Effect of simulated space environments on piezoelectric vinylidene flouride-based polymers

Piezoelectric polymers based on polyvinylidene flouride (PVDF) are of interest as adaptive materials for large aperture space-based telescopes. In this study, two piezoelectric polymers, PVDF and P(VDF-TrFE), were exposed to conditions simulating the thermal, radiative and atomic oxygen conditions of low Earth orbit. The degradation pathways were governed by a combination of chemical and physical degradation processes with the molecular changes primarily induced via radiative damage, and physical damage from temperature and atomic oxygen exposure, as evident from depoling, loss of orientation and surface erosion. The piezoelectric responsiveness of each polymer was strongly dependent on exposure temperature. Radiation and atomic oxygen exposure caused physical and chemical degradation, which would ultimately cause terminal damage of thin films, but did not adversely affect the piezoelectric properties.

Piezoelectric vinylidene-fluoride based polymers for use in space environments

The effects of simulated low earth orbit conditions on vinylidene-fluoride based thin-film piezoelectrics for use in lightweight, large surface area spacecraft such as telescope mirrors and antennae is presented. The environmental factors considered as having the greatest potential to cause damage are temperature, atomic oxygen and vacuum UV radiation. Using the piezoelectric strain coefficients and bimorph deflection measurements the piezoelectric performance over the temperature range -100 to +150°C was studied. The effects of simultaneous AO/VUV exposure were also examined and films characterized by their piezoelectric, surface, and thermal properties. Two fluorinated piezoelectric polymers, poly(vinylidene fluoride) and poly(vinylidene fluoride-co-trifluoroethylene), were adversely affected at elevated temperatures due to depoling caused by randomization of the dipole orientation, while AO/VUV contributed little to depoling but did cause significant surface erosion and, in the case of P(VDF-TrFE), bulk crosslinking. These results highlight the importance of materials selection for use in space environments.

Dynamics of in vitro polymer degradation of polycaprolactone-based scaffolds : accelerated versus simulated physiological conditions

The increasing use of biodegradable devices in tissue engineering and regenerative medicine means it is essential to study and understand their degradation behaviour. Accelerated degradation systems aim to achieve similar degradation profiles within a shorter period of time, compared with standard conditions. However, these conditions only partially mimic the actual situation, and subsequent analyses and derived mechanisms must be treated with caution and should always be supported by actual long-term degradation data obtained under physiological conditions. Our studies revealed that polycaprolactone (PCL) and PCL-composite scaffolds degrade very differently under these different degradation conditions, whilst still undergoing hydrolysis. Molecular weight and mass loss results differ due to the different degradation pathways followed (surface degradation pathway for accelerated conditions and bulk degradation pathway for simulated physiological conditions). Crystallinity studies revealed similar patterns of recrystallization dynamics, and mechanical data indicated that the scaffolds retained their functional stability, in both instances, over the course of degradation. Ultimately, polymer degradation was shown to be chiefly governed by molecular weight, crystallinity susceptibility to hydrolysis and device architecture considerations whilst maintaining its thermodynamic equilibrium.

Raman spectroscopy of gallium based hydrotalcites of formula Mg6Ga2(CO3)(OH)16•4H2O

Insight into the unique structure of hydrotalcites has been obtained using Raman spectroscopy. Gallium containing hydrotalcites of formula Mg4Ga2(CO3)(OH)12•4H2O (2:1 Ga-HT) to Mg8Ga2(CO3)(OH)20•4H2O (4:1 Ga-HT) have been successfully synthesised and characterized by X-ray diffraction and Raman spectroscopy. The d(003) spacing varied from 7.83 Å for the 2:1 hydrotalcite to 8.15 Å for the 3:1 gallium containing hydrotalcite. Raman spectroscopy complemented with selected infrared data has been used to characterise the synthesised gallium containing hydrotalcites of formula Mg6Ga2(CO3)(OH)16•4H2O. Raman bands observed at around 1046, 1048 and 1058 cm-1 were attributed to the symmetric stretching modes of the (CO32-) units. Multiple ν3 CO32- antisymmetric stretching modes are found at around 1346, 1378, 1446, 1464 and 1494 cm-1. The splitting of this mode indicates the carbonate anion is in a perturbed state. Raman bands observed at 710 and 717 cm-1 assigned to the ν4 (CO32-) modes support the concept of multiple carbonate species in the interlayer.

