“More tick-the-box”: the challenge of promoting interdisciplinary learning in the middle years through the Australian history curriculum

The Australian Curriculum marks national reforms in social science education, first with the return to the disciplines of history and geography and second, through a new approach to interdisciplinary learning. This paper raises the question of whether the promise of interdisciplinary learning can be realised in the middle years of schooling if teachers have to teach history as a discipline rather than within an over-arching integrated curriculum framework. The paper explores the national blueprints and considers the national history curriculum in light of theories of teachers’ knowledge and middle school education. Evidence from teacher interviews indicates that historical understanding can be achieved through integrated frameworks to meet the goals of middle schooling.

Top Ten Box Office Blockbusters of All Time

‘Top Ten Box Office Blockbusters in Dollars’, is an ongoing series of works that represent the production budgets and worldwide gross profits of the top ten grossing films of all time. By displaying this data on top of the full running time of each blockbuster, the viewer’s attention is drawn back and forth between the amassing dollar figures, and the original film’s highly polished presentation. In doing so, the work aims to provide a new opportunity to enjoy these immensely popular films with a new sense of value. The exhibition was selected for the Artistic Program at MetroArts, Brisbane in 2010

Unlocking black box models of leadership effectiveness: Exploring alternative research and policy metaphors

There is an intimate interconnectivity between policy guidelines defining reform and the delineation of what research methods would be subsequently applied to determine reform success. Research is guided as much by the metaphors describing it as by the ensuing empirical definition of actions of results obtained from it. In a call for different reform policy metaphors Lumby and English (2010) note, “The primary responsibility for the parlous state of education... lies with the policy makers that have racked our schools with reductive and dehumanizing processes, following the metaphors of market efficiency, and leadership models based on accounting and the characteristics of machine bureaucracy” (p. 127)

Understanding user experience of mobile video : framework, measurement, and optimization

Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study.

Optimal sitting and sizing of distributed generators considering plug-in electric vehicles

Some uncertainties such as the stochastic input/output power of a plug-in electric vehicle due to its stochastic charging and discharging schedule, that of a wind unit and that of a photovoltaic generation source, volatile fuel prices and future uncertain load growth, all together could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distributed systems. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal sitting and sizing problem of DGs. First, a mathematical model of CCP is developed with the minimization of DGs investment cost, operational cost and maintenance cost as well as the network loss cost as the objective, security limitations as constraints, the sitting and sizing of DGs as optimization variables. Then, a Monte Carolo simulation embedded genetic algorithm approach is developed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is employed to verify the feasibility and effectiveness of the developed model and method. This work is supported by an Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Project on Intelligent Grids Under the Energy Transformed Flagship, and Project from Jiangxi Power Company.

What's in your tool box?

This is a professional practice paper for Psychology practitioners to reflect on their skills and therapeutic practices. A Master- practitioner model or Artizan - apprentice analogy is used to understand the development of a practicing psychologist from his/her "salad days" (when we are green [Shakespeare- Anthony and Cleopatra]) to our Autumn years in the profession.

Development of a transformation system for sorghum (Sorghum bicolor L.)

