Engineering Commons^™

Farmer Perceptions Of Land Cover Classification Of Uas Imagery Of Coffee Agroecosystems In Puerto Rico, Jose Cabrera, Blake Neal, Kevin Adkins, Ronny Schroeder, Gwendolyn Klenke, Shannon Brines, Nayethzi Hernandez, Kevin Li, Riley Glancy, Ivette Perfecto

Publications

Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously there has been an increased use of uncrewed aerial systems (UAS) in remote sensing as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UAS and the attention on agroecosystems, there exists an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UAS to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and …

Human Factors In Aviation Maintenance: Understanding Errors, Management, And Technological Trends, Rajee Olaganathan

Publications

Aircraft maintenance and inspection are complex systems that work on a time-based schedule and require teamwork of different professionals to maintain the airworthiness of aircraft. Errors in maintenance and inspection processes cause in-flight engine shutdowns, flight delays, flight cancellation, sometimes resulting in accidents and incidents that cause significant economic consequences. Due to the substantial impact on both safety and financial aspects of an air carrier, this paper focuses on hangar maintenance as the work is carried out across several shifts by different technicians, addressing various human factor issues that contribute to errors. The paper will also briefly discuss shift work …

Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro

Publications

The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.

Experimental Analysis Of The Integrated High-Lift Propulsor, Robert W. Deters, Byron Ward, Shreyas Narsipur

Publications

Wind tunnel testing was conducted to evaluate the performance of the Integrated High Lift Propulsor (IHLP), a novel Distributed Electric Propulsion (DEP) system. The IHLP integrates traditional Krueger flap/slat elements with a Distributed Electric Propulsion design, enhancing high lift performance and cruise efficiency compared to conventional pylon-mounted DEP configurations. Starting from a baseline configuration determined from pretest Computational Fluid Dynamics (CFD) analyses, a parametric study was performed to determine the influence on the aerodynamic characteristics (𝐶𝑙 , 𝐶𝑥, and 𝐶𝑚). The study involved variations in flap settings, slat angles, overlap, propeller tilt, and propeller position. The impact of Reynolds number, …

On Progress In Exploring Controlled Viscous Limit-Cycle Oscillations In Modified Glauert Airfoil, Ethan Deweese, Lap Nguyen, Erik Vataker, William Mackunis, Vladimir Golubev, Ron Efrati, Oksana Stalnov

Publications

The paper reports on the progress in the development of a novel robust, nonlinear flow control technology that employs an array of synthetic-jet actuators (SJAs) embedded in 2-DOF, elastically mounted, optimized Modified Glauert (MG) airfoil design in order to control limit cycle oscillations (LCO) at low subsonic flow regimes. The focus here is on the conceptual design of the wind energy harvesting system that employs, e.g., a piezoelectric device to extract energy from plunging LCO, with the closed-loop controller being capable to sustain the required LCO amplitudes over a wide range of wind speeds. The current high-fidelity studies first include …

Experimental Environmental Profiles And Sloshing Dynamics Aboard Zero-G Aircraft, Pedro J. Llanos, Sathya Gangadharan, Kevin Crosby

Publications

This study presents the results of a parabolic flight experiment to study the sloshing dynamics of the magneto-active propellant management device experiment. This device utilizes a magnetoactive membrane and magnets located external to the tank to effectively damp the liquid free surface motion. This research work establishes a benchmark with sloshing analytical formulation and sensor calibration methods that can be used to characterize future research parabolic flights while providing important environmental profiles measured during flight, such as accelerations, pitch angle, velocity, temperature, total volatile content, carbon dioxide, relative humidity, magnetic field, and radiation. Correlation between these flight variables and the …

Tutorial: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur

Publications

Personalizing conversational agents can enhance the quality of conversations and increase user engagement. However, they often lack external knowledge to tend to a user’s persona appropriately. This is particularly crucial for practical applications like mental health support, nutrition planning, culturally sensitive conversations, or reducing toxic behavior in conversational agents. To enhance the relevance and comprehensiveness of personalized responses, we propose using a two-step approach that involves (1) selectively integrating user personas and (2) contextualizing the response with supplementing information from a background knowledge source. We develop K-PERM (Knowledge-guided PErsonalization with Reward Modulation), a dynamic conversational agent that combines these elements. …

Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth

Publications

Despite their wide applications to language understanding tasks, large language models (LLMs) still face challenges such as hallucinations - the occasional fabrication of information, and alignment issues - the lack of associations with human-curated world models (e.g., intuitive physics or common-sense knowledge). Additionally, the black-box nature of LLMs makes it highly challenging to train them meaningfully in order to achieve a desired behavior. Specifically, the attempt to adjust LLMs’ concept embedding spaces can be highly intractable, which involves analyzing the implicit impact on LLMs’ numerous parameters and the resulting inductive biases. This paper proposes a novel architecture that wraps powerful …

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 …

Metal Organic Framework Modifications Of Structural Fibers, Marwan Al-Haik

Publications

A reinforced carbon composite can include a carbon sub­strate and a metal organic framework bonded to the carbon substrate. For example, a reinforced carbon composite can include a first layer, a second layer, and a resin adhered to the first layer and the second layer. The first layer can include a carbon substrate and a metal organic framework bonded to the carbon substrate. The second layer can include a carbon substrate and a metal organic framework bonded to the carbon substrate.

