Children's understanding of sustainability in their home and kindergarten

This article presents an ongoing study within early childhood education for sustainability at the Department for Early Childhood Education in Stavanger, in collaboration with the School of Early Childhood, Queensland University of Technology, in Brisbane, Australia. The study commenced in 2014, and will compare the responses to interviews of young children (4-5 years) in Brisbane with those of children in Stavanger, in order to find out ways to enhance learning about sustainability topics, to identify which kind of environmental/sustainability activities are memorable for young children, and to obtain mutual inspiration about early childhood education for sustainability from the different countries.

The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.

Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.

A comparison of classification algorithms within the Classifynder pollen imaging system

We describe an investigation into how Massey University's Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University's pollen reference collection (2890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set. In addition to the Classifynder's native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples. © 2013 AIP Publishing LLC.

DroplIT, an improved image analysis method for droplet identification in high-throughput crystallization trials

The application of robotics to protein crystallization trials has resulted in the production of millions of images. Manual inspection of these images to find crystals and other interesting outcomes is a major rate-limiting step. As a result there has been intense activity in developing automated algorithms to analyse these images. The very first step for most systems that have been described in the literature is to delineate each droplet. Here, a novel approach that reaches over 97% success rate and subsecond processing times is presented. This will form the seed of a new high-throughput system to scrutinize massive crystallization campaigns automatically. © 2010 International Union of Crystallography Printed in Singapore-all rights reserved.

Capturing natural-colour 3D models of insects for species discovery and diagnostics

Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity - past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition.) Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control. © 2014 Nguyen et al.

Multi-modal deformable medical image registration

Non-rigid image registration is an essential tool required for overcoming the inherent local anatomical variations that exist between images acquired from different individuals or atlases. Furthermore, certain applications require this type of registration to operate across images acquired from different imaging modalities. One popular local approach for estimating this registration is a block matching procedure utilising the mutual information criterion. However, previous block matching procedures generate a sparse deformation field containing displacement estimates at uniformly spaced locations. This neglects to make use of the evidence that block matching results are dependent on the amount of local information content. This paper presents a solution to this drawback by proposing the use of a Reversible Jump Markov Chain Monte Carlo statistical procedure to optimally select grid points of interest. Three different methods are then compared to propagate the estimated sparse deformation field to the entire image including a thin-plate spline warp, Gaussian convolution, and a hybrid fluid technique. Results show that non-rigid registration can be improved by using the proposed algorithm to optimally select grid points of interest.

Development of fourth-grade students’ understanding of experimental and theoretical probability

Students explored variation and expectation in a probability activity at the end of the first year of a 3-year longitudinal study across grades 4-6. The activity involved experiments in tossing coins both manually and with simulation using the graphing software, TinkerPlots. Initial responses indicated that the students were aware of uncertainty, although an understanding of chance concepts appeared limited. Predicting outcomes of 10 tosses reflected an intuitive notion of equiprobability, with little awareness of variation. Understanding the relationship between experimental and theoretical probability did not emerge until multiple outcomes and representations were generated with the software.

Politics and the Press in Indonesia : Understanding an Evolving Political Culture

This book explores the evolving political culture in Indonesia, by discussing the country's dominant political philosophies, then showing how those philosophies affect the working lives of ordinary Indonesian citizens. It focuses in particular on the working lives of news journalists, a group that occupies a strategic social and political position.

Unified user experience model enabling a more comprehensive understanding of emotional experience design

Design deals with improving the lives of people. As such interactions with products, interfaces, and systems should facilitate not only usable and practical concerns but also mediate emotionally meaningful experiences. This paper presents an integrated and comprehensive model of experience, labeled 'Unified User Experience Model', covering the most prominent perspectives from across the design field. It is intended to support designers from different disciplines to consider the complexity of user experience. The vision of the model is to support both the analysis of existing products, interfaces, and systems, as well as the development of new designs that take into account this complexity. In essence, we hope the model can enable designers to develop more marketable, appropriate, and enhanced products to improve experiences and ultimately the lives of people.

