350 resultados para Statistical tools


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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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In this work, a previously-developed, statistical-based, damage-detection approach was validated for its ability to autonomously detect damage in bridges. The damage-detection approach uses statistical differences in the actual and predicted behavior of the bridge caused under a subset of ambient trucks. The predicted behavior is derived from a statistics-based model trained with field data from the undamaged bridge (not a finite element model). The differences between actual and predicted responses, called residuals, are then used to construct control charts, which compare undamaged and damaged structure data. Validation of the damage-detection approach was achieved by using sacrificial specimens that were mounted to the bridge and exposed to ambient traffic loads and which simulated actual damage-sensitive locations. Different damage types and levels were introduced to the sacrificial specimens to study the sensitivity and applicability. The damage-detection algorithm was able to identify damage, but it also had a high false-positive rate. An evaluation of the sub-components of the damage-detection methodology and methods was completed for the purpose of improving the approach. Several of the underlying assumptions within the algorithm were being violated, which was the source of the false-positives. Furthermore, the lack of an automatic evaluation process was thought to potentially be an impediment to widespread use. Recommendations for the improvement of the methodology were developed and preliminarily evaluated. These recommendations are believed to improve the efficacy of the damage-detection approach.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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The overarching goal of this project was to identify and evaluate cognitive and behavioral indices that are sensitive to sleep deprivation and may help identify commercial motor vehicle drivers (CMV) who are at-risk for driving in a sleep deprived state and may prove useful in field tests administered by officers. To that end, we evaluated indices of driver physiognomy (e.g., yawning, droopy eyelids, etc.) and driver behavioral/cognitive state (e.g. distracted driving) and the sensitivity of these indices to objective measures of sleep deprivation. The measures of sleep deprivation were sampled on repeated occasions over a period of 3.5-months in each of 44 drivers diagnosed with Obstructive Sleep Apnea (OSA) and 22 controls (matched for gender, age within 5 years, education within 2 years, and county of residence for rural vs. urban driving). Comprehensive analyses showed that specific dimensions of driver physiognomy associated with sleepiness in previous research and face-valid composite scores of sleepiness did not: 1) distinguish participants with OSA from matched controls; 2) distinguish participants before and after PAP treatment including those who were compliant with their treatment; 3) predict levels of sleep deprivation acquired objectively from actigraphy watches, not even among those chronically sleep deprived. Those findings are consistent with large individual differences in driver physiognomy. In other words, when individuals were sleep deprived as confirmed by actigraphy watch output they did not show consistently reliable behavioral markers of being sleep deprived. This finding held whether each driver was compared to him/herself with adequate and inadequate sleep, and even among chronically sleep deprived drivers. The scientific evidence from this research study does not support the use of driver physiognomy as a valid measure of sleep deprivation or as a basis to judge whether a CMV driver is too fatigued to drive, as on the current Fatigued Driving Evaluation Checklist.. Fair and accurate determinations of CMV driver sleepiness in the field will likely require further research on alternative strategies that make use of a combination of information sources besides driver physiognomy, including work logs, actigraphy, in vehicle data recordings, GPS data on vehicle use, and performance tests.

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The Iowa Juvenile Court Services Offices are issuing their fourth annual statewide report. The the Iowa Division of Criminal and Juvenile Justice Planning (CJJP). This report would not be possible without the dedication of, and assistance from, all of the above-mentioned people. The eight Chief Juvenile Court Officers would like to take this opportunity to thank their staff for their dedication and their ability to enter accurate information on every youth referred to Juvenile Court Services; the staff at the Iowa Court Information System, without whom this report would not be possible; and CJJP for their maintenance of the Iowa Justice Data Warehouse and their support in preparing this document.

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The Iowa Juvenile Court Services Offices are issuing their fourth annual statewide report. The the Iowa Division of Criminal and Juvenile Justice Planning (CJJP). This report would not be possible without the dedication of, and assistance from, all of the above-mentioned people. The eight Chief Juvenile Court Officers would like to take this opportunity to thank their staff for their dedication and their ability to enter accurate information on every youth referred to Juvenile Court Services; the staff at the Iowa Court Information System, without whom this report would not be possible; and CJJP for their maintenance of the Iowa Justice Data Warehouse and their support in preparing this document.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program