Thesis (Ph. D.)--University of Hong Kong, 1998. / Includes bibliographical references.

Thesis (Ph. D.)--University of Rhode Island, 2005. / Typescript. Includes bibliographical references (leaves 100-108).

The efficiency of low voltage scanning electron microscopy, which presents near-surface information, has been well known for a long time. However, it is not widely known that the high resolution capability can only be achieved when the surface reveals the original characteristics of the materials without any deterioration due contamination. Therefore, initial attention in this study is directed at clarifying the efficient use of the ultra high resolution, low voltage SEM (UHRLV SEM), (Ultra55, Zeiss). The SEM images and the selected electrons for detection, and damage that occurs through UHRVL SEM observation are also researched. Subsequently, the most efficient specimen preparation technique, which is appropriate for the characteristics of the individual materials, is investigated for galvanized steel, ultrasonically welded alloys of Al6111 and AZ31 alloy, Ti6Al4V alloy honeycomb structure and a ceramic sensor. The outcomes of appropriate specimen preparation technique and use of the extremely Low-Voltage below 2.0 kV, are presented in the results section. The study also presented the challenge of improving the low compositional contrast for the dissimilar materials of aluminium and magnesium, and to reduce charging effects in an insulating material comprising a ceramic sensor. As an application of the surface prepared by the process in this study, 3D tomography is also introduced.

No description available.

Image interpolation in the medical area is of vital importance as most 3D biomedical volume images are sampled where the distance between consecutive slices is significantly greater than the in-plane pixel size due to radiation dose or scanning time. Image interpolation creates a certain number of new slices between known slices in order to obtain an isotropic volume image. The results can be used for the higher quality of 2D and 3D visualization or reconstruction of human body structure. Semantic interpolation on the manifold has been proved to be very useful for smoothing the interpolation process. Nevertheless, all previous methods focused on low-resolution image interpolation, and most of which work poorly on high-resolution images. Besides, the medical field puts a high threshold for the quality of interpolations, as they need to be semantic and realistic enough, and resemble real data with only small errors permitted. Typically, people downsample the images into 322 and 642 for semantic interpolation, which does not meet the requirement for high-resolution in the medical field. Thus, we explore a novel way to generate semantically correct interpolations and maintain the resolution at the same time. Our method has been proved to generate realistic and high-resolution interpolations on the sizes of 5262 and 5122. Our main contribution is, first, we propose a novel network, High Resolution Interpolation Network (HRINet), aiming at producing semantically correct high-resolution CT image interpolations. Second, by combining the idea of ACAI and GANs, we propose a unique alternative supervision method by applying supervised and unsupervised training alternatively to raise the accuracy and fidelity of body structure in CT when interpolated while keeping high quality. Third, we introduce an extra Markovian discriminator as a texture or fine details regularizer to make our model generate results indistinguishable from real data. In addition, we explore other possibilities or tricks to further improve the performance of our model, including low-level feature maps mixing, and removing batch normalization layers within the autoencoder. Moreover, we compare the impacts of MSE based and perceptual based loss optimizing methods for high quality interpolation, and show the trade-off between the structural correctness and sharpness. The interpolation experiments show significant improvement on both sizes of 256 2 and 5122 images quantitatively and qualitatively. We find that interpolations produced by HRINet are sharper and more realistic compared with other existing methods such as AE and ACAI in terms of various metrics. As an application of high-resolution interpolation, we have done 2D volume projection and 3D volume reconstruction from axial view CT data and their interpolations. We show the great enhancement of applying HRINet for both in sharpness and fidelity. Specifically, for 2D volume projection, we explore orthogonal projection and weighted projection respectively so as to show the improved effectiveness for visualizing internal and external human body structure.

