Modeling videokeratoscopic height data with spherical harmonics

Purpose: All currently considered parametric models used for decomposing videokeratoscopy height data are viewercentered and hence describe what the operator sees rather than what the surface is. The purpose of this study was to ascertain the applicability of an object-centered representation to modeling of corneal surfaces. Methods: A three-dimensional surface decomposition into a series of spherical harmonics is considered and compared with the traditional Zernike polynomial expansion for a range of videokeratoscopic height data. Results: Spherical harmonic decomposition led to significantly better fits to corneal surfaces (in terms of the root mean square error values) than the corresponding Zernike polynomial expansions with the same number of coefficients, for all considered corneal surfaces, corneal diameters, and model orders. Conclusions: Spherical harmonic decomposition is a viable alternative to Zernike polynomial decomposition. It achieves better fits to videokeratoscopic height data and has the advantage of an object-centered representation that could be particularly suited to the analysis of multiple corneal measurements.

Signs, symptoms and comorbidities in contact lens-related microbial keratitis

Purpose: The aim of this study was to characterize the clinical signs, symptoms, and ocular and systemic comorbidities in a large case series of contact lens-related microbial keratitis. Methods: Two hundred ninety-seven cases of contact lens-related microbial keratitis, aged between 15 and 64 years were detected through surveillance of hospital and community based ophthalmic practitioners in Australia and New Zealand. Full clinical data were available for 190 cases and 90 were interviewed by telephone. Clinical data included the size, location, and degree of anterior chamber response. Symptom data were available from the practitioner and from participant self-report. Associations between symptoms and disease severity were evaluated. Data on ocular and systemic disease were collected from participants and practitioners. The frequency of comorbidities was compared between the different severities of disease and to population norms. Results: More severe disease was associated with greater symptom severity and pain was the most prevalent symptom reported. Ninety-one percent of cases showed progression of ocular symptoms after lens removal, and symptom progression was associated with all severities of disease. Twenty-five percent of cases reported prior episodes requiring emergency attention. Thyroid disease (p 0.05) and self-reported poor health (p 0.001) were more common in cases compared with age-matched population norms. Discussion: Information on the signs, symptoms, and comorbidities associated with contact lens-related microbial keratitis may be useful in patient education and for practitioners involved in the fitting of lenses and management of complications. Although pain was the most common symptom experienced, progression of symptoms despite lens removal was close to universal. Poor general health, particularly respiratory disease and thyroid disease was more common in cases than in the general population, which may prompt practitioners to recommend flexibility in wear schedules when in poor health or the selection of a lower risk wear schedule in at risk patients

Realism and control : problem-based learning programs as a data source for work-related research

Problem-based learning (PBL) is a pedagogical methodology that presents the learner with a problem to be solved to stimulate and situate learning. This paper presents key characteristics of a problem-based learning environment that determines its suitability as a data source for workrelated research studies. To date, little has been written about the availability and validity of PBL environments as a data source and its suitability for work-related research. We describe problembased learning and use a research project case study to illustrate the challenges associated with industry work samples. We then describe the PBL course used in our research case study and use this example to illustrate the key attributes of problem-based learning environments and show how the chosen PBL environment met the work-related research requirements of the research case study. We propose that the more realistic the PBL work context and work group composition, the better the PBL environment as a data source for a work-related research. The work context is more realistic when relevant and complex project-based problems are tackled in industry-like work conditions over longer time frames. Work group composition is more realistic when participants with industry-level education and experience enact specialized roles in different disciplines within a professional community.

