Revisiting Irish poetic modernisms

This thesis discusses Irish Modernist poetry written between 1905 and 1970, specifically the poetry of Joseph Campbell (1879-1944), Thomas MacGreevy (1893-1967), Denis Devlin (1908-1959) and Brian Coffey (1905-1995). All four poets have been largely neglected in criticism until a growth of interest encouraged by Michael Smith and Trevor Joyce’s New Writers’ Press during the 1970s. J.C.C. Mays, Stan Smith, Susan Schreibman, Terence Brown, Patricia Coughlan and Alex Davis published subsequent critical support during the ‘80s and ‘90s. My research aims to highlight poetry previously omitted from the canon of Irish literature, those with connections to British or continental European literary movements as well as poetry by women writers and writers from the North. Part of this exploration of Irish Poetic Modernisms involves an investigation of intersections between poetic modernisms and Irish war poetry and of depictions of Irish masculinity in the poetry of Devlin and Coffey. My discussion of Campbell’s poetry focuses on links between the early regional modernism of his poetry and later Irish modernist poetry, including his participation in the Ulster Literary Theatre, with the Literary Revival community in Dublin and his association with the proto-Imagist movement in London. My examination of connections between Irish war poetry and Irish modernism allows me to discuss the writing of several underrecognized Irish poets who are contemporaries and near contemporaries of the main subjects of my thesis. Thomas MacGreevy’s poetry is the most clear case study of the links between Irish modernist poetry and poetry about Ireland’s participation in the Great War. MacGreevy’s writing reveals his multiple allegiances: he both elegizes and challenges the increasing cultural inhibitions of Free State Ireland. Denis Devlin’s poetic portrayals of Ireland reveal his rejection both of the Literary Revival’s fascination with Celticism and of Dublin’s literary community while upholding tradition poetic gender roles. My research explores representations of masculinity and Irish politics, including heroic masculine imagery, in the long poems of Devlin and Coffey. My discussion of Brian Coffey considers the importance of the figure of the “poet as maker” to his writing and his relationship with Ireland during his long writing career. I also consider his role as the editor and executor of Devlin’s literary estate and the impact that had on both the latter’s posthumous reputation and Coffey’s later writing.

The lived experience of Irish diocesan priests. A qualitative study of clerical identity, obedience and celibacy.

The main aim of this thesis is to document and explore the lived experience of Irish diocesan priests and former priests, in order to explore the reality of diocesan priesthood in contemporary Ireland, and to investigate how, if at all, diocesan priesthood has changed in Ireland during the past fifty years. It sought to do this by interrogating the stories of thirty-three diocesan priests and former priests, and by placing their individual stories within the broader context of Irish society and the Catholic Church, during the fifty-year period, 1962–2012. The research focused on three core areas of priesthood – identity, obedience, and celibacy – and it addressed the following questions. First, how do Irish diocesan priests understand their priesthood and how has this understanding changed over time, if at all? I will argue that three paradigms of priesthood co-exist in the contemporary Irish Church, and that each of these models corresponds with a distinct period in contemporary Irish Church history. I will also demonstrate the existence of underlying similarities in the cultural practice of priesthood that transcend the different generations of priests. Second, how do Irish diocesan priests negotiate their priesthood within a large and complex institution? My study suggests that Irish diocesan priests are typically loyal and obedient. However, they are not necessarily subservient. Third, how do Irish diocesan priests understand and experience celibacy in their day-to-day lives? My study demonstrates that celibacy is typically understood and experienced along a continuum, ranging from total acceptance to total rejection, with most priests somewhere in between. Fourth, I will argue that while priests are experiencing many difficulties in their lives, there is insufficient evidence from the present study to indicate they are experiencing a crisis.

Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer.