Development of an integrated GIS and land use planning course : impacts of hybrid instructional methods

This study reports an action research undertaken at Queensland University of Technology. It evaluates the effectiveness of the integration of GIS within the substantive domains of an existing land use planning course in 2011. Using student performance, learning experience survey, and questionnaire survey data, it also evaluates the impacts of incorporating hybrid instructional methods (e.g., in-class and online instructional videos) in 2012 and 2013. Results show that: students (re)iterated the importance of GIS in the course justifying the integration; the hybrid methods significantly increased student performance; and unlike replacement, the videos are more suitable as a complement to in-class activity.

Strategies for rapid congestion recovery using ramp metering

This research investigated strategies for motorway congestion management from a different angle: that is, how to quickly recover motorway from congestion at the end of peak hours, given congestion cannot be eliminated due to excessive demand during the long peak hours nowadays. The project developed a zone recovery strategy using ramp metering for rapid congestion recovery, and a serious of traffic simulation investigations were included to evaluate the developed strategy. The results, from both microscopic and macroscopic simulation, demonstrated the effectiveness of the zone recovery strategy.

Breastfeeding self-efficacy of women using second-line strategies for healthy term infants in the first week postpartum : an Australian observational study

Background Breastfeeding self-efficacy (BFSE) supports breastfeeding initiation and duration. Challenges to breastfeeding may undermine BFSE, but second-line strategies including nipple shields, syringe, cup, supply line and bottle feeding may support breastfeeding until challenges are resolved. The primary aim of this study was to examine BFSE in a sample of women using second-line strategies for feeding healthy term infants in the first week postpartum. Methods A retrospective self-report study was conducted using the Breastfeeding Self-Efficacy Scale - Short Form (BSES-SF), demographic and infant feeding questionnaires. Breastfeeding women who gave birth to a singleton healthy term infant at one private metropolitan birthing facility in Australia from November 2008 to February 2009 returned anonymous questionnaires by mail. Results A total of 128 (73 multiparous, 55 primiparous) women participated in the study. The mean BSES-SF score was 51.18 (Standard deviation, SD: 12.48). The median BSES-SF score was 53. Of women using a second-line strategy, 16 exceeded the median, and 42 were below. Analyses using Kruskal-Wallis tests confirmed this difference was statistically significant (H = 21.569, p = 0.001). The rate of second-line strategy use was 48%. The four most commonly used second-line strategies were: bottles with regular teats (77%); syringe feeding (44%); bottles with wide teats (34%); and nipple shields (27%). Seven key challenges were identified that contributed to the decision to use second-line strategies, including: nipple pain (40%); unsettled infant (40%); insufficient milk supply (37%); fatigue (37%); night nursery care (25%); infant weight loss > 10% (24%); and maternal birth associated pain (20%). Skin-to-skin contact at birth was commonly reported (93%). At seven days postpartum 124 women (97%) were continuing to breastfeed. Conclusions The high rate of use of second-line strategies identified in this study and high rate of breastfeeding at day seven despite lower BFSE indicate that such practices should not be overlooked by health professionals. The design of this study does not enable determination of cause-effect relationships to identify factors which contribute to use of second-line strategies. Nevertheless, the significantly lower BSES-SF score of women using a second-line strategy highlights this group of women have particular needs that require attention.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Power sharing control with frequency droop in a hybrid microgrid

A microgrid may contain a large number of distributed generators (DGs). These DGs can be either inertial or non-inertial, either dispatchable or non-dispatchable. Moreover, the DGs may operate in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new control algorithm for converter interfaced (dispatchable) DG is proposed which facilitates smooth operation in a hybrid microgrid containing inertial and non-inertial DGs. The control algorithm works satisfactorily even when some of the DGs operate in plug and play mode. The proposed strategy is validated through PSCAD simulation studies.

Not just another ball game : young adult and adult football fictions are different

Current media attention on the crossover novel highlights the increasing permeability of the boundaries between young adult and adult fiction. This paper will focus upon some of the difficulties around definitions of young adult fiction before considering the fiction of football, or soccer as it is more commonly known in Australia. The football genre exhibits a number of discrete and identifiable differences between young adult and adult readerships including, for example, the role of the protagonist, and the narrative’s distance from the game. This paper will use Franco Moretti’s Mapping as Distant Reading model of abstraction to highlight and unpack these and other characteristic differences in the narratological and stylistic techniques employed across adult and young adult texts. Close reading analysis of the adult football fiction Striker (1992) by Hunter Davies and young adult football fiction Lucy Zeezou’s Goal (2008) by Liz Deep-Jones’ will further illustrate the range of tensions and divergences as they are reflected across those readerships. The texts have been selected because they speak to themes of fear and safety; Joe Swift (Striker) is driven by a need to move away from childhood poverty and insecurity, while Lucy Zeezou shelters a homeless friend. With both protagonists being kidnapped for ransom for example, the texts have also been selected for their striking similarities in form and content.

