A multi-train movement simulator with moving blocking signalling

Abstract Being as a relatively new approach of signalling, moving-block scheme significantly increases line capacity, especially on congested railways. This paper describes a simulation system for multi-train operation under moving-block signalling scheme. The simulator can be used to calculate minimum headways and safety characteristics under pre-set timetables or headways and different geographic and traction conditions. Advanced software techniques are adopted to support the flexibility within the simulator so that it is a general-purpose computer-aided design tool to evaluate the performance of moving block signalling.

A 3D visualisation model applied to a thick, multi-layered alluvial groundwater system under stress : Condamine Valley, QLD

The upper Condamine River in southern Queensland has formed extensive alluvial deposits which have been used for irrigation of cotton crops for over 40 years. Due to excessive use and long term drought conditions these groundwater resources are under substantial threat. This condition is now recognised by all stakeholders, and Qld Department of Environment and Resource Management (DERM) are currently undertaking a water planning process for the Central Condamine Alluvium with water users and other stakeholders. DERM aims to effectively demonstrate the character of the groundwater system and its current status, and notably the continued long-term drawdown of the watertable. It was agreed that 3D visualisation was an ideal tool to achieve this. The Groundwater Visualisation System (GVS) developed at QUT was utilised and the visualisation model developed in conjunction with DERM to achieve a planning-management tool for this particular application

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Asset renewal decision modelling with application to the water utility industry

Reliable infrastructure assets impact significantly on quality of life and provide a stable foundation for economic growth and competitiveness. Decisions about the way assets are managed are of utmost importance in achieving this. Timely renewal of infrastructure assets supports reliability and maximum utilisation of infrastructure and enables business and community to grow and prosper. This research initially examined a framework for asset management decisions and then focused on asset renewal optimisation and renewal engineering optimisation in depth. This study had four primary objectives. The first was to develop a new Asset Management Decision Framework (AMDF) for identifying and classifying asset management decisions. The AMDF was developed by applying multi-criteria decision theory, classical management theory and life cycle management. The AMDF is an original and innovative contribution to asset management in that: · it is the first framework to provide guidance for developing asset management decision criteria based on fundamental business objectives; · it is the first framework to provide a decision context identification and analysis process for asset management decisions; and · it is the only comprehensive listing of asset management decision types developed from first principles. The second objective of this research was to develop a novel multi-attribute Asset Renewal Decision Model (ARDM) that takes account of financial, customer service, health and safety, environmental and socio-economic objectives. The unique feature of this ARDM is that it is the only model to optimise timing of asset renewal with respect to fundamental business objectives. The third objective of this research was to develop a novel Renewal Engineering Decision Model (REDM) that uses multiple criteria to determine the optimal timing for renewal engineering. The unique features of this model are that: · it is a novel extension to existing real options valuation models in that it uses overall utility rather than present value of cash flows to model engineering value; and · it is the only REDM that optimises timing of renewal engineering with respect to fundamental business objectives; The final objective was to develop and validate an Asset Renewal Engineering Philosophy (AREP) consisting of three principles of asset renewal engineering. The principles were validated using a novel application of real options theory. The AREP is the only renewal engineering philosophy in existence. The original contributions of this research are expected to enrich the body of knowledge in asset management through effectively addressing the need for an asset management decision framework, asset renewal and renewal engineering optimisation based on fundamental business objectives and a novel renewal engineering philosophy.

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modelling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modelling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modelling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.

Probabilistic subgroup identification using Bayesian finite mixture modelling : a case study in Parkinson’s disease phenotype identification

This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).

Deterministic diffraction loss modelling for novel broadband communication in rural environments

This paper presents a deterministic modelling approach to predict diffraction loss for an innovative Multi-User-Single-Antenna (MUSA) MIMO technology, proposed for rural Australian environments. In order to calculate diffraction loss, six receivers have been considered around an access point in a selected rural environment. Generated terrain profiles for six receivers are presented in this paper. Simulation results using classical diffraction models and diffraction theory are also presented by accounting the rural Australian terrain data. Results show that in an area of 900 m by 900 m surrounding the receivers, path loss due to diffraction can range between 5 dB and 35 dB. Diffraction loss maps can contribute to determine the optimal location for receivers of MUSA-MIMO systems in rural areas.