A risk-based approach to course quality assurance

A decade ago, Queensland University of Technology (QUT) developed an innovative annual Courses Performance Report, but through incremental change, this report became quite labour-intensive. A new risk-based approach to course quality assurance, that consolidates voluminous data in a simple dashboard, responds to the changing context of the higher education sector. This paper will briefly describe QUT’s context and outline the second phase of implementation of this new approach to course quality assurance. The main components are: Individual Course Reports (ICRs), the Consolidated Courses Performance Report (CCPR), Underperforming Courses Status Update and the Strategic Faculty Courses Update (SFCU). These components together form a parsimonious and strategic annual cycle of reporting and place QUT in a positive position to respond to future sector change

Cascading appearance-based features for visual voice activity detection

The detection of voice activity is a challenging problem, especially when the level of acoustic noise is high. Most current approaches only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to overcome this is to use the visual modality. The current state-of-the-art visual feature extraction technique is one that uses a cascade of visual features (i.e. 2D-DCT, feature mean normalisation, interstep LDA). In this paper, we investigate the effectiveness of this technique for the task of visual voice activity detection (VAD), and analyse each stage of the cascade and quantify the relative improvement in performance gained by each successive stage. The experiments were conducted on the CUAVE database and our results highlight that the dynamics of the visual modality can be used to good effect to improve visual voice activity detection performance.

Temporal-based support vector machines for facial expression recognition

When classifying a signal, ideally we want our classifier to trigger a large response when it encounters a positive example and have little to no response for all other examples. Unfortunately in practice this does not occur with responses fluctuating, often causing false alarms. There exists a myriad of reasons why this is the case, most notably not incorporating the dynamics of the signal into the classification. In facial expression recognition, this has been highlighted as one major research question. In this paper we present a novel technique which incorporates the dynamics of the signal which can produce a strong response when the peak expression is found and essentially suppresses all other responses as much as possible. We conducted preliminary experiments on the extended Cohn-Kanade (CK+) database which shows its benefits. The ability to automatically and accurately recognize facial expressions of drivers is highly relevant to the automobile. For example, the early recognition of “surprise” could indicate that an accident is about to occur; and various safeguards could immediately be deployed to avoid or minimize injury and damage. In this paper, we conducted initial experiments on the extended Cohn-Kanade (CK+) database which shows its benefits.

Improved correlation-based modal strain energy method for global damage detection of truss bridge structures

The previous investigations have shown that the modal strain energy correlation method, MSEC, could successfully identify the damage of truss bridge structures. However, it has to incorporate the sensitivity matrix to estimate damage and is not reliable in certain damage detection cases. This paper presents an improved MSEC method where the prediction of modal strain energy change vector is differently obtained by running the eigensolutions on-line in optimisation iterations. The particular trail damage treatment group maximising the fitness function close to unity is identified as the detected damage location. This improvement is then compared with the original MSEC method along with other typical correlation-based methods on the finite element model of a simple truss bridge. The contributions to damage detection accuracy of each considered mode is also weighed and discussed. The iterative searching process is operated by using genetic algorithm. The results demonstrate that the improved MSEC method suffices the demand in detecting the damage of truss bridge structures, even when noised measurement is considered.

Cluster-based Intrusion Detection (CBID) architecture for mobile ad hoc networks

The ad hoc networks are vulnerable to attacks due to distributed nature and lack of infrastructure. Intrusion detection systems (IDS) provide audit and monitoring capabilities that offer the local security to a node and help to perceive the specific trust level of other nodes. The clustering protocols can be taken as an additional advantage in these processing constrained networks to collaboratively detect intrusions with less power usage and minimal overhead. Existing clustering protocols are not suitable for intrusion detection purposes, because they are linked with the routes. The route establishment and route renewal affects the clusters and as a consequence, the processing and traffic overhead increases due to instability of clusters. The ad hoc networks are battery and power constraint, and therefore a trusted monitoring node should be available to detect and respond against intrusions in time. This can be achieved only if the clusters are stable for a long period of time. If the clusters are regularly changed due to routes, the intrusion detection will not prove to be effective. Therefore, a generalized clustering algorithm has been proposed that can run on top of any routing protocol and can monitor the intrusions constantly irrespective of the routes. The proposed simplified clustering scheme has been used to detect intrusions, resulting in high detection rates and low processing and memory overhead irrespective of the routes, connections, traffic types and mobility of nodes in the network. Clustering is also useful to detect intrusions collaboratively since an individual node can neither detect the malicious node alone nor it can take action against that node on its own.

