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published_or_final_version / Medicine / Master / Master of Philosophy

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This dissertation presents the design of a miniature injection-molded objective lens for a fiber-optic confocal reflectance microscope. This is part of an effort to demonstrate the ability to fabricate low cost, high performance biomedical optics for high resolution in vivo imaging. Disposable endoscopic microscope objectives could help in vivo confocal microscopy technology mature to enable large-scale clinical screening and detection of early cancers and pre-cancerous lesions. This five lens plastic objective has been tested as a stand-alone optical system and has been coupled to a confocal microscope for in vivo imaging of cells and tissue. Changing the spacing and rotation of the individual optical elements can compensate for fabrication inaccuracies and improve performance. An optical-bench testing system was constructed to allow interactive alignment during testing. The modulation transfer function (MTF) of the miniature objective lens is determined using the slanted-edge method. A custom MATLAB program, edgeMTF, was written to collect, analyize, and record test data. An estimated Strehl ratio of 0.64 and an MTF value of 0.70, at the fiber-optic bundle Nyquist frequency, have been obtained. The main performance limitations of the miniature objective are mechanical alignment and flow-induced birefringence. Annealing and experimental injection molding runs were conducted in effort to reduce birefringence.

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Graphene is one of the most popular material due to its promising properties, for instance electronics applications. Graphene films were grown on silicon carbide (SiC) substrate using chemical vapor deposition (CVD). Influence of the deposition temperature on the morphology of the films was investigated. Characterizations were done by reflectance mapping, atomic force microscopy and Raman spectroscopy. Two samples were done by sublimation process, to compare the number of layers and the morphology of the graphene films with the one grown by chemical vapor deposition.The reflectance mapping showed that the number of layers on the samples made by CVD was notinfluenced by the deposition temperature. But also, demonstrated that sublimation growth is present in allthe samples due to the presence of silicon coating in the susceptor. The growth probably started by sublimation and then CVD deposition. The step morphology characteristic of the silicon carbide substrate surface was conserved during the deposition of graphene. But due to surface step bunching, a decrease inthe step height occurred and the width of the terraces increased. The decreasing in deposition temperature leads to a smoother surface with the CVD method. Raman spectroscopy confirmed the presence ofgraphene and of the buffer layer characteristic of the sublimation growth. Moreover, it demonstrated the presence of compressive strain in the graphene layers.

Uncertainties associated with the microphysical and radiative properties of ice clouds remain an active research area because of the importance these clouds have in atmospheric radiative transfer problems and the energy balance of the Earth. In this study, an adding/doubling model is used to simulate the top of atmosphere (TOA) radiance and full Stokes vector from an ice cloud at the wavelength lambda = 865 nm with many different combinations of assumed ice habits (shapes) and different degrees of ice surface roughness, and the polarized radiance at a wide range of scattering angles is derived. Simulated results are compared with polarized radiance data from the POLDER (POLarization and Directionality of the Earth's Reflectances) instrument on board the PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) satellite. Bulk ice scattering properties are obtained by using five different size distributions collected during field campaigns ranging in effective diameter from 10 micrometers to 90 micrometers. Bulk scattering properties for the MODIS Collection 5 ice cloud product are used in this study, along with properties for two mid-latitude ice cloud models, a polar/mid-latitude ice model, and a model built for ice clouds over deep convection. Solid columns and hollow columns are used as well. The polarized radiance simulation results for the moderate surface roughness level best fit the satellite measurements for all ice models, though severely roughened ice crystals do fare well in a few cases. Hollow columns are the best fit to the satellite polarization measurements, but of the ensemble ice models, the polar/mid-latitude model at an effective diameter of 90 micrometers best fits the polarized radiance measurements for the one day of PARASOL data considered. This model should be the best to simulate ice cloud properties on a global scale.

This research investigates the spectral reflectance characteristics of soil and vegetation using multi-angular and single view hyperspectral data. The question of the thesis is ???How much information can be obtained from multi-angular hyperspectral remote sensing in comparison with single view angle hyperspectral remote sensing of soil and vegetation???? This question is addressed by analysing multi-angular and single view angle hyperspectral remote sensing using data from the field, airborne and space borne hyperspectral sensors. Spectral mapping, spectral indices and Functional Data Analysis (FDA) are used to analyse the data. Spectral mapping has been successfully used to distinguish features of soil and cotton with hyperspectral data. Traditionally, spectral mapping is based on collecting endmembers of pure pixels and using these as training areas for supervised classification. There are, however, limitations in the use of these algorithms when applied to multi-angular images, as the reflectance of a single ground unit will differ at each angle. Classifications using six-class endmembers identified using single angle imagery were assessed using multi-angular Compact High Resolution Imaging Spectrometer (CHRIS) imagery, as well as a set of vegetation indices. The results showed no significant difference between the angles. Low nutrient content in the soil produced lower vegetation index values, and more nutrients increased the index values. This research introduces FDA as an image processing tool for multi-angular hyperspectral imagery of soil and cotton, using basis functions for functional principal component analysis (fPCA) and functional linear modelling. FDA has advantages over conventional statistical analysis because it does not assume the errors in the data are independent and uncorrelated. Investigations showed that B-splines with 20-basis functions was the best fit for multi-angular soil spectra collected using the spectroradiometer and the satellite mounted CHRIS. Cotton spectra collected from greenhouse plants using a spectrodiometer needed 30-basis functions to fit the model, while 20-basis functions were sufficient for cotton spectra extracted from CHRIS. Functional principal component analysis (fPCA) of multi-angular soil spectra show the first fPCA explained a minimum of 92.5% of the variance of field soil spectra for different azimuth and zenith angles and 93.2% from CHRIS for the same target. For cotton, more than 93.6% of greenhouse trial and 70.6% from the CHRIS data were explained by the first fPCA. Conventional analysis of multi-angular hyperspectral data showed significant differences exist between soil spectra acquired at different azimuth and zenith angles. Forward scan direction of zenith angle provides higher spectral reflectance than backward direction. However, most multi-angular hyperspectral data analysed as functional data show no significant difference from nadir, except for small parts of the wavelength of cotton spectra using CHRIS. There is also no significant difference for soil spectra analysed as functional data collected from the field, although there was some difference for soil spectra extracted from CHRIS. Overall, the results indicate that multi-angular hyperspectral data provides only a very small amount of additional information when used for conventional analyses.