Impact Of Weather Factors On Airport Arrival Rates: Application Of Machine Learning In Air Transportation, Robert W. Maxson, Dothang Truong, Woojin Choi

Publications

Weather is responsible for approximately 70% of air transportation delays in the National Airspace System, and delays resulting from convective weather alone cost airlines and passengers millions of dollars each year due to delays that could be avoided. This research sought to establish relationships between environmental variables and airport efficiency estimates by data mining archived weather and airport performance data at ten geographically and climatologically different airports. Several meaningful relationships were discovered from six out of ten airports using various machine learning methods within an overarching data mining protocol, and the developed models were tested using historical data.

An Ontology Design Pattern For Representing Causality, Utkarshani Jaimini, Cory Henson, Amit Sheth

Publications

The causal pattern is a proposed ontology design pattern for representing the structure of causal relations in a knowledge graph. This pattern is grounded in the concepts defined and used by the CausalAI community i.e., Causal Bayesian Networks and do-calculus. Specifically, the pattern models three primary concepts: (1) causal relations, (2) causal event roles, and (3) causal effect weights. Two use cases involving a sprinkler system and asthma patients are provided along with their relevant competency questions.

Strategies For Engagement Of Non-Traditional Students In Engineering-Related Courses, Kimberly T. Luthi Dr., David Harvie, Keith Wilson, Monica Surrency

Publications

Project Goals

Overview

• Goal #1: Increase students' commitment to engineering pathways.
• Goal #2: Increase academic performance and persistence in engineering.
• Goal #3: Increase persistence of Veterans in engineering pathways.

Research Questions

• How does students' participation in peer-led team learning activities in online engineering courses correlate to their a) commitment to engineering, b) engineering identity, and c) self-efficacy.
• How do students in peer-led team learning activities compare to students in non-PLTL groups in terms of a) academic performance and b) persistence in engineering pathways?

An Evaluation Of Parameters Which Affect Dairy Herd Movement On Irish Pasture-Based Farms, Paul James Maher, Michael D. Murphy, Michael Egan, Patrick Tuohy

Publications

In pasture-based grazing systems, farm roadways are a pivotal link to connect paddocks on the grazing platform to the milking parlour. However, their effectiveness in the efficient movement of the dairy herd between the grazing paddocks and the milking parlour has yet to be fully quantified. A validation experiment was conducted on a research farm to analyse characteristics on farm roadways that may affect cow throughput, which was observed as the number of cows per minute (CPM) passing a specified location. Roadway width (R2 = 0.96) and surface condition score (SC) (R2 = 0.78, respectively) were both positively associated with …

Eeg Functional Connectivity In Infants At Elevated Familial Likelihood For Autism Spectrum Disorder, Christian O'Reilly, Scott Huberty, Stefon Van Noordt, James Desjardins, Nicky Wright, Julie Scorah, Sara Jane Webb, Mayada Elsabbagh, Basis Team

Publications

Background

Many studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, we know relatively little about the development of these differences in infancy.

Methods

We used a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6 and 12 months of age in infants at typical (N = 92) or elevated likelihood for ASD (N = 90), determined by the presence of an older sibling with ASD. We computed the functional connectivity between …

Perception Of Crisis Management, Service Quality, And Loyalty Programs On Airline Travel Intention: What Roles Do Fear Of Covid-19 And Risk Attitude Play?, Sohel M. Imroz, Tamilla Curtis, Scott C. Ambrose

Publications

This research investigates the antecedents of airline travel intention, including the effects of crisis management, service quality perceptions, and loyalty programs, along with the fear of coronavirus disease (COVID-19) and risk attitude among individuals from different parts of the world during the peak of the pandemic. Its main objective is to assess how these variables impact passenger airline travel intention. Partial least squares structural equation modeling was used to assess the measurement model and test the hypothesized relationships on the sample of 944 travelers. Results indicated strong positive associations between fear of COVID-19, risk-averse attitudes, and service quality with respect …

Reducing Brain Kynurenic Acid Synthesis Precludes Kynurenine-Induced Sleep Disturbances, Katherine M. Rentschler, Snezana Milosavljevic, Annalisa M. Baratta, Courtney J. Wright, Maria V. Piroli, Zachary Tentor, Homayoun Valafar, Christian O'Reilly, Ana Pocivavsek