A prototype augmented reality collaborative process modelling tool

Identifying, modelling and documenting business processes usually requires the collaboration of many stakeholders that may be spread across companies in inter-organizational business settings. While there are many process modelling tools available, the support they provide for remote collaboration is still limited. This demonstration showcases a novel prototype application that implements collaborative virtual environment and augmented reality technologies to improve remote collaborative process modelling, with an aim to assisting common collaboration tasks by providing an increased sense of immersion in an intuitive shared work and task space. Our tool is easily deployed using open source software, and commodity hardware, and is expected to assist with saving money on travel costs for large scale process modelling projects covering national and international centres within an enterprise.

Antiretroviral therapy (ART) adherence among people living with HIV/AIDS (PLHIV) in the north of Vietnam : a multi-method approach

The antiretroviral therapy (ART) program for People Living with HIV/AIDS (PLHIV) in Vietnam has been scaled up rapidly in recent years (from 50 clients in 2003 to almost 38,000 in 2009). ART success is highly dependent on the ability of the patients to fully adhere to the prescribed treatment regimen. Despite the remarkable extension of ART programs in Vietnam, HIV/AIDS program managers still have little reliable data on levels of ART adherence and factors that might promote or reduce adherence. Several previous studies in Vietnam estimated extremely high levels of ART adherence among their samples, although there are reasons to question the veracity of the conclusion that adherence is nearly perfect. Further, no study has quantitatively assessed the factors influencing ART adherence. In order to reduce these gaps, this study was designed to include several phases and used a multi-method approach to examine levels of ART non-adherence and its relationship to a range of demographic, clinical, social and psychological factors. The study began with an exploratory qualitative phase employing four focus group discussions and 30 in-depth interviews with PLHIV, peer educators, carers and health care providers (HCPs). Survey interviews were completed with 615 PLHIV in five rural and urban out-patient clinics in northern Vietnam using an Audio Computer Assisted Self-Interview (ACASI) and clinical records extraction. The survey instrument was carefully developed through a systematic procedure to ensure its reliability and validity. Cultural appropriateness was considered in the design and implementation of both the qualitative study and the cross sectional survey. The qualitative study uncovered several contrary perceptions between health care providers and HIV/AIDS patients regarding the true levels of ART adherence. Health care providers often stated that most of their patients closely adhered to their regimens, while PLHIV and their peers reported that “it is not easy” to do so. The quantitative survey findings supported the PLHIV and their peers’ point of view in the qualitative study, because non-adherence to ART was relatively common among the study sample. Using the ACASI technique, the estimated prevalence of onemonth non-adherence measured by the Visual Analogue Scale (VAS) was 24.9% and the prevalence of four-day not-on-time-adherence using the modified Adult AIDS Clinical Trials Group (AACTG) instrument was 29%. Observed agreement between the two measures was 84% and kappa coefficient was 0.60 (SE=0.04 and p<0.0001). The good agreement between the two measures in the current study is consistent with those found in previous research and provides evidence of cross-validation of the estimated adherence levels. The qualitative study was also valuable in suggesting important variables for the survey conceptual framework and instrument development. The survey confirmed significant correlations between two measures of ART adherence (i.e. dose adherence and time adherence) and many factors identified in the qualitative study, but failed to find evidence of significant correlations of some other factors and ART adherence. Non-adherence to ART was significantly associated with untreated depression, heavy alcohol use, illicit drug use, experiences with medication side-effects, chance health locus of control, low quality of information from HCPs, low satisfaction with received support and poor social connectedness. No multivariate association was observed between ART adherence and age, gender, education, duration of ART, the use of adherence aids, disclosure of ART, patients’ ability to initiate communication with HCPs or distance between clinic and patients’ residence. This is the largest study yet reported in Asia to examine non-adherence to ART and its possible determinants. The evidence strongly supports recent calls from other developing nations for HIV/AIDS services to provide screening, counseling and treatment for patients with depressive symptoms, heavy use of alcohol and substance use. Counseling should also address fatalistic beliefs about chance or luck determining health outcomes. The data suggest that adherence could be enhanced by regularly providing information on ART and assisting patients to maintain social connectedness with their family and the community. This study highlights the benefits of using a multi-method approach in examining complex barriers and facilitators of medication adherence. It also demonstrated the utility of the ACASI interview method to enhance open disclosure by people living with HIV/AIDS and thus, increase the veracity of self-reported data.

