Static and dynamic strain sensing using a polymer : carbon nanotube film strain sensor

The search for new multipoint, multidirectional strain sensing devices has received a new impetus since the discovery of carbon nanotubes. The excellent electrical, mechanical, and electromechanical properties of carbon nanotubes make them ideal candidates as primary materials in the design of this new generation of sensing devices. Carbon nanotube based strain sensors proposed so far include those based on individual carbon nanotubes for integration in nano or micro elecromechanical systems (NEMS/MEMS) [1], or carbon nanotube films consisting of spatially connected carbon nanotubes [2], carbon nanotube - polymer composites [3,4] for macroscale strain sensing. Carbon nanotube films have good strain sensing response and offer the possibility of multidirectional and multipoint strain sensing, but have poor performance due to weak interaction between carbon nanotubes. In addition, the carbon nanotube film sensor is extremely fragile and difficult to handle and install. We report here the static and dynamic strain sensing characteristics as well as temperature effects of a sandwich carbon nanotube - polymer sensor fabricated by infiltrating carbon nanotube films with polymer.

Examining spirituality and intrinsic religious orientation as a means of coping with exam anxiety

Spirituality and religiosity have traditionally had a troubled relationship with psychology. However, a new field of study has emerged that is examining the health benefits of spirituality and religion. The current study examined the relationship between spirituality, religiosity and coping among a group of university students facing exams. Participants completed the Spiritual Well-Being Scale, Age Universal Religious Orientation Scale, Spiritual Transcendence Scale, Brief COPE, Test Anxiety Inventory, and State Trait Anxiety Inventory. Regression analyses found that existential well-being as measured by the Spiritual Well Being Scale was the best predictor of reduced anxiety. Maladaptive coping, however, was found to be inversely related to spirituality and religiosity, but highly predictive of elevated anxiety in this sample. Strengths and limitations of this study along with recommendations for further research are made.

Field portable time resolved SORS sensor for the identification of concealed hazards

Raman spectroscopy, when used in spatially offset mode, has become a potential tool for the identification of explosives and other hazardous substances concealed in opaque containers. The molecular fingerprinting capability of Raman spectroscopy makes it an attractive tool for the unambiguous identification of hazardous substances in the field. Additionally, minimal sample preparation is required compared with other techniques. We report a field portable time resolved Raman sensor for the detection of concealed chemical hazards in opaque containers. The new sensor uses a pulsed nanosecond laser source in conjunction with an intensified CCD detector. The new sensor employs a combination of time and space resolved Raman spectroscopy to enhance the detection capability. The new sensor can identify concealed hazards by a single measurement without any chemometric data treatments.

Functionalised zinc oxide nanowire gas sensors : enhanced NO2 gas sensor response by chemical modification of nanowire surfaces

Surface coating with an organic self-assembled monolayer (SAM) can enhance surface reactions or the absorption of specific gases and hence improve the response of a metal oxide (MOx) sensor toward particular target gases in the environment. In this study the effect of an adsorbed organic layer on the dynamic response of zinc oxide nanowire gas sensors was investigated. The effect of ZnO surface functionalisation by two different organic molecules, tris(hydroxymethyl)aminomethane (THMA) and dodecanethiol (DT), was studied. The response towards ammonia, nitrous oxide and nitrogen dioxide was investigated for three sensor configurations, namely pure ZnO nanowires, organic-coated ZnO nanowires and ZnO nanowires covered with a sparse layer of organic-coated ZnO nanoparticles. Exposure of the nanowire sensors to the oxidising gas NO2 produced a significant and reproducible response. ZnO and THMA-coated ZnO nanowire sensors both readily detected NO2 down to a concentration in the very low ppm range. Notably, the THMA-coated nanowires consistently displayed a small, enhanced response to NO2 compared to uncoated ZnO nanowire sensors. At the lower concentration levels tested, ZnO nanowire sensors that were coated with THMA-capped ZnO nanoparticles were found to exhibit the greatest enhanced response. ΔR/R was two times greater than that for the as-prepared ZnO nanowire sensors. It is proposed that the ΔR/R enhancement in this case originates from the changes induced in the depletion-layer width of the ZnO nanoparticles that bridge ZnO nanowires resulting from THMA ligand binding to the surface of the particle coating. The heightened response and selectivity to the NO2 target are positive results arising from the coating of these ZnO nanowire sensors with organic-SAM-functionalised ZnO nanoparticles.

