AITSL pilot projects [Queensland University of Technology : The existing school-based practices and processes for the use of NAPLAN data] Final report

This pilot project investigated the existing practices and processes of Proficient, Highly Accomplished and Lead teachers in the interpretation, analysis and implementation of National Assessment Program – Literacy and Numeracy (NAPLAN) data. A qualitative case study approach was the chosen methodology, with nine teachers across a variety of school sectors interviewed. Themes and sub-themes were identified from the participants’ interview responses revealing the ways in which Queensland teachers work with NAPLAN data. The data illuminated that generally individual schools and teachers adopted their own ways of working with data, with approaches ranging from individual/ad hoc, to hierarchical or a whole school approach. Findings also revealed that data are the responsibility of various persons from within the school hierarchy; some working with the data electronically whilst others rely on manual manipulation. Manipulation of data is used for various purposes including tracking performance, value adding and targeting programmes for specific groups of students, for example the gifted and talented. Whilst all participants had knowledge of intervention programmes and how practice could be modified, there were large inconsistencies in knowledge and skills across schools. Some see the use of data as a mechanism for accountability, whilst others mention data with regards to changing the school culture and identifying best practice. Overall, the findings showed inconsistencies in approach to focus area 5.4. Recommendations therefore include a more national approach to the use of educational data.

Recent advances in modeling the vulnerability of transportation networks

It is well known that, for major infrastructure networks such as electricity, gas, railway, road, and urban water networks, disruptions at one point have a knock on effect throughout the network. There is an impressive amount of individual research projects examining the vulnerability of critical infrastructure network. However, there is little understanding of the totality of the contribution made by these projects and their interrelationships. This makes their review a difficult process for both new and existing researchers in the field. To address this issue, a two-step literature review process is used, to provide an overview of the vulnerability of the transportation network in terms of four main themes - research objective, transportation mode, disruption scenario and vulnerability indicator –involving the analysis of related articles from 2001 to 2013. Two limitations of existing research are identified: (1) the limited amount of studies relating to multi-layer transportation network vulnerability analysis, and (2) the lack of evaluation methods to explore the relationship between structure vulnerability and dynamical functional vulnerability. In addition to indicating that more attention needs to be paid to these two aspects in future, the analysis provides a new avenue for the discovery of knowledge, as well as an improved understanding of transportation network vulnerability.

Modeling and control of a CLC resonant dual active bridge

This paper proposes a linear large signal state-space model for a phase controlled CLC (Capacitor Inductor Capacitor) Resonant Dual Active Bridge (RDAB). The proposed model is useful for fast simulation and for the estimation of state variables under large signal variation. The model is also useful for control design because the slow changing dynamics of the dq variables are relatively easy to control. Simulation results of the proposed model are presented and compared to the simulated circuit model to demonstrate the proposed model's accuracy. This proposed model was used for the design of a Proportional-Integral (PI) controller and it has been implemented in the circuit simulation to show the proposed models usefulness in control design.

A conceptual approach to track design changes within a multi-disciplinary BIM environment

Successful management of design changes is critical for the efficient delivery of construction projects. Building Information Modeling (BIM) is envisioned to play an important role in integrating design, construction and facility management processes through coordinated changes throughout the project life-cycle. BIM currently provides significant benefits in coordinating changes across different views in a single model, and identifying conflicts between different discipline-specific models. However, current BIM tools provide limited support in managing changes across several discipline-specific models. This paper describes an approach to represent, coordinate, and track changes within a collaborative multi-disciplinary BIM environment. This approach was informed by a detailed case study of a large, complex, fast-tracked BIM project where we investigated numerous design changes, analyzed change management processes, and evaluated existing BIM tools. Our approach characterises design changes in an ontology to represent changed component attributes, dependencies between components, and change impacts. It explores different types of dependencies amongst different design changes and describes how a graph based approach and dependency matrix could assist with automating the propagation and impact of changes in a BIM-based project delivery process.

