A framework for collecting inclusive design data for the UK population

Successful inclusive product design requires knowledge about the capabilities, needs and aspirations of potential users and should cater for the different scenarios in which people will use products, systems and services. This should include: the individual at home; in the workplace; for businesses, and for products in these contexts. It needs to reflect the development of theory, tools and techniques as research moves on.

Supporting the development of inclusive products : the effects of everyday ambient illumination levels and contrast on older adults' near visual acuity

Current older adult capability data-sets fail to account for the effects of everyday environmental conditions on capability. This article details a study that investigates the effects of everyday ambient illumination conditions (overcast, 6000 lx; in-house lighting, 150 lx and street lighting, 7.5 lx) and contrast (90%, 70%, 50% and 30%) on the near visual acuity (VA) of older adults (n= 38, 65-87 years). VA was measured at a 1-m viewing distance using logarithm of minimum angle of resolution (LogMAR) acuity charts. Results from the study showed that for all contrast levels tested, VA decreased by 0.2 log units between the overcast and street lighting conditions. On average, in overcast conditions, participants could detect detail around 1.6 times smaller on the LogMAR charts compared with street lighting. VA also significantly decreased when contrast was reduced from 70% to 50%, and from 50% to 30% in each of the ambient illumination conditions. Practitioner summary: This article presents an experimental study that investigates the impact of everyday ambient illumination levels and contrast on older adults' VA. Results show that both factors have a significant effect on their VA. Findings suggest that environmental conditions need to be accounted for in older adult capability data-sets/designs.

Cross-calbration of push-broom 2D LIDARs and cameras in natural scenes

This paper addresses the problem of automatically estimating the relative pose between a push-broom LIDAR and a camera without the need for artificial calibration targets or other human intervention. Further we do not require the sensors to have an overlapping field of view, it is enough that they observe the same scene but at different times from a moving platform. Matching between sensor modalities is achieved without feature extraction. We present results from field trials which suggest that this new approach achieves an extrinsic calibration accuracy of millimeters in translation and deci-degrees in rotation.

Perceptions and attitudes of nursing students’ towards electronic health records

Introduction The onset of Personally Controlled Electronic Health Records in Australia demand healthcare decision making processes to comprise, understand and accept electronic health records (EHR). Nurses play a key, central role in the healthcare decision making process and their perceptions and attitudes of EHRs are significant [1], which develop during their academic life. However, studies aimed at nursing students’ attitudes of EHRs are very limited [2-4]. A proper understanding of these attitudes and how they evolve with academic progress is important. This paper presents results from a survey conducted at a leading University in Queensland, Australia as a first step to filling this gap.

Tag-based interaction in online and mobile banking : a preliminary study of the effect on usability

In this paper we describe tag-based interaction afforded by a tag-based interface in online and mobile banking, and present our preliminary usability evaluation findings. We conducted a pilot usability study with a group of banking users by comparing the present 'conventional' interface and tag-based interface. The results show that participants perceive the tag-based interface as more usable in both online and mobile contexts. Participants also rated the tag-based interface better despite their unfamiliarity and perceived it as more user-friendly. Additionally, the results highlight that tag-based interaction is more effective in the mobile context especially to inexperienced mobile banking users. This in turn could have a positive effect on the adoption and acceptance of mobile banking in general and also specifically in Australia. We discuss our findings in more detail in the later sections of this paper and conclude with a discussion on future work.

A comparative usability study of a tag-based interface in the mobile banking context

This paper presents a comparative study to evaluate the usability of a tag-based interface alongside the present 'conventional' interface in the Australian mobile banking context. The tag-based interface is based on user-assigned tags to banking resources with support for different types of customization. And the conventional interface is based on standard HTML objects such as select boxes, lists, tables and etc, with limited customization. A total of 20 banking users evaluated both interfaces based on a set of tasks and completed a post-test usability questionnaire. Efficiency, effectiveness, and user satisfaction were considered to evaluate the usability of the interfaces. Results of the evaluation show improved usability in terms of user satisfaction with the tag-based interface compared to the conventional interface. This outcome is more apparent among participants without prior mobile banking experience. Therefore, there is a potential for the tag-based interface to improve user satisfaction of mobile banking and also positively affect the adoption and acceptance of mobile banking, particularly in Australia.