Sorghum (Sorghum bicolor (L.) Moench) is the world’s fifth major cereal crop and holds importance as a construction material, food and fodder source. More recently, the potential of this plant as a biofuel source has been noted. Despite its agronomic importance, the use of sorghum production is being constrained by both biotic and abiotic factors. These challenges could be addressed by the use of genetic engineering strategies to complement conventional breeding techniques. However, sorghum is one of the most recalcitrant crops for genetic modification with the lack of an efficient tissue culture system being amongst the chief reasons. Therefore, the aim of this study was to develop an efficient tissue culture system for establishing regenerable embryogenic cell lines, micropropagation and acclimatisation for Sorghum bicolor and use this to optimise parameters for genetic transformation via Agrobacterium-mediated transformation and microprojectile bombardment. Using five different sorghum cultivars, SA281, 296B, SC49, Wray and Rio, numerous parameters were investigated in an attempt to establish an efficient and reproducible tissue culture and transformation system. Using immature embryos (IEs) as explants, regenerable embryogenic cell lines (ECLs) could only be established from cultivars SA281 and 296B. Large amounts of phenolics were produced from IEs of cultivars, SC49, Wary and Rio, and these compounds severely hindered callus formation and development. Cultivar SA281 also produced phenolics during regeneration. Attempts to suppress the production of these compounds in cultivars SA281 and SC49 using activated charcoal, PVP, ascorbic acid, citric acid and liquid filter paper bridge methods were either ineffective or had a detrimental effect on embryogenic callus formation, development and regeneration. Immature embryos sourced during summer were found to be far more responsive in vitro than those sourced during winter. In an attempt to overcome this problem, IEs were sourced from sorghum grown under summer conditions in either a temperature controlled glasshouse or a growth chamber. However, the performance of these explants was still inferior to that of natural summer-sourced explants. Leaf whorls, mature embryos, shoot tips and leaf primordia were found to be unsuitable as explants for establishing ECLs in sorghum cultivars SA281 and 296B. Using the florets of immature inflorescences (IFs) as explants, however, ECLs were established and regenerated for these cultivars, as well as for cultivar Tx430, using callus induction media, SCIM, and regeneration media, VWRM. The best in vitro responses, from the largest possible sized IFs, were obtained using plants at the FL-2 stage (where the last fully opened leaf was two leaves away from the flag leaf). Immature inflorescences could be stored at 25oC for up to three days without affecting their in vitro responses. Compared to IEs, the IFs were more robust in tissue culture and showed responses which were season and growth condition independent. A micropropagation protocol for sorghum was developed in this study. The optimum plant growth regulator (PGR) combination for the micropropagation of in vitro regenerated plantlets was found to be 1.0 mg/L BAP in combination with 0.5 mg/L NAA. With this protocol, cultivars 296B and SA281 produced an average of 57 and 13 off-shoots per plantlet, respectively. The plantlets were successfully acclimatised and developed into phenotypically normal plants that set seeds. A simplified acclimatisation protocol for in vitro regenerated plantlets was also developed. This protocol involved deflasking in vitro plantlets with at least 2 fully-opened healthy leaves and at least 3 roots longer than 1.5 cm, washing the media from the roots with running tap water, planting in 100 mm pots and placing in plastic trays covered with a clear plastic bag in a plant growth chamber. After seven days, the corners of the plastic cover were opened and the bags were completely removed after 10 days. All plantlets were successfully acclimatised regardless of whether 1:1 perlite:potting mix, potting mix, UC mix or vermiculite were used as potting substrates. Parameters were optimised for Agrobacterium-mediated transformation (AMT) of cultivars SA281, 296B and Tx430. The optimal conditions were the use of Agrobacterium strain LBA4404 at an inoculum density of 0.5 OD600nm, heat shock at 43oC for 3 min, use of the surfactant Pluronic F-68 (0.02% w/v) in the inoculation media with a pH of 5.2 and a 3 day co-cultivation period in dark at 22oC. Using these parameters, high frequencies of transient GFP expression was observed in IEs precultured on callus initiation media for 1-7 days as well as in four weeks old IE- and IF-derived callus. Cultivar SA281 appeared very sensitive to Agrobacterium since all tissue turned necrotic within two weeks post-exposure. For cultivar 296B, GFP expression was observed up to 20 days post co-cultivation but no stably transformed plants were regenerated. Using cultivar Tx430, GFP was expressed for up to 50 days post co-cultivation. Although no stably transformed plants of this cultivar were regenerated, this was most likely due to the use of unsuitable regeneration media. Parameters were optimised for transformation by particle bombardment (PB) of cultivars SA281, 296B and Tx430. The optimal conditions were use of 3-7 days old IEs and 4 weeks old IF callus, 4 hour pre- and post-bombardment osmoticum treatment, use of 0.6 µm gold microparticles, helium pressure of 1500 kPa and target distance of 15 cm. Using these parameters for PB, transient GFP expression was observed for up to 14, 30 and 50 days for cultivars SA281, 296B and Tx430, respectively. Further, the use of PB resulted in less tissue necrosis compared to AMT for the respective cultivars. Despite the presence of transient GFP expression, no stably transformed plants were regenerated. The establishment of regenerable ECLs and the optimization of AMT and PB parameters in this study provides a platform for future efforts to develop an efficient transformation protocol for sorghum. The development of GM sorghum will be an important step towards improving its agronomic properties as well as its exploitation for biofuel production.

Composite SaaS placement and resource optimization in Cloud computing using evolutionary algorithms

Software as a Service (SaaS) is gaining more and more attention from software users and providers recently. This has raised many new challenges to SaaS providers in providing better SaaSes that suit everyone needs at minimum costs. One of the emerging approaches in tackling this challenge is by delivering the SaaS as a composite SaaS. Delivering it in such an approach has a number of benefits, including flexible offering of the SaaS functions and decreased cost of subscription for users. However, this approach also introduces new problems for SaaS resource management in a Cloud data centre. We present the problem of composite SaaS resource management in Cloud data centre, specifically on its initial placement and resource optimization problems aiming at improving the SaaS performance based on its execution time as well as minimizing the resource usage. Our approach differs from existing literature because it addresses the problems resulting from composite SaaS characteristics, where we focus on the SaaS requirements, constraints and interdependencies. The problems are tackled using evolutionary algorithms. Experimental results demonstrate the efficiency and the scalability of the proposed algorithms.

Multi-objective design optimization of morphing UAV aerofoil/wing using hybridised MOGA

The paper investigates two advanced Computational Intelligence Systems (CIS) for a morphing Unmanned Aerial Vehicle (UAV) aerofoil/wing shape design optimisation. The first CIS uses Genetic Algorithm (GA) and the second CIS uses Hybridized GA (HGA) with the concept of Nash-Equilibrium to speed up the optimisation process. During the optimisation, Nash-Game will act as a pre-conditioner. Both CISs; GA and HGA, are based on Pareto optimality and they are coupled to Euler based Computational Fluid Dynamic (CFD) analyser and one type of Computer Aided Design (CAD) system during the optimisation.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Smart grid-demand side response model for optimization air conditioning

The growing demand of air-conditioning is one of the largest contributors to Australia’s overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission.