Statistics (Scholarly Publications) http://hdl.handle.net/2262/202 2013-05-25T03:46:06Z 2013-05-25T03:46:06Z DREW, EILEEN PATRICIA HUMBERT, ANNE LAURE http://hdl.handle.net/2262/64128 2012-07-04T16:00:33Z 2010-11-01T00:00:00Z

Title: Squaring the Circle? Work and Family Issues among Owners of Small Business Author: DREW, EILEEN PATRICIA; HUMBERT, ANNE LAURE Editor: ISBE Abstract: This paper addresses the largely under-researched theme of how entrepreneurs in Ireland manage their business lives in parallel with their family commitments, with specific reference to dependent children. Since the emergence of dual earner couples as ‘typical’, there has been an expanding attention to the working lives of parents and the issue of work-family conflict in the context of employment. This strand of literature sought to explain patterns of working, e.g. sector of employment, hours of work and flexibility, in terms of highly gendered preferences. The discourse has moved from woman/mother/family-friendly to more gender neutral work-life balance (WLB), in tracking the responses of organisations to the needs of their employees, in the broader context of ability to provide family care. Some research examined both sides of the ‘reconciliation’ divide by surveying the needs of employers and employees (O’Brien and Shemilt, 2003; Drew et al, 2003). These and subsequent studies noted that even in organisations with well developed policies in place, take-up of WLB arrangements was highly gendered and associated with lower level occupations (clerical/administrative). It has been further observed that, in an Irish context, managers fail to lead by example (Drew and Murtagh, 2005) and often adopt a gatekeeping role in the practice and availability of WLB arrangements for themselves and their staff (Drew and Daverth, 2009). With the growth of smaller enterprises a gap is evident in our knowledge of how entrepreneurs behave in their unique multi-functional roles (as owner employer/employee), particularly when they become parents. Description: PUBLISHED

2010-11-01T00:00:00Z WILSON, SIMON PAUL http://hdl.handle.net/2262/64036 2012-06-27T11:37:53Z 2011-01-01T00:00:00Z

Title: Estimating production test properties from test measurement data Author: WILSON, SIMON PAUL Abstract: A complex sequence of tests on components and the system is a part of many manufacturing processes. Statistical imperfect test and repair models can be used to derive the properties of such test sequences but require model parameters to be specified. We describe a technique for estimating such parameters from typical data that are available from past testing. A Gaussian mixture model is used to model the wide variety of statistical properties of test data, including outliers, multi-modality and skewness, from which test properties are derived. Model fitting is through a Bayesian approach, implented by Markov chain Monte Carlo. Description: PUBLISHED

2011-01-01T00:00:00Z HOULDING, BRETT http://hdl.handle.net/2262/63770 2012-06-18T15:23:40Z 2012-01-01T00:00:00Z

Title: Nonparametric Predictive Utility Inference Author: HOULDING, BRETT Abstract: We consider the natural combination of two strands of recent statistical research, i.e., that of decision making with uncertain utility and that of Nonparametric Predictive Inference (NPI). In doing so we present the idea of Nonparametric Predictive Utility Inference (NPUI), which is suggested as a possible strategy for the problem of utility induction in cases of extremely vague prior information. An example of the use of NPUI within a motivating sequential decision problem is also considered for two extreme selection criteria, i.e., a rule that is based on an attitude of extreme pessimism and a rule that is based on an attitude of extreme optimism. Description: IN_PRESS

2012-01-01T00:00:00Z WALSH, CATHAL DOMINIC http://hdl.handle.net/2262/60817 2013-03-29T20:31:16Z 2011-01-01T00:00:00Z

Title: Bayesian Calibration of a Natural History Model with Application to a Population Model for Colorectal Cancer Author: WALSH, CATHAL DOMINIC Abstract: Background. Cancer natural history models are essential when evaluating screening/preventative interventions or changes to diagnostic pathways. Natural history models commonly use a state transition structure, but it is often not possible to observe the state transition probabilities required for parameterization. Aim. The work aimed to accurately represent the uncertainty in the parameters of a state transition model for the natural history of colorectal cancer by embedding the problem in the framework of Bayesian inference. Methods. The Metropolis-Hastings algorithm was used to estimate natural history parameters and screening test characteristics by generating multiple sets of parameters from the posterior distribution, which is the probability distribution that is compatible with the observed data. Observed data included colorectal cancer incidence categorized by age and stage, autopsy data on polyp prevalence, and cancer and polyp detection rates from the first round of screening with the fecal occult blood test in England. The approach was implemented using Visual Basic. Results. The results were subsequently examined for convergence using the package CODA in R 2.8.0. Outputs from fitting were samples from the joint posterior distribution of the natural history parameters given the epidemiological data. The parameter sets obtained are shown to have a good fit to all the observed data sets. These parameter sets are used when running probabilistic sensitivity analysis. Conclusion. The advantages of this strategy are that it draws efficiently from a high-dimensional correlated parameter space. The algorithm is simple to code and runs overnight on a standard desktop PC. Using this method, the parameter sets are drawn according to their posterior probability given calibration data, and thus they correctly summarize the residual uncertainty in the parameter space. Description: PUBLISHED

