Digital Commons Network^™

Conceptthread: Visualizing Threaded Concepts In Mooc Videos, Zhiguang Zhou, Li Ye, Lihong Cai, Lei Wang, Yigang Wang, Yongheng Wang, Wei Chen, Yong Wang

Research Collection School Of Computing and Information Systems

Massive Open Online Courses (MOOCs) platforms are becoming increasingly popular in recent years. Online learners need to watch the whole course video on MOOC platforms to learn the underlying new knowledge, which is often tedious and time-consuming due to the lack of a quick overview of the covered knowledge and their structures. In this paper, we propose ConceptThread , a visual analytics approach to effectively show the concepts and the relations among them to facilitate effective online learning. Specifically, given that the majority of MOOC videos contain slides, we first leverage video processing and speech analysis techniques, including shot recognition, …

Walleye (Sander Vitreus) Do Not Exhibit An Aggregative Predatory Response To Larval White Sturgeon (Acipenser Transmontanus) In The Upper Columbia River In Lake Roosevelt, Washington, Seth A. Barr

EWU Masters Thesis Collection

Seasonal prey abundance can drive predatory fishes to aggregate in areas of high prey density. This project aimed to determine whether Walleye (Sander vitreus) exhibit an aggregative predation response to larval White Sturgeon (Acipenser transmontanus) drifts in the Lake Roosevelt system which is a reservoir of the Columbia River in Washington State. Populations of sturgeon are threatened worldwide, and are in need of conservation research. Walleye are a popular nonnative piscivorous game fish that were accidentally or illegally introduced to Lake Roosevelt in the 1950’s. Walleye in this study were obtained by gillnetting during White Sturgeon pre-spawn, peak spawn, and …

Causal Event Graph-Guided Language-Based Spatiotemporal Question Answering, Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit Sheth

Publications

Large Language Models have excelled at encoding and leveraging language patterns in large text-based corpora for various tasks, including spatiotemporal event-based question answering (QA). However, due to encoding a text-based projection of the world, they have also been shown to lack a fullbodied understanding of such events, e.g., a sense of intuitive physics, and cause-and-effect relationships among events. In this work, we propose using causal event graphs (CEGs) to enhance language understanding of spatiotemporal events in language models, using a novel approach that also provides proofs for the model’s capture of the CEGs. A CEG consists of events denoted by …

Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy

Publications

Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance1.

How Intensity Impacts Success In Collegiate Flight Programs, Andrew Leonard

Journal of Aviation/Aerospace Education & Research

With colleges and universities continuing to face challenges around student retention and degree completion, collegiate aviation program are attempting to find ways to improve the success rate of students enrolled in their programs. This is more important than ever as the demand for pilots in the commercial aviation industry continues to grow (Boeing, 2022). Research has shown that there is a connection between effort and success in higher education. Astin (1993) identified and measured student effort by the amount of time spent on tasks studying. He indicated a positive correlation with almost every academic outcome he tested, including grades, persistence, …

Training Methods Research Opportunities For A Pilot Workforce In Transition: A Literature Review, James Birdsong, Kurt L. Reesman

Journal of Aviation/Aerospace Education & Research

Over the next 15 years, 50% of the U.S. commercial air carrier workforce will retire, making way for younger pilots from Generations Y and Z. This review identifies the emerging pilot workforce and training methods, including emerging technologies and learning methods, as well as research gaps.

Addressing The Target Outcomes, Functional Objectives And Functional Skills Of Aspiring Aviators In Individualized Education Plans And Section 504 Plans, Gary C. Booker

Journal of Aviation/Aerospace Education & Research

The Federal Aviation Administration (FAA) has very specific requirements for individuals with Attention Deficit Hyperactivity Disorder (ADHD) that center around the executive function abilities of individuals without the aid of ADHD medications, which are forbidden for use by the FAA. These abilities are evaluated by the FAA's medical examination process, which involve a background investigation into a person's history. K-12 Administrators and educators can assist young aspiring pilots with ADHD by placing aviation-specific functional educational goals in their Individualized Educational Plans (IEPs) and Section 504 Plans.

