Decision support system for contractor pre-qualification : artificial neural network model

The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

XCFS - a novel approach for clustering XML documents using both the structure and the content

XML document clustering is essential for many document handling applications such as information storage, retrieval, integration and transformation. An XML clustering algorithm should process both the structural and the content information of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. This paper introduces a novel approach that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The proposed method reduces the high dimensionality of input data by using only the structure-constrained content. The empirical analysis reveals that the proposed method can effectively cluster even very large XML datasets and outperform other existing methods.

An investigation into how work-related road safety can be enhanced

Despite the facts that vehicle incidents continue to be the most common mechanism for Australian compensated fatalities and that employers have statutory obligations to provide safe workplaces, very few organisations are proactively and comprehensively managing their work-related road risks. Unfortunately, limited guidance is provided in the existing literature to assist practitioners in managing work-related road risks. The current research addresses this gap in the literature. To explore how work-related road safety can be enhanced, three studies were conducted. Study one explored the effectiveness of a range of risk management initiatives and whether comprehensive risk management practices were associated with safety outcomes. Study two explored barriers to, and facilitators for, accepting risk management initiatives. Study three explored the influence of organisational factors on road safety outcomes to identify optimal work environments for managing road risks. To maximise the research sample and increase generalisability, the studies were designed to allow data collection to be conducted simultaneously drawing upon the same sample obtained from four Australian organisations. Data was collected via four methods. A structured document review of published articles was conducted to identify what outcomes have been observed in previously investigated work-related road safety initiatives. The documents reviewed collectively assessed the effectiveness of 19 work-related road safety initiatives. Audits of organisational practices and process operating within the four researched organisations were conducted to identify whether organisations with comprehensive work-related road risk management practices and processes have better safety outcomes than organisations with limited risk management practices and processes. Interviews were conducted with a sample of 24 participants, comprising 16 employees and eight managers. The interviews were conducted to identify what barriers and facilitators within organisations are involved in implementing work-related road safety initiatives and whether differences in fleet safety climate, stage of change and safety ownership relate to work-related road safety outcomes. Finally, questionnaires were administered to a sample of 679 participants. The questionnaires were conducted to identify which initiatives are perceived by employees to be effective in managing work-related road risks and whether differences in fleet safety climate, stage of change and safety ownership relate to work-related road safety outcomes. Seven research questions were addressed in the current research project. The key findings with respect to each of the research questions are presented below. Research question one: What outcomes have been observed in previously investigated work-related road safety initiatives? The structured document review indicated that initiatives found to be positively associated with occupational road safety both during and after the intervention period included: a pay rise; driver training; group discussions; enlisting employees as community road safety change agents; safety reminders; and group and individual rewards. Research question two: Which initiatives are perceived by employees to be effective in managing work-related road risks? Questionnaire findings revealed that employees believed occupational road risks could best be managed through making vehicle safety features standard, providing practical driver skills training and through investigating serious vehicle incidents. In comparison, employees believed initiatives including signing a promise card commitment to drive safely, advertising the organisation’s phone number on vehicles and consideration of driving competency in staff selection process would have limited effectiveness in managing occupational road safety. Research question three: Do organisations with comprehensive work-related road risk management practices and processes have better safety outcomes than organisations with limited risk management practices and processes? The audit identified a difference among the organisations in their management of work-related road risks. Comprehensive risk management practices were associated with employees engaging in overall safer driving behaviours, committing less driving errors, and experiencing less fatigue and distraction issues when driving. Given that only four organisations participated in this research, these findings should only be considered as preliminary. Further research should be conducted to explore the relationship between comprehensiveness of risk management practices and road safety outcomes with a larger sample of organisations. Research question four: What barriers and facilitators within organisations are involved in implementing work-related road safety initiatives? The interviews identified that employees perceived six organisational characteristics as potential barriers to implementing work-related road safety initiatives. These included: prioritisation of production over safety; complacency towards work-related road risks; insufficient resources; diversity; limited employee input in safety decisions; and a perception that road safety initiatives were an unnecessary burden. In comparison, employees perceived three organisational characteristics as potential facilitators to implementing work-related road safety initiatives. These included: management commitment; the presence of existing systems that could support the implementation of initiatives; and supportive relationships. Research question five: Do differences in fleet safety climate relate to work-related road safety outcomes? The interviews and questionnaires identified that organisational climates with high management commitment, support for managing work demands, appropriate safety rules and safety communication were associated with employees who engaged in safer driving behaviours. Regression analyses indicated that as participants’ perceptions of safety climate increased, the corresponding likelihood of them engaging in safer driving behaviours increased. Fleet safety climate was perceived to influence road safety outcomes through several avenues. Some of these included: the allocation of sufficient resources to manage occupational road risks; fostering a supportive environment of mutual responsibility; resolving safety issues openly and fairly; clearly communicating to employees that safety is the top priority; and developing appropriate work-related road safety policies and procedures. Research question six: Do differences in stage of change relate to work-related road safety outcomes? The interviews and questionnaires identified that participants’ perceptions of initiative effectiveness were found to vary with respect to their individual stage of readiness, with stage-matched initiatives being perceived most effective. In regards to safety outcomes, regression analyses identified that as participants’ progress through the stages of change, the corresponding likelihood of them being involved in vehicle crashes decreases. Research question seven: Do differences in safety ownership relate to work-related road safety outcomes? The interviews and questionnaires revealed that management of road risks is often given less attention than other areas of health and safety management in organisations. In regards to safety outcomes, regression analyses identified that perceived authority and perceived shared ownership both emerged as significant independent predictors of self-reported driving behaviours pertaining to fatigue and distractions. The regression models indicated that as participants’ perceptions of the authority of the person managing road risks increases, and perceptions of shared ownership of safety tasks increases, the corresponding likelihood of them engaging in driving while fatigued or multitasking while driving decreases. Based on the findings from the current research, the author makes several recommendations to assist practitioners in developing proactive and comprehensive approaches to managing occupational road risks. The author also suggests several avenues for future research in the area of work-related road safety.

