The knowledge exchange intermediary as service provider : a discussion and an Australian case

The critical impact of innovation on national and the global economies has been discussed at length in the literature. Economic development requires the diffusion of innovations into markets. It has long been recognised that economic growth and development depends upon a constant stream of innovations. Governments have been keenly aware of the need to ensure this flow does not dry to a trickle and have introduced many and varied industry policies and interventions to assist in seeding, supporting and diffusing innovations. In Australia, as in many countries, Government support for the transfer of knowledge especially from publicly funded research has resulted in the creation of knowledge exchange intermediaries. These intermediaries are themselves service organisations, seeking innovative service offerings for their markets. The choice for most intermediaries is generally a dichotomous one, between market-pull and technology-push knowledge exchange programmes. In this article, we undertake a case analysis of one such innovative intermediary and its flagship programme. We then compare this case with other successful intermediaries in Europe. We put forward a research proposition that the design of intermediary programmes must match the service type they offer. That is, market-pull programmes require market-pull design, in close collaboration with industry, whereas technology programmes can be problem-solving innovations where demand is latent. The discussion reflects the need for an evolution in knowledge transfer policies and programmes beyond the first generation ushered in with the US Bayh-Dole Act (1980) and Stevenson-Wydler Act (1984). The data analysed is a case study comparison of market-pull and technology-push programmes, focusing on primary and secondary socio-economic benefits (using both Australian and international comparisons).

ePortfolio use by university students in Australia: Informing excellence in policy and practice

In mid 2007, the Australian Learning and Teaching Council (ALTC), formerly the Carrick Institute for Learning and Teaching in Higher Education, commissioned an intensive research project to examine the use of ePortfolios by university students in Australia. The project was awarded to a consortium of four universities: Queensland University of Technology as lead institution, The University of Melbourne, University of New England and University of Wollongong.---------- The overarching aim of the research project, which was given the working title of the Australian ePortfolio Project, was to examine the current levels of ePortfolio practice in Australian higher education. The principal project goals sought to provide an overview and analysis of the national and international ePortfolio contexts, document the types of ePortfolios used in Australian higher education, examine the relationship with the National Diploma Supplement project funded by the Federal government, identify any significant issues relating to ePortfolio implementation, and offer guidance about future opportunities for ePortfolio development. The research findings revealed that there was a high level of interest in the use of ePortfolios in the context of higher education, particularly in terms of the potential to help students become reflective learners who are conscious of their personal and professional strengths and weaknesses, as well as to make their existing and developing skills more explicit. There were some good examples of early adoption in different institutions, although this tended to be distributed across the sector. The greatest use of ePortfolios was recorded in coursework programs, rather than in research programs, with implementation generally reflecting subject-specific or program-based activity, as opposed to faculty- or university-wide activity. Accordingly, responsibility for implementation frequently rested with the individual teaching unit, although an alternative centralised model of coordination by ICT services, careers and employment or teaching and learning support was beginning to emerge. The project report concludes with a series of recommendations to guide the process, drawing on the need for open dialogue and effective collaboration between the stakeholders across the range of contexts: government policy, international technical standards, academic policy, and learning and teaching research and practice.

