This thesis deals with the development of an Airspace Sector Occupancy Model (ASOM). The model determines the occupancy of Air Traffic Control Center (ARTCC) sectors for a given geometry of sectors and flight schedules, and can be used to study the impact of alternative flight schedules on the workload imposed on the sectors. Along with complimentary airspace analysis models, this can serve as an advisory tool to approve flight plans in the Free Flight Scenario, or to reschedule flights around a Special Use Airspace (SUA). ASOM is developed using Matlab 5.2, and can be run on an IBM compatible PC, Macintosh, or Unix Workstation. The computerized model incorporates the powerful features of graphics and hierarchical modeling inherent in Matlab, to design an effective tool for analyzing air traffic scenarios and their respective sector occupancies. / Master of Science

<p>  </p> <p>Some of the variability found in measures of mental workload (see e.g. Singleton et al. 1973; Wierwille and Connor 1983; Steelman-Allen et al. 2011; Casner and Gore 2010) may be due to the effort applied to the task by participants, rather than by the independent variable of interest. If true, capturing and removing the variation due to ‘applied effort’ could improve the ability of studies to detect effects of interest. </p> <p>While introducing participants to two sub-tasks derived from Multi-Attribute Task Battery II (Santiago-Espada et al. 2011), the study investigated the influence of applied effort on MATB-II performance measures of mental workload while holding other effects constant. Two groups of participants each completed easy and hard trials of MATB-II-derived sub-tasks. Treatment group of participants was offered an additional reward if they achieved a sufficiently high performance.</p> <p>The treatment group performed better by just under 4% in both easy and hard trials which provides a suggestion about the size of the effect of applied effort in this study. </p> <p>Additionally pilot error analysis was performed using Tracking task results. Error probability distributions did not fit known distributions and did not show consistent difference between treatment and control groups. Novel method of distribution “tails” comparison showed significant difference in extreme error durations, extents and delays between treatment and control groups.</p> <p>Measuring or controlling for applied effort can improve the ability of researchers to determine the effects of interventions on workload measures by reducing the amount of variability that is captured as error. Also, “tails” method seems to be a viable tool in comparing probability  </p>

Monitoring external workloads and countermovement jump performance may be useful for coaches. PURPOSE: The purpose of this study was to determine the effects of external load on player performance as measured by a CMJ and specific blood biomarkers throughout the preseason. METHODS:10 female division 1 basketball athletes had PlayerLoadTM (PL) monitored for all mandatory basketball training during six weeks of the preseason and CMJs were performed weekly. Blood biomarkers were collected before preseason and at the end of preseason. Data were analyzed via the Catapult Sport software (Openfield, Catapult, Innovations, Melbourne, VIC, Australia) to quantify all participant movement. Data from CMJs were analyzed via Sparta Science technology (SpartaTrac; SPARTA Performance Science, v1.2.4). Cumulative effect of physical activity (CTPL) was estimated as a sum of total PL up to each jump testing session divided by the number of days. Linear mixed-effects models were used to model data related to the efficacy of PL and CTPL. Athletes (id) and their positions were examined as potential random effects. RESULTS: The best fit model suggested a high-order polynomial pattern between PL and the number of days since the first jump testing session with a random effect for the intercept (marginal R2 = 0.290; conditional R2 = 0.471). The fixed effect for the slope of the first order term was found to be positive. There was a significant negative effect of CTPL on JH (p = 0.0037). The boot strapped model showed a marginal R2 of 0.0183 (95% CI [0.000952, 0.0744]) and a conditional R2 of 0.884 (95% CI [0.762, 0.956]). For RSImod, a significant negative association between RSImod and CTPL (p = 0.0039, 95% CI [-0.0002214, -4.597081e-05]). CONCLUSION: Workloads increase during preseason. CMJ height and RSImod may have limited utility in displaying the effects cumulative workloads. Position played did not impact workload or the impact of that workload on the player. PRACTICAL APPLICATION: Cumulative effect of physical activity may be tracked using CTPL derived from PL. Practitioners may be encouraged to monitor alternative countermovement variables to better understand performance response to the cumulative effect of physical activity.

