Quantitative fit assessment of a precontoured fracture fixation plate : its automation and an investigation on the borderline cases

Virtual methods to assess the fitting of a fracture fixation plate were proposed recently, however with limitations such as simplified fit criteria or manual data processing. This study aims to automate a fit analysis procedure using clinical-based criteria, and then to analyse the results further for borderline fit cases. Three dimensional (3D) models of 45 bones and of a precontoured distal tibial plate were utilized to assess the fitting of the plate automatically. A Matlab program was developed to automatically measure the shortest distance between the bone and the plate at three regions of interest and a plate-bone angle. The measured values including the fit assessment results were recorded in a spreadsheet as part of the batch-process routine. An automated fit analysis procedure will enable the processing of larger bone datasets in a significantly shorter time, which will provide more representative data of the target population for plate shape design and validation. As a result, better fitting plates can be manufactured and made available to surgeons, thereby reducing the risk and cost associated with complications or corrective procedures. This in turn, is expected to translate into improving patients' quality of life.

The contribution of leadership attributes to large scale, complex project success

Mismanagement of large-scale, complex projects has resulted in spectacular failures, cost overruns, time blowouts, and stakeholder dissatisfaction. We focus discussion on the interaction of key management and leadership attributes which facilitate leaders’ adaptive behaviors. These behaviors should in turn influence adaptive team member behavior, stakeholder engagement and successful project outcomes, outputs and impacts. An understanding of this type of management will benefit from a perspective based in managerial and organizational cognition. The research question we explore is whether successful leaders of large-scale complex projects have an internal process leading to a display of administrative, adaptive, and enabling behaviors that foster adaptive processes and enabling behaviors within their teams and with external stakeholders. At the core of the model we propose interactions of key attributes, namely cognitive flexibility, affect, and emotional intelligence. The result of these cognitive-affective attribute interactions is leadership leading to enhanced likelihood of complex project success.

The impact of organisational culture on the project selection process : The case of public infrastructure project in Indonesia

Project selection is a complex decision-making process as it involves multiple objectives, constraints and stakeholders. Understanding the organisation, in particular organisational culture, is an essential stage in improving decision-making process. The influences of organisational culture on decision-making can be seen in the way people work as a team, act and cooperate in their teamwork to achieve the set goals, and also in how people think, prioritize and decide. This paper aims to give evidence of the impact of organisational culture on the decision-making process in project selection, in the Indonesian context. Data was collected from a questionnaire survey developed based on the existing models of organisational culture (Denison 1990, Hofstede 2001, and Glaser et al 1987). Four main cultural traits (involvement, consistency, mission and power-distance) were selected and employed to examine the influence of organisational culture on the effectiveness of decision-making in the current Indonesian project selection processes. The results reveal that there are differences in organisational cultures for two organisations in three provinces. It also suggests that organisational culture (particularly the traits of ‘involvement’, ‘consistency’ and ‘mission’) contribute to the effectiveness of decision-making in the selected cases.

A multidisciplinary examination of fast bowling talent development in cricket

Research on expertise, talent identification and development has tended to be mono-disciplinary, typically adopting geno-centric or environmentalist positions, with an overriding focus on operational issues. In this thesis, the validity of dualist positions on sport expertise is evaluated. It is argued that, to advance understanding of expertise and talent development, a shift towards a multidisciplinary and integrative science focus is necessary, along with the development of a comprehensive multidisciplinary theoretical rationale. Dynamical systems theory is utilised as a multidisciplinary theoretical rationale for the succession of studies, capturing how multiple interacting constraints can shape the development of expert performers. Phase I of the research examines experiential knowledge of coaches and players on the development of fast bowling talent utilising qualitative research methodology. It provides insights into the developmental histories of expert fast bowlers, as well as coaching philosophies on the constraints of fast bowling expertise. Results suggest talent development programmes should eschew the notion of common optimal performance models and emphasize the individual nature of pathways to expertise. Coaching and talent development programmes should identify the range of interacting constraints that impinge on the performance potential of individual athletes, rather than evaluating current performance on physical tests referenced to group norms. Phase II of this research comprises three further studies that investigate several of the key components identified as important for fast bowling expertise, talent identification and development extrapolated from Phase I of this research. This multidisciplinary programme of work involves a comprehensive analysis of fast bowling performance in a cross-section of the Cricket Australia high performance pathways, from the junior, emerging and national elite fast bowling squads. Briefly, differences were found in trunk kinematics associated with the generation of ball speed across the three groups. These differences in release mechanics indicated the functional adaptations in movement patterns as bowlers’ physical and anatomical characteristics changed during maturation. Second to the generation of ball speed, the ability to produce a range of delivery types was highlighted as a key component of expertise in the qualitative phase. The ability of athletes to produce consistent results on different surfaces and in different environments has drawn attention to the challenge of measuring consistency and flexibility in skill assessments. Examination of fast bowlers in Phase II demonstrated that national bowlers can make adjustments to the accuracy of subsequent deliveries during performance of a cricket bowling skills test, and perform a range of delivery types with increased accuracy and consistency. Finally, variability in selected delivery stride ground reaction force components in fast bowling revealed the degenerate nature of this complex multi-articular skill where the same performance outcome can be achieved with unique movement strategies. Utilising qualitative and quantitative methodologies to examine fast bowling expertise, the importance of degeneracy and adaptability in fast bowling has been highlighted alongside learning design that promotes dynamic learning environments.

