Hyperspectral Mineral Identification using SVM and SOM

Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).

Exploring female graduate students' multifaceted and intersecting roles and identities in a complex educational milieu /

This qualitative phenomenological investigation explored six female Master of Education students' critical understandings of their identity and role negotiations, and their perceptions of environmental conditions that facilitated or impeded their identity explorations and negotiations within the institution. The interweaving of Feminist and Women's Development theories enabled the data to be examined under different, yet complementary, lenses. The data collection strategies included: four to five in-depth semistructured interviews, three take-home activities (involving identity mapping, object and metaphor identification, and strategy development), and the compilation of extensive interview notes as well as researcher reflections. The combination of a constant comparative method and a voice-centered method were used in tandem to analyze the data. Together they uncovered five emergent themes: (a) intricate understandings of key terms; (b) life-long learning and transformative pathways; (c) gender issues; (d) challenges, tensions, and possibilities; as well as (e) personal, professional, and educational implications. The findings underscored the possibility for both a singular static identity and dynamic multifaceted identities to exist in tandem, and the emergence of natural or logical identity intersections, as well as disjointed or colliding identity intersections. Ultimately, it is the continuous negotiation of internal and external spheres that contributes to the complexity and multidimensionality of graduate students' identities.

Physical volcanology, sedimentology, stratigraphy and petrochemistry of the Berry Creek metavolcanics: an Archean calc-alkaline complex, Lake of the Woods, Ontario

The steeply dipping, isoclinally folded early Precambrian (Archean) Berry Creek Metavolcanic Complex comprises primary to resedimented pyroclastic, epiclastic and autoclastic deposits. Tephra erupted from central volcanic edifices was dumped by mass flow mechanisms into peripheral volcanosedimentary depressions. Sedimentation has been essentially contemporaneous with eruption and transport of tephra. The monolithic to heterolithic tuffaceous horizons are interpreted as subaerial to subaqueous pumice and ash flows, secondary debris flows, lahars, slump deposits and turbidites. Monolithic debris flows, derived from crumble breccia and dcme talus, formed during downslope collapse and subsequent gravity flowage. Heterolithic tuff, lahars and lava flow morphologies suggest at least temporary emergence of the edifice. Local collapse may have accompanied pyroclastic volcanism. The tephra, produced by hydromagmatic to magmatic eruptions, were rapidly transported, by primary and secondary mechanisms, to a shallow littoral to deep water subaqueous fan developed upon the subjacent mafic metavolcanic platform. Deposition resulted from traction, traction carpet, and suspension sedimentation from laminar to turbulent flows. Facies mapping revealed proximal (channel to overbank) to distal facies epiclastics (greywackes, argillite) intercalated with proximal vent to medial fan facies crystal rich ash flows, debris flows, bedded tuff and shallow water to deep water lava flows. Framework and matrix support debris flows exhibit a variety of subaqueous sedimentary structures, e.g., coarse tail grading, double grading, inverse to normal grading, graded stratified pebbly horizons, erosional channels. Pelitic to psammitic AE turbidites also contain primary stru~tures, e.g., flames, load casts, dewatering pipes. Despite low to intermediate pressure greenschist to amphibolite grade metamorphism and variably penetrative deformation, relicts of pumice fragments and shards were recognized as recrystallized quartzofeldspathic pseudomorphs. The mafic to felsic metavolcanics and metasediments contain blasts of hornblende, actinolite, garnet, pistacitic epidote, staurolite, albitic plagioclase, and rarely andalusite and cordierite. The mafic metavolcanics (Adams River Bay, Black River, Kenu Lake, Lobstick Bay, Snake Bay) display _holeiitic trends with komatiitic affinities. Chemical variations are consistent with high level fractionation of olivine, plagioclase, amphibole, and later magnetite from a parental komatiite. The intermediate to felsic (64-74% Si02) metavolcanics generally exhibit calc-alkaline trends. The compositional discontinuity, defined by major and trace element diversity, can be explained by a mechanism involving two different magma sources. Application of fractionation series models are inconsistent with the observed data. The tholeiitic basalts and basaltic andesites are probably derived by low pressure fractionation of a depleted (high degree of partial melting) mantle source. The depleted (low Y, Zr) calc-alkaline metavolcanics may be produced by partial melting of a geochemically evolved source, e.g., tonalitetrondhjemite, garnet amphibolite or hydrous basalt.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.