Rich probabilistic representations for bearing only decentralised data fusion

The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.

An assessment system for evaluation of driving competencies

Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

Grounding action in visuo-haptic space using experience networks

Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.

Using reputation management in participatory sensing for data classification

Participatory sensing enables collection, processing, dissemination and analysis of environmental sensory data by ordinary citizens, through mobile devices. Researchers have recognized the potential of participatory sensing and attempted applying it to many areas. However, participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data quality has become a significant issue. This study proposes using reputation management to classify the gathered data and provide useful information for campaign organizers and data analysts to facilitate their decisions.

Auditory spatial acuity approximates the resolving power of space-specific neurons

The relationship between neuronal acuity and behavioral performance was assessed in the barn owl (Tyto alba), a nocturnal raptor renowned for its ability to localize sounds and for the topographic representation of auditory space found in the midbrain. We measured discrimination of sound-source separation using a newly developed procedure involving the habituation and recovery of the pupillary dilation response. The smallest discriminable change of source location was found to be about two times finer in azimuth than in elevation. Recordings from neurons in its midbrain space map revealed that their spatial tuning, like the spatial discrimination behavior, was also better in azimuth than in elevation by a factor of about two. Because the PDR behavioral assay is mediated by the same circuitry whether discrimination is assessed in azimuth or in elevation, this difference in vertical and horizontal acuity is likely to reflect a true difference in sensory resolution, without additional confounding effects of differences in motor performance in the two dimensions. Our results, therefore, are consistent with the hypothesis that the acuity of the midbrain space map determines auditory spatial discrimination.

Sulfate anion templation of macrocycles, capsules, interpenetrated and interlocked structures

This review examines the potential of anions, in particular sulfate, to template the formation of complex molecular architectures. Until recently, sulfate has been largely overlooked in this area and the examples described herein demonstrate this anion’s versatility in templating the formation of a diverse range of molecular systems including macrocycles, helixes, molecular capsules, interpenetrated and interlocked assemblies such as catenanes. In addition sulfate has been shown to template the formation of interpenetrated structures on a range of solid surfaces including gold, polystyrene beads and silicate nanoparticles, highlighting the potential of this anion in the fabrication of functional sensory devices exhibiting highly selective binding behaviour.

Elementary teacher’s conceptions of inquiry teaching : messages for teacher development

The advocacy for inquiry-based learning in contemporary curricula assumes the principle that students learn in their own way by drawing on direct experience fostered by the teacher. That students should be able to discover answers themselves through active engagement with new experiences was central to the thinking of eminent educators such as Pestalozzi, Dewey and Montessori. However, even after many years of research and practice, inquiry learning as a referent for teaching still struggles to find expression in the average teachers' pedagogy. This study drew on interview data from 20 elementary teachers. A phenomenographic analysis revealed three conceptions of teaching for inquiry learning in science in the elementary years of schooling: (a) The Experience- centred conception where teachers focused on providing interesting sensory experiences to students; (b) The Problem-centred conception where teachers focused on challenging students with engaging problems; and (c) The Question-centred conception where teachers focused on helping students to ask and answer their own questions. Understanding teachers' conceptions has implications for both the enactment of inquiry teaching in the classroom as well as the uptake of new teaching behaviours during professional development, with enhanced outcomes for engaging students in Science.