A Krylov-based finite state projection algorithm for solving the chemical master equation arising in the discrete modelling of biological systems

Biochemical reactions underlying genetic regulation are often modelled as a continuous-time, discrete-state, Markov process, and the evolution of the associated probability density is described by the so-called chemical master equation (CME). However the CME is typically difficult to solve, since the state-space involved can be very large or even countably infinite. Recently a finite state projection method (FSP) that truncates the state-space was suggested and shown to be effective in an example of a model of the Pap-pili epigenetic switch. However in this example, both the model and the final time at which the solution was computed, were relatively small. Presented here is a Krylov FSP algorithm based on a combination of state-space truncation and inexact matrix-vector product routines. This allows larger-scale models to be studied and solutions for larger final times to be computed in a realistic execution time. Additionally the new method computes the solution at intermediate times at virtually no extra cost, since it is derived from Krylov-type methods for computing matrix exponentials. For the purpose of comparison the new algorithm is applied to the model of the Pap-pili epigenetic switch, where the original FSP was first demonstrated. Also the method is applied to a more sophisticated model of regulated transcription. Numerical results indicate that the new approach is significantly faster and extendable to larger biological models.

Parallel implementation of stochastic simulation for large scale cellular processes

Experimental and theoretical studies have shown the importance of stochastic processes in genetic regulatory networks and cellular processes. Cellular networks and genetic circuits often involve small numbers of key proteins such as transcriptional factors and signaling proteins. In recent years stochastic models have been used successfully for studying noise in biological pathways, and stochastic modelling of biological systems has become a very important research field in computational biology. One of the challenge problems in this field is the reduction of the huge computing time in stochastic simulations. Based on the system of the mitogen-activated protein kinase cascade that is activated by epidermal growth factor, this work give a parallel implementation by using OpenMP and parallelism across the simulation. Special attention is paid to the independence of the generated random numbers in parallel computing, that is a key criterion for the success of stochastic simulations. Numerical results indicate that parallel computers can be used as an efficient tool for simulating the dynamics of large-scale genetic regulatory networks and cellular processes

Creating new narratives through shared time and space : the performer/audience connection in multi-site dance events

Site-specific performance provides choices in audience experience via degrees of scale, proximity, levels of immersion and viewing perspectives. Beyond these choices, multi-site promenade events also form a connected audience/performer relationship in which moving together in time and space can produce a shared narrative and aesthetic sensibility of collective, yet individuated and shifting meanings. This paper interrogates this notion through audience/performer experiences in two separate multi-site, dance-led events. here/there/then/now occurred in four intimate sites within the Brisbane Powerhouse, providing a theatricalised platform for audiences to create linked narratives through open-ended and fragmented intertextuality. Accented Body, based on the concept of “the body as site and in site” and notions of connectivity, provided a more expansive platform for a similar, but heightened, shared engagement. Audiences traversed 6 outdoor and 2 indoor Brisbane sites moving to varying levels of a large complex. Eleven, predominantly interactive, screens provided links to other sites as well as to distributed presences in Seoul and London. The differentiation in scale and travel time between sites deepened the immersive experiences of audiences who reported transformative engagements with both site and architecture, accompanied by a sense of extended and yet quickened time.