Bifocal lens control of myopia progression in children

This research investigated underlying issues that were critical to the success of the bifocal trial and comprised of three studies. The first study evaluated if Chinese-Canadian children were suitable subjects for the bifocal trial. The high prevalence of myopia in Chinese children suggests that genetic input plays a role in myopia development, but the rapid increase in prevalence over the last few decades indicates environmental factors are also important. Since this bifocal trial was conducted in Canada, this work aimed to determine whether Chinese children who had migrated to Canada would still have high myopia prevalence and a high rate of myopia progression. The second study determined the optimal bifocal lens power for myopia treatment and the effect of incorporating base-in prism into the bifocal. In the majority of published myopia control studies, the power of the prescribed near addition was usually predetermined in the belief that the near addition would always help to improve the near focus. In fact, the effect of near addition on the accommodative error might be quite different even for individuals in which the same magnitude of accommodation lag had been measured. Therefore, this work was necessary to guide the selection of bifocal and prism powers most suitable for the subsequent bifocal trial. The third study, the ultimate goal of this research, was to conduct a longitudinal clinical trial to determine if bifocals and prismatic bifocals could control myopia progression in children.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Biometric template security using higher order spectra

A method of improving the security of biometric templates which satisfies desirable properties such as (a) irreversibility of the template, (b) revocability and assignment of a new template to the same biometric input, (c) matching in the secure transformed domain is presented. It makes use of an iterative procedure based on the bispectrum that serves as an irreversible transformation for biometric features because signal phase is discarded each iteration. Unlike the usual hash function, this transformation preserves closeness in the transformed domain for similar biometric inputs. A number of such templates can be generated from the same input. These properties are illustrated using synthetic data and applied to images from the FRGC 3D database with Gabor features. Verification can be successfully performed using these secure templates with an EER of 5.85%

Performing with grid music systems

Grid music systems provide discrete geometric methods for simplified music-making by providing spatialised input to construct patterned music on a 2D matrix layout. While they are conceptually simple, grid systems may be layered to enable complex and satisfying musical results. Grid music systems have been applied to a range of systems from small portable devices up to larger systems. In this paper we will discuss the use of grid music systems in general and present an overview of the HarmonyGrid system we have developed as a new interactive performance system. We discuss a range of issues related to the design and use of larger-scale grid- based interactive performance systems such as the HarmonyGrid.

Do androids dream of electric chimera?

This paper describes the use of the Chimera Architecture as the basis for a generative rhythmic improvisation system that is intended for use in ensemble contexts. This interactive soft- ware system learns in real time based on an audio input from live performers. The paper describes the components of the Chimera Architecture including a novel analysis engine that uses prediction to robustly assess the rhythmic salience of the input stream. Analytical results are stored in a hierarchical structure that includes multiple scenarios which allow ab- stracted and alternate interpretations of the current metrical context. The system draws upon this Chimera Architecture when generating a musical response. The generated rhythms are intended to have a particular ambiguity in relation to the music performance by other members of the ensemble. Ambi- guity is controlled through alternate interpretations of the Chimera. We describe an implementation of the Chimera Ar- chitecture that focuses on rhythmic material, and present and discuss initial experimental results of the software system playing along with recordings of a live performance.

