Analytical and numerical solutions of the space and time fractional bloch-torrey equation

Fractional order dynamics in physics, particularly when applied to diffusion, leads to an extension of the concept of Brown-ian motion through a generalization of the Gaussian probability function to what is termed anomalous diffusion. As MRI is applied with increasing temporal and spatial resolution, the spin dynamics are being examined more closely; such examinations extend our knowledge of biological materials through a detailed analysis of relaxation time distribution and water diffusion heterogeneity. Here the dynamic models become more complex as they attempt to correlate new data with a multiplicity of tissue compartments where processes are often anisotropic. Anomalous diffusion in the human brain using fractional order calculus has been investigated. Recently, a new diffusion model was proposed by solving the Bloch-Torrey equation using fractional order calculus with respect to time and space (see R.L. Magin et al., J. Magnetic Resonance, 190 (2008) 255-270). However effective numerical methods and supporting error analyses for the fractional Bloch-Torrey equation are still limited. In this paper, the space and time fractional Bloch-Torrey equation (ST-FBTE) is considered. The time and space derivatives in the ST-FBTE are replaced by the Caputo and the sequential Riesz fractional derivatives, respectively. Firstly, we derive an analytical solution for the ST-FBTE with initial and boundary conditions on a finite domain. Secondly, we propose an implicit numerical method (INM) for the ST-FBTE, and the stability and convergence of the INM are investigated. We prove that the implicit numerical method for the ST-FBTE is unconditionally stable and convergent. Finally, we present some numerical results that support our theoretical analysis.

Stability and convergence of implicit numerical methods for a class of fractional advection-dispersion models

In this paper, a class of fractional advection-dispersion models (FADM) is investigated. These models include five fractional advection-dispersion models: the immobile, mobile/immobile time FADM with a temporal fractional derivative 0 < γ < 1, the space FADM with skewness, both the time and space FADM and the time fractional advection-diffusion-wave model with damping with index 1 < γ < 2. They describe nonlocal dependence on either time or space, or both, to explain the development of anomalous dispersion. These equations can be used to simulate regional-scale anomalous dispersion with heavy tails, for example, the solute transport in watershed catchments and rivers. We propose computationally effective implicit numerical methods for these FADM. The stability and convergence of the implicit numerical methods are analyzed and compared systematically. Finally, some results are given to demonstrate the effectiveness of our theoretical analysis.

Domestic energy monitoring in Victorian households with PV solar installations : feasibility report for GV Community Energy

Australia requires decisive action on climate change and issues of sustainability. The Urban Informatics Research Lab has been funded by the Queensland State Government to conduct a three year study (2009 – 2011) exploring ways to support Queensland residents in making more sustainable consumer and lifestyle choices. We conduct user-centred design research that inform the development of real-time, mobile, locational, networked information interfaces, feedback mechanisms and persuasive and motivational approaches that in turn assist in-situ decision making and environmental awareness in everyday settings. The study aims to deliver usable and useful prototypes offering individual and collective visualisations of ecological impact and opportunities for engagement and collaboration in order to foster a participatory and sustainable culture of life in Australia. Raising people’s awareness with environmental data and educational information does not necessarily trigger sufficient motivation to change their habits towards a more environmentally friendly and sustainable lifestyle. Our research seeks to develop a better understanding how to go beyond just informing and into motivating and encouraging action and change. Drawing on participatory culture, ubiquitous computing, and real-time information, the study delivers research that leads to viable new design approaches and information interfaces which will strengthen Australia’s position to meet the targets of the Clean Energy Future strategy, and contribute to the sustainability of a low-carbon future in Australia. As part of this program of research, the Urban Informatics Research Lab has been invited to partner with GV Community Energy Pty Ltd on a project funded by the Victorian Government Sustainability Fund. This feasibility report specifically looks at the challenges and opportunities of energy monitoring in households in Victoria that include a PV solar installation. The report is structured into two parts: In Part 1, we first review a range of energy monitoring solutions, both stand-alone and internet-enabled. This section primarily focusses on the technical capacilities. However, in order to understand this information and make an informed decision, it is crucial to understand the basic principles and limitations of energy monitoring as well as the opportunities and challenges of a networked approach towards energy monitoring which are discussed in Section 2.

