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Given the increased reliance on adjunct faculty and the increased demand for online courses, the online adjunct faculty member is an important figure to know and understand. Unfortunately, there is a dearth of research on this population, particularly in terms of how their feelings of connection to their colleagues, administration, and their institution affects their beliefs about their online teaching abilities. This non-experimental correlational study investigated the relationship between sense of belonging and instructor self-efficacy among online adjunct faculty in higher education. Additionally, this study sought to determine if there is a predictive element between these two variables. This study utilized the Organizational Sense of Belonging (OSB) subscale and the Sense of Efficacy for Online Teaching Scale (SEOTS) as well as demographic questions in order to collect data on the study variables. Questionnaires were distributed to online adjunct faculty members from six higher education institutions within the states of Florida, Virginia, and Nevada. A total of 122 online adjunct faculty members completed the questionnaire. Data were analyzed using descriptive analyses, ANOVA, Pearson’s Correlation Coefficient, and regression analysis. Results indicated that sense of belonging and instructor self-efficacy share a significant linear relationship. Additionally, a stronger sense of belonging and a higher instructional self-efficacy were found among participants who participate in universitysponsored faculty development opportunities, who participate in non-academic university events, and who communicate with other online adjunct faculty members through social media. Furthermore, sense of belonging was found to be a significant predictor of selfefficacy, both when controlling for significant variables and when not controlling for variables. Further research is needed to determine causality between sense of belonging and instructor self-efficacy. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

The first essay introduces a portfolio theory motivated approach to measuring mutual fund family-level diversification and hedging strategies. Diversification of idiosyncratic risk (systematic risk) is measured by the average cross-fund correlation in idiosyncratic returns (predicted returns from the multifactor model). Using new methodology, I find evidence of cross-sectional variation in family-level diversification and examine several fund families’ characteristics as the determinants of this crosssectional variation. On average, fund families that offer more objectives are more diversified in terms of both idiosyncratic and systematic risks; however, in the subsample of larger fund families, greater number of objectives is associated with increase (decrease) in idiosyncratic (systematic) risk diversification. Families that concentrate in the retail sector are more diversified. I also find that less diversification of idiosyncratic risk on the family level is associated with better risk-adjusted performance, while greater diversification of systematic risk is associated with greater performance during an economic downturn. The second essay examines whether new measures of diversification are additional determinants of fund family flows and flow volatility. I find that fund family capital flows increase in systematic risk focus, as more of the fund family’s assets are held by institutional investors. Family flow volatility decreases in diversification of systematic risk during market downturn, increase in market uncertainty and during recession. I further find that families with greater concentration in the retail sector (institutional sector) exhibit less family capital flow volatility as the diversification of systematic risk (idiosyncratic risk) increases. Fund-level volatility of focused and concentrated funds within diversified families is greater than in less diversified families, signaling that diversification on the family level may decrease participation costs for the investors. Moreover, in support of participation cost hypothesis, I find that the performance of worst performing funds within fund families increases in the family-level diversification; thus, family-level diversification affects the convexity in the fund flowperformance relation documented in the previous studies. On the family-level, diversification is associated with convexity in flow-performance relation, while family focus with more direct flow-performance relation. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Little Blue Herons, Snowy Egrets, and Tricolored Herons that nest in the Everglades have declined sharply over the past decade, due in part to food resource limitations. Here, I examined the diet of small herons to determine how prey characteristics affected the fitness of small herons in the highly modified Florida Everglades. Analysis of these diet differences showed birds nesting in 2017, a hydrologically dryer-than average year, and a more taxonomically varied diet were associated with nest success and improved body condition of nestlings. Over half (51%) of the fish biomass Little Blue Herons consumed were non-native species, compared to 14% and 19% non-native fish biomass consumed by Snowy Egrets and Tricolored Herons, respectively. Surprisingly, <7% of fish biomass available in the Everglades were comprised of non-native fish species, suggesting that small herons, and Little Blue Herons in particular, may be using alternative foraging habitats, to supplement their dietary needs. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Southeast Florida is a region of the U.S. that is predicted to incur severe damage due to climate change (CC). As a result, one particular grassroots organization created a CC workshop to educate, advocate, and build resiliency locally. Social movement’s literature reveals processes of framing, resource mobilization, and organizational structure that have had successful outcomes locally while climate action literature argues that civil society has been ineffective at creating significant impacts on the global scale of climate policy. In order to expand this literature further, I conducted a research project to examine how different frames presented in CC education influence climate actions in the Southeast Florida region. Using qualitative research methods of participant observations and interviews, my analysis of the data collected suggests that organizers of the workshop used an environmental and climate justice narrative along with a collective action framework, relying on three master frames of place, justice, and power to educate members on CC. Amongst the prognoses presented to members during the education were climate action solutions primarily within the meso (community/civic engagement) level to create structural change within the region. I found that participants interpreted CC to be an issue of 2 places in Southeast Florida, one on the coast and one inland and, thus, depending on which region participants lived, their level of climate action was affected, whether at the individual or community/civic level. Therefore, some participants focused on individual behavioral and household consumer tactics, while other participants worked on community building and creating structural change. Given the unsuccessful nature of local organizations at impacting global climate negotiations and the goal of social movement processes to create change within societal structures, this case study contributes to the growing body of knowledge regarding the influence of climate education on climate actions. / Includes bibliography. / Thesis (M.A.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

A hypothesis for the self-organization of receptive fields throughout the hierarchy of biological vision is empirically tested using simulations of deep artificial neural networks. Results from many fields for topographic organization of receptive fields throughout the visual hierarchy remain disconnected. Although extensive simulation research has been done to model topographic organization in early visual areas, little to no research has investigated such organization in higher visual areas. We propose that parsimonious structured sparsity principles, that permit the learning of topographic receptive fields in simulated visual areas, are sufficient for the emergence of a semantic topology in object-level representations of a deep neural network. These findings suggest wide-reaching implications for the functional organization of the biological visual system and we conjecture that such observed results in nature could serve as the foundation for unsupervised learning of taxonomic and semantic relations between entities in the world. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Lower costs of clean energy generation, the need for a more secure grid, and environmental concerns are leading to create more opportunities for integration of renewable energy resources utilization in the power systems. The recent concept of Microgrid (MG), as a part of the development of smart grid, is required in order to integrate the renewable sources in the utility grid. An MG is described as a small-scale distribution grid that consists of diversified Distributed Energy Resources (DERs), Battery Energy Storage Systems (BESSs), and local flexible loads that typically can either be operated in islanded or grid-connected modes. The optimal utilization control of such an MG system is a challenging task due to the complexity of coordination among the DERs, BESSs and load management possibilities. Therefore, in this dissertation, optimal component sizing and operation of MGs under different operational strategies is proposed. MGs typically consist of Photovoltaic (PV) systems, wind turbines as well as microgas turbines, fuel cells, batteries and other dispatchable generating units. Firstly, a methodology to perform the optimal component sizing for DERs in islanded/grid-tied modes is developed. The proposed optimal algorithm aims to determine the appropriate configuration among a set of components by taking into consideration the system’s constraints. An Iterative optimization technique is proposed in order to minimize the annual cost of energy and cost of emissions including CO2, SO2, and NOx. A case study from South Florida area, given the local weather data and load demand is investigated for the modeling verification. Using the results from optimal component sizes, a day-ahead optimization problem for the operation of an MG under different scenarios is introduced. Also, the objective function is formulated as a constrained non-linear problem. The uncertainties of stochastic variables (solar radiation, wind speed, and load) are modeled and renewable generations and load demand are forecasted. An advanced dynamic programing procedure is proposed to assess various operational policies. The simulation results show the efficiency of the proposed method. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection