Micro-structure differences in kaolinite suspensions

SEM observations of the aqueous suspensions of kaolinite from Birdwood (South Australia) and Georgia (USA) show noticeable differences in number of physical behaviour which has been explained by different microstructure constitution.. Birdwood kaolinite dispersion gels are observed at very low solid loadings in comparison with Georgia KGa-1 kaolinite dispersions which remain fluid at higher solids loading. To explain this behaviour, the specific particle interactions of Birdwood kaolinite, different from interaction in Georgia kaolinite have been proposed. These interactions may be brought about by the presence of nano-bubbles on clay crystal edges and may force clay particles to aggregate by bubble coalescence. This explains the predominance of stair step edge-edge like (EE) contacts in suspension of Birdwood kaolinite. Such EE linked particles build long strings that form a spacious cell structure. Hydrocarbon contamination of colloidal kaolinite particles and low aspect ratio are discussed as possible explanations of this unusual behaviour of Birdwood kaolinite. In Georgia KGa-1 kaolinite dispersions instead of EE contact between platelets displayed in Birdwood kaolinite, most particles have edge to face (EF) contacts building a cardhouse structure. Such an arrangement is much less voluminous in comparison with the Birdwood kaolinite cellular honeycomb structure observed previously in smectite aqueous suspensions. Such structural characteristics of KGa-1 kaolinite particles enable higher solid volume fractions pulps to form before significantly networked gel consistency is attained.

Multi-Outcome Construction Policies : Industry-Focused Research Summary

The Multi-outcomes Construction Policies research project, funded by the Cooperative Research Centre for Construction Innovation (Project 2006-036-A), sought to explore the costs and benefits of leveraging social outcomes on public construction contracts. The context of the research project was the trend towards the contracting out of public construction works and the attempts that have been made to use new contractual arrangements with construction companies to construction achieve a wide range of social outcomes. In federal and state jurisdictions it is now common for governments to impose a range of additional requirements on public works contractors that relate to broad social/community objectives. These requirements include commitments to train apprentices and trainees; to provide local and/or indigenous employment opportunities; to buy local materials; and to include art works. The cost and benefits of using public construction contracts to achieve social/community goals have, to our knowledge, not been thoroughly researched in an Australian context. This is likely to reflect in large part the relatively short history of contracting out public works. As Jensen and Stonecash (2004) explain, most previous empirical studies of contracting out have attempted to measure the cost savings achieved through privatization, as this was the focus of policy debate in the 1980s and 1990s. Relatively few studies have addressed the ability of contracting arrangements to ensure the delivery of desired ‘quality’ outcomes1, or the costs of achieving these outcomes via contracting arrangements. One of the potential costs of attempting to leverage social/community outcomes on public construction projects is a reduction in the amount of competition for these projects, with obvious consequences for average bid prices and choice. In jurisdictions, such as Western Australia and Queensland, where currently construction market conditions are already

Principal preparation and training : a look at China and its issues

Purpose: The purpose of this paper is to provide an understanding of principal preparation and training in China by providing a background discussion of principal preparation in a number of countries. As an illustration, it provides an overview of the curriculum used in the initial preparation of school principals at Beijing Normal University.-----Design/methodology/approach: The paper draws mainly on writing and research from China, Australia and the USA to explore principal preparation and training in China.-----Findings: In addition to providing a rich description of principal preparation in China, the paper's main findings comprise seven key challenges that confront China as it endeavours to provide quality principal preparation. These challenges include China's diversity and uneven social, cultural and educational development; limited resources in some regions throughout China; the place and importance of study tours for principal preparation; the teaching approach used to train principals; the process used for assessing principal learning during their training programs; the limited transfer of learning from the classroom to the school environment; and the timing of training for principals.-----Practical implications: Each of the challenges arising here raises important practical implications for developers of principal training programs.-----Originality/value: The paper paints a picture of principal preparation in China and raises a number of issues and challenges with which it continues to grapple. Of note is that China is not alone in facing some of these ongoing concerns.

Prognosis of bearing failure based on health state estimation

This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.

CSI Lincoln : an investigation into a declining housing market

The residential property market in New Zealand has been experiencing a boom and bubble period from 2001 through to mid 2007. Following a number of increases in the Official Cash Rate by the Reserve Bank and a decline in net migration numbers the housing market was perceived to be over inflated and due for a major correction. Numerous media, Government Departments, property experts and economists have been predicting significant reductions in the median price of residential property throughout New Zealand. This paper will analyse house prices in specific socio-economic locations within Christchurch over the past 12 months to determine how significant the current housing decline is. This study will review the change in residential property prices, variations in property listings since April 2008, sale volumes and days on the market across a range of housing sectors to determine the extent and range of any residential property downturn in the NZ recession.

Robot navigation in sensor space

This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.

Dynamics of railway wagons subjected to braking/traction torque

Braking or traction torque is regarded as an important source of wheelset skid and a potential source of derailment risk that adversely affects the safety levels of train operations; therefore, this research examines the effect of braking/traction torque to the longitudinal and lateral dynamics of wagons. This paper reports how train operations safety could be adversely affected due to various braking strategies. Sensitivity of wagon dynamics to braking severity is illustrated through numerical examples. The influence of wheel/rail interface friction coefficient and the effects of two types of track geometry defects on wheel unloading ratio and wagon pitch are also discussed in the paper.

