Fellowship plan and conceptual framework

This document is written to provide: (1) a brief plan of the intended directions of the ALTC program ‘A Pedagogy of Supervision in the Technology disciplines’; and (2) an overview of existing research outcomes which are likely to be of interest to the technology disciplines, including some cross disciplinary research and some focussed specifically on some part of the technology field.

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.

Developing a best practice framework for implementing public private partnerships (PPP) in Hong Kong

Public Private Partnership (PPP) is a well established methodology for procuring public works projects. By incorporating the private sector’s expertise, efficiency, innovation, business sense, risk sharing, financing etc. into public works projects, the quality of public services and facilities can be uplifted. Like many jurisdictions, Hong Kong is also keen to take aboard this methodology which is so familiar but yet so distant. Although they have been one of the first jurisdictions to utilise the private sector in public works projects, their comfortable financial reserves has meant that there has been no urge to push the movement until recently. PPP has become increasingly popular amongst governments. The Hong Kong Special Administrative Region (HKSAR) government is no exception. Some of the more active works departments have commissioned studies to investigate the best ways to deliver these projects, others have even trialed the method themselves. The efficiency Unit of the HKSAR government has also become an active arm in conducting research in this area. Although so, the information that is currently available is still very broad. Building from their works there is a need to develop a best practice framework for implementing PPP projects in Hong Kong by incorporating international experiences. To develop a best practice framework will require thorough investigation into the benefits, difficulties and critical success factor of PPP. PPP should also be compared with other procurement methods. In order to do so it is important to clearly understand the local situation by an analysis of projects conducted to date. Lessons learnt can further be derived from other countries and incorporated to those derived locally. Finally the best conditions in terms of project nature, complexity, types, and scales for adopting PPP should be derived. The aim and objectives of this study were achieved via a comprehensive literature review, in-depth case analyses, interview survey with experts from both Hong Kong and overseas, and finally a large scale data collection was conducted via a questionnaire survey with PPP practitioners. These findings were further triangulated before they were used as the basis to form the best practice framework presented in this thesis. The framework was then further validated by PPP experts to ensure it is comprehensive, objective, reliable and practical. This study has presented a methodology that can be adopted for future studies. It has also updated our knowledge on the development trends of PPP as well as opened up the experiences of other jurisdictions. The findings have shown that the local industry is familiar with “what” should be done in PPP projects but they are unsure of “how” these goals can be achieved. This framework has allowed this further knowledge to be delivered to PPP practitioners. As a result, the development of this framework can help to resolve the current economic crisis by encouraging more developments and business opportunities for the private sector. In addition, the correct projects can be delivered by PPP, the advantages of PPP can be maximised, and the general public can benefit from the private sector’s participation.

National consumer credit laws, financial exclusion and interest rate caps : The case for diversity within a centralised framework

Australia is going through a major reform of consumer credit regulation, with the implementation of a proposal to transfer regulatory responsibility from the State and Territory Governments to the Commonwealth Government. While the broad policy approach is supported, the reform process has missed a significant opportunity to engage directly with issues of financial exclusion and with the potential role of regulation to reduce financial exclusion. The imposition of an interest rate cap can limit the impact of financial exclusion. However, the future of the existing interest rate caps is uncertain, given the diversity of approaches, and the heated debate that surrounds this issue. In the absence of support for regulatory initiatives to increase the availability of low cost, small loans, permitting regulatory diversity on this issue of interest rate caps, within an otherwise centralised regulatory framework., can minimise the impact of financial exclusion on consumers.

A Proposed Framework for Understanding Information Security Culture and Practices in the Saudi Context

An examination of Information Security (IS) and Information Security Management (ISM) research in Saudi Arabia has shown the need for more rigorous studies focusing on the implementation and adoption processes involved with IS culture and practices. Overall, there is a lack of academic and professional literature about ISM and more specifically IS culture in Saudi Arabia. Therefore, the overall aim of this paper is to identify issues and factors that assist the implementation and the adoption of IS culture and practices within the Saudi environment. The goal of this paper is to identify the important conditions for creating an information security culture in Saudi Arabian organizations. We plan to use this framework to investigate whether security culture has emerged into practices in Saudi Arabian organizations.

Information security culture : a behaviour compliance conceptual framework

Understanding the complex dynamic and uncertain characteristics of organisational employees who perform authorised or unauthorised information security activities is deemed to be a very important and challenging task. This paper presents a conceptual framework for classifying and organising the characteristics of organisational subjects involved in these information security practices. Our framework expands the traditional Human Behaviour and the Social Environment perspectives used in social work by identifying how knowledge, skills and individual preferences work to influence individual and group practices with respect to information security management. The classification of concepts and characteristics in the framework arises from a review of recent literature and is underpinned by theoretical models that explain these concepts and characteristics. Further, based upon an exploratory study of three case organisations in Saudi Arabia involving extensive interviews with senior managers, department managers, IT managers, information security officers, and IT staff; this article describes observed information security practices and identifies several factors which appear to be particularly important in influencing information security behaviour. These factors include values associated with national and organisational culture and how they manifest in practice, and activities related to information security management.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Graduate Attribute Mapping With the Extended CDIO Framework

The CDIO (Conceive-Design-Implement-Operate) Initiative has been globally recognised as an enabler for engineering education reform. With the CDIO process, the CDIO Standards and the CDIO Syllabus, many scholarly contributions have been made around cultural change, curriculum reform and learning environments. In the Australasian region, reform is gaining significant momentum within the engineering education community, the profession, and higher education institutions. This paper presents the CDIO Syllabus cast into the Australian context by mapping it to the Engineers Australia Graduate Attributes, the Washington Accord Graduate Attributes and the Queensland University of Technology Graduate Capabilities. Furthermore, in recognition that many secondary schools and technical training institutions offer introductory engineering technology subjects, this paper presents an extended self-rating framework suited for recognising developing levels of proficiency at a preparatory level. A demonstrator mapping tool has been created to demonstrate the application of this extended graduate attribute mapping framework as a precursor to an integrated curriculum information model.

