1522 research outputs found
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The 20-Year Strategy for the Irish Language and the Irish Speaking Communities: an Ethnographic Investigation
Get PDFThis study examines the impact of the ‘20 Year Strategy for the Irish Language 2010-2030’. This policy works toward the promotion and revival of Irish language usage in Ireland, particularly in the Gaeltacht (Irish speaking) regions. The research aims at ascertaining how this policy has been received by the population and assessing its effects, so far, on Irish speaking communities. Taking an ethnographic approach, the research involved participant observation and interviews conducted at twelve sites covering a variety of locations, including villages, towns and islands located in the seven Gaeltacht regions. Initial findings show the heterogeneous character of Irish-speaking regions problematic for centrally imposed policy
Service Innovation Diagnostics: Guidelines for Developing and Validating a Measure of Service Innovation Capability Maturity
Get PDFSuccess does not depend on singular, discrete service innovations, but the ability to achieve them repeatedly and continuously, labelled service innovation capability (Lillis et al., 2015) • Organisations are unable to diagnose their service innovation capability performance (Hogan et al., 2011) • Lack of measures that observe guidelines in their development and that neglect the assessment of maturity, or sophistication with which this capability is execute
THE MEDIATING ROLE OF OPTIMISM ON THE RELATIONSHIP BETWEEN LEADER MEMBER EXCHANGE (LMX) AND EMPLOYEE ENGAGEMENT: EVIDENCE FROM THE IRISH FURTHER EDUCATION AND TRAINING (FET) SECTOR
Get PDFEmployee engagement is recognised as a facilitator of positive work performance and greater employee wellbeing. As such fostering employee engagement is of significant interest to Further Education and Training (FET) organisational leaders, as they seek a competitive advantage in the sector. Whilst the connection between leadership and employee engagement has been identified, the role of the leader in fostering employee engagement has received limited research attention. The significance of this study lies in its particular focus on the perceived impact of the dyadic exchange relationship between the leader and the follower on employee engagement through the mediating mechanism of optimism. Optimism is recognised as a personal resource linked to multiple organisational outcomes including employee engagement. Prior studies have confirmed it as a direct predictor of employee engagement and as mediating mechanism in the leadership and engagement relationship. A deductive, quantitative approach was used and data was gathered from 156 respondents in three Education and Training Boards (ETBs) using an online survey. Subsequent regression and mediation analysis revealed that optimism is mediating between LMX and Employee engagement at the 95% level. In addition, optimism is also found to mediate between components of LMX and Employee Engagement. This study makes a practical contribution by facilitating a new understanding of the pivotal role of high quality LMX relationships between managers and FET teaching staff in driving employee engagement. An understanding of findings confirming the differential value of LMX currencies and LMX as a distal predictor of employee engagement through optimism will support FET leaders seeking to drive employee engagement in their organisations. The theoretical contribution of this study is based on its position as the first study to confirm that optimism mediates the LMX and employee engagement relationship. In this way it builds on the work of prior studies which confirmed LMX as a predictor of employee engagement
An investigation into the effect of alcohol consumption on health status and health care utilization in Ireland
Get PDFThis paper presents a study of the effect of alcohol consumption on individual health status and health care utilization in Ireland using the 2007 Slán National Health and Lifestyle Survey, while accounting for the endogenous relationship between alcohol and health. Drinkers are categorized as those who never drank, non-drinkers, moderate drinkers, or heavy drinkers, based on national recommended weekly drinking levels in Ireland. The drinking-status equation is estimated using an ordered probit model. Predicted values for the inverse mills ratio are generated, which are then included in the health and health-care utilization equations. Differences in health status for each category of drinker are examined, and the relationship between both alcohol consumption and health with a host of other personal and socio-economic variables is also identified. Given that the measure of health status available is self-assessed, the effect of alcohol consumption on health-care utilization is also analyzed as an alternative measure of health. Findings show that in Ireland, moderate drinkers enjoy the best health status. More moderate drinkers report having very good or excellent health compared with heavy drinkers, non-drinkers, or those who never drank. While heavy drinkers do not report having as good a health status as moderate drinkers, they are better off in terms of health when compared with non-drinkers and those who are lifetime abstainers
Non-dietary determinants and correlates of plasma concentrations of lutein and zeaxanthin in an Irish population
Get PDFThe macula is a specialised area of the retina that mediates central and colour vision. Three dietary carotenoids, lutein (L), zeaxanthin (Z) and meso-zeaxanthin (MZ), accumulate in the macula, where they are collectively referred to as macular pigment (MP). Age-related macular degeneration (AMD) is a disease of the macula that, in its advanced stage, results in a loss of central vision. The light-filtering and antioxidant properties of MP render this pigment important for optimising visual function and protecting against AMD. The current investigation (conducted as part of The Irish Longitudinal Study on Ageing [TILDA]) is the first study to report plasma concentrations of L and Z in a large representative sample of the Irish population. TILDA is a comprehensive study on the health, economic and social status of over 8,000 Irish adults aged 50 years and over. The main focus of this study was to quantify and assess plasma concentrations of L and Z from TILDA participants, and investigate their association with the prevalence of AMD, and non-dietary determinants of these carotenoids. Firstly, the findings from this study indicated that plasma concentrations of L and Z are lower in association with indicators of a poor lifestyle (high BMI, tobacco use, and less physical exercise) and lower education, indicating that modifying lifestyle in a positive way is likely to be reflected in higher concentrations of plasma carotenoids with consequential health benefits. The second part of this study indicated that plasma concentrations of L and Z were significantly higher in association with grading-confirmed presence of AMD and awareness (self-report) of AMD, which is likely due to greater supplement use in these participants. This research will contribute to the existing scientific literature, and will hopefully guide healthcare and medical practice regarding the importance of macular carotenoids for eye health and general wellbeing
