Preparing pre-service teachers for classroom practice in a virtual world: A pilot study using Second Life

Many pre-service teachers feel under-prepared to teach students with a diverse range of needs and abilities and continue to be concerned about classroom behaviour management when undertaking practicum experiences. In order to address these concerns, teacher educators have explored alternative pedagogical approaches, including computer based simulations and immersion in virtual worlds. This paper reports on the results of a pilot study conducted with eight pre-service teachers who operated avatars in a virtual classroom created within Second Life (SL)™. The pre-service teachers were able to role-play students with a diverse range of behaviours and engage in reflective discussion about their experiences. The results showed that the pre-service teachers appreciated the opportunity to engage in an authentic classroom experience without impacting on "real" students, but that the platform of SL proved limiting in enacting certain aspects of desired teaching pedagogy. The findings of this pilot study are discussed in relation to improving the preparation of pre-service teachers for practicum.

Capacity-building in nonprofit organizations using blended learning as a gateway to practitioner education

Experience to date in for-profit as well as in educational settings has demonstrated that blended learning models are effective training vehicles for online instruction and workplace training. Increasingly, technology is playing a critical role in how e-learning is being delivered. Concern for the sustainability and relevance of nonprofit organizations has heightened interest in building effective capacity-building models for the sector. Because blended learning is a remarkably adaptable and fluid model, its potential for transforming capacity-building models in the nonprofit sector can be significant. Are web-based technologies enhancing capacity-building models in the Third Sector? This chapter explores the use of blended learning models within different educational environments to provide the context for asking the question: can blended learning paradigms that incorporate interactive next-generation technologies be widely accepted and implemented in the Third Sector? To establish a baseline for future studies, researchers surveyed nonprofit practitioners in Western Pennsylvania, US and Victoria, Australia. Results from three surveys conducted in 2011 reflect an awareness of the value of web-based training and education for nonprofit practitioners, but do not provide evidence of widespread usage. © 2013 Nova Science Publishers, Inc. All rights reserved.

An optimized mean variance estimation method for uncertainty quantification of wind power forecasts

A statistical optimized technique for rapid development of reliable prediction intervals (PIs) is presented in this study. The mean-variance estimation (MVE) technique is employed here for quantification of uncertainties related with wind power predictions. In this method, two separate neural network models are used for estimation of wind power generation and its variance. A novel PI-based training algorithm is also presented to enhance the performance of the MVE method and improve the quality of PIs. For an in-depth analysis, comprehensive experiments are conducted with seasonal datasets taken from three geographically dispersed wind farms in Australia. Five confidence levels of PIs are between 50% and 90%. Obtained results show while both traditional and optimized PIs are hypothetically valid, the optimized PIs are much more informative than the traditional MVE PIs. The informativeness of these PIs paves the way for their application in trouble-free operation and smooth integration of wind farms into energy systems. © 2014 Elsevier Ltd. All rights reserved.

Hierarchical Bayesian models of subtask learning

 The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking task, which logged participant actions, enabling measurement of strategy use and subtask performance. Model comparison was performed using deviance information criterion (DIC), posterior predictive checks, plots of model fits, and model recovery simulations. Results showed that although learning tended to be monotonically decreasing and decelerating, and approaching an asymptote for all subtasks, there was substantial inconsistency in learning curves both at the group- and individual-levels. This inconsistency was most apparent when constraining both the rate and the ratio of learning to asymptote to be equal across subtasks, thereby giving learning curves only 1 parameter for scaling. The inclusion of 6 strategy covariates provided improved prediction of subtask performance capturing different subtask learning processes and subtask trade-offs. In addition, strategy use partially explained the inconsistency in subtask learning. Overall, the model provided a more nuanced representation of how complex tasks can be decomposed in terms of simpler learning mechanisms.

