortion. The current design rules in AS/NZS 4600 (SA, 2005) for flexural members subject to lateral distortional buckling were found to be conservative by about 8% in the inelastic buckling region. Therefore, a new design rule was developed for LSBs subject to lateral distortional buckling based on finite element analyses of LSBs. The effect of section geometry was then considered and several geometrical parameters were used to develop an advanced set of design rules. This paper presents the details of the finite element analyses and the design curve development for hollow flange sections subject to lateral distortional buckling.
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Several approaches have been proposed to recognize handwritten Bengali characters using different curve fitting algorithms and curvature analysis. In this paper, a new algorithm (Curve-fitting Algorithm) to identify various strokes of a handwritten character is developed. The curve-fitting algorithm helps recognizing various strokes of different patterns (line, quadratic curve) precisely. This reduces the error elimination burden heavily. Implementation of this Modified Syntactic Method demonstrates significant improvement in the recognition of Bengali handwritten characters.
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Campylobacter jejuni followed by Campylobacter coli contribute substantially to the economic and public health burden attributed to food-borne infections in Australia. Genotypic characterisation of isolates has provided new insights into the epidemiology and pathogenesis of C. jejuni and C. coli. However, currently available methods are not conducive to large scale epidemiological investigations that are necessary to elucidate the global epidemiology of these common food-borne pathogens. This research aims to develop high resolution C. jejuni and C. coli genotyping schemes that are convenient for high throughput applications. Real-time PCR and High Resolution Melt (HRM) analysis are fundamental to the genotyping schemes developed in this study and enable rapid, cost effective, interrogation of a range of different polymorphic sites within the Campylobacter genome. While the sources and routes of transmission of campylobacters are unclear, handling and consumption of poultry meat is frequently associated with human campylobacteriosis in Australia. Therefore, chicken derived C. jejuni and C. coli isolates were used to develop and verify the methods described in this study. The first aim of this study describes the application of MLST-SNP (Multi Locus Sequence Typing Single Nucleotide Polymorphisms) + binary typing to 87 chicken C. jejuni isolates using real-time PCR analysis. These typing schemes were developed previously by our research group using isolates from campylobacteriosis patients. This present study showed that SNP + binary typing alone or in combination are effective at detecting epidemiological linkage between chicken derived Campylobacter isolates and enable data comparisons with other MLST based investigations. SNP + binary types obtained from chicken isolates in this study were compared with a previously SNP + binary and MLST typed set of human isolates. Common genotypes between the two collections of isolates were identified and ST-524 represented a clone that could be worth monitoring in the chicken meat industry. In contrast, ST-48, mainly associated with bovine hosts, was abundant in the human isolates. This genotype was, however, absent in the chicken isolates, indicating the role of non-poultry sources in causing human Campylobacter infections. This demonstrates the potential application of SNP + binary typing for epidemiological investigations and source tracing. While MLST SNPs and binary genes comprise the more stable backbone of the Campylobacter genome and are indicative of long term epidemiological linkage of the isolates, the development of a High Resolution Melt (HRM) based curve analysis method to interrogate the hypervariable Campylobacter flagellin encoding gene (flaA) is described in Aim 2 of this study. The flaA gene product appears to be an important pathogenicity determinant of campylobacters and is therefore a popular target for genotyping, especially for short term epidemiological studies such as outbreak investigations. HRM curve analysis based flaA interrogation is a single-step closed-tube method that provides portable data that can be easily shared and accessed. Critical to the development of flaA HRM was the use of flaA specific primers that did not amplify the flaB gene. HRM curve analysis flaA interrogation was successful at discriminating the 47 sequence variants identified within the 87 C. jejuni and 15 C. coli isolates and correlated to the epidemiological background of the isolates. In the combinatorial format, the resolving power of flaA was additive to that of SNP + binary typing and CRISPR (Clustered regularly spaced short Palindromic repeats) HRM and fits the PHRANA (Progressive hierarchical resolving assays using nucleic acids) approach for genotyping. The use of statistical methods to analyse the HRM data enhanced sophistication of the method. Therefore, flaA HRM is a rapid and cost effective alternative to gel- or sequence-based flaA typing schemes. Aim 3 of this study describes the development of a novel bioinformatics driven method to interrogate Campylobacter MLST gene fragments using HRM, and is called ‘SNP Nucleated Minim MLST’ or ‘Minim typing’. The method involves HRM interrogation of MLST fragments that encompass highly informative “Nucleating SNPS” to ensure high resolution. Selection of fragments potentially suited to HRM analysis was conducted in silico using i) “Minimum SNPs” and ii) the new ’HRMtype’ software packages. Species specific sets of six “Nucleating SNPs” and six HRM fragments were identified for both C. jejuni and C. coli to ensure high typeability and resolution relevant to the MLST database. ‘Minim typing’ was tested empirically by typing 15 C. jejuni and five C. coli isolates. The association of clonal complexes (CC) to each isolate by ‘Minim typing’ and SNP + binary typing were used to compare the two MLST interrogation schemes. The CCs linked with each C. jejuni isolate were consistent for both methods. Thus, ‘Minim typing’ is an efficient and cost effective method to interrogate MLST genes. However, it is not expected to be independent, or meet the resolution of, sequence based MLST gene interrogation. ‘Minim typing’ in combination with flaA HRM is envisaged to comprise a highly resolving combinatorial typing scheme developed around the HRM platform and is amenable to automation and multiplexing. The genotyping techniques described in this thesis involve the combinatorial interrogation of differentially evolving genetic markers on the unified real-time PCR and HRM platform. They provide high resolution and are simple, cost effective and ideally suited to rapid and high throughput genotyping for these common food-borne pathogens.
