The vanishing endpoint of settler colonialism

In this paper, we interrogate the way that narratives about the unfolding of settler colonialism through time are encoded in recent Australian Indigenous policy frameworks. We argue that the postcolonial image of a single transformative moment of radical political break is embedded in Australian policy frameworks, but is deployed in ways that fuse this idea with the moment of colonial completion and in so doing assist the colonial project. By merging the moment of decolonisation and the moment of colonial completion, temporal narratives mobilise conservative and progressive settler voices towards colonial goals. We identify three recent policy approaches: reconciliation, neoliberal contractualism and intervention, and interrogate the narratives of the present and future that they reflect and deploy. We argue these unacknowledged stories of the colonial future must be contested, so that debates about how settler and Indigenous people might live together differently across time are not foreclosed.

Modeling users’ web search behavior and their cognitive styles

Previous studies have shown that users’ cognitive styles play an important role during Web searching. However, only limited studies have showed the relationship between cognitive styles and Web search behavior. Most importantly, it is not clear which components of Web search behavior are influenced by cognitive styles. This paper examines the relationships between users’ cognitive styles and their Web searching and develops a model that portrays the relationship. The study uses qualitative and quantitative analyses to inform the study results based on data gathered from 50 participants. A questionnaire was utilised to collect participants’ demographic information, and Riding’s (1991) Cognitive Style Analysis (CSA) test to assess their cognitive styles. Results show that users’ cognitive styles influenced their information searching strategies, query reformulation behaviour, Web navigational styles and information processing approaches. The user model developed in this study depicts the fundamental relationships between users’ Web search behavior and their cognitive styles. Modeling Web search behavior with a greater understanding of user’s cognitive styles can help information science researchers and information systems designers to bridge the semantic gap between the user and the systems. Implications of the research for theory and practice, and future work are discussed.

A comparison of the histochemical and image-derived proteoglycan content of articular cartilage

There are several methods for determining the proteoglycan content of cartilage in biomechanics experiments. Many of these include assay-based methods and the histochemistry or spectrophotometry protocol where quantification is biochemically determined. More recently a method based on extracting data to quantify proteoglycan content has emerged using the image processing algorithms, e.g., in ImageJ, to process histological micrographs, with advantages including time saving and low cost. However, it is unknown whether or not this image analysis method produces results that are comparable to those obtained from the biochemical methodology. This paper compares the results of a well-established chemical method to those obtained using image analysis to determine the proteoglycan content of visually normal (n=33) and their progressively degraded counterparts with the protocols. The results reveal a strong linear relationship with a regression coefficient (R2) = 0.9928, leading to the conclusion that the image analysis methodology is a viable alternative to the spectrophotometry.

Image segmentation and pose estimation of humans in video

This thesis introduces improved techniques towards automatically estimating the pose of humans from video. It examines a complete workflow to estimating pose, from the segmentation of the raw video stream to extract silhouettes, to using the silhouettes in order to determine the relative orientation of parts of the human body. The proposed segmentation algorithms have improved performance and reduced complexity, while the pose estimation shows superior accuracy during difficult cases of self occlusion.

Electrochemical formation of Cu/Ag surfaces and their applicability as heterogeneous catalysts

In this work the electrochemical formation of porous Cu/Ag materials is reported via the simple and quick method of hydrogen bubble templating. The bulk and surface composition ratio between Ag and Cu was varied in a systematic manner and was readily controlled by the concentration of precursor metal salts in the electrolyte. The incorporation of Ag within the Cu scaffold only affected the formation of well-defined pores at high Ag loading whereas the internal pore wall structure gradually transformed from dendritic to cube like and finally needle like structures, which was due to the concomitant formation of Cu2O within the structure. The materials were characterised by scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Their surface properties were further investigated by surface enhanced Raman spectroscopy (SERS) and electrochemically probed by recording the hydrogen evolution reaction (HER) which is highly sensitive to the nature of the surface. The effect of surface composition was then investigated for its influence on two catalytic reactions namely the reduction of ferricyanide ions with thiosulphate ions and the reduction of 4-nitrophenol with NaBH4 in aqueous solution where it was found that the presence of Ag had a beneficial effect in both cases but more so in the case of nitrophenol reduction. It is believed that this material may have many more potential applications in the area of catalysis, electrocatalysis and photocatalysis.