Re-thinking how we plan to address technically complex problems : drawing on planning theory to guide practice in revision of land use plans in coastal high hazard zones

Queensland's new State Planning Policy for Coastal Protection, released in March and approved in April 2011 as part of the Queensland Coastal Plan, stipulates that local governments prepare and implement adaptation strategies for built up areas projected to be subject to coastal hazards between present day and 2100. Urban localities within the delineated coastal high hazard zone (as determined by models incorporating a 0.8 meter rise in sea level and a 10% increase in the maximum cyclone activity) will be required to re-evaluate their plans to accommodate growth, revising land use plans to minimise impacts of anticipated erosion and flooding on developed areas and infrastructure. While implementation of such strategies would aid in avoidance or minimisation of risk exposure, communities are likely to face significant challenges in such implementation, especially as development in Queensland is so intensely focussed upon its coasts with these new policies directing development away from highly desirable waterfront land. This paper examines models of planning theory to understand how we plan when faced with technically complex problems towards formulation of a framework for evaluating and improving practice.

An actor-network research frame for analysing complex socio-technical situations

This paper presents a “research frame” which we have found useful in analyzing complex socio- technical situations. The research frame is based on aspects of actor-network theory: “interressment”, “enrollment”, “points of passage” and the “trial of strength”. Each of these aspects are described in turn, making clear their purpose in the overall research frame. Having established the research frame it is used to analyse two examples. First, the use of speech recognition technology is examined in two different contexts, showing how to apply the frame to compare and contrast current situations. Next, a current medical consultation context is described and the research frame is used to consider how it could change with innovative technology. In both examples, the research frame shows that the use of an artefact or technology must be considered together with the context in which it is used.

Ageing and use of complex product interfaces

This paper presents an experiment designed to investigate if redundancy in an interface has any impact on the use of complex interfaces by older people and people with low prior-experience with technology. The important findings of this study were that older people (65+ years) completed the tasks on the Words only based interface faster than on Redundant (text and symbols) interface. The rest of the participants completed tasks significantly faster on the Redundant interface. From a cognitive processing perspective, sustained attention (one of the functions of Central Executive) has emerged as one of the important factors in completing tasks on complex interfaces faster and with fewer of errors.

Systematics of the Ustilago-Sporisorium-Macalpinomyces complex of smut fungi

Smut fungi are important pathogens of grasses, including the cultivated crops maize, sorghum and sugarcane. Typically, smut fungi infect the inflorescence of their host plants. Three genera of smut fungi (Ustilago, Sporisorium and Macalpinomyces) form a complex with overlapping morphological characters, making species placement problematic. For example, the newly described Macalpinomyces mackinlayi possesses a combination of morphological characters such that it cannot be unambiguously accommodated in any of the three genera. Previous attempts to define Ustilago, Sporisorium and Macalpinomyces using morphology and molecular phylogenetics have highlighted the polyphyletic nature of the genera, but have failed to produce a satisfactory taxonomic resolution. A detailed systematic study of 137 smut species in the Ustilago-Sporisorium- Macalpinomyces complex was completed in the current work. Morphological and DNA sequence data from five loci were assessed with maximum likelihood and Bayesian inference to reconstruct a phylogeny of the complex. The phylogenetic hypotheses generated were used to identify morphological synapomorphies, some of which had previously been dismissed as a useful way to delimit the complex. These synapomorphic characters are the basis for a revised taxonomic classification of the Ustilago-Sporisorium-Macalpinomyces complex, which takes into account their morphological diversity and coevolution with their grass hosts. The new classification is based on a redescription of the type genus Sporisorium, and the establishment of four genera, described from newly recognised monophyletic groups, to accommodate species expelled from Sporisorium. Over 150 taxonomic combinations have been proposed as an outcome of this investigation, which makes a rigorous and objective contribution to the fungal systematics of these important plant pathogens.

An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata

Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.

The influence of personality traits in predicting information processing and message persuasiveness

Gray‘s (2000) revised Reinforcement Sensitivity Theory (r-RST) was used to investigate personality effects on information processing biases to gain-framed and loss-framed anti-speeding messages and the persuasiveness of these messages. The r-RST postulates that behaviour is regulated by two major motivational systems: reward system or punishment system. It was hypothesised that both message processing and persuasiveness would be dependent upon an individual‘s sensitivity to reward or punishment. Student drivers (N = 133) were randomly assigned to view one of four anti-speeding messages or no message (control group). Individual processing differences were then measured using a lexical decision task, prior to participants completing a personality and persuasion questionnaire. Results indicated that participants who were more sensitive to reward showed a marginally significant (p = .050) tendency to report higher intentions to comply with the social gain-framed message and demonstrate a cognitive processing bias towards this message, than those with lower reward sensitivity.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

The relationship between parents’ self-efficacy beliefs, outcome expectations, child behaviour, and management of atopic dermatitis

Atopic dermatitis (AD) is a chronic inflammatory skin condition, characterized by intense pruritis, with a complex aetiology comprising multiple genetic and environmental factors. It is a common chronic health problem among children, and along with other allergic conditions, is increasing in prevalence within Australia and in many countries worldwide. Successful management of childhood AD poses a significant and ongoing challenge to parents of affected children. Episodic and unpredictable, AD can have profound effects on children’s physical and psychosocial wellbeing and quality of life, and that of their caregivers and families. Where concurrent child behavioural problems and parenting difficulties exist, parents may have particular difficulty achieving adequate and consistent performance of the routine management tasks that promote the child’s health and wellbeing. Despite frequent reports of behaviour problems in children with AD, past research has neglected the importance of child behaviour to parenting confidence and competence with treatment. Parents of children with AD are also at risk of experiencing depression, anxiety, parenting stress, and parenting difficulties. Although these factors have been associated with difficulty in managing other childhood chronic health conditions, the nature of these relationships in the context of child AD management has not been reported. This study therefore examined relationships between child, parent, and family variables, and parents’ management of child AD and difficult child behaviour, using social cognitive and self-efficacy theory as a guiding framework. The study was conducted in three phases. It employed a quantitative, cross-sectional study design, accessing a community sample of 120 parents of children with AD, and a sample of 64 child-parent dyads recruited from a metropolitan paediatric tertiary referral centre. In Phase One, instruments designed to measure parents’ self-reported performance of AD management tasks (Parents’ Eczema Management Scale – PEMS) and parents’ outcome expectations of task performance (Parents’ Outcome Expectations of Eczema Management Scale – POEEMS) were adapted from the Parental Self-Efficacy with Eczema Care Index (PASECI). In Phase Two, these instruments were used to examine relationships between child, parent, and family variables, and parents’ self-efficacy, outcome expectations, and self-reported performance of AD management tasks. Relationships between child, parent, and family variables, parents’ self-efficacy for managing problem behaviours, and reported parenting practices, were also examined. This latter focus was explored further in Phase Three, in which relationships between observed child and parent behaviour, and parent-reported self-efficacy for managing both child AD and problem behaviours, were explored. Phase One demonstrated the reliability of both PEMS and POEEMS, and confirmed that PASECI was reliable and valid with modification as detailed. Factor analyses revealed two-factor structures for PEMS and PASECI alike, with both scales containing factors related to performing routine management tasks, and managing the child’s symptoms and behaviour. Factor analysis was also applied to POEEMS resulting in a three-factor structure. Factors relating to independent management of AD by the parent, involving healthcare professionals in management, and involving the child in management of AD were found. Parents’ self-efficacy and outcome expectations had a significant influence on self-reported task performance. In Phase Two, relationships emerged between parents’ self-efficacy and self-reported performance of AD management tasks, and AD severity, child behaviour difficulties, parent depression and stress, conflict over parenting issues, and parents’ relationship satisfaction. Using multiple linear regressions, significant proportions of variation in parents’ self-efficacy and self-reported performance of AD management tasks were explained by child behaviour difficulties and parents’ formal education, and self-efficacy emerged as a likely mediator for the relationships between both child behaviour and parents’ education, and performance of AD management tasks. Relationships were also found between parents’ self-efficacy for managing difficult child behaviour and use of dysfunctional parenting strategies, and child behaviour difficulties, parents’ depression and stress, conflict over parenting issues, and relationship satisfaction. While significant proportions of variation in self-efficacy for managing child behaviour were explained by both child behaviour and family income, family income was the only variable to explain a significant proportion of variation in parent-reported use of dysfunctional parenting strategies. Greater use of dysfunctional parenting strategies (both lax and authoritarian parenting) was associated with more severe AD. Parents reporting lower self-efficacy for managing AD also reported lower self-efficacy for managing difficult child behaviour; likewise, less successful self-reported performance of AD management tasks was associated with greater use of dysfunctional parenting strategies. When child and parent behaviour was directly observed in Phase Three, more aversive child behaviour was associated with lower self-efficacy, less positive outcome expectations, and poorer self-reported performance of AD management tasks by parents. Importantly, there were strong positive relationships between these variables (self-efficacy, outcome expectations, and self-reported task performance) and parents’ observed competence when providing treatment to their child. Less competent performance was also associated with greater parent-reported child behaviour difficulties, parent depression and stress, parenting conflict, and relationship dissatisfaction. Overall, this study revealed the importance of child behaviour to parents’ confidence and practices in the contexts of child AD and child behaviour management. Parents of children with concurrent AD and behavioural problems are at particular risk of having low self-efficacy for managing their child’s AD and difficult behaviour. Children with more severe AD are also at higher risk of behaviour problems, and thus represent a high-risk group of children whose parents may struggle to manage the disease successfully. As one of the first studies to examine the role and correlates of parents’ self-efficacy in child AD management, this study identified a number of potentially modifiable factors that can be targeted to enhance parents’ self-efficacy, and improve parent management of child AD. In particular, interventions should focus on child behaviour and parenting issues to support parents caring for children with AD and improve child health outcomes. In future, findings from this research will assist healthcare teams to identify parents most in need of support and intervention, and inform the development and testing of targeted multidisciplinary strategies to support parents caring for children with AD.

