Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

Combined analysis of categorical and numerical descriptors of Australian groundnut accessions using nonlinear principal component analysis

For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

Topological localization using optical flow descriptors

We propose a topological localization method based on optical flow information. We analyse the statistical characteristics of the optical flow signal and demonstrate that the flow vectors can be used to identify and describe key locations in the environment. The key locations (nodes) correspond to significant scene changes and depth discontinuities. Since optical flow vectors contain position, magnitude and angle information, for each node, we extract low and high order statistical moments of the vectors and use them as descriptors for that node. Once a database of nodes and their corresponding optical flow features is created, the robot can perform topological localization by using the Mahalanobis distance between the current frame and the database. This is supported by field trials, which illustrate the repeatability of the proposed method for detecting and describing key locations in indoor and outdoor environments in challenging and diverse lighting conditions.

Peer Leader Roles Descriptors

Across QUT there are a spectrum of peer-to-peer programs and activities initiated by both staff and students that have been designed to build the capacity of all students to ensure they reach their full learning potential. Peer leader roles have in common a focus on building students' sense of belonging to the university, and in doing so, boosting their confidence as learners and capacity to succeed academically. This document provides a set of descriptors that provides details of the various peer leader roles across QUT and their associated responsibilities.

The correlation of pore morphology, interconnectivity and physical properties of 3D ceramic scaffolds with bone ingrowth

In the design of tissue engineering scaffolds, design parameters including pore size, shape and interconnectivity, mechanical properties and transport properties should be optimized to maximize successful inducement of bone ingrowth. In this paper we describe a 3D micro-CT and pore partitioning study to derive pore scale parameters including pore radius distribution, accessible radius, throat radius, and connectivity over the pore space of the tissue engineered constructs. These pore scale descriptors are correlated to bone ingrowth into the scaffolds. Quantitative and visual comparisons show a strong correlation between the local accessible pore radius and bone ingrowth; for well connected samples a cutoff accessible pore radius of approximately 100 microM is observed for ingrowth. The elastic properties of different types of scaffolds are simulated and can be described by standard cellular solids theory: (E/E(0))=(rho/rho(s))(n). Hydraulic conductance and diffusive properties are calculated; results are consistent with the concept of a threshold conductance for bone ingrowth. Simple simulations of local flow velocity and local shear stress show no correlation to in vivo bone ingrowth patterns. These results demonstrate a potential for 3D imaging and analysis to define relevant pore scale morphological and physical properties within scaffolds and to provide evidence for correlations between pore scale descriptors, physical properties and bone ingrowth.

Understanding how to enhance business creativity

This PhD study examines some of what happens in an individual’s mind regarding creativity during problem solving within an organisational context. It presents innovations related to creative motivation, cognitive style and framing effects that can be applied by managers to enhance individual employee creativity within the organisation and thereby assist organisations to become more innovative. The project delivers an understanding of how to leverage natural changes in creative motivation levels during problem solving. This pattern of response is called Creative Resolve Response (CRR). The project also presents evidence of how framing effects can be used to influence decisions involving creative options in order to enhance the potential for managers get employees to select creative options more often for implementation. The study’s objectives are to understand: • How creative motivation changes during problem solving • How cognitive style moderates these creative motivation changes • How framing effects apply to decisions involving creative options to solve problems • How cognitive style moderate these framing effects The thesis presents the findings from three controlled experiments based around self reports during contrived problem solving and decision making situations. The first experiment suggests that creative motivation varies in a predictable and systematic way during problem solving as a function of the problem solver’s perception of progress. The second experiment suggests that there are specific framing effects related to decisions involving creativity. It seems that simply describing an alternative as innovative may activate perceptual biases that overcome risk based framing effects. The third experiment suggests that cognitive style moderates decisions involving creativity in complex ways. It seems that in some contexts, decision makers will prefer a creative option, regardless of their cognitive style, if this option is both outside the bounds of what is officially allowed and yet ultimately safe. The thesis delivers innovation on three levels: theoretical, methodological and empirical. The highlights of these findings are outlined below: 1. Theoretical innovation with the conceptualisation of Creative Resolve Response based on an extension of Amabile’s research regarding creative motivation. 2. Theoretical innovation linking creative motivation and Kirton’s research on cognitive style. 3. Theoretical innovation linking both risk based and attribute framing effects to cognitive style. 4. Methodological innovation for defining and testing preferences for creative solution implementation in the form of operationalised creativity decision alternatives. 5. Methodological innovation to identify extreme decision options by applying Shafir’s findings regarding attribute framing effects in reverse to create a test. 6. Empirical innovation with statistically significant research findings which indicate creative motivation varies in a systematic way. 7. Empirical innovation with statistically significant research findings which identify innovation descriptor framing effects 8. Empirical innovation with statistically significant research findings which expand understanding of Kirton’s cognitive style descriptors including the importance of safe rule breaking. 9. Empirical innovation with statistically significant research findings which validate how framing effects do apply to decisions involving operationalised creativity. Drawing on previous research related to creative motivation, cognitive style, framing effects and supervisor interactions with employees, this study delivers insights which can assist managers to increase the production and implementation of creativity in organisations. Hopefully this will result in organisations which are more innovative. Such organisations have the potential to provide ongoing economic and social benefits.