Public awareness of “green” and “energy efficient” residential property : an empirical survey based on data from New Zealand

Purpose – The purpose of this paper is to examine the buyer awareness and acceptance of environmental and energy efficiency measures in the New Zealand residential property markets. This study aims to provide a greater understanding of consumer behaviour in the residential property market in relation to green housing issues ---------- Design/methodology/approach – The paper is based on an extensive survey of Christchurch real estate offices and was designed to gather data on the factors that were considered important by buyers in the residential property market. The survey was designed to allow these factors to be analysed on a socio-economic basis and to compare buyer behaviour based on property values. ---------- Findings – The results show that regardless of income levels, buyers still consider that the most important factor in the house purchase decision is the location of the property and price. Although the awareness of green housing issues and energy efficiency in housing is growing in the residential property market, it is only a major consideration for young and older buyers in the high income brackets and is only of some importance for all other buyer sectors of the residential property market. Many of the voluntary measures introduced by Governments to improve the energy efficiency of residential housing are still not considered important by buyers, indicating that a more mandatory approach may have to be undertaken to improve energy efficiency in the established housing market, as these measures are not valued by the buyer. ---------- Originality/value – The paper confirms the variations in real estate buyer behaviour across the full range of residential property markets and the acceptance and awareness of green housing issues and measures. These results would be applicable to most established and transparent residential property markets.

A penalty-based genetic algorithm for the composite SaaS placement problem in the cloud

Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications’ placement methods in data centres are not concerned with the placement of the component’s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider’s servers. Experimental results demonstrate the feasibility and the scalability of the GA.

TCP-DR an effective protocol for infrastructure based wireless networks

TCP is a dominant protocol for consistent communication over the internet. It provides flow, congestion and error control mechanisms while using wired reliable networks. Its congestion control mechanism is not suitable for wireless links where data corruption and its lost rate are higher. The physical links are transparent from TCP that takes packet losses due to congestion only and initiates congestion handling mechanisms by reducing transmission speed. This results in wasting already limited available bandwidth on the wireless links. Therefore, there is no use to carry out research on increasing bandwidth of the wireless links until the available bandwidth is not optimally utilized. This paper proposed a hybrid scheme called TCP Detection and Recovery (TCP-DR) to distinguish congestion, corruption and mobility related losses and then instructs the data sending host to take appropriate action. Therefore, the link utilization is optimal while losses are either due to high bit error rate or mobility.

Typical accuracy and quality control of a process for creating CT-Based virtual bone models

A pragmatic method for assessing the accuracy and precision of a given processing pipeline required for converting computed tomography (CT) image data of bones into representative three dimensional (3D) models of bone shapes is proposed. The method is based on coprocessing a control object with known geometry which enables the assessment of the quality of resulting 3D models. At three stages of the conversion process, distance measurements were obtained and statistically evaluated. For this study, 31 CT datasets were processed. The final 3D model of the control object contained an average deviation from reference values of −1.07±0.52 mm standard deviation (SD) for edge distances and −0.647±0.43 mm SD for parallel side distances of the control object. Coprocessing a reference object enables the assessment of the accuracy and precision of a given processing pipeline for creating CTbased 3D bone models and is suitable for detecting most systematic or human errors when processing a CT-scan. Typical errors have about the same size as the scan resolution.

Spherical image-based visual servo and structure estimation

This paper presents a formulation of image-based visual servoing (IBVS) for a spherical camera where coordinates are parameterized in terms of colatitude and longitude: IBVSSph. The image Jacobian is derived and simulation results are presented for canonical rotational, translational as well as general motion. Problems with large rotations that affect the planar perspective form of IBVS are not present on the sphere, whereas the desirable robustness properties of IBVS are shown to be retained. We also describe a structure from motion (SfM) system based on camera-centric spherical coordinates and show how a recursive estimator can be used to recover structure. The spherical formulations for IBVS and SfM are particularly suitable for platforms, such as aerial and underwater robots, that move in SE(3).