A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

A collaborative model for learning and assessment of legal placements

This paper will report on the evaluation of a new undergraduate legal workplace unit, LWB421 Learning in Professional Practice. LWB421 was developed in response to the QUT’s strategic planning and a growing view that work experience is essential to developing the skills that law graduates need in order to be effective legal practitioners (Stuckey, 2007). Work integrated learning provides a context for students to develop their skills, to see the link between theory and practice and support students in making the transition from university to practice (Shirley, 2006). The literature in Australian legal education has given little consideration to the design of legal internship subjects (as distinct from legal clinic programs). Accordingly the design of placement subjects needs to be carefully considered to ensure alignment of learning objectives, learning tasks and assessment. Legal placements offer students the opportunity to develop their professional skills in practice, reflect on their own learning and job performance and take responsibility for their career development and planning. This paper will examine the literature relating to the design of placement subjects, particularly in a legal context. It will propose a collaborative model to facilitate learning and assessment of legal work placement subjects. The basis of the model is a negotiated learning contract between the student, workplace supervisor and academic supervisor. Finally the paper will evaluate the model in the context of LWB421. The evaluation will be based on data from surveys of students and supervisors and focus group sessions.

Case study of collaborative learning in two contexts : what do English language learners gain?

This chapter describes the use of collaborative learning as an approach to enhance English language learning by students from non-English speaking backgrounds. Communicative Language Teaching (CLT) principles were applied to two case studies, one comprising of undergraduate English as Foreign Language Learners in Turkey and the other involved English as Second Language learners in Australia. Social constructivism inspired communicative language teaching using collaborative learning activities such as team work, interactive peer-based learning, and iterative stages of learning matrix were incorporated to enhance students' learning outcomes. Data collected after the CLT intervention was made up of field notes, reflective logs and focus group interviews which revealed complementarities, as well as subtle differences between the two cases. The findings were summarized as learning dispositions; speaking fluency and confidence; learning diagnostics and completion deficiencies; task engagement, flow theory and higher order thinking skills; in addition to self efficacy and development of student identity. CLT has the potential to provide a more inclusive and dynamic education for diverse learners through vital outcomes and benefits which resonate with the real world.

Cipher cities

Cipher Cities was a practice-led research project developed in 3 stages between 2005 and 2007 resulting in the creation of a unique online community, ‘Cipher Cities’, that provides simple authoring tools and processes for individuals and groups to create their own mobile events and event journals, build community profile and participate in other online community activities. Cipher Cities was created to revitalise peoples relationship to everyday places by giving them the opportunity and motivation to create and share complex digital stories in simple and engaging ways. To do so we developed new design processes and methods for both the research team and the end user to appropriate web and mobile technologies. To do so we collaborated with ethnographers, designers and ICT researchers and developers. In teams we ran a series of workshops in a wide variety of cities in Australia to refine an engagement process and to test a series of iteratively developed prototypes to refine the systems that supported community motivation and collaboration. The result of the research is 2 fold: 1. a sophisticated prototype for researchers and designers to further experiment with community engagement methodologies using existing and emerging communications technologies. 2. A ‘human dimensions matrix’. This matrix assists in the identification and modification of place based interventions in the social, technical, spatial, cultural, pedagogical conditions of any given community. This matrix has now become an essential part of a number of subsequent projects and assists design collaborators to successfully conceptualise, generate and evaluate interactive experiences. the research team employed practice-led action research methodologies that involved a collaborative effort across the fields of interaction design and social science, in particular ethnography, in order to: 1. seek, contest, refine a design methodology that would maximise the successful application of a dynamic system to create new kinds of interactions between people, places and artefacts’. 2. To design and deploy an application that intervenes in place-based and mobile technologies and offers people simple interfaces to create and share digital stories. Cipher Cities was awarded 3 separate CRC competitive grants (over $270,000 in total) to assist 3 stages of research covering the development of the Ethnographic Design Methodologies, the development of the tools, and the testing and refinement of both the engagement models and technologies. The resulting methodologies and tools are in the process of being commercialised by the Australasian CRC for Interaction Design.

Evidence-based practice and information literacy

Evidence-based Practice (EBP) has recently emerged as a topic of discussion amongst professionals within the library and information services (LIS) industry. Simply stated, EBP is the process of using formal research skills and methods to assist in decision making and establishing best practice. The emerging interest in EBP within the library context serves to remind the library profession that research skills and methods can help ensure that the library industry remains current and relevant in changing times. The LIS sector faces ongoing challenges in terms of the expectation that financial and human resources will be managed efficiently, particularly if library budgets are reduced and accountability to the principal stakeholders is increased. Library managers are charged with the responsibility to deliver relevant and cost effective services, in an environment characterised by rapidly changing models of information provision, information access and user behaviours. Consequently they are called upon not only to justify the services they provide, or plan to introduce, but also to measure the effectiveness of these services and to evaluate the impact on the communities they serve. The imperative for innovation in and enhancements to library practice is accompanied by the need for a strong understanding of the processes of review, measurement, assessment and evaluation. In 2001 the Centre for Information Research was commissioned by the Chartered Institute of Library and Information Professionals (CILIP) in the UK to conduct an examination into the research landscape for library and information science. The examination concluded that research is “important for the LIS [library and information science] domain in a number of ways” (McNicol & Nankivell, 2001, p.77). At the professional level, research can inform practice, assist in the future planning of the profession, raise the profile of the discipline, and indeed the reputation and standing of the library and information service itself. At the personal level, research can “broaden horizons and offer individuals development opportunities” (McNicol & Nankivell, 2001, p.77). The study recommended that “research should be promoted as a valuable professional activity for practitioners to engage in” (McNicol & Nankivell, 2001, p.82). This chapter will consider the role of EBP within the library profession. A brief review of key literature in the area is provided. The review considers issues of definition and terminology, highlights the importance of research in professional practice and outlines the research approaches that underpin EBP. The chapter concludes with a consideration of the specific application of EBP within the dynamic and evolving field of information literacy (IL).