Does the summative assessment of real world learning using criterion-referenced assessment need to be discipline specific?

This paper synthesises the existing literature on the contemporary conception of ‘real world’ and compares it with similar notions such as ‘authentic’ and ‘work integrated learning’. While the term ‘real world’ may be partly dependent on the discipline, it does not necessarily follow that the criterion-referenced assessment of ‘real world’ assessment must involve criteria and performance descriptors that are discipline specific. Two examples of summative assessment (court report and trial process exercise) from a final year core subject at the Queensland University of Technology, LWB432 Evidence, emphasise real world learning, are authentic, innovative and better prepare students for the transition into the workplace than more generic forms of assessment such as tutorial participation or oral presentations. The court report requires students to attend a criminal trial in a Queensland Court and complete a two page report on what they saw in practice compared with what they learned in the classroom. The trial process exercise is a 50 minute written closed book activity conducted in tutorials, where students plan questions that they would ask their witness in examination-in-chief, plan questions that they would ask their opponent’s witness in cross-examination, plan questions that they would ask in reexamination given what their opponent asked in cross-examination, and prepare written objections to their opponent’s questions. The trial process exercise simulates the real world, whereas the court report involves observing the real world, and both assessment items are important to the role of counsel. The design of the criterion-referenced assessment rubrics for the court report and trial process exercise is justified by the literature. Notably, the criteria and performance descriptors are not necessarily law specific and this paper highlights the parts that may be easily transferred to other disciplines.

Development of descriptor tools for the characterization of Australian sugar mill evaporator scale

Cleaning of sugar mill evaporators is an expensive exercise. Identifying the scale components assists in determining which chemical cleaning agents would result in effective evaporator cleaning. The current methods (based on x-ray diffraction techniques, ion exchange/high performance liquid chromatography and thermogravimetry/differential thermal analysis) used for scale characterisation are difficult, time consuming and expensive, and cannot be performed in a conventional analytical laboratory or by mill staff. The present study has examined the use of simple descriptor tests for the characterisation of Australian sugar mill evaporator scales. Scale samples were obtained from seven Australian sugar mill evaporators by mechanical means. The appearance, texture and colour of the scale were noted before the samples were characterised using x-ray fluorescence and x-ray powder diffraction to determine the compounds present. A number of commercial analytical test kits were used to determine the phosphate and calcium contents of scale samples. Dissolution experiments were carried out on the scale samples with selected cleaning agents to provide relevant information about the effect the cleaning agents have on different evaporator scales. Results have shown that by simply identifying the colour and the appearance of the scale, the elemental composition and knowing from which effect the scale originates, a prediction of the scale composition can be made. These descriptors and dissolution experiments on scale samples can be used to provide factory staff with an on-site rapid process to predict the most effective chemicals for chemical cleaning of the evaporators.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

Reference bias : presentation of extreme health states prior to EQ-VAS improves health-related quality of life scores. A randomised crossover trial.

Background: Clinical practice and clinical research has made a concerted effort to move beyond the use of clinical indicators alone and embrace patient focused care through the use of patient reported outcomes such as healthrelated quality of life. However, unless patients give consistent consideration to the health states that give meaning to measurement scales used to evaluate these constructs, longitudinal comparison of these measures may be invalid. This study aimed to investigate whether patients give consideration to a standard health state rating scale (EQ-VAS) and whether consideration of good and poor health state descriptors immediately changes their selfreport. Methods: A randomised crossover trial was implemented amongst hospitalised older adults (n = 151). Patients were asked to consider descriptions of extremely good (Description-A) and poor (Description-B) health states. The EQ-VAS was administered as a self-report at baseline, after the first descriptors (A or B), then again after the remaining descriptors (B or A respectively). At baseline patients were also asked if they had considered either EQVAS anchors. Results: Overall 106/151 (70%) participants changed their self-evaluation by ≥5 points on the 100 point VAS, with a mean (SD) change of +4.5 (12) points (p < 0.001). A total of 74/151 (49%) participants did not consider the best health VAS anchor, of the 77 who did 59 (77%) thought the good health descriptors were more extreme (better) then they had previously considered. Similarly 85/151 (66%) participants did not consider the worst health anchor of the 66 who did 63 (95%) thought the poor health descriptors were more extreme (worse) then they had previously considered. Conclusions: Health state self-reports may not be well considered. An immediate significant shift in response can be elicited by exposure to a mere description of an extreme health state despite no actual change in underlying health state occurring. Caution should be exercised in research and clinical settings when interpreting subjective patient reported outcomes that are dependent on brief anchors for meaning. Trial Registration: Australian and New Zealand Clinical Trials Registry (#ACTRN12607000606482) http://www.anzctr. org.au

Development and evaluation of an integrated clinical learning model to inform continuing education for acute care nurses

