Physical and MAC layer techniques for next generation satellite communications

In this thesis, we consider four different scenarios of interest in modern satellite communications. For each scenario, we will propose the use of advanced solutions aimed at increasing the spectral efficiency of the communication links. First, we will investigate the optimization of the current standard for digital video broadcasting. We will increase the symbol rate of the signal and determine the optimal signal bandwidth. We will apply the time packing technique and propose a specifically design constellation. We will then compare some receiver architectures with different performance and complexity. The second scenario still addresses broadcast transmissions, but in a network composed of two satellites. We will compare three alternative transceiver strategies, namely, signals completely overlapped in frequency, frequency division multiplexing, and the Alamouti space-time block code, and, for each technique, we will derive theoretical results on the achievable rates. We will also evaluate the performance of said techniques in three different channel models. The third scenario deals with the application of multiuser detection in multibeam satellite systems. We will analyze a case in which the users are near the edge of the coverage area and, hence, they experience a high level of interference from adjacent cells. Also in this case, three different approaches will be compared. A classical approach in which each beam carries information for a user, a cooperative solution based on time division multiplexing, and the Alamouti scheme. The information theoretical analysis will be followed by the study of practical coded schemes. We will show that the theoretical bounds can be approached by a properly designed code or bit mapping. Finally, we will consider an Earth observation scenario, in which data is generated on the satellite and then transmitted to the ground. We will study two channel models, taking into account one or two transmit antennas, and apply techniques such as time and frequency packing, signal predistortion, multiuser detection and the Alamouti scheme.

Investigation and development of techniques for the characterisation of the synthetic/biological interface

The purpose of this study is to increase our knowledge of the nature of the surface properties of polymeric materials and improve our understanding of how these factors influence the deposition of proteins to form a reactive biological/synthetic interface. A number of surface analytical techniques were identified as being of potential benefit to this investigation and included in a multidisciplinary research program. Cell adhesion in culture was the primary biological sensor of surface properties, and it showed that the cell response to different materials can be modified by adhesion promoting protein layers: cell adhesion is a protein-mediated event. A range of surface rugosity can be produced on polystyrene, and the results presented here show that surface rugosity does not play a major role in determining a material's cell adhesiveness. Contact angle measurements showed that surface energy (specifically the polar fraction) is important in promoting cell spreading on surfaces. The immunogold labelling technique indicated that there were small, but noticeable differences, between the distribution of proteins on a range of surfaces. This study has shown that surface analysis techniques have different sensitivities in terms of detection limits and depth probed, and these are important in determining the usefulness of the information obtained. The techniques provide information on differing aspects of the biological/synthetic interface, and the consequence of this is that a range of techniques is needed in any full study of such a complex field as the biomaterials area.

The production of the enzyme dextransucrase by batch and continuous fermentation techniques

A review of the literature of work carried out on dextransucrase production, purification, immobilization and reactions has been carried out. A brief review has also been made of the literature concerning general enzyme biotechnology and fermentation technology. Fed-batch fermentation of the bacteria Leuconostoc mesenteroides NRRL B512 (F) to produce dextransucrase has formed the major part of this research. Aerobic and anaerobic fermentations have been studied using a 16 litre New Brunswick fermenter which has a 3-12 litre working volume. The initial volume of broth used in the studies was 6 litres. The results of the fed-batch fermentations showed for the first time that yields of dextransucrase are much higher under the anaerobic conditions than during the aerobic fermentations. Dextransucrase containing 300-350 DSU/cm3 of enzyme activity has been obtained during the aerobic fermentations, while in the anaerobic fermentations, enzyme yields containing 450-500 DSU/cm3 have been obtained routinely. The type of yeast extract used in the fermentation medium has been found to have significant effects on enzyme yield. Of the different types studied, the Gistex Standard was found to be the type that favoured the highest enzyme production. Studies have also been carried out on the effect of agitation rate and antifoam on the enzyme production during the anaerobic experiments. Agitation rates of up to 600 rpm were found not to affect the enzyme yield, however, the presence of antifoam in the medium led to a significant reduction in enzyme activity (less than 300 DSU/cm3). Scale-up of the anaerobic fermentations has been performed at up to the 1000 litre level with enzyme yields containing more than 400 DSU/cm3 of activity being produced. Some of the enzyme produced at this scale was used for the first time to produce dextran on an industrial scale via the enzyme route, with up to 99% conversion of sucrose to dextran being obtained. An attempt has been made at continuous dextransucrase production. Cell washout was observed to occur at dilution rates of greater than 0.4 h-1. Dextransucrase containing up to 25 DSU/cm3/h has been produced continuously.

