5 resultados para quantitative traits analysis
em DRUM (Digital Repository at the University of Maryland)
Resumo:
The purpose of this quantitative study was to explore the previously unexamined phenomenon of middle school parental engagement in a large urban/suburban/rural school district of 209 schools in the mid-Atlantic region of the United States. Across 22 middle schools serving grades six-eight, this study collected and examined perceptions of the three key adult stakeholder groups – administrators, teachers, and parents – most actively involved in middle school parental engagement as described within the theoretical framework of academic socialization. Their reports of observable parental engagement activities were used to document how district stakeholders operationalize behaviors that represent the five actionable constructs and three themes of academic socialization to determine how the district “fares” in employing academic socialization as a middle school parent engagement strategy. The study also applied quantitative descriptive analysis through a one-way ANOVA to determine the significance of observable variations in actionable constructs between the perspectives of the three stakeholder groups. Finally, the study illuminated, through regression modeling, when confounding factors/independent variables such as race, income, school size, administrator and teacher experience, parents’ educational background, etc., impacted operationalization of academic socialization behaviors for middle school parent and family engagement. Rejecting the null hypothesis, the study found that the three stakeholder groups had statistically significant differences in perceptions of their implementation of activities aligned to academic socialization. This study ultimately illuminated ways in which these adult stakeholder groups share similar and varied perceptions about their engagement actions that support the achievement and maturation of middle school students. Significantly, this study provided key findings that illuminated areas that can be systemically addressed to transform middle school parent engagement practices through applied academic socialization theory into consistent and effective collaborative efforts between the home and school. The process of operationalizing academic socialization was outlined in terms that any school or district can follow to improve programs and practices of middle school parental engagement to serve in the best interests of students during this period of great transition for both child/adolescent growth and development and adult navigation of systems to provide support for students in this unique stage of growth and maturation.
Resumo:
In quantitative risk analysis, the problem of estimating small threshold exceedance probabilities and extreme quantiles arise ubiquitously in bio-surveillance, economics, natural disaster insurance actuary, quality control schemes, etc. A useful way to make an assessment of extreme events is to estimate the probabilities of exceeding large threshold values and extreme quantiles judged by interested authorities. Such information regarding extremes serves as essential guidance to interested authorities in decision making processes. However, in such a context, data are usually skewed in nature, and the rarity of exceedance of large threshold implies large fluctuations in the distribution's upper tail, precisely where the accuracy is desired mostly. Extreme Value Theory (EVT) is a branch of statistics that characterizes the behavior of upper or lower tails of probability distributions. However, existing methods in EVT for the estimation of small threshold exceedance probabilities and extreme quantiles often lead to poor predictive performance in cases where the underlying sample is not large enough or does not contain values in the distribution's tail. In this dissertation, we shall be concerned with an out of sample semiparametric (SP) method for the estimation of small threshold probabilities and extreme quantiles. The proposed SP method for interval estimation calls for the fusion or integration of a given data sample with external computer generated independent samples. Since more data are used, real as well as artificial, under certain conditions the method produces relatively short yet reliable confidence intervals for small exceedance probabilities and extreme quantiles.
Resumo:
Drowsy driving impairs motorists’ ability to operate vehicles safely, endangering both the drivers and other people on the road. The purpose of the project is to find the most effective wearable device to detect drowsiness. Existing research has demonstrated several options for drowsiness detection, such as electroencephalogram (EEG) brain wave measurement, eye tracking, head motions, and lane deviations. However, there are no detailed trade-off analyses for the cost, accuracy, detection time, and ergonomics of these methods. We chose to use two different EEG headsets: NeuroSky Mindwave Mobile (single-electrode) and Emotiv EPOC (14- electrode). We also tested a camera and gyroscope-accelerometer device. We can successfully determine drowsiness after five minutes of training using both single and multi-electrode EEGs. Devices were evaluated using the following criteria: time needed to achieve accurate reading, accuracy of prediction, rate of false positives vs. false negatives, and ergonomics and portability. This research will help improve detection devices, and reduce the number of future accidents due to drowsy driving.
Resumo:
The U.S. Nuclear Regulatory Commission implemented a safety goal policy in response to the 1979 Three Mile Island accident. This policy addresses the question “How safe is safe enough?” by specifying quantitative health objectives (QHOs) for comparison with results from nuclear power plant (NPP) probabilistic risk analyses (PRAs) to determine whether proposed regulatory actions are justified based on potential safety benefit. Lessons learned from recent operating experience—including the 2011 Fukushima accident—indicate that accidents involving multiple units at a shared site can occur with non-negligible frequency. Yet risk contributions from such scenarios are excluded by policy from safety goal evaluations—even for the nearly 60% of U.S. NPP sites that include multiple units. This research develops and applies methods for estimating risk metrics for comparison with safety goal QHOs using models from state-of-the-art consequence analyses to evaluate the effect of including multi-unit accident risk contributions in safety goal evaluations.
Resumo:
Restoration of natural wetlands may be informed by macroinvertebrate community composition. Macroinvertebrate communities of wetlands are influenced by environmental characteristics such as vegetation, soil, hydrology, land use, and isolation. This dissertation explores multiple approaches to the assessment of wetland macroinvertebrate community composition, and demonstrates how these approaches can provide complementary insights into the community ecology of aquatic macroinvertebrates. Specifically, this work focuses on macroinvertebrates of Delmarva Bays, isolated seasonal wetlands found on Maryland’s eastern shore. A comparison of macroinvertebrate community change over a nine years in a restored wetland complex indicated that the macroinvertebrate community of a rehabilitated wetlands more rapidly approximated the community of a reference site than did a newly created wetland. The recovery of a natural macroinvertebrate community in the rehabilitated wetland indicated that wetland rehabilitation should be prioritized over wetland creation and long-term monitoring may be needed to evaluate restoration success. This study also indicated that characteristics of wetland vegetation reflected community composition. The connection between wetland vegetation and macroinvertebrate community composition led to a regional assessment of predaceous diving beetle (Coleoptera: Dytiscidae) community composition in 20 seasonal wetlands, half with and half without sphagnum moss (Sphagnum spp.). Species-level identifications indicated that wetlands with sphagnum support unique and diverse assemblages of beetles. These patterns suggest that sphagnum wetlands provide habitat that supports biodiversity on the Delmarva Peninsula. To compare traits of co-occurring beetles, mandible morphology and temporal and spatial variation were measured between three species of predaceous diving beetles. Based on mandible architecture, all species may consume similarly sized prey, but prey characteristics likely differ in terms of piercing force required for successful capture and consumption. Therefore, different assemblages of aquatic beetles may have different effects on macroinvertebrate community structure. Integrating community-level and species-level data strengthens the association between individual organisms and their ecological role. Effective restoration of imperiled wetlands benefits from this integration, as it informs the management practices that both preserve biodiversity and promote ecosystem services.