A comprehensive method to identify the kinetics of static recrystallization using the hot torsion test results with an inverse solution

Many difficulties exist in directly following the static recrystallization of metals, particularly during hotworking. Indirect measurement of static recrystallization has been extensively performed in the literature where, for example, the recrystallization behavior of austenite in steels has commonly been measured indirectly using the fractional softening method. This method relies on the yield stress changes during recrystallization which are physically simulated by hot torsion or compression tests. However, the inherent heterogeneity of deformation during a mechanical test leads to a non-uniform static recrystallization distribution in the test sample. This, in turn, poses a serious question concerning the reliability of the measurement since the stress calculation techniques during recrystallization are not adequately developed in the existing literature. This paper develops a computer-based method to account for heterogeneous deformation during fractional softening measurements based on the hot torsion test data. The importance of the fractional softening gradient in determining the kinetics is emphasized and deficiencies in our understanding of the basic mechanisms are highlighted. A computer-based method is introduced to generate the experimental and computational components in a cost function. The cost function is then utilized by an inverse solution to calibrate the design parameters in a static recrystallization model.

In vitro simulator with numerical stress analysis for evaluation of stent-assisted coiling embolization in cerebral aneurysm treatments

There are several complications associated with Stent-assisted Coil Embolization (SACE) in cerebral aneurysm treatments, due to damaging operations by surgeons and undesirable mechanical properties of stents. Therefore, it is necessary to develop an in vitro simulator that provides both training and research for evaluating the mechanical properties of stents.

On optimally reducing power loss in micro-grids with power storage devices

Smart micro-grids can produce 'renewable' energy and store them in power storage devices. Power loss, however, is a significant problem in power exchange among the micro-grids and between the macro-station and individual micro-grids. To optimally reduce the total power losses in such a power grid system, in this paper, a greedy coalition formation algorithm is proposed, which allows the macro-station to coordinate mutual power exchange among the micro-grids and between each micro-grid and the macro-station. Our algorithm optimizes the total power losses across the entire power grid, including the cost of charging and discharging power storage devices and power losses due to power transfers. The algorithm creates exchange pairs among the micro-grids, giving priority to pairs with higher power loss reduction per exchanged power unit. Through computer-based simulations, we demonstrate that the proposed approach significantly reduces the average power loss compared with the conventional noncooperative method. The simulations also demonstrate that the communications overhead of our proposal (due to negotiations aimed at forming coalitions) does not significantly affect the available communication resource. © 2014 IEEE.

A randomised controlled trial investigating the effects of Mediterranean diet and aerobic exercise on cognition in cognitively healthy older people living independently within aged care facilities: The Lifestyle Intervention in Independent Living Aged Car

Background: The rapid ageing of the population is becoming an area of great concern, both globally and in Australia. On a societal level, the cost of supporting an ageing demographic, particularly with their associated medical requirements, is becoming an ever increasing burden that is only predicted to rise in the foreseeable future. The progressive decline in individuals' cognitive ability as they age, particularly with respect to the ever increasing incidence of Alzheimer's Disease (AD) and other cognitive complications, is in many respects one of the foundation stones of these concerns. There have been numerous observational studies reporting on the positive effects that aerobic exercise and the Mediterranean diet appear to have on improving cognitive ability. However, the ability of such interventions to improve cognitive ability, or even reduce the rate of cognitive ageing, has not been fully examined by substantial interventional studies within an ageing population. Methods: The LIILAC trial will investigate the potential for cognitive change in a cohort of cognitively healthy individuals, between the ages of 60 and 90 years, living in independent accommodation within Australian aged care facilities. This four-arm trial will investigate the cognitive changes which may occur as a result of the introduction of aerobic exercise and/or Mediterranean diet into individuals' lifestyles, as well as the mechanisms by which these changes may be occurring. Participants will be tested at baseline and 6 months on a battery of computer based cognitive assessments, together with cardiovascular and blood biomarker assessments. The cardiovascular measures will assess changes in arterial stiffness and central pulse pressures, while the blood measures will examine changes in metabolic profiles, including brain derived neurotrophic factor (BDNF), inflammatory factors and insulin sensitivity. Conclusion: It is hypothesised that exercise and Mediterranean diet interventions, both individually and in combination, will result in improvements in cognitive performance compared with controls. Positive findings in this research will have potential implications for the management of aged care, particularly in respect to reducing the rate of cognitive decline and the associated impacts both on the individual and the broader community.