Understanding Formal and Informal Governance on Infrastructure Projects - Literature Review [industry report]

In Australia, collaborative contracts have been increasingly used to govern infrastructure projects. These contracts combine formal and informal mechanisms to manage project delivery. Formal mechanisms (e.g. financial risk sharing) are specified in the contract, while informal mechanisms (e.g. integrated team) are not. The paper reports on a literature review to operationalise the concepts of formal and informal governance, as the literature contains a multiplicity of, often un-testable, definitions. This work is the first phase of a study that will examine the optimal balance of formal and informal governance structures. Desk-top review of leading journals in the areas of construction management and business management, as well as recent government documents and industry guidelines, was undertaken to to conceptualise and operatinalise formal and informal governance mechanisms. The study primarily draws on transaction-cost economics (e.g. Williamson 1979; 1991), relational contract theory (Feinman 2000; Macneil 2000) and social psychology theory (e.g. Gulati 1995). Content analysis of the literature was undertaken to identify key governance mechanisms. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. Formal governance mechanisms were found to be usefully broken down into four measurable categories: (1) target cost arrangement (2) financial risk and reward sharing regime (3) transparent financials and (4) collaborative multi-party agreement Informal governance mechanisms were found to be usefully broken down into three measurable categories: (1) leadership structure (2) integrated team (3) joint management system We expect these categories to effectively capture the key governance drivers of outcomes on infrastructure projects. These categories will be further refined and broken down into individual governance mechanisms for assessment through a large-scale Australian survey planned for late 2012. These individual mechanisms will feature in the questionnaire that QUT will deliver to AAA in October 2012.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Modeling and control of a 3500 tonne mining robot

Draglines are extremely large machines that are widely used in open-cut coal mines for overburden stripping. Since 1994 we have been working toward the development of a computer control system capable of automatically driving a dragline for a large portion of its operating cycle. This has necessitated the development and experimental evaluation of sensor systems, machines models, closed-loop control controllers, and an operator interface. This paper describes our steps toward the goal through scale-model and full-scale field experimentation.

Investigating the impact of project definition clarity on project performance: Structural equation modeling study

Having a clear project definition is crucial for successful construction projects. It affects design quality, project communication between stakeholders and final project performance in terms of cost, schedule and quality. This study examines the relationship between project definition and final project performance through a structural equation model comprising 4 latent constructs and 6 path hypotheses using data from a questionnaire survey of 120 general contractors in the Malaysian construction industry. The results show that in the study population, all three items impact the project performance, but the link between design quality and project performance is indirect. Instead, the clarity of project definition affects project performance indirectly through design quality and project communication and design quality affects project performance indirectly through project communication. The primary contribution is to provide quantitative confirmation of the more general statements made in the literature from around the world and therefore adds to and consolidates existing knowledge. Practical implications derived from the finding are also proposed for various project stakeholders. Furthermore, as lack of the clarity of project definition is a very common occurrence in construction projects globally, these findings have important ramifications for all construction projects in expanding and clarifying existing knowledge on what is needed for the successful delivery of construction projects.

Numerical modeling of thin steel roof battens under wind uplift loads

Extreme wind events such as tropical cyclones, tornadoes and storms are more likely to impact the Australian coastal regions due to possible climate changes. Such events can be extremely destructive to building structures, in particular, low-rise buildings with lightweight roofing systems that are commonly made of thin steel roofing sheets and battens. Large wind uplift loads that act on the roofs during high wind events often cause premature roof connection failures. Recent wind damage investigations have shown that roof failures have mostly occurred at the batten to rafter or truss screw connections. In most of these cases, the screw fastener heads pulled through the bottom flanges of thin steel roof battens. This roof connection failure is very critical as both roofing sheets and battens will be lost during the high wind events. Hence, a research study was conducted to investigate this critical pull-through failure using both experimental and numerical methods. This paper presents the details of numerical modeling and the results.

