Australian Catholic University

About: Australian Catholic University is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 2721 authors who have published 10013 publications receiving 215248 citations. The organization is also known as: ACU & ACU National.

Assessment of Science Teaching Efficacy of Preservice Teachers in an Australian University

Abstract: Research investigating science teaching efficacy was conducted in 1 Australian university. A sample of 314 elementary preservice teachers responded to the Science Teaching Efficacy Belief Instrument (STEBI; L. G. Enochs & I. M. Riggs, 1990), which assesses 2 teaching efficacy dimensions: Personal Science Teaching Efficacy Beliefs (PSTEB) and Science Teaching Outcome Expectancy (STOE). Confirmatory factor analysis substantiated this 2-factor structure. The use of this instrument revealed that the completion of 2 science teaching subjects within the preservice program had a significant effect on the PSTEB, but not the STOE. Similarly, the number of high school science subjects studied by these elementary preservice teachers had a significant effect on PSTEB, but not STOE. However, neither gender nor the particular high school science subjects studied by these elementary preservice teachers had a significant effect on either the PSTEB or the STOE.

An adaptive differential evolution algorithm to optimal multi-level thresholding for MRI brain image segmentation

Abstract: Segmentation is an important method for MRI medical image analysis as it can provide the radiologists with noninvasive information about a patient that is crucial to the diagnostic process. The efficiency of such a computer-aided diagnosis system relies on the accuracy of an adopted image segmentation method. Multi-level thresholding is a segmentation method that has been widely adopted in medical image analysis in recent studies, where selecting the optimal thresholds has a pivotal role in determining the efficiency and the accuracy of the segmentation algorithm. While some well-known methods, such as Kapur’s and Otsu’s, are proven effective for bi-level thresholding, multi-level thresholding remains a challenge as it is computationally expensive. Evolutionary algorithms, such as Differential Evolution (DE), have the potential to address this problem, as they can find sufficiently good solutions with manageable computational effort. While a number of DE solutions have been proposed for multi-level thresholding, they are not stable, in that, when the number of thresholds increases, the algorithm efficiency decreases due to the imbalance between exploration and exploitation. In this paper, we propose a DE solution that achieves a good balance between exploration and exploitation through a new adaptive approach and new mutation strategies. The new adaptive approach can generate optimal solutions in assigning populations by measuring the quality of candidate solutions to evaluate the efficiency of different parts of the proposed DE algorithm. The new mutation methods harness Mantegna Levy and Cauchy distributions, as well as Cotes’ Spiral to improve global search, and to further balance between exploitation and exploration. We further experimentally compare the proposed DE algorithm, referred to as Adaptive Differential Evolution with Levy Distribution (ALDE), against three DE benchmark algorithms on T2 weighted MRI brain images. Our results show that ALDE can, not only obtain optimal thresholds at a reasonable computational cost, but more importantly, clearly outperforms the benchmark algorithms.

Risk Factors Associated with Impact Severity of Cyberbullying Victimization: A Qualitative Study of Adolescent Online Social Networking

Abstract: Cyberbullying victimization is associated with a range of emotional and behavioral outcomes for adolescents. However, previous research has shown that this type of victimization does not affect all individuals negatively. The factors that account for individual differences in reactions to the same online experiences are not well understood. Using a qualitative inductive approach, a set of strong themes relating to factors that either increased the severity of impact of cyberbullying victimization or buffered victims against the impact emerged from interviews with 25 adolescents aged 15–24 years. Themes related to publicity, anonymity of perpetrators, features of the medium, presence of bystanders, and individual level factors were identified as potential influences upon impact severity. The implications of these results for further research and for school/university cyberbullying prevention programs for victims, perpetrators, and bystanders are discussed.

The Role of Self-Efficacy and Friend Support on Adolescent Vigorous Physical Activity:

Abstract: Objectives. Physical activity, including some form of vigorous activity, is a key component of a healthy lifestyle in young people. Self-efficacy and social support have been identified as key determinants of physical activity; however, the mechanism that reflects the interplay of these two factors is not well understood. The aim of the current study was to test social cognitive theory’s notion that self-efficacy relates to intention that translates into behavior and to investigate whether friend support and self-efficacy synergize, interfere, or compensate for one another to predict vigorous physical activity in adolescents—a population at risk of rapid decreases in physical activity. Method. A survey at two points in time was conducted in 226 students aged 12 to 16 years. In a conditional process analysis, friend support and physical activity self-efficacy were specified as interacting predictors of intention. The latter was specified as a mediator between self-efficacy and later vigorous physical activ...