Latent variable models in statistical genetics

Understanding the complexities that are involved in the genetics of multifactorial diseases is still a monumental task. In addition to environmental factors that can influence the risk of disease, there is also a number of other complicating factors. Genetic variants associated with age of disease onset may be different from those variants associated with overall risk of disease, and variants may be located in positions that are not consistent with the traditional protein coding genetic paradigm. Latent Variable Models are well suited for the analysis of genetic data. A latent variable is one that we do not directly observe, but which is believed to exist or is included for computational or analytic convenience in a model. This thesis presents a mixture of methodological developments utilising latent variables, and results from case studies in genetic epidemiology and comparative genomics. Epidemiological studies have identified a number of environmental risk factors for appendicitis, but the disease aetiology of this oft thought useless vestige remains largely a mystery. The effects of smoking on other gastrointestinal disorders are well documented, and in light of this, the thesis investigates the association between smoking and appendicitis through the use of latent variables. By utilising data from a large Australian twin study questionnaire as both cohort and case-control, evidence is found for the association between tobacco smoking and appendicitis. Twin and family studies have also found evidence for the role of heredity in the risk of appendicitis. Results from previous studies are extended here to estimate the heritability of age-at-onset and account for the eect of smoking. This thesis presents a novel approach for performing a genome-wide variance components linkage analysis on transformed residuals from a Cox regression. This method finds evidence for a dierent subset of genes responsible for variation in age at onset than those associated with overall risk of appendicitis. Motivated by increasing evidence of functional activity in regions of the genome once thought of as evolutionary graveyards, this thesis develops a generalisation to the Bayesian multiple changepoint model on aligned DNA sequences for more than two species. This sensitive technique is applied to evaluating the distributions of evolutionary rates, with the finding that they are much more complex than previously apparent. We show strong evidence for at least 9 well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least 7 classes in an alignment of four mammals, including human. A pattern of enrichment and depletion of genic regions in the profiled segments suggests they are functionally significant, and most likely consist of various functional classes. Furthermore, a method of incorporating alignment characteristics representative of function such as GC content and type of mutation into the segmentation model is developed within this thesis. Evidence of fine-structured segmental variation is presented.

Efficient and accurate retrieval of business process models through indexing

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective than developing them from scratch. As process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. Experiments are conducted to demonstrate that our proposal achieves a significant reduction in query evaluation time.

Investigation of MEMS inertial sensors and aircraft dynamic models in global positioning system integrity monitoring for approaches with vertical guidance