Gender differences in rumination : a meta-analysis

Starting in adolescence and continuing through adulthood, women are twice as likely as men to experience depression. According to the response styles theory (RST), gender differences in depression result, in part, from women's tendency to ruminate more than men. A meta-analysis was performed to evaluate gender differences in rumination in adults (k = 59; N = 14,321); additionally, an analysis of subtypes of rumination - brooding and reflection - was conducted (k = 23). Fixed effects analyses indicated that women scored higher than men in rumination (d = .24, p < .01, SEd = .02), brooding (d = .19, p < .01, SEd = .03) and reflection (d = .17, p < .01, SEd = .03); there was no evidence of heterogeneity or publication bias across studies for these effect sizes. Although statistically significant, the effect sizes for gender differences in rumination were small in magnitude. Results are discussed with respect to the RST and gender differences in depression

Robust aerodynamic design optimisation of morphing aerofoil/wing using distributed moga

In this paper, the shape design optimisation using morphing aerofoil/wing techniques, namely the leading and/or trailing edge deformation of a natural laminar flow RAE 5243 aerofoil is investigated to reduce transonic drag without taking into account of the piezo actuator mechanism. Two applications using a Multi-Objective Genetic Algorithm (MOGA)coupled with Euler and boundary analyser (MSES) are considered: the first example minimises the total drag with a lift constraint by optimising both the trailing edge actuator position and trailing edge deformation angle at a constant transonic Mach number (M! = 0.75)and boundary layer transition position (xtr = 45%c). The second example consists of finding reliable designs that produce lower mean total drag (μCd) and drag sensitivity ("Cd) at different uncertainty flight conditions based on statistical information. Numerical results illustrate how the solution quality in terms of mean drag and its sensitivity can be improved using MOGA software coupled with a robust design approach taking account of uncertainties (lift and boundary transition positions) and also how transonic flow over aerofoil/wing can be controlled to the best advantage using morphing techniques.

Multi-objective design optimisation of GFRP sandwich beams

A novel Glass Fibre Reinforced Polymer (GFRP) sandwich panel was developed by an Australian manufacturer for civil engineering applications. This research is motivated by the new applications of GFRP sandwich structures in civil engineering such as slab, beam, girder and sleeper. An optimisation methodology is developed in this work to enhance the design of GFRP sandwich beams. The design of single and glue laminated GFRP sandwich beam were conducted by using numerical optimisation. The numerical multi-objective optimisation considered a design two objectives simultaneously. These objectives are cost and mass. The numerical optimisation uses the Adaptive Range Multi-objective Genetic Algorithm (ARMOGA) and Finite Element (FE) method. Trade-offs between objectives was found during the optimisation process. Multi-objective optimisation shows a core to skin mass ratio equal to 3.68 for the single sandwich beam cross section optimisation and it showed that the optimum core to skin thickness ratio is 11.0.

3D thermal mapping of building interiors using an RGB-D and thermal camera

The building sector is the dominant consumer of energy and therefore a major contributor to anthropomorphic climate change. The rapid generation of photorealistic, 3D environment models with incorporated surface temperature data has the potential to improve thermographic monitoring of building energy efficiency. In pursuit of this goal, we propose a system which combines a range sensor with a thermal-infrared camera. Our proposed system can generate dense 3D models of environments with both appearance and temperature information, and is the first such system to be developed using a low-cost RGB-D camera. The proposed pipeline processes depth maps successively, forming an ongoing pose estimate of the depth camera and optimizing a voxel occupancy map. Voxels are assigned 4 channels representing estimates of their true RGB and thermal-infrared intensity values. Poses corresponding to each RGB and thermal-infrared image are estimated through a combination of timestamp-based interpolation and a pre-determined knowledge of the extrinsic calibration of the system. Raycasting is then used to color the voxels to represent both visual appearance using RGB, and an estimate of the surface temperature. The output of the system is a dense 3D model which can simultaneously represent both RGB and thermal-infrared data using one of two alternative representation schemes. Experimental results demonstrate that the system is capable of accurately mapping difficult environments, even in complete darkness.

