Detecting news topics from microblogs using sequential pattern mining

This thesis presents a sequential pattern based model (PMM) to detect news topics from a popular microblogging platform, Twitter. PMM captures key topics and measures their importance using pattern properties and Twitter characteristics. This study shows that PMM outperforms traditional term-based models, and can potentially be implemented as a decision support system. The research contributes to news detection and addresses the challenging issue of extracting information from short and noisy text.

Smart Inter-Phase Switching of Residential Loads in Low Voltage Distribution Feeders

In order to dynamically reduce voltage unbalance along a low voltage distribution feeder, a smart residential load transfer system is discussed. In this scheme, residential loads can be transferred from one phase to another to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch and a controller. The master controller, installed at the transformer, observes the power consumption in each house and will determine which house(s) should be transferred from an initially connected phase to another in order to keep the voltage unbalance minimum. The performance of the smart load transfer scheme is demonstrated by simulations.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.

Visualization of predictive distributions for discrete spatial-temporal log Cox processes approximated with MCMC

An important aspect of decision support systems involves applying sophisticated and flexible statistical models to real datasets and communicating these results to decision makers in interpretable ways. An important class of problem is the modelling of incidence such as fire, disease etc. Models of incidence known as point processes or Cox processes are particularly challenging as they are ‘doubly stochastic’ i.e. obtaining the probability mass function of incidents requires two integrals to be evaluated. Existing approaches to the problem either use simple models that obtain predictions using plug-in point estimates and do not distinguish between Cox processes and density estimation but do use sophisticated 3D visualization for interpretation. Alternatively other work employs sophisticated non-parametric Bayesian Cox process models, but do not use visualization to render interpretable complex spatial temporal forecasts. The contribution here is to fill this gap by inferring predictive distributions of Gaussian-log Cox processes and rendering them using state of the art 3D visualization techniques. This requires performing inference on an approximation of the model on a discretized grid of large scale and adapting an existing spatial-diurnal kernel to the log Gaussian Cox process context.

Towards a smart cancer registry

Aims Pathology notification for a Cancer Registry is regarded as the most valid information for the confirmation of a diagnosis of cancer. In view of the importance of pathology data, an automatic medical text analysis system (Medtex) is being developed to perform electronic Cancer Registry data extraction and coding of important clinical information embedded within pathology reports. Methods The system automatically scans HL7 messages received from a Queensland pathology information system and analyses the reports for terms and concepts relevant to a cancer notification. A multitude of data items for cancer notification such as primary site, histological type, stage, and other synoptic data are classified by the system. The underlying extraction and classification technology is based on SNOMED CT1 2. The Queensland Cancer Registry business rules3 and International Classification of Diseases – Oncology – Version 34 have been incorporated. Results The cancer notification services show that the classification of notifiable reports can be achieved with sensitivities of 98% and specificities of 96%5, while the coding of cancer notification items such as basis of diagnosis, histological type and grade, primary site and laterality can be extracted with an overall accuracy of 80%6. In the case of lung cancer staging, the automated stages produced were accurate enough for the purposes of population level research and indicative staging prior to multi-disciplinary team meetings2 7. Medtex also allows for detailed tumour stream synoptic reporting8. Conclusions Medtex demonstrates how medical free-text processing could enable the automation of some Cancer Registry processes. Over 70% of Cancer Registry coding resources are devoted to information acquisition. The development of a clinical decision support system to unlock information from medical free-text could significantly reduce costs arising from duplicated processes and enable improved decision support, enhancing efficiency and timeliness of cancer information for Cancer Registries.

Creating regional resilience in Australia

This paper explores the impact that extreme weather events can have on communities. Using the Brisbane floods of 2011 to examine the recovery operations, the paper highlights the effectiveness of recovery and rebuilding in already strong and resilient communities. Our research has shown that communities which have a strong sense of identity, as well as organized places to meet, develop resilient networks that come into play in times of crisis. The increasing trend of the fly-in/fly-out (FIFO) or drive-in/drive-out (DIDO) workforce to service regional areas has undermined the resilience of existing communities. The first hint of this occurs with community groups not knowing who their neighbours are. The paper is based on research examining the needs of groups in regional communities with the goal to better equip regional communities with the capacity to respond positively to change (and crisis) through in-novative, evidence-based policies, resilience strategies and tools. Part of this process was to build an evidence-base to address a range of challenges associated with the place-based environments and the sharing of information systems within communities and decision makers. The first part of the paper explores the context in which communities have been required to mobilize in response to crises; the issues that have galvanized a common purpose; and the methods by which these communities shared their knowledge. The second part of the paper examines how communities could plan for and mitigate natural disasters in the future by developing better decision making tools. The paper defines the requirements for information systems that will link data models of built infrastruc-ture with data from the disaster and response plans. These will then form the basis for the use of social media to coordinate activities between official crews and the public to improve response coordination and provide the technology that could reduce the time required to allow communities to resume some semblance of normality.

Developing Co-operating Legal Knowledge Based Systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work supplements rule-based reasoning with case based reasoning and intelligent information retrieval. This research, specifies an approach to the case based retrieval problem which relies heavily on an extended object-oriented / rule-based system architecture that is supplemented with causal background information. Machine learning techniques and a distributed agent architecture are used to help simulate the reasoning process of lawyers. In this paper, we outline our implementation of the hybrid IKBALS II Rule Based Reasoning / Case Based Reasoning system. It makes extensive use of an automated case representation editor and background information.

The IKBALS project: multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.

The once-and-for-all withdrawal of the Liverpool Care Pathway in the UK : what are the implications for Australia?

