Using optical coherence tomography to assess corneoscleral morphology after soft contact lens wear

Purpose. To evaluate the use of optical coherence tomography (OCT) to assess the effect of different soft contact lenses on corneoscleral morphology. Methods. Ten subjects had anterior segment OCT B-scans taken in the morning and again after six hours of soft contact lens wear. For each subject, three different contact lenses were used in the right eye on non-consecutive days, including a hydrogel sphere, a silicone hydrogel sphere and a silicone hydrogel toric. After image registration and layer segmentation, analyses were performed of the first hyper-reflective layer (HRL), the epithelial basement membrane (EBL) and the epithelial thickness (HRL to EBL). A root mean square difference (RMSD) of the layer profiles and the thickness change between the morning and afternoon measurements, was used to assess the effect of the contact lens on the corneoscleral morphology. Results. The soft contact lenses had a statistically significant effect on the morphology of the anterior segment layers (p <0.001). The average amounts of change for the three lenses (average RMSD values) for the corneal region were lower (3.93±1.95 µm for the HRL and 4.02±2.14 µm for the EBL) than those measured in the limbal/scleral region (11.24±6.21 µm for the HRL and 12.61±6.42 µm for the EBL). Similarly, averaged across the three lenses, the RMSD in epithelial thickness was lower in the cornea (2.84±0.84 µm) than the limbal/scleral (5.47±1.71 µm) region. Post-hoc analysis showed that ocular surface changes were significantly smaller with the silicone hydrogel sphere lens than both the silicone hydrogel toric (p<0.005) and hydrogel sphere (p<0.02) for the combined HRL and EBL data. Conclusions. In this preliminary study, we have shown that soft contact lenses can produce small but significant changes in the morphology of the limbal/scleral region and that OCT technology is useful in assessing these changes. The clinical significance of these changes is yet to be determined.

The impact of a model of nurse education to improve knowledge and recognition of delirium in older persons by registered nurses

Introduction: Delirium is a serious issue associated with high morbidity and mortality in older hospitalised people. Early recognition enables diagnosis and treatment of underlying cause/s, which can lead to improved patient outcomes. However, research shows knowledge and accurate nurse recognition of delirium and is poor and lack of education appears to be a key issue related to this problem. Thus, the purpose of this randomised controlled trial (RCT) was to evaluate, in a sample of registered nurses, the usability and effectiveness of a web-based learning site, designed using constructivist learning principles, to improve acute care nurse knowledge and recognition of delirium. Prior to undertaking the RCT preliminary phases involving; validation of vignettes, video-taping five of the validated vignettes, website development and pilot testing were completed. Methods: The cluster RCT involved consenting registered nurse participants (N = 175) from twelve clinical areas within three acute health care facilities in Queensland, Australia. Data were collected through a variety of measures and instruments. Primary outcomes were improved ability of nurses to recognise delirium using written validated vignettes and improved knowledge of delirium using a delirium knowledge questionnaire. The secondary outcomes were aimed at determining nurse satisfaction and usability of the website. Primary outcome measures were taken at baseline (T1), directly after the intervention (T2) and two months later (T3). The secondary outcomes were measured at T2 by participants in the intervention group. Following baseline data collection remaining participants were assigned to either the intervention (n=75) or control (n=72) group. Participants in the intervention group were given access to the learning intervention while the control group continued to work in their clinical area and at that time, did not receive access to the learning intervention. Data from the primary outcome measures were examined in mixed model analyses. Results: Overall, the effect of the online learning intervention over time comparing the intervention group and the control group were positive. The intervention groups‘ scores were higher and the change over time results were statistically significant [T3 and T1 (t=3.78 p=<0.001) and T2 and T1 baseline (t=5.83 p=<0.001)]. Statistically significant improvements were also seen for delirium recognition when comparing T2 and T1 results (t=2.58 p=0.012) between the control and intervention group but not for changes in delirium recognition scores between the two groups from T3 and T1 (t=1.80 p=0.074). The majority of the participants rated the website highly on the visual, functional and content elements. Additionally, nearly 80% of the participants liked the overall website features and there were self-reported improvements in delirium knowledge and recognition by the registered nurses in the intervention group. Discussion: Findings from this study support the concept that online learning is an effective and satisfying method of information delivery. Embedded within a constructivist learning environment the site produced a high level of satisfaction and usability for the registered nurse end-users. Additionally, the results showed that the website significantly improved delirium knowledge & recognition scores and the improvement in delirium knowledge was retained at a two month follow-up. Given the strong effect of the intervention the online delirium intervention should be utilised as a way of providing information to registered nurses. It is envisaged that this knowledge would lead to improved recognition of delirium as well as improvement in patient outcomes however; translation of this knowledge attainment into clinical practice was outside the scope of this study. A critical next step is demonstrating the effect of the intervention in changing clinical behaviour, and improving patient health outcomes.