Coordinated probabilistic optimal decision-making model for multi-area ATC with risk control

In the decision-making of multi-area ATC (Available Transfer Capacity) in electricity market environment, the existing resources of transmission network should be optimally dispatched and coordinately employed on the premise that the secure system operation is maintained and risk associated is controllable. The non-sequential Monte Carlo simulation is used to determine the ATC probability density distribution of specified areas under the influence of several uncertainty factors, based on which, a coordinated probabilistic optimal decision-making model with the maximal risk benefit as its objective is developed for multi-area ATC. The NSGA-II is applied to calculate the ATC of each area, which considers the risk cost caused by relevant uncertainty factors and the synchronous coordination among areas. The essential characteristics of the developed model and the employed algorithm are illustrated by the example of IEEE 118-bus test system. Simulative result shows that, the risk of multi-area ATC decision-making is influenced by the uncertainties in power system operation and the relative importance degrees of different areas.

Long exposure localization in darkness using consumer cameras

In this paper we demonstrate passive vision-based localization in environments more than two orders of magnitude darker than the current benchmark using a 100 webcam and a 500 camera. Our approach uses the camera’s maximum exposure duration and sensor gain to achieve appropriately exposed images even in unlit night-time environments, albeit with extreme levels of motion blur. Using the SeqSLAM algorithm, we first evaluate the effect of variable motion blur caused by simulated exposures of 132 ms to 10000 ms duration on localization performance. We then use actual long exposure camera datasets to demonstrate day-night localization in two different environments. Finally we perform a statistical analysis that compares the baseline performance of matching unprocessed greyscale images to using patch normalization and local neighbourhood normalization – the two key SeqSLAM components. Our results and analysis show for the first time why the SeqSLAM algorithm is effective, and demonstrate the potential for cheap camera-based localization systems that function across extreme perceptual change.

Image-based visual navigation for mobile robots

We introduce a new image-based visual navigation algorithm that allows the Cartesian velocity of a robot to be defined with respect to a set of visually observed features corresponding to previously unseen and unmapped world points. The technique is well suited to mobile robot tasks such as moving along a road or flying over the ground. We describe the algorithm in general form and present detailed simulation results for an aerial robot scenario using a spherical camera and a wide angle perspective camera, and present experimental results for a mobile ground robot.

A Systematic review of a statistical vacuum circuit breaker model for condition monitoring

Vacuum circuit breaker (VCB) overvoltage failure and its catastrophic failures during shunt reactor switching have been analyzed through computer simulations for multiple reignitions with a statistical VCB model found in the literature. However, a systematic review (SR) that is related to the multiple reignitions with a statistical VCB model does not yet exist. Therefore, this paper aims to analyze and explore the multiple reignitions with a statistical VCB model. It examines the salient points, research gaps and limitations of the multiple reignition phenomenon to assist with future investigations following the SR search. Based on the SR results, seven issues and two approaches to enhance the current statistical VCB model are identified. These results will be useful as an input to improve the computer modeling accuracy as well as the development of a reignition switch model with point-on-wave controlled switching for condition monitoring

Analysis and optimisation of the preferences of decision-makers in black-start group decision-making

As the first stage of power system restoration after a blackout, an optimal black-start scheme is very important for speeding up the whole restoration procedure. Up to now, much research work has been done on generating or selecting an optimal black-start scheme by a single round of decision-making. However, less attention has been paid for improving the final decision-making results through a multiple-round decision-making procedure. In the group decision-making environment, decision-making results evaluated by different black-start experts may differ significantly with each other. Thus, the consistency of black-start decision-making results could be deemed as an important indicator in assessing the black-start group decision-making results. Given this background, an intuitionistic fuzzy distance-based method is presented to analyse the consistency of black-start group decision-making results. Moreover, the weights of black-start indices as well as the weights of decision-making experts are modified in order to optimise the consistency of black-start group decision-making results. Finally, an actual example is served for demonstrating the proposed method.