Community engagement or community conversation?: Boomtown, a large-scale regional, outdoor community theatrical event

On the 18th of July 2013, three hundred local members of Gladstone, Queensland erupted into song and dance performing the fraught history of their community harbourside through tug boat ballets, taiko drumming, German bell ringing and BMX bike riding. Over 17,500 people attended the four performances of Boomtown, a Queensland Music Festival event. This was the largest regional, outdoor community-engaged musical performance staged in Australia. The narrative moved beyond the dominant, pejorative view of Gladstone as an industrial town to include the community members’ sense of purpose and aspirations. It was a celebratory, contentious and ambitious project that sought to disrupt the traditional conventions of performance-making through working in artistically democratic ways. This article explores the potential for Australian Community Engaged Arts (CEA) projects such as Boomtown to democratically engage community members and co-create culturally meaningful work within a community. Research into CEA projects rarely consider how the often delicate conversations between practitioners and the community work. The complex processes of finding and co-writing the narrative, casting, and rehearsing Boomtown are discussed with reference to artistic director/dramaturge Sean Mee’s innovative approaches. Boomtown began with and concluded with community conversations. Skilful negotiation ensured congruence between the townspeople’s stories and the “community story” presented on stage, abrogating potential problems of narrative ownership. To supplement the research, twenty-one personal interviews were undertaken with Gladstone community members invested in the production before, during and after the project: performers, audience members and local professionals. The stories shared and emphasised in the theatricalised story were based on propitious, meaningful, local stories from lived experiences rather than preconceived, trivial or tokenistic matters, and were underpinned by a consensus formed on what was in the best interests of the majority of community members. Boomtown exposed hidden issues in the community and gave voice to thoughts, feelings and concerns which triggered not just engagement, but honest conversation within the community.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Client learning and the performance of collaborative infrastructure projects

Australia is a leading user of collaborative procurement methods, which are used to deliver large and complex infrastructure projects. Project alliances, Early Contractor Involvement (ECI), and partnering are typical examples of collaborative procurement models. In order to increase procurement effectiveness and value for money (VfM), clients have adopted various learning strategies for new contract development. However client learning strategies and behaviours have not been systematically analysed before. Therefore, the current paper undertakes a literature review addressing the research question “How can client learning capabilities be effectively understood?”. From the resource-based and dynamic capability perspectives, this paper proposes that the collaborative learning capability (CLC) of clients drives procurement model evolution. Learning routines underpinning CLC carry out exploratory, transformative and exploitative learning phases associated with collaborative project delivery. This learning improves operating routines, and ultimately performance. The conceptualization of CLC and the three sequential learning phases is used to analyse the evidence in the construction management literature. The main contribution of this study is the presentation of a theoretical foundation for future empirical studies to unveil effective learning strategies, which help clients to improve the performance of collaborative projects in the dynamic infrastructure market.

Time and cost performance of design–build projects

The design-build (DB) delivery method has been widely used in the United States due to its reputed superior cost and time performance. However, rigorous studies have produced inconclusive support and only in terms of overall results, with few attempts being made to relate project characteristics with performance levels. This paper provides a larger and more finely grained analysis of a set of 418 DB projects from the online project database of the Design-Build Institute of America (DBIA), in terms of the time-overrun rate (TOR), early start rate (ESR), early completion rate (ECR) and cost overrun rate (COR) associated with project type (e.g., commercial/institutional buildings and civil infrastructure projects), owners (e.g., Department of Defense and private corporations), procurement methods (e.g., ‘best value with discussion’ and qualifications-based selection), contract methods (e.g., lump sum and GMP) and LEED levels (e.g., gold and silver). The results show ‘best value with discussion’ to be the dominant procurement method and lump sum the most frequently used contract method. The DB method provides relatively good time performance, with more than 75% of DB projects completed on time or before schedule. However, with more than 50% of DB projects cost overrunning, the DB advantage of cost saving remains uncertain. ANOVA tests indicate that DB projects within different procurement methods have significantly different time performance and that different owner types and contract methods significantly affect cost performance. In addition to contributing to empirical knowledge concerning the cost and time performance of DB projects with new solid evidence from a large sample size, the findings and practical implications of this study are beneficial to owners in understanding the likely schedule and budget implications involved for their particular project characteristics.

Data driven modeling for power transformer lifespan evaluation

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation’s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.

Cardiovascular diseases and vulnerable plaques: data, modeling, predictions and clinical applications PREFACE

Introduction Two symposia on “cardiovascular diseases and vulnerable plaques” Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, bio- mechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these dis- eases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on “Cardio-vascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications.” One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.