Participatory design for technological disruption within the agricultural sector

Agricultural adoption of innovation has traditionally been described as slow to diffuse. This paper therefore describes a case study grounded in PD to address a disruptive technology/system within the livestock industry. Results of the process were positive, as active engagement of stakeholders returned rich data. The contribution of the work is also presented as grounds for further design research in the livestock industry.

Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Participatory action research card set

These cards are designed as a resource for implementing participatory action research (PAR) in social programs. Each card covers one of the five key stages of PAR as outlined in the manual 'On PAR- Using participatory Action Research to Improve Early Intervention' (Crane and O'Regan 2010).

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Animateur : participatory studio-based learning in computer graphics animation

The impact of digital technology within the creative industries has brought with it a range of new opportunities for collaborative, cross-disciplinary and multi-disciplinary practice. Along with these opportunities has come the need to re-evaluate how we as educators approach teaching within this new digital culture. Within the field of animation, there has been a radical shift in the expectations of students, industry and educators as animation has become central to a range of new moving image practices. This paper interrogates the effectiveness of adopting a studio-based collaborative production project as a method for educating students within this new moving-image culture. The project was undertaken, as part of the Creative Industries Transitions to New Professional Environments program at Queensland University of Technology (QUT) in Brisbane Australia. A number of students studying across the Creative Industries Faculty and the Faculty of Science and Technology were invited to participate in the development of a 3D animated short film. The project offered students the opportunity to become actively involved in all stages of the creative process, allowing them to experience informal learning through collaborative professional practice. It is proposed that theoretical principles often associated with andragogy and constructivism can be used to design and deliver programs that address the emerging issues surrounding the teaching of this new moving image culture.

Integrating Responses to Homelessness: The Contribution of Participatory Action Research

In recent years Participatory Action Research (PAR) and other collaborative inquiry processes have been used in a wide variety of program and service contexts. Early childhood services, Indigenous services, youth drug and alcohol services, and education and vocational training support services have all been sites where PAR has been utilized. Action research is important as it helps improve policy and ensures that best practice and experience can be shared.

Participatory action research workbook

Provides a structure and a series of proformas for documenting a participatory action research (PAR) process. Includes tools for documenting PAR questions, documenting each element of the PAR cycle, and for writing a case study. Users can write into the word version of this workbook so it provides an ongoing record of the PAR process used.

Analysis of detection performance in spectrum sensing optimisation for long sensing periods

Spectrum sensing optimisation techniques maximise the efficiency of spectrum sensing while satisfying a number of constraints. Many optimisation models consider the possibility of the primary user changing activity state during the secondary user's transmission period. However, most ignore the possibility of activity change during the sensing period. The observed primary user signal during sensing can exhibit a duty cycle which has been shown to severely degrade detection performance. This paper shows that (a) the probability of state change during sensing cannot be neglected and (b) the true detection performance obtained when incorporating the duty cycle of the primary user signal can deviate significantly from the results expected with the assumption of no such duty cycle.

Designing disruption : linking participatory design and design thinking in technology orientated industries

A vast proportion of companies nowadays are looking to design and are focusing on the end users as a means of driving new projects. However still many companies are drawn to technological improvements which drive innovation within their industry context. The Australian livestock industry is no different. To date the adoption of new products and services within the livestock industry has been documented as being quite slow. This paper investigates how disruptive innovation should be a priority for these technologically focused companies and demonstrates how the use of design led innovation can bring about a higher quality engagement between end user and company alike. A case study linking participatory design and design thinking is presented. Within this, a conceptual model of presenting future scenarios to internal and external stakeholders is applied to the livestock industry; assisting companies to apply strategy, culture and advancement in meaningful product offerings to consumers.