A framework for network RTK data processing based on grid computing

Real-Time Kinematic (RTK) positioning is a technique used to provide precise positioning services at centimetre accuracy level in the context of Global Navigation Satellite Systems (GNSS). While a Network-based RTK (N-RTK) system involves multiple continuously operating reference stations (CORS), the simplest form of a NRTK system is a single-base RTK. In Australia there are several NRTK services operating in different states and over 1000 single-base RTK systems to support precise positioning applications for surveying, mining, agriculture, and civil construction in regional areas. Additionally, future generation GNSS constellations, including modernised GPS, Galileo, GLONASS, and Compass, with multiple frequencies have been either developed or will become fully operational in the next decade. A trend of future development of RTK systems is to make use of various isolated operating network and single-base RTK systems and multiple GNSS constellations for extended service coverage and improved performance. Several computational challenges have been identified for future NRTK services including: • Multiple GNSS constellations and multiple frequencies • Large scale, wide area NRTK services with a network of networks • Complex computation algorithms and processes • Greater part of positioning processes shifting from user end to network centre with the ability to cope with hundreds of simultaneous users’ requests (reverse RTK) There are two major requirements for NRTK data processing based on the four challenges faced by future NRTK systems, expandable computing power and scalable data sharing/transferring capability. This research explores new approaches to address these future NRTK challenges and requirements using the Grid Computing facility, in particular for large data processing burdens and complex computation algorithms. A Grid Computing based NRTK framework is proposed in this research, which is a layered framework consisting of: 1) Client layer with the form of Grid portal; 2) Service layer; 3) Execution layer. The user’s request is passed through these layers, and scheduled to different Grid nodes in the network infrastructure. A proof-of-concept demonstration for the proposed framework is performed in a five-node Grid environment at QUT and also Grid Australia. The Networked Transport of RTCM via Internet Protocol (Ntrip) open source software is adopted to download real-time RTCM data from multiple reference stations through the Internet, followed by job scheduling and simplified RTK computing. The system performance has been analysed and the results have preliminarily demonstrated the concepts and functionality of the new NRTK framework based on Grid Computing, whilst some aspects of the performance of the system are yet to be improved in future work.

Bearing-only SLAM : a vision-based navigation system for autonomous robots

To navigate successfully in a previously unexplored environment, a mobile robot must be able to estimate the spatial relationships of the objects of interest accurately. A Simultaneous Localization and Mapping (SLAM) sys- tem employs its sensors to build incrementally a map of its surroundings and to localize itself in the map simultaneously. The aim of this research project is to develop a SLAM system suitable for self propelled household lawnmowers. The proposed bearing-only SLAM system requires only an omnidirec- tional camera and some inexpensive landmarks. The main advantage of an omnidirectional camera is the panoramic view of all the landmarks in the scene. Placing landmarks in a lawn field to define the working domain is much easier and more flexible than installing the perimeter wire required by existing autonomous lawnmowers. The common approach of existing bearing-only SLAM methods relies on a motion model for predicting the robot’s pose and a sensor model for updating the pose. In the motion model, the error on the estimates of object positions is cumulated due mainly to the wheel slippage. Quantifying accu- rately the uncertainty of object positions is a fundamental requirement. In bearing-only SLAM, the Probability Density Function (PDF) of landmark position should be uniform along the observed bearing. Existing methods that approximate the PDF with a Gaussian estimation do not satisfy this uniformity requirement. This thesis introduces both geometric and proba- bilistic methods to address the above problems. The main novel contribu- tions of this thesis are: 1. A bearing-only SLAM method not requiring odometry. The proposed method relies solely on the sensor model (landmark bearings only) without relying on the motion model (odometry). The uncertainty of the estimated landmark positions depends on the vision error only, instead of the combination of both odometry and vision errors. 2. The transformation of the spatial uncertainty of objects. This thesis introduces a novel method for translating the spatial un- certainty of objects estimated from a moving frame attached to the robot into the global frame attached to the static landmarks in the environment. 3. The characterization of an improved PDF for representing landmark position in bearing-only SLAM. The proposed PDF is expressed in polar coordinates, and the marginal probability on range is constrained to be uniform. Compared to the PDF estimated from a mixture of Gaussians, the PDF developed here has far fewer parameters and can be easily adopted in a probabilistic framework, such as a particle filtering system. The main advantages of our proposed bearing-only SLAM system are its lower production cost and flexibility of use. The proposed system can be adopted in other domestic robots as well, such as vacuum cleaners or robotic toys when terrain is essentially 2D.

