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Techniques for the generation of quantitative ultrasonic images in non-destructive testing have generally involved a substantial cost in terms of data storage and computational time, and have thus found limited application. Preference has therefore been given to the more straightforward imaging methods, such as main beam projection, which detect the presence of defects and provide a limited flaw sizing capability. The relatively small number of flaws requiring detailed examination, coupled with substantial increases in available data storage and computational power, have made it possible to use a number of straightforward tomographic reconstruction methods to produce high resolution images of flaws contained within the material under examination. A set of these images are then fused together using a novel fuzzy logic image fusion technique into a single image from which more accurate measurements of flaw size, shape and orientation can be made. However, if the quality of the raw A-scan data is not sufficiently high then the data will be filtered using Maximum Likelihood Deconvolution (MLD). The aim of this blind deconvolution method is to improve the time resolution and Signal to Noise Ratio of the A-scan data with only knowledge obtained from the data, this is in contrast to the majority of techniques currently used for this purpose. The three tomographic methods which have been implemented in this work are Reflection tomography, Time-of-flight Diffraction tomography and Transmission tomography. In addition a Single Bounce Image Enhancement method has been developed to improve the images. Selection of images used in the fusion process depends on the nature of the flaw, as each of these methods identifies different characteristics of the flaw shape. The components of the imaging system have been validated experimentally by the generation of high resolution images from a variety of flaws contained within cylindrical aluminium test specimens.

Wireless Sensor Networks (WSNs) are a relatively new technology with many potential applications, including military and homeland security surveillance operations. Accurate classification of WSN contacts has been attempted using various sensor combinations over the past few years, yet video and photographic imagery remain the only choices for attaining context specific contact classification. While cameras have been successfully installed within some WSNs, there are serious limitations to this solution. Most stemming from the scarce power resources, immobility, and small form factor common among conventional WSN nodes. An efficient, low cost answer to this problem involves the use of unmanned aerial vehicles (UAVs) to acquire imagery of WSN contacts. For this system to scale to the wide expanses that WSNs deploy over, UAV contact surveillance operations must be controlled autonomously. The objective of this thesis is to research and implement an autonomous UAV WSN system, where an optimized two-dimensional flight plan is produced in response to WSN contact detection. Flight plans autonomously guide the UAV on a course to either an estimated interception point with the WSN contact or to the instigated WSN cluster, depending upon user input. The event driven application produced in this study functions in the periphery of the Kestrel Autopilot System, communicating flight plans to the UAV through properly crafted Kestrel packets.

This study examines the scholarship of J. A. Rogers and Rogers' use of vindicationist African-American history as a tool to illustrate his own ideas about humanism. Rogers' use of One-Drop ideology, Great Man history, and the philosophy of the bran of history combined into a subtle tool for undermining the entrenched racial attitudes of white supremacy during the twentieth century. This study was based on the premise that Rogers' use of vindicationism as a tool for humanism made his particular brand of vindicationist history relevant to Africana history. A historiographic critical approach to vindicationist history is used in order to determine what relevancy vindicationism has to Africana history and to what extent Rogers' humanism infused subtle arguments, contributed to Rogers' relevancy to Africana history. An examination of the goals and methodologies of other vindicationist scholars was utilized to find points of similarity and difference with Rogers' scholarship. This contrast of Rogers with other vindicationists allowed the salient points of Rogers' relevancy to be distilled. The conclusions of this study suggest that Rogers' relevancy is in his contribution to Humanism. Rogers attempts to demystify and debunk the idea of race and the history of racial intermixing, along with his championing the idea of the unity of humanity are more relevant than his vindicationist history. Additionally this study shows that both the critics of Rogers and those vindicationist historians who have followed in his footsteps have missed the subtlety in his writing. Both have viewed Rogers merely as a vindicationist. Whereas vindicationism' s tableau of black heroes is a reactionary response to Eurocentric history, Rogers' use of One-Drop ideology to debunk the idea of race was revolutionary.

Doctor of Philosophy / Curriculum and Instruction / F. Todd Goodson / This study investigates visual representation of three perspectives: the context of school, the pedagogy, and the teacher-student relationships when viewing photographs taken during the first half of the 20th Century of American Schools. Grounded in the understanding of visual culture, this image-based study utilized photographs as a rich source of data. The photographs collected for this study were taken between 1900 -1959 in American schools and were categorized by the Library of Congress as still images of classrooms in the United States. The Library of Congress collection was utilized to provide reliable categorized and documented images of schooling. The collection included 1,812 photographs archived in the Library of Congress Prints and Photographs collections specifically labeled as Classrooms United States; the non-digitized Frances Benjamin Johnston Photograph Collection of United States Indian School; and, Look Magazine Teacher Issue Charlotte Brooks negatives collection. A three-layered analysis utilized an initial layer of analysis placing each of the photographs into four predetermined categories: Time Period (1900-1950’s), Urban-Rural, Wealth-Poverty, Active-Passive environment. The placement of each photograph into the above continua provided evidence of the balance of visual elements within the data collection. Seven themes emerged through an open-coding process within the second layer of analysis when each photograph was coded using a specific perspective: context, pedagogy, and teacher-student relationship. As themes were extracted, a third layer of analysis utilized a semiotic approach to identifying over 20 cultural icons representational of schooling within the photograph. Implications for further research are provided.

Image-related communications are forming an increasingly large part of modern communications, bringing the need for efficient and effective compression. Image compression is important for effective storage and transmission of images. Many techniques have been developed in the past, including transform coding, vector quantization and neural networks. In this thesis, a novel adaptive compression technique is introduced based on adaptive rather than fixed transforms for image compression. The proposed technique is similar to Neural Network (NN)-based image compression and its superiority over other techniques is presented It is shown that the proposed algorithm results in higher image quality for a given compression ratio than existing Neural Network algorithms and that the training of this algorithm is significantly faster than the NN based algorithms. This is also compared to the JPEG in terms of Peak Signal to Noise Ratio (PSNR) for a given compression ratio and computational complexity. Advantages of this idea over JPEG are also presented in this thesis.

This body of work examines the plausibility of applying partial di erential equations and time-fractional partial di erential equations to images. The standard di usion equation is coupled with a nonlinear cubic source term of the Fitzhugh-Nagumo type to obtain a model with di usive properties and a binarizing e ect due to the source term. We examine the e ects of applying this model to a class of images known as document images; images that largely comprise text. The e ects of this model result in a binarization process that is competitive with the state-of-the-art techniques. Further to this application, we provide a stability analysis of the method as well as high-performance implementation on general purpose graphical processing units. The model is extended to include time derivatives to a fractional order which a ords us another degree of control over this process and the nature of the fractionality is discussed indicating the change in dynamics brought about by this generalization. We apply a semi-discrete method derived by hybridizing the Laplace transform and two discretization methods: nite-di erences and Chebyshev collocation. These hybrid techniques are coupled with a quasi-linearization process to allow for the application of the Laplace transform, a linear operator, to a nonlinear equation of fractional order in the temporal domain. A thorough analysis of these methods is provided giving rise to conditions for solvability. The merits and demerits of the methods are discussed indicating the appropriateness of each method.