Patterns of engagement in workplace learning amongst employees from social sectors

Continuous learning and development has become increasingly important in the information age. However, employees with limited formal education in lower status occupations may be disadvantaged in their opportunities for development, as their jobs tend to require more limited knowledge and skills. In mature age, such workers may be subject to cumulative disadvantage with respect to work related learning and development, as well as negative stereotyping. This thesis concerns work related learning and development from a lifespan development psychology perspective. Development across the lifespan is grounded in biocultural co-constructivism. That is, the reciprocal influences of the individual and environment produce change in the individual. Existing theories and models of adaptive development attempt to explain how developmental resources are allocated across the lifespan. These included the Meta- theory of Selective Optimisation with Compensation, Dual Process Model of Self Regulation, and Developmental Regulation via Optimisation and Primary and Secondary Control. These models were integrated to create the Model of Adaptive Development for Work Related Learning. The Learning and Development Survey (LDS) was constructed to measure the hypothesised processes of adaptive development for work related learning, which were individual goal selection, individual goal engagement, individual goal disengagement, organisational opportunities (selection and engagement), and organisational constraints. Data collection was undertaken in two phases: the pilot study and the main study. The objective of the pilot study was to test the LDS on a target population of 112 employees from a local government organisation. Exploratory factor analysis reduced the pilot version of the survey to 38 items encompassing eight constructs which covered the processes of the model of adaptive development for work related learning. In the main study, the Revised Learning and Development Survey (R-LDS) was administered to another group of 137 employees from the local government organisation, as well as 110 employees from a private healthcare organisation. The purpose of the main study was to validate the R-LDS on two different groups to provide evidence of stability, and compare survey scores according to age and occupational status to determine construct validity. Findings from the main study indicated that only four constructs of the R-LDS were stable, which were organisational opportunities – selection, individual goal engagement, organisational constraints – disengagement and organisational opportunities – engagement. In addition, MANOVA studies revealed that the demographic variables affected organisational opportunities and constraints in the workplace, although individual goal engagement was not influenced by age. The findings from the pilot and main study partially supported the model of adaptive development for work related learning. Given that only four factors displayed adequate reliability in terms of internal consistency and stability, the findings suggest that individual goal selection and individual goal disengagement are less relevant to work related learning and development. Some recent research which emerged during the course of the current study has suggested that individual goal selection and individual goal disengagement are more relevant when goal achievement is impeded by biological constraints such as ageing. However, correlations between the retained factors support the model of adaptive development for work related learning, and represent the role of biocultural co-constructivism in development. Individual goal engagement was positively correlated with both opportunity factors (selection and engagement), while organisational constraints – disengagement was negatively correlated with organisational opportunities – selection. Demographic findings indicated that higher occupational status was associated with more opportunities for development. Age was associated with fewer opportunities or greater constraints for development, especially for lower status workers.

The applicability of biased estimation in model and model order selection

Biased estimation has the advantage of reducing the mean squared error (MSE) of an estimator. The question of interest is how biased estimation affects model selection. In this paper, we introduce biased estimation to a range of model selection criteria. Specifically, we analyze the performance of the minimum description length (MDL) criterion based on biased and unbiased estimation and compare it against modern model selection criteria such as Kay's conditional model order estimator (CME), the bootstrap and the more recently proposed hook-and-loop resampling based model selection. The advantages and limitations of the considered techniques are discussed. The results indicate that, in some cases, biased estimators can slightly improve the selection of the correct model. We also give an example for which the CME with an unbiased estimator fails, but could regain its power when a biased estimator is used.

Young children's early modelling with data

An educational priority of many nations is to enhance mathematical learning in early childhood. One area in need of special attention is that of statistics. This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling activities. Such modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (i.e., identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. Results are reported from the first year of a three-year longitudinal study in which three classes of first-grade children and their teachers engaged in activities that required the creation of data models. The theme of “Looking after our Environment,” a component of the children’s science curriculum at the time, provided the context for the activities. Findings focus on how the children dealt with given complex attributes and how they generated their own attributes in classifying broad data sets, and the nature of the models the children created in organising, structuring, and representing their data.

