A Novel Multimodal Interface for Improving Visually Impaired People's Web Accessibility

This paper introduces a novel interface designed to help blind and visually impaired people to explore and navigate on the Web. In contrast to traditionally used assistive tools, such as screen readers and magnifiers, the new interface employs a combination of both audio and haptic features to provide spatial and navigational information to users. The haptic features are presented via a low-cost force feedback mouse allowing blind people to interact with the Web, in a similar fashion to their sighted counterparts. The audio provides navigational and textual information through the use of non-speech sounds and synthesised speech. Interacting with the multimodal interface offers a novel experience to target users, especially to those with total blindness. A series of experiments have been conducted to ascertain the usability of the interface and compare its performance to that of a traditional screen reader. Results have shown the advantages that the new multimodal interface offers blind and visually impaired people. This includes the enhanced perception of the spatial layout of Web pages, and navigation towards elements on a page. Certain issues regarding the design of the haptic and audio features raised in the evaluation are discussed and presented in terms of recommendations for future work.

An Extended Implementation of the Great Deluge Algorithm for Course Timetabling

Course Scheduling consists of assigning lecture events to a limited set of specific timeslots and rooms. The objective is to satisfy as many soft constraints as possible, while maintaining a feasible solution timetable. The most successful techniques to date require a compute-intensive examination of the solution neighbourhood to direct searches to an optimum solution. Although they may require fewer neighbourhood moves than more exhaustive techniques to gain comparable results, they can take considerably longer to achieve success. This paper introduces an extended version of the Great Deluge Algorithm for the Course Timetabling problem which, while avoiding the problem of getting trapped in local optima, uses simple Neighbourhood search heuristics to obtain solutions in a relatively short amount of time. The paper presents results based on a standard set of benchmark datasets, beating over half of the currently published best results with in some cases up to 60% of an improvement.