Dealing with shadows : capturing intrinsic scene appearance for image-based outdoor localisation

In outdoor environments shadows are common. These typically strong visual features cause considerable change in the appearance of a place, and therefore confound vision-based localisation approaches. In this paper we describe how to convert a colour image of the scene to a greyscale invariant image where pixel values are a function of underlying material property not lighting. We summarise the theory of shadow invariant images and discuss the modelling and calibration issues which are important for non-ideal off-the-shelf colour cameras. We evaluate the technique with a commonly used robotic camera and an autonomous car operating in an outdoor environment, and show that it can outperform the use of ordinary greyscale images for the task of visual localisation.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Large-scale analysis of formations in soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Consumer created reviews and ratings : the importance of word of mouth in information search

This study explored the creation, dissemination and exchange of electronic word of mouth, in the form of product reviews and ratings of digital technology products. Based on 43 in-depth interviews and 500 responses to an online survey, it reveals a new communication model describing consumers' info-active and info-passive information search styles. The study delivers an in-depth understanding of consumers' attitudes towards current advertising tools and user-generated content, and points to new marketing techniques emerging in the online environment.

Cyclic mechanical strain guides capillary-like morphology in vitro

Introduction Stretching of tissue stimulates angiogenesis but increased motion at a fracture site hinders revascularisation. In vitro studies have indicated that mechanical stimuli promote angiogenic responses in endothelial cells, but can either inhibit or enhance responses when applied directly to angiogenesis assays. We anticipated that cyclic tension applied during endothelial network assembly would increase vascular structure formation up to a certain threshold. Methods Fibroblast/HUVEC co-cultures were subjected to cyclic equibiaxial strain (1 Hz; 6 h/day; 7 days) using the FlexerCell FX-4000T system and limiting rings for simultaneous application of multiple strain magnitudes (0–13%). Cells were labelled using anti-PECAM-1, and image analysis provided measures of endothelial network length and numbers of junctions. Results Cyclic stretching had no significant effect on the total length of endothelial networks (P > 0.2) but resulted in a strain-dependent decrease in branching and localised alignments of endothelial structures, which were in turn aligned with the supporting fibroblastic construct. Conclusion The organisation of endothelial networks under cyclic strain is dominated by structural adaptation to the supporting construct. It may be that, in fracture healing, the formation and integrity of the granulation tissue and callus is ultimately critical in revascularisation and its failure under severe strain conditions.

Phenytoin metabolism by human cytochrome P450 : involvement of P450 3A and 2C forms in secondary metabolism and drug-protein adduct formation

The anticonvulsant phenytoin (5,5-diphenylhydantoin) provokes a skin rash in 5 to 10% of patients, which heralds the start of an idiosyncratic reaction that may result from covalent modification of normal self proteins by reactive drug metabolites. Phenytoin is metabolized by cytochrome P450 (P450) enzymes primarily to 5-(p-hydroxyphenyl-),5-phenylhydantoin (HPPH), which may be further metabolized to a catechol that spontaneously oxidizes to semiquinone and quinone species that covalently modify proteins. The aim of this study was to determine which P450s catalyze HPPH metabolism to the catechol, proposed to be the final enzymatic step in phenytoin bioactivation. Recombinant human P450s were coexpressed with NADPH-cytochrome P450 reductase in Escherichia coli. Novel bicistronic expression vectors were constructed for P450 2C19 and the three major variants of P450 2C9, i.e., 2C9*1, 2C9*2, and 2C9*3. HPPH metabolism and covalent adduct formation were assessed in parallel. P450 2C19 was the most effective catalyst of HPPH oxidation to the catechol metabolite and was also associated with the highest levels of covalent adduct formation. P450 3A4, 3A5, 3A7, 2C9*1, and 2C9*2 also catalyzed bioactivation of HPPH, but to a lesser extent. Fluorographic analysis showed that the major targets of adduct formation in bacterial membranes were the catalytic P450 forms, as suggested from experiments with human liver microsomes. These results suggest that P450 2C19 and other forms from the 2C and 3A subfamilies may be targets as well as catalysts of drug-protein adduct formation from phenytoin.

Using image quality metrics to detect smoke-affected laser data

Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

Supplementary information : weighted tree kernels for sequence analysis

Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.