Future integrated factories: a system of systems engineering perspective

The manufacturing sector has gone through tremendous change in the last decade. We have witnessed the transformation from stand alone, manual processes to smart and integrated systems, from hand written reports to interactive computer-based dashboards. Future integrated factories will operate as a system of systems through intelligent machines, human factors integration, and integrated supply chains. To effectively operate and manage these emerging enterprises, a systems science approach is required. Modelling and simulation is recognised as a key enabling technology, with application from stakeholder engagement and knowledge elicitation to operational decision support through self-tuning and self-assembling simulations. Our research has led to the introduction of effective modelling and simulation methods and tools to enable real time planning, dynamic risk analysis and effective visualisation for production processes, resources and systems. This paper discusses industrial applicable concepts for real-time simulation and decision support, and the implications to future integrated factories, or factories of the future, are explored through relevant case studies from aerospace manufacturing to mining and materials processing enterprises.

The status and function of Inanimate 'object-actors' in cyborg theatre

 This practice-led research investigates the relationships between human and technological actors in theatre with specific reference to theatrical presence.The research proposes to advance knowledge in the fields of directing and theatre making by putting forward new strategies for directing actors who perform with computer-based technologies.

Influence of body mass index on prescribing costs and potential cost savings of a weight management programme in primary care

Objectives Prescribed medications represent a high and increasing proportion of UK health care funds. Our aim was to quantify the influence of body mass index (BMI) on prescribing costs, and then the potential savings attached to implementing a weight management intervention.

Methods Paper and computer-based medical records were reviewed for all drug prescriptions over an 18-month period for 3400 randomly selected adult patients (18–75 years) stratified by BMI, from 23 primary care practices in seven UK regions. Drug costs from the British National Formulary at the time of the review were used. Multivariate regression analysis was applied to estimate the cost for all drugs and the ‘top ten’ drugs at each BMI point. This allowed the total and attributable prescribing costs to be estimated at any BMI. Weight loss outcomes achieved in a weight management programme (Counterweight) were used to model potential effects of weight change on drug costs. Anticipated savings were then compared with the cost programme delivery. Analysis was carried out on patients with follow-up data at 12 and 24 months as well as on an intention-to-treat basis. Outcomes from Counterweight were based on the observed lost to follow-up rate of 50%, and the assumption that those patients would continue a generally observed weight gain of 1 kg per year from baseline.

Results The minimum annual cost of all drug prescriptions at BMI 20 kg/m2 was £50.71 for men and £62.59 for women. Costs were greater by £5.27 (men) and £4.20 (women) for each unit increase in BMI, to a BMI of 25 (men £77.04, women £78.91), then by £7.78 and £5.53, respectively, to BMI 30 (men £115.93 women £111.23), then by £8.27 and £4.95 to BMI 40 (men £198.66, women £160.73). The relationship between increasing BMI and costs for the top ten drugs was more pronounced. Minimum costs were at a BMI of 20 (men £8.45, women £7.80), substantially greater at BMI 30 (men £23.98, women £16.72) and highest at BMI 40 (men £63.59, women £27.16). Attributable cost of overweight and obesity accounted for 23% of spending on all drugs with 16% attributable to obesity. The cost of the programme was estimated to be approximately £60 per patient entered. Modelling weight reductions achieved by the Counterweight weight management programme would potentially reduce prescribing costs by £6.35 (men) and £3.75 (women) or around 8% of programme costs at one year, and by £12.58 and £8.70, respectively, or 18% of programme costs after two years of intervention. Potential savings would be increased to around 22% of the cost of the programme at year one with full patient retention and follow-up.