Development Of A Safety Performance Decision-Making Tool For Flight Training Organizations, Marisa Aguiar, Carolina L. Anderson, Dothang Truong, Gregory S. Woo, Kenneth Byrnes

Journal of Aviation/Aerospace Education & Research

The purpose of the research was to create and validate a safety performance decision-making tool to transform a reactive safety model into a predictive, decision-making tool, specific to flight training organizations, to increase safety and aid in operational decision-making. Using Monte Carlo simulation, the study conducted simulation runs based on operational ranges to simulate the operating conditions with varying levels of controllable resources in terms of personnel (Aviation Maintenance Technicians and Instructor Pilots) and expenditures (active flight students and available aircraft). Four What-if Scenarios were conducted by manipulating the controllable inputs. Changes to the controllable inputs are reflected by variations …

Assessing Past Airworthiness Directives And How Safety Management Systems May Benefit Aviation Product Design And Manufacturing, Damon Lercel, Manoj Patankar, Richard Steckel

Journal of Aviation/Aerospace Education & Research

The European Union Aviation Safety Agency (EASA) continues to promulgate Safety Management Systems (SMS) across aviation organizations when it recently issued SMS requirements for EASA certificated Part 145 maintenance, repair and overhaul (MRO) organizations and Part 21 Design & Manufacturing (D&M) organizations. Currently, the Federal Aviation Administration (FAA) has no such rule in place for these U.S.-based organizations, which may challenge those doing business in countries where EASA policies apply. Given that a majority of the United States’ D&M and MRO population is made up of smaller organizations, it is likely a U.S. SMS regulation will require justification of the …

History’S Slowest Digital Transformation: The Long Road To Flight Data Monitoring, Michael Ott

Journal of Aviation/Aerospace Education & Research

Flight data monitoring (FDM) began in the flight test community in 1939 and entered the airline industry in 1974. In the 48 years since, however, very few operators have chosen to adopt this practice, which has shown clear safety benefits where it has found acceptance. While technical issues have created some obstacles, cultural issues have proven the greatest hindrance to wider FDM adoption. These cultural issues originated in the traits associated with pilots’ personalities, especially distrust of the regulators and operators who would administer flight data analysis programs (FDAP) that used FDM information. U.S. regulators have relied on voluntary adoption, …

Application Of Density Altitude Climatology To General Aviation Impacts, Thomas A. Guinn, Daniel J. Halperin, Sarah Strazzo

Journal of Aviation/Aerospace Education & Research

Density altitude (DA) plays a key role in flight safety because it helps pilots anticipate poor aircraft performance when temperatures are warmer than standard. In this study, a 30-year climatology of DA for the conterminous United States was created using the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate (ERA5) dataset was applied to four separate DA-based, aircraft-performance, rules-of-thumb for general aviation (GA) flight. The goal was to demonstrate a technique to create educational visualization tools showing the variation of operational flight impacts with both month and location. Four such parameters were chosen to show …

'I’M A Pilot First, Female Second': Why Flight Deck Gender Imbalance Persists And The Case For Allyship, Kimberly Perkins, Rachael H. Merola, Sourojit Ghosh, Cecilia Aragon

Journal of Aviation/Aerospace Education & Research

Why is there greater gender parity for long-haul truck drivers, astronauts, and paleontologists than for women airline captains? This study uses a mixed-methods approach to examine the underlying causes of the gender imbalance in the United States aviation industry, in which only 3.6% of airline captains are women. Two polls and one survey gather data from professional pilots (N=1093) on their experience with stereotyping, gender bias, and allyship. Direct comments were analyzed to shed light on the results of the survey. Results suggest that, contrary to prevailing perceptions, the persistent gender imbalance in the flight deck can largely be attributed …

Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Austin T. Walden, Paul J. Thomas

Journal of Aviation/Aerospace Education & Research

Increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations: 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) developing an embedded machine learning framework. Data cleanup and …

Chatgpt In The Classroom: A Practical Guide For Educators, Sang-A Lee, Jacob Welch, Ryan J. Wallace, David Cross, Jon M. Loffi