Dynamic Lock Synchronisation for collaborative 3D applications

In a typical collaborative application, users contends for common resources by mutual exclusion. The introduction of multi-modal environment, however, introduced problems such as frequent dropping of connection or limited connectivity speed of mobile users. This paper target 3D resources which require additional considerations such as dependency of users' manipulation command. This paper introduces Dynamic Locking Synchronisation technique to enable seamless and collaborative environment for large number of user, by combining the contention-free concepts of locking mechanism and the seamless nature of lockless design.

Big art small viewer : a collaborative community project

Campus Kindergarten is a community-based centre for early childhood education and care located on campus at the University of Queensland (UQ) in Brisbane, Australia. Being located within this diverse community has presented many opportunities for Campus Kindergarten. It is creating and embracing possibilities that has formed the basis for ongoing projects for children and teachers involving research and investigation. In 2002 Campus Kindergarten embarked on a collaborative project with the Art Museum bringing together these two departments within the university community.

Collaborative recovery: An integrative model for working with individuals that experience chronic or recurring mental illness.

Objectives: Recovery is an emerging movement in mental health. Evidence for recovery-based approaches is not well developed and approaches to implement recovery-oriented services are not well articulated. The collaborative recovery model (CRM) is presented as a model that assists clinicians to use evidence-based skills with consumers, in a manner consistent with the recovery movement. A current 5 year multisite Australian study to evaluate the effectiveness of CRM is briefly described. Conclusion: The collaborative recovery model puts into practice several aspects of policy regarding recovery-oriented services, using evidence-based practices to assist individuals who have chronic or recurring mental disorders (CRMD). It is argued that this model provides an integrative framework combining (i) evidence-based practice; (ii) manageable and modularized competencies relevant to case management and psychosocial rehabilitation contexts; and (iii) recognition of the subjective experiences of consumers.

Mining Negative Relevance Feedback for Information Filtering

It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.

An effective model of using negative relevance feedback for information filtering

Over the years, people have often held the hypothesis that negative feedback should be very useful for largely improving the performance of information filtering systems; however, we have not obtained very effective models to support this hypothesis. This paper, proposes an effective model that use negative relevance feedback based on a pattern mining approach to improve extracted features. This study focuses on two main issues of using negative relevance feedback: the selection of constructive negative examples to reduce the space of negative examples; and the revision of existing features based on the selected negative examples. The former selects some offender documents, where offender documents are negative documents that are most likely to be classified in the positive group. The later groups the extracted features into three groups: the positive specific category, general category and negative specific category to easily update the weight. An iterative algorithm is also proposed to implement this approach on RCV1 data collections, and substantial experiments show that the proposed approach achieves encouraging performance.

Augmenting competitiveness of cities through tourism planning : the role of collaborative decision support systems

Many cities around the globe are now considering tourism facilities and their remarkable revenues in order to become competitive in the global economy. In many of these cities a great emphasis is given to the cultural tourism as it plays an important role in the establishment of creative and knowledge-base of cities. The literature points out the importance of local community support in cultural tourism. In such context, the use of new approach and technologies in tourism planning in order to increase the community participation and competitiveness of cities’ cultural assets gains a great significance. This paper advocates a new planning approach for tourism planning, particularly for cultural tourism, to increase the competitiveness of cities. As part of this new approach, the paper introduces the joined up planning approach integrated with a collaborative decision support system: ‘the community-oriented decision support system’. This collaborative planning support system is an effective and efficient tool for cultural tourism planning, which provides a platform for local communities’ participation in the development decision process.

A role mining inspired approach to representing user behaviour in ERP systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Primary students' group metacognitive processes in a computer supported collaborative learning environment

The current understanding of students’ group metacognition is limited. The research on metacognition has focused mainly on the individual student. The aim of this study was to address the void by developing a conceptual model to inform the use of scaffolds to facilitate group metacognition during mathematical problem solving in computer supported collaborative learning (CSCL) environments. An initial conceptual framework based on the literature from metacognition, cooperative learning, cooperative group metacognition, and computer supported collaborative learning was used to inform the study. In order to achieve the study aim, a design research methodology incorporating two cycles was used. The first cycle focused on the within-group metacognition for sixteen groups of primary school students working together around the computer; the second cycle included between-group metacognition for six groups of primary school students working together on the Knowledge Forum® CSCL environment. The study found that providing groups with group metacognitive scaffolds resulted in groups planning, monitoring, and evaluating the task and team aspects of their group work. The metacognitive scaffolds allowed students to focus on how their group was completing the problem-solving task and working together as a team. From these findings, a revised conceptual model to inform the use of scaffolds to facilitate group metacognition during mathematical problem solving in computer supported collaborative learning (CSCL) environments was generated.