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.

Development of distributed fuzzy systems with a runtime-adaptable mobile components framework

A distributed fuzzy system is a real-time fuzzy system in which the input, output and computation may be located on different networked computing nodes. The ability for a distributed software application, such as a distributed fuzzy system, to adapt to changes in the computing network at runtime can provide real-time performance improvement and fault-tolerance. This paper introduces an Adaptable Mobile Component Framework (AMCF) that provides a distributed dataflow-based platform with a fine-grained level of runtime reconfigurability. The execution location of small fragments (possibly as little as few machine-code instructions) of an AMCF application can be moved between different computing nodes at runtime. A case study is included that demonstrates the applicability of the AMCF to a distributed fuzzy system scenario involving multiple physical agents (such as autonomous robots). Using the AMCF, fuzzy systems can now be developed such that they can be distributed automatically across multiple computing nodes and are adaptable to runtime changes in the networked computing environment. This provides the opportunity to improve the performance of fuzzy systems deployed in scenarios where the computing environment is resource-constrained and volatile, such as multiple autonomous robots, smart environments and sensor networks.

Gas sensing characteristics of Fe-doped tungsten oxide thin films

This study reports on the gas sensing characteristics of Fe-doped (10 at.%) tungsten oxide thin films of various thicknesses (100–500 nm) prepared by electron beam evaporation. The performance of these films in sensing four gases (H2, NH3, NO2 and N2O) in the concentration range 2–10,000 ppm at operating temperatures of 150–280 °C has been investigated. The results are compared with the sensing performance of a pure WO3 film of thickness 300 nm produced by the same method. Doping of the tungsten oxide film with 10 at.% Fe significantly increases the base conductance of the pure film but decreases the gas sensing response. The maximum response measured in this experiment, represented by the relative change in resistance when exposed to a gas, was ΔR/R = 375. This was the response amplitude measured in the presence of 5 ppm NO2 at an operating temperature of 250 °C using a 400 nm thick WO3:Fe film. This value is slightly lower than the corresponding result obtained using the pure WO3 film (ΔR/R = 450). However it was noted that the WO3:Fe sensor is highly selective to NO2, exhibiting a much higher response to NO2 compared to the other gases. The high performance of the sensors to NO2 was attributed to the small grain size and high porosity of the films, which was obtained through e-beam evaporation and post-deposition heat treatment of the films at 300 °C for 1 h in air.

Spectrum sensing using two-stage detection to compensate for reduced primary user duty cycle

Spectrum sensing is considered to be one of the most important tasks in cognitive radio. One of the common assumption among current spectrum sensing detectors is the full presence or complete absence of the primary user within the sensing period. In reality, there are many situations where the primary user signal only occupies a portion of the observed signal and the assumption of primary user duty cycle not necessarily fulfilled. In this paper we show that the true detection performance can degrade from the assumed achievable values when the observed primary user exhibits a certain duty cycle. Therefore, a two-stage detection method incorporating primary user duty cycle that enhances the detection performance is proposed. The proposed detector can improve the probability of detection under low duty cycle at the expense of a small decrease in performance at high duty cycle.

Unusual scene detection using distributed behaviour model and sparse representation

The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

Managing open incremental process innovation : absorptive capacity and distributed learning

In this conceptual article, we extend earlier work on Open Innovation and Absorptive Capacity. We suggest that the literature on Absorptive Capacity does not place sufficient emphasis on distributed knowledge and learning or on the application of innovative knowledge. To accomplish physical transformations, organisations need specific Innovative Capacities that extend beyond knowledge management. Accessive Capacity is the ability to collect, sort and analyse knowledge from both internal and external sources. Adaptive Capacity is needed to ensure that new pieces of equipment are suitable for the organisation's own purposes even though they may have been originally developed for other uses. Integrative Capacity makes it possible for a new or modified piece of equipment to be fitted into an existing production process with a minimum of inessential and expensive adjustment elsewhere in the process. These Innovative Capacities are controlled and coordinated by Innovative Management Capacity, a higher-order dynamic capability.

Intensity pulsations in distributed feedback Yb:Phosphate waveguide lasers

The intensity pulsations of a cw 1030 nm Yb:Phosphate monolithic waveguide laser with distributed feedback are described. We show that the pulsations could result from the coupling of the two orthogonal polarization modes through the two photon process of cooperative luminescence. The predictions of the presented theoretical model agree well with the observed behaviour.

