Partnerships to promote school to work transitions : evidence from the field

Internationally, vocational education and training (VET) is challenged by increasing skills shortages in certain industries and rapidly changing skill requirements. Rigid and centralised state bureaucracies have proven inadequate to adapt to these challenges. Increasingly, partnerships between schools and industry have been established as a potential strategy to address local labour market demand and to provide school to work transition programs. Drawing on experiences in Australia, this paper reports on a case study of government-let partnerships between schools and industry. The Queensland Gateway schools initiative currently involves over 120 schools. The study aimed to understand how partnerships were constructed in this initiative. Selected partnerships were analysed in terms of the following principles of public-private partnerships – efficiency, effectiveness, sustainability, and beneficiaries. Although there are some benefits of partnership activities reported by both school and industry stakeholders, little evidence was found that the above underlying principles had been addressed to a significant extent in the Gateway school initiative. Further, these partnerships are often tenuously facilitated by individuals who have limited infrastructure or strategic support. Implications are that project stakeholders have not sufficiently accommodated theoretical perspectives on implementation and management of partnerships. Similar initiatives may be improved if stakeholders are cognisant of the underlying principles supporting successful public-private partnerships.

The Cube : a very large-scale interactive engagement space

“The Cube” is a unique facility that combines 48 large multi-touch screens and very large-scale projection surfaces to form one of the world’s largest interactive learning and engagement spaces. The Cube facility is part of the Queensland University of Technology’s (QUT) newly established Science and Engineering Centre, designed to showcase QUT’s teaching and research capabilities in the STEM (Science, Technology, Engineering, and Mathematics) disciplines. In this application paper we describe, the Cube, its technical capabilities, design rationale and practical day-to-day operations, supporting up to 70,000 visitors per week. Essential to the Cube’s operation are five interactive applications designed and developed in tandem with the Cube’s technical infrastructure. Each of the Cube’s launch applications was designed and delivered by an independent team, while the overall vision of the Cube was shepherded by a small executive team. The diversity of design, implementation and integration approaches pursued by these five teams provides some insight into the challenges, and opportunities, presented when working with large distributed interaction technologies. We describe each of these applications in order to discuss the different challenges and user needs they address, which types of interactions they support and how they utilise the capabilities of the Cube facility.

CubIT : Large-scale multi-user presentation and collaboration

CubIT is a multi-user, large-scale presentation and collaboration framework installed at the Queensland University of Technology’s (QUT) Cube facility, an interactive facility made up 48 multi-touch screens and very large projected display screens. CubIT was built to make the Cube facility accessible to QUT’s academic and student population. The system allows users to upload, interact with and share media content on the Cube’s very large display surfaces. CubIT implements a unique combination of features including RFID authentication, content management through multiple interfaces, multi-user shared workspace support, drag and drop upload and sharing, dynamic state control between different parts of the system and execution and synchronisation of the system across multiple computing nodes.

The confidence of speech-language pathology students regarding communicating with people with aphasia

Background Aphasia is an acquired language disorder that can present a significant barrier to patient involvement in healthcare decisions. Speech-language pathologists (SLPs) are viewed as experts in the field of communication. However, many SLP students do not receive practical training in techniques to communicate with people with aphasia (PWA) until they encounter PWA during clinical education placements. Methods This study investigated the confidence and knowledge of SLP students in communicating with PWA prior to clinical placements using a customised questionnaire. Confidence in communicating with people with aphasia was assessed using a 100-point visual analogue scale. Linear, and logistic, regressions were used to examine the association between confidence and age, as well as confidence and course type (graduate-entry masters or undergraduate), respectively. Knowledge of strategies to assist communication with PWA was examined by asking respondents to list specific strategies that could assist communication with PWA. Results SLP students were not confident with the prospect of communicating with PWA; reporting a median 29-points (inter-quartile range 17–47) on the visual analogue confidence scale. Only, four (8.2%) of respondents rated their confidence greater than 55 (out of 100). Regression analyses indicated no relationship existed between confidence and students‘ age (p = 0.31, r-squared = 0.02), or confidence and course type (p = 0.22, pseudo r-squared = 0.03). Students displayed limited knowledge about communication strategies. Thematic analysis of strategies revealed four overarching themes; Physical, Verbal Communication, Visual Information and Environmental Changes. While most students identified potential use of resources (such as images and written information), fewer students identified strategies to alter their verbal communication (such as reduced speech rate). Conclusions SLP students who had received aphasia related theoretical coursework, but not commenced clinical placements with PWA, were not confident in their ability to communicate with PWA. Students may benefit from an educational intervention or curriculum modification to incorporate practical training in effective strategies to communicate with PWA, before they encounter PWA in clinical settings. Ensuring students have confidence and knowledge of potential communication strategies to assist communication with PWA may allow them to focus their learning experiences in more specific clinical domains, such as clinical reasoning, rather than building foundation interpersonal communication skills.

Development of a large scale flexible LED display matrix for the screen industry

This project addresses the viability of lightweight, low power consumption, flexible, large format LED screens. The investigation encompasses all aspects of the electrical and mechanical design, individually and as a system, and achieves a successful full scale prototype. The prototype implements novel techniques to achieve large displacement colour aliasing, a purely passive thermal management solution, a rapid deployment system, individual seven bit LED current control with two way display communication, auto-configuration and complete signal redundancy, all of which are in direct response to industry needs.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Work environment, job satisfaction, stress and burnout among haemodialysis nurses

Aim To examine the relationships among nurse and work characteristics, job satisfaction, stress, burnout and the work environment of haemodialysis nurses. Background Haemodialysis nursing is characterised by frequent and intense contact with patients in a complex and intense environment. Method Cross-sectional online survey of 417 haemodialysis nurses that included nurse and work characteristics, the Brisbane Practice Environment Measure, Index of Work Satisfaction, Nursing Stress Scale and the Maslach Burnout Inventory. Results Haemodialysis nurses reported an acceptable level of job satisfaction and perceived their work environment positively, although high levels of burnout were found. Nurses who were older and had worked in haemodialysis the longest had higher satisfaction levels, experienced less stress and lower levels of burnout than younger nurses. The in-centre type of haemodialysis unit had greater levels of stress and burnout than home training units. Greater satisfaction with the work environment was strongly correlated with job satisfaction, lower job stress and emotional exhaustion. Conclusion Haemodialysis nurses experienced high levels of burnout even though their work environment was favourable and they had acceptable levels of job satisfaction. Implications for Nursing Management: Targeted strategies are required to retain and avoid burnout in younger and less experienced nurses in this highly specialised field of nursing.

Supporting collaboration in large-scale multi-user workspaces

CubIT is a multi-user, large-scale presentation and collaboration framework installed at the Queensland University of Technology’s (QUT) Cube facility, an interactive facility made up 48 multi-touch screens and very large projected display screens. The CubIT system allows users to upload, interact with and share their own content on the Cube’s display surfaces. This paper outlines the collaborative features of CubIT which are implemented via three user interfaces, a large-screen multi-touch interface, a mobile phone and tablet application and a web-based content management system. Each of these applications plays a different role and supports different interaction mechanisms supporting a wide range of collaborative features including multi-user shared workspaces, drag and drop upload and sharing between users, session management and dynamic state control between different parts of the system.

