Learning English as an adult: a narrative of women's improvised and empowered lives /

This thesis is a narrative inquiry of learning English as an adult. It stories the journey of 7 women, including me, and unravels lived experiences that serve as learning models. Learning English as an adult presents challenges and results in lifelong implications both in personal and professional life. Every learner's experience is imique and, when reflected upon, each experience is a valuable source of knowledge for constructing meanings and forging new identities. The stories are testimony to the participants' lives: interrupted yet improvised, silenced yet roused, dependent yet independent, intimidated yet courageous, vulnerable yet empowered. The personal experiences elucidate the passion, the inner voices, the dreams, and the rewards that compel persistence in learning a new language and releaming new social roles. The stories provide encouragement and hope to other women who are learning or will learn English in their adult years, and the lived experiences will offer insights for English language teachers. This thesis employs the phenomenology methodology of research with heuristic (discovery) and hermeneutical (interpretative) approaches using the reflective-responsivereflexive writing and interviewing methods for data gathering and unravelling. The narrative inquiry approach reaffirms that storytelling is an important tool in conducting research and constructing new knowledge. This thesis narrates a new story about sharing experiences, interconnecting, and continuing to learn.

Geological image processing of petrographic thin sections using the rotating polarizer stage

One of the fundamental problems with image processing of petrographic thin sections is that the appearance (colour I intensity) of a mineral grain will vary with the orientation of the crystal lattice to the preferred direction of the polarizing filters on a petrographic microscope. This makes it very difficult to determine grain boundaries, grain orientation and mineral species from a single captured image. To overcome this problem, the Rotating Polarizer Stage was used to replace the fixed polarizer and analyzer on a standard petrographic microscope. The Rotating Polarizer Stage rotates the polarizers while the thin section remains stationary, allowing for better data gathering possibilities. Instead of capturing a single image of a thin section, six composite data sets are created by rotating the polarizers through 900 (or 1800 if quartz c-axes measurements need to be taken) in both plane and cross polarized light. The composite data sets can be viewed as separate images and consist of the average intensity image, the maximum intensity image, the minimum intensity image, the maximum position image, the minimum position image and the gradient image. The overall strategy used by the image processing system is to gather the composite data sets, determine the grain boundaries using the gradient image, classify the different mineral species present using the minimum and maximum intensity images and then perform measurements of grain shape and, where possible, partial crystallographic orientation using the maximum intensity and maximum position images.

Sustainability, Fashion Design, and Consumerism: Undergraduate Entry Level Fashion Students' Knowledge, Attitudes, and Habits

This qualitative inquiry explored 7 undergraduate students' attitudes, habits, and knowledge of consumerism, fashion design, and sustainability. The postmodern study employed crystallization as its methodological framework to gain insight into how participants' knowledge is manifested in their daily habits, and used 4 methods of data gathering: semistructured interviews, visual exercises, journal entries, and the researcher's own reflections. Four major themes emerged: Knowledge-Concepts Linked and Fragmented; Dissonance Between Knowledge Versus Attitudes and Consumer Habits; Surrendering to the Unsustainable Structures; Design Process and Caring Attitude. Findings indicate that participants possessed some knowledge of sustainability but lacked a well-rounded understanding of environmental and humanitarian implications of Western consumer society. Findings also reveal a dissonance between participants' knowledge and attitudes-affecting how their knowledge influences their behaviour-and how reflection, creative thinking, and drawing initiate change in participants' underlying attitudes. Recommendations are made to merge a variety of theoretical frameworks into the educational system in order to create curricula that offer a holistic overview and unique insights into sustainability challenges, particularly in specialized areas of the fashion industry.