Scheduling trains as a blocking parallel-machine job shop scheduling problem

In this paper, the train scheduling problem is modelled as a blocking parallel-machine job shop scheduling (BPMJSS) problem. In the model, trains, single-track sections and multiple-track sections, respectively, are synonymous with jobs, single machines and parallel machines, and an operation is regarded as the movement/traversal of a train across a section. Due to the lack of buffer space, the real-life case should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold the train until next section on the routing becomes available. Based on literature review and our analysis, it is very hard to find a feasible complete schedule directly for BPMJSS problems. Firstly, a parallel-machine job-shop-scheduling (PMJSS) problem is solved by an improved shifting bottleneck procedure (SBP) algorithm without considering blocking conditions. Inspired by the proposed SBP algorithm, feasibility satisfaction procedure (FSP) algorithm is developed to solve and analyse the BPMJSS problem, by an alternative graph model that is an extension of the classical disjunctive graph models. The proposed algorithms have been implemented and validated using real-world data from Queensland Rail. Sensitivity analysis has been applied by considering train length, upgrading track sections, increasing train speed and changing bottleneck sections. The outcomes show that the proposed methodology would be a very useful tool for the real-life train scheduling problems

Techniques for inserting additional trains into existing timetables

In this paper techniques for scheduling additional train services (SATS) are considered as is train scheduling involving general time window constraints, fixed operations, maintenance activities and periods of section unavailability. The SATS problem is important because additional services must often be given access to the railway and subsequently integrated into current timetables. The SATS problem therefore considers the competition for railway infrastructure between new services and existing services belonging to the same or different operators. The SATS problem is characterised as a hybrid job shop scheduling problem with time window constraints. To solve this problem constructive algorithm and metaheuristic scheduling techniques that operate upon a disjunctive graph model of train operations are utilised. From numerical investigations the proposed framework and associated techniques are tested and shown to be effective.

Community engagement for development and application of 3D visualisation models : a two edged

Background: SEQ Catchments Ltd and QUT are collaborating on groundwater investigations in the SE Qld region, which utilise community engagement and 3D Visualisation methodologies. The projects, which have been funded by the Australian Government’s NHT and Caring for our Country programmes, were initiated from local community concerns regarding groundwater sustainability and quality in areas where little was previously known. ----- Objectives: Engage local and regional stakeholders to tap all available sources of information;•Establish on-going (2 years +) community-based groundwater / surface water monitoring programmes;•Develop 3D Visualisation from all available data; and•Involve, train and inform the local community for improved on-ground land and water use management. ----- Results and findings: Respectful community engagement yielded information, access to numerous monitoring sites and education opportunities at low cost, which would otherwise be unavailable. A Framework for Community-Based Groundwater Monitoring has been documented (Todd, 2008).A 3D visualisation models have been developed for basaltic settings, which relate surface features familiar to the local community with the interpreted sub-surface hydrogeology. Groundwater surface movements have been animated and compared to local rainfall using the time-series monitoring data.An important 3D visualisation feature of particular interest to the community was the interaction between groundwater and surface water. This factor was crucial in raising awareness of potential impacts of land and water use on groundwater and surface water resources.

Residential property market performance in a declining market : Christchurch case study

The residential property market in New Zealand has been experiencing a boom and bubble period from 2001 through to mid 2007. Following a number of increases in the Official Cash Rate by the Reserve Bank and a decline in net migration numbers the housing market was perceived to be over-inflated and due for major correction.

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.

Correlating vehicle forces and track profile

A research project was conducted at Queensland University of Technology on the relationship between the forces at the wheel-rail interface in track and the rate of degradation of track. Data for the study was obtained from an instrumented vehicle which ran repeatedly over a section of Queensland Rail's track in Central Queensland over a 6-month period. The wheel-rail forces had to be correlated with the elements of roughness in the test track profile, which were measured with a variety of equipment. At low frequencies, there was strong correlation between forces and profile, as expected, but diminishing correlation as frequencies increased.

Liking vs. wanting food : importance for human appetite control and weight regulation

Current train of thought in appetite research is favouring an interest in non-homeostatic or hedonic (reward) mechanisms in relation to overconsumption and energy balance. This tendency is supported by advances in neurobiology that precede the emergence of a new conceptual approach to reward where affect and motivation (liking and wanting) can be seen as the major force in guiding human eating behaviour. In this review, current progress in applying processes of liking and wanting to the study of human appetite are examined by discussing the following issues: How can these concepts be operationalised for use in human research to reflect the neural mechanisms by which they may be influenced? Do liking and wanting operate independently to produce functionally significant changes in behaviour? Can liking and wanting be truly experimentally separated or will an expression of one inevitably contain elements of the other? The review contains a re-examination of selected human appetite research before exploring more recent methodological approaches to the study of liking and wanting in appetite control. In addition, some theoretical developments are described in four diverse models that may enhance current understanding of the role of these processes in guiding ingestive behaviour. Finally, the implications of a dual process modulation of food reward for weight gain and obesity are discussed. The review concludes that processes of liking and wanting are likely to have independent roles in characterising susceptibility to weight gain. Further research into the dissociation of liking and wanting through implicit and explicit levels of processing would help to disclose the relative importance of these components of reward for appetite control and weight regulation.