Delivering value for money in the procurement of public sector major infrastructure : a new first-order decision making model

The significant challenge faced by government in demonstrating value for money in the delivery of major infrastructure resolves around estimating costs and benefits of alternative modes of procurement. Faced with this challenge, one approach is to focus on a dominant performance outcome visible on the opening day of the asset, as the means to select the procurement approach. In this case, value for money becomes a largely nominal concept and determined by selected procurement mode delivering, or not delivering, the selected performance outcome, and notwithstanding possible under delivery on other desirable performance outcomes, as well as possibly incurring excessive transaction costs. This paper proposes a mind-set change in this particular practice, to an approach in which the analysis commences with the conditions pertaining to the project and proceeds to deploy transaction cost and production cost theory to indicate a procurement approach that can claim superior value for money relative to other competing procurement modes. This approach to delivering value for money in relative terms is developed in a first-order procurement decision making model outlined in this paper. The model developed could be complementary to the Public Sector Comparator (PSC) in terms of cross validation and the model more readily lends itself to public dissemination. As a possible alternative to the PSC, the model could save time and money in preparation of project details to lesser extent than that required in the reference project and may send a stronger signal to the market that may encourage more innovation and competition.

Modelling web search behaviour : a user’s cognitive style perspective [Unpublished]

Many researchers have investigated and modelled aspects of Web searching. A number of studies have explored the relationships between individual differences and Web searching. However, limited studies have explored the role of users’ cognitive styles in determining Web searching behaviour. Current models of Web searching have limited consideration of users’ cognitive styles. The impact of users’ cognitive style on Web searching and their relationships are little understood or represented. Individuals differ in their information processing approaches and the way they represent information, thus affecting their performance. To create better models of Web searching we need to understand more about user’s cognitive style and their Web search behaviour, and the relationship between them. More rigorous research is needed in using more complex and meaningful measures of relevance; across a range of different types of search tasks and different populations of Internet users. The project further explores the relationships between the users’ cognitive style and their Web searching. The project will develop a model depicting the relationships between a user’s cognitive style and their Web searching. The related literature, aims and objectives and research design are discussed.

An innovative robust reactive surgery assignment model

Online scheduling in the Operating Theatre Department is a dynamic process that deals with both elective and emergency patients. Each business day begins with an elective schedule determined in advance based on a mastery surgery schedule. Throughout the course of the day however, disruptions to this baseline schedule occur due to variations in treatment time, emergency arrivals, equipment failure and resource unavailability. An innovative robust reactive surgery assignment model is developed for the operating theatre department. Following the completion of each surgery, the schedule is re-solved taking into account any disruptions in order to minimise cancellations of pre-planned patients and maximise throughput of emergency cases. The single theatre case is solved and future work on the computationally more complex multiple theatre case under resource constraints is discussed.

The QUT creative industries experience

This publication assembles essays by people who are leading voices and practitioners in the creative industries, writing from the perspectives of education, research and business development. The idea for the publication arose from a request in 2007 from key Chinese policy academics for information on what they called ‘The Queensland model’. Apart from a co-authored article published in Chinese in that year by three of the contributors to this publication, there was little assembled evidence of the model. The interest from China culminated in requests to visit and see the Queensland model first hand. Since 2007, there have been many visitors to the Creative Industries Precinct and the Kelvin Grove Urban Village. The tours have generally taken people to different organisational units within the larger complex. This publication follows this approach but also shows how the various organisational units are integrated.

A model for constraint and delegation management

This paper introduces a model to facilitate delegation, including ad-hoc delegation, in cross security domain activities. Specifically, this paper proposes a novel delegation constraint management model to manage and track delegation constraints across security domains. An algorithm to trace the authority of delegation constraints is introduced as well as an algorithm to form a delegation constraint set and detect/prevent potential conflicts. The algorithms and the management model are built upon a set of formal definitions of delegation constraints.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.

Spatial stimulus : Model making in the architectural design studio

This action research examines the enhancement of visual communication within the architectural design studio through physical model making. „It is through physical model making that designers explore their conceptual ideas and develop the creation and understanding of space,‟ (Salama & Wilkinson 2007:126). This research supplements Crowther‟s findings extending the understanding of visual dialogue to include physical models. „Architecture Design 8‟ is the final core design unit at QUT in the fourth year of the Bachelor of Design Architecture. At this stage it is essential that students have the ability to communicate their ideas in a comprehensive manner, relying on a combination of skill sets including drawing, physical model making, and computer modeling. Observations within this research indicates that students did not integrate the combination of the skill sets in the design process through the first half of the semester by focusing primarily on drawing and computer modeling. The challenge was to promote deeper learning through physical model making. This research addresses one of the primary reasons for the lack of physical model making, which was the limited assessment emphasis on the physical models. The unit was modified midway through the semester to better correlate the lecture theory with studio activities by incorporating a series of model making exercises conducted during the studio time. The outcome of each exercise was assessed. Tutors were surveyed regarding the model making activities and a focus group was conducted to obtain formal feedback from students. Students and tutors recognised the added value in communicating design ideas through physical forms and model making. The studio environment was invigorated by the enhanced learning outcomes of the students who participated in the model making exercises. The conclusions of this research will guide the structure of the upcoming iteration of the fourth year design unit.