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Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the complex cells, which causes subtle differences in the responses. In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.
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This thesis is about the derivation of the addition law on an arbitrary elliptic curve and efficiently adding points on this elliptic curve using the derived addition law. The outcomes of this research guarantee practical speedups in higher level operations which depend on point additions. In particular, the contributions immediately find applications in cryptology. Mastered by the 19th century mathematicians, the study of the theory of elliptic curves has been active for decades. Elliptic curves over finite fields made their way into public key cryptography in late 1980’s with independent proposals by Miller [Mil86] and Koblitz [Kob87]. Elliptic Curve Cryptography (ECC), following Miller’s and Koblitz’s proposals, employs the group of rational points on an elliptic curve in building discrete logarithm based public key cryptosystems. Starting from late 1990’s, the emergence of the ECC market has boosted the research in computational aspects of elliptic curves. This thesis falls into this same area of research where the main aim is to speed up the additions of rational points on an arbitrary elliptic curve (over a field of large characteristic). The outcomes of this work can be used to speed up applications which are based on elliptic curves, including cryptographic applications in ECC. The aforementioned goals of this thesis are achieved in five main steps. As the first step, this thesis brings together several algebraic tools in order to derive the unique group law of an elliptic curve. This step also includes an investigation of recent computer algebra packages relating to their capabilities. Although the group law is unique, its evaluation can be performed using abundant (in fact infinitely many) formulae. As the second step, this thesis progresses the finding of the best formulae for efficient addition of points. In the third step, the group law is stated explicitly by handling all possible summands. The fourth step presents the algorithms to be used for efficient point additions. In the fifth and final step, optimized software implementations of the proposed algorithms are presented in order to show that theoretical speedups of step four can be practically obtained. In each of the five steps, this thesis focuses on five forms of elliptic curves over finite fields of large characteristic. A list of these forms and their defining equations are given as follows: (a) Short Weierstrass form, y2 = x3 + ax + b, (b) Extended Jacobi quartic form, y2 = dx4 + 2ax2 + 1, (c) Twisted Hessian form, ax3 + y3 + 1 = dxy, (d) Twisted Edwards form, ax2 + y2 = 1 + dx2y2, (e) Twisted Jacobi intersection form, bs2 + c2 = 1, as2 + d2 = 1, These forms are the most promising candidates for efficient computations and thus considered in this work. Nevertheless, the methods employed in this thesis are capable of handling arbitrary elliptic curves. From a high level point of view, the following outcomes are achieved in this thesis. - Related literature results are brought together and further revisited. For most of the cases several missed formulae, algorithms, and efficient point representations are discovered. - Analogies are made among all studied forms. For instance, it is shown that two sets of affine addition formulae are sufficient to cover all possible affine inputs as long as the output is also an affine point in any of these forms. In the literature, many special cases, especially interactions with points at infinity were omitted from discussion. This thesis handles all of the possibilities. - Several new point doubling/addition formulae and algorithms are introduced, which are more efficient than the existing alternatives in the literature. Most notably, the speed of extended Jacobi quartic, twisted Edwards, and Jacobi intersection forms are improved. New unified addition formulae are proposed for short Weierstrass form. New coordinate systems are studied for the first time. - An optimized implementation is developed using a combination of generic x86-64 assembly instructions and the plain C language. The practical advantages of the proposed algorithms are supported by computer experiments. - All formulae, presented in the body of this thesis, are checked for correctness using computer algebra scripts together with details on register allocations.