An Approach with Vertical Guidance (APV) is an instrument approach procedure which provides horizontal and vertical guidance to a pilot on approach to landing in reduced visibility conditions. APV approaches can greatly reduce the safety risk to general aviation by improving the pilot’s situational awareness. In particular the incidence of Controlled Flight Into Terrain (CFIT) which has occurred in a number of fatal air crashes in general aviation over the past decade in Australia, can be reduced. APV approaches can also improve general aviation operations. If implemented at Australian airports, APV approach procedures are expected to bring a cost saving of millions of dollars to the economy due to fewer missed approaches, diversions and an increased safety benefit. The provision of accurate horizontal and vertical guidance is achievable using the Global Positioning System (GPS). Because aviation is a safety of life application, an aviation-certified GPS receiver must have integrity monitoring or augmentation to ensure that its navigation solution can be trusted. However, the difficulty with the current GPS satellite constellation alone meeting APV integrity requirements, the susceptibility of GPS to jamming or interference and the potential shortcomings of proposed augmentation solutions for Australia such as the Ground-based Regional Augmentation System (GRAS) justifies the investigation of Aircraft Based Augmentation Systems (ABAS) as an alternative integrity solution for general aviation. ABAS augments GPS with other sensors at the aircraft to help it meet the integrity requirements. Typical ABAS designs assume high quality inertial sensors to provide an accurate reference trajectory for Kalman filters. Unfortunately high-quality inertial sensors are too expensive for general aviation. In contrast to these approaches the purpose of this research is to investigate fusing GPS with lower-cost Micro-Electro-Mechanical System (MEMS) Inertial Measurement Units (IMU) and a mathematical model of aircraft dynamics, referred to as an Aircraft Dynamic Model (ADM) in this thesis. Using a model of aircraft dynamics in navigation systems has been studied before in the available literature and shown to be useful particularly for aiding inertial coasting or attitude determination. In contrast to these applications, this thesis investigates its use in ABAS. This thesis presents an ABAS architecture concept which makes use of a MEMS IMU and ADM, named the General Aviation GPS Integrity System (GAGIS) for convenience. GAGIS includes a GPS, MEMS IMU, ADM, a bank of Extended Kalman Filters (EKF) and uses the Normalized Solution Separation (NSS) method for fault detection. The GPS, IMU and ADM information is fused together in a tightly-coupled configuration, with frequent GPS updates applied to correct the IMU and ADM. The use of both IMU and ADM allows for a number of different possible configurations. Three are investigated in this thesis; a GPS-IMU EKF, a GPS-ADM EKF and a GPS-IMU-ADM EKF. The integrity monitoring performance of the GPS-IMU EKF, GPS-ADM EKF and GPS-IMU-ADM EKF architectures are compared against each other and against a stand-alone GPS architecture in a series of computer simulation tests of an APV approach. Typical GPS, IMU, ADM and environmental errors are simulated. The simulation results show the GPS integrity monitoring performance achievable by augmenting GPS with an ADM and low-cost IMU for a general aviation aircraft on an APV approach. A contribution to research is made in determining whether a low-cost IMU or ADM can provide improved integrity monitoring performance over stand-alone GPS. It is found that a reduction of approximately 50% in protection levels is possible using the GPS-IMU EKF or GPS-ADM EKF as well as faster detection of a slowly growing ramp fault on a GPS pseudorange measurement. A second contribution is made in determining how augmenting GPS with an ADM compares to using a low-cost IMU. By comparing the results for the GPS-ADM EKF against the GPS-IMU EKF it is found that protection levels for the GPS-ADM EKF were only approximately 2% higher. This indicates that the GPS-ADM EKF may potentially replace the GPS-IMU EKF for integrity monitoring should the IMU ever fail. In this way the ADM may contribute to the navigation system robustness and redundancy. To investigate this further, a third contribution is made in determining whether or not the ADM can function as an IMU replacement to improve navigation system redundancy by investigating the case of three IMU accelerometers failing. It is found that the failed IMU measurements may be supplemented by the ADM and adequate integrity monitoring performance achieved. Besides treating the IMU and ADM separately as in the GPS-IMU EKF and GPS-ADM EKF, a fourth contribution is made in investigating the possibility of fusing the IMU and ADM information together to achieve greater performance than either alone. This is investigated using the GPS-IMU-ADM EKF. It is found that the GPS-IMU-ADM EKF can achieve protection levels approximately 3% lower in the horizontal and 6% lower in the vertical than a GPS-IMU EKF. However this small improvement may not justify the complexity of fusing the IMU with an ADM in practical systems. Affordable ABAS in general aviation may enhance existing GPS-only fault detection solutions or help overcome any outages in augmentation systems such as the Ground-based Regional Augmentation System (GRAS). Countries such as Australia which currently do not have an augmentation solution for general aviation could especially benefit from the economic savings and safety benefits of satellite navigation-based APV approaches.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

Customer-oriented deviance (COD) : a conceptualisation, development and validation of a behavioural measure

