Efficient solution of multiple cracks in great number using eigen COD boundary integral equations with iteration procedure

A newly developed computational approach is proposed in the paper for the analysis of multiple crack problems based on the eigen crack opening displacement (COD) boundary integral equations. The eigen COD particularly refers to a crack in an infinite domain under fictitious traction acting on the crack surface. With the concept of eigen COD, the multiple cracks in great number can be solved by using the conventional displacement discontinuity boundary integral equations in an iterative fashion with a small size of system matrix to determine all the unknown CODs step by step. To deal with the interactions among cracks for multiple crack problems, all cracks in the problem are divided into two groups, namely the adjacent group and the far-field group, according to the distance to the current crack in consideration. The adjacent group contains cracks with relatively small distances but strong effects to the current crack, while the others, the cracks of far-field group are composed of those with relatively large distances. Correspondingly, the eigen COD of the current crack is computed in two parts. The first part is computed by using the fictitious tractions of adjacent cracks via the local Eshelby matrix derived from the traction boundary integral equations in discretized form, while the second part is computed by using those of far-field cracks so that the high computational efficiency can be achieved in the proposed approach. The numerical results of the proposed approach are compared not only with those using the dual boundary integral equations (D-BIE) and the BIE with numerical Green's functions (NGF) but also with those of the analytical solutions in literature. The effectiveness and the efficiency of the proposed approach is verified. Numerical examples are provided for the stress intensity factors of cracks, up to several thousands in number, in both the finite and infinite plates.

A banded preconditioner for the two-sided, nonlinear space-fractional diffusion equation

The method of lines is a standard method for advancing the solution of partial differential equations (PDEs) in time. In one sense, the method applies equally well to space-fractional PDEs as it does to integer-order PDEs. However, there is a significant challenge when solving space-fractional PDEs in this way, owing to the non-local nature of the fractional derivatives. Each equation in the resulting semi-discrete system involves contributions from every spatial node in the domain. This has important consequences for the efficiency of the numerical solver, especially when the system is large. First, the Jacobian matrix of the system is dense, and hence methods that avoid the need to form and factorise this matrix are preferred. Second, since the cost of evaluating the discrete equations is high, it is essential to minimise the number of evaluations required to advance the solution in time. In this paper, we show how an effective preconditioner is essential for improving the efficiency of the method of lines for solving a quite general two-sided, nonlinear space-fractional diffusion equation. A key contribution is to show, how to construct suitable banded approximations to the system Jacobian for preconditioning purposes that permit high orders and large stepsizes to be used in the temporal integration, without requiring dense matrices to be formed. The results of numerical experiments are presented that demonstrate the effectiveness of this approach.

The doctrine of command responsibility in the midst of war : legal fallacy or reflection of reality

The history of war is blighted with astonishing reminders of man’s ability to cast his sense of humanity aside and inflict unspeakable harm upon one another. The ruthless bombing of Dresden, the callousness of the Nazi concentration camps and the massacre of the Tutsis are but a few of the atrocities that have haunted our past. In response to these atrocities, society has imposed an ever-increasing number of laws and rules to regulate warfare. Amongst these is the doctrine of command responsibility. The doctrine of command responsibility states that a commander is criminally liable for the crimes of his subordinates if he knew or should have known of their crimes. This paper will examine whether the doctrine is an appropriate and realistic legal standard to hold commanders accountable to or whether the doctrine is more a reflection of social sentiment and legal rhetoric. If the doctrine, and indeed the law of war in general, is unrealistic then the law cannot fulfil its purpose - that is, the prevention of atrocities. Instead of being solely a reflection of moral authority and social sentiments the law must also be a tool that guides and shapes the decisions and actions of the military through the chaotic and brutal nature of war...

Spatial variation of particle number concentration in school microscale environments and its impact on exposure assessment

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

Managing memory and reducing I/O cost for correlation matrix calculation in bioinformatics

The generation of a correlation matrix from a large set of long gene sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. The generation is not only computationally intensive but also requires significant memory resources as, typically, few gene sequences can be simultaneously stored in primary memory. The standard practice in such computation is to use frequent input/output (I/O) operations. Therefore, minimizing the number of these operations will yield much faster run-times. This paper develops an approach for the faster and scalable computing of large-size correlation matrices through the full use of available memory and a reduced number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different problems with different correlation matrix sizes. The significant performance improvement of the approach over the existing approaches is demonstrated through benchmark examples.