Publications

Patients with neurocognitive disorders often battle sleep disturbances. Kynurenic acid is a tryptophan metabolite of the kynurenine pathway implicated in the pathology of these illnesses. Modest increases in kynurenic acid, an antagonist at glutamatergic and cholinergic receptors, result in cognitive impairments and sleep dysfunction. We explored the hypothesis that inhibition of the kynurenic acid synthesising enzyme, kynurenine aminotransferase II, may alleviate sleep disturbances. At the start of the light phase, adult male and female Wistar rats received systemic injections of either: (i) vehicle; (ii) kynurenine (100 mg kg−1; i.p.); (iii) the kynurenine aminotransferase II inhibitor, PF-04859989 (30 mg kg−1; s.c.); …

Systems Thinking Applied To Higher Education Curricula Development, Reza Rahdar, Mark London, Yuetong Lin, Hong Jiang

Publications

Systems Thinking (ST) is a general and yet nebulous term that describes an approach to understanding and working with complexity in the real world. ST seeks to evaluate different behaviors of individual system elements when they operate in isolation as opposed to when they are integrated as part of a larger system and placed within a particular operating environment. The education environment consists of multiple systems with different digital content, learning goals/outcomes that serve different stakeholders including teachers, learners, and administrators. The inherent complexity and interaction among these various educational system elements and functions make this environment a worthy candidate …

Validation Of A Biomechanical Injury And Disease Assessment Platform Applying An Inertial-Based Biosensor And Axis Vector Computation, Wangdo Kim, Emir A. Vela, Sean S. Kohles, Victor Huayamave

Publications

Inertial kinetics and kinematics have substantial influences on human biomechanical function. A new algorithm for Inertial Measurement Unit (IMU)-based motion tracking is presented in this work. The primary aims of this paper are to combine recent developments in improved biosensor technology with mainstream motion-tracking hardware to measure the overall performance of human movement based on joint axis-angle representations of limb rotation. This work describes an alternative approach to representing three-dimensional rotations using a normalized vector around which an identified joint angle defines the overall rotation, rather than a traditional Euler angle approach. Furthermore, IMUs allow for the direct measurement of …

Additively Manufactured Engineered Fingerprint (Amef) Antenna And Related Detection, Eduardo Antonio Rojas, Noemi Miguelea-Gomez

Publications

Antenna structures can include an additively manufactured engineered fingerprint (AMEF). AMEF antenna features facilitate individual or type classification of an unknown source antenna. As described herein, physical features can be included in an additively manufactured antenna to facili­tate source identification, such as without sacrificing antenna performance. In general, AMEF techniques can improve physical layer security, such as without dramatically increas­ing production cost or decreasing production throughput, as compared to other approaches.

Ki-Cook: Clustering Multimodal Cooking Representations Through Knowledge-Infused Learning, Revathy Venkataramanan, Swati Padhee, Saini Rohan Rao, Ronak Kaoshik, Anirudh Sundara Rajan, Amit Sheth

Publications

Cross-modal recipe retrieval has gained prominence due to its ability to retrieve a text representation given an image representation and vice versa. Clustering these recipe representations based on similarity is essential to retrieve relevant information about unknown food images. Existing studies cluster similar recipe representations in the latent space based on class names. Due to inter-class similarity and intraclass variation, associating a recipe with a class name does not provide sufficient knowledge about recipes to determine similarity. However, recipe title, ingredients, and cooking actions provide detailed knowledge about recipes and are a better determinant of similar recipes. In this study, …

Ecg Recordings As Predictors Of Very Early Autism Likelihood: A Machine Learning Approach, Deepa Tilwani, Jessica Bradshaw, Amit Sheth, Christian O'Reilly

Publications

In recent years, there has been a rise in the prevalence of autism spectrum disorder (ASD). The diagnosis of ASD requires behavioral observation and standardized testing completed by highly trained experts. Early intervention for ASD can begin as early as 1–2 years of age, but ASD diagnoses are not typically made until ages 2–5 years, thus delaying the start of intervention. There is an urgent need for non-invasive biomarkers to detect ASD in infancy. While previous research using physiological recordings has focused on brain-based biomarkers of ASD, this study investigated the potential of electrocardiogram (ECG) recordings as an ASD biomarker …

Design Of Bamboo Reinforced Concrete Beams Considering Variability In Tensile Strength Of Bamboo, Bibek Bhardwaj, Michael Stoner, Weichiang Pang

Publications

In recent years, the price of steel has soared, making steel reinforcement in concrete structures unaffordable for households in low-income countries. Seismic activities in low-income households, particularly those in developing countries, pose a significant threat to life and property to unreinforced concrete structures. The application of bamboo as an alternative to steel in reinforced concrete is still in its early stages of development. Unlike steel, bamboo is a natural material, and its structural properties vary greatly based on species, location, age, and geometric properties. Thus, the design of bamboo-reinforced concrete involves more uncertainties than steel-reinforced concrete. This research investigates the …