Inquiry teaching in primary science : a phenomenographic study

In spite of having a long history in education, inquiry teaching (the teaching in ways that foster inquiry based learning in students) in science education is still a highly problematic issue. However, before teacher educators can hope to effectively influence teacher implementation of inquiry teaching in the science classroom, educators need to understand teachers’ current conceptions of inquiry teaching. This study describes the qualitatively different ways in which 20 primary school teachers experienced inquiry teaching in science education. A phenomenographic approach was adopted and data sourced from interviews of these teachers. The three categories of experiences that emerged from this study were; Student Centred Experiences (Category 1), Teacher Generated Problems (Category 2), and Student Generated Questions (Category 3). In Category 1 teachers structure their teaching around students sensory experiences, expecting that students will see, hear, feel and do interesting things that will focus their attention, have them asking science questions, and improve their engagement in learning. In Category 2 teachers structure their teaching around a given problem they have designed and that the students are required to solve. In Category 3 teachers structure their teaching around helping students to ask and answer their own questions about phenomena. These categories describe a hierarchy with the Student Generated Questions Category as the most inclusive. These categories were contrasted with contemporary educational theory, and it was found that when given the chance to voice their own conceptions without such comparison teachers speak of inquiry teaching in only one of the three categories mentioned. These results also help inform our theoretical understanding of teacher conceptions of inquiry teaching. Knowing what teachers actually experience as inquiry teaching, as opposed to understand theoretically, is a valuable contribution to the literature. This knowledge provides a valuable contribution to educational theory, which helps policy, curriculum development, and the practicing primary school teachers to more fully understand and implement the best educative practices in their daily work. Having teachers experience the qualitatively different ways of experiencing inquiry teaching uncovered in this study is expected to help teachers to move towards a more student-centred, authentic inquiry outcome for their students and themselves. Going beyond this to challenge teacher epistemological beliefs regarding the source of knowledge may also assist them in developing more informed notions of the nature of science and of scientific inquiry during professional development opportunities. The development of scientific literacy in students, a high priority for governments worldwide, will only to benefit from these initiatives.

Emergent task-specific object semantics through distributed experience networks

Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.

Aerial SLAM with a single camera using visual expectation

Micro aerial vehicles (MAVs) are a rapidly growing area of research and development in robotics. For autonomous robot operations, localization has typically been calculated using GPS, external camera arrays, or onboard range or vision sensing. In cluttered indoor or outdoor environments, onboard sensing is the only viable option. In this paper we present an appearance-based approach to visual SLAM on a flying MAV using only low quality vision. Our approach consists of a visual place recognition algorithm that operates on 1000 pixel images, a lightweight visual odometry algorithm, and a visual expectation algorithm that improves the recall of place sequences and the precision with which they are recalled as the robot flies along a similar path. Using data gathered from outdoor datasets, we show that the system is able to perform visual recognition with low quality, intermittent visual sensory data. By combining the visual algorithms with the RatSLAM system, we also demonstrate how the algorithms enable successful SLAM.

Assessment of retinal structure and visual function in association with diabetic peripheral neuropathy

Diabetes is an increasingly prevalent disease worldwide. Providing early management of the complications can prevent morbidity and mortality in this population. Peripheral neuropathy, a significant complication of diabetes, is the major cause of foot ulceration and amputation in diabetes. Delay in attending to complication of the disease contributes to significant medical expenses for diabetic patients and the community. Early structural changes to the neural components of the retina have been demonstrated to occur prior to the clinically visible retinal vasculature complication of diabetic retinopathy. Additionally visual functionloss has been shown to exist before the ophthalmoscopic manifestations of vasculature damage. The purpose of this thesis was to evaluate the relationship between diabetic peripheral neuropathy and both retinal structure and visual function. The key question was whether diabetic peripheral neuropathy is the potential underlying factor responsible for retinal anatomical change and visual functional loss in people with diabetes. This study was conducted on a cohort with type 2 diabetes. Retinal nerve fibre layer thickness was assessed by means of Optical Coherence Tomography (OCT). Visual function was assessed using two different methods; Standard Automated Perimetry (SAP) and flicker perimetry were performed within the central 30 degrees of fixation. The level of diabetic peripheral neuropathy (DPN) was assessed using two techniques - Quantitative Sensory Testing and Neuropathy Disability Score (NDS). These techniques are known to be capable of detecting DPN at very early stages. NDS has also been shown as a gold standard for detecting 'risk of foot ulceration'. Findings reported in this thesis showed that RNFL thickness, particularly in the inferior quadrant, has a significant association with severity of DPN when the condition has been assessed using NDS. More specifically it was observed that inferior RNFL thickness has the ability to differentiate individuals who are at higher risk of foot ulceration from those who are at lower risk, indicating that RNFL thickness can predict late-staged DPN. Investigating the association between RNFL and QST did not show any meaningful interaction, which indicates that RNFL thickness for this cohort was not as predictive of neuropathy status as NDS. In both of these studies, control participants did not have different results from the type 2 cohort who did not DPN suggesting that RNFL thickness is not a marker for diagnosing DPN at early stages. The latter finding also indicated that diabetes per se, is unlikely to affect the RNFL thickness. Visual function as measured by SAP and flicker perimetry was found to be associated with severity of peripheral neuropathy as measured by NDS. These findings were also capable of differentiating individuals at higher risk of foot ulceration; however, visual function also proved not to be a maker for early diagnosis of DPN. It was found that neither SAP, nor flicker sensitivity have meaningful associations with DPN when neuropathy status was measured using QST. Importantly diabetic retinopathy did not explain any of the findings in these experiments. The work described here is valuable as no other research to date has investigated the association between diabetic peripheral neuropathy and either retinal structure or visual function.