Planning and evaluation

Introduction: The core business of public health is to protect and promote health in the population. Public health planning is the means to maximise these aspirations. Health professionals develop plans to address contemporary health priorities as the evidence about changing patterns of mortality and morbidity is presented. Officials are also alert to international trends in patterns of disease that have the potential to affect the health of Australians. Integrated planning and preparation is currently underway involving all emergency health services, hospitals and population health units to ensure Australia's quick and efficient response to any major infectious disease outbreak, such as avian influenza (bird flu). Public health planning for the preparations for the Sydney Olympics and Paralympic Games in 2000 took almost three years. ‘Its major components included increased surveillance of communicable disease; presentations to sentinel emergency departments; medical encounters at Olympic venues; cruise ship surveillance; environmental and food safety inspections; bioterrorism surveillance and global epidemic intelligence’ (Jorm et al 2003, 102). In other words, the public health plan was developed to ensure food safety, hospital capacity, safe crowd control, protection against infectious diseases, and an integrated emergency and disaster plan. We have national and state plans for vaccinating children against infectious diseases in childhood; plans to promote dental health for children in schools; and screening programs for cervical, breast and prostate cancer. An effective public health response to a change in the distribution of morbidity and mortality requires planning. All levels of government plan for the public’s health. Local governments (councils) ensure healthy local environments to protect the public’s health. They plan parks for recreation, construct traffic-calming devices near schools to prevent childhood accidents, build shade structures and walking paths, and even embed drafts/chess squares in tables for people to sit and play. Environmental Health officers ensure food safety in restaurants and measure water quality. These public health measures attempt to promote the quality of life of residents. Australian and state governments produce plans that protect and promote health through various policy and program initiatives and innovations. To be effective, program plans need to be evaluated. However, building an integrated evaluation plan into a program plan is often forgotten, as planning and evaluation are seen as two distinct entities. Consequently, it is virtually impossible to measure, with any confidence, the extent to which a program has achieved its goals and objectives. This chapter introduces you to the concepts of public health program planning and evaluation. Case studies and reflection questions are presented to illustrate key points. As various authors use different terminology to describe the same concepts/actions of planning and evaluation, the glossary at the back of this book will help you to clarify the terms used in this chapter.

Persistent navigation and mapping using a biologically inspired SLAM system

The challenge of persistent navigation and mapping is to develop an autonomous robot system that can simultaneously localize, map and navigate over the lifetime of the robot with little or no human intervention. Most solutions to the simultaneous localization and mapping (SLAM) problem aim to produce highly accurate maps of areas that are assumed to be static. In contrast, solutions for persistent navigation and mapping must produce reliable goal-directed navigation outcomes in an environment that is assumed to be in constant flux. We investigate the persistent navigation and mapping problem in the context of an autonomous robot that performs mock deliveries in a working office environment over a two-week period. The solution was based on the biologically inspired visual SLAM system, RatSLAM. RatSLAM performed SLAM continuously while interacting with global and local navigation systems, and a task selection module that selected between exploration, delivery, and recharging modes. The robot performed 1,143 delivery tasks to 11 different locations with only one delivery failure (from which it recovered), traveled a total distance of more than 40 km over 37 hours of active operation, and recharged autonomously a total of 23 times.

Hippocampal models for simultaneous localisation and mapping on an autonomous robot

To navigate successfully in a novel environment a robot needs to be able to Simultaneously Localize And Map (SLAM) its surroundings. The most successful solutions to this problem so far have involved probabilistic algorithms, but there has been much promising work involving systems based on the workings of part of the rodent brain known as the hippocampus. In this paper we present a biologically plausible system called RatSLAM that uses competitive attractor networks to carry out SLAM in a probabilistic manner. The system can effectively perform parameter self-calibration and SLAM in one dimension. Tests in two dimensional environments revealed the inability of the RatSLAM system to maintain multiple pose hypotheses in the face of ambiguous visual input. These results support recent rat experimentation that suggest current competitive attractor models are not a complete solution to the hippocampal modelling problem.

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment

This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.

Simultaneous localisation and mapping from natural landmarks using RatSLAM

This paper describes the current state of RatSLAM, a Simultaneous Localisation and Mapping (SLAM) system based on models of the rodent hippocampus. RatSLAM uses a competitive attractor network to fuse visual and odometry information. Energy packets in the network represent pose hypotheses, which are updated by odometry and can be enhanced or inhibited by visual input. This paper shows the effectiveness of the system in real robot tests in unmodified indoor environments using a learning vision system. Results are shown for two test environments; a large corridor loop and the complete floor of an office building.

Effect of representation size and visual ambiguity on RatSLAM system performance

RatSLAM is a vision-based SLAM system based on extended models of the rodent hippocampus. RatSLAM creates environment representations that can be processed by the experience mapping algorithm to produce maps suitable for goal recall. The experience mapping algorithm also allows RatSLAM to map environments many times larger than could be achieved with a one to one correspondence between the map and environment, by reusing the RatSLAM maps to represent multiple sections of the environment. This paper describes experiments investigating the effects of the environment-representation size ratio and visual ambiguity on mapping and goal navigation performance. The experiments demonstrate that system performance is weakly dependent on either parameter in isolation, but strongly dependent on their joint values.

