Reuse of learning objects? why, how and when?

This paper describes the rationale behind the specification and acquisition of a Digital Objects Management System (DOMS) at Deakin University. Key drivers are: compliance with the provisions of the Digital Agenda Act for the communication of copyright works; improved management of Deakin’s intellectual property, and reduction in costs of delivering online content via a learning management system.

Details of the desired functionality and potential integration issues are addressed. During the specification stage, additional uses for a digital object management system were identified that relate to the broader notion of knowledge management, and these will be discussed.

At the time of writing, no decision has been made as to which vendor(s) will be successful in gaining the University’s contract for the management of digital learning objects.

Culturally adaptive learning objects : challenges for educators and developers

In this paper the authors argue that the major problem facing local
courseware developers is that of representing cultural artefacts in their
courseware. They also discuss an emerging learning-object model that can be
adopted to address this problem by providing a systematic way to approach
implementing and representing cultural artefacts in courseware.

Depth estimation of metallic objects using multiwavelets scale-space representation

The problem of dimensional defects in aluminum die-castings is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic with highly reflective nature, it is extremely hard to estimate true dimensionality of these metallic parts, autonomously. Some existing vision systems are capable of estimating depth to high accuracy, however are very much hardware dependent, involving the use of light and laser pattern projectors, integrated into vision systems or laser scanners. However, due to the reflective nature of these metallic parts and variable factory environments, the aforementioned vision systems tend to exhibit unpromising performance. Moreover, hardware dependency makes these systems cumbersome and costly. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a pair of stereo cameras and a defused fluorescent light. The proposed vision system is capable of estimating surface depths within the accuracy of 0.5mm. In addition, the system is invariant to illuminative variations as well as orientation and location of the objects on the input image space, making the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup. The proposed system is a major part of quality inspection system for the automotive manufacturing industry.

Spiel : a novel & animating objects of desire : exegetical reflections

Thesis consists of a novel and an exegetical reflections with references. There is no abstract provided by the author.

2. Scanning and processing 3D objects for web display

We present a case study of scanning 3D objects for the purposes of education and public information. We begin by describing the original design of a 3D scanning system now in use in Cairo’s Egyptian Museum. The system captures both the geometry and surface color and detail of museum artifacts. We report on the experience using the system in the museum setting, and how practical problems with the system were addressed. We present samples of how the processed 3D data will be used on a web site designed to communicate Egyptian culture.We present a case study of scanning 3D objects for the purposes of education and public information. We begin by describing the original design of a 3D scanning system now in use in Cairo’s Egyptian Museum. The system captures both the geometry and surface color and detail of museum artifacts. We report on the experience using the system in the museum setting, and how practical problems with the system were addressed. We present samples of how the processed 3D data will be used on a web site designed to communicate Egyptian culture.

Realistic grasping of rigid virtual objects through event-based haptics

This research presents a novel haptic grasping interface and demonstrates its ability within multi-point event-based feedback. Through experimental methodology, the dynamics involved in grasp contact interactions are modelled based on first principles. The proposed approach demonstrates a method of realistically representing grasp contact with rigid virtual objects through multi-point interaction.

Data-based dynamic haptic interaction model with deformable 3D objects

The data-based modeling of the haptic interaction simulation is a growing trend in research. These techniques offer a quick alternative to parametric modeling of the simulation. So far, most of the use of the data-based techniques was applied to static simulations. This paper introduces how to use data-based model in dynamic simulations. This ensures realistic behavior and produce results that are very close to parametric modeling. The results show that a quick and accurate response can be achieved using the proposed methods.

Data-driven computation of contact dynamics during two-point manipulation of deformable objects

This study represents a preliminary step towards data-driven computation of contact dynamics during manipulation of deformable objects at two points of contact. A modeling approach is proposed that characterizes the individual interaction at both points and the mutual effects of the two interactions on each other via a set of parameters. Both global as well as local coordinate systems are tested for encoding the contact mechanics. Artificial neural networks are trained on simulated data to capture the object behavior. A comparison of test data with the output of the trained system reveals a mean squared error percentage between 1% and 3% for simple interactions.