Piezoelectric PVDF materials performance and operation limits in space environments

Piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes. Dimensional adjustments of adaptive polymer films are achieved via charge deposition and require a detailed understanding of the piezoelectric material responses which are expected to suffer due to strong vacuum UV, gamma, X-ray, energetic particles and atomic oxygen under low earth orbit exposure conditions. The degradation of PVDF and its copolymers under various stress environments has been investigated. Initial radiation aging studies using gamma- and e-beam irradiation have shown complex material changes with significant crosslinking, lowered melting and Curie points (where observable), effects on crystallinity, but little influence on overall piezoelectric properties. Surprisingly, complex aging processes have also been observed in elevated temperature environments with annealing phenomena and cyclic stresses resulting in thermal depoling of domains. Overall materials performance appears to be governed by a combination of chemical and physical degradation processes. Molecular changes are primarily induced via radiative damage, and physical damage from temperature and AO exposure is evident as depoling and surface erosion. Major differences between individual copolymers have been observed providing feedback on material selection strategies.

Redland Youth Space development: evaluation report

This report provides an evaluation of the Capalaba Youth Space.The evaluation included elements of process and impact evaluation and used a participatory action research approach informed by engagement processes, focus groups, a community survey, interviews and secondary analysis of existing data.

Non-redundant sequential association rule mining based on closed sequential patterns

In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or relationships within the data. Sequential association rule mining is one of the possible methods used to analyse this data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules. Because of the complexity and temporal ordered characteristics of sequential data, current research on sequential association rule mining is limited. Although several sequential association rule prediction models using either sequence constraints or temporal constraints have been proposed, none of them considered the redundancy problem in rule mining. The main contribution of this research is to propose a non-redundant association rule mining method based on closed frequent sequences and minimal sequential generators. We also give a definition for the non-redundant sequential rules, which are sequential rules with minimal antecedents but maximal consequents. A new algorithm called CSGM (closed sequential and generator mining) for generating closed sequences and minimal sequential generators is also introduced. A further experiment has been done to compare the performance of generating non-redundant sequential rules and full sequential rules, meanwhile, performance evaluation of our CSGM and other closed sequential pattern mining or generator mining algorithms has also been conducted. We also use generated non-redundant sequential rules for query expansion in order to improve recommendations for infrequently purchased products.

A suspicious behaviour detection using a context space model for smart surveillance systems

Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

Enriching XML documents clustering by using concise structure and content

With the growing number of XML documents on theWeb it becomes essential to effectively organise these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. However, many issues arise in discovering knowledge from these types of semi-structured documents due to their heterogeneity and structural irregularity. Most of the existing research on clustering techniques focuses only on one feature of the XML documents, this being either their structure or their content due to scalability and complexity problems. The knowledge gained in the form of clusters based on the structure or the content is not suitable for reallife datasets. It therefore becomes essential to include both the structure and content of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both these kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. The overall objective of this thesis is to address these issues by: (1) proposing methods to utilise frequent pattern mining techniques to reduce the dimension; (2) developing models to effectively combine the structure and content of XML documents; and (3) utilising the proposed models in clustering. This research first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. A clustering framework with two types of models, implicit and explicit, is developed. The implicit model uses a Vector Space Model (VSM) to combine the structure and the content information. The explicit model uses a higher order model, namely a 3- order Tensor Space Model (TSM), to explicitly combine the structure and the content information. This thesis also proposes a novel incremental technique to decompose largesized tensor models to utilise the decomposed solution for clustering the XML documents. The proposed framework and its components were extensively evaluated on several real-life datasets exhibiting extreme characteristics to understand the usefulness of the proposed framework in real-life situations. Additionally, this research evaluates the outcome of the clustering process on the collection selection problem in the information retrieval on the Wikipedia dataset. The experimental results demonstrate that the proposed frequent pattern mining and clustering methods outperform the related state-of-the-art approaches. In particular, the proposed framework of utilising frequent structures for constraining the content shows an improvement in accuracy over content-only and structure-only clustering results. The scalability evaluation experiments conducted on large scaled datasets clearly show the strengths of the proposed methods over state-of-the-art methods. In particular, this thesis work contributes to effectively combining the structure and the content of XML documents for clustering, in order to improve the accuracy of the clustering solution. In addition, it also contributes by addressing the research gaps in frequent pattern mining to generate efficient and concise frequent subtrees with various node relationships that could be used in clustering.

Redland city youth and public space report : provisions for good practice

Written for Redland City Council in collaboration with the Capalaba Stakeholders Group. The provisions detailed in this report constitute a protocol agreement developed through the Capalaba Stakeholders Group between 2009 and 2011 around young people and public spaces in Redland City, Queensland. These provisions include agreed principles, standards and responses to tensions or unacceptable behaviour, how various tensions and problems can be resolved in constructive ways and how people, including young people can work together to make a public or community accessed space safe and accessible. It is based on the recognition that young people are part of the community and that strategies to resolve tensions that arise should be inclusive and employ a mixed methods approach.

