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In predicting environmental hazards or estimating the impact of human activities on the marine ecosystem, scientists have multiplied the need for sample analysis. The classical microscopic approach is time consuming and wastes the talent and intellectual abilities of trained specialists. Therefore, scientists developed an automated optical tool, called a Flow Cytometer (FC), to analyse samples quickly and in large quantities. The flow cytometer has successfully been applied to real phytoplankton studies. However, analysis of the data extracted from samples is still required. Artificial Neural Networks (ANNs) are one of the tools applied to FC data analysis. Despite several successful applications, ANNs have not been widely adopted by the marine biologist community, as they can not possible to change the number of species in the classification problem without retraining of the full system from scratch. Training is time consuming and requires expertise in ANNs. Moreover, most ANN paradigms cannot cope effectively with unknown data, such as data coming from new phytoplankton species or from species outside the scope of the studies. This project developed a new ANN technique based on a modular architecture that removes the need for retraining and allows unknowns to be detected and rejected. Furthermore, the Support Vector Machine architecture is applied in this domain for the first time and compared against another ANN paradigm called Radial Basis Function Networks. The results show that the modular architecture is able to effectively deal with new data which can be incorporated into the ANN architecture without fully retraining the system.

This dissertation explores how scholars have extended Sharon Hays’ (1997) influential work on Intensive Motherhood Ideology (IM). In conceptualizing IM, Dr. Hays proposed that IM ideology leads women in cisgender heterosexual unions to spend more time caregiving despite increased participation in paid work, compared to prior decades. Dr. Hays further asserted IM is a form of resistance to neoliberalism (i.e., capitalism based on a free-market system). However, it is unclear to what degree women are driven by an oppressive ideology and/or are making important social contributions based on conscious choice, which carries important implications for women’s agency. Through content analyses, I examine scholars’ treatment of ideology and agency across IM literature. Additionally, I engage in an autoethnographic study to make meaning of how I perceive women’s (and my) experiences reflected in the literature. Findings suggest limitations and androcentric perspectives that affect our understanding of motherhood. Most scholars focus on how women adhere to IM ideology, rarely why. Authors’ positions on agency are clearly articulated in only a small subset of articles. Participants are often described as adapting to or negotiating with a pervasive ideology within their unique contexts and only some manage to resist. I also find that women’s social constraints are ignored or considered in limited ways. Lastly, such limitations in IM literature risk tainting the larger motherhood literature with such perspectives. Implications of these findings are discussed, and suggestions made to promote a more representative and accurate understanding of women’s lived experience.

This thesis discusses topics in the field of process engineering that have received much attention over the past twenty years, process integration and optimization of energy and environmental systems. It emphasizes the applications of three commercial software tools for process integration, ADVENT, HEXTRAN and SlTPERTARGET, that are readily available to academic users at low costs. Specifically, Chapter 1 presents an overview of the basic concepts used in process integration of energy systems. Chapter 2 compares the use of single and dual temperature-of-approach methods to synthesize energy-optimum and minimum-cost, heat-exchanger networks (HENs), and shows how to implement them using three software tools. Chapters 3 and 4 demonstrate how to optimize the energy recovery in petroleum refinery distillation systems via process integration. Chapter 3 presents an extension to a case study of heat integration of a vacuum distillation system. Chapter 4 describes the detailed synthesis, retrofit and optimization of HENs for a system of atmospheric and vacuum distillation towers, and it represents the first process integration and optimization study of a complex process in petroleum refineries using all three commercial software tools. Chapter 5 presents, through four progressive tutorial examples, a recent conceptual method developed in the field of process integration of environmental systems applied to wastewater minimization and to the design of distributed effluent treatment systems.