Conclusion Drug prescriptions rise from a minimum at BMI of 20 kg/m2 and steeply above BMI 30 kg/m2. An effective weight management programme in primary care could potentially reduce prescription costs and lead to substantial cost avoidance, such that at least 8% of the programme delivery cost would be recouped from prescribing savings alone in the first year.

GTES: An optimized game-theoretic demand-side management scheme for smart grid

Demand-side management in smart grids has emerged as a hot topic for optimizing energy consumption. In conventional research works, energy consumption is optimized from the perspective of either the users or the power company. In this paper, we investigate how energy consumption may be optimized by taking into consideration the interaction between both parties. We propose a new energy price model as a function of total energy consumption. Also, we propose a new objective function, which optimizes the difference between the value and cost of energy. The power supplier pulls consumers in a round-robin fashion and provides them with energy price parameter and current consumption summary vector. Each user then optimizes his own schedule and reports it to the supplier, which, in turn, updates its energy price parameter before pulling the next consumers. This interaction between the power company and its consumers is modeled through a two-step centralized game, based on which we propose our game-theoretic energy schedule (GTES) method. The objective of our GTES method is to reduce the peak-to-average power ratio by optimizing the users' energy schedules. The performance of the GTES approach is evaluated through computer-based simulations. © 2014 IEEE.

A machine-driven process for human limb length estimation using inertial sensors

The computer based human motion tracking systems are widely used in medicine and sports. The accurate determination of limb lengths is crucial for not only constructing the limb motion trajectories which are used for evaluation process of human kinematics, but also individually recognising human beings. Yet, as the common practice, the limb lengths are measured manually which is inconvenient, time-consuming and requires professional knowledge. In this paper, the estimation process of limb lengths is automated with a novel algorithm calculating curvature using the measurements from inertial sensors. The proposed algorithm was validated with computer simulations and experiments conducted with four healthy subjects. The experiment results show the significantly low root mean squared error percentages such as upper arm - 5.16%, upper limbs - 5.09%, upper leg - 2.56% and lower extremities - 6.64% compared to measured lengths.

Effects of low- versus high-fidelity simulations on the cognitive burden and performance of entry-level paramedicine students: a mixed-methods comparison trial using eye-tracking, continuous heart rate, difficulty rating scales, video observation and inte

INTRODUCTION: High-fidelity simulation-based training is often avoided for early-stage students because of the assumption that while practicing newly learned skills, they are ill suited to processing multiple demands, which can lead to "cognitive overload" and poorer learning outcomes. We tested this assumption using a mixed-methods experimental design manipulating psychological immersion. METHODS: Thirty-nine randomly assigned first-year paramedicine students completed low- or high-environmental fidelity simulations [low-environmental fidelity simulations (LFenS) vs. high-environmental fidelity simulation (HFenS)] involving a manikin with obstructed airway (SimMan3G). Psychological immersion and cognitive burden were determined via continuous heart rate, eye tracking, self-report questionnaire (National Aeronautics and Space Administration Task Load Index), independent observation, and postsimulation interviews. Performance was assessed by successful location of obstruction and time-to-termination. RESULTS: Eye tracking confirmed that students attended to multiple, concurrent stimuli in HFenS and interviews consistently suggested that they experienced greater psychological immersion and cognitive burden than their LFenS counterparts. This was confirmed by significantly higher mean heart rate (P < 0.001) and National Aeronautics and Space Administration Task Load Index mental demand (P < 0.05). Although group allocation did not influence the proportion of students who ultimately revived the patient (58% vs. 30%, P < 0.10), the HFenS students did so significantly more quickly (P < 0.01). The LFenS students had low immersion resulting in greater assessment anxiety. CONCLUSIONS: High-environmental fidelity simulation engendered immersion and a sense of urgency in students, whereas LFenS created assessment anxiety and slower performance. We conclude that once early-stage students have learned the basics of a clinical skill, throwing them in the "deep end" of high-fidelity simulation creates significant additional cognitive burden but this has considerable educational merit.