Computer animation of hot spot development in bulk coal as an aid for training coal miners

The processes that take place during the development of a heating are difficult to visualise. Bulk coal self-heating tests at The University of Queensland (UQ) using a two-metre column are providing graphic evidence of the stages that occur during a heating. Data obtained from these tests, both temperature and corresponding off-gas evolution can be transformed into what is effectively a video-replay of the heating event. This is achieved by loading both sets of data into a newly developed animation package called Hotspot. The resulting animation is ideal for spontaneous combustion training purposes as the viewer can readily identify the different hot spot stages and corresponding off-gas signatures. Colour coding of the coal temperature, as the hot spot forms, highlights its location in the coal pile and shows its ability to migrate upwind. An added benefit of the package is that once a mine has been tested in the UQ two-metre column, there is a permanent record of that particular coals performance for mine personnel to view.

Using the Amazon metric to construct an image database based on what people do, not what they say

Current image database metadata schemas require users to adopt a specific text-based vocabulary. Text-based metadata is good for searching but not for browsing. Existing image-based search facilities, on the other hand, are highly specialised and so suffer similar problems. Wexelblat's semantic dimensional spatial visualisation schemas go some way towards addressing this problem by making both searching and browsing more accessible to the user in a single interface. But the question of how and what initial metadata to enter a database remains. Different people see different things in an image and will organise a collection in equally diverse ways. However, we can find some similarity across groups of users regardless of their reasoning. For example, a search on Amazon.com returns other products also, based on an averaging of how users navigate the database. In this paper, we report on applying this concept to a set of images for which we have visualised them using traditional methods and the Amazon.com method. We report on the findings of this comparative investigation in a case study setting involving a group of randomly selected participants. We conclude with the recommendation that in combination, the traditional and averaging methods would provide an enhancement to current database visualisation, searching, and browsing facilities.