Engineering Commons^™

Leveraging Algebraic Thinking In Stem Education To Equip The Next Generation Of Problem Solvers, Asenath Odondi, Comfort Temitope Aje

Indiana STEM Education Conference

Algebraic thinking is a critical skill in mathematics education, involving pattern recognition, generalization, symbolic manipulation, and problem-solving. It is essential for success in STEM fields and should be developed throughout education, starting in early grades. This literature review synthesizes research on algebraic thinking, focusing on problem-based learning. The review indicates that incorporating algebraic thinking into problem-based learning with non-routine activities enhances students' understanding and real-world problem-solving in STEM.

Observing Evidence Of Fixation During K-12 Engineering Design Challenges Using Variables Adapted From Post-Secondary Research, Sopheak Seng, William S. Walker Iii

Indiana STEM Education Conference

Design fixation is a phenomenon impacting students when they generate ideas for an engineering challenge and subsequently hesitate to consider alternative ideas throughout the design activity. Research into fixation with post-secondary students has shown that fixation can limit the quantity and the quality of design solutions. This research brief will describe how fixation has been measured at the post-secondary level and suggest the need for complementing quantitative with qualitative analyses.

Impacts Of Informal Stem Summer Camps On Middle School Student Stem Identity, Austin R. Jenkins, Joshua Faith, Steve Heinold

Indiana STEM Education Conference

Informal or out of school STEM spaces have been documented as sites of positive STEM identity development for youth historically marginalized in formal STEM spaces (Çolakoğlu et al., 2023). To increase the number of students who develop positive STEM identities during the critical juncture of middle school, Indiana GEAR UP offered summer camps to rising 7th and 8th grade students at selected middle schools across the state. Longitudinal interviews with students indicate the importance of informal STEM spaces, like summer camps, in fostering positive STEM identity development.

Innovative Stem Learning Through Solar Oven Design: Promoting Creativity And Teamwork In Stem Education, Humphrey Chinenye Ochulor, Abigail Erskine, Comfort Temitope Aje

Indiana STEM Education Conference

STEM education benefits significantly from integrating design-based learning (DBL) which fosters student creativity and teamwork. This research brief examines how solar oven design projects for K-12 students that involve DBL promote students' creative skills and teamwork. A literature review was done to investigate how solar oven design activities impacted student learning. Research has shown that students improve creativity and teamwork when these activities are carried out using DBL strategies.

Indiana Interstate Speed Profiles 2020-2024, Rahul Suryakant Sakhare, Jairaj Desai, Deborah Horton, Darcy M. Bullock

Indiana Mobility Reports

This report presents a graphical summary of monthly mile-hours of congestion across the 8 Indiana interstates (I-64, I-65, I-69, I-70, I-74, I-94, I-465, and I-469) and the Indiana Toll Road (I-90) analyzed longitudinally over the last five years from January 2020 to December 2024. It is a continuation of speed profile summaries that are published in previous years. Such systemwide interstate performance measures provide important information for decision makers to plan capital projects and assess operations.

Hours of operation by speed bins (0 to 14 mph, 15 mph to 24 mph, 25 mph to 34 mph, 35 mph to 44 …

Crawfordsville District Interstate Speed Profiles: April 2020–March 2025, Rahul Suryakant Sakhare, Jairaj Desai, Deborah Horton, Darcy M. Bullock

Indiana Mobility Reports

This report presents a graphical summary of monthly mile-hours of congestion across the three interstates (I-65, I-70, and I-74) in INDOT’s Crawfordville District analyzed longitudinally over the last five years from April 2020 to March 2025. It is a continuation of speed profile summaries that are published in previous years. Such systemwide interstate performance measures provide important information for decision makers to plan capital projects and assess operations.

Hours of operation by speed bins (0 to 14 mph, 15 mph to 24 mph, 25 mph to 34 mph, 35 mph to 44 mph, 45 mph to 54 mph, 55 mph …

Quantifying The Transfer Effectiveness Of An Artificial Intelligence-Based Simulator Pre-Training Program For Student Pilots, Ryan Guthridge

Journal of Aviation/Aerospace Education & Research

Since the airline pilot shortage was initially studied in 2016, the pilot hiring model has been significantly impacted, with airlines hiring qualified pilots at unprecedented rates. The COVID-19 pandemic has slowed this hiring rate, however it is expected that airline hiring will soon increase to a rate higher than initially expected (Bureau of Transportation Statistics, 2022). With this dynamic, certified flight instructors are often the most qualified recruits for airlines, due to the number of hours and experience they have gained in the flight training organization. In turn, certified flight instructors are in short supply for flight training organizations worldwide. …

Analysis Of Public Acceptance Of Urban Air Mobility (Uam) Based On Air Travel Frequency, Seuggyun Jin, Kim O. Chambers

