Relevance feature discovery for text analysis

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition

Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

Feature-domain super-resolution framework for gabor-based face and iris recognition

The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Leading the transformation of learning and praxis in science classrooms

Individual science teachers who have inspired colleagues to transform their classroom praxis have been labelled transformational leaders. As the notion of distributed leadership became more accepted in the educational literature, the focus on the individual teacher-leader shifted to the study of leadership praxis both by individuals (whoever they might be) and by collectives within schools and science classrooms. This review traces the trajectory of leadership research, in the context of learning and teaching science, from an individual focus to a dialectical relationship between individual and collective praxis. The implications of applying an individual-collective perspective to praxis for teachers, students and their designated leaders are discussed.

Agrobacterium-mediated transformation of indica rice cultivars using binary and superbinary vectors

The Agrobacterium-mediated transformation system was extended to two indica cultivars: a widely cultivated breeding line IR-64 and an elite basmati cultivar Karnal Local. Root tips and shoot tips of seedlings, and scutellar-calli derived from mature seeds showed high-efficiency Agrobacterium tumefaciens infection and stable transformation. In addition to the superbinary vector pTOK233 in Agrobacterium strain LBA4404, almost equally high levels of transformation were achieved with a relatively much smaller (13.1 kb) binary vector (pCAMBIA1301) in a supervirulent host strain AGL1. In both cases, as well as in both cultivars, while 60–90% of the infected explants produced calli resistant to the selectable agent hygromycin, 59–75% of such calli tested positive for GUS. A high level (400 μM) of acetosyringone in the preinduction medium for Agrobacterium and a higher level (500 μM) in the cocultivation medium was necessary for an enhancement in transformation frequency of the binary vector to levels comparable to a superbinary. Hygromycin-resistant calli could be produced from all the explants used. Transformants could be regenerated for both cultivars using the superbinary and binary vector, but only for calli of scutellar origin. In addition to the molecular confirmation of hpt and gus gene transfer and transcription, absence of gene sequences outside the transferred DNA (T-DNA) region confirmed absence of any long T-DNA transfer.

Qualitative inquiry as transformation and agency : the black sheep and workplace mobbing

This chapter discusses an action research project into the lived experience of the workplace mobbing phenomenon. The action research methodology is based on the exemplarian model (Coenen & Khonraad, 2003) from the Netherlands Group. This model requires positive outcomes for those immersed in the problem to reduce the adversity of their circumstances. The findings challenge the psychological perspective of the existing bullying literature that tends to focus on individual behaviour. This research, undertaken over a three year period with 212 participants, identified the dysfunctional nature of public sector bureaucracies and the power gained through gossip and rumour as some of the key emergent themes to explain the workplace mobbing problem. In addition, resistance, conscientisation, and agency were identified as the key to transformation for those targeted. The discussion focuses on the crystallisation phase of the exemplarian model where the participants identified themselves as the Black Sheep and adopted the motto that “a black sheep is a biting beast” (Bastard, 1565 or 6-1618, p. 90), reflecting a sense of empowerment, individual agency, and a sense of humour in dealing with the serious yet seemingly absurd reality of their situations. The identity of the Black Sheep was consolidated when the group organised a 2 day conference with over 200 attendees to discuss how best to prevent workplace mobbing. This self-affirming action was a proactive step towards metaphorically “biting back” at the problem. A number of positive outcomes were achieved including the conference with over 200 attending leading to national media coverage across Australia and additional interviews with magazines, newspapers, and radio.

Development of a transformation system for sorghum (Sorghum bicolor L.)

