Graphene-like nano-sheets for surface acoustic wave gas sensor applications

The gas sensing properties of graphene-like nano-sheets deposited on 36° YX lithium tantalate (LiTaO3) surface acoustic wave (SAW) transducers are reported. The thin graphene-like nano-sheets were produced via the reduction of graphite oxide which was deposited on SAW interdigitated transducers (IDTs). Their sensing performance was assessed towards hydrogen (H2) and carbon monoxide (CO) in a synthetic air carrier gas at room temperature (25 °C) and 40 °C. Raman and X-ray photoelectron spectroscopy (XPS) revealed that the deposited graphite oxide (GO) was not completely reduced creating small, graphitic nanocrystals ∼2.7 nm in size. © 2008 Elsevier B.V.

Large scale participatory acoustic sensor data analysis : tools and reputation models to enhance effectiveness

Acoustic sensors play an important role in augmenting the traditional biodiversity monitoring activities carried out by ecologists and conservation biologists. With this ability however comes the burden of analysing large volumes of complex acoustic data. Given the complexity of acoustic sensor data, fully automated analysis for a wide range of species is still a significant challenge. This research investigates the use of citizen scientists to analyse large volumes of environmental acoustic data in order to identify bird species. Specifically, it investigates ways in which the efficiency of a user can be improved through the use of species identification tools and the use of reputation models to predict the accuracy of users with unidentified skill levels. Initial experimental results are reported.

Novel corrosion sensor based on carbon nanotube composites for structural health monitoring

Bridges are important infrastructures of all nations and are required for transportation of goods as well as human. A catastrophic failure can result in loss of lives and enormous financial hardship to the nation. Hence, there is an urgent need to monitor our infrastructures to prolong their life span, at the same time catering for heavier and faster moving traffics. Although various kinds of sensors are now available to monitor the health of the structures due to corrosion, they do not provide permanent and long term measurements. This paper investigates the fabrication of Carbon Nanotube (CNT) based composite sensors for structural health monitoring. The CNTs, a key material in nanotechnology has aroused great interest in the research community due to their remarkable mechanical, electrochemical, piezoresistive and other physical properties. Multi-wall CNT (MWCNT)/Nafion composite sensors were fabricated to evaluate their electrical properties when subjected to chemical solutions, to simulate a chemical reaction due to corrosion and real life corrosion experimental tests. The electrical resistance of the sensor electrode was dramatically changed due to corrosion. The novel sensor is expected to effectively detect corrosion in structures based on the measurement of electrical impedances of the CNT composite.

A hydrogen gas sensor based on Pt/nanostructured WO3/SiC Schottky diode

Pt/nanostructured WO3/SiC Schottky diodes were fabricated and applied for hydrogen gas sensing applications. The nanostructured WO3 films were synthesized from tungsten coated SiC substrates via an acid-etching method using a 1.5 M HNO3 solution for 1 hr, 2 hrs and 3 hrs duration. Scanning electron microscopy of the developed films revealed platelet crystals with thicknesses in the order of 20-60 nm and lengths between 100-700 nm. X-ray diffraction analysis revealed that the rate of oxidation of tungsten increases as the duration of acid-etching increases. The devices were tested towards hydrogen gas balanced in air at different temperatures from 25°C to 200°C. At 200°C, voltage shifts of 0.45 V, 0.93 V and 2.37 V were recorded for devices acid-etched for 1 hr, 2 hrs and 3 hrs duration, respectively upon exposure to 1% hydrogen, under a constant forward bias current of 500 µA.

Comparison of intraocular pressure measurement between rebound, non-contact and Goldmann applanation tonometry in treated glaucoma patients

Background: To compare the intraocular pressure readings obtained with the iCare rebound tonometer and the 7CR non-contact tonometer with those measured by Goldmann applanation tonometry in treated glaucoma patients. Design: A prospective, cross sectional study was conducted in a private tertiary glaucoma clinic. Participants: 109 (54M:55F) patients including only eyes under medical treatment for glaucoma. Methods: Measurement by Goldmann applanation tonometry, iCare rebound tonometry and 7CR non-contact tonometry. Main Outcome Measures: Intraocular pressure. Results: There were strong correlations between the intraocular pressure measurements obtained with Goldmann and both the rebound and non-contact tonometers (Spearman r values ≥ 0.79, p < 0.001). However, there were small, statistically significant differences between the average readings for each tonometer. For the rebound tonometer, the mean intraocular pressure was slightly higher compared to the Goldmann applanation tonometer in the right eyes (p = 0.02), and similar in the left eyes (p = 0.93) however these differences did not reach statistical significance. The Goldmann correlated measurements from the noncontact tonometer were lower than the average Goldmann reading for both right (p < 0.001) and left (p > 0.01) eyes. The corneal compensated measurements from the non-contact tonometer were significantly higher compared to the other tonometers (p ≤ 0.001). Conclusions: The iCare rebound tonometer and the 7CR non-contact tonometer measure IOP in fundamentally different ways to the Goldmann applanation tonometer. The resulting IOP values vary between the instruments and will need to be considered when comparing clinical versus home acquired measurements.