Community Partnerships for Fostering Student Interest and Engagement in STEM

The foundations of Science, Technology, Engineering and Mathematics (STEM) education begins in the early years of schooling when students encounter formal learning experiences primarily in mathematics and science. Politicians, economists and industrialists recognise the importance of STEM in society, and therefore a number of strategies have been implemented to foster interest. Similarly, most students see the importance of science and mathematics in their lives, but school science and mathematics is usually seen as irrelevant, particularly by students in developed countries. This paper reports on the establishment and implementation of partnerships with industry experts from one jurisdiction which have, over a decade, attempted to reconcile the interests of youth and the contemporary world of science. Four case studies are presented and qualitative findings analyzed in terms of program outcomes and student engagement. The key finding is that the formation of relationships and partnerships, in which students have high degree of autonomy and sense of responsibility, is paramount to positive dispositions towards STEM. Those features of successful partnerships are also discussed. The findings raise some hope that innovative schools and partnerships can foster innovation and connect youth with the real world.

Numerical techniques for simulating a fractional mathematical model of epidermal wound healing

A number of mathematical models investigating certain aspects of the complicated process of wound healing are reported in the literature in recent years. However, effective numerical methods and supporting error analysis for the fractional equations which describe the process of wound healing are still limited. In this paper, we consider the numerical simulation of a fractional mathematical model of epidermal wound healing (FMM-EWH), which is based on the coupled advection-diffusion equations for cell and chemical concentration in a polar coordinate system. The space fractional derivatives are defined in the Left and Right Riemann-Liouville sense. Fractional orders in the advection and diffusion terms belong to the intervals (0, 1) or (1, 2], respectively. Some numerical techniques will be used. Firstly, the coupled advection-diffusion equations are decoupled to a single space fractional advection-diffusion equation in a polar coordinate system. Secondly, we propose a new implicit difference method for simulating this equation by using the equivalent of Riemann-Liouville and Grünwald-Letnikov fractional derivative definitions. Thirdly, its stability and convergence are discussed, respectively. Finally, some numerical results are given to demonstrate the theoretical analysis.

The first year experience of social work students : developing a “sense of fit” and engagement with the profession : a practice report

Engagement is believed to be critical to a successful first year experience. This paper examines a range of strategies introduced into a first year Social Work and Human Services unit at Queensland University of Technology. The focus of these strategies was to enhance student engagement through building connections with peers, lecturers and the Social Work and Human Services professions. It is argued in this paper that students are more likely to continue with their studies if they are supported in building an emerging identity as both a university student and as a Social Work or Human Services practitioner. A range of strategies was introduced, including restructuring the unit to include an early intensive teaching block; inviting current practitioners to speak with students about the realities of practice; and embedding an academic skills component into the unit. Feedback from students highlighted the success of these strategies in developing their academic skills, building connections and embedding a sense of fit with the profession.

A context-fusion framework for enhancing context-awareness on mobile application

Mobile devices and smartphones have become a significant communication channel for everyday life. The sensing capabilities of mobile devices are expanding rapidly, and sensors embedded in these devices are cheaper and more powerful than before. It is evident that mobile devices have become the most suitable candidates to sense contextual information without needing extra tools. However, current research shows only a limited number of sensors are being explored and investigated. As a result, it still needs to be clarified what forms of contextual information extracted from mo- bile sensors are useful. Therefore, this research investigates the context sensing using current mobile sensors, the study follows experimental methods and sensor data is evaluated and synthesised, in order to deduce the value of various sensors and combinations of sensor for the use in context-aware mobile applications. This study aims to develop a context fusion framework that will enhance the context-awareness on mobile applications, as well as exploring innovative techniques for context sensing on smartphone devices.

