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Articles 1 - 10 of 10
Full-Text Articles in Training and Development
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw
Faculty Publications
Generative Adversarial Networks (GANs) have received immense attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. This manuscript focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to empirically determine the effects of 10 fundamental image degradation modes, applied to the training image dataset, on the Fréchet inception distance …
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino
Theses and Dissertations
Generative Adversarial Networks (GANs) have received increasing attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. While this research has yielded GAN variants robust to training set shrinkage and corruption, our research focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to determine empirically the effects of 10 fundamental …
Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman
Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman
Faculty Publications
Purpose — Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.
Design/methodology/approach — This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the …
The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon
The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon
Theses and Dissertations
Immersive simulations such as virtual reality is becoming more prevalent for use in training environments for many professions. United States Air Force firefighters may benefit from incorporating VR technology into their training program to increase organizational commitment, job satisfaction, self-efficacy, and job performance. With implementing a new training platform, it is also important to understand the relationship between these variables and the perceived benefits and efficacy of the VR training, which has not yet been studied in previous research. This study addresses this issue by gathering data from fire departments currently fielding a VR fire training platform.
Applying Data Organizational Techniques To Enhance Air Force Learning, Jacob A. Orner
Applying Data Organizational Techniques To Enhance Air Force Learning, Jacob A. Orner
Theses and Dissertations
The USAF and the DoD use traditional schoolhouses to educate and train personnel. The physical aspects of these schoolhouses limit throughput. A method to increase throughput is to shift towards an asynchronous learning environment where students move through content at individually. This research introduces a methodology for transforming a set of unstructured documents into an organized TM students can use to orient themselves in a domain. The research identifies learning paths within the TM to create a directed KSAT. We apply this methodology in four case studies, each an education or training course. Using a graph comparison metric and the …
Conceptualization And Application Of Deep Learning And Applied Statistics For Flight Plan Recommendation, Nicholas C. Forrest
Conceptualization And Application Of Deep Learning And Applied Statistics For Flight Plan Recommendation, Nicholas C. Forrest
Theses and Dissertations
The Air Forces Pilot Training Next (PTN) program seeks a more efficient pilot training environment emphasizing the use of virtual reality flight simulators alongside periodic real aircraft experience. The PTN program wants to accelerate the training pace and progress in undergraduate pilot training compared to traditional undergraduate pilot training. Currently, instructor pilots spend excessive time planning and scheduling flights. This research focuses on methods to auto-generate the planning of in-flight events using hybrid filtering and deep learning techniques. The resulting approach captures temporal trends of user-specific and program-wide student performance to recommend a feasible set of graded flight events for …
Breaking Down The Barriers To Operator Workload Estimation: Advancing Algorithmic Handling Of Temporal Non-Stationarity And Cross-Participant Differences For Eeg Analysis Using Deep Learning, Ryan G. Hefron
Theses and Dissertations
This research focuses on two barriers to using EEG data for workload assessment: day-to-day variability, and cross- participant applicability. Several signal processing techniques and deep learning approaches are evaluated in multi-task environments. These methods account for temporal, spatial, and frequential data dependencies. Variance of frequency- domain power distributions for cross-day workload classification is statistically significant. Skewness and kurtosis are not significant in an environment absent workload transitions, but are salient with transitions present. LSTMs improve day- to-day feature stationarity, decreasing error by 59% compared to previous best results. A multi-path convolutional recurrent model using bi-directional, residual recurrent layers significantly increases …
In Pursuit Of An Aptitude Test For Potential Cyberspace Warriors, Tiffiny S. Smith
In Pursuit Of An Aptitude Test For Potential Cyberspace Warriors, Tiffiny S. Smith
Theses and Dissertations
The Air Force has officially assumed the cyberspace mission. To perform this mission well, it is important to employ personnel who have the necessary skill sets and motivation to work in a cyberspace environment. The first step in employing the right people is to screen all possible candidates and select those with an aptitude for acquiring the skill sets and with the motivation to perform this work. This thesis attempts to determine the necessary skills and motivations to perform the cyberspace mission and recommends a screening process to select the candidates with the highest probability for success. Since this mission …
An Evaluation Of Organizational And Experience Factors Affecting The Perceived Transfer Of U.S. Air Force Basic Combat Skills Training, Shirley D. Crow
An Evaluation Of Organizational And Experience Factors Affecting The Perceived Transfer Of U.S. Air Force Basic Combat Skills Training, Shirley D. Crow
Theses and Dissertations
The United States Air Force is in a state of transformation. Due to ongoing operations in Iraq and Afghanistan, the focus of Basic Military Training is shifting to basic combat skills, or the skills needed to survive and operate in a hostile environment. In this study, basic combat skills training was evaluated using a number of training factors that potentially affect trainees’ perception of training transfer, or their ability to apply the skills they learned in training on the job or in a hostile environment. The analysis used structural equation modeling to evaluate the paths between each of the factors …
The Effect Of Interactivity And Instructional Exposure On Learning Effectiveness And Knowledge Retention: A Comparative Study Of Two U.S. Air Force Computer-Based Training (Cbt) Courses For Network User Licensing, Matthew J. Imperial
Theses and Dissertations
The United States Air Force (USAF) currently employs the use of computer-based training (CET) across a host of requirements. One such requirement is in the Information Assurance (IA) arena and involves the training/licensing of over one-million computer network end-users. USAF use of CETs has been shown to possess a potential for substantial fiscal savings. However, studies investigating the learning outcomes of learning effectiveness (initial learning) and knowledge retention (sustained learning) associated with USAF CETs are lacking.