23,430 research outputs found

    On Machine Capacitance Dimensional and Surface Profile Measurement System

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    A program was awarded under the Air Force Machine Tool Sensor Improvements Program Research and Development Announcement to develop and demonstrate the use of a Capacitance Sensor System including Capacitive Non-Contact Analog Probe and a Capacitive Array Dimensional Measurement System to check the dimensions of complex shapes and contours on a machine tool or in an automated inspection cell. The manufacturing of complex shapes and contours and the subsequent verification of those manufactured shapes is fundamental and widespread throughout industry. The critical profile of a gear tooth; the overall shape of a graphite EDM electrode; the contour of a turbine blade in a jet engine; and countless other components in varied applications possess complex shapes that require detailed and complex inspection procedures. Current inspection methods for complex shapes and contours are expensive, time-consuming, and labor intensive

    Variables Predicting the Severity of a Mass Shooting: the connection to white supremacy

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    Since mass shootings have become increasingly relevant in today’s society, the subject of what makes a mass shooting deadly has become more and more popular. This project focuses on how selected variables correlate with the severity of a mass shooting, and especially focuses on the impact of white supremacy ideology. Theoretically, a shooter imbued with this ideology will likely be more violent, thus causing a higher victim count (injuries + deaths). The other variables included in the model are: the use of a long gun, the use of multiple guns, the use of semi-automatic guns, mental illness, and shooter suicide. This project seeks to assess the relationships of these variables to the victim count, and the statistical significance of each of these relationships. By drawing from two prominent mass-shooting databases and associated media sources, a dataset was constructed, then analyzed with correlation, regression, and ANOVA. These analyses confirmed all of the hypotheses, with predictor variable correlating positively and significantly to victim count. Most importantly, the findings confirmed the significance of the white supremacy ideology variable in predicting the violence of a mass shooting, and the effect withstood the introduction of a variety of important control variables; in short, shooters with a white supremacy background tend to inflict a higher victim count during a mass shooting. Based on these findings, suggestions for further research include separating active-shooter mass shootings from other types of mass shootings; standardizing the operational definition of a mass shooting; and increasing the number of possible predictor variables in current mass shooting databases

    Populist Strategies in African Democracies

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    Drawing on insights from Latin America, this paper examines the factors that contributed to the use of populist strategies by political parties during recent presidential elections in Kenya, South Africa, and Zambia. Specifically, the paper argues that the nature of party competition in Africa, combined with rapid urbanization and informalization of the labour force, provided a niche for populist leaders to espouse a message relevant to the region’s growing urban poor. Simultaneously, such leaders employed ethno-linguistic appeals to mobilize a segment of rural voters who could form a minimum winning coalition in concert with the urban poor and thereby deliver sizeable electoral victories. While such strategies are similar to those used by Latin American populists, the paper highlights key contrasts as well. By combining crossregional and sub-national perspectives, this paper therefore aims to contribute to a better understanding of how demographic and socioeconomic changes in Africa intersect with voting behaviour and political party development.Africa, democratization, political parties, populism, urbanization, voting behaviour

    Asymptotic Normality of Degree Counts in a Preferential Attachment Model

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    Preferential attachment is a widely adopted paradigm for understanding the dynamics of social networks. Formal statistical inference,for instance GLM techniques, and model verification methods will require knowing test statistics are asymptotically normal even though node or count based network data is nothing like classical data from independently replicated experiments. We therefore study asymptotic normality of degree counts for a sequence of growing simple undirected preferential attachment graphs. The methods of proof rely on identifying martingales and then exploiting the martingale central limit theorems
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