2 resultados para Competitiveness of Finnish Wind Power Industry
em DRUM (Digital Repository at the University of Maryland)
Resumo:
Mental illness affects a sizable minority of Americans at any given time, yet many people with mental illness (hereafter PWMI) remain unemployed or underemployed relative to the general population. Research has suggested that part of the reason for this is discrimination toward PWMI. This research investigated mechanisms that affect employment discrimination against PWMI. Drawing from theories on stigma and power, three studies assessed 1) the stereotyping of workers with mental illness as unfit for workplace success, 2) the impact of positive information on countering these negative stereotypes, and whether negatively-stereotyped conditions elicited discrimination; and 3) the effects of power on mental illness stigma components. I made a series of predictions related to theories on the Stereotype Content Model, illness attribution, the contact hypothesis, gender and mental health, and power. Studies tested predictions using, 1) an online vignette survey measuring attitudes, 2) an online survey measuring responses to fictitious applications for a middle management position, and 3) a laboratory experiment in which some participants were primed to feel powerful and some were not. Results of Study 1 demonstrated that PWMI were routinely stigmatized as incompetent, dangerous, and lacking valued employment attributes, relative to a control condition. This was especially evident for workers presented as having PTSD from wartime service and workers with schizophrenia, and when the worker was a woman. Study 2 showed that, although both war-related PTSD and schizophrenia evoke negative stereotypes, only schizophrenia evoked hiring discrimination. Finally, Study 3 found no effect of being primed to feel powerful on stigmatizing attitudes toward a person with symptoms of schizophrenia. Taken together, findings suggest that employment discrimination towards PWMI is driven by negative stereotypes; but, stereotypes might not lead to actual hiring discrimination for some labeled individuals.
Resumo:
Common building energy modeling approaches do not account for the influence of surrounding neighborhood on the energy consumption patterns. This thesis develops a framework to quantify the neighborhood impact on a building energy consumption based on the local wind flow. The airflow in the neighborhood is predicted using Computational Fluid Dynamics (CFD) in eight principal wind directions. The developed framework in this study benefits from wind multipliers to adjust the wind velocity encountering the target building. The input weather data transfers the adjusted wind velocities to the building energy model. In a case study, the CFD method is validated by comparing with on-site temperature measurements, and the building energy model is calibrated using utilities data. A comparison between using the adjusted and original weather data shows that the building energy consumption and air system heat gain decreased by 5% and 37%, respectively, while the cooling gain increased by 4% annually.