Mixing colours: An ICT tool based on a semiotic framework for mathematical meaning-makng about ratio and fractions

This paper reports on the research and development of an ICT tool to facilitate the learning of ratio and fractions by adult prisoners. The design of the ICT tool was informed by a semiotic framework for mathematical meaning-making. The ICT tool thus employed multiple semiotic resources including topological, typological, and social-actional resources. The results showed that individual semiotic resource could only represent part of the mathematical concept, while at the same time it might signify something else to create a misconception. When multiple semiotic resources were utilised the mathematical ideas could be better learnt.

An extended CDIO syllabus framework with preparatory engineering proficiencies

The CDIO Initiative has been globally recognised as an enabler for engineering education reform. With the CDIO process, the CDIO Standards and the CDIO Syllabus, many scholarly contributions have been made around cultural change, curriculum reform and learning environments. In the Australasian region, reform is gaining significant momentum within the engineering education community, the profession, and higher education institutions. This paper presents the CDIO Syllabus cast into the Australian context by mapping it to the Engineers Australia Graduate Attributes, the Washington Accord Graduate Attributes and the Queensland University of Technology Graduate Capabilities. Furthermore, in recognition that many secondary schools and technical training institutions offer introductory engineering technology subjects, this paper presents an extended self-rating framework suited for recognising developing levels of proficiency at a preparatory level. The framework is consistent with conventional application to undergraduate programs and professional practice, but adapted for the preparatory context. As with the original CDIO framework with proficiency levels, this extended framework is informed by Bloom’s Educational Objectives. A proficiency evaluation of Queensland Study Authority’s Engineering Technology senior syllabus is demonstrated indicating proficiency levels embedded within this secondary school subject within a preparatory scope. Through this extended CDIO framework, students and faculty have greater awareness and access to tools to promote (i) student engagement in their own graduate capability development, (ii) faculty engagement in course and program design, through greater transparency and utility of the continuum of graduate capability development with associate levels of proficiency, and the context in which they exist in terms of pre-tertiary engineering studies; and (iii) course maintenance and quality audit methodology for the purpose of continuous improvement processes and program accreditation.

An evaluation framework for educational reform projects for teacher quality improvements in developing countries : a case study of Egyptian education reform

The role of the evaluation for Official Development Assistance (ODA) enterprises including educational development has become critical after increasing “aid fatigue” experienced by the international community in the 1990s. To date, however, monitoring and evaluating outcomes of the projects has been limited to the project life. Consequently these have been mainly through the international aid agencies. Furthermore, the monitoring and evaluation led by international aid agencies have paid little attention to aspects of the sustainability of technical cooperation in educational development. To sustain the impact of technical cooperation, the reinforcement of evaluation has drawn increasing attention in light of the emerging modalities in international development. Therefore this research was inspired to investigate alternative evaluation frameworks for an educational reform project for teacher quality improvement that may increase possibilities for long term sustainability. Importantly, the new modalities in international development and educational issues provide new options. In addition, the research reviewed theoretical and practical issues surrounding evaluation in general, and highlighted the evaluation of education reform projects. The research reported explored via case studies, the evaluation processes employed by the Egyptian education reform projects implemented by the Japan International Cooperation Agency (JICA) and the United Nations Children’s Fund (UNICEF). The case studies used three data sources (archival and relevant documents, a survey questionnaire and interviews) to illuminate the contextually-embedded evaluation processes. The research found that process evaluation is a potential alternative method since it is likely to be locally institutionalised, which may yield long-term sustainability of the projects.

Improved GMM-based speaker verification using SVM-driven impostor dataset selection

The problem of impostor dataset selection for GMM-based speaker verification is addressed through the recently proposed data-driven background dataset refinement technique. The SVM-based refinement technique selects from a candidate impostor dataset those examples that are most frequently selected as support vectors when training a set of SVMs on a development corpus. This study demonstrates the versatility of dataset refinement in the task of selecting suitable impostor datasets for use in GMM-based speaker verification. The use of refined Z- and T-norm datasets provided performance gains of 15% in EER in the NIST 2006 SRE over the use of heuristically selected datasets. The refined datasets were shown to generalise well to the unseen data of the NIST 2008 SRE.

Data-driven impostor selection for T-norm score normalisation and the background dataset in SVM-based speaker verification

A data-driven background dataset refinement technique was recently proposed for SVM based speaker verification. This method selects a refined SVM background dataset from a set of candidate impostor examples after individually ranking examples by their relevance. This paper extends this technique to the refinement of the T-norm dataset for SVM-based speaker verification. The independent refinement of the background and T-norm datasets provides a means of investigating the sensitivity of SVM-based speaker verification performance to the selection of each of these datasets. Using refined datasets provided improvements of 13% in min. DCF and 9% in EER over the full set of impostor examples on the 2006 SRE corpus with the majority of these gains due to refinement of the T-norm dataset. Similar trends were observed for the unseen data of the NIST 2008 SRE.