Frontline employee behaviours are recognised as vital for achieving a competitive advantage for service organisations. The services marketing literature has comprehensively examined ways to improve frontline employee behaviours in service delivery and recovery. However, limited attention has been paid to frontline employee behaviours that favour customers in ways that go against organisational norms or rules. This study examines these behaviours by introducing a behavioural concept of Customer-Oriented Deviance (COD). COD is defined as, “frontline employees exhibiting extra-role behaviours that they perceive to defy existing expectations or prescribed rules of higher authority through service adaptation, communication and use of resources to benefit customers during interpersonal service encounters.” This thesis develops a COD measure and examines the key determinants of these behaviours from a frontline employee perspective. Existing research on similar behaviours that has originated in the positive deviance and pro-social behaviour domains has limitations and is considered inadequate to examine COD in the services context. The absence of a well-developed body of knowledge on non-conforming service behaviours has implications for both theory and practice. The provision of ‘special favours’ increases customer satisfaction but the over-servicing of customers is also counterproductive for the service delivery and costly for the organisation. Despite these implications of non-conforming service behaviours, there is little understanding about the nature of these behaviours and its key drivers. This research builds on inadequacies in prior research on positive deviance, pro-social and pro-customer literature to develop the theoretical foundation of COD. The concept of positive deviance which has predominantly been used to study organisational behaviours is applied within a services marketing setting. Further, it addresses previous limitations in pro-social and pro-customer behavioural literature that has examined limited forms of behaviours with no clear understanding on the nature of these behaviours. Building upon these literature streams, this research adopts a holistic approach towards the conceptualisation of COD. It addresses previous shortcomings in the literature by providing a well bounded definition, developing a psychometrically sound measure of COD and a conceptually well-founded model of COD. The concept of COD was examined across three separate studies and based on the theoretical foundations of role theory and social identity theory. Study 1 was exploratory and based on in-depth interviews using the Critical Incident Technique (CIT). The aim of Study 1 was to understand the nature of COD and qualitatively identify its key drivers. Thematic analysis was conducted to analyse the data and the two potential dimensions of COD behaviours of Deviant Service Adaptation (DSA) and Deviant Service Communication (DSC) were revealed in the analysis. In addition, themes representing the potential influences of COD were broadly classified as individual factors, situational factors, and organisational factors. Study 2 was a scale development procedure that involved the generation and purification of items for the measure based on two student samples working in customer service roles (Pilot sample, N=278; Initial validation sample, N=231). The results for the reliability and Exploratory Factor Analyses (EFA) on the pilot sample suggested the scale had poor psychometric properties. As a result, major revisions were made in terms of item wordings and new items were developed based on the literature to reflect a new dimension, Deviant Use of Resources (DUR). The revised items were tested on the initial validation sample with the EFA analysis suggesting a four-factor structure of COD. The aim of Study 3 was to further purify the COD measure and test for nomological validity based on its theoretical relationships with key antecedents and similar constructs (key correlates). The theoretical model of COD consisting of nine hypotheses was tested on a retail and hospitality sample of frontline employees (Retail N=311; Hospitality N=305) of a market research panel using an online survey. The data was analysed using Structural Equation Modelling (SEM). The results provided support for a re-specified second-order three-factor model of COD which consists of 11 items. Overall, the COD measure was found to be reliable and valid, demonstrating convergent validity, discriminant validity and marginal partial invariance for the factor loadings. The results showed support for nomological validity, although the antecedents had differing impact on COD across samples. Specifically, empathy and perspective-taking, role conflict, and job autonomy significantly influenced COD in the retail sample, whereas empathy and perspective-taking, risk-taking propensity and role conflict were significant predictors in the hospitality sample. In addition, customer orientation-selling orientation, the altruistic dimension of organisational citizenship behaviours, workplace deviance, and social desirability responding were found to correlate with COD. This research makes several contributions to theory. First, the findings of this thesis extend the literature on positive deviance, pro-social and pro-customer behaviours. Second, the research provides an empirically tested model which describes the antecedents of COD. Third, this research contributes by providing a reliable and valid measure of COD. Finally, the research investigates the differential effects of the key antecedents in different service sectors on COD. The research findings also contribute to services marketing practice. Based on the research findings, service practitioners can better understand the phenomenon of COD and utilise the measurement tool to calibrate COD levels within their organisations. Knowledge on the key determinants of COD will help improve recruitment and training programs and drive internal initiatives within the firm.

Virtual Environment Visualisation of Executable Business Process Models

Business Process Modelling is a fast growing field in business and information technology, which uses visual grammars to model and execute the processes within an organisation. However, many analysts present such models in a 2D static and iconic manner that is difficult to understand by many stakeholders. Difficulties in understanding such grammars can impede the improvement of processes within an enterprise due to communication problems. In this chapter we present a novel framework for intuitively visualising animated business process models in interactive Virtual Environments. We also show that virtual environment visualisations can be performed with present 2D business process modelling technology, thus providing a low barrier to entry for business process practitioners. Two case studies are presented from film production and healthcare domains that illustrate the ease with which these visualisations can be created. This approach can be generalised to other executable workflow systems, for any application domain being modelled.

Behavioural biases and information disclosure laws relating to residential property sales : narrowing the gap between existing laws and calls for future reforms

Market failures involving the sale of complex merchandise, such as residential property, financial products and credit, have principally been attributed to information asymmetries. Existing legislative and regulatory responses were developed having regard to consumer protection policies based on traditional economic theories that focus on the notion of the ‘rational consumer’. Governmental responses therefore seek to impose disclosure obligations on sellers of complex goods or products to ensure that consumers have sufficient information upon which to make a decision. Emergent research, based on behavioural economics, challenges traditional ideas and instead focuses on the actual behaviour of consumers. This approach suggests that consumers as a whole do not necessarily benefit from mandatory disclosure because some, if not most, consumers do not pay attention to the disclosed information before they make a decision to purchase. The need for consumer policies to take consumer characteristics and behaviour into account is being increasingly recognised by governments, and most recently in the policy framework suggested by the Australian Productivity Commission

Driver behaviour and decision making at railway level crossings : An exploratory on-road case study

Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

Are organ donation communication decisions reasoned or reactive? A test of the utility of an augmented Theory of Planned Behaviour with the Prototype/Willingness Model