2011-01-01T00:00:00Z GARRETA, VINCENT http://hdl.handle.net/2262/54922 2011-05-19T15:50:10Z 2011-01-01T00:00:00Z

Title: Calibration of cosmogenic 36Cl production rates from Ca and K spallation in lava flows from Mt. Etna (38°N, Italy) and Payun Matru (36°S, Argentina) Author: GARRETA, VINCENT Abstract: Published cosmogenic 36Cl production rates from Ca and K spallation differ by almost a factor of 2. In this paper we determine production rates of 36Cl from Ca and K in samples of known age containing little Cl. Ca-rich plagioclases and K-feldspars were separated from a total of 13 samples collected on the surfaces of four basaltic lava flows at Mt. Etna (38°N, Italy) and from a trachyte lava flow at Payun Matru volcano (36°S, Argentina). Eruption ages, determined by independent methods, range between 0.4 and 32 ka. Sample site elevations range between 500 and 2500 m. Corresponding scaling factors were calculated using five different published scaling models, four of which consider paleo-geomagnetic field variations integrated over the exposure durations. The resulting five data sets were then analyzed using a Bayesian statistical model that incorporates the major inherent uncertainties in a consistent way. Spallation production rates from Ca and K, considering all major uncertainties, are 42.2 ± 4.8 atoms 36Cl (g Ca)-1a-1 and 124.9 ± 8.1 atoms 36Cl (g K)-1a-1 normalized to sea level and high latitude using the scaling method of Stone (2000). Scaling models that account for paleo-geomagnetic intensity changes yield very similar mean values (at most +4%). If the uncertainties in the independent ages are neglected in the Bayesian model, the calculated element specific production rates would be about 12% higher. Our results are in agreement with previous production rate estimations both for Ca and K if only low Cl (i.e. 20 ppm) samples are considered. Description: PUBLISHED

2011-01-01T00:00:00Z DREW, EILEEN PATRICIA http://hdl.handle.net/2262/54445 2011-04-04T10:10:42Z 2011-01-01T00:00:00Z

Title: Who's Minding the Kids? Work and Family Issues among Owners of Small Business Enterprises in Ireland Author: DREW, EILEEN PATRICIA Editor: Cary Cooper and Ron Burke Abstract: This chapter addresses the largely under-researched theme of how entrepreneurs in Ireland manage their business lives in parallel with their family commitments, with specific reference to dependent children. Since the emergence of dual-earner couples as “typical”, there has been an expanding attention to the working lives of parents and the issue of work–family conflict in the context of employment. This strand of literature sought to explain patterns of working, for example, sector of employment, hours of work and flexibility, in terms of highly gendered preferences. The discourse has moved from woman/mother/family-friendly to more gender-neutral work–life balance (WLB), in tracking the responses of organizations to the needs of their employees, in the broader context of ability to provide family care. Some research examined both sides of the “reconciliation” divide by surveying the needs of employers and employees (Drew et al., 2003; O’Brien & Shemilt, 2003). These and subsequent studies noted that even in organizations with well-developed policies in place, take-up of WLB arrangements was highly gendered and associated with lower-level occupations (clerical/administrative). It has been further observed that, in an Irish context, managers fail to lead by example (Drew & Murtagh, 2005) and often adopt a gatekeeping role in the practice and availability of WLB arrangements for themselves and their staff (Drew & Daverth, 2009). With the growth of smaller enterprises a gap is evident in our knowledge of how entrepreneurs behave in their unique multi-functional roles (as owner employer/employee), particularly when they become parents. Description: PUBLISHED; Cheltenham, UK. Northampton, MA, USA; Series: New Horizons in Management

2011-01-01T00:00:00Z HARDIMAN, ORLA MC LAUGHLIN, RUSSELL BEDE, PETER WALSH, CATHAL DOMINIC http://hdl.handle.net/2262/53330 2013-03-29T20:26:46Z 2011-01-01T00:00:00Z