The costs arising from pressure ulcers attributable to malnutrition

Aim To estimate the economic consequences of pressure ulcers attributable to malnutrition. Method Statistical models were developed to predict the number of cases of pressure ulcer, associated bed days lost and the dollar value of these losses in public hospitals in 2002/2003 in Queensland, Australia. The following input parameters were specified and appropriate probability distributions fitted • Number of at risk discharges per annum • Incidence rate for pressure ulcer • Attributable fraction of malnutrition in the development of pressure ulcer • Independent effect of pressure ulcer on length of hospital stay • Opportunity cost of hospital bed day One thousand random re-samples were made and the results expressed as (output) probabilistic distributions. Results The model predicts a mean 16060 (SD 5 671) bed days lost and corresponding mean economic cost of AU$12 968 668 (SD AU$4 924 148) (EUROS 6 925 268 SD 2 629 495; US$ 7 288 391 SD 2 767 371) of pressure ulcer attributable to malnutrition in 2002/2003 in public hospitals in Queensland, Australia. Conclusion The cost of pressure ulcer attributable to malnutrition in bed days and dollar terms are substantial. The model only considers costs of increased length of stay associated with pressure ulcer and not other factors associated with care.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

A QUT experience in combining sustainability research with educational activities and professional practice

The paper discusses the development and delivery of a university subject on sustainable construction, using related research projects as case studies and learning materials. It exposed students from a variety of disciplines to real life scenarios, to group around project cases, and learn to work with one another in solving sustainable development problems. The problem based learning approach directly responds to the new trends of learning by practising which, in the area of sustainability education, is particularly appropriate because of the need for multidisciplinary approach to complex issues, and the impetus for research and development to provide timely input for education in this growing discipline with a relatively short history. Collaboration of students from cross-disciplines, the engagement of industry and practitioners, the concept of using project cases and student design competition, and the tangible improvement of students’ comprehension of the sustainability phenomenon as a whole, have been the highlights of this Australian experience.

New modal feed network for a compact monopole array with isolated ports

An element spacing of less than half a wavelength introduces strong mutual coupling between the ports of compact antenna arrays. The strong coupling causes significant system performance degradation. A decoupling network may compensate for the mutual coupling. Alternatively, port decoupling can be achieved using a modal feed network. In response to an input signal at one of the input ports, this feed network excites the antenna elements in accordance with one of the eigenvectors of the array scattering parameter matrix. In this paper, a novel 4-element monopole array is described. The feed network of the array is implemented as a planar ring-type circuit in stripline with four coupled line sections. The new configuration offers a significant reduction in size, resulting in a very compact array.

Computer vision onboard UAVs for civilian tasks

Computer vision is much more than a technique to sense and recover environmental information from an UAV. It should play a main role regarding UAVs’ functionality because of the big amount of information that can be extracted, its possible uses and applications, and its natural connection to human driven tasks, taking into account that vision is our main interface to world understanding. Our current research’s focus lays on the development of techniques that allow UAVs to maneuver in spaces using visual information as their main input source. This task involves the creation of techniques that allow an UAV to maneuver towards features of interest whenever a GPS signal is not reliable or sufficient, e.g. when signal dropouts occur (which usually happens in urban areas, when flying through terrestrial urban canyons or when operating on remote planetary bodies), or when tracking or inspecting visual targets—including moving ones—without knowing their exact UMT coordinates. This paper also investigates visual serving control techniques that use velocity and position of suitable image features to compute the references for flight control. This paper aims to give a global view of the main aspects related to the research field of computer vision for UAVs, clustered in four main active research lines: visual serving and control, stereo-based visual navigation, image processing algorithms for detection and tracking, and visual SLAM. Finally, the results of applying these techniques in several applications are presented and discussed: this study will encompass power line inspection, mobile target tracking, stereo distance estimation, mapping and positioning.

The development and evaluation of an innovative nursing practice model to improve undergraduate nursing students' competence in paediatric physical assessment