First international workshop on theory and applications of process visualization

The representation of business process models has been a continuing research topic for many years now. However, many process model representations have not developed beyond minimally interactive 2D icon-based representations of directed graphs and networks, with little or no annotation for information over- lays. With the rise of desktop computers and commodity mobile devices capable of supporting rich interactive 3D environments, we believe that much of the research performed in computer human interaction, virtual reality, games and interactive entertainment has much potential in areas of BPM; to engage, pro- vide insight, and to promote collaboration amongst analysts and stakeholders alike. This initial visualization workshop seeks to initiate the development of a high quality international forum to present and discuss research in this field. Via this workshop, we intend to create a community to unify and nurture the development of process visualization topics as a continuing research area.

Integrating driving and traffic simulators to study railway level crossing safety interventions : a methodology

Safety at Railway Level Crossings (RLXs) is an important issue within the Australian transport system. Crashes at RLXs involving road vehicles in Australia are estimated to cost $10 million each year. Such crashes are mainly due to human factors; unintentional errors contribute to 46% of all fatal collisions and are far more common than deliberate violations. This suggests that innovative intervention targeting drivers are particularly promising to improve RLX safety. In recent years there has been a rapid development of a variety of affordable technologies which can be used to increase driver’s risk awareness around crossings. To date, no research has evaluated the potential effects of such technologies at RLXs in terms of safety, traffic and acceptance of the technology. Integrating driving and traffic simulations is a safe and affordable approach for evaluating these effects. This methodology will be implemented in a driving simulator, where we recreated realistic driving scenario with typical road environments and realistic traffic. This paper presents a methodology for evaluating comprehensively potential benefits and negative effects of such interventions: this methodology evaluates driver awareness at RLXs , driver distraction and workload when using the technology . Subjective assessment on perceived usefulness and ease of use of the technology is obtained from standard questionnaires. Driving simulation will provide a model of driving behaviour at RLXs which will be used to estimate the effects of such new technology on a road network featuring RLX for different market penetrations using a traffic simulation. This methodology can assist in evaluating future safety interventions at RLXs.

Beyond demand management : the value of sharing electricity information

Technologies such as smart meters and electricity feedback are becoming an increasingly compelling focus for HCI researchers in light of rising power prices and peak demand. We argue, however, that a pre-occupation with the goal of demand management has limited the scope of design for these technologies. In this paper we present our work-in-progress investigating the potential value of socially sharing electricity information as a means of broadening the scope of design for these devices. This paper outlines some preliminary findings gathered from a design workshop and a series of qualitative interviews with householders in Brisbane, Australia, regarding their attitudes towards electricity feedback and sharing consumption information. Preliminary findings suggest that; (1) the social sharing of electricity feedback information has the potential to be of value in better informing consumption decisions, however; (2) the potential for sharing may be constrained by attitudes towards privacy, trust and the possibility of misinformation being shared. We conclude by outlining ideas for our future research on this topic and invite comments on these ideas.

Challenges for researchers investigating contraceptive use and pregnancy intentions of young women living in urban and rural Australia : face-to-face discussions to increase participation in a web-based survey

Background: It is imperative to understand how to engage young women in research about issues that are important to them. There is limited reliable data on how young women access contraception in Australia especially in rural areas where services may be less available. Objective: This paper identifies the challenges involved in engaging young Australian women aged 18-23 years to participate in a web-based survey on contraception and pregnancy and ensure their ongoing commitment to follow-up web-based surveys. Methods: A group of young women, aged 18-23 years and living in urban and rural New South Wales, Australia, were recruited to participate in face-to-face discussions using several methods of recruitment: direct contact (face-to-face, telephone or email)and snowball sampling by potential participants inviting their friends. All discussions were transcribed verbatim and analyzed using thematic analysis. Results: Twenty young women participated (urban, n=10: mean age 21.6 years; rural, n=10: 20.0 years) and all used computers or smart phones to access the internet on a daily basis. All participants were concerned about the cost of internet access and utilized free access to social media on their mobile phones. Their willingness to participate in a web-based survey was dependent on incentives with a preference for small financial rewards. Most participants were concerned about their personal details and survey responses remaining confidential and secure. The most appropriate survey would take up to 15 minutes to complete, be a mix of short and long questions and eye-catching with bright colours. Questions on the sensitive topics of sexual activity, contraception and pregnancy were acceptable if they could respond with “I prefer not to answer”. Conclusions: There are demographic, participation and survey design challenges in engaging young women in a web-based survey. Based on our findings, future research efforts are needed to understand the full extent of the role social media and incentives play in the decision of young women to participate in web-based research.