Understanding preservice teachers’ development of pedagogical knowledge practices when co-teaching primary science to peers

Preservice teachers articulate the need for more teaching experiences for developing their practices, however, extending beyond existing school arrangements may present difficulties. Thus, it is important to understand preservice teachers’ development of pedagogical knowledge practices when in the university setting. This mixed-method study investigated 48 second-year preservice teachers’ development of pedagogical knowledge practices as a result of co-teaching primary science to peers. Data were collected through a survey, video-recorded lessons, extended written responses and researcher observations. The study showed how these preservice teachers demonstrated 9 of 11 pedagogical knowledge practices within the co-teaching arrangement. However, research is needed to determine the level of development on each pedagogical knowledge practice and how these practices can be transferred into authentic primary classroom settings.

Gen Y recruitment: Understanding graduate intentions to join an organisation using the Theory of Planned Behaviour

Purpose Using the Theory of Planned Behaviour (TPB) framework, this study explored whether the standard TPB constructs explained variance in Gen Y individuals’ intentions to join their ideal organisation. Design/methodology/approach A mixed methods approach was used featuring qualitative and quantitative methods. Findings The overall TPB model accounted for a significant 51.6% of the variance in intention to join one’s ideal organisation in the next six months with the significant predictors in the model being subjective norm and perceived behaviour control but not attitude. Research limitations/implications Using graduating students from a single Australian university sample may mean that the current findings may not extend to all Gen Y individuals. The current study has demonstrated the explanatory utility of the TPB in relation to graduate Gen Y’s intention to join their ideal organisation, providing further evidence of the robustness of the TPB framework in an organisational setting. Practical implications These findings have implications for enhancing understanding of the most effective recruitment processes for Gen Y students entering the workforce. The findings could inform recruitment policies and strategies to attract Gen Y applicants. Originality/value To our knowledge this study is the first application of the TPB to this topic. The current research extends the recruitment literature with a theoretically-based investigation. Identification of factors which inform organisational recruitment strategies, allow organisations to stand out from their competitors and potentially achieve a larger application pool from which to select the best human capital and sustain competitive advantage.

A survey of radiographers' confidence and self-perceived accuracy in frontline image interpretation and their continuing educational preferences

Introduction The provision of a written comment on traumatic abnormalities of the musculoskeletal system detected by radiographers can assist referrers and may improve patient management, but the practice has not been widely adopted outside the United Kingdom. The purpose of this study was to investigate Australian radiographers’ perceptions of their readiness for practice in a radiographer commenting system and their educational preferences in relation to two different delivery formats of image interpretation education, intensive and non-intensive. Methods A cross-sectional web-based questionnaire was implemented between August and September 2012. Participants included radiographers with experience working in emergency settings at four Australian metropolitan hospitals. Conventional descriptive statistics, frequency histograms, and thematic analysis were undertaken. A Wilcoxon signed-rank test examined whether a difference in preference ratings between intensive and non-intensive education delivery was evident. Results The questionnaire was completed by 73 radiographers (68% response rate). Radiographers reported higher confidence and self-perceived accuracy to detect traumatic abnormalities than to describe traumatic abnormalities of the musculoskeletal system. Radiographers frequently reported high desirability ratings for both the intensive and the non-intensive education delivery, no difference in desirability ratings for these two formats was evident (z = 1.66,P = 0.11). Conclusions Some Australian radiographers perceive they are not ready to practise in a frontline radiographer commenting system. Overall, radiographers indicated mixed preferences for image interpretation education delivered via intensive and non-intensive formats. Further research, preferably randomised trials, investigating the effectiveness of intensive and non-intensive education formats of image interpretation education for radiographers is warranted.

Investigative trends in understanding penalty-kick performance in association football: An ecological dynamics perspective

There have been different approaches to studying penalty-kick performance in association football. In this paper, the authors synthesize key findings within an ecological dynamics theoretical framework. According to this theoretical perspective, information is the cornerstone for understanding the dynamics of action regulation in penalty-kick performance. Research suggests that investigators need to identify the information sources that are most relevant to penalty-kick performance. An important task is to understand how constraints can channel (i.e. change, emphasize or mask) information sources used to regulate upcoming actions and how the influence of these constraints is expressed in players' behavioural dynamics. Due to the broad range of constraints influencing penalty-kick performance, it is recommended that future research adopts an interdisciplinary focus on performance assessment to overcome the current lack of representativeness in penalty-kick experimental designs. Such an approach would serve to capture the information-based control of action of both players as components of this dyadic system in competitive sport.