Control issues for velocity sourced Series Elastic Actuators

The Series Elasic Actuator has been proposed as a method for providing safe force or torque based acutation for robots that interact with humans. In this paper we look at some outstanding issues in the implementation and control of Series Elastic Actuators. The study addresses issues in making the Series Elastic Actuator respond effectively in the presence of physical difficulties such as restriction, using a computation efficient controller. The improvement over previous implementations is achieved by treating the motor as a velocity source to the elastic element, rather than as a torque source.

Fast and robust stereo object recognition for spheres

The paper presents a fast and robust stereo object recognition method. The method is currently unable to identify the rotation of objects. This makes it very good at locating spheres which are rotationally independent. Approximate methods for located non-spherical objects have been developed. Fundamental to the method is that the correspondence problem is solved using information about the dimensions of the object being located. This is in contrast to previous stereo object recognition systems where the scene is first reconstructed by point matching techniques. The method is suitable for real-time application on low-power devices.

Assessing the safety of a velocity sourced series elastic actuator using the head injury criterion

The Velocity Sourced Series Elastic Actuator has been proposed as a method for providing safe force or torque based actuation for robots without compromising the actuator performance. In this paper we assess the safety of Velocity Sourced Series Elastic Actuators by measuring the Head Injury Criterion scores for collisions with a model head. The study makes a comparative analysis against stiff, high impedance actuation using the same motor without the series elastic component, showing that the series elastic component brings about a massive reduction in the chance of head injury. The benefits of a collision detection and safe reaction system are shown to be limited to collisions at low speeds, providing greater interaction comfort but not necessarily contributing to safety from injury.

Biologically inspired visual landmark processing for simultaneous localization and mapping

This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.

Modeling and exploiting behavior patterns in dynamic environments

This paper presents a new approach to improving the effectiveness of autonomous systems that deal with dynamic environments. The basis of the approach is to find repeating patterns of behavior in the dynamic elements of the system, and then to use predictions of the repeating elements to better plan goal directed behavior. It is a layered approach involving classifying, modeling, predicting and exploiting. Classifying involves using observations to place the moving elements into previously defined classes. Modeling involves recording features of the behavior on a coarse grained grid. Exploitation is achieved by integrating predictions from the model into the behavior selection module to improve the utility of the robot's actions. This is in contrast to typical approaches that use the model to select between different strategies or plays. Three methods of adaptation to the dynamic features of the environment are explored. The effectiveness of each method is determined using statistical tests over a number of repeated experiments. The work is presented in the context of predicting opponent behavior in the highly dynamic and multi-agent robot soccer domain (RoboCup).

In Bed with Autobiography: Unravelling the Fabric of Gender and Genre in Women’s Bed(room) Confessions

This thesis consists of a confessional narrative, What My Mother Doesn’t Know, and an accompanying exegesis, And Why I Should (Maybe) Tell Her. The creative piece employs the confessional mode as a subversive device in three separate narratives, each of which situates the bed as a site of resistance. The exegesis investigates how this self-disclosure in a domestic space flouts the governing rules of self-representation, specifically: telling the truth, respecting privacy and displaying normalcy. The female confession, I argue, creates an alternative space in women’s autobiography where notions of truth-telling can be undermined, the political dimensions of personal experience can be uncovered and the discourse of normality can be negotiated. In particular, women’s confessions told in, on or about the bed, dismantle the genre’s illusion of self and confirm the representative aspects of women’s experience. Framed within these parameters of power and powerlessness, the exegesis includes textual analyses of Charlotte Perkins Gilman’s The Yellow Wallpaper (1892), Tracey Emin’s My Bed (1999) and Lauren Slater’s Lying (2000), each of which exposes in a bedroom space, the author’s most obscure, intimate and traumatic experiences. Situated firmly within and against the genre’s traditional masculine domain, the exegesis also includes mediations on the creative work that validate the bed as my fabric for confession.