Investigating the long term planning framework for the Galway Bay community from climate change.

This research looked at the scientific evidence available on climate change and in particular, projections on sea level rise which ranged from 0.5m to 2m by the end of the century. These projections were then considered in an Irish context. A review of current policy in Ireland revealed that there was no dedicated Government policy on climate change or coastal zone management. In terms of spatial planning policy, it became apparent that there was little or no guidance on climate change either at a national, regional or local level. Therefore, to determine the likely impacts of sea level rise in Ireland based on current spatial planning practice and policy, a scenario-building exercise was carried out for two case study areas in Galway Bay. The two case study areas were: Oranmore, a densely populated town located to the east of Inner Galway Bay; and Tawin Island, a rural dispersed community, located to the south east of Inner Galway Bay. A ‘best’ and ‘worse’ case scenario was envisaged for both areas in terms of sea level rise. In the absence of specific climate change policies it was projected that in the ‘best’ case scenario of 0.5m sea level rise, Tawin Island would suffer serious and adverse impacts while Oranmore was likely to experience slight to moderate impacts. However, in the ‘worse’ case scenario of a 2m sea level rise, it was likely that Tawin Island would be abandoned while many houses, businesses and infrastructure built within the floodplain of Oranmore Bay would be inundated and permanently flooded. In this regard, it was the author’s opinion that a strategic and integrated climate change policy and adaptation plan is vital for the island of Ireland that recognises the importance of integrated land use and spatial planning in terms of mitigation and adaptation to climate change.

Instrumentation and software for the VERITAS Project and the detection of TeV Gamma-Ray Emission from the BL Lacertae Object 1ES1959+650

Transmission of Cherenkov light through the atmosphere is strongly influenced by the optical clarity of the atmosphere and the prevailing weather conditions. The performance of telescopes measuring this light is therefore dependent on atmospheric effects. This thesis presents software and hardware developed to implement a prototype sky monitoring system for use on the proposed next-generation gamma-ray telescope array, VERITAS. The system, consisting of a CCD camera and a far-infrared pyrometer, was successfully installed and tested on the ten metre atmospheric Cherenkov imaging telescope operated by the VERITAS Collaboration at the F.L. Whipple Observatory in Arizona. The thesis also presents the results of observations of the BL Lacertae object, 1ES1959+650, made with the Whipple ten metre telescope. The observations provide evidence for TeV gamma-ray emission from the BL Lacertae object, 1ES1959+650, at a level of more than 15 standard deviations above background. This represents the first unequivocal detection of this object at TeV energies, making it only the third extragalactic source seen at such levels of significance in this energy range. The flux variability of the source on a number of timescales is also investigated.

Design, development and testing of a CAD integrated design for environment software tool.

The research described in this thesis was developed as part o f the Information Management for Green Design (IMA GREE) Project. The 1MAGREE Project was founded by Enterprise Ireland under a Strategic Research Grant Scheme as a partnership project between Galway Mayo Institute o f Technology and C1MRU University College Galway. The project aimed to develop a CAD integrated software tool to support environmental information management for design, particularly for the electronics-manufacturing sector in Ireland.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.