Objectives: To explore whether people's organ donation consent decisions occur via a reasoned and/or social reaction pathway. --------- Design: We examined prospectively students' and community members' decisions to register consent on a donor register and discuss organ donation wishes with family. --------- Method: Participants completed items assessing theory of planned behaviour (TPB; attitude, subjective norm, perceived behavioural control (PBC)), prototype/willingness model (PWM; donor prototype favourability/similarity, past behaviour), and proposed additional influences (moral norm, self-identity, recipient prototypes) for registering (N=339) and discussing (N=315) intentions/willingness. Participants self-reported their registering (N=177) and discussing (N=166) behaviour 1 month later. The utility of the (1) TPB, (2) PWM, (3) augmented TPB with PWM, and (4) augmented TPB with PWM and extensions was tested using structural equation modelling for registering and discussing intentions/willingness, and logistic regression for behaviour. --------- Results: While the TPB proved a more parsimonious model, fit indices suggested that the other proposed models offered viable options, explaining greater variance in communication intentions/willingness. The TPB, augmented TPB with PWM, and extended augmented TPB with PWM best explained registering and discussing decisions. The proposed and revised PWM also proved an adequate fit for discussing decisions. Respondents with stronger intentions (and PBC for registering) had a higher likelihood of registering and discussing. --------- Conclusions: People's decisions to communicate donation wishes may be better explained via a reasoned pathway (especially for registering); however, discussing involves more reactive elements. The role of moral norm, self-identity, and prototypes as influences predicting communication decisions were highlighted also.

Hippocampal models for simultaneous localisation and mapping on an autonomous robot

To navigate successfully in a novel environment a robot needs to be able to Simultaneously Localize And Map (SLAM) its surroundings. The most successful solutions to this problem so far have involved probabilistic algorithms, but there has been much promising work involving systems based on the workings of part of the rodent brain known as the hippocampus. In this paper we present a biologically plausible system called RatSLAM that uses competitive attractor networks to carry out SLAM in a probabilistic manner. The system can effectively perform parameter self-calibration and SLAM in one dimension. Tests in two dimensional environments revealed the inability of the RatSLAM system to maintain multiple pose hypotheses in the face of ambiguous visual input. These results support recent rat experimentation that suggest current competitive attractor models are not a complete solution to the hippocampal modelling problem.

A Helicopter named Dolly : behavioural cloning for autonomous helicopter control

This paper considers the pros and cons of using Behavioural cloning for the development of low-level helicopter automation modules. Over the course of this project several Behavioural cloning approaches have been investigated. The results of the most effective Behavioural cloning approach are then compared to PID modules designed for the same aircraft. The comparison takes into consideration development time, reliability, and control performance. It has been found that Behavioural cloning techniques employing local approximators and a wide state-space coverage during training can produce stabilising control modules in less time than tuning PID controllers. However, performance and reliabity deficits have been found to exist with the Behavioural Cloning, attributable largely to the time variant nature of the dynamics due to the operating environment, and the pilot actions being poor for teaching. The final conclusion drawn here is that tuning PID modules remains superior to behavioural cloning for low-level helicopter automation.

Emotional and behavioural reaction to intrusive thoughts

A self-report measure of the emotional and behavioural reactions to intrusive thoughts was developed. The paper presents data that confirm the stability, reliability and validity of the new 7-item measure. Emotional and behavioural reactions to intrusions emerged as separate factors on the Emotional and Behavioural Reactions to Intrusions Questionnaire (EBRIQ), a finding confirmed by an independent stress study. Test retest reliability over 30-70 days was good. Expected relationships with other constructs were significant. Stronger negative responses to intrusions were associated with lower mindfulness scores and higher ratings of experiential avoidance, thought suppression and intensity and frequency of craving. The EBRIQ will help explore differences in reactions to intrusive thoughts in clinical and non clinical populations, and across different emotional and behavioural states. It will also be useful in assessing the effects of therapeutic approaches such as mindfulness.

Driving performance on monotonous roads

Driving on motorways has largely been reduced to a lane-keeping task with cruise control. Rapidly, drivers are likely to get bored with such a task and take their attention away from the road. This is of concern in terms of road safety – particularly for professional drivers - since inattention has been identified as one of the main contributing factors to road crashes and is estimated to be involved in 20 to 30% of these crashes. Furthermore, drivers are not aware that their vigilance level has decreased and that their driving performance is impaired. Intelligent Transportation System (ITS) intervention can be used as a countermeasure against vigilance decrement. This paper aims to identify a variety of metrics impacted during monotonous driving - ranging from vehicle data to physiological variables - and relate them to two monotonous factors namely the monotony of the road design (straightness) and the monotony of the environment (landscape, signage, traffic). Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). The two monotonous factors are varied (high and low) leading to the use of four different driving scenarios (40 minutes each). We show with Generalised Linear Mixed Models that driver performance decreases faster when the road is monotonous. We also highlight that road monotony impairs a variety of driving performance and vigilance measures, ranging from speed, lateral position of the vehicle to physiological measurements such as heart rate variability, blink frequency and electrodermal activity. This study informs road designers of the importance of having a varied road environment. It also provides a range of metrics that can be used to detect in real-time the impairment of driving performance on monotonous roads. Such knowledge could result in the development of an in-vehicle device warning drivers at early signs of driving performance impairment on monotonous roads.

Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.