Emergent participant interaction

Emergence has the potential to effect complex, creative or open-ended interactions and novel game-play. We report on research into an emergent interactive system. This investigates emergent user behaviors and experience through the creation and evaluation of an interactive system. The system is +-NOW, an augmented reality, tangible, interactive art system. The paper briefly describes the qualities of emergence and +-NOW before focusing on its evaluation. This was a qualitative study with 30 participants conducted in context. Data analysis followed Grounded Theory Methods. Coding schemes, induced from data and external literature are presented. Findings show that emergence occurred in over half of the participants. The nature of these emergent behaviors is discussed along with examples from the data. Other findings indicate that participants found interaction with the work satisfactory. Design strategies for facilitating satisfactory experience despite the often unpredictable character of emergence, are briefly reviewed and potential application areas for emergence are discussed.

JFA based Speaker Recognition using Delta-Phase and MFCC features

This paper investigates the use of mel-frequency deltaphase (MFDP) features in comparison to, and in fusion with, traditional mel-frequency cepstral coefficient (MFCC) features within joint factor analysis (JFA) speaker verification. MFCC features, commonly used in speaker recognition systems, are derived purely from the magnitude spectrum, with the phase spectrum completely discarded. In this paper, we investigate if features derived from the phase spectrum can provide additional speaker discriminant information to the traditional MFCC approach in a JFA based speaker verification system. Results are presented which provide a comparison of MFCC-only, MFDPonly and score fusion of the two approaches within a JFA speaker verification approach. Based upon the results presented using the NIST 2008 Speaker Recognition Evaluation (SRE) dataset, we believe that, while MFDP features alone cannot compete with MFCC features, MFDP can provide complementary information that result in improved speaker verification performance when both approaches are combined in score fusion, particularly in the case of shorter utterances.

Timed and Probabilistic Automata for Automatic Animal Call Recognition

Automatic Call Recognition is vital for environmental monitoring. Patten recognition has been applied in automatic species recognition for years. However, few studies have applied formal syntactic methods to species call structure analysis. This paper introduces a novel method to adopt timed and probabilistic automata in automatic species recognition based upon acoustic components as the primitives. We demonstrate this through one kind of birds in Australia: Eastern Yellow Robin.

The backfilled GEI : a cross-capture modality gait feature for frontal and side-view gait recognition

In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

The role of the internet and digital technologies in the struggle for recognition of the forgotten Australians

Our contemporary public sphere has seen the 'emergence of new political rituals, which are concerned with the stains of the past, with self disclosure, and with ways of remembering once taboo and traumatic events' (Misztal, 2005). A recent case of this phenomenon occurred in Australia in 2009 with the apology to the 'Forgotten Australians': a group who suffered abuse and neglect after being removed from their parents – either in Australia or in the UK - and placed in Church and State run institutions in Australia between 1930 and 1970. This campaign for recognition by a profoundly marginalized group coincides with the decade in which the opportunities of Web 2.0 were seen to be diffusing throughout different social groups, and were considered a tool for social inclusion. This paper examines the case of the Forgotten Australians as an opportunity to investigate the role of the internet in cultural trauma and public apology. As such, it adds to recent scholarship on the role of digital web based technologies in commemoration and memorials (Arthur, 2009; Haskins, 2007; Cohen and Willis, 2004), and on digital storytelling in the context of trauma (Klaebe, 2011) by locating their role in a broader and emerging domain of social responsibility and political action (Alexander, 2004).

