Effects of rescaling bilinear interpolant on image interpolation quality

Rescaling bilinear (RB) interpolant's pixels is a novel image interpolation scheme. In the current study, we investigate the effects on the quality of interpolated images. RB determines the lower and upper bounds using the standard deviation of the four nearest pixels to find the new interval or range that will be used to rescale the bilinear interpolant's pixels. The products of the rescaled-pixels and corresponding distance-based-weights are added to estimate the new pixel value, to be assigned at the empty locations of the destination image. Effects of RB on image interpolation quality were investigated using standard full-reference and non-reference objective image quality metrics, particularly those focusing on interpolated images features and distortion similarities. Furthermore, variance and mean based metrics were also employed to further investigate the effects in terms of contrast and intensity increment or decrement. The Matlab based simulations demonstrated generally superior performances of RB compared to the traditional bilinear (TB) interpolation algorithm. The studied scheme's major drawback was a higher processing time and tendency to rely on the image type and/or specific interpolation scaling ratio to achieve superior performances. Potential applications of rescaling based bilinear interpolation may also include ultrasound scan conversion in cardiac ultrasound, endoscopic ultrasound, etc

Demographic Variations in Achievement Goal Orientations among Prisoners on Formal and Vocational Training in Uganda

Educating Prisoners has become a worldwide concern as a measure that can save community costs associated with criminal behavior. In Uganda, there is low participation in formal and vocational training among prisoners which can be associated with lack of knowledge on achievement goal orientations. This is central for adequate implementation of academic and vocational education in prisons, otherwise it may lead to wasted Government initiative and commitment on education as a rehabilitation strategy for prisoners. The purpose of the study was to assess demographic variations in achievement goal orientations among prisoners on formal and vocational training in Uganda. This study adopted across sectional survey design with a mixed methods approach. The population was adult male and female prisoners enrolled on both formal and vocational training in Luzira prison using census sampling strategy. Measures used included the bio data section and the Patterns of Adaptive Learning Survey. Permission was sought from all relevant authorities and data analysed using the Statistical Package for Social Scientists (SPSS) version 20. The study found out that there is no statistically significant relationship between mastery goals and demographic information; and between performance approach goals and demographic information reflected in the P values. However, there is a statistically significant relationship between performance avoidance goals and gender (P=.013). There is no statistically significant relationship between Approach avoidance goals and other demographic variables as reflected in their P values. The findings of this study may be used by prison education instructors, administrators and curriculum planners in bridging the gap between demographic variations and achievement goal orientations. This study posit to the importance of understanding prisoners goal orientations and how these goals influence their learning and academic outcomes. It is generally acknowledged that setting achievement goal orientations may be integrated into instructional materials to promote better academic achievement. Prisoners participating in academic and vocational education should be encouraged to adopt achievement goals according to the broader social and psychological horizon which shall help to direct their attention towards activities that will help them energies performance there by motivating prisoners expend greater effort in line with difficulties of achieving goals, spend more time and persist longer working on tasks to improve the overall performanc

Efficient concurrent data structure access parallelism techniques for increasing scalability

Multi-core processors have revolutionised the way data structures are designed by bringing parallelism to mainstream computing. Key to exploiting hardware parallelism available in multi-core processors are concurrent data structures. However, some concurrent data structure abstractions are inherently sequential and incapable of harnessing the parallelism performance of multi-core processors. Designing and implementing concurrent data structures to harness hardware parallelism is challenging due to the requirement of correctness, efficiency and practicability under various application constraints. In this thesis, our research contribution is towards improving concurrent data structure access parallelism to increase data structure performance. We propose new design frameworks that improve access parallelism of already existing concurrent data structure designs. Also, we propose new concurrent data structure designs with significant performance improvements. To give an insight into the interplay between hardware and concurrent data structure access parallelism, we give a detailed analysis and model the performance scalability with varying parallelism.In the first part of the thesis, we focus on data structure semantic relaxation. By relaxing the semantics of a data structure, a bigger design space, that allows weaker synchronization and more useful parallelism, is unveiled. Investigating new data structure designs, capable of trading semantics for achieving better performance in a monotonic way, is a major challenge in the area. We algorithmically address this challenge in this part of the thesis. We present an efficient, lock-free, concurrent data structure design framework for out-of-order semantic relaxation. We introduce a new two-dimensional algorithmic design, that uses multiple instances of a given data structure to improve access parallelism. In the second part of the thesis, we propose an efficient priority queue that improves access parallelism by reducing the number of synchronization points for each operation. Priority queues are fundamental abstract data types, often used to manage limited resources in parallel systems. Typical proposed parallel priority queue implementations are based on heaps or skip lists. In recent literature, skip lists have been shown to be the most efficient design choice for implementing priority queues. Though numerous intricate implementations of skip list based queues have been proposed in the literature, their performance is constrained by the high number of global atomic updates per operation and the high memory consumption, which are proportional to the number of sub-lists in the queue. In this part of the thesis, we propose an alternative approach for designing lock-free linearizable priority queues, that significantly improve memory efficiency and throughput performance, by reducing the number of global atomic updates and memory consumption as compared to skip-list based queues. To achieve this, our new design combines two structures; a search tree and a linked list, forming what we call a Tree Search List Queue (TSLQueue). Subsequently, we analyse and introduce a model for lock-free concurrent data structure access parallelism. The major impediment to scaling concurrent data structures is memory contention when accessing shared data structure access points, leading to thread serialisation, and hindering parallelism. Aiming to address this challenge, a significant amount of work in the literature has proposed multi-access techniques that improve concurrent data structure parallelism. However, there is little work on analysing and modelling the execution behaviour of concurrent multi-access data structures especially in a shared memory setting. In this part of the thesis, we analyse and model the general execution behaviour of concurrent multi-access data structures in the shared memory setting. We study and analyse the behaviour of the two popular random access patterns: shared (Remote) and exclusive (Local) access, and the behaviour of the two most commonly used atomic primitives for designing lock-free data structures: Compare and Swap, and, Fetch and Add

Challenges of 3D Surface Reconstruction in Capsule Endoscopy

There are currently many challenges specific to three-dimensional (3D) surface reconstruction using capsule endoscopy (CE) images. There are also challenges specific to viewing the content of CE reconstructed 3D surfaces for bowel disease diagnosis purposes. In this preliminary work, the author focuses on the latter and discusses the effects such challenges have on the content of reconstructed 3D surfaces from CE images. Discussions are divided into two parts. The first part focuses on the comparison of the content of 3D surfaces reconstructed using both preprocessed and non-preprocessed CE images. The second part focuses on the comparison of the content of 3D surfaces viewed at the same azimuth angles and different elevation angles of the line of sight. Experiments-based conclusion suggests 3D printing as a solution to the line of sight and 2D screen visual restrictions.Comment: 5 pages, 3 figure