The educational affordances of generative media in arts education

Network Jamming systems provide real-time collaborative media performance experiences for novice or inexperienced users. In this paper we will outline the theoretical and developmental drivers for our Network Jamming software, called jam2jam. jam2jam employs generative algorithmic techniques with particular implications for accessibility and learning. We will describe how theories of engagement have directed the design and development of jam2jam and show how iterative testing cycles in numerous international sites have informed the evolution of the system and its educational potential. Generative media systems present an opportunity for users to leverage computational systems to make sense of complex media forms through interactive and collaborative experiences. Generative music and art are a relatively new phenomenon that use procedural invention as a creative technique to produce music and visual media. These kinds of systems present a range of affordances that can facilitate new kinds of relationships with music and media performance and production. Early systems have demonstrated the potential to provide access to collaborative ensemble experiences to users with little formal musical or artistic expertise.This presentation examines the educational affordances of these systems evidenced by field data drawn from the Network Jamming Project. These generative performance systems enable access to a unique kind of music/media’ ensemble performance with very little musical/ media knowledge or skill and they further offer the possibility of unique interactive relationships with artists and creative knowledge through collaborative performance. Through the process of observing, documenting and analysing young people interacting with the generative media software jam2jam a theory of meaningful engagement has emerged from the need to describe and codify how users experience creative engagement with music/media performance and the locations of meaning. In this research we observed that the musical metaphors and practices of ‘ensemble’ or collaborative performance and improvisation as a creative process for experienced musicians can be made available to novice users. The relational meanings of these musical practices afford access to high level personal, social and cultural experiences. Within the creative process of collaborative improvisation lie a series of modes of creative engagement that move from appreciation through exploration, selection, direction toward embodiment. The expressive sounds and visions made in real-time by improvisers collaborating are immediate and compelling. Generative media systems let novices access these experiences with simple interfaces that allow them to make highly professional and expressive sonic and visual content simply by using gestures and being attentive and perceptive to their collaborators. These kinds of experiences present the potential for highly complex expressive interactions with sound and media as a performance. Evidence that has emerged from this research suggest that collaborative performance with generative media is transformative and meaningful. In this presentation we draw out these ideas around an emerging theory of meaningful engagement that has evolved from the development of network jamming software. Primarily we focus on demonstrating how these experiences might lead to understandings that may be of educational and social benefit.

Identification of alcohol involvement in injury-related hospitalisations using routine data compared to medical record review

Objective: To quantify the extent to which alcohol related injuries are adequately identified in hospitalisation data using ICD-10-AM codes indicative of alcohol involvement. Method: A random sample of 4373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across 4 states in Australia. From this sample, cases were identified as involving alcohol if they contained an ICD-10-AM diagnosis or external cause code referring to alcohol, or if the text description extracted from the medical records mentioned alcohol involvement. Results: Overall, identification of alcohol involvement using ICD codes detected 38% of the alcohol-related sample, whilst almost 94% of alcohol-related cases were identified through a search of the text extracted from the medical records. The resultant estimate of alcohol involvement in injury-related hospitalisations in this sample was 10%. Emergency department records were the most likely to identify whether the injury was alcohol-related with almost three-quarters of alcohol-related cases mentioning alcohol in the text abstracted from these records. Conclusions and Implications: The current best estimates of the frequency of hospital admissions where alcohol is involved prior to the injury underestimate the burden by around 62%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine administrative data sources for identification of alcohol-related injuries.

Sources of coding discrepancies in injury morbidity data: Implications for injury surveillance

Objective: To examine the sources of coding discrepancy for injury morbidity data and explore the implications of these sources for injury surveillance.-------- Method: An on-site medical record review and recoding study was conducted for 4373 injury-related hospital admissions across Australia. Codes from the original dataset were compared to the recoded data to explore the reliability of coded data aand sources of discrepancy.---------- Results: The most common reason for differences in coding overall was assigning the case to a different external cause category with 8.5% assigned to a different category. Differences in the specificity of codes assigned within a category accounted for 7.8% of coder difference. Differences in intent assignment accounted for 3.7% of the differences in code assignment.---------- Conclusions: In the situation where 8 percent of cases are misclassified by major category, the setting of injury targets on the basis of extent of burden is a somewhat blunt instrument Monitoring the effect of prevention programs aimed at reducing risk factors is not possible in datasets with this level of misclassification error in injury cause subcategories. Future research is needed to build the evidence base around the quality and utility of the ICD classification system and application of use of this for injury surveillance in the hospital environment.