Journal of Aviation/Aerospace Education & Research

This paper explores the potential applications of ChatGPT, a powerful Artificial Intelligence (AI) large language model (LLM) developed by OpenAI, for aviation education applications. The authors provide an overview of ChatGPT and its unique features, such as accessibility, conversational abilities, and personalized learning capabilities. The scalability of ChatGPT allows individualized and personalized instruction, a revolutionary aspect that can potentially enhance the student learning experience. This applied research employed an exploratory design to investigate ChatGPT's potential applications to enhance learning at varied levels of learning. The study investigated four research questions: (1) How can ChatGPT be used by students to support …

Identifying Aircraft Damage Mitigating Factors With Explainable Artificial Intelligence (Xai): An Evidence-Based Approach To Rule-Making For Pilot Training Schools, Ryan Zierman, Burak Cankaya

Journal of Aviation/Aerospace Education & Research

Recent pilot shortages have brought pilot training into focus as the industry attempts to rectify a compounding problem. The FAA has implemented some recent rule-making regarding pilot training that has left the General Aviation community questioning the motive or justification behind the rules. FAA incident data are inconsistent, specifically with aviation activity in general; flight activity that does not result in an accident or incident is not recorded for analysis. Despite the present shortcomings in the AIDS data, applying Machine Learning techniques make it possible to predict what characteristics mitigate aircraft damage during an incident (AUC=0.913, Accuracy=97%, Recall=84%, Precision=89%). Machine …

Human-Ai Teams In Aviation: Considerations From Human Factors And Team Science, Jenna Korentsides, Joseph R. Keebler, Crystal M. Fausett, Sabina M. Patel, Elizabeth H. Lazzara

Journal of Aviation/Aerospace Education & Research

Artificial Intelligence (AI) has transformed the way human-computer interaction (HCI) teams can collaborate and coordinate in various domains, including aviation and crew resource management (CRM). AI's transformative capabilities enhance teamwork, efficiency, and safety, particularly in risk management. AI's ability to process vast amounts of data and provide real-time insights enables informed decision-making and automation of repetitive tasks in aviation. By combining the strengths of AI and humans, outlined in our modified version of the ‘HABA-MABA’ framework, a dynamic teamwork relationship emerges, provided roles are successfully allocated. AI systems are able to act as intelligent assistants, offering timely recommendations, fostering effective …

Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study In Aviation Maintenance, Nadine Amin, Tracy L. Yother, Julia Rayz

Journal of Aviation/Aerospace Education & Research

With timeliness and efficiency being critical in the aviation maintenance industry, the need has been growing for smart technological solutions that optimize and streamline the different underlying tasks (Bergkvist & Sabbagh, 2021). One such task is the technical documentation of the performed maintenance operations (Chandola et al., 2022). Instead of manual documentation, voice tools that transcribe spoken logbook entries allow technicians to document their work right away in a hands-free and time efficient manner. However, an accurate automatic speech recognition (ASR) model requires large training corpora (Siyaev & Jo, 2021a), which are lacking in the domain of aviation maintenance. In …

An Enhanced Deep Autoencoder For Flight Delay Prediction, Desmond B. Bisandu, Dan Andrei Soviani-Sitoiu, Irene Moulitsas

Journal of Aviation/Aerospace Education & Research

Accurate and timely flight delay prediction cannot be overemphasized because of the ever-increasing demand for air travel and its importance in deploying intelligent transportation systems. Nonetheless, there has not been a universal solution to the problem, as more intelligent flight decision systems are required for the aviation industry's future growth. Existing flight delay classification and prediction approaches are mainly shallow traffic models and do not satisfy many applications in the real world. Our motivation to rethink the deep architecture model for predicting flight delays emanates from the problem. In this research, we proposed a technique that modified stacked autoencoder architecture …

Real-Time Detection Of Sea Turtles Using Uav And Neural Networks On Edge Devices, Jose A. Gonzalez Nunez, Jose G. Gonzalez Nunez, Mustafa I. Akbas, Patrick Currier, Nickolas D. Macchiarella