Complex modelling in the primary/middle school years

The world’s increasing complexity, competitiveness, interconnectivity, and dependence on technology generate new challenges for nations and individuals that cannot be met by continuing education as usual (Katehi, Pearson, & Feder, 2009). With the proliferation of complex systems have come new technologies for communication, collaboration, and conceptualisation. These technologies have led to significant changes in the forms of mathematical and scientific thinking that are required beyond the classroom. Modelling, in its various forms, can develop and broaden children’s mathematical and scientific thinking beyond the standard curriculum. This paper first considers future competencies in the mathematical sciences within an increasingly complex world. Next, consideration is given to interdisciplinary problem solving and models and modelling. Examples of complex, interdisciplinary modelling activities across grades are presented, with data modelling in 1st grade, model-eliciting in 4th grade, and engineering-based modelling in 7th-9th grades.

Complex learning through cognitively demanding tasks

The world’s increasing complexity, competitiveness, interconnectivity, and dependence on technology generate new challenges for nations and individuals that cannot be met by “continuing education as usual” (The National Academies, 2009). With the proliferation of complex systems have come new technologies for communication, collaboration, and conceptualization. These technologies have led to significant changes in the forms of mathematical thinking that are required beyond the classroom. This paper argues for the need to incorporate future-oriented understandings and competencies within the mathematics curriculum, through intellectually stimulating activities that draw upon multidisciplinary content and contexts. The paper also argues for greater recognition of children’s learning potential, as increasingly complex learners capable of dealing with cognitively demanding tasks.

Mathematics and complex learning

There is unprecedented worldwide demand for mathematical solutions to complex problems. That demand has generated a further call to update mathematics education in a way that develops students’ abilities to deal with complex systems.