Previous research has highlighted key taxonomic factors that have been found to influence human performance on vigilance tasks. However, previous literature has focused on research conducted in laboratory settings but has not examined vigilance tasks in remote environments. The present dissertation addresses this gap in the literature by examining human performance on a remote vigilance task, as well as workload and stress associated with the task. Qualitative data were collected to further understand the environment and distractions that participants experienced. Across three experiments, 372 participants were asked to complete a vigilance task and answer surveys pertaining to stress, workload, and ambient distractions. Experiment one manipulated the taxonomic factors of event rate and signal discrimination. Next, experiment two manipulated the taxonomic factors of event rate and source complexity. Finally, experiment three manipulated the taxonomic factors of event rate and task type. Across all three experiments, results identified significant differences in performance for the low and high event rate conditions, which are consistent with previous findings. Furthermore, signal discrimination type, source complexity, and task type (i.e., sensory vs. cognitive) resulted in significant differences between groups on measures of performance. All three experiments reported changes in perceived stress and increases in perceived workload. Ambient distractions, when they occurred, did impact performance, but only for experiment two. Overall, this study provides further support for several facets of the vigilance taxonomy and attempts to understand the impact of remote environments and ambient distractions on vigilance performance. Thus, these findings are advancing our understanding of the vigilance taxonomy and how environmental effects may influence human performance.

The effort-reward imbalance model allows us to see disparity in effort and reward and how this can be a predictor for a variety of constructs. The present study seeks to gather data utilizing the ERI modal in the nursing profession. Previous research has utilized the ERI model but methods for gathering data were not quick and efficient. This study seeks to utilize a database called Glassdoor to rapidly and effectively gather data. The researchers are interested in seeing the likelihood of nurses to recommend their company to a friend based on perceived effort and rewards. The sample included a random selection of 40 reviews from 40 randomly selected hospitals. To collect these random samplings, we used an excel random generator formula. We selected the 40 hospitals based on the corresponding number of the excel random generator and utilized the same method to select the 40 reviews. Sample words were developed through reviewing previous research. The frequency of each type of word was summed to create a numerical variable for effort and reward. Not only was the actual content of the review assessed, but the overall rating the user gave on Glassdoor for each particular variable was also used as reference to maintain accuracy. Bivariate correlations were conducted on the data to determine the strength of the effort-likelihood to recommend relationship and the reward-likelihood to recommend relationship. Results indicated that nurses who reported putting more effort into their company, were significantly more likely to recommend their company to a friend. Results also indicated that nurses who reported more rewards such as raises, compensation, and benefits were significantly more likely to recommend their company to a friend.

The aim of the research was to develop the non-intrusive physiological measure of using human facial skin temperature change as an indicator of mental workload. The forehead and nose temperature were obtained via thermography from the participants who drove in a simulator driving environment and/or in instrumented car experiments. The NASA TLX and the Modified Cooper-Harper metrics were adopted to assess the subjective workload for the validation of the physiological measure. Three driving experiments were conducted in order to acquire the physiological response and the workload score for the performed tasks. Forehead temperature was very stable throughout the experiments. Nose temperature dropped significantly after the experimental drive for all conditions in simulator test. Experiment 1 (NASA TLX Group: N=10; MCH Group: N=14) used simulator driving with different terrains as loading tasks. Neither the significant difference of the subjective workload nor the temperature drop was detected between different terrain conditions. In experiment 2 (N=33), mental workload was increased in a controlled manner by the introduction of mental arithmetic tests to the primary simulated drive. The mental arithmetic test conditions provoked a significantly greater nose temperature drop and also a higher perceived workload than the conditions without the arithmetic test. A weak correlation between the nose temperature drop and the subjective workload metric was yielded from the experiments. In Experiment 3 (N=13), facial temperature response and subjective workload score were compared between the simulator test and on-road driving. Driving in the simulator resulted in higher subjective workload and greater nose temperature drop than in real-car driving. When participants perceived a higher workload for a task, their nose temperature exhibited a greater drop. A significant correlation between the nose temperature change and the subjective workload score was found. Actual or potential applications of this research include real-time and unobtrusive mental workload assessment for human-system interaction development.

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