Over the coming decades, both food consumption and agricultural water use are expected to increase in response to growing populations. In light of these concerns, there has been a growing awareness and appreciation of the objectives of agricultural sustainability, which has the broad aim of securing food and water resources, without adversely affecting the environment or disenfranchising future generations. To ensure that irrigated fields optimize their water use towards a more sustainable application while remaining compliant with any imposed restrictions on access to water supplies (i.e. through water licensing), it is necessary to understand and quantify the water consumption of crops at appropriate spatial and temporal scales. Evaporation (E), also commonly referred to as evapotranspiration (ET), is the physical process of water vapor transport from the surface into the atmosphere. Evaporation can be estimated via interpretive modeling approaches that combine meteorological, radiative, vegetation, and other related properties to estimate land surface fluxes at any given time. The research presented herein aims to investigate the evaporative response of agricultural croplands across a range of spatial and temporal scales, with a focus on high-resolution and field-scale estimation. In particular, we explore the utility of novel CubeSat imagery to produce the highest spatial resolution (3 m) crop water use estimates ever retrieved from space. These high-resolution results are expanded through time by retrieving a daily evaporation product, offering an enhanced capacity to provide new insights into precision agriculture. The effects and implications of higher spatiotemporal resolutions are explored and contrasted against governmental satellite missions that operate at lower resolutions. An exploratory study on the use of unmanned aerial vehicles (UAVs) is also performed, specifically in the context of their capacity to mount miniaturized thermal sensors: with the accuracy and limitations of these sensors for deriving evaporation-type products examined. The overarching goal of this research is to advance the utility of space-based estimates of evaporation for precision agricultural applications, and to provide new high-spatial and temporal agricultural insights that can be directed towards improving water management and address food security concerns in a more sustainable manner.

No / The purpose of the research was to examine the practical feasibility of developing a hyperspectral camera from a Zeiss fundus camera and to illustrate its use in imaging diabetic retinopathy and glaucoma patients. The original light source of the camera was replaced with an external lamp filtered by a fast tunable liquid-crystal filter. The filtered light was then brought into the camera through an optical fiber. The original film camera was replaced by a digital camera. Images were obtained in normals and patients (primary open angle glaucoma, diabetic retinopathy) recruited at the Manchester Royal Eye Hospital. A series of eight images were captured across 495- to 720-nm wavelengths, and recording time was less than 1.6s. The light level at the cornea was below the ANSI limits, and patients judged the measurement to be very comfortable. Images were of high quality and were used to generate a pixel-to-pixel oxygenation map of the optic nerve head. Frame alignment is necessary for frame-to-frame comparison but can be achieved through simple methods. We have developed a hyperspectral camera with high spatial and spectral resolution across the whole visible spectrum that can be adapted from a standard fundus camera. The hyperspectral technique allows wavelength-specific visualization of retinal lesions that may be subvisible using a white light source camera. This hyperspectral technique may facilitate localization of retinal and disc pathology and consequently facilitate the diagnosis and management of retinal disease.

<p> The Lower Cretaceous (Upper Albian) Viking Formation of central Alberta contains numerous linear sandbodies and fewer large irregularly-shaped sandbodies. Most studies to date have focused on individual sandbodies, leaving their interrelationships largely unknown. Developing a high-resolution allostratigraphy for the Viking of central Alberta allows mapping of regional bounding discontinuities and the definition of distinct allomembers. Placement of the Viking hydrocarbon fields within this framework permits an understanding of the exact stratigraphic relationships of the various fields. </p> <p> Examination of 120 cores and numerous well log correlations suggests the existence of four regionally mappable bounding discontinuities (BDl-4) which separate five distinct allomembers (I-V). Sandbodies within these allomembers were deposited in a variety of sedimentologically distinct environments. These include 'regional Viking' offshore to shoreface sandstones, prograding highstand shoreface sediments, transgressive incised shoreface sediments, and forced regressive, onlapping shoreface 'tongues'. The series of linear trending hydrocarbon fields from Joffre to Chain are also stratigraphically distinct. The sandbodies exist at five separate stratigraphic horizons and therefore are not all part of the same incised shoreface deposits. </p> <p> The four regional bounding discontinuities are interpreted as transgressive surfaces of erosion formed by four separate drops and subsequent rises of relative sea level. These fluctuations were greater than 30m and each complete cycle occurred over roughly 375,000 years. </p> / Thesis / Master of Science (MSc)

QuickBird satellite data was used to examine stem density, basal area, and crown density, as potential forest strata to aid in volume estimations for a regional inventory program. The classes used for analysis were pine pole and sawtimber, and hardwood pole and sawtimber. Total height, height to live crown, diameter at breast height (dbh), and crown class were measured on 129 field plots used in image classification and accuracy assessments. Supervised classification produced overall accuracy of 85% with a Kappa of 0.8065. The classification was used for the extraction of mean band data and percent of forested pixels. Satellite derived variables were used with field measurements such as average basal area and stem density for regression analysis to predict forest characteristics such as stem density and crown closure that are indicators of volume variability. The R2 values ranged from 0.0005 to 0.2815 for hardwoods and 0.0001 to 0.6174 for pines.

No description available.