A to Z safari

An alphabet app designed by Deakin University researchers specialising in literacy education, IT and graphic design to support children beginning to learn letter-sound relationships using research into memory retention. Tested with Australian primary school students, the ‘form-taking’ images used in this app have been found to be more effective at assisting children to learn common letter-sound relationships than images that are not form-taking (e.g. integrated images). A to Z Safari offers engaging mini-games to explore and reinforce letter-sound relationships, along with a password-protected admin/data area where students’ progress and gameplay statistics are recorded – data which can be emailed directly to the teacher. A to Z Safari has not been designed to replace classroom activities, but was designed as an electronic application to complement them. An A3-sized alphabet chart accompanies the app in the teacher area so that teachers can print the charts out to place on their students’ tables for their reference outside of game play.

Optimal algorithm for a mobile intelligent gas detection device

This thesis is based on the development of a gas detection device that can be mounted on a mobile robotic platform. The focus was on development of the A.I recognition algorithm with an array of sensors to detect trace amounts of explosive and volatile gases in the environments it is exposed to.

Digital technology policies in Canada and Australia: an analysis of new rules for ‘new tech'

As mobile touch screen digital devices (MTSD) have moved into a more prominent position in classrooms and schools, the development of new policies to address these devices have also emerged at a rapid pace. While policy documents aimed at MTSD usage in schools are evident at range of levels, from school-based to education ministries and departments, there is relatively little research that examines such documents or their impact on teaching and learning. This paper reports on initial analyses of educational digital media and MSTD policies in education departments and schools in Victoria, Australia and Alberta, Canada. We examined these policy documents in relation to implications for resourcing, usage and teaching practice, as a part of a large-scale Canadian-funded comparative research project studying digital tools and practices. Schools must mediate and negotiate complex entangled environments that are all at once enabling and dis-abling of innovation, in relation to digital technologies. These complex environments are made visible through a closer reading of artifacts such as policy documents guiding technology use in schools and classrooms. Our paper will interrogate such documents, across both countries (Canada and Australia) and regions (Victoria and Alberta), in relation to several emergent themes: private vs. school funded ownership, attitudes towards ‘bring your own device' (BYOD) initiatives and "co-contributions", equity and access, and surveillance and control. As well, we will address how hopes and fears and understandings of digital literacy are represented, described and enacted through such policies. Our analyses will also contextualize our data in terms of the broader cultural, political and educational considerations that framing and undergirding policies in both countries, and, finally, we will address the different (and similar) assumptions that are communicated within the digital policy documents.

A miniature neural recording device

This paper presents a portable neural recording device for use with laboratory animals. It can detect and record neural signals from the cortical region of the brain during pre-clinical trials. The device utilizes simplified circuitry to perform signal detection, filtering, sampling, and storage. It includes analog and digital components each implemented on a separate small printed circuit board. The two printed circuit boards are then attached to one another to form the device. It is capable of uninterrupted operation for over 2 hours on a single coin battery. A bench-testing of the device was performed with pre-recorded neural signal which then injected to the input of the device to give validation of efficient operation of the device. Its amplification and filtration features have been analyzed. An overall 56 dB amplification and filtration in the frequency range of 300 Hz to 4 KHz was achieved. Sampling and storage at a reduced power and computational load is demonstrated with uninterrupted storage of the neural signal. A comparison of the input and reconstructed neural signals shows minimal variation error.

Graph theory based QoE-driven cooperation stimulation for content dissemination in device-To-device communication

With multimedia dominating the digital contents, Device-To-Device (D2D) communication has been proposed as a promising data offloading solution in the big data area. As the quality of experience (QoE) is a major determining factor in the success of new multimedia applications, we propose a QoEdriven cooperative content dissemination (QeCS) scheme in this work. Specifically, all users predict the QoE of the potential connections characterized by the mean opinion score (MOS), and send the results to the content provider (CP). Then CP formulates a weighted directed graph according to the network topology and MOS of each potential connection. In order to stimulate cooperation among the users, the content dissemination mechanism is designed through seeking 1-factor of the weighted directed graph with the maximum weight thus achieving maximum total user MOS. Additionally, a debt mechanism is adopted to combat the cheat attacks. Furthermore, we extend the proposed QeCS scheme by considering a constrained condition to the optimization problem for fairness improvement. Extensive simulation results demonstrate that the proposed QeCS scheme achieves both efficiency and fairness especially in large scale and density networks.