How can we exploit mobile data to customise learning based on a student’s environmental surroundings?

User-Based intelligent systems are already commonplace in a student’s online digital life. Each time they browse, search, buy, join, comment, play, travel, upload, download, a system collects, analyses and processes data in an effort to customise content and further improve services. This panel session will explore how intelligent systems, particularly those that gather data from mobile devices, can offer new possibilities to assist in the delivery of customised, personal and engaging learning experiences. The value of intelligent systems for education lies in their ability to formulate authentic and complex learner profiles that bring together and systematically integrate a student’s personal world with a formal curriculum framework. As we well know, a mobile device can collect data relating to a student’s interests (gathered from search history, applications and communications), location, surroundings and proximity to others (GPS, Bluetooth). However, what has been less explored is the opportunity for a mobile device to map the movements and activities of a student from moment to moment and over time. This longitudinal data provides a holistic profile of a student, their state and surroundings. Analysing this data may allow us to identify patterns that reveal a student’s learning processes; when and where they work best and for how long. Through revealing a student’s state and surroundings outside of schools hour, this longitudinal data may also highlight opportunities to transform a student’s everyday world into an inventory for learning, punctuating their surroundings with learning recommendations. This would in turn lead to new ways to acknowledge and validate and foster informal learning, making it legitimate within a formal curriculum.

Students’ conceptual knowledge about workplace pedagogies and applications to learning in the workplace

The development of effective workplace pedagogies is integral to work-integrated and work-based learning. The workplace pedagogies that facilitate and support learning include: activities in which individuals engage such as daily work practices, questioning; observing, and listening; interactions with more experienced workers through coaching and modelling; and referencing documented procedures. Each of these dimensions is significant in enhancing processes of workplace learning. Learning can be optimised when these pedagogies are appropriately embedded in the context of and process of participating in normal work activities. Yet learners need to understand the nature of these pedagogies, and how and for what purposes to use these to achieve a range of learning outcomes. This is because it is the worker-learners who play the key roles in the process and outcomes of learning through work. A pilot study was conducted on students’ conceptions of how each of these dimensions of workplace pedagogy help their learning, by providing examples of learning from these sources; and stating their preferences for learning in the workplace. A sample of seventeen students, enrolled in the second year of a Diploma in Nursing course at a Technical and Further Education institution, participated in a survey intended to capture these conceptions and the importance attached to each of them. The findings indicate that these students have basic understanding of how each of seven workplace pedagogic practices can contribute to their learning. They reported relying mostly on daily practices, observing and listening to others, modelling, coaching, and other workers. Their selection of these contributions emphasise significant opportunities for guided learning by others, yet suggest fewer student-initiated interactions, less intensity in interactions, and likelihood that learning is more passive. The data also suggests that these students rely mostly on using academic learning skill, and limited workplace learning skills. It is proposed, therefore, that the knowledge and understandings about workplace learning and pedagogies might be best embedded in the full curriculum and not become add-on shortly before students go on work placement. This approach will allow students to appreciate the significance and use of workplace pedagogies for learning.