Large-scale association study identifies ICAM gene region as breast and prostate cancer susceptibility locus

We conducted a large-scale association study to identify genes that influence nonfamilial breast cancer risk using a collection of German cases and matched controls and >25,000 single nucleotide polymorphisms located within 16,000 genes. One of the candidate loci identified was located on chromosome 19p13.2 [odds ratio (OR) = 1.5, P = 0.001]. The effect was substantially stronger in the subset of cases with reported family history of breast cancer (OR = 3.4, P = 0.001). The finding was subsequently replicated in two independent collections (combined OR = 1.4, P < 0.001) and was also associated with predisposition to prostate cancer in an independent sample set of prostate cancer cases and matched controls (OR = 1.4, P = 0.002). High-density single nucleotide polymorphism mapping showed that the extent of association spans 20 kb and includes the intercellular adhesion molecule genes ICAM1, ICAM4, and ICAM5. Although genetic variants in ICAM5 showed the strongest association with disease status, ICAM1 is expressed at highest levels in normal and tumor breast tissue. A variant in ICAM5 was also associated with disease progression and prognosis. Because ICAMs are suitable targets for antibodies and small molecules, these findings may not only provide diagnostic and prognostic markers but also new therapeutic opportunities in breast and prostate cancer.

Nonlinear actuator fault detection for small-scale UAS

This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating corresponding velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.

An interpretive field study of packaged software selection processes

Packaged software is pre-built with the intention of licensing it to users in domestic settings and work organisations. This thesis focuses upon the work organisation where packaged software has been characterised as one of the latest ‘solutions’ to the problems of information systems. The study investigates the packaged software selection process that has, to date, been largely viewed as objective and rational. In contrast, this interpretive study is based on a 21⁄2 year long field study of organisational experiences with packaged software selection at T.Co, a consultancy organisation based in the United Kingdom. Emerging from the iterative process of case study and action research is an alternative theory of packaged software selection. The research argues that packaged software selection is far from the rationalistic and linear process that previous studies suggest. Instead, the study finds that aspects of the traditional process of selection incorporating the activities of gathering requirements, evaluation and selection based on ‘best fit’ may or may not take place. Furthermore, even where these aspects occur they may not have equal weight or impact upon implementation and usage as may be expected. This is due to the influence of those multiple realities which originate from the organisational and market environments within which packages are created, selected and used, the lack of homogeneity in organisational contexts and the variously interpreted characteristics of the package in question.

Practical applications for clay-derived zeolite N : an ammonium-selective ion exchanger for industry use

Over the past ten years, scaled-up utilisation of a previously under-exploited zeolite, Zeolite N1, has been demonstrated for selective ion exchange of ammonium and other ions in aqueous environments. As with many zeolite syntheses, the required source material should contain predictable levels of aluminium and silicon and, for full-scale industrial applications, kaolin and/or montmorillonite serve such a purpose. Field, pilot and commercial scale trials of kaolin-derived Zeolite N have focused on applications in agriculture and water treatment as these sectors are primary producers or users of ammonium. The format for the material – as fine powders, granules or extrudates – depends on the specific application albeit each has been evaluated.

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

Distinguishing between mean-field, moment dynamics and stochastic descriptions of birth-death-movement processes

Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.

Formative evaluation for improving collaborative planning : a case study at the regional scale

In an earlier paper (Cameron & Johnson 2004) we introduced the idea of formative evaluation (or evaluation for development), the purpose of which is to provide information for improving planning programs and activities. This type of evaluation differs from the two other types: outcome evaluation which aims to judge the success or otherwise of a program; and evaluation for knowledge which seeks to contribute to theoretical work on planning processes and activities. In the earlier paper we also outlined the first stage of formative evaluation in the SEQ 2021 regional planning exercise showing how the process of planning for community engagement was modified in light of the evaluation findings. This current paper details the second stage of formative evaluation in which the collaborative planning component of SEQ 2021 was evaluated, as such it further demonstrates how formative evaluation can be used to improve planning programs. The evaluation findings also provide insights into strategies for more effective collaborative planning. We begin with an overview of collaborative approaches to regional planning, including the SEQ 2021 regional planning program. We then outline formal and informal evaluations of various collaborative regional planning exercises, including the predecessor of SEQ 2021 - SEQ 2001. This sets the scene for discussion of the approach used to evaluate the collaborative component of SEQ 2021. After outlining the main findings from the evaluation and the ways these findings were used to refine the collaborative planning process we conclude with a series of recommendations, relevant not only to SEQ 2021 but to other collaborative planning exercises