Characterisation and surface-profiling techniques for composite particles produced by dry powder coating in pharmaceutical drug delivery

The production of composite particles using dry powder coating is a one-step, environmentally friendly, process for the fabrication of particles with targeted properties and favourable functionalities. Diverse functionalities, such flowability enhancement, content uniformity, and dissolution, can be developed from dry particle coating. In this review, we discuss the particle functionalities that can be tailored and the selection of characterisation techniques relevant to understanding their molecular basis. We address key features in the powder blend sampling process and explore the relevant characterisation techniques, focussing on the functionality delivered by dry coating and on surface profiling that explores the dynamics and surface characteristics of the composite blends. Dry particle coating is a solvent- and heat-free process that can be used to develop functionalised particles. However, assessment of the resultant functionality requires careful selection of sensitive analytical techniques that can distinguish particle surface changes within nano and/or micrometre ranges.

Projection and interpolation based techniques for structured and impulsive noise filtering

In this chapter we present the relevant mathematical background to address two well defined signal and image processing problems. Namely, the problem of structured noise filtering and the problem of interpolation of missing data. The former is addressed by recourse to oblique projection based techniques whilst the latter, which can be considered equivalent to impulsive noise filtering, is tackled by appropriate interpolation methods.

Visual data mining using principled projection algorithms and information visualization techniques

We introduce a flexible visual data mining framework which combines advanced projection algorithms from the machine learning domain and visual techniques developed in the information visualization domain. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection algorithms, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates and billboarding, to provide a visual data mining framework. Results on a real-life chemoinformatics dataset using GTM are promising and have been analytically compared with the results from the traditional projection methods. It is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework. Copyright 2006 ACM.

Immunoblotting and tear sampling techniques for the study of contact lens-induced variations in tear protein profiles

More information on the biochemical interactions taking place between the tear film and the contact lens is required to further our understanding of the causative mechanisms behind the symptoms of dryness and grittiness often experienced by contact lens wearers. These symptoms can often lead to an intolerance to contact lens wear.

Document understanding using data mining and machine learning techniques

With the explosive growth of the volume and complexity of document data (e.g., news, blogs, web pages), it has become a necessity to semantically understand documents and deliver meaningful information to users. Areas dealing with these problems are crossing data mining, information retrieval, and machine learning. For example, document clustering and summarization are two fundamental techniques for understanding document data and have attracted much attention in recent years. Given a collection of documents, document clustering aims to partition them into different groups to provide efficient document browsing and navigation mechanisms. One unrevealed area in document clustering is that how to generate meaningful interpretation for the each document cluster resulted from the clustering process. Document summarization is another effective technique for document understanding, which generates a summary by selecting sentences that deliver the major or topic-relevant information in the original documents. How to improve the automatic summarization performance and apply it to newly emerging problems are two valuable research directions. To assist people to capture the semantics of documents effectively and efficiently, the dissertation focuses on developing effective data mining and machine learning algorithms and systems for (1) integrating document clustering and summarization to obtain meaningful document clusters with summarized interpretation, (2) improving document summarization performance and building document understanding systems to solve real-world applications, and (3) summarizing the differences and evolution of multiple document sources.

UTILIZATION OF GIS AND SPATIAL ANALYSIS TECHNIQUES IN ARTISANAL AND SMALL SCALE MINING TO LOCATE A CENTRALIZED PROCESSING CENTRE

One of the global phenomena with threats to environmental health and safety is artisanal mining. There are ambiguities in the manner in which an ore-processing facility operates which hinders the mining capacity of these miners in Ghana. These problems are reviewed on the basis of current socio-economic, health and safety, environmental, and use of rudimentary technologies which limits fair-trade deals to miners. This research sought to use an established data-driven, geographic information (GIS)-based system employing the spatial analysis approach for locating a centralized processing facility within the Wassa Amenfi-Prestea Mining Area (WAPMA) in the Western region of Ghana. A spatial analysis technique that utilizes ModelBuilder within the ArcGIS geoprocessing environment through suitability modeling will systematically and simultaneously analyze a geographical dataset of selected criteria. The spatial overlay analysis methodology and the multi-criteria decision analysis approach were selected to identify the most preferred locations to site a processing facility. For an optimal site selection, seven major criteria including proximity to settlements, water resources, artisanal mining sites, roads, railways, tectonic zones, and slopes were considered to establish a suitable location for a processing facility. Site characterizations and environmental considerations, incorporating identified constraints such as proximity to large scale mines, forest reserves and state lands to site an appropriate position were selected. The analysis was limited to criteria that were selected and relevant to the area under investigation. Saaty’s analytical hierarchy process was utilized to derive relative importance weights of the criteria and then a weighted linear combination technique was applied to combine the factors for determination of the degree of potential site suitability. The final map output indicates estimated potential sites identified for the establishment of a facility centre. The results obtained provide intuitive areas suitable for consideration