Excess power circulation in distribution networks containing distributed energy resources

The presence of large number of single-phase distributed energy resources (DERs) can cause severe power quality problems in distribution networks. The DERs can be installed in random locations. This may cause the generation in a particular phase exceeds the load demand in that phase. Therefore the excess power in that phase will be fed back to the transmission network. To avoid this problem, the paper proposes the use of distribution static compensator (DSTATCOM) that needs to be connected at the first bus following a substation. When operated properly, the DSTATCOM can facilitate a set of balanced current flow from the substation, even when excess power is generated by DERs. The proposals are validated through extensive digital computer simulation studies using PSCAD and MATLAB.

Thermally evaporated tungsten oxide (WO3) thin films for gas sensing applications

In this thesis, the author proposed and developed gas sensors made of nanostructured WO3 thin film by a thermal evaporation technique. This technique gives control over film thickness, grain size and purity. The device fabrication, nanostructured material synthesis, characterization and gas sensing performance have been undertaken. Three different types of nanostructured thin films, namely, pure WO3 thin films, iron-doped WO3 thin films by co-evaporation and Fe-implanted WO3 thin films have been synthesized. All the thin films have a film thickness of 300 nm. The physical, chemical and electronic properties of these films have been optimized by annealing heat treatment at 300ºC and 400ºC for 2 hours in air. Various analytical techniques were employed to characterize these films. Atomic Force Microscopy and Transmission Electron Microscopy revealed a very small grain size of the order 5-10 nm in as-deposited WO3 films, and annealing at 300ºC or 400ºC did not result in any significant change in grain size. X-ray diffraction (XRD) analysis revealed a highly amorphous structure of as-deposited films. Annealing at 300ºC for 2 hours in air did not improve crystallinity in these films. However, annealing at 400ºC for 2 hours in air significantly improved the crystallinity in pure and iron-doped WO3 thin films, whereas it only slightly improved the crystallinity of iron-implanted WO3 thin film as a result of implantation. Rutherford backscattered spectroscopy revealed an iron content of 0.5 at.% and 5.5 at.% in iron-doped and iron-implanted WO3 thin films, respectively. The RBS results have been confirmed using energy dispersive x-ray spectroscopy (EDX) during analysis of the films using transmission electron microscopy (TEM). X-ray photoelectron spectroscopy (XPS) revealed significant lowering of W 4f7/2 binding energy in all films annealed at 400ºC as compared with the as-deposited and 300ºC annealed films. Lowering of W 4f7/2 is due to increase in number of oxygen vacancies in the films and is considered highly beneficial for gas sensing. Raman analysis revealed that 400ºC annealed films except the iron-implanted film are highly crystalline with significant number of O-W-O bonds, which was consistent with the XRD results. Additionally, XRD, XPS and Raman analyses showed no evidence of secondary peaks corresponding to compounds of iron due to iron doping or implantation. This provided an understanding that iron was incorporated in the host WO3 matrix rather than as a separate dispersed compound or as catalyst on the surface. WO3 thin film based gas sensors are known to operate efficiently in the temperature range 200ºC-500 ºC. In the present study, by optimizing the physical, chemical and electronic properties through heat treatment and doping, an optimum response to H2, ethanol and CO has been achieved at a low operating temperature of 150ºC. Pure WO3 thin film annealed at 400ºC showed the highest sensitivity towards H2 at 150ºC due to its very small grain size and porosity, coupled with high number of oxygen vacancies, whereas Fe-doped WO3 film annealed at 400ºC showed the highest sensitivity to ethanol at an operating temperature of 150ºC due to its crystallinity, increased number of oxygen vacancies and higher degree of crystal distortions attributed to Fe addition. Pure WO3 films are known to be insensitive to CO, but iron-doped WO3 thin film annealed at 300ºC and 400ºC showed an optimum response to CO at an operating temperature of 150ºC. This result is attributed to lattice distortions produced in WO3 host matrix as a result of iron incorporation as substitutional impurity. However, iron-implanted WO3 thin films did not show any promising response towards the tested gases as the film structure has been damaged due to implantation, and annealing at 300ºC or 400ºC was not sufficient to induce crystallinity in these films. This study has demonstrated enhanced sensing properties of WO3 thin film sensors towards CO at lower operating temperature, which was achieved by optimizing the physical, chemical and electronic properties of the WO3 film through Fe doping and annealing. This study can be further extended to systematically investigate the effects of different Fe concentrations (0.5 at.% to 10 at.%) on the sensing performance of WO3 thin film gas sensors towards CO.