Diversity and Differentiation

New ways of working are being embraced by early childhood educators as they cope with demands from national reforms and changing communities. While reformers are pressing for social equity and improved outcomes for families and children, communities are diverging in terms of ethnicity, culture, language and socioeconomic status. As a consequence, early childhood educators are being challenged to expand their existing repertoire of practices in order to more effectively provide quality learning experiences for every child in their care. Practice enhancement and differentiated pedagogy are needed to address the additional needs of an increasing number of diverse learners. Community expectations are particularly focused on better educational supports for children in five cluster areas: • Culturally diverse and Indigenous backgrounds • ‘at risk’ because of socio-economic and abuse conditions • Communicative, emotional and behavioural disorders • Disabilities and learning difficulties and • Recognised gifts and talents This chapter focuses on some everyday ractices that can be used strategically to better support all children, including those with additional educational needs. All practices are well supported in the literature and are substantiated by either research findings or strong, socially determined values. They also very ‘doable’ and sustainable in today’s dynamic and multifaceted early childhood settings. Seven keys practices will be introduced, together with examples of how they can be applied to both enhance the learning of individual children and to strengthen a sense of group belonging. The practices are: • Having positive beliefs about all children • Learning about each child • Building meaningful relationships around the child • Creating supportive learning environments for the child • Providing engaging learning experiences for the child • Differentiating instruction for the child • Using child progress data to improve learning and teaching

Vision based control for micro aerial vehicles : Application to sense and avoid

This work presents a collision avoidance approach based on omnidirectional cameras that does not require the estimation of range between two platforms to resolve a collision encounter. Our method achieves minimum separation between the two vehicles involved by maximising the view-angle given by the omnidirectional sensor. Only visual information is used to achieve avoidance under a bearing- only visual servoing approach. We provide theoretical problem formulation, as well as results from real flights using small quadrotors

Let the journey begin : cultivating student identity and a sense of belonging through a formal academic welcome

Queensland University of Technology [QUT] Caboolture campus is a satellite campus co-located with Brisbane North Institute of TAFE. Building a sense of belonging on-campus continues to be challenging, with anecdotal evidence suggesting that QUT Caboolture students feel like second-class students, isolated from the prestige and excitement of the city campuses. A student identity and fostering a sense of belonging are fundamental to on-campus engagement and have been linked to retention (Field & Morgan-Klein, 2010). A formal welcome ceremony, including an academic procession in full regalia, was a new inclusion for QUT Caboolture’s 2013 Orientation Day. The ritual was intended to be a temporal mark for students to recognise their personal transition and emerging identity as a university student. Cultural capital is one ingredient in a complex mix of interactions and relationships to build a sense of identity. (Ecclestone, Biesta & Hughes, 2010). Fostering a sense of belonging and a connection to the campus and its staff was also anticipated. Students responded positively to the event, reporting feelings of excitement, inspiration and being welcomed into the university culture. The ceremony marked the beginning of the students’ journey together as QUT Caboolture students.

Determining process model precision and generalization with weighted artificial negative events

Process mining encompasses the research area which is concerned with knowledge discovery from event logs. One common process mining task focuses on conformance checking, comparing discovered or designed process models with actual real-life behavior as captured in event logs in order to assess the “goodness” of the process model. This paper introduces a novel conformance checking method to measure how well a process model performs in terms of precision and generalization with respect to the actual executions of a process as recorded in an event log. Our approach differs from related work in the sense that we apply the concept of so-called weighted artificial negative events towards conformance checking, leading to more robust results, especially when dealing with less complete event logs that only contain a subset of all possible process execution behavior. In addition, our technique offers a novel way to estimate a process model’s ability to generalize. Existing literature has focused mainly on the fitness (recall) and precision (appropriateness) of process models, whereas generalization has been much more difficult to estimate. The described algorithms are implemented in a number of ProM plugins, and a Petri net conformance checking tool was developed to inspect process model conformance in a visual manner.

Social media metrics : are we measuring business value?

Over the past few years many organizations that directly or indirectly interact with consumers have invested heavily into a social media presence. As a consequence some success indicators are openly available to users of many social media platforms, such as the number of fans (or followers, members, visitors and others) or the amount of content(tweets, images, shares or other content). Many organizations additionally track their social activities internally to understand audience reach, consumer influence, brand image, consumer preference or other key metrics that make sense for a business. However, most of the immediately available social media success metrics are activity-based and many organizations are struggling with establishing a direct relationship to business success. This paper systematically reviews some of the common social media metrics/ratings used by organisations, critically analyse its business value and identify gaps formulating research questions for empirical study and concluding with recommendations and suggestions for future research.