Teaching Teachers for the Future (TTF) project TPACK Survey : summary of the key findings

This paper presents a summary of the key findings of the TTF TPACK Survey developed and administered for the Teaching the Teachers for the Future (TTF) Project implemented in 2011. The TTF Project, funded by an Australian Government ICT Innovation Fund grant, involved all 39 Australian Higher Education Institutions which provide initial teacher education. TTF data collections were undertaken at the end of Semester 1 (T1) and at the end of Semester 2 (T2) in 2011. A total of 12881 participants completed the first survey (T1) and 5809 participants completed the second survey (T2). Groups of like-named items from the T1 survey were subject to a battery of complementary data analysis techniques. The psychometric properties of the four scales: Confidence - teacher items; Usefulness - teacher items; Confidence - student items; Usefulness- student items, were confirmed both at T1 and T2. Among the key findings summarised, at the national level, the scale: Confidence to use ICT as a teacher showed measurable growth across the whole scale from T1 to T2, and the scale: Confidence to facilitate student use of ICT also showed measurable growth across the whole scale from T1 to T2. Additional key TTF TPACK Survey findings are summarised.

Field measurement of wheel-rail impact force at insulated rail joint

When wheels pass over insulated rail joints (IRJs) a vertical impact force is generated. The ability to measure the impact force is valuable as the force signature helps understand the behaviour of the IRJs, in particular their potential for failure. The impact forces are thought to be one of the main factors that cause damage to the IRJ and track components. Study of the deterioration mechanism helps finding new methods to improve the service life of IRJs in track. In this research, the strain-gage-based wheel load detector, for the first time, is employed to measure the wheel–rail contact-impact force at an IRJ in a heavy haul rail line. In this technique, the strain gages are installed within the IRJ assembly without disturbing the structural integrity of IRJ and arranged in a full wheatstone bridge to form a wheel load detector. The instrumented IRJ is first tested and calibrated in the lab and then installed in the field. For comparison purposes, a reference rail section is also instrumented with the same strain gage pattern as the IRJ. In this paper the measurement technique, the process of instrumentation, and tests as well as some typical data obtained from the field and the inferences are presented.

Keyboarding plus handbook

A quick, easy and fun way of learning keyboarding!

Talk and web searching in an early years classroom

Recent Australian early childhood policy and curriculum guidelines promoting the use of technologies invite investigations of young children’s practices in classrooms. This study examined the practices of one preparatory year classroom, to show teacher and child interactions as they engaged in Web searching. The study investigated the in situ practices of the teacher and children to show how they accomplished the Web search. The data corpus consists of eight hours of videorecorded interactions over three days where children and teachers engaged in Web searching. One episode was selected that showed a teacher and two children undertaking a Web search. The episode is shown to consist of four phases: deciding on a new search subject, inputting the search query, considering the result options, and exploring the selected result. The sociological perspectives of ethnomethodology and conversation analysis were employed as the conceptual and methodological frameworks of the study, to analyse the video-recorded teacher and child interactions as they co-constructed a Web search. Ethnomethodology is concerned with how people make ‘sense’ in everyday interactions, and conversation analysis focuses on the sequential features of interaction to show how the interaction unfolds moment by moment. This extended single case analysis showed how the Web search was accomplished over multiple turns, and how the children and teacher collaboratively engaged in talk. There are four main findings. The first was that Web searching featured sustained teacher-child interaction, requiring a particular sort of classroom organisation to enable the teacher to work in this sustained way. The second finding was that the teacher’s actions recognised the children’s interactional competence in situ, orchestrating an interactional climate where everyone was heard. The third finding was that the teacher drew upon a range of interactional resources designed to progress the activity at hand, that of accomplishing the Web search. The teacher drew upon the interactional resources of interrogatives, discourse markers, and multi-unit turns during the Web search, and these assisted the teacher and children to co-construct their discussion, decide upon and co-ordinate their future actions, and accomplish the Web search in a timely way. The fourth finding explicates how particular social and pedagogic orders are accomplished through talk, where children collaborated with each other and with the teacher to complete the Web search. The study makes three key recommendations for the field of early childhood education. The study’s first recommendation is that fine-grained transcription and analysis of interaction aids in understanding interactional practices of Web searching. This study offers material for use in professional development, such as using transcribed and videorecorded interactions to highlight how teachers strategically engage with children, that is, how talk works in classroom settings. Another strategy is to focus on the social interactions of members engaging in Web searches, which is likely to be of interest to teachers as they work to engage with children in an increasingly online environment. The second recommendation involves classroom organisation; how teachers consider and plan for extended periods of time for Web searching, and how teachers accommodate children’s prior knowledge of Web searching in their classrooms. The third recommendation is in relation to future empirical research, with suggested possible topics focusing on the social interactions of children as they engage with peers as they Web search, as well as investigations of techno-literacy skills as children use the Internet in the early years.