Background Significant ongoing learning needs for nurses have occurred as a direct result of the continuous introduction of technological innovations and research developments in the healthcare environment. Despite an increased worldwide emphasis on the importance of continuing education, there continues to be an absence of empirical evidence of program and session effectiveness. Few studies determine whether continuing education enhances or develops practice and the relative cost benefits of health professionals’ participation in professional development. The implications for future clinical practice and associated educational approaches to meet the needs of an increasingly diverse multigenerational and multicultural workforce are also not well documented. There is minimal research confirming that continuing education programs contribute to improved patient outcomes, nurses’ earlier detection of patient deterioration or that standards of continuing competence are maintained. Crucially, evidence-based practice is demonstrated and international quality and safety benchmarks are adhered to. An integrated clinical learning model was developed to inform ongoing education for acute care nurses. Educational strategies included the use of integrated learning approaches, interactive teaching concepts and learner-centred pedagogies. A Respiratory Skills Update education (ReSKU) program was used as the content for the educational intervention to inform surgical nurses’ clinical practice in the area of respiratory assessment. The aim of the research was to evaluate the effectiveness of implementing the ReSKU program using teaching and learning strategies, in the context of organisational utility, on improving surgical nurses’ practice in the area of respiratory assessment. The education program aimed to facilitate better awareness, knowledge and understanding of respiratory dysfunction in the postoperative clinical environment. This research was guided by the work of Forneris (2004), who developed a theoretical framework to operationalise a critical thinking process incorporating the complexities of the clinical context. The framework used educational strategies that are learner-centred and participatory. These strategies aimed to engage the clinician in dynamic thinking processes in clinical practice situations guided by coaches and educators. Methods A quasi experimental pre test, post test non–equivalent control group design was used to evaluate the impact of the ReSKU program on the clinical practice of surgical nurses. The research tested the hypothesis that participation in the ReSKU program improves the reported beliefs and attitudes of surgical nurses, increases their knowledge and reported use of respiratory assessment skills. The study was conducted in a 400 bed regional referral public hospital, the central hub of three smaller hospitals, in a health district servicing the coastal and hinterland areas north of Brisbane. The sample included 90 nurses working in the three surgical wards eligible for inclusion in the study. The experimental group consisted of 36 surgical nurses who had chosen to attend the ReSKU program and consented to be part of the study intervention group. The comparison group included the 39 surgical nurses who elected not to attend the ReSKU program, but agreed to participate in the study. Findings One of the most notable findings was that nurses choosing not to participate were older, more experienced and less well educated. The data demonstrated that there was a barrier for training which impacted on educational strategies as this mature aged cohort was less likely to take up educational opportunities. The study demonstrated statistically significant differences between groups regarding reported use of respiratory skills, three months after ReSKU program attendance. Between group data analysis indicated that the intervention group’s reported beliefs and attitudes pertaining to subscale descriptors showed statistically significant differences in three of the six subscales following attendance at the ReSKU program. These subscales included influence on nursing care, educational preparation and clinical development. Findings suggest that the use of an integrated educational model underpinned by a robust theoretical framework is a strong factor in some perceptions of the ReSKU program relating to attitudes and behaviour. There were minimal differences in knowledge between groups across time. Conclusions This study was consistent with contemporary educational approaches using multi-modal, interactive teaching strategies and a robust overarching theoretical framework to support study concepts. The construct of critical thinking in the clinical context, combined with clinical reasoning and purposeful and collective reflection, was a powerful educational strategy to enhance competency and capability in clinicians.

Interaction in a Paired Speaking Test : the Rater's Perspective

Paired speaking tests are increasingly used in both low-and high-stakes second language assessment contexts. Until recently, very little was known about the way in which raters interpret and apply descriptors relating to interactional competence to a performance that is co-constructed. This book presents a study which explores the interactional features of a paired speaking test that were sailient to raters and the extent to which raters viewed the performance as separable. The study shows that raters use their own frames of reference to interpret descriptors and that they viewed certain features of the performance as mutual accomplishments. The book takes us 'beyond scores', and in doing so, contributes to the growing body of research on paired speaking tests.

Spectral–texture feature extraction using statistical moments with application to object-based vegetation species classification

The use of appropriate features to characterise an output class or object is critical for all classification problems. In order to find optimal feature descriptors for vegetation species classification in a power line corridor monitoring application, this article evaluates the capability of several spectral and texture features. A new idea of spectral–texture feature descriptor is proposed by incorporating spectral vegetation indices in statistical moment features. The proposed method is evaluated against several classic texture feature descriptors. Object-based classification method is used and a support vector machine is employed as the benchmark classifier. Individual tree crowns are first detected and segmented from aerial images and different feature vectors are extracted to represent each tree crown. The experimental results showed that the proposed spectral moment features outperform or can at least compare with the state-of-the-art texture descriptors in terms of classification accuracy. A comprehensive quantitative evaluation using receiver operating characteristic space analysis further demonstrates the strength of the proposed feature descriptors.