Theoretical investigation of mechanisms of formation and interaction of nanoparticles

In this thesis an investigation into theoretical models for formation and interaction of nanoparticles is presented. The work presented includes a literature review of current models followed by a series of five chapters of original research. This thesis has been submitted in partial fulfilment of the requirements for the degree of doctor of philosophy by publication and therefore each of the five chapters consist of a peer-reviewed journal article. The thesis is then concluded with a discussion of what has been achieved during the PhD candidature, the potential applications for this research and ways in which the research could be extended in the future. In this thesis we explore stochastic models pertaining to the interaction and evolution mechanisms of nanoparticles. In particular, we explore in depth the stochastic evaporation of molecules due to thermal activation and its ultimate effect on nanoparticles sizes and concentrations. Secondly, we analyse the thermal vibrations of nanoparticles suspended in a fluid and subject to standing oscillating drag forces (as would occur in a standing sound wave) and finally on lattice surfaces in the presence of high heat gradients. We have described in this thesis a number of new models for the description of multicompartment networks joined by a multiple, stochastically evaporating, links. The primary motivation for this work is in the description of thermal fragmentation in which multiple molecules holding parts of a carbonaceous nanoparticle may evaporate. Ultimately, these models predict the rate at which the network or aggregate fragments into smaller networks/aggregates and with what aggregate size distribution. The models are highly analytic and describe the fragmentation of a link holding multiple bonds using Markov processes that best describe different physical situations and these processes have been analysed using a number of mathematical methods. The fragmentation of the network/aggregate is then predicted using combinatorial arguments. Whilst there is some scepticism in the scientific community pertaining to the proposed mechanism of thermal fragmentation,we have presented compelling evidence in this thesis supporting the currently proposed mechanism and shown that our models can accurately match experimental results. This was achieved using a realistic simulation of the fragmentation of the fractal carbonaceous aggregate structure using our models. Furthermore, in this thesis a method of manipulation using acoustic standing waves is investigated. In our investigation we analysed the effect of frequency and particle size on the ability for the particle to be manipulated by means of a standing acoustic wave. In our results, we report the existence of a critical frequency for a particular particle size. This frequency is inversely proportional to the Stokes time of the particle in the fluid. We also find that for large frequencies the subtle Brownian motion of even larger particles plays a significant role in the efficacy of the manipulation. This is due to the decreasing size of the boundary layer between acoustic nodes. Our model utilises a multiple time scale approach to calculating the long term effects of the standing acoustic field on the particles that are interacting with the sound. These effects are then combined with the effects of Brownian motion in order to obtain a complete mathematical description of the particle dynamics in such acoustic fields. Finally, in this thesis, we develop a numerical routine for the description of "thermal tweezers". Currently, the technique of thermal tweezers is predominantly theoretical however there has been a handful of successful experiments which demonstrate the effect it practise. Thermal tweezers is the name given to the way in which particles can be easily manipulated on a lattice surface by careful selection of a heat distribution over the surface. Typically, the theoretical simulations of the effect can be rather time consuming with supercomputer facilities processing data over days or even weeks. Our alternative numerical method for the simulation of particle distributions pertaining to the thermal tweezers effect use the Fokker-Planck equation to derive a quick numerical method for the calculation of the effective diffusion constant as a result of the lattice and the temperature. We then use this diffusion constant and solve the diffusion equation numerically using the finite volume method. This saves the algorithm from calculating many individual particle trajectories since it is describes the flow of the probability distribution of particles in a continuous manner. The alternative method that is outlined in this thesis can produce a larger quantity of accurate results on a household PC in a matter of hours which is much better than was previously achieveable.

Preparation of future weather data to study the impact of climate change on buildings

The dynamic interaction between building systems and external climate is extremely complex, involving a large number of difficult-to-predict variables. In order to study the impact of climate change on the built environment, the use of building simulation techniques together with forecast weather data are often necessary. Since most of building simulation programs require hourly meteorological input data for their thermal comfort and energy evaluation, the provision of suitable weather data becomes critical. In this paper, the methods used to prepare future weather data for the study of the impact of climate change are reviewed. The advantages and disadvantages of each method are discussed. The inherent relationship between these methods is also illustrated. Based on these discussions and the analysis of Australian historic climatic data, an effective framework and procedure to generate future hourly weather data is presented. It is shown that this method is not only able to deal with different levels of available information regarding the climate change, but also can retain the key characters of a “typical” year weather data for a desired period.