Motivational Interviewing (MINT) improves Continuous Positive Airway Pressure (CPAP) acceptance and adherence : a randomised controlled trial

Objective: Adherence to Continuous Positive Airway Pressure Therapy (CPAP) for Obstructive Sleep Apnoea (OSA) is poor. We assessed the effectiveness of a motivational interviewing intervention (MINT) in addition to best practice standard care to improve acceptance and adherence to CPAP therapy in people with a new diagnosis of OSA. Method: 106 Australian adults (69% male) with a new diagnosis of obstructive sleep apnoea and clinical recommendation for CPAP treatment were recruited from a tertiary sleep disorders centre. Participants were randomly assigned to receive either three sessions of a motivational interviewing intervention ‘MINT’ (n=53; mean age=55.4 years), or no intervention ‘Control’ (n=53; mean age=57.74). The primary outcome was the difference between the groups in objective CPAP adherence at 1 month, 2 months, 3 months and 12 months follow-up. Results: Fifty (94%) participants in the MINT group and 50 (94%) of participants in the control group met all inclusion and exclusion criteria and were included in the primary analysis. The hours of CPAP use per night in the MINT group at 3 months was 4.63 hours and 3.16 hours in the control group (p=0.005). This represents almost 50% better adherence in the MINT group relative to the control group. Patients in the MINT group were substantially more likely to accept CPAP treatment. Conclusions: MINT is a brief, manualized, effective intervention which improves CPAP acceptance and objective adherence rates as compared to standard care alone.

Peer passenger identity and passenger pressure on young drivers' speeding intentions

Young drivers, aged 17 to 24 years, have the highest fatality rate in Australia. It is believed that part of this risk is due to pressure from peer passengers to engage in speeding; which may be active (i.e., verbal encouragement) or passive (i.e., perceived pressure on the part of the driver). The Theory of Planned Behaviour (TPB) was used to investigate this impact of peer passengers on young drivers, particularly the influence of the type of peer pressure and a driver’s level of identification with their passengers. A scenario-based questionnaire was constructed, informed by focus groups and pilot studies, and distributed to university students (N = 398). The questionnaire measured participants’ intentions and the TPB constructs, including two components of perceived behaviour control, within a baseline scenario as well as an experimental scenario in which the variables of type of pressure and identification were manipulated. Consistent with the hypotheses, the study found that attitudes and self-efficacy significantly predicted intentions over and above the variance explained by the sociodemographic variables of age, gender, self-esteem, sensation seeking, as well as past behaviour and exposure. Across the scenarios, attitudes explained between 4.3% and 14.5%, while self-efficacy to refrain from speeding explained between 4.9% and 17.1%, of the unique variance in intentions to speed. However, contrary to expectations, intentions to speed were found to be higher in the “no passenger” than “passenger present” conditions, although this finding is not completely inconsistent with recent literature. A high level of identification with passengers led to higher intentions to speed than low identification as expected, but, inconsistent with expectations, different types of pressure (i.e., active versus passive) did not influence intentions to speed.

Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

Effect of geometry on the melting rates of iron rods burning in high pressure oxygen

The effect of sample geometry on the melting rates of burning iron rods was assessed. Promoted-ignition tests were conducted with rods having cylindrical, rectangular, and triangular cross-sectional shapes over a range of cross-sectional areas. The regression rate of the melting interface (RRMI) was assessed using a statistical approach which enabled the quantification of confidence levels for the observed differences in RRMI. Statistically significant differences in RRMI were observed for rods with the same cross-sectional area but different cross-sectional shape. The magnitude of the proportional difference in RRMI increased with the cross-sectional area. Triangular rods had the highest RRMI, followed by rectangular rods, and then cylindrical rods. The dependence of RRMI on rod shape is shown to relate to the action of molten metal at corners. The corners of the rectangular and triangular rods melted faster than the faces due to their locally higher surface area to volume ratios. This phenomenon altered the attachment geometry between liquid and solid phases, increasing the surface area available for heat transfer, causing faster melting. Findings relating to the application of standard flammability test results in industrial situations are also presented.

Condition monitoring and diagnosis of injector faults in a diesel engine using in-cylinder pressure and acoustic emission techniques

Failing injectors are one of the most common faults in diesel engines. The severity of these faults could have serious effects on diesel engine operations such as engine misfire, knocking, insufficient power output or even cause a complete engine breakdown. It is thus essential to prevent such faults from occurring by monitoring the condition of these injectors. In this paper, the authors present the results of an experimental investigation on identifying the signal characteristics of a simulated incipient injector fault in a diesel engine using both in-cylinder pressure and acoustic emission (AE) techniques. A time waveform event driven synchronous averaging technique was used to minimize or eliminate the effect of engine speed variation and amplitude fluctuation. It was found that AE is an effective method to detect the simulated injector fault in both time (crank angle) and frequency (order) domains. It was also shown that the time domain in-cylinder pressure signal is a poor indicator for condition monitoring and diagnosis of the simulated injector fault due to the small effect of the simulated fault on the engine combustion process. Nevertheless, good correlations between the simulated injector fault and the lower order components of the enveloped in-cylinder pressure spectrum were found at various engine loading conditions.

Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

Understanding innovation adoption : effects of orientation, pressure and control on adoption

We develop and test a theoretically-based integrative framework of key proximal factors (orientation, pressure, and control) that helps to explain the effects of more general factors (the organisation's strategy, structure, and environment) on intentions to adopt an innovation one year later. Senior managers from 134 organizations were surveyed and confirmatory factor analyses showed that these hypothesized core factors provided a good fit to the data, indicating that our framework can provide a theoretical base to the previous, largely a theoretical, literature. Moreover, in a subgroup of 63 organizations, control mediated the effects of organizational strategy and centralisation on organizational innovation adoption intentions one year later. We suggest this model of core factors enables researchers to understand why certain variables are important to organisational innovation adoption and promotes identification of fertile research areas around orientation, pressure and control, and it enables managers to focus on the most proximal triggers for increasing innovation adoption.