Towards condition-invariant sequence-based route recognition

In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountainbiking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

Government community service contracts : restraining abuse of power

The use of grant contracts to deliver community services is now a significant feature of all Australian government administrations. These contracts are the primary instrument governing the provision of such services to citizens and are largely outside the usual parliamentary review mechanisms and constraints. This article examines the extent of the erosion of fundamental constitutional principles facilitated by the use of private contracts, by applying the principles used in scrutiny of delegated legislation to standard form federal and State community service contracts. It reveals extensive executive power which, if the relationship were founded in legislative instruments rather than in private contract, would have to be justified to Parliament at least and possibly not tolerated.

Not for profit income tax exemption : is there a hole in the bucket, dear Henry?

Australia’s Future Tax System Review, headed by the then head of the Australian Treasury, and the Productivity Commission’s Research Report on the not for profit sector, both examined the state of tax concessions to Australia’s not for profit sector in the light of the High Court’s decision in Commissioner of Taxation v Word Investments Ltd. Despite being unable to quantify with any certainty the pre- or post-Word Investments cost of the tax concessions, both Reports indicated their support for continuation of the income tax exemption. However, the government acted in the 2011 Budget to target the not for profit income tax concessions more precisely, mainly on competitive neutrality grounds. This article examines the income tax exemption by applying the five taxation design principles, proposed in the Australia’s Future Tax System Review, for assessing tax expenditure. The conclusion is that the exemptions can be justified and, further, that a rationale for the exemption can be consistent with the reasoning in the Word Investments case.

Domestic and international innovation partnerships : do they matter for innovation outcomes of South African firms?

This paper studies the impact of the diversity of domestic and international innovation partnerships on the innovation outcomes of South African firms. A number of competing hypotheses are formulated and tested empirically using a sample of South African firms in manufacturing and services by applying Ordinary Least Squares regression analyses. Results show that having an innovation partnership, particularly an international partnership, is beneficial to innovation outcomes. However, it also emerges that too diverse a set of international partnerships is detrimental to innovation outcomes. The paper concludes with a discussion and a number of proposals for future research.

Using Web Search Logs to Identify Query Classification Terms

Purpose – The work presented in this paper aims to provide an approach to classifying web logs by personal properties of users. Design/methodology/approach – The authors describe an iterative system that begins with a small set of manually labeled terms, which are used to label queries from the log. A set of background knowledge related to these labeled queries is acquired by combining web search results on these queries. This background set is used to obtain many terms that are related to the classification task. The system then ranks each of the related terms, choosing those that most fit the personal properties of the users. These terms are then used to begin the next iteration. Findings – The authors identify the difficulties of classifying web logs, by approaching this problem from a machine learning perspective. By applying the approach developed, the authors are able to show that many queries in a large query log can be classified. Research limitations/implications – Testing results in this type of classification work is difficult, as the true personal properties of web users are unknown. Evaluation of the classification results in terms of the comparison of classified queries to well known age-related sites is a direction that is currently being exploring. Practical implications – This research is background work that can be incorporated in search engines or other web-based applications, to help marketing companies and advertisers. Originality/value – This research enhances the current state of knowledge in short-text classification and query log learning. Classification schemes, Computer networks, Information retrieval, Man-machine systems, User interfaces

An exploration of the role of web and mobile social media in the implementation of e-Government in Malaysia

This paper reports on an exploratory study of the role of web and social media in e-governments, especially in the context of Malaysia, with some comparisons and contrasts from other countries where such governmental efforts have been underway for awhile. It describes the current e-government efforts in Malaysia, and proposes that applying a theoretical framework would help understand the context and streamline these ongoing efforts. Specifically, it lays out a theoretical and cultural framework based on Mary Douglas’ (1996) Grid-Group Theory, Mircea Georgescu’s (2005) Three Pillars of E-Government, and Gerald Grant’s and Derek Chau’s (2006) Generic Framework for E-Government. Although this study is in its early stages, it has relevance to everyone who is interested in e-government efforts across the world, and especially relevant to developing countries.

Thresholds for error probability measures of business process models

The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2,000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curves method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.

Feature-based visual odometry and featureless place recognition for SLAM in 2.5D environments

In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

Multiple perspectives of design thinking in business education

Business education leaders have expressed interest in learning more about design and design thinking and their contributions to better problem framing, problem solving and to generating new solutions. Many business schools have engaged in educational programs with students from multiple disciplines, applying design thinking to business problems around workplace issues. This paper investigates a range of educational programs that teach design thinking to students in business education, at undergraduate and postgraduate levels around the world. We identify four patterns of program delivery that are emerging: human-centered design, integrative thinking, design management and design as strategy and discuss contributions from each. We expect that these four patterns of program delivery will continue and predict an increasing focus on programs around design as strategy in the near future.

Evaluation cortical bone elasticity in response to pulse power excitation using ultrasonic technique

This paper presents the ultrasonic velocity measurement method which investigates the possible effects of high voltage high frequency pulsed power on cortical bone material elasticity. Before applying a pulsed power signal on a live bone, it is essential to determine the safe parameters of pulsed power applied on bone non-destructively. Therefore, the possible changes in cortical bone material elasticity due to a specified pulsed power excitation have been investigated. A controllable positive buck-boost converter with adjustable output voltage and frequency has been used to generate high voltage pulses (500V magnitude at 10 KHz frequency). To determine bone elasticity, an ultrasonic velocity measurement has been conducted on two groups of control (unexposed to pulse power but in the same environmental condition) and cortical bone samples exposed to pulsed power. Young’s modulus of cortical bone samples have been determined and compared before and after applying the pulsed power signal. After applying the high voltage pulses, no significant variation in elastic property of cortical bone specimens was found compared to the control. The result shows that pulsed power with nominated parameters can be applied on cortical bone tissue without any considerable negative effect on elasticity of bone material.

