Whatever it takes : an exploration of writing tools and strategies for completing a novel

This thesis consists of a novel written with the express purpose of exploring what practices and strategies are most useful in writing novel-length fiction as well as an exegesis which discusses the process. By its very nature, an undergraduate degree in Creative Writing is broad and general in approach. The Creative Writing undergraduate is being trained to manage many and varying writing tasks but none of them larger than can be readily marked and assessed in class quantities. This does not prepare the writing graduate for the gargantuan task of managing a project as large as a single title novel which can be up to 100,000 words and often is more. This study explores the question of what writing tools and practices best equip an emerging writer to begin, write and manage a long narrative within a deadline.

Exploiting multiple feature sets in data-driven impostor dataset selection for speaker verification

This study assesses the recently proposed data-driven background dataset refinement technique for speaker verification using alternate SVM feature sets to the GMM supervector features for which it was originally designed. The performance improvements brought about in each trialled SVM configuration demonstrate the versatility of background dataset refinement. This work also extends on the originally proposed technique to exploit support vector coefficients as an impostor suitability metric in the data-driven selection process. Using support vector coefficients improved the performance of the refined datasets in the evaluation of unseen data. Further, attempts are made to exploit the differences in impostor example suitability measures from varying features spaces to provide added robustness.

Darjeeling, a feature-rich VM for the resource poor

The programming and retasking of sensor nodes could benefit greatly from the use of a virtual machine (VM) since byte code is compact, can be loaded on demand, and interpreted on a heterogeneous set of devices. The challenge is to ensure good programming tools and a small footprint for the virtual machine to meet the memory constraints of typical WSN platforms. To this end we propose Darjeeling, a virtual machine modelled after the Java VM and capable of executing a substantial subset of the Java language, but designed specifically to run on 8- and 16-bit microcontrollers with 2 - 10 KB of RAM. The Darjeeling VM uses a 16- rather than a 32-bit architecture, which is more efficient on the targeted platforms. Darjeeling features a novel memory organisation with strict separation of reference from non-reference types which eliminates the need for run-time type inspection in the underlying compacting garbage collector. Darjeeling uses a linked stack model that provides light-weight threads, and supports synchronisation. The VM has been implemented on three different platforms and was evaluated with micro benchmarks and a real-world application. The latter includes a pure Java implementation of the collection tree routing protocol conveniently programmed as a set of cooperating threads, and a reimplementation of an existing environmental monitoring application. The results show that Darjeeling is a viable solution for deploying large-scale heterogeneous sensor networks. Copyright 2009 ACM.

Wide-angle visual feature matching for outdoor localization

Wide-angle images exhibit significant distortion for which existing scale-space detectors such as the scale-invariant feature transform (SIFT) are inappropriate. The required scale-space images for feature detection are correctly obtained through the convolution of the image, mapped to the sphere, with the spherical Gaussian. A new visual key-point detector, based on this principle, is developed and several computational approaches to the convolution are investigated in both the spatial and frequency domain. In particular, a close approximation is developed that has comparable computation time to conventional SIFT but with improved matching performance. Results are presented for monocular wide-angle outdoor image sequences obtained using fisheye and equiangular catadioptric cameras. We evaluate the overall matching performance (recall versus 1-precision) of these methods compared to conventional SIFT. We also demonstrate the use of the technique for variable frame-rate visual odometry and its application to place recognition.

The Machine Vision Toolbox : A MATLAB Toolbox for vision and vision-based control

The article described an open-source toolbox for machine vision called Machine Vision Toolbox (MVT). MVT includes more than 60 functions including image file reading and writing, acquisition, display, filtering, blob, point and line feature extraction, mathematical morphology, homographies, visual Jacobians, camera calibration, and color space conversion. MVT can be used for research into machine vision but is also versatile enough to be usable for real-time work and even control. MVT, combined with MATLAB and a model workstation computer, is a useful and convenient environment for the investigation of machine vision algorithms. The article illustrated the use of a subset of toolbox functions for some typical problems and described MVT operations including the simulation of a complete image-based visual servo system.

Polydipsia : a feature of peritoneal dialysis

Background Some dialysis patients fail to comply with their fluid restriction causing problems due to volume overload. These patients sometimes blame excessive thirst. There has been little work in this area and no work documenting polydipsia among peritoneal dialysis (PD) patients. Methods We measured motivation to drink and fluid consumption in 46 haemodialysis patients (HD), 39 PD patients and 42 healthy controls (HC) using a modified palmtop computer to collect visual analogue scores at hourly intervals. Results Mean thirst scores were markedly depressed on the dialysis day (day 1) for HD (P<0.0001). The profile for day 2 was similar to that of HC. PD generated consistently higher scores than HD day 1 and HC (P = 0.01 vs. HC and P<0.0001 vs HD day 1). Reported mean daily water consumption was similar for HD and PD with both significantly less than HC (P<0.001 for both). However, measured fluid losses were similar for PD and HC whilst HD were lower (P<0.001 for both) suggesting that the PD group may have underestimated their fluid intake. Conclusion Our results indicate that HD causes a protracted period of reduced thirst but that the population's thirst perception is similar to HC on the interdialytic day despite a reduced fluid intake. In contrast, the PD group recorded high thirst scores throughout the day and were apparently less compliant with their fluid restriction. This is potentially important because the volume status of PD patients influences their survival.