Value co-creation in social marketing wellness services

Customer perceived value is concerned with the experiences of consumers when using a service and is often referred to in the context of service provision or on the basis of service quality (Auh, et al., 2007; Chang, 2008; Jackson, 2007; Laukkanen, 2007; Padgett & Mulvey, 2007; Shamdasani, Mukherjee & Malhotra, 2008). Understanding customer perceived value has benefits for social marketing and allows scholars and practitioners alike to identify why consumers engage in positive social behaviours through the use of services. Understanding consumers’ use of wellness services in particular is important, because the use of wellness services demonstrates the fulfilment of social marketing aims; performing pro-active, positive social behaviours that are of benefit to the individual and to society (Andreasen, 1994). As consumers typically act out of self-interest (Rothschild, 1999), this research posits that a value proposition must be made to consumers in order to encourage behavioural change. Thus, this research seeks to identify how value is created for consumers of wellness services in social marketing. This results in the overall research question of this research: How is value created in social marketing wellness services? A traditional method towards understanding value has been the adoption of an economic approach, which considers the utility gained and where value is a direct outcome of a cost-benefit analysis (Payne & Holt, 1999). However, there has since been a shift towards the adoption of an experiential approach in understanding value. This experiential approach considers the consumption experience of the consumer which extends beyond the service exchange and includes pre- and post-consumption stages (Russell-Bennett, Previte & Zainuddin, 2009). As such, this research uses an experiential approach to identify the value that exists in social marketing wellness services. Four dimensions of value have been commonly conceptualised and identified in the commercial marketing literature; functional, emotional, social, and altruistic value (Holbrook, 1994; Sheth, Newman & Gross, 1991; Sweeney & Soutar, 2001). It is not known if these value dimensions also exist in social marketing. In addition, sources of value said to influence value dimensions have been conceptualised in the literature. Sources of value such as information, interaction, environment, service, customer co-creation, and social mandate have been conceptually identified both in the commercial and social marketing literature (Russell-Bennet, Previte & Zainuddin, 2009; Smith & Colgate, 2007). However, it is not clear which sources of value contribute to the creation of value for users of wellness services. Thus, this research seeks to explore these relationships. This research was conducted using a wellness service context, specifically breast cancer screening services. The primary target consumer of these services is women aged 50 to 69 years old (inclusive) who have never been diagnosed with breast cancer. It is recommended that women in this target group have a breast screen every 2 years in order to achieve the most effective medical outcomes from screening. A two-study mixed method approach was utilised. Study 1 was a qualitative exploratory study that analysed individual-depth interviews with 25 information-rich respondents. The interviews were transcribed verbatim and analysed using NVivo 8 software. The qualitative results provided evidence of the existence of the four value dimensions in social marketing. The results also allowed for the development of a typology of experiential value by synthesising current understanding of the value dimensions, with the activity aspects of experiential value identified by Holbrook (1994) and Mathwick, Malhotra and Rigdon (2001). The qualitative results also provided evidence for the existence of sources of value in social marketing, namely information, interaction, environment and consumer participation. In particular, a categorisation of sources of value was developed as a result of the findings from Study 1, which identify organisational, consumer, and third party sources of value. A proposed model of value co-creation and a set of hypotheses were developed based on the results of Study 1 for further testing in Study 2. Study 2 was a large-scale quantitative confirmatory study that sought to test the proposed model of value co-creation and the hypotheses developed. An online-survey was administered Australia-wide to women in the target audience. A response rate of 20.1% was achieved, resulting in a final sample of 797 useable responses after removing ineligible respondents. Reliability and validity analyses were conducted on the data, followed by Exploratory Factor Analysis (EFA) in PASW18, followed by Confirmatory Factor Analysis (CFA) in AMOS18. Following the preliminary analyses, the data was subject to Structural Equation Modelling (SEM) in AMOS18 to test the path relationships hypothesised in the proposed model of value creation. The SEM output revealed that all hypotheses were supported, with the exception of one relationship which was non-significant. In addition, post hoc tests revealed seven further significant non-hypothesised relationships in the model. The quantitative results show that organisational sources of value as well as consumer participation sources of value influence both functional and emotional dimensions of value. The experience of both functional and emotional value in wellness services leads to satisfaction with the experience, followed by behavioural intentions to perform the behaviour and use the service again. One of the significant non-hypothesised relationships revealed that emotional value leads to functional value in wellness services, providing further empirical evidence that emotional value features more prominently than functional value for users of wellness services. This research offers several contributions to theory and practice. Theoretically, this research addresses a gap in the literature by using social marketing theory to provide an alternative method of understanding individual behaviour in a domain that has been predominantly investigated in public health. This research also clarifies the concept of value and offers empirical evidence to show that value is a multi-dimensional construct with separate and distinct dimensions. Empirical evidence for a typology of experiential value, as well as a categorisation of sources of value is also provided. In its practical contributions, this research identifies a framework that is the value creation process and offers health services organisations a diagnostic tool to identify aspects of the service process that facilitate the value creation process.

A multi-level model of leadership in complex project management

Management (or perceived mismanagement) of large-scale, complex projects poses special problems and often results in spectacular failures, cost overruns, time blowouts and stakeholder dissatisfaction. While traditional project management responds with increasingly administrative constraints, we argue that leaders of such projects also need to display adaptive and enabling behaviours to foster adaptive processes, such as opportunity recognition, which requires an interaction of cognitive and affective processes of individual, project, and team leader attributes and behaviours. At the core of this model we propose is an interaction of cognitive flexibility, affect and emotional intelligence. The result of this interaction is enhanced leader opportunity recognition that, in turn, facilitates multilevel outcomes.

Bayesian mixtures for modelling complex medical data : a case study in Parkinson’s disease

Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.