Mixed mode education: implications for library user services

The Faculty of Information Technology at QUT does not formally carry out distance education for any of its courses. However, it has pursued a number of initiatives that have made it possible for students to carry out an increasing proportion of their coursework off-site. These initiatives include computer-managed learning, World Wide Web and CDROM delivery of administrative and educational materials, and most recently the development of an integrated learning environment (ILE) for electronic delivery. These developments have been complemented and supported by the QUT Library by means of different avenues of access to CDROMs, a regional electronic document delivery service (REDD), and an electronic reserve (E-Reserve) service. Issues associated with the operation and evaluation of such facilities are described, and future library role in educational delivery are discussed

Shape Generation using Spatially Partitioned Point Clouds

We propose a method to generate 3D shapes using point clouds. Given a point-cloud representation of a 3D shape, our method builds a kd-tree to spatially partition the points. This orders them consistently across all shapes, resulting in reasonably good correspondences across all shapes. We then use PCA analysis to derive a linear shape basis across the spatially partitioned points, and optimize the point ordering by iteratively minimizing the PCA reconstruction error. Even with the spatial sorting, the point clouds are inherently noisy and the resulting distribution over the shape coefficients can be highly multi-modal. We propose to use the expressive power of neural networks to learn a distribution over the shape coefficients in a generative-adversarial framework. Compared to 3D shape generative models trained on voxel-representations, our point-based method is considerably more light-weight and scalable, with little loss of quality. It also outperforms simpler linear factor models such as Probabilistic PCA, both qualitatively and quantitatively, on a number of categories from the ShapeNet dataset. Furthermore, our method can easily incorporate other point attributes such as normal and color information, an additional advantage over voxel-based representations.Comment: To appear at BMVC 201

Shipley College: report from the Inspectorate (FEFC inspection report; 13/94 and 58/98)

The Further Education Funding Council has a legal duty to make sure further education in England is properly assessed. The FEFC’s inspectorate inspects and reports on each college of further education according to a four-year cycle. This record comprises the reports for periods 1994-95 and 1997-98