Time-dependent analysis of length of stay and mortality due urinary tract infections in ten developing countries : INICC findings

Catheter associated urinary tract infections (CAUTI) are a worldwide problem that may lead to increased patient morbidity, cost and mortality.1e3 The literature is divided on whether there are real effects from CAUTI on length of stay or mortality. Platt4 found the costs and mortality risks to be largeyetGraves et al found the opposite.5 A reviewof the published estimates of the extra length of stay showed results between zero and 30 days.6 The differences in estimates may have been caused by the different epidemiological methods applied. Accurately estimating the effects of CAUTI is difficult because it is a time-dependent exposure. This means that standard statistical techniques, such asmatched case-control studies, tend to overestimate the increased hospital stay and mortality risk due to infection. The aim of the study was to estimate excess length of stay andmortality in an intensive care unit (ICU) due to a CAUTI, using a statistical model that accounts for the timing of infection. Data collected from ICU units in lower and middle income countries were used for this analysis.7,8 There has been little research for these settings, hence the need for this paper.

The First Steps Program : a case study of a new model of community child health service

Community Child Health Nursing Services provide support for new mothers; however, the focus has often been on individual consultations, complemented by a series of group sessions soon after birth. We describe a new model of community care for first-time mothers that centres on group sessions throughout the whole contact period. The model was developed by practicing child health nurses for a large health service district in south-east Queensland, which offers a comprehensive community child health service. Issues identified by clinicians working within existing services, feedback from clients and the need for more resource-efficient methods of service provision underpinned the development of the model. The pilot program was implemented in two community child health centres in Brisbane. An early individual consultation to engage the family with the service was added in response to feedback from clinicians and clients. The modified model has since been implemented service-wide as the ‘First Steps Program’. The introduction of this model has ensured that the service has been able to retain a comprehensive service for first-time parents from a universal population, while responding to the challenges of population growth and the increasing number of complex clients placing demands on resources.

Model-order selection in Zernike polynomial expansion of corneal surfaces using the efficient detection criterion

Corneal-height data are typically measured with videokeratoscopes and modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information-theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. In this paper, we propose to use the efficient detection criterion (EDC), which has the same general form of information-theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information-theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces.

XML documents clustering using tensor space model - A preliminary study

A hierarchical structure is used to represent the content of the semi-structured documents such as XML and XHTML. The traditional Vector Space Model (VSM) is not sufficient to represent both the structure and the content of such web documents. Hence in this paper, we introduce a novel method of representing the XML documents in Tensor Space Model (TSM) and then utilize it for clustering. Empirical analysis shows that the proposed method is scalable for a real-life dataset as well as the factorized matrices produced from the proposed method helps to improve the quality of clusters due to the enriched document representation with both the structure and the content information.

Towards an integrated model of information behavior

Information behavior models generally focus on one of many aspects of information behavior, either information finding, conceptualized as information seeking, information foraging or information sense-making, information organizing and information using. This ongoing study is developing an integrated model of information behavior. The research design involves a 2-week-long daily information journal self-maintained by the participants, combined with two interviews, one before, and one after the journal-keeping period. The data from the study will be analyzed using grounded theory to identify when the participants engage in the various behaviors that have already been observed, identified, and defined in previous models, in order to generate useful sequential data and an integrated model.

Extending Alexander’s ecological dominance-social competition (EDSC) evolutional model

Alexander’s Ecological Dominance and Social Competition (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality (Alexander, 1990; Finn, Geary & Ward, 2005; Irons, 2005). His model provides a basis for explaining the evolution of human socio-cognitive abilities. Our paper examines the extension of Alexander’s model to incorporate the human trait of information behavior in synergy with ecological dominance and social competition as a human socio-cognitive competence. This paper discusses the various interdisciplinary perspectives exploring how evolution has shaped information behavior and why information behavior is emerging as an important human socio-cognitive competence. This paper outlines these issues, including the extension of Spink and Currier’s (2006a,b) evolution of information behavior model towards a more integrated understanding of how information behaviors have evolved (Spink & Cole, 2006).

Extending Alexander’s ecological dominance-social competition model : information behavior adaptation

Alexander’s Ecological Dominance and Social Competition (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality (Alexander, 1990; Finn, Geary & Ward, 2005; Irons, 2005). His model provides a basis for explaining the evolution of human socio-cognitive abilities. Our paper examines the extension of Alexander’s model to incorporate the human trait of information behavior in synergy with ecological dominance and social competition as a human socio-cognitive competence. This paper discusses the various interdisciplinary perspectives exploring how evolution has shaped information behavior and why information behavior is emerging as an important human socio-cognitive competence. This paper outlines these issues, including the extension of Spink and Currier’s (2006a,b) evolution of information behavior model towards a more integrated understanding of how information behaviors have evolved (Spink & Cole, 2006).