Journal of Aviation/Aerospace Education & Research

Sea turtle populations continue to diminish around the globe for various reasons. Therefore, the need for innovative solutions to monitor sea turtles has been increasing. This research paper focuses on an innovative application of artificial intelligence (AI) and machine learning (ML) together with unmanned aerial vehicles (UAV) to improve sea turtle conservation efforts. We outline the design, implementation, and evaluation of a system that deploys UAVs equipped with high-resolution cameras, coupled with a purpose-built neural network to recognize, classify, and monitor sea turtles. This project thus serves as a platform for understanding the wider applicability and limitations of this technology …

In Spirit And In Truth: (Re)Searching Christianity And Racial Liberation In Education, Phillip Smith, J. J. Lyiscott, A. M. Neal-Stanley, B. Harris Garad, L. Caraballo, J. Hoskins, D. Wallace

GSE Faculty Publications

As educational justice scholarship addressing racial oppression continues to name the role of the spirit, there is a need for Black and Brown Christian educators and researchers to locate ourselves as grounded in the epistemologies and pedagogies of Christ as our spiritual home. This paper brings together eight Black and Brown Christian educators and researchers to grapple with what it means to be Christians committed to racial justice in education against the backdrop of centuries of religious corruption. Through collaborative autoethnography, we turn to our spiritual and religious lives situated within our racialized identities to challenge the disciplinary and material …

Endorsing A Biophychosocial Perspective Of Pain In Individuals With Chronic Pain: Development And Validation Of A Scale, Maria Kleinstäuber, Eric L. Garland, Brittany L. Sisco-Taylor, Mathias Sanyer, Julia Corfe-Tan, Antonia Barke

Psychology Faculty Publications

Objectives:

Patients' beliefs about pain play an important role in their readiness to engage with chronic pain self-management. The central aim of this study was to validate a self-report instrument to assess a specific set of pain beliefs, patients' endorsement of a biopsychosocial model of chronic pain (PEB).

Methods:

Interdisciplinary experts in the field of pain were involved in creating an instrument, the PEB Scale, to operationalize patients' endorsement of a biopsychosocial pain model. A sample of 199 patients with chronic pain was recruited to evaluate the factorial structure (principal axis factoring), the internal consistency (Cronbach's alpha), the convergent …

Dynamic Analysis And Experimental Verification Of Flexible Unbalance Rotor Supported By Two Identical Journal Bearings, Omar Ahmed, Hussein Sayed, T.A. El-Sayed

Trends in advanced sciences and technology

Abstract BACKGROUND: Analyzing the vibrations for rotor-bearing systems is a critical issue in the field of rotor dynamics. It is crucial to identify rotary machine vibrations, behaviors, and stability conditions. The main causes of vibration in rotating machinery are unbalanced masses, misalignment, mechanical looseness, shaft cracks, and other defects. METHODS: This paper investigates the experimental verification of a theoretical model, using a steel shaft with a disc set at the midpoint, supported by two symmetric fluid film bearings. The study examines the effect of unbalance on the dynamic behavior of the rotor and its vibration characteristics. The experimental investigation involved …

Melt Pool Feature Extraction, A State-Space Model And Spatial Layer-To-Layer Control For Powder Bed Fusion, Xin Wang

Doctoral Dissertations

"Powder Bed Fusion (PBF) is an Additive Manufacturing (AM) technique which can reduce material waste and is a fast-prototyping technique for complex geometries. However, the lack of consistent quality is a major problem in industrial applications. An InfraRed (IR) camera is a common tool to monitor a surface temperature field and melt pool morphology in PBF. With melt pool features from camera videos, manufacturing researchers use spatial feature maps to visualize defect locations and control researchers use layer-to-layer control to achieve more uniform melt pools and less defects.

Paper I presents a simulation method to characterize the effect of down-sampling …

Efficient Modeling And Simulation For The Aerothermal Analysis Of Particle-Laden Hypersonic Flows, Andrew Hinkle

Doctoral Dissertations

"Standard approaches for simulating hypersonic flows in particle-laden environments have key limitations in practice, such as high cost and numerical noise. In this work, efficient solution strategies for particle-laden hypersonic flows were developed using both Lagrangian and Eulerian models for the particle phase with the focus on investigating spacecraft surface erosion, as well as convective and radiative heat flux augmentation due to atmospheric particulate encountered during planetary entry.