Accounting for calibration uncertainty in phylogenetic estimation of evolutionary divergence times

The estimation of phylogenetic divergence times from sequence data is an important component of many molecular evolutionary studies. There is now a general appreciation that the procedure of divergence dating is considerably more complex than that initially described in the 1960s by Zuckerkandl and Pauling (1962, 1965). In particular, there has been much critical attention toward the assumption of a global molecular clock, resulting in the development of increasingly sophisticated techniques for inferring divergence times from sequence data. In response to the documentation of widespread departures from clocklike behavior, a variety of local- and relaxed-clock methods have been proposed and implemented. Local-clock methods permit different molecular clocks in different parts of the phylogenetic tree, thereby retaining the advantages of the classical molecular clock while casting off the restrictive assumption of a single, global rate of substitution (Rambaut and Bromham 1998; Yoder and Yang 2000).

Sandwiched carbon nanotube film as strain sensor

Two types of carbon nanotube nanocomposite strain sensors were prepared by mixing carbon nanotubes with epoxy (nanocomposite sensor) and sandwiching a carbon nanotube film between two epoxy layers (sandwich sensor). The conductivity, response and sensitivity to static and dynamic mechanical strains in these sensors were investigated. The nanocomposite sensor with 2-3 wt.% carbon nanotube demonstrated high sensitivity to mechanical strain and environmental temperature, with gauge factors of 5-8. On the other hand, a linear relationship between conductivity and dynamic mechanical strain was observed in the sandwich sensor. The sandwich sensor was also not sensitive to temperature although its strain sensitivity (gauge factor of about 3) was lower as compared with the nanocomposite sensor. Both sensors have excellent response to static and dynamic strains, thereby having great potential for strain sensing applications.

A high sensitive fiber Bragg grating strain sensor with automatic temperature compensation

A high sensitive fiber Bragg grating (FBG) strain sensor with automatic temperature compensation is demonstrated. FBG is axially linked with a stick and their free ends are fixed to the measured object. When the measured strain changes, the stick does not change in length, but the FBG does. When the temperature changes, the stick changes in length to pull the FBG to realize temperature compensation. In experiments, 1.45 times strain sensitivity of bare FBG with temperature compensation of less than 0.1 nm Bragg wavelength drift over 100 ◦C shift is achieved.

A high sensitive fiber Bragg grating cryogenic temperature sensor

At cryogenic temperature, a fiber Bragg grating (FBG) temperature sensor with controllable sensitivity and variable measurement range is demonstrated by using bimetal configuration. In experiments, sensitivities of -51.2, -86.4, and -520 pm/K are achieved by varying the lengths of the metals. Measurement ranges of 293-290.5, 283-280.5, and 259-256.5 K are achieved by shortening the distance of the gap among the metals.

The effect of mill orientation angle on bagasse moisture content

THIS PAPER DESCRIBES an experimental investigation to explore a concept designed to reduce the moisture content of bagasse. It takes advantage of gravity to separate juice from bagasse by feeding bagasse upwards into the nip of the mill while juice drains downwards under gravity. The investigation found that orienting the feed to a mill upwards does reduce bagasse moisture content and that the benefit is expected to be greater than two units of moisture. While an advantage was found in orienting the feed up to 50° above the horizontal, no extra benefit was found in increasing the angle higher (up to 60° was explored) and so a 50° orientation was identified as the preferred angle for this design concept.

Non-invasive method for detecting changes in soil moisture using wireless sensor networks

There are several popular soil moisture measurement methods today such as time domain reflectometry, electromagnetic (EM) wave, electrical and acoustic methods. Significant studies have been dedicated in developing method of measurements using those concepts, especially to achieve the characteristics of noninvasiveness. EM wave method provides an advantage because it is non-invasive to the soil and does not need to utilise probes to penetrate or bury in the soil. But some EM methods are also too complex, expensive, and not portable for the application of Wireless Sensor Networks; for example satellites or UAV (Unmanned Aerial Vehicle) based sensors. This research proposes a method in detecting changes in soil moisture using soil-reflected electromagnetic (SREM) wave from Wireless Sensor Networks (WSNs). Studies have shown that different levels of soil moisture will affects soil’s dielectric properties, such as relative permittivity and conductivity, and in turns change its reflection coefficients. The SREM wave method uses a transmitter adjacent to a WSNs node with purpose exclusively to transmit wireless signals that will be reflected by the soil. The strength from the reflected signal that is determined by the soil’s reflection coefficients is used to differentiate the level of soil moisture. The novel nature of this method comes from using WSNs communication signals to perform soil moisture estimation without the need of external sensors or invasive equipment. This innovative method is non-invasive, low cost and simple to set up. There are three locations at Brisbane, Australia chosen as the experiment’s location. The soil type in these locations contains 10–20% clay according to the Australian Soil Resource Information System. Six approximate levels of soil moisture (8, 10, 13, 15, 18 and 20%) are measured at each location; with each measurement consisting of 200 data. In total 3600 measurements are completed in this research, which is sufficient to achieve the research objective, assessing and proving the concept of SREM wave method. These results are compared with reference data from similar soil type to prove the concept. A fourth degree polynomial analysis is used to generate an equation to estimate soil moisture from received signal strength as recorded by using the SREM wave method.

