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Two studies are reported which investigated the effect of individual demographics on training performance in air traffic controllers. The first study investigated the relationship between the demographics of age, sex and education level, and pass/fail rates at an air traffic control training centre. The data for this study was an historic data set provided by Airways Corporation, which oversees air traffic management in New Zealand. This includes training all controllers and providing all air traffic control in the country. The primary result of the first study was that trainees with post-secondary education achieved better during training than trainees with a high school education. Additionally, the level of education attained by the trainee appeared to be the best predictor (of the three demographic characteristics) for a trainee’s success. The data was limited, due to a significant amount of incomplete trainee records. This impaired the ability to conclusively resolve the role of these demographic characteristics for trainee success. The second study, investigated the impact these same demographics may have on trainee success in a much smaller (N=16), but complete (i.e., no missing records) and current cohort. In addition, the feedback given and received in a training centre to the 16 trainees was examined. The trainees under consideration in this study were attending the Airways training centre. The trainees’ debriefs after their air traffic control training sessions in Airways’ immersive tower simulator were recorded. The trends in the data validate the need for further research. The primary result of the second study however, was that there was a significant difference in the pass rates of those trainees with only a high school education (66.7% failed) and those with post-secondary education (0% failed). The other two demographic characteristics of interest, age and sex, did not significantly differ for those trainees who passed and failed. The combined results of these studies indicate that the air-traffic control community in New Zealand may benefit from further investigating these differences and potentially raising education requirements for air traffic control trainees.

In this thesis, we investigate the impact of channels that have a bursty nature in a cognitive radio network scenario. Our goal is to design a general channel usage model that can handle bursty primary user channel usage. The proposed model describes idle periods with a discrete platoon arrival process and describes busy periods with a discrete phase type distribution. The performance of the proposed model is compared with two more traditionally encountered channel usage models in three different secondary user access schemes. First, we design a reactive access scheme to show the poor performance results an in- vestigator can potentially obtain when ignoring bursty data traffic. We have also analyzed two proactive secondary network access schemes. Numerical results show that the achiev- able utilization and interference probability of the network are affected when traditional channel models are used in a bursty PU channel.