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When asymptotic series methods are applied in order to solve problems that arise in applied mathematics in the limit that some parameter becomes small, they are unable to demonstrate behaviour that occurs on a scale that is exponentially small compared to the algebraic terms of the asymptotic series. There are many examples of physical systems where behaviour on this scale has important effects and, as such, a range of techniques known as exponential asymptotic techniques were developed that may be used to examinine behaviour on this exponentially small scale. Many problems in applied mathematics may be represented by behaviour within the complex plane, which may subsequently be examined using asymptotic methods. These problems frequently demonstrate behaviour known as Stokes phenomenon, which involves the rapid switches of behaviour on an exponentially small scale in the neighbourhood of some curve known as a Stokes line. Exponential asymptotic techniques have been applied in order to obtain an expression for this exponentially small switching behaviour in the solutions to orginary and partial differential equations. The problem of potential flow over a submerged obstacle has been previously considered in this manner by Chapman & Vanden-Broeck (2006). By representing the problem in the complex plane and applying an exponential asymptotic technique, they were able to detect the switching, and subsequent behaviour, of exponentially small waves on the free surface of the flow in the limit of small Froude number, specifically considering the case of flow over a step with one Stokes line present in the complex plane. We consider an extension of this work to flow configurations with multiple Stokes lines, such as flow over an inclined step, or flow over a bump or trench. The resultant expressions are analysed, and demonstrate interesting implications, such as the presence of exponentially sub-subdominant intermediate waves and the possibility of trapped surface waves for flow over a bump or trench. We then consider the effect of multiple Stokes lines in higher order equations, particu- larly investigating the behaviour of higher-order Stokes lines in the solutions to partial differential equations. These higher-order Stokes lines switch off the ordinary Stokes lines themselves, adding a layer of complexity to the overall Stokes structure of the solution. Specifically, we consider the different approaches taken by Howls et al. (2004) and Chap- man & Mortimer (2005) in applying exponential asymptotic techniques to determine the higher-order Stokes phenomenon behaviour in the solution to a particular partial differ- ential equation.
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PURPOSE: The aim of this study was to further evaluate the validity and clinical meaningfulness of appetite sensations to predict overall energy intake as well as body weight loss. METHODS: Men (n=176) and women (n=139) involved in six weight loss studies were selected to participate in this study. Visual analogue scales were used to measure appetite sensations before and after a fixed test meal. Fasting appetite sensations, 1 h post-prandial area under the curve (AUC) and the satiety quotient (SQ) were used as predictors of energy intake and body weight loss. Two separate measures of energy intake were used: a buffet style ad libitum test lunch and a three-day self-report dietary record. RESULTS: One-hour post-prandial AUC for all appetite sensations represented the strongest predictors of ad libitum test lunch energy intake (p0.001). These associations were more consistent and pronounced for women than men. Only SQ for fullness was associated with ad libitum test lunch energy intake in women. Similar but weaker relationships were found between appetite sensations and the 3-day self-reported energy intake. Weight loss was associated with changes in appetite sensations (p0.01) and the best predictors of body weight loss were fasting desire to eat; hunger; and PFC (p0.01). CONCLUSIONS: These results demonstrate that appetite sensations are relatively useful predictors of spontaneous energy intake, free-living total energy intake and body weight loss. They also confirm that SQ for fullness predicts energy intake, at least in women.
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Nanoindentation is a useful technique for probing the mechanical properties of bone, and finite element (FE) modeling of the indentation allows inverse determination of elasto-plastic constitutive properties. However, FE simulations to date have assumed frictionless contact between indenter and bone. The aim of this study was to explore the effect of friction in simulations of bone nanoindentation. Two dimensional axisymmetric FE simulations were performed using a spheroconical indenter of tip radius 0.6m and angle 90°. The coefficient of friction between indenter and bone was varied between 0.0 (frictionless) and 0.3. Isotropic linear elasticity was used in all simulations, with bone elastic modulus E=13.56GPa and Poisson’s ratio =0.3. Plasticity was incorporated using both Drucker-Prager and von Mises yield surfaces. Friction had a modest effect on the predicted force-indentation curve for both von Mises and Drucker-Prager plasticity, reducing maximum indenter displacement by 10% and 20% respectively as friction coefficient was increased from zero to 0.3 (at a maximum indenter force of 5mN). However, friction has a much greater effect on predicted pile-up after indentation, reducing predicted pile-up from 0.27m to 0.11m with a von Mises model, and from 0.09m to 0.02m with Drucker-Prager plasticity. We conclude that it is important to include friction in nanoindentation simulations of bone.
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The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.