Collaboration and competition on a Wiki : the praxis of online social learning to improve academic writing and research in under-graduate students

The number of internet users in Australia has been steadily increasing, with over 10.9 million people currently subscribed to an internet provider (ABS, 2011). Over the past year, the most avid users of the Internet were 15 – 24 year olds, with approximately 95% accessing the internet on a regular basis (ABS, Social Trends, 2011). While the internet, in particularly Web 2.0, has been described as fundamental to higher education students, social and leisure internet tools are also increasingly being used by these students to generate and maintain their social and professional networks and interactions (Duffy & Bruns, 2006). Rapid technological advancements have enabled greater and faster access to information for learning and education (Hemmi et al, 2009; Glassman & Kang, 2011). As such, we sought to integrate interactive, online social media into the assessment profile of a Public Health undergraduate cohort at the Queensland University of Technology (QUT). The aim of this exercise was to engage undergraduate students to both develop and showcase their research on a range of complex, contemporary health issues within the online forum of Wikispaces for review and critique by their peers. We applied Bandura’s Social Learning Theory (SLT) to analyse the interactive processes from which students developed deeper and more sustained learning, and via which their overall academic writing standards were enriched. This paper outlines the assessment task, and the students’ feedback on their learning outcomes in relation to the Attentional, Retentional, Motor Reproduction, and Motivational Processes outlined by Bandura in SLT. We conceptualise the findings in a theoretical model, and discuss the implications for this approach within the broader tertiary environment.

Computationally sound automated proofs of cryptographic schemes

Proving security of cryptographic schemes, which normally are short algorithms, has been known to be time-consuming and easy to get wrong. Using computers to analyse their security can help to solve the problem. This thesis focuses on methods of using computers to verify security of such schemes in cryptographic models. The contributions of this thesis to automated security proofs of cryptographic schemes can be divided into two groups: indirect and direct techniques. Regarding indirect ones, we propose a technique to verify the security of public-key-based key exchange protocols. Security of such protocols has been able to be proved automatically using an existing tool, but in a noncryptographic model. We show that under some conditions, security in that non-cryptographic model implies security in a common cryptographic one, the Bellare-Rogaway model [11]. The implication enables one to use that existing tool, which was designed to work with a different type of model, in order to achieve security proofs of public-key-based key exchange protocols in a cryptographic model. For direct techniques, we have two contributions. The first is a tool to verify Diffie-Hellmanbased key exchange protocols. In that work, we design a simple programming language for specifying Diffie-Hellman-based key exchange algorithms. The language has a semantics based on a cryptographic model, the Bellare-Rogaway model [11]. From the semantics, we build a Hoare-style logic which allows us to reason about the security of a key exchange algorithm, specified as a pair of initiator and responder programs. The other contribution to the direct technique line is on automated proofs for computational indistinguishability. Unlike the two other contributions, this one does not treat a fixed class of protocols. We construct a generic formalism which allows one to model the security problem of a variety of classes of cryptographic schemes as the indistinguishability between two pieces of information. We also design and implement an algorithm for solving indistinguishability problems. Compared to the two other works, this one covers significantly more types of schemes, but consequently, it can verify only weaker forms of security.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Budget-aware role based access control

The suitability of Role Based Access Control (RBAC) is being challenged in dynamic environments like healthcare. In an RBAC system, a user's legitimate access may be denied if their need has not been anticipated by the security administrator at the time of policy specification. Alternatively, even when the policy is correctly specified an authorised user may accidentally or intentionally misuse the granted permission. The heart of the challenge is the intrinsic unpredictability of users' operational needs as well as their incentives to misuse permissions. In this paper we propose a novel Budget-aware Role Based Access Control (B-RBAC) model that extends RBAC with the explicit notion of budget and cost, where users are assigned a limited budget through which they pay for the cost of permissions they need. We propose a model where the value of resources are explicitly defined and an RBAC policy is used as a reference point to discriminate the price of access permissions, as opposed to representing hard and fast rules for making access decisions. This approach has several desirable properties. It enables users to acquire unassigned permissions if they deem them necessary. However, users misuse capability is always bounded by their allocated budget and is further adjustable through the discrimination of permission prices. Finally, it provides a uniform mechanism for the detection and prevention of misuses.