ABSTRACT The aim of the study is to investigate the impact of the Gwembe Tonga Development Project (GTDP) on the Gwembe Tonga (GT) people. The GT people were displaced in 1956 to pave way for the construction of the Kariba Dam that would increase the electricity supply to the mines in the Copperbelt and farmers. The number of people displaced was 57, 000 and they were not adequately resettled, rehabilitated and compensated. The GTDP was created in 1996 with the main objective to mitigate the negative impacts that the GT people have endured from the time they were displaced to date. A review of international literature on dams has indicated that dam constructions have led to displacement of the poor and marginalized people. Over 40 million people have been displaced worldwide. As shown in the literature review, are case studies that demonstrate the impacts of dams on people. In this study there six countries that have been listed namely India, China, Lesotho, Togo, Mozambique and Zambia. The people in these countries have experienced similar problems in terms of inadequate compensation, resettlement and rehabilitation. It is also noted that these dams leave a negative impact on the local community and environment. Development projects are equated with a general process of modernization where developed nations’ ways of conducting its affairs have been adopted by the developing countries to boost their economic development. This study has also looked at the developmental theories that the developing countries have adopted for economic transformation of both natural and built environments through construction of projects such as dams, roads, irrigation systems, pipelines, and energy resources, aimed eventually at generating and supporting both agricultural and industrial growth, and with them, increased national incomes. These large-scale development projects frequently make references to benefit the general population but experience has shown that the social costs of these projects are often borne by the indigent rural communities.

<p>Accurate quantification of anatomical and pathological structures in the eye is crucial for the study and diagnosis of potentially blinding diseases. Earlier and faster detection of ophthalmic imaging biomarkers also leads to optimal treatment and improved vision recovery. While modern optical imaging technologies such as optical coherence tomography (OCT) and adaptive optics (AO) have facilitated in vivo visualization of the eye at the cellular scale, the massive influx of data generated by these systems is often too large to be fully analyzed by ophthalmic experts without extensive time or resources. Furthermore, manual evaluation of images is inherently subjective and prone to human error.</p><p>This dissertation describes the development and validation of a framework called graph theory and dynamic programming (GTDP) to automatically detect and quantify ophthalmic imaging biomarkers. The GTDP framework was validated as an accurate technique for segmenting retinal layers on OCT images. The framework was then extended through the development of the quasi-polar transform to segment closed-contour structures including photoreceptors on AO scanning laser ophthalmoscopy images and retinal pigment epithelial cells on confocal microscopy images. </p><p>The GTDP framework was next applied in a clinical setting with pathologic images that are often lower in quality. Algorithms were developed to delineate morphological structures on OCT indicative of diseases such as age-related macular degeneration (AMD) and diabetic macular edema (DME). The AMD algorithm was shown to be robust to poor image quality and was capable of segmenting both drusen and geographic atrophy. To account for the complex manifestations of DME, a novel kernel regression-based classification framework was developed to identify retinal layers and fluid-filled regions as a guide for GTDP segmentation.</p><p>The development of fast and accurate segmentation algorithms based on the GTDP framework has significantly reduced the time and resources necessary to conduct large-scale, multi-center clinical trials. This is one step closer towards the long-term goal of improving vision outcomes for ocular disease patients through personalized therapy.</p> / Dissertation