Residential voltage dip and swell mitigation using Plug-in Hybrid Electric Vehicle in smart grid

Solutions to remedy the voltage disturbances have been mostly suggested only for industrial customers. However, not much research has been done on the impact of the voltage problems on residential facilities. This paper proposes a new method to reduce the effect of voltage dip and swell in smart grids equipped by communication systems. To reach this purpose, a voltage source inverter and the corresponding control system are employed. The behavior of a power system during voltage dip and swell are analyzed. The results demonstrate reasonable improvement in terms of voltage dip and swell mitigation. All simulations are implemented in MATLAB/Simulink environment.

A phase-locked-loop design for the smooth operation of a hybrid microgrid

A microgrid contains both distributed generators (DGs) and loads and can be viewed by a controllable load by utilities. The DGs can be either inertial synchronous generators or non-inertial converter interfaced. Moreover, some of them can come online or go offline in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new phase locked loop (PLL) algorithm is proposed for smooth synchronization of plug and play DGs. A frequency droop for power sharing is used and a pseudo inertia has been introduced to non-inertial DGs in order to match their response with inertial DGs. The proposed strategy is validated through PSCAD simulation studies.

Hybrid multi-channel cooperative spectrum sensing to satisfy channel target

Spectrum sensing of multiple primary user channels is a crucial function in cognitive radio networks. In this paper we propose an optimal, sensing resource allocation algorithm for multi-channel cooperative spectrum sensing. The channel target is implemented as an objective and constraint to ensure a pre-determined number of empty channels are detected for secondary user network operations. Based on primary user traffic parameters, we calculate the minimum number of primary user channels that must be sensed to satisfy the channel target. We implement a hybrid sensing structure by grouping secondary user nodes into clusters and assign each cluster to sense a different primary user channels. We then solve the resource allocation problem to find the optimal sensing configuration and node allocation to minimise sensing duration. Simulation results show that the proposed algorithm requires the shortest sensing duration to achieve the channel target compared to existing studies that require long sensing and cannot guarantee the target.

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K-means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley’s Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.

An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

Control strategies to prevent total hip replacement-related infections : a systematic review and mixed treatment comparison

OBJECTIVE: To synthesise the available evidence and estimate the comparative efficacy of control strategies to prevent total hip replacement (THR)-related surgical site infections (SSIs) using a mixed treatment comparison. DESIGN: Systematic review and mixed treatment comparison. SETTING: Hospital and other healthcare settings. PARTICIPANTS: Patients undergoing THR. PRIMARY AND SECONDARY OUTCOME MEASURES: The number of THR-related SSIs occurring following the surgical operation. RESULTS: 12 studies involving 123 788 THRs and 9 infection control strategies were identified. The strategy of 'systemic antibiotics+antibiotic-impregnated cement+conventional ventilation' significantly reduced the risk of THR-related SSI compared with the referent strategy (no systemic antibiotics+plain cement+conventional ventilation), OR 0.13 (95% credible interval (CrI) 0.03-0.35), and had the highest probability (47-64%) and highest median rank of being the most effective strategy. There was some evidence to suggest that 'systemic antibiotics+antibiotic-impregnated cement+laminar airflow' could potentially increase infection risk compared with 'systemic antibiotics+antibiotic-impregnated cement+conventional ventilation', 1.96 (95% CrI 0.52-5.37). There was no high-quality evidence that antibiotic-impregnated cement without systemic antibiotic prophylaxis was effective in reducing infection compared with plain cement with systemic antibiotics, 1.28 (95% CrI 0.38-3.38). CONCLUSIONS: We found no convincing evidence in favour of the use of laminar airflow over conventional ventilation for prevention of THR-related SSIs, yet laminar airflow is costly and widely used. Antibiotic-impregnated cement without systemic antibiotics may not be effective in reducing THR-related SSIs. The combination with the highest confidence for reducing SSIs was 'systemic antibiotics+antibiotic-impregnated cement+conventional ventilation'. Our evidence synthesis underscores the need to review current guidelines based on the available evidence, and to conduct further high-quality double-blind randomised controlled trials to better inform the current clinical guidelines and practice for prevention of THR-related SSIs.

A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.

A hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration

This paper deals with an efficient hybrid evolutionary optimization algorithm in accordance with combining the ant colony optimization (ACO) and the simulated annealing (SA), so called ACO-SA. The distribution feeder reconfiguration (DFR) is known as one of the most important control schemes in the distribution networks, which can be affected by distributed generations (DGs) for the multi-objective DFR. In such a case, DGs is used to minimize the real power loss, the deviation of nodes voltage and the number of switching operations. The approach is carried out on a real distribution feeder, where the simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving the DFR problem.

Regulating online : participant-driven approaches

This thesis considers and evaluates different approaches to regulating online gaming communities, including traditional top-down regulation, as well as bottom-up and hybrid forms led by participants. I examine the regulatory environment in both the video game and gambling industries through case studies of the science fiction, massively multiplayer game Eve Online and offshore gambling platforms and their community sites. I identify that the participant driven approach to regulation sometimes used in the offshore gambling industry was dependent on a number of factors, notably the strength of the community and the risks to platform operators of negative publicity. By subsequently comparing this to the video gaming industry, I suggest that participant driven processes may be an appropriate way to resolve disputes in the games industry, and show how these are – to a limited extent – already being applied.