First, an efficient integration strategy for Lagrangian methods, the Trajectory Control Volume (TCV) method, was developed for steady analysis of dilute particle phase problems on general geometries. The TCV method was shown …

Georgia Southern Libraries Annual Report 2023 - 2024, Georgia Southern University Libraries

Library Annual Reports

No abstract provided.

A Roadmap For Improving Data Quality Through Standards For Collaborative Intelligence In Human-Robot Applications, Shakra Mehak, Inês F. Ramos, Keerthi Sagar, Aswin Ramasubramanian, John D. Kelleher, Michael Guilfoyle, Gabriele Gianini, Ernesto Damiani, Maria Chiara Leva

Research Outputs: 2025-Present

Collaborative intelligence (CI) involves human-machine interactions and is deemed safety-critical because their reliable interactions are crucial in preventing severe injuries and environmental damage. As these applications become increasingly data-driven, the reliability of CI applications depends on the quality of data, shaping the system’s ability to interpret and respond in diverse and often unpredictable environments. In this regard, it is important to adhere to data quality standards and guidelines, thus facilitating the advancement of these collaborative systems in industry. This study presents the challenges of data quality in CI applications within industrial environments, with two use cases that focus on the …

Race, Inequality, And Social Capital In The U.S. Counties, Mi-Son Kim, Dongkyu Kim, Natasha Altema Mcneely

Political Science Faculty Publications

This study examines how the interplay between racial diversity and economic inequality affects variations of social capital in the U.S. counties. In general, racial and economic heterogeneity is assumed to provide a negative environment for the growth of social capital. Building on this, we argue the effect of economic inequality is weaker than that of racial diversity because increased economic heterogeneity is felt less visibly and acutely than racial heterogeneity. Moreover, economic inequality can positively condition the adverse impact of racial diversity on social capital when the two interact. Based on the crosscutting cleavages theory, income inequality in a racially …

Mental Workload As A Predictor Of Atco's Performance: Lessons Learnt From Atm Task-Related Experiments, Enrique Muñoz-De-Escalona, Maria Chiara Leva, José Juan Cañas

Articles

Air Traffic Controllers' (ATCos) mental workload is likely to remain the specific greatest functional limitation on the capacity of the Air Traffic Management (ATM) system. Developing computational models to monitor mental workload and task complexity is essential for enabling ATCOs and ATM systems to adapt to varying task demands. Most methodologies have computed task complexity based on basic parameters such as air-traffic density; however, literature research has shown that it also depends on many other factors. In this paper, we present a study in which we explored the possibility of predicting task complexity and performance through mental workload measurements of …

Elective Corporate Governance: Does Board Choice Matter?, Martin Gelter, Mathias M. Siems

Faculty Scholarship

Recent literature discusses how “menu laws” allow corporations to opt into one of multiple competing statutory regimes. This paper contributes to this literature by presenting original empirical research on the choice between corporate board models. Today, many countries not only allow modifications of a particular board structure, but they provide separate legal templates, giving firms a choice between a one-tier and a two-tier board model (and sometimes a third hybrid model). However, how companies actually use these rules is largely underexplored. Based on data from 14 European countries that permit a choice between two models, this paper examines the use …

Hubris Or Talent? Estimating The Role Of Overconfidence In Chinese Households’ Investment Decisions, Jing Xu, Maroula Khraiche, Xi Mao, Xuan Wang

School of Economics and Finance Faculty Publications

We document the extent to which overconfidence in one’s financial literacy (FL overconfidence) plays a role in households’ reported financial risk aversion and their actual investment behavior, using data from the China Household Finance Survey. We measure FL overconfidence by estimating the gap between people’s self-reported financial literacy and their objectively measured financial knowledge. Our results indicate that FL overconfidence is negatively associated with self-reported financial risk aversion. Additionally, FL overconfidence is positively associated with the likelihood of having a brokerage account, holding risky financial instruments (other than just stock), and a proportion of assets allocated towards risky assets. We …