Characterisation of multi wall carbon nanotube–polymer composites for strain sensing applications

Carbon nanotubes (CNTs) have excellent electrical, mechanical and electromechanical properties. When CNTs are incorporated into polymers, electrically conductive composites with high electrical conductivity at very low CNT content (often below 1% wt CNT) result. Due to the change in electrical properties under mechanical load, carbon nanotube/polymer composites have attracted significant research interest especially due to their potential for application in in-situ monitoring of stress distribution and active control of strain sensing in composite structures or as strain sensors. To sucessfully develop novel devices for such applications, some of the major challenges that need to be overcome include; in-depth understanding of structure-electrical conductivity relationships, response of the composites under changing environmental conditions and piezoresistivity of different types of carbon nanotube/polymer sensing devices. In this thesis, direct current (DC) and alternating current (AC) conductivity of CNT-epoxy composites was investigated. Details of microstructure obtained by scanning electron microscopy were used to link observed electrical properties with structure using equivalent circuit modeling. The role of polymer coatings on macro and micro level electrical conductivity was investigated using atomic force microscopy. Thermal analysis and Raman spectroscopy were used to evaluate the heat flow and deformation of carbon nanotubes embedded in the epoxy, respectively, and related to temperature induced resistivity changes. A comparative assessment of piezoresistivity was conducted using randomly mixed carbon nanotube/epoxy composites, and new concept epoxy- and polyurethane-coated carbon nanotube films. The results indicate that equivalent circuit modelling is a reliable technique for estimating values of the resistance and capacitive components in linear, low aspect ratio-epoxy composites. Using this approach, the dominant role of tunneling resistance in determining the electrical conductivity was confirmed, a result further verified using conductive-atomic force microscopy analysis. Randomly mixed CNT-epoxy composites were found to be highly sensitive to mechanical strain and temperature variation compared to polymer-coated CNT films. In the vicinity of the glass transition temperature, the CNT-epoxy composites exhibited pronounced resistivity peaks. Thermal and Raman spectroscopy analyses indicated that this phenomenon can be attributed to physical aging of the epoxy matrix phase and structural rearrangement of the conductive network induced by matrix expansion. The resistivity of polymercoated CNT composites was mainly dominated by the intrinsic resistivity of CNTs and the CNT junctions, and their linear, weakly temperature sensitive response can be described by a modified Luttinger liquid model. Piezoresistivity of the polymer coated sensors was dominated by break up of the conducting carbon nanotube network and the consequent degradation of nanotube-nanotube contacts while that of the randomly mixed CNT-epoxy composites was determined by tunnelling resistance between neighbouring CNTs. This thesis has demonstrated that it is possible to use microstructure information to develop equivalent circuit models that are capable of representing the electrical conductivity of CNT/epoxy composites accurately. New designs of carbon nanotube based sensing devices, utilising carbon nanotube films as the key functional element, can be used to overcome the high temperature sensitivity of randomly mixed CNT/polymer composites without compromising on desired high strain sensitivity. This concept can be extended to develop large area intelligent CNT based coatings and targeted weak-point specific strain sensors for use in structural health monitoring.

Spectrum sensing, detection and optimisation in cognitive radio for non-stationary primary user signals

Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

Contextualizing a university-school STEM education collaboration : distributed and self-activated leadership for project outcomes

Implementing educational reform requires partnerships, and university-school collaborations in the form of investigative and experimental projects can aim to determine the practicalities of reform. However, there are funded projects that do not achieve intended outcomes. In the context of a new reform initiative in education, namely, science, technology, engineering and mathematics (STEM) education, this article explores the management of a government-funded project. In a university school partnership for STEM education, how can leadership be distributed for achieving project outcomes? Participants included university personnel from different STEM areas, school teachers and school executives. Data collected included observations, interviews, resource materials, and video and photographic images. Findings indicated that leadership roles were distributed and selfactivated by project partners according to their areas of expertise and proximal activeness to the project phases, that is: (1) establishing partnerships; (2) planning and collaboration; (3) project implementation; and (4) project evaluation and further initiatives. Leadership can be intentional and unintentional within project phases, and understanding how leadership can be distributed and selfactivated more purposefully may aid in generating more expedient project outcomes.