Analytical and numerical solutions of the space and time fractional bloch-torrey equation

Fractional order dynamics in physics, particularly when applied to diffusion, leads to an extension of the concept of Brown-ian motion through a generalization of the Gaussian probability function to what is termed anomalous diffusion. As MRI is applied with increasing temporal and spatial resolution, the spin dynamics are being examined more closely; such examinations extend our knowledge of biological materials through a detailed analysis of relaxation time distribution and water diffusion heterogeneity. Here the dynamic models become more complex as they attempt to correlate new data with a multiplicity of tissue compartments where processes are often anisotropic. Anomalous diffusion in the human brain using fractional order calculus has been investigated. Recently, a new diffusion model was proposed by solving the Bloch-Torrey equation using fractional order calculus with respect to time and space (see R.L. Magin et al., J. Magnetic Resonance, 190 (2008) 255-270). However effective numerical methods and supporting error analyses for the fractional Bloch-Torrey equation are still limited. In this paper, the space and time fractional Bloch-Torrey equation (ST-FBTE) is considered. The time and space derivatives in the ST-FBTE are replaced by the Caputo and the sequential Riesz fractional derivatives, respectively. Firstly, we derive an analytical solution for the ST-FBTE with initial and boundary conditions on a finite domain. Secondly, we propose an implicit numerical method (INM) for the ST-FBTE, and the stability and convergence of the INM are investigated. We prove that the implicit numerical method for the ST-FBTE is unconditionally stable and convergent. Finally, we present some numerical results that support our theoretical analysis.

Their space, my space, our space? Report of the 2009 Redland City Council Youth and Public Space Survey

This report analyses data collected through the Redland City Council’s Young People and Public Space Survey of 2148 high school students aged 12-19. The survey conducted in 2009 explored their sense of safety and experiences in public spaces across the City, and views on what Council could do to improve these. It is apparent they base their assessment of a space as ‘public’ on their ‘use’ of a space alone or with friends, and where strangers may be present, rather than on a type of ownership of a space (public/ private). The findings of the survey are summarised according to the themes of safety, community attitudes towards young people being in public spaces, young people and authorities, young people’s views of what is needed, and understanding different young people’s experiences of public space.

End-expiratory lung volume recovers more slowly after closed endotracheal suctioning than after open suctioning : a randomized crossover study

Purpose Endotracheal suctioning causes significant lung derecruitment. Closed suction (CS) minimizes lung volume loss during suction, and therefore, volumes are presumed to recover more quickly postsuctioning. Conflicting evidence exists regarding this. We examined the effects of open suction (OS) and CS on lung volume loss during suctioning, and recovery of end-expiratory lung volume (EELV) up to 30 minutes postsuction. Material and Methods Randomized crossover study examining 20 patients postcardiac surgery. CS and OS were performed in random order, 30 minutes apart. Lung impedance was measured during suction, and end-expiratory lung impedance was measured at baseline and postsuctioning using electrical impedance tomography. Oximetry, partial pressure of oxygen in the alveoli/fraction of inspired oxygen ratio and compliance were collected. Results Reductions in lung impedance during suctioning were less for CS than for OS (mean difference, − 905 impedance units; 95% confidence interval [CI], − 1234 to –587; P < .001). However, at all points postsuctioning, EELV recovered more slowly after CS than after OS. There were no statistically significant differences in the other respiratory parameters. Conclusions Closed suctioning minimized lung volume loss during suctioning but, counterintuitively, resulted in slower recovery of EELV postsuction compared with OS. Therefore, the use of CS cannot be assumed to be protective of lung volumes postsuctioning. Consideration should be given to restoring EELV after either suction method via a recruitment maneuver.

Slotted distributed space-time coding

Distributed space-time coding (DSTC) exploits the concept of cooperative diversity and space-time coding to offer a powerful bandwidth efficient solution with improved diversity. In this paper, we evaluate the performance of DSTC with slotted amplify-and-forward protocol (SAF). Relay nodes between the source and the destination nodes are grouped into two relay clusters based on their respective locations and these relay clusters cooperate to transmit the space-time coded signal to the destination node in different time frames. We further extend the proposed Slotted-DSTC to Slotted DSTC with redundant code (Slotted-DSTC-R) protocol where the relay nodes in both relay clusters forward the same space-time coded signal to the destination node to achieve a higher diversity order.

Classification of the Johnson Space Center stratospheric dust collection

A review of 291 catalogued particles on the bases of particle size, shape, bulk chemistry, and texture is used to establish a reliable taxonomy. Extraterrestrial materials occur in three defined categories: spheres, aggregates and fragments. Approximately 76% of aggregates are of probable extraterrestrial origin, whereas spheres contain the smallest amount of extraterrestrial material (approx 43%). -B.M.

Progress toward a cosmic dust collection facility on space station

Scientific and programmatic progress toward the development of a cosmic dust collection facility (CDCF) for the proposed space station is documented. Topics addressed include: trajectory sensor concepts; trajectory accuracy and orbital evolution; CDCF pointing direction; development of capture devices; analytical techniques; programmatic progress; flight opportunities; and facility development.

Stratospheric dust collections : valuable resources for space and atmospheric scientists

Collections of solid particles from the Earths' stratosphere have been a significant part of atmospheric research programs since 1965 [1], but it has only been in the past decade that space-related disciplines have provided the impetus for a continued interest in these collections. Early research on specific particle types collected from the stratosphere established that interplanetary dust particles (IDP's) can be collected efficiently and in reasonable abundance using flat-plate collectors [2-4]. The tenacity of Brownlee and co-workers in this subfield of cosmochemistry has led to the establishment of a successful IDP collection and analysis program (using flat-plate collectors on high-flying aircraft) based on samples available for distribution from Johnson Space Center [5]. Other stratospheric collections are made, but the program at JSC offers a unique opportunity to study well-documented, individual particles (or groups of particles) from a wide variety of sources [6]. The nature of the collection and curation process, as well as the timeliness of some sampling periods [7], ensures that all data obtained from stratospheric particles is a valuable resource for scientists from a wide range of disciplines. A few examples of the uses of these stratospheric dust collections are outlined below.