Introduction The purpose of this study was to develop, implement and evaluate the impact of an educational intervention, comprising an innovative model of clinical decisionmaking and educational delivery strategy for facilitating nursing students‘ learning and development of competence in paediatric physical assessment practices. Background of the study Nursing students have an undergraduate education that aims to produce graduates of a generalist nature who demonstrate entry level competence for providing nursing care in a variety of health settings. Consistent with population morbidity and health care roles, paediatric nursing concepts typically form a comparatively small part of undergraduate curricula and students‘ exposure to paediatric physical assessment concepts and principles are brief. However, the nursing shortage has changed traditional nursing employment patterns and new graduates form the majority of the recruitment pool for paediatric nursing speciality staff. Paediatric nursing is a popular career choice for graduates and anecdotal evidence suggests that nursing students who select a clinical placement in their final year intend to seek employment in paediatrics upon graduation. Although concepts of paediatric nursing are included within undergraduate curriculum, students‘ ability to develop the required habits of mind to practice in what is still regarded as a speciality area of practice is somewhat limited. One of the areas of practice where this particularly impacts is in paediatric nursing physical assessment. Physical assessment is a fundamental component of nursing practice and competence in this area of practice is central to nursing students‘ development of clinical capability for practice as a registered nurse. Timely recognition of physiologic deterioration of patients is a key outcome of nurses‘ competent use of physical assessment strategies, regardless of the practice context. In paediatric nursing contexts children‘s physical assessment practices must specifically accommodate the child‘s different physiological composition, function and pattern of clinical deterioration (Hockenberry & Barrera, 2007). Thus, to effectively manage physical assessment of patients within the paediatric practice setting nursing students need to integrate paediatric nursing theory into their practice. This requires significant information processing and it is in this process where students are frequently challenged. The provision of rules or models can guide practice and assist novice-level nurses to develop their capabilities (Benner, 1984; Benner, Hooper-Kyriakidis & Stannard, 1999). Nursing practice models are cognitive tools that represent simplified patterns of expert analysis employing concepts that suit the limited reasoning of the inexperienced, and can represent the =rules‘ referred to by Benner (1984). Without a practice model of physical assessment students are likely to be uncertain about how to proceed with data collection, the interpretation of paediatric clinical findings and the appraisal of findings. These circumstances can result in ad hoc and unreliable nursing physical assessment that forms a poor basis for nursing decisions. The educational intervention developed as part of this study sought to resolve this problem and support nursing students‘ development of competence in paediatric physical assessment. Methods This study utilised the Context Input Process Product (CIPP) Model by Stufflebeam (2004) as the theoretical framework that underpinned the research design and evaluation methodology. Each of the four elements in the CIPP model were utilised to guide discrete stages of this study. The Context element informed design of the clinical decision-making process, the Paediatric Nursing Physical Assessment model. The Input element was utilised in appraising relevant literature, identifying an appropriate instructional methodology to facilitate learning and educational intervention delivery to undergraduate nursing students, and development of program content (the CD-ROM kit). Study One employed the Process element and used expert panel approaches to review and refine instructional methods, identifying potential barriers to obtaining an effective evaluation outcome. The Product element guided design and implementation of Study Two, which was conducted in two phases. Phase One employed a quasiexperimental between-subjects methodology to evaluate the impact of the educational intervention on nursing students‘ clinical performance and selfappraisal of practices in paediatric physical assessment. Phase Two employed a thematic analysis and explored the experiences and perspectives of a sample subgroup of nursing students who used the PNPA CD-ROM kit as preparation for paediatric clinical placement. Results Results from the Process review in Study One indicated that the prototype CDROM kit containing the PNPA model met the predetermined benchmarks for face validity and the impact evaluation instrumentation had adequate content validity in comparison with predetermined benchmarks. In the first phase of Study Two the educational intervention did not result in statistically significant differences in measures of student performance or self-appraisal of practice. However, in Phase Two qualitative commentary from students, and from the expert panel who reviewed the prototype CD-ROM kit (Study One, Phase One), strongly endorsed the quality of the intervention and its potential for supporting learning. This raises questions regarding transfer of learning and it is likely that, within this study, several factors have influenced students‘ transfer of learning from the educational intervention to the clinical practice environment, where outcomes were measured. Conclusion In summary, the educational intervention employed in this study provides insights into the potential e-learning approaches offer for delivering authentic learning experiences to undergraduate nursing students. Findings in this study raise important questions regarding possible pedagogical influences on learning outcomes, issues within the transfer of theory to practice and factors that may have influenced findings within the context of this study. This study makes a unique contribution to nursing education, specifically with respect to progressing an understanding of the challenges faced in employing instructive methods to impact upon nursing students‘ development of competence. The important contribution transfer of learning processes make to students‘ transition into the professional practice context and to their development of competence within the context of speciality practice is also highlighted. This study contributes to a greater awareness of the complexity of translating theoretical learning at undergraduate level into clinical practice, particularly within speciality contexts.

Waking up with friends : breakfast news, Sunrise and the "televisual sphere"

This paper examines the Australian breakfast news program Sunrise. By drawing on interviews with both viewers and producers, as well as selected textual analysis, it examines the show, how it is "used" as a news source, and explores its role within the audience’s morning routines. By viewing the show as a part of what Baym has termed the "Televisual Sphere", it will argue against the common discourse that the program has simply followed a populist style in pursuit of higher ratings. Because of its success in communicating and connecting with viewers, it may be more constructive to consider Sunrise a very effective form of journalism which has been at the forefront of the recent trend towards increased levels of viewer input in television journalism.