Doctor of Philosophy / Department of Special Education, Counseling and Student Affairs / Fred O. Bradley / Over the last few years, the safety record of U.S. commercial airlines has improved to the point where the statistics on accidents are negligible. The overwhelming numbers of aviation fatalities occur in General Aviation (GA) accidents. While the fatal accident rate has improved—from around 5.0 per 100,000 miles flown in the post–World War II era to varying between 1.2 and 1.5 since 1996—it still results in 450 to 700 deaths per year. In 2013, improving GA safety was on the National Transportation Safety Board’s (NTSB’s) most wanted list. The NTSB has cited a lack of aeronautical knowledge as the cause of many of these accidents. If pilots are required to pass Federal Aviation Administration (FAA) knowledge and practical tests prior to obtaining a new pilot certificate, how could they not possess the knowledge needed to operate in the National Airspace System (NAS)? Some, attributing it to a failure to learn basic aeronautical knowledge, are concerned that potential pilots memorize the answers to test questions published in commercially available test guides and quickly forget the material after passing the test. The purpose of this retrospective causal comparative study was to see if airman knowledge tests scores are related to fatal accidents. Fatal GA accidents that had pilot error as a causal factor were compared with those in which maintenance factors caused the accidents, to see if there were significant differences in the pilots’ knowledge test scores. The time that potential pilots took to answer skill-based questions that required calculation or interpretation was compared to the time to answer recall questions to see if rote memorization may have been involved in passing the knowledge test. The results of this paper may have implications on how AFS 630 structures the FAA knowledge tests and how instructors prepare potential pilots for these tests.

La presente tesis es el resultado de una interacción de evaluaciones de campo como los resultados de los ensayos del sistema de canteras, pavimento existente, humedad natural, mix de aeronaves que operan y de topografía, así mismo de la traducción de manuales y catálogos, ya que nuestro País está afiliado y se rige por las Normas de la Organización de Aviación Civil Internacional (OACI), por los métodos de diseño de la Federal Aviation Administration (FAA) entidad oficial de la aeronáutica civil en los E.E.U.U. y a las especificaciones técnicas para al construcción de aeropuertos.

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Detection systems are widely used in industry. Designers, operators and users of these systems need to choose an appropriate design, based on the intended usage and the operating environment. The purpose of this research is to analyze the effect of various system design variables (controllable) and system parameters (uncontrollable) on the performance of detection systems. To optimize system performance one must manage the tradeoff between two errors that can occur. A False Alarm occurs if the detection system falsely indicates a target is present and a False Clear occurs if the detection system falsely fails to indicate a target is present. Given a particular detection system and a pre-specified false clear (or false alarm) rate, there is a minimal false alarm (or false clear) rate that can be achieved. Earlier research has developed methods that address this false alarm, false clear tradeoff problem (FAFCT) by formulating a Neyman-Pearson hypothesis problem, which can be solved as a Knapsack problem. The objective of this research is to develop guidelines that can be of help in designing detection systems. For example, what system design variables must be implemented to achieve a certain false clear standard for a parallel 2-sensor detection system for Salmonella detection? To meet this objective, an experimental design is constructed and an analysis of variance is performed. Computational results are obtained using the FAFCT-methodology and the results are presented and analyzed using ROC (Receiver Operating Characteristic) curves and an analysis of variance. The research shows that sample size (i.e., size of test data set used to estimate the distribution of sensor responses) has very little effect on the FAFCT compared to other factors. The analysis clearly shows that correlation has the most influence on the FAFCT. Negatively correlated sensor responses outperform uncorrelated and positively correlated sensor responses with large margins, especially for strict FC-standards (FC-standard is defined as the maximum allowed False Clear rate). Suggestions for future research are also included. FC-standard is the second most influential design variable followed by grid size. / Master of Science

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