Working on the art of writing

In this short Case story Bronwyn Fredericks shares some of her tips on writing and about the craft of writing. This Case story is contained within the publication titled 'Researching Indigenous Health: A Practical Guide for Researchers', by Alison Laycock, Diane Walker, Nea Harrison and Jenny Brands and published by The Lowitja Institute(pp.266-267).

Merging fact with fiction : a study of year 9 students' developing scientific literacy through the writing of hybridised scientific narratives on a socioscientific issue

International assessments of student science achievement, and growing evidence of students' waning interest in school science, have ensured that the development of scientific literacy continues to remain an important educational priority. Furthermore, researchers have called for teaching and learning strategies to engage students in the learning of science, particularly in the middle years of schooling. This study extends previous national and international research that has established a link between writing and learning science. Specifically, it investigates the learning experiences of eight intact Year 9 science classes as they engage in the writing of short stories that merge scientific and narrative genres (i.e., hybridised scientific narratives) about the socioscientific issue of biosecurity. This study employed a triangulation mixed methods research design, generating both quantitative and qualitative data, in order to investigate three research questions that examined the extent to which the students' participation in the study enhanced their scientific literacy; the extent to which the students demonstrated conceptual understanding of related scientific concepts through their written artefacts and in interviews about the artefacts; and the extent to which the students' participation in the project influenced their attitudes toward science and science learning. Three aspects of scientific literacy were investigated in this study: conceptual science understandings (a derived sense of scientific literacy), the students' transformation of scientific information in written stories about biosecurity (simple and expanded fundamental senses of scientific literacy), and attitudes toward science and science learning. The stories written by students in a selected case study class (N=26) were analysed quantitatively using a series of specifically-designed matrices that produce numerical scores that reflect students' developing fundamental and derived senses of scientific literacy. All students (N=152) also completed a Likert-style instrument (i.e., BioQuiz), pretest and posttest, that examined their interest in learning science, science self-efficacy, their perceived personal and general value of science, their familiarity with biosecurity issues, and their attitudes toward biosecurity. Socioscientific issues (SSI) education served as a theoretical framework for this study. It sought to investigate an alternative discourse with which students can engage in the context of SSI education, and the role of positive attitudes in engaging students in the negotiation of socioscientific issues. Results of the study have revealed that writing BioStories enhanced selected aspects of the participants' attitudes toward science and science learning, and their awareness and conceptual understanding of issues relating to biosecurity. Furthermore, the students' written artefacts alone did not provide an accurate representation of the level of their conceptual science understandings. An examination of these artefacts in combination with interviews about the students' written work provided a more comprehensive assessment of their developing scientific literacy. These findings support extensive calls for the utilisation of diversified writing-to-learn strategies in the science classroom, and therefore make a significant contribution to the writing-to-learn science literature, particularly in relation to the use of hybridised scientific genres. At the same time, this study presents the argument that the writing of hybridised scientific narratives such as BioStories can be used to complement the types of written discourse with which students engage in the negotiation of socioscientific issues, namely, argumentation, as the development of positive attitudes toward science and science learning can encourage students' participation in the discourse of science. The implications of this study for curricular design and implementation, and for further research, are also discussed.

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.

The monster chronicles : the role of children’s stories featuring monsters in managing childhood fears and promoting empowerment

Children’s fascination with monsters is a normal part of childhood development. Children’s literature reflects this with a wealth of stories featuring monsters, ranging from fairy tales to picture books to books for independent readers. These stories can raise concerns from educators, parents and other sections of the community such as political and religious institutions on the basis that they could be disturbing or harmful to children. In contrast, there is evidence to indicate the potential for managing fears and enhancing feelings of empowerment in children through the reading of stories featuring monsters. A reappraisal of these stories from a predominantly therapeutic perspective reveals that they may act as agents of positive change in six ways – catharsis, naming, taming, integration, transformation and moral empowerment. Two of these functions, transformation and moral empowerment, are examined further in three case studies of stories for the older reader that feature monsters, Wolf Brother by Michelle Paver, Monster Blood Tattoo, Book One: Foundling by D.M. Cornish and my manuscript, ‘The Monster Chronicles’. The insights from this research have been used to inform the writing and editing of ‘The Monster Chronicles’ and inherent to that, my goal of creating a children’s story featuring monsters that is sensitive to children’s fears and their desire for empowerment.