Locating 'Agency' Within Ubiquitous Computing Systems

The final shape of the "Internet of Things" ubiquitous computing promises relies on a cybernetic system of inputs (in the form of sensory information), computation or decision making (based on the prefiguration of rules, contexts, and user-generated or defined metadata), and outputs (associated action from ubiquitous computing devices). My interest in this paper lies in the computational intelligences that suture these positions together, and how positioning these intelligences as autonomous agents extends the dialogue between human-users and ubiquitous computing technology. Drawing specifically on the scenarios surrounding the employment of ubiquitous computing within aged care, I argue that agency is something that cannot be traded without serious consideration of the associated ethics.

Comparing the medium-term effects of exercise or dietary restriction on appetite regulation and compensatory responses

Previous studies have shown that exercise (Ex) interventions create a stronger coupling between energy intake (EI) and energy expenditure (EE) leading to increased homeostasis of the energy-balance (EB) regulatory system compared to a diet intervention where an un-coupling between EI and EE occurs. The benefits of weight loss from Ex and diet interventions greatly depend on compensatory responses. The present study investigated an 8-week medium-term Ex and diet intervention program (Ex intervention comprised of 500kcal EE five days per week over four weeks at 65-75% maximal heart rate, whereas the diet intervention comprised of a 500kcal decrease in EI five days per week over four weeks) and its effects on compensatory responses and appetite regulation among healthy individuals using a between- and within-subjects design. Effects of an acute dietary manipulation on appetite and compensatory behaviours and whether a diet and/or Ex intervention pre-disposes individuals to disturbances in EB homeostasis were tested. Energy intake at an ad libitum lunch test meal after a breakfast high- and low-energy pre-load (the high energy pre-load contained 556kcal and the low energy pre-load contained 239kcal) were measured at the Baseline (Weeks -4 to 0) and Intervention (Weeks 0 to 4) phases in 13 healthy volunteers (three males and ten females; mean age 35 years [sd + 9] and mean BMI 25 kg/m2 [sd + 3.8]) [participants in each group included Ex=7, diet=5 (one female in the diet group dropped out midway), thus, 12 participants completed the study]. At Weeks -4, 0 and 4, visual analogue scales (VAS) were used to assess hunger and satiety and liking and wanting (L&W) for nutrient and taste preferences using a computer-based system (E-Prime v1.1.4). Ad libitum test meal EI was consistently lower after the HE pre-load compared to the LE pre-load. However, this was not consistent during the diet intervention however. A pre-load x group interaction on ad libitum test meal EI revealed that during the intervention phase the Ex group showed an improved sensitivity to detect the energy content between the two pre-loads and improved compensation for the ad libitum test meal whereas the diet group’s ability to differentiate between the two pre-loads decreased and showed poorer compensation (F[1,10]=2.88, p-value not significant). This study supports previous findings of the effect Ex and diet interventions have on appetite and compensatory responses; Ex increases and diet decreases energy balance sensitivity.

Rooms on view : home and design exhibition

The expression of a narrative realized through a constructed interior environment provides a significant and engaging response that falls between the realms of design and theatre in which the space itself provides the role of actor.

Meaningful engagement with music composition

Musical value cannot be experienced without direct knowledge of music, and engagement with the interactive elements of materials, expressive character and structure. Through these channels something is communicated, something is transmitted, some residue of ‘meaning’ is left with us. When a work of art stirs us it is more than simply sensory stimulation or some kind of emotional indulgence. We are gaining knowledge and expanding our experience... contributing to knowledge of ourselves and of the world.