Lost in translation (and rotation) : rapid extrinsic calibration for 2D and 3D LIDARs

This paper describes a novel method for determining the extrinsic calibration parameters between 2D and 3D LIDAR sensors with respect to a vehicle base frame. To recover the calibration parameters we attempt to optimize the quality of a 3D point cloud produced by the vehicle as it traverses an unknown, unmodified environment. The point cloud quality metric is derived from Rényi Quadratic Entropy and quantifies the compactness of the point distribution using only a single tuning parameter. We also present a fast approximate method to reduce the computational requirements of the entropy evaluation, allowing unsupervised calibration in vast environments with millions of points. The algorithm is analyzed using real world data gathered in many locations, showing robust calibration performance and substantial speed improvements from the approximations.

Role of ubiquitous sensor network in patient care

Efficient caring for the patient's information is an important aspect of caring for the patient. If these processes are possible to monitor anytime anywhere as per the patients' and doctors desecrations the cost of patient care could be minimised. In this connection, Ubiquitous Sensor Network is playing a key role on communication between physicians and patients as well as information sharing among health care providers with rapid access to medical information through reliable and trusted computer network systems. This paper argues possibilities of such scenarios by introducing a ubiquitous sensor network in patient care for 21st century's requirements and standards.

Integrated vision-based attitude estimation

For many years, computer vision has lured researchers with promises of a low-cost, passive, lightweight and information-rich sensor suitable for navigation purposes. The prime difficulty in vision-based navigation is that the navigation solution will continually drift with time unless external information is available, whether it be cues from the appearance of the scene, a map of features (whether built online or known a priori), or from an externally-referenced sensor. It is not merely position that is of interest in the navigation problem. Attitude (i.e. the angular orientation of a body with respect to a reference frame) is integral to a visionbased navigation solution and is often of interest in its own right (e.g. flight control). This thesis examines vision-based attitude estimation in an aerospace environment, and two methods are proposed for constraining drift in the attitude solution; one through a novel integration of optical flow and the detection of the sky horizon, and the other through a loosely-coupled integration of Visual Odometry and GPS position measurements. In the first method, roll angle, pitch angle and the three aircraft body rates are recovered though a novel method of tracking the horizon over time and integrating the horizonderived attitude information with optical flow. An image processing front-end is used to select several candidate lines in a image that may or may not correspond to the true horizon, and the optical flow is calculated for each candidate line. Using an Extended Kalman Filter (EKF), the previously estimated aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and location of the horizon in the image. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To evaluate the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42° and 0.71° respectively when compared with a truth attitude source. The Cessna 172 flight resulted in pitch and roll error standard deviations of 1.79° and 1.75° respectively. In the second method for estimating attitude, a novel integrated GPS/Visual Odometry (GPS/VO) navigation filter is proposed, using a structure similar to a classic looselycoupled GPS/INS error-state navigation filter. Under such an arrangement, the error dynamics of the system are derived and a Kalman Filter is developed for estimating the errors in position and attitude. Through similar analysis to the GPS/INS problem, it is shown that the proposed filter is capable of recovering the complete attitude (i.e. pitch, roll and yaw) of the platform when subjected to acceleration not parallel to velocity for both the monocular and stereo variants of the filter. Furthermore, it is shown that under general straight line motion (e.g. constant velocity), only the component of attitude in the direction of motion is unobservable. Numerical simulations are performed to demonstrate the observability properties of the GPS/VO filter in both the monocular and stereo camera configurations. Furthermore, the proposed filter is tested on imagery collected using a Cessna 172 to demonstrate the observability properties on real-world data. The proposed GPS/VO filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. Since no platformspecific dynamics are required, the proposed filter is not limited to the aerospace domain and has the potential to be deployed in other platforms such as ground robots or mobile phones.

Towards the development of a gas sensor system for monitoring pollutant gases in the low troposphere using small unmanned aerial vehicles

The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.