Transition from n- to p-type of spray pyrolysis deposited Cu doped ZnO thin films for NO2 sensing

The structural, optical, and gas-sensing properties of spray pyrolysis deposited Cu doped ZnO thin films were investigated. Gas response of the undoped and doped films to N02 (oxidizing) gas shows an increase and decrease in resistance, respectively, indicating p-type conduction in doped samples. The UV-Vis spectra of the films show decrease in the bandgap with increasing Cu concentration in ZnO. The observed p-type conductivity is attributed to the holes generated by incorporated Cu atoms on Zn sites in ZnO thin films. The X-ray diffraction spectra showed that samples are polycrystalline with the hexagonal wurtzite structure and increasing the concentration of Cu caused a decrease in the intensity of the dominant (002) peak. The surface morphology of films was studied by scanning electron microscopy and the presence of Cu was also confirmed by X-ray photoelectron spectroscopy. Seebeck effect measurements were utilized to confirm the p-type conduction of Cu doped ZnO thin films. Copyright © 2009 American Scientific Publishers All rights reserved.

Reversed bias Pt/nanostructured ZnO Schottky diode with enhanced electric field for hydrogen sensing

In this paper, the effect of electric field enhancement on Pt/nanostructured ZnO Schottky diode based hydrogen sensors under reverse bias condition has been investigated. Current-voltage characteristics of these diodes have been studied at temperatures from 25 to 620 °C and their free carrier density concentration was estimated by exposing the sensors to hydrogen gas. The experimental results show a significantly lower breakdown voltage in reversed bias current-voltage characteristics than the conventional Schottky diodes and also greater lateral voltage shift in reverse bias operation than the forward bias. This can be ascribed to the increased localized electric fields emanating from the sharp edges and corners of the nanostructured morphologies. At 620 °C, voltage shifts of 114 and 325 mV for 0.06% and 1% hydrogen have been recorded from dynamic response under the reverse bias condition. © 2010 Elsevier B.V. All rights reserved.

Nanowires of metal oxides for gas sensing applications

Nanowires of different metal oxides (SnO2, ZnO) have been grown by evaporation-condensation process. Their chemical composition has been investigated by using XPS. The standard XPS quantification through main photoelectron peaks, modified Auger parameter and valence band spectra were examined for the accurate determination of oxidation state of metals in the nanowires. Morphological investigation has been conducted by acquiring and analyzing the SEM images. For the simulation of working conditions of sensor, the samples were annealed in ultra high vacuum (UHV) up to 500°C and XPS analysis repeated after this treatment. Finally, the nanowires of SnO 2 have were used to produce a novel gas sensor based on Pt/oxide/SiC structure and operating as Schottky diode. Copyright © 2008 John Wiley & Sons, Ltd.

Platinum/graphene nanosheet/SiC contacts and their application for hydrogen gas sensing

Pt/graphene nanosheet/SiC based devices are fabricated and characterized and their performances toward hydrogen gas are investigated. The graphene nanosheets are synthesized via the reduction of spray-coated graphite oxide deposited onto SiC substrates. Raman and X-ray photoelectron spectroscopies indicate incomplete reduction of the graphite oxide, resulting in partially oxidized graphene nanosheet layers of less than 10 nm thickness. The effects of interfaces on the nonlinear behavior of the Pt/graphene and graphene/SiC junctions are investigated. Current-voltage measurements of the sensors toward 1% hydrogen in synthetic air gas mixture at various temperatures ranging up to 100. ° C are performed. From the dynamic response, a voltage shift of ∼100 mV is recorded for 1% hydrogen at a constant current bias of 1 mA at 100. °C. © 2010 American Chemical Society.

Compressive sensing for gait recognition

Compressive Sensing (CS) is a popular signal processing technique, that can exactly reconstruct a signal given a small number of random projections of the original signal, provided that the signal is sufficiently sparse. We demonstrate the applicability of CS in the field of gait recognition as a very effective dimensionality reduction technique, using the gait energy image (GEI) as the feature extraction process. We compare the CS based approach to the principal component analysis (PCA) and show that the proposed method outperforms this baseline, particularly under situations where there are appearance changes in the subject. Applying CS to the gait features also avoids the need to train the models, by using a generalised random projection.