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.

Civil applications in the Magistrates Court are often set down for hearing by a judicial registrar, but there is now some uncertainty on the limitation of this practice

The decision of the District Court of Queensland in Mark Treherne & Associates -v- Murray David Hopkins [2010] QDC 36 will have particular relevance for early career lawyers. This decision raises questions about the limits of the jurisdiction of judicial registrars in the Magistrates Court.

Default judgment set aside without costs

A recent District Court case is believed to be the first in Queensland in which UCPR r 5 has been used to support the setting aside of a regularly entered default judgment without a costs order.

Corporations Act 2001 s 459G : application to set aside statutory demand

The application before the court in Millerview Constructions Pty Ltd v Palmer Plumbing Pty Ltd [2008] QSC 005 raised a significant question regarding the appropriate construction of s 459G of the Corporations Act 2001 (Cth) (the Act). The decision emphasises the importance of ensuring that any application to set aside a statutory demand must be served in a timely way on the creditor at the creditor’s address for service as stated in the statutory demand, or in strict compliance with another manner authorised by the Act.

Navigating in a sea of change : second set of working papers of the higher education policy project

This volume represents teh second collection of working papers and articles by participants in the Higher Education Policy Project (HEPP), a project funded by the Australian Research Council and based in the Graduate School of Education at the University of Queensland. The first volume, 'Higher Education in Transition: Working Papers of the Higher Education Policy Project (Bella, McCollow and Knight, 1993), took the broad theme of "higher education in transition" in order to introduce readers the HEPP and give them some idea of the breadth of the research being pursued by the HEPP research team itself and by the cohort of post-graduate students also associated with the project. Since then, higher education has remained in transition. Stubborn and resurgent questions continue: such as what a university ought to be, what forms of research should be supported in a mass system, and how institutional accountability can be demonstrated. In differing ways and using a variety of research perspectives and methodologies, the contributors to this volume explore these and other questions of relevance to higher education today.

Hydrogen-bonding in the structures of the 1:1 salts of isonipecotamide with a set of four polyfunctional monocyclic heteroaromatic carboxylic acids

The crystal structures of the 1:1 proton-transfer compounds of isonipecotamide (piperidine-4-carboxamide) with the monocyclic heteroaromatic carboxylic acids, isonicotinic acid, picolinic acid, dipicolinic acid and pyrazine-2,3-dicarboxylic acid have been determined at 200 K and their hydrogen-bonding patterns examined. The compounds are respectively anhydrous 4-carbamoylpiperidinium pyridine-4-carboxylate (1), the partial hydrate 4-carbamoylpiperidinium pyridine-2-carboxylate 0.25 water (2), the solvate 4-carbamoylpiperidinium 6-carboxypyridine-2-carboxylate methanol monosolvate (3), and anhydrous 4-carbamoylpiperidinium 3-carboxypyrazine-2-carboxylate (4). In compounds 1 and 3, hydrogen-bonding interactions give two-dimensional sheet structures which feature enlarged cyclic ring systems, while in compounds 2 and 4, three-dimensional structures are found. The previously described cyclic R2/2(8) hydrogen-bonded amide-amide dimer is present in 2 and 3. The hydrogen-bonding in 2 involves the partial-occupancy water molecule while the structure of 4 is based on inter-linked homomolecular hydrogen-bonded cation-cation and anion-anion associated chains comprising head-to-tail interactions. This work further demonstrates the utility of the isonipecotamide cation in the generation of chemically stable hydrogen-bonded systems, particularly with aromatic carboxylate anions, providing crystalline solids.

A new approach for power system black-start decision-making with vague set theory

Power system restoration after a large area outage involves many factors, and the procedure is usually very complicated. A decision-making support system could then be developed so as to find the optimal black-start strategy. In order to evaluate candidate black-start strategies, some indices, usually both qualitative and quantitative, are employed. However, it may not be possible to directly synthesize these indices, and different extents of interactions may exist among these indices. In the existing black-start decision-making methods, qualitative and quantitative indices cannot be well synthesized, and the interactions among different indices are not taken into account. The vague set, an extended version of the well-developed fuzzy set, could be employed to deal with decision-making problems with interacting attributes. Given this background, the vague set is first employed in this work to represent the indices for facilitating the comparisons among them. Then, a concept of the vague-valued fuzzy measure is presented, and on that basis a mathematical model for black-start decision-making developed. Compared with the existing methods, the proposed method could deal with the interactions among indices and more reasonably represent the fuzzy information. Finally, an actual power system is served for demonstrating the basic features of the developed model and method.

The application of a set of principles to safeguard student learning engagement

Student engagement is a key contributor to student achievement and retention. Increasingly, international and Australasian universities are introducing a range of specific initiatives aimed at monitoring and intervening with students who are at risk of disengaging, particularly in their first year of study. A multi-site case study formed the focus of a national learning and teaching project to develop a suite of resources to guide good practice for safeguarding student learning engagement that were consistent with the notions of equity and social justice. Pivotal to the suite of resources is the Social Justice Framework and a set of social justice principles that emerged through a synthesis of existing literature and were further refined through the examination of qualitative data collected across the participating institutions. These social justice principles reflect general notions of equity and social justice, embrace the philosophical position of recognitive social justice, and are presented in an interconnected and co-dependent way within the framework. Participants will be provided with the opportunity to identify and discuss the practical applications of the principles to student engagement activities in their own institutions.

Encouraging visitors : a new set of guidelines for designing prison visitors’ centres

Visitors to prison are generally innocent of committing crime, but their interaction with inmates has been studied as a possible incentive to reduce recidivism. The way visitors’ centres are currently designed takes in consideration mainly security principles and the needs of guards or prison management. The human experience of the relatives or friends aiming to provide emotional support to inmates is usually not considered; facilities have been designed with an approach that often discourages people from visiting. This paper discusses possible principles to design prison visitors’ centres taking in consideration practical needs, but also human factors. A comparative case study analysis of different secure typologies, like libraries, airports or children hospitals, provides suggestions about how to approach the design of prison in order to ensure the visitor is not punished for the crimes of those they are visiting.

The effect of poser race on the happy categorization advantage depends on stimulus type, set size, and presentation duration

The question as to whether poser race affects the happy categorization advantage, the faster categorization of happy than of negative emotional expressions, has been answered inconsistently. Hugenberg (2005) found the happy categorization advantage only for own race faces whereas faster categorization of angry expressions was evident for other race faces. Kubota and Ito (2007) found a happy categorization advantage for both own race and other race faces. These results have vastly different implications for understanding the influence of race cues on the processing of emotional expressions. The current study replicates the results of both prior studies and indicates that face type (computer-generated vs. photographic), presentation duration, and especially stimulus set size influence the happy categorization advantage as well as the moderating effect of poser race.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

Rough set based approach to text classification

Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.