The emergence of JD in the Australian Legal Education marketplace and its impact on academic standards

Over the last decade there has been an expansion in the number of Juris Doctor (JD) courses in the Australian legal education marketplace. Across the board it is graduate-entry, but it is currently offered in undergraduate, postgraduate and ‘hybrid’ forms. In this article we will discuss recent research conducted as part of an Australian Learning and Teaching Council grant. This project included an exploration of whether JD courses in Australia were applying different and higher level academic standards to those operating in Bachelor of Laws degrees. Our research findings reveal justification for concerns about the academic standards of some JD courses, particularly where masters level students were being taught alongside their undergraduate counterparts. They also provide some insights into perceptions in the marketplace of JD graduates. Finally, we will discuss the future viability of such courses in light of recent revisions to the Australian Qualifications Framework.

Exceptional teachers for disadvantaged schools

This article reports on the first year of the Exceptional Teachers for Disadvantaged Schools project, a teacher education approach designed to prepare high quality teachers for low socio-economic schools. The Exceptional Teachers for Disadvantaged Schools (ETDS) project is an innovative way to prepare high-quality teachers for employment in low-SES schools. The program, based at Queensland University of Technology (QUT), offers a specialised curriculum, designed to equip high-achieving pre-service teachers for work in the schools that need them most. Selected pre-service teachers at QUT are invited to take part in the trial course, based on their academic performance over the first two years of their four-year Bachelor of Education degree, and on a demonstrated commitment to social justice. These participants undertake a modified version of QUT's B Ed on-campus curriculum. They have their practicum/field experience at one of a range of disadvantaged schools throughout Queensland which have agreed to partner with QUT in the program. In the past, teacher education for disadvantaged schools has been described as applying a 'missionary' or deficit model (Larabee, 2010; Comber and Kamler, 2004; Flessa, 2007). The principals of schools participating in the ETDS react strongly against such an approach, and have explicitly asked project staff not to send them anyone who 'thinks they can save the world'. The ETDS project has moved well away from such a model, towards a position that is explicitly centred on notions of academic excellence. The project is now at the end of its first trial year.

Privacy compliance verification in cryptographic protocols

To provide privacy protection, cryptographic primitives are frequently applied to communication protocols in an open environment (e.g. the Internet). We call these protocols privacy enhancing protocols (PEPs) which constitute a class of cryptographic protocols. Proof of the security properties, in terms of the privacy compliance, of PEPs is desirable before they can be deployed. However, the traditional provable security approach, though well-established for proving the security of cryptographic primitives, is not applicable to PEPs. We apply the formal language of Coloured Petri Nets (CPNs) to construct an executable specification of a representative PEP, namely the Private Information Escrow Bound to Multiple Conditions Protocol (PIEMCP). Formal semantics of the CPN specification allow us to reason about various privacy properties of PIEMCP using state space analysis techniques. This investigation provides insights into the modelling and analysis of PEPs in general, and demonstrates the benefit of applying a CPN-based formal approach to the privacy compliance verification of PEPs.

Capacity-building workshops on the responsibility to protect (R2P) and the protection of civilians (POC) in armed conflict - Summary Report

In June 2011, a research project team from the Institute for Ethics, Governance and Law (IEGL), Queensland University of Technology, the United Nations University, and the Australian Government’s Asia Pacific Civil-Military Centre of Excellence (APCMCOE) held three Capacity-Building Workshops (the Workshops) on the Responsibility to Protect (R2P) and the Protection of Civilians (POC) in Armed Conflict in Manila, Kuala Lumpur, and Jakarta. The research project is funded by the Australian Responsibility to Protect Fund, with support from APCMCOE. Developments in Libya and Cote d’Ivoire and the actions of the United Nations Security Council have given new significance to the relationship between R2P and POC, providing impetus to the relevance and application of the POC principle recognised in numerous Security Council resolutions, and the R2P principle, which was recognised by the United Nations General Assembly in 2005 and, now, by the Security Council. The Workshops considered the relationship between R2P and POC. The project team presented the preliminary findings of their study and sought contributions and feedback from Workshop participants. Prior to the Workshops, members of the project team undertook interviews with UN offices and agencies, international organisations (IOs) and non-government organisations (NGOs) in Geneva and New York as part of the process of mapping the relationship between R2P and POC. Initial findings were considered at an Academic-Practitioner Workshop held at the University of Sydney in November 2010. In addition to an extensive literature review and a series of academic publications, the project team is preparing a practical guidance text (the Guide) on the relationship between R2P and POC to assist the United Nations, governments, regional bodies, IOs and NGOs in considering and applying appropriate protection strategies. It is intended that the Guide be presented to the United Nations Secretariat in New York in early 2012. The primary aim of the Workshops was to test the project’s initial findings among an audience of diplomats, military, police, civilian policy-makers, practitioners, researchers and experts from within the region. Through dialogue and discussion, the project team gathered feedback – comments, questions, critique and suggestions – to help shape the development of practical guidance about when, how and by whom R2P and POC might be implemented.

Structural damage detection using frequency response functions and neural networks

This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.