Title: Rate of familial amyotrophic lateral sclerosis: a systematic review and meta-analysis. Author: HARDIMAN, ORLA; MC LAUGHLIN, RUSSELL; BEDE, PETER; WALSH, CATHAL DOMINIC Abstract: Background The population rate of familial amyotrophic lateral sclerosis (FALS) is frequently reported as 10%. However, a systematic review and meta-analysis of the true population based frequency of FALS has never been performed. Method A Medline literature review identified all original articles reporting a rate of FALS. Studies were grouped according to the type of data presented and examined for sources of case ascertainment. A systematic review and meta-analysis of reported rates of FALS was then conducted to facilitate comparison between studies and calculate a pooled rate of FALS. Results 38 papers reported a rate of FALS. Thirty-three papers were included in analysis and the rate of FALS for all studies was 4.6% (95% CI 3.9% to 5.5%). Restricting the analysis to prospective population based registry data revealed a rate of 5.1% (95% CI 4.1% to 6.1%). The incidence of FALS was lower in southern Europe. There was no correlation between rate of FALS and reported SOD1 mutation rates. Conclusion The rate of FALS among prospective population based registries is 5.1% (CI 4.1 to 6.1%), and not 10% as is often stated. Further detailed prospective population based studies of familial ALS are required to confirm this rate. Description: PUBLISHED

2011-01-01T00:00:00Z DAHYOT, ROZENN http://hdl.handle.net/2262/52985 2011-03-03T17:21:26Z 2005-01-01T00:00:00Z

Title: Workshop on Machine Learning Techniques for Processing Multimedia Content Author: DAHYOT, ROZENN Editor: Matthieu Cord Pádraig Cunningham Rozenn Dahyot Tamás Szirányi Abstract: Machine Learning (ML) techniques are used in situations where data is available in electronic format and ML algorithms can ’add value’ by analysing this data. This is the situation with the processing of multimedia content. The ’added value’ from ML can take a number of forms: • by providing insight into the domain from which the data is drawn, • by improving the performance of another process that is manipulating the data, • by organising the data in some way or • by helping to interpret multimedia content to make it more understandable. This potential for ML to add value in processing of multimedia content has made this one of the most popular application areas for ML research. Multimedia content has some characteristics that place specific demands on ML. The data is typically of very high dimension and dimension reduction is often required. The normal distinction between supervised and unsupervised techniques doesn’t always apply; it is often the case that only some of the data is labeled or the user may assist in labeling the data during processing. Typically the ML process is preceded by a feature extraction stage and the success of the ML stage will often depend on the feature extraction. This workshop on Machine Learning Techniques for Processing Multimedia Content has been organized because of these special issues that arise with multimedia data. We have papers describing applications in image processing, video analysis and music classification. The research described in these papers has drawn on a wide range of ML techniques. It is hoped that this workshop will help identify important research directions for Machine Learning that will help in the processing of multimedia content. Description: Proceedings of the Workshop on Machine Learning Techniques for Processing Multimedia Content 2005

2005-01-01T00:00:00Z HOULDING, BRETT http://hdl.handle.net/2262/41149 2010-11-13T03:02:28Z 2011-01-01T00:00:00Z

Title: Adaptive utility and trial aversion Author: HOULDING, BRETT Abstract: Decision making with adaptive utility provides a generalisation to classical Bayesian decision theory, allowing the creation of a normative theory for decision selection when preferences are initially uncertain. In this paper we address some of the foundational issues of adaptive utility as seen from the perspective of a Bayesian statistician. The implications that such a generalisation has upon the traditional utility concepts of value of information and risk aversion are also explored, with a new concept of trial aversion introduced that is similar to risk aversion, but which concerns a decision maker's aversion to selecting decisions with high uncertainty over resulting utility. Description: PUBLISHED

2011-01-01T00:00:00Z WILSON, SIMON PAUL http://hdl.handle.net/2262/40592 2010-08-30T12:49:48Z 2009-01-01T00:00:00Z

Title: Modeling and adapting production environmental stress testing Author: WILSON, SIMON PAUL Abstract: This study describes the production sampling environmental stress test (PSEST) process and the offline analysis conducted. Some of the key characteristics and parameters of the test are outlined. The analytical process is based on two types of regression model, each of which links a dependent variable (the log of time to failure in each dwell, or the log of the number failed in each dwell) to independent variables such as temperature and age. These two types of regression are known as Weibull regression1 and Poisson regression.2 Using the estimated regression coefficients, expressions for the probability distribution of a unit under test can be written and used to optimize the test duration. Description: PUBLISHED

2009-01-01T00:00:00Z