Oidhreacht na nDéise: A Study of the Music of the Déise 1800-1950 Volumes 1 & 2
No full textThe subject of this study is the exploration of the musical heritage of the Déise region of the south-east of Ireland from c.1800-1950. A number of music manuscripts, published music collections and audio music collections made in the Déise region, in the above time period, were analysed in this study to determine the nature of the music, its role in Déise society and the role of the collectors in the music’s representation. This thesis discusses the nature of the music in the Déise region: song, instrumental music and dance. Song in the Déise region was sung principally in the Irish language and consisted of songs composed by Gaelic poets from the 18th century and locally composed songs from within the Déise community. Instrumental music consisted largely of dance music but also contained popular Scottish songs and stage music. Various dance types, from the allemande to the hornpipe, existed in the Déise region throughout the time period of this study. Information regarding this wide array of dances is extrapolated from the catalogues of the handwritten manuscripts included in the accompanying appendices, while the contents of the audio and published collections are included in the text. While the repertoire contained within the extant music collections from the Déise region is considerable, this repertoire was not significantly different from the music collected elsewhere in Ireland during the same period. The music played in the Déise region at the beginning of the 19th century, however, differed somewhat from that played in the 20th century. Due to the similarity of repertoire between the Déise and general Irish music repertoires in the stated time period, this study’s examination of the developing or changing Déise repertoire is indicative of the corresponding developments or changes in the greater Irish repertoire. It has been shown in this study that music fulfilled two roles in Déise society. Music was a projection of an immediate Déise communal identity and it also projected a broader Gaelic cultural identity. These ‘identity markers’ of the Déise people are gleaned from the Déise music collections which, therefore, place the collectors themselves primarily in the role of custodians of the music and, indirectly, custodians of the cultural identity of the Déise people themselves. While there have been other studies of Déise music undertaken, they were often of a limited nature which addressed only a particular aspect of the region’s musical heritage. This thesis, however, provides a comprehensive study of the musical heritage of the entire Déise region from c. 1800 to 1950
Modeling Learning Automata based classifification algorithms
Get PDFLearning Automata is extensively used as a tool by researchers to achieve solutions to various problems pertaining to engineering. One such application is a learning automata based classi- fication algorithm. However, at present, learning automata based classifiers have been limited to only 2-class classification. In this research two learning automata based models, for multi- class classification, have been presented. The performance of the proposed techniques has been evaluated using data sets that are extensively used for benchmarking purposes. Since the ultimate goal of an efficient model is to be accurate with low computational complexity, both the performance and complexity of the proposed techniques have been evaluated us- ing the benchmark data sets. Furthermore, the performance of the proposed model has been compared to the performance of existing and extensively used machine learning algorithms on the same benchmark data sets. Apart from modeling and testing the algorithms, the present research also proposes a methodology for evaluating the performance of machine learning algorithms. A detailed study of the existing performance evaluation techniques for machine learning algorithms has been provided; highlighting their drawbacks and then proposing a simple and efficient technique for evaluating their performance. For both pieces of the work, i.e. both the proposed learning automata based multi-class classification algorithms and the performance evaluation methodology, the theoretical analysis has been carried out in a tight mathematical framework supported by simulation results. A theoretical background of learn- ing automata has also been provided, along with a description of the evolution of the proposed algorithms from the basics of learning automata theory
Designing a Domestic Heating Product for Older people Within the Concept of ‘Contained Living Spaces’
Get PDFA Collaborative Mobile Sensing Framework using Mobile Cloud Computing
Get PDFThe ubiquity of mobile devices, tablets, wearables and other smart devices, with ever-more
capable embedded sensors, has accelerated the use of mobile sensing applications. These
applications harness the processed sensor data to offer a more context-aware and
personalized user-experience for purposes including healthcare, entertainment,
environmental monitoring and promoting socialization.
However, the resource limitation of mobile devices creates a significant bottleneck for the
realization of such applications. In this scenario, Mobile Cloud Computing (MCC) is a
promising solution that allows the offload of raw or pre-processed sensed data to the
application logic hosted in the cloud. This research utilizes the scalability and processing
capabilities of MCC to present an intelligent framework that readily supports collaborative
sensing and provides efficient collection of the sensed data, whilst conserving the energy of
the mobile devices and meeting the performance constraints of applications.
The benefits of this collaborative sensing framework include the capability to satisfy
multiple mobile applications with optimal sensing using minimal number of mobile devices,
context-driven reporting of sensed data to the application cloud, and achieving all of this in
an energy efficient manner