Vernacular perceptions of masculinity and fatherhood among Newfoundland offshore workers and their families

My thesis is an ethnographic study of how offshore workers of Newfoundland and Labrador, as well as their families, express and reflect upon traditional Newfoundland constructs of fatherhood and masculinity through narrative and ritual. With a schedule that often involves a constant shift between home and away, offshore workers in the province take part in high-risk professions in order to provide for their families back home. These professions, and their associated lifestyles, involve the incorporation of routine strategies that allows family culture to maintain itself. At the same time, these professions largely carry on a tradition of hegemonically masculine practices, albeit in a newer context. Drawing on a blend of literary and ethnographic research based on the Avalon Peninsula, I utilize examples of current Newfoundland culture to describe how nostalgic memoirs of outport Newfoundland create models of hegemonically masculine fatherhood in the province. I go on to explain how those models manifest themselves in the experiences of current offshore workers, and how they affect their spouses and children. Furthermore, through examining how young adults with offshore-working parents describe their experiences of their fathers, it is possible to see how the effects of local hegemonic masculinities are manifested through narratives about fathers who worked away from home.

Industrial fault detection and diagnosis using Bayesian belief network

Rapid development in industry have contributed to more complex systems that are prone to failure. In applications where the presence of faults may lead to premature failure, fault detection and diagnostics tools are often implemented. The goal of this research is to improve the diagnostic ability of existing FDD methods. Kernel Principal Component Analysis has good fault detection capability, however it can only detect the fault and identify few variables that have contribution on occurrence of fault and thus not precise in diagnosing. Hence, KPCA was used to detect abnormal events and the most contributed variables were taken out for more analysis in diagnosis phase. The diagnosis phase was done in both qualitative and quantitative manner. In qualitative mode, a networked-base causality analysis method was developed to show the causal effect between the most contributing variables in occurrence of the fault. In order to have more quantitative diagnosis, a Bayesian network was constructed to analyze the problem in probabilistic perspective.