Interactive visualisation for low literacy users

Sixteen percent (5.2 million) of the UK population possess low levels of literacy. The Government and other non-profit organisations, due to funding reforms, are forced to reduce the provision of face-to-face advice, and therefore, are pushing advice services via telephone or internet. As a consequence, low literacy users are experiencing difficulties finding the information they need to solve their day to day problems online. This thesis evaluates how walk in clients of a local Citizens Advice Bureau (CAB) who come to get social service information, obtain information online using the Adviceguide website. The thesis presents two challenges: (i) knowing the users in a way that can help consider design solutions that are probably not in a typical designer’s standard repertoire of design patterns, and (ii) knowing what is the problem that needs to be addressed. It is not simply an issue of usability or the need for simpler language, but understanding that these low literacy users are very different from the high literacy users. These low literacy users need this information to solve their day-to-day problems and are likely to be less successful in doing so. By providing an information architecture that permits them of a reasoning space and context, while supporting less abstract skills by visualized information in an unconventional way. The above challenges leave us with these research questions to address: what is the basis of such a design, how can these designs be incorporated into existing non-traditional interface proof of concept and finally how can these designs be evaluated

Multiple sensor-based weed segmentation

Bidens pilosa L (commonly known as cobbler's peg) is an annual broad-leaf weed in tropical and subtropical regions and reportedly needs to be identified and eliminated when farming 31 different crop varieties. This paper presents a multi-modal sensing approach for detecting Bidens leaves within wheat plants. Visual cue-based automatic discrimination of Bidens and wheat leaves is non-trivial owing to the curled-up nature of the wheat leaves. Therefore, spectral responses of Bidens and wheat leaves are first analysed to understand the discriminative spectral bands. Then a multi-modal sensory system consisting of a near infra red (NIR) and a visual camera set-up is proposed. Information retrieved from the sensory set up is then processed to generate a series of cues that are fed into a classification algorithm. Classification results are validated through experimentation. The proposed technique is able to achieve an accuracy of 88-95 per cent even when there is substantial overlapping between Bidens and wheat leaves. Further, it is also shown that the algorithm is robust enough to discriminate some other commonly available plant species

Active visual object search using affordance-map in real world: A human-centric approach

© 2014 IEEE. Human context is the most natural explanation why objects are placed and arranged in a particular order in an indoor environment. Usually, humans arrange objects in order to support their intended activities in a given environment. However, most of the common approaches for robotic object search involve modelling object-object relationships. In this paper, we hypothesize such relationships are centered around humans and bring human context to object search by modelling human-objects relationships through affordance-map. It identifies locations in a 3D map which support a particular affordance using virtual human models. Therefore, our approach does not require to observe real humans in the scene. The affordance-map and object-human-robot relationship are then used to infer the object search strategy. We tested our algorithm using a mobile robot that actively searched for the object 'computer monitors' in an office environment with promising results

Design of stable fuzzy controllers for an AGV

Fuzzy logic control is a relatively new technology and hence it needs rigorous comparative analyses with other well-established conventional control schemes. Further, fuzzy controller stability analysis is a major hindrance for its popularity among control engineers. This paper shows how stable fuzzy controllers may be synthesized for a typical AGV from the perspective of variable structure systems (VSS) theory. VSS or sliding model control (SMC) is an established robust non-linear control methodology. The AGV is characterized by highly non-linear, coupled and configuration dependent dynamics, with uncertainty in model parameters. Similarity in performance of the fuzzy controllers to the SMC controller is demonstrated through experimental results obtained for steer control of the AGV

Identifying information seeking behaviours of low and high literacy users: combined cognitive task analysis.

Motivation – According to the UK’s National Skills for Life survey carried out in 2003, 16% or equivalent to 5.2 million of the UK population presented low levels of literacy (Williams, et al. 2003). In this study we investigate the differences in information seeking behaviours between low and high literacy users of an on-line social service system. Research approach – Ten volunteers participated in the study. Using the National Skills for Life Survey, five were classified as high literacy; five as low literacy. All participants were asked to think-aloud whilst carrying out the information search using the “Adviceguide” website. The four tasks were of varying difficulty; easy, medium and difficult. Observations, video recording, and a semi structured interview technique that uses cognitive probes were used. The qualitative data were transcribed and analysed using Strauss and Corbin’s (1998) Grounded Theory and Wong and Blandford (2002) Emergent Themes Analysis approach. Findings/Design – We identified eight themes or characteristics from this study; Verification, Reading, Recovery, Trajectories, Abandon, Focus, Satisfied, and Perception. Results showed that low and high literacy users demonstrated critically different characteristics. Take away message – To better support the low and high literacy users with information seeking, we plan to look at information seeking behaviour models as theoretical lenses to analyse their behaviour from the identified characteristics (Makri, Blandford & Cox, 2008). The behaviour models will better inform the development of interface design for low and high literacy users