Sorghum (Sorghum bicolor (L.) Moench) is the world’s fifth major cereal crop and holds importance as a construction material, food and fodder source. More recently, the potential of this plant as a biofuel source has been noted. Despite its agronomic importance, the use of sorghum production is being constrained by both biotic and abiotic factors. These challenges could be addressed by the use of genetic engineering strategies to complement conventional breeding techniques. However, sorghum is one of the most recalcitrant crops for genetic modification with the lack of an efficient tissue culture system being amongst the chief reasons. Therefore, the aim of this study was to develop an efficient tissue culture system for establishing regenerable embryogenic cell lines, micropropagation and acclimatisation for Sorghum bicolor and use this to optimise parameters for genetic transformation via Agrobacterium-mediated transformation and microprojectile bombardment. Using five different sorghum cultivars, SA281, 296B, SC49, Wray and Rio, numerous parameters were investigated in an attempt to establish an efficient and reproducible tissue culture and transformation system. Using immature embryos (IEs) as explants, regenerable embryogenic cell lines (ECLs) could only be established from cultivars SA281 and 296B. Large amounts of phenolics were produced from IEs of cultivars, SC49, Wary and Rio, and these compounds severely hindered callus formation and development. Cultivar SA281 also produced phenolics during regeneration. Attempts to suppress the production of these compounds in cultivars SA281 and SC49 using activated charcoal, PVP, ascorbic acid, citric acid and liquid filter paper bridge methods were either ineffective or had a detrimental effect on embryogenic callus formation, development and regeneration. Immature embryos sourced during summer were found to be far more responsive in vitro than those sourced during winter. In an attempt to overcome this problem, IEs were sourced from sorghum grown under summer conditions in either a temperature controlled glasshouse or a growth chamber. However, the performance of these explants was still inferior to that of natural summer-sourced explants. Leaf whorls, mature embryos, shoot tips and leaf primordia were found to be unsuitable as explants for establishing ECLs in sorghum cultivars SA281 and 296B. Using the florets of immature inflorescences (IFs) as explants, however, ECLs were established and regenerated for these cultivars, as well as for cultivar Tx430, using callus induction media, SCIM, and regeneration media, VWRM. The best in vitro responses, from the largest possible sized IFs, were obtained using plants at the FL-2 stage (where the last fully opened leaf was two leaves away from the flag leaf). Immature inflorescences could be stored at 25oC for up to three days without affecting their in vitro responses. Compared to IEs, the IFs were more robust in tissue culture and showed responses which were season and growth condition independent. A micropropagation protocol for sorghum was developed in this study. The optimum plant growth regulator (PGR) combination for the micropropagation of in vitro regenerated plantlets was found to be 1.0 mg/L BAP in combination with 0.5 mg/L NAA. With this protocol, cultivars 296B and SA281 produced an average of 57 and 13 off-shoots per plantlet, respectively. The plantlets were successfully acclimatised and developed into phenotypically normal plants that set seeds. A simplified acclimatisation protocol for in vitro regenerated plantlets was also developed. This protocol involved deflasking in vitro plantlets with at least 2 fully-opened healthy leaves and at least 3 roots longer than 1.5 cm, washing the media from the roots with running tap water, planting in 100 mm pots and placing in plastic trays covered with a clear plastic bag in a plant growth chamber. After seven days, the corners of the plastic cover were opened and the bags were completely removed after 10 days. All plantlets were successfully acclimatised regardless of whether 1:1 perlite:potting mix, potting mix, UC mix or vermiculite were used as potting substrates. Parameters were optimised for Agrobacterium-mediated transformation (AMT) of cultivars SA281, 296B and Tx430. The optimal conditions were the use of Agrobacterium strain LBA4404 at an inoculum density of 0.5 OD600nm, heat shock at 43oC for 3 min, use of the surfactant Pluronic F-68 (0.02% w/v) in the inoculation media with a pH of 5.2 and a 3 day co-cultivation period in dark at 22oC. Using these parameters, high frequencies of transient GFP expression was observed in IEs precultured on callus initiation media for 1-7 days as well as in four weeks old IE- and IF-derived callus. Cultivar SA281 appeared very sensitive to Agrobacterium since all tissue turned necrotic within two weeks post-exposure. For cultivar 296B, GFP expression was observed up to 20 days post co-cultivation but no stably transformed plants were regenerated. Using cultivar Tx430, GFP was expressed for up to 50 days post co-cultivation. Although no stably transformed plants of this cultivar were regenerated, this was most likely due to the use of unsuitable regeneration media. Parameters were optimised for transformation by particle bombardment (PB) of cultivars SA281, 296B and Tx430. The optimal conditions were use of 3-7 days old IEs and 4 weeks old IF callus, 4 hour pre- and post-bombardment osmoticum treatment, use of 0.6 µm gold microparticles, helium pressure of 1500 kPa and target distance of 15 cm. Using these parameters for PB, transient GFP expression was observed for up to 14, 30 and 50 days for cultivars SA281, 296B and Tx430, respectively. Further, the use of PB resulted in less tissue necrosis compared to AMT for the respective cultivars. Despite the presence of transient GFP expression, no stably transformed plants were regenerated. The establishment of regenerable ECLs and the optimization of AMT and PB parameters in this study provides a platform for future efforts to develop an efficient transformation protocol for sorghum. The development of GM sorghum will be an important step towards improving its agronomic properties as well as its exploitation for biofuel production.

Robust facial feature extraction and matching

Automated feature extraction and correspondence determination is an extremely important problem in the face recognition community as it often forms the foundation of the normalisation and database construction phases of many recognition and verification systems. This paper presents a completely automatic feature extraction system based upon a modified volume descriptor. These features form a stable descriptor for faces and are utilised in a reversible jump Markov chain Monte Carlo correspondence algorithm to automatically determine correspondences which exist between faces. The developed system is invariant to changes in pose and occlusion and results indicate that it is also robust to minor face deformations which may be present with variations in expression.

ACE research vignette 020: Entrepreneurial becoming - a self-induced transformation

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. In this vignette, Dr Marcello Tonelli and Associate Professor Carol Dalglish consider the delivery of entrepreneurial education through experiential learning in a developing context.

A rhetorical study of in-flight real estate advertisements as a potential site of ethical transformation in Chinese cities

Real estate markets in Chinese cities are in transition. Advertising for new developments in these markets often reflects changing city aspirations and branding rather than environmental and social experience. This paper investigates real estate marketing as a site of potential ethical transformation of values related to new urban development. It uses Kenneth Burke’s rhetorical analysis as an approach to coding real estate representations from in-flight magazine advertisements as a means of capturing environmental and social viewpoints in China during 2008 - 2009. Both Chinese and foreign participants coded representations into four code modalities. These were based on anthropocentric - non-anthropocentric environmental orientations and nationalistic - universal social orientations. The results suggested that new developments in China are more likely to be understood as based on environmental resource use for continued national economic expansion rather than for a more sustainable world. Emerging patterns in coded representations have opened up the possibility of greater social choices that were however difficult to unambiguously decode from Chinese real estate advertising. From this it is concluded that it may take some time before real estate demand shifts in response to representations of Chinese eco-cities being promoted by Chinese policy makers in the 2000s.