This Perspective reflects on the withdrawal of the Liverpool Care Pathway in the UK, and its implications for Australia. Integrated care pathways are documents which outline the essential steps of multidisciplinary care in addressing a specific clinical problem. They can be used to introduce best clinical practice, to ensure that the most appropriate management occurs at the most appropriate time and that it is provided by the most appropriate health professional. By providing clear instructions, decision support and a framework for clinician-patient interactions, care pathways guide the systematic provision of best evidence-based care. The Liverpool Care Pathway (LCP) is an example of an integrated care pathway, designed in the 1990s to guide care for people with cancer who are in their last days of life and are expected to die in hospital. This pathway evolved out of a recognised local need to better support non-specialist palliative care providers’ care for patients dying of cancer within their inpatient units. Historically, despite the large number of people in acute care settings whose treatment intent is palliative, dying patients receiving general hospital acute care tended to lack sufficient attention from senior medical staff and nursing staff. The quality of end-of-life care was considered inadequate, therefore much could be learned from the way patients were cared for by palliative care services. The LCP was a strategy developed to improve end-of-life care in cancer patients and was based on the care received by those dying in the palliative care setting.

Priority Threat Management for Pilbara Species of Conservation Significance

This project provides a costed and appraised set of management strategies for mitigating threats to species of conservation significance in the Pilbara IBRA bioregion of Western Australia (hereafter 'the Pilbara'). Conservation significant species are either listed under federal and state legislation, international agreements or considered likely to be threatened in the next 20 years. Here we report on the 17 technically and socially feasible management strategies, which were drawn from the collective experience and knowledge of 49 experts and stakeholders in the ecology and management of the Pilbara region. We determine the relative ecological cost-effectiveness of each strategy, calculated as the expected benefit of management to the persistence of 53 key threatened native fauna and flora species, divided by the expected cost of management. Finally we provide decision support to assist prioritisation of the strategies on the basis of ecological cost-effectiveness.

What are pregnant women told about models of maternity care in Australia? A retrospective study of women's reports

Objective To describe women’s reports of the model of care options General Practitioners (GPs) discussed with them at the first pregnancy consultation and women’s self-reported role in decisionmaking about model of care. Methods Women who had recently given birth responded to survey items about the models of care GPs discussed, their role in final decision-making, and socio-demographic, obstetric history, and early pregnancy characteristics. Results The proportion of women with whom each model of care was discussed varied between 8.2% (for private midwifery care with home birth) and 64.4% (GP shared care). Only 7.7% of women reported that all seven models were discussed. Exclusive discussion about private obstetric care and about all public models was common, and women’s health insurance status was the strongest predictor of the presence of discussions about each model. Most women (82.6%) reported active involvement in final decision-making about model of care. Conclusion Although most women report involvement in maternity model of care decisions, they remain largely uninformed about the breadth of available model of care options. Practical implications Strategies that facilitate women’s access to information on the differentiating features and outcomes for all models of care should be prioritized to better ensure equitable and quality decisions.

Climate variability, climate change and land degradation

Effective response by government and individuals to the risk of land degradation requires an understanding of regional climate variations and the impacts of climate and management on condition and productivity of land and vegetation resources. Analysis of past land degradation and climate variability provides some understanding of vulnerability to current and future climate changes and the information needs for more sustainable management. We describe experience in providing climate risk assessment information for managing for the risk of land degradation in north-eastern Australian arid and semi-arid regions used for extensive grazing. However, we note that information based on historical climate variability, which has been relied on in the past, will now also have to factor in the influence of human-induced climate change. Examples illustrate trends in climate for Australia over the past decade and the impacts on indicators of resource condition. The analysis highlights the benefits of insights into past trends and variability in rainfall and other climate variables based on extended historic databases. This understanding in turn supports more reliable regional climate projections and decision support information for governments and land managers to better manage the risk of land degradation now and in the future.

Developing an evaluation framework for hospital disaster resilience : tertiary hospitals of Shandong Province, China

This thesis provided a definition and conceptual framework for hospital disaster resilience; it used a mixed-method, including an empirical study in tertiary hospitals of Shandong Province in China, to devise an assessment instrument for measuring hospital resilience. The instrument is the first of its type and will allow hospitals to measure their resilience levels. The concept of disaster resilience has gained prominence in the light of the increased impact of various disasters. The notion of resilience encompasses the qualities that enable the organisation or community to resist, respond to, and recover from the impact of disasters. Hospital resilience is essential as it provides 'lifeline' services which minimize disaster impact. This thesis has provided a framework and instrument to evaluate the level of hospital resilience. Such an instrument could be used to better understand hospital resilience, and also as a decision-support tool for its promoting strategies and policies.

Event interval analysis: Why do processes take time?

Through the application of process mining, valuable evidence-based insights can be obtained about business processes in organisations. As a result the field has seen an increased uptake in recent years as evidenced by success stories and increased tool support. However, despite this impact, current performance analysis capabilities remain somewhat limited in the context of information-poor event logs. For example, natural daily and weekly patterns are not considered. In this paper a new framework for analysing event logs is defined which is based on the concept of event gap. The framework allows for a systematic approach to sophisticated performance-related analysis of event logs containing varying degrees of information. The paper formalises a range of event gap types and then presents an implementation as well as an evaluation of the proposed approach.

Development of a dragline in-bucket bulk density monitor

This paper details the implementation and trialling of a prototype in-bucket bulk density monitor on a production dragline. Bulk density information can provide feedback to mine planning and scheduling to improve blasting and consequently facilitating optimal bucket sizing. The bulk density measurement builds upon outcomes presented in the AMTC2009 paper titled ‘Automatic In-Bucket Volume Estimation for Dragline Operations’ and utilises payload information from a commercial dragline monitor. While the previous paper explains the algorithms and theoretical basis for the system design and scaled model testing this paper will focus on the full scale implementation and the challenges involved.