Predicting Corrosion Damage In The Human Body Using Artificial Intelligence: In Vitro Progress And Future Applications Applications, Michael A. Kurtz, Ruoyu Yang, Mohan S. R. Elapolu, Audrey C. Wessinger, William Nelson, Kazzandra Alaniz, Rahul Rai, Jeremy L. Gilbert

Publications

Artificial intelligence (AI) is used in the clinic to improve patient care. While the successes illustrate the impact AI can have, few studies have led to improved clinical outcomes. A gap in translational studies, beginning at the basic science level, exists. In this review, we focus on how AI models implemented in non-orthopedic fields of corrosion science may apply to the study of orthopedic alloys. We first define and introduce fundamental AI concepts and models, as well as physiologically relevant corrosion damage modes. We then systematically review the corrosion/AI literature. Finally, we identify several AI models that may be Preprint …

Hyper-Local Weather Predictions With The Enhanced General Urban Area Microclimate Predictions Tool, Kevin A. Adkins, William Becker, Sricharan Ayyalasomayajula, Steven Lavenstein, Kleoniki Vlachou, David Miller, Marc Compere, Avinash Muthu Krishnan, Nickolas Macchiarella

Publications

This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. For the further development and demonstration of GUMP, the Embry–Riddle Aeronautical University (ERAU) campus was used as a test environment. Local weather sensors provided data to train ML models, and CFD models of urban- and suburban-like areas of ERAU’s campus were created and iterated through with a wide assortment of inlet wind speed and direction combinations. ML weather sensor predictions were combined with best-fit …

From Prosumer To Flexumer: Case Study On The Value Of Flexibility In Decarbonizing The Multi-Energy System Of A Manufacturing Company, Markus Fleschutz, Markus Bohlayer, Marco Braun, Michael B. Murphy

Publications

Digitalization and sector coupling enable companies to turn into flexumers. By using the flexibility of their multi-energy system (MES), they reduce costs and carbon emissions while balancing the electricity grid. However, to identify the necessary investments in energy conversion and storage technologies to leverage demand response (DR) potentials, companies need to assess the value of flexibility. Therefore, this study quantifies the flexibility value of a production company’s MES by optimizing the synthesis, design, and operation of a decarbonizing MES considering self-consumption optimization, peak shaving, and integrated DR based on hourly prices and carbon emission factors (CEFs). The detailed case study …

Impact Of Critical Narrative On Students’ Abilities To Recognize Ethical Dilemmas In Engineering Work, Jeff Brown, Chad Rohrbacher, Taylor J. Mitchell, Dr. Leroy Long Iii, Jenna Korentsides, Joseph R. Keebler

Publications

This study aims to investigate the impact of exposure to critical narratives on students' abilities to recognize ethical dilemmas and broader impacts in engineering work. Critical narratives are place-based stories that engage students and help them enhance their critical thinking skills by making connections between the narratives, broader impacts of engineering work, and their responsibility to address these issues. The effectiveness of the critical narrative intervention was assessed by implementing discussion-based assignments around three critical narratives, which required students to listen to the narrative, respond to focus questions, engage with their peers, and reflect on the process. The intervention was …

Advances In Spacecraft Thermal Control, Sandra K. S. Boetcher, Robert C. Consolo Jr.

Publications

Spacecraft thermal management is critical for ensuring mission success, as it affects the performance and longevity of onboard systems. A comprehensive overview of the state of the art in spacecraft thermal control solutions, as well as a design methodology framework for efficient and effective thermal management, is provided. Various thermal control solutions, including coatings, insulation, heat pipes, phase-change materials, conductive materials, thermal devices, actively pumped fluid loops, and radiators, are discussed along with the primary sources of heat loading in space. The need for accurate modeling and analysis of the thermal environment to identify appropriate thermal control solutions and design …

Model-Driven Analysis Of Ecg Using Reinforcement Learning, Christian O'Reilly, Sai Durga Rithvik Oruganti, Deepa Tilwani, Jessica Bradshaw

Publications

Modeling is essential to better understand the generative mechanisms responsible for experimental observations gathered from complex systems. In this work, we are using such an approach to analyze the electrocardiogram (ECG). We present a systematic framework to decompose ECG signals into sums of overlapping lognormal components. We use reinforcement learning to train a deep neural network to estimate the modeling parameters from an ECG recorded in babies from 1 to 24 months of age. We demonstrate this model-driven approach by showing how the extracted parameters vary with age. From the 751,510 PQRST complexes modeled, 82.7% provided a signal-to-noise ratio that …