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Microstructural studies of quenched partially-melted Y-123 materials and Y-123 with Y-211, PtO2 and CeO2 additions

The microstructure of YBa2Cu3O7-delta (Y-123) materials partially-melted in air and quenched from the temperature range 900-1100 degrees C, has been characterized using a combination of X-ray diffractometry, optical microscopy, scanning electron microscopy, electron microprobe analyses, transmission electron microscopy and energy and wave dispersive X-ray spectrometries. The microstructural studies reveal significant changes in the character of the quenched partial-melt as a function of temperature and time before quenching. BaCu2O2 and BaCuO2 are found to co-exist in stoichiometric samples quenched from the temperature range 920-960 degrees C. Under suitable cooling conditions, large pockets of melt cristallize as BaCuO2 with an exsolution of BaCu2O2 in the form of thin plates (approximate to 50-100 nm thick) along facets. Y2BaCuO5 (Y-211) additions are associated with the formation of BaCu2O2 at 1100 degrees C. Preliminary results on the effects of PtO2 and CeO2 additions to Y-123 (and Y-123 with Y-211 additions) show that these enhace the formation of BaCu2O2 at the melting temperature of 1100 degrees C. (C) 1998 Elsevier Science S.A. All rights reserved.

Cultural relativity as exchange : J.W. Lindt’s 'bush character and Aboriginal' from 'The Grafton Album', circa 1872

J.W.Lindt’s Colonial man and Aborigine image from the GRAFTON ALBUM: “On chemistry and optics all does not depend, art must with these in triple union blend” (text from J.W. Lindt’s photographic backing card) In this paper, I follow an argument that Lindt held a position in his particular colonial environment where he was simultaneously both an insider and an outsider and that such a position may be considered prerequisite in stimulating exchange. A study of the transition of J.W. Lindt in Grafton, N.S.W. in the 1860s from a traveller to a migrant and subsequently to a professional photographer, as well as Lindt’s photographic career, which evolved through strategic action and technical approaches to photography, bears witness to his cultural relativity. One untitled photograph from this period of work constructs a unique commentary of Australian colonial life that illustrates a non-hegemonic position, particularly as it was included in one of the first albums of photographs of Aborigines that Lindt gifted to an illustrious person (in this case the Mayor of Grafton). As in his other studio constructions, props and backdrops were arranged and sitters were positioned with care, but this photograph is the only one in the album that includes a non-Aborigine in a relationship to an Aborigine. An analysis of the props, technical details of the album and the image suggests a reconciliatory aspect that thwarts the predominant attitudes towards Aborigines in the area at that time.

Image Region Salience for Improving Appearance-Based Place Recognition using a Supervised Classifier System

Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Electron paramagnetic resonance, optical absorption and Raman spectral studies on a pyrite/chalcopyrite mineral

Pyrite and chalcopyrite mineral samples from Mangampet barite mine, Kadapa, Andhra Pradesh, India are used in the present study. XRD data indicate that the pyrite mineral has a face centered cubic lattice structure with lattice constant 5.4179 Å. Also it possesses an average particle size of 91.9 nm. An EPR study on the powdered samples confirms the presence of iron in pyrite and iron and Mn(II) in chalcopyrite. The optical absorption spectrum of chalcopyrite indicates presence of copper which is in a distorted octahedral environment. NIR results confirm the presence of water fundamentals and Raman spectrum reveals the presence of water and sulfate ions.