Journal of Aviation/Aerospace Education & Research

Urban Air Mobility (UAM) is an innovative air transportation system designed for efficient travel in urban and suburban areas, offering significant time saving compared to traditional ground transportation. However, concerns about UAM services, such as safety and noise, remain prominent. Understanding public acceptance of UAM is crucial to identifying potential customers and ensuring the sustainability of commercial UAM operations. This study utilizes an online survey from a total of 254 consumer attitudes on the scales of reliability, usefulness, behavioral intention, safety, and concerns to examine public acceptance of UAM based on people's air travel frequencies. Using a one-way ANOVA, the …

The Influence Of Social Achievement Goals On Grit In Aviation Education, Austin T. Walden

Journal of Aviation/Aerospace Education & Research

Aviation students have multiple ways of persisting and persevering in their aviation education, and they do not learn in a vacuum. Their social goals may help explain why some aviation students show more grit than others in an aviation education environment. The study examined the relationship and predictive ability of social achievement goals (i.e., social development goal, social demonstration-approach goal, and social demonstration-avoid goal) to predict grit in an aviation education environment. The constructs of social achievement goals and grit have yet to be examined together in motivation research. This paper provides a new predictive model for using the two …

Empowering Precision Forecasting: Self-Supervised Lstm For Hourly Pressure And Temperature Prediction, Anand Shankar, Deepak K. Singh, Mantosh Kumar, Pankaj Kumar, Pradhan Parth Sarthi

Journal of Aviation/Aerospace Education & Research

The most important parts of any flight are landing and takeoff, and an aircraft's takeoff configuration must balance the regulated takeoff weight, runway length, and weather conditions to ensure a safe departure and arrival. In addition to runway length, wind, temperature, pressure, and visibility determine the total allowed takeoff weight and the economic viability of any trip. Thus, any meteorological office involved in flight planning and operation at any airport must accurately assess these factors, known as takeoff data. This research paper suggests multivariate self-supervised LSTM-based models to accurately predict the temperature and pressure (MSLP) of the takeoff data. The …

The State Of Uas Operations At Airports, A Perspective From Airport Managers, Damon Lercel, Sarah M. Hubbard

Journal of Aviation/Aerospace Education & Research

As the number of Uncrewed Aircraft Systems (UAS) operating in our National Airspace System (NAS) increases, so do UAS operations near or at an airport. The accelerating technology in Advanced Air Mobility (AAM) and related business opportunities will only further increase UAS operations at airports. This continued growth in new UAS technologies and applications introduces new hazards and risks to the airport environment. This proliferation of UAS highlights the importance of airports developing a robust Safety Management System (SMS) that includes specific UAS risk mitigations. There is currently little empirical data regarding UAS traffic around airports and there is no …

Build Digital Annual Survey 2024 Results, Clare Eriksson, Robert Moore, Bilal Succar

Reports

The Build Digital Annual Survey 2024 presents a sector-wide snapshot of digital adoption and transformation across Ireland’s construction and built environment sector. Based on 137 responses, the report shows that most participating organisations have begun their digital transformation journey, with expected benefits including improved accuracy, operational efficiency, quality, cost reduction, and faster clash resolution. The findings indicate widespread use of common digital deliverables and increasing awareness of ISO 19650, CDEs, OpenBIM, and CWMF BIM requirements. However, the report also identifies persistent challenges, including skills gaps, uneven training provision, limited digital competence, and variable implementation of BIM requirements across public and …

Multitec: A Data-Driven Multimodal Short Video Detection Framework For Healthcare Misinformation On Tiktok, Lanyu Shang, Yang Zhang, Yawen Deng, Dong Wang

Computer Science Faculty Works

With the prevalence of social media and short video sharing platforms (e.g., TikTok, YouTube Shorts), the proliferation of healthcare misinformation has become a widespread and concerning issue that threatens public health and undermines trust in mass media. This paper focuses on an important problem of detecting multimodal healthcare misinformation in short videos on TikTok. Our objective is to accurately identify misleading healthcare information that is jointly conveyed by the visual, audio, and textual content within the TikTok short videos. Three critical challenges exist in solving our problem: i) how to effectively extract information from distractive and manipulated visual content in …

Development And Evaluation Of Machine Learning Models For Early Pediatric Sepsis Prediction, Ancita M. Andrade

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Sepsis is a leading cause of pediatric mortality, claiming more lives in the United States annually than all childhood cancers combined. Early identification in Emergency Departments (EDs) remains challenging, as the current Phoenix criteria establishes an updated international consensus definition for sepsis, however is not designed for use as a screening tool. This study aimed to develop predictive models identifying pediatric patients at risk of sepsis within 24 hours of admission. Multiple tree-based and deep learning models were trained utilizing clinical and laboratory data from the initial four hours of presentation. Both the LightGBM and LSTM architectures demonstrated superior performance, …

Cellular Mechanisms Of Spinal Motoneuron Hypoexcitability Underlying Dynapenia In Aging, Ibrahim Abdul Halim

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Age-related weakness remains poorly understood as the underlying mechanisms remain unclear. While synaptic input and muscular changes have been investigated with age, intrinsic motoneuron excitability alterations are often overlooked. This thesis provides the first direct assessment of intrinsic excitability and ion channel properties of spinal α-MNs from male and female mice across three ages: young, middle aged, and old. Our findings reveal a decline in intrinsic excitability of motoneurons with age in both sexes. Mechanistic analysis shows sex specific differences: female motoneurons exhibit increased dendritic size, hyperpolarized RMP, and SK channel overactivation, whereas males show only SK overactivation with age. …

Wearable Sensor Data Analysis For Machine Learning-Based Detection Of Posture And Autonomic Responses, Chaitanya Vardhini Anumula

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This study investigates how Iyengar yoga postures influence autonomic nervous system (ANS) activity by analyzing multimodal physiological signals collected via wearable sensors. The physiological mechanisms underlying Iyengar yoga’s therapeutic effects remain under-explored at the granular, pose-level. Using data collected from 16 participants, this research evaluates whether machine learning models can distinguish between baseline, parasympathetic-dominant, and sympathetic-dominant states based on wrist-worn sensor data. The goals were to explore whether subtle postural variations elicit measurable autonomic responses and to identify which sensor features most effectively capture these changes. Participants performed a sequence of yoga poses while wearing synchronized sensors measuring electrodermal activity …

Impact Of Graph Structures For Rag Outcomes In Llms, Chris Davis Jaldi

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Explainability, interpretability and adaptability (EIA) remain three central motivations for next-generation Artificial Intelligence (AI), especially as Large Language Models (LLMs) continue to engage with ever-increasing knowledge bodies. As the landscape pushes toward controllable agentic Retrieval-Augmented Generation (RAG) systems where AI agents engage in iterative, guided reasoning, a critical question arises as to the extent to which the knowledge design itself shapes these models' reasoning behavior. This work conducts a systematic evaluation of how different conceptualizations and representation of the identical knowledge affect an LLM's path-based reasoning capabilities. Through the introduction of controlled variations along graph structural complexity, linguistic and semantic …

Re-Parameterizing Adversarial Reprogramming In Low-Dimensional Subspace For Efficient Software Vulnerability Detection, Hootan Alavizadeh

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Software vulnerabilities are a major cause of security breaches, making effective detection critical. Traditional learning-based methods require large datasets and significant computational resources, which are often impractical due to high annotation costs and data scarcity. To address this, we propose an innovative system, RearVul, which Re-parameterizes adversarial reprogramming in a low-dimensional subspace for software vulnerability detection. Unlike conventional approaches, RearVul repurposes a pre-trained classification model using adversarial reprogramming, enabling detection with minimal modifications. It learns a universal perturbation applied to program representations, preserving the original model’s feature extraction capabilities while adapting it to a new domain. Furthermore, we introduce a …

Subjective Readiness Forecasting Using Supervised Machine Learning And Wearable Device Data, Nathaniel Michael Weiland

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Recent advances in wearable technology allow continuous monitoring of physiological and behavioral data, opening new opportunities for real-time assessments of readiness and well-being. However, creating predictive models that generalize across diverse users remains challenging, especially in high-stakes settings like the military, where preventable injuries, illnesses, and stress-related performance declines are frequent. This research assesses the feasibility of using supervised machine learning models trained on wearable device data to predict subjective readiness indicators—recovery, stress, injury, and illness. Data from over 10,000 users in the OHWS (Optimizing the Human Weapons System) program combined daily check ins with physiological metrics from Garmin, Polar, …

Computational Assessment Of Vitrimers Self-Healing For Renewable Energy And Aerospace Structures, Walaaeldin Mohamed Ahmed Derbala

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Self-healing polymers, particularly vitrimers, are emerging as promising candidates in the development of advanced materials for renewable energy and aerospace structures. These materials exhibit dynamic covalent bond exchange mechanisms that enable reprocess ability, damage repair, and extended operational lifetime under harsh conditions. This study presents a density functional theory (DFT)-based computational investigation of the mechanistic pathways and energetics of bond exchange reactions in model vitrimer systems. We explore transition states, energy barriers, and thermodynamic features corresponding to associative and dissociative self-healing reactions in vitrimers. The study focuses on Diaminodiphenyl disulfide (AFD), a bifunctional molecule composed of two para-substituted aminophenyl rings …

Ab Initio Simulations For Oxidation Of An Ultra-High Temperature Ceramic (Hfb2), Wesley I. Black

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Ultra-High Temperature Ceramics are a class of ceramics that possess high strength and melting points in excess of 3000°C. These ceramics are promising for aerospace applications, where materials need to endure high-temperature and high-stress environments. Utilizing ab initio simulations, this thesis research focuses on the atomistic details of oxidation for a typical ultra-high temperature ceramic material, namely hafnium diboride. The simulations provide energy barriers for transition from the initial to final structures via transition states on the (0 0 0 1) surface. These result in estimates for reaction rates and other thermodynamic features that are essential for assessing applicability under …

Reinforcement Learning For Adversarial Environments: Multi-Agent Hide And Seek With Multi-Modal Sensing, Christian Alejandro