Infrared thermography: A non-invasive window into thermal physiology

Infrared thermography is a non-invasive technique that measures mid to long-wave infrared radiation emanating from all objects and converts this to temperature. As an imaging technique, the value of modern infrared thermography is its ability to produce a digitized image or high speed video rendering a thermal map of the scene in false colour. Since temperature is an important environmental parameter influencing animal physiology and metabolic heat production an energetically expensive process, measuring temperature and energy exchange in animals is critical to understanding physiology, especially under field conditions. As a non-contact approach, infrared thermography provides a non-invasive complement to physiological data gathering. One caveat, however, is that only surface temperatures are measured, which guides much research to those thermal events occurring at the skin and insulating regions of the body. As an imaging technique, infrared thermal imaging is also subject to certain uncertainties that require physical modeling, which is typically done via built-in software approaches. Infrared thermal imaging has enabled different insights into the comparative physiology of phenomena ranging from thermogenesis, peripheral blood flow adjustments, evaporative cooling, and to respiratory physiology. In this review, I provide background and guidelines for the use of thermal imaging, primarily aimed at field physiologists and biologists interested in thermal biology. I also discuss some of the better known approaches and discoveries revealed from using thermal imaging with the objective of encouraging more quantitative assessment.

Extracting Ramachandran torsional angle distributions from 2D NMR data using Tikhonov regularization /

Solid state nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for studying structural and dynamical properties of disordered and partially ordered materials, such as glasses, polymers, liquid crystals, and biological materials. In particular, twodimensional( 2D) NMR methods such as ^^C-^^C correlation spectroscopy under the magicangle- spinning (MAS) conditions have been used to measure structural constraints on the secondary structure of proteins and polypeptides. Amyloid fibrils implicated in a broad class of diseases such as Alzheimer's are known to contain a particular repeating structural motif, called a /5-sheet. However, the details of such structures are poorly understood, primarily because the structural constraints extracted from the 2D NMR data in the form of the so-called Ramachandran (backbone torsion) angle distributions, g{^,'4)), are strongly model-dependent. Inverse theory methods are used to extract Ramachandran angle distributions from a set of 2D MAS and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) data. This is a vastly underdetermined problem, and the stability of the inverse mapping is problematic. Tikhonov regularization is a well-known method of improving the stability of the inverse; in this work it is extended to use a new regularization functional based on the Laplacian rather than on the norm of the function itself. In this way, one makes use of the inherently two-dimensional nature of the underlying Ramachandran maps. In addition, a modification of the existing numerical procedure is performed, as appropriate for an underdetermined inverse problem. Stability of the algorithm with respect to the signal-to-noise (S/N) ratio is examined using a simulated data set. The results show excellent convergence to the true angle distribution function g{(j),ii) for the S/N ratio above 100.

Quadtree representation and compression of spatial data

Spatial data representation and compression has become a focus issue in computer graphics and image processing applications. Quadtrees, as one of hierarchical data structures, basing on the principle of recursive decomposition of space, always offer a compact and efficient representation of an image. For a given image, the choice of quadtree root node plays an important role in its quadtree representation and final data compression. The goal of this thesis is to present a heuristic algorithm for finding a root node of a region quadtree, which is able to reduce the number of leaf nodes when compared with the standard quadtree decomposition. The empirical results indicate that, this proposed algorithm has quadtree representation and data compression improvement when in comparison with the traditional method.

New Contig Creation Algorithm for the de novo DNA Assembly Problem

DNA assembly is among the most fundamental and difficult problems in bioinformatics. Near optimal assembly solutions are available for bacterial and small genomes, however assembling large and complex genomes especially the human genome using Next-Generation-Sequencing (NGS) technologies is shown to be very difficult because of the highly repetitive and complex nature of the human genome, short read lengths, uneven data coverage and tools that are not specifically built for human genomes. Moreover, many algorithms are not even scalable to human genome datasets containing hundreds of millions of short reads. The DNA assembly problem is usually divided into several subproblems including DNA data error detection and correction, contig creation, scaffolding and contigs orientation; each can be seen as a distinct research area. This thesis specifically focuses on creating contigs from the short reads and combining them with outputs from other tools in order to obtain better results. Three different assemblers including SOAPdenovo [Li09], Velvet [ZB08] and Meraculous [CHS+11] are selected for comparative purposes in this thesis. Obtained results show that this thesis’ work produces comparable results to other assemblers and combining our contigs to outputs from other tools, produces the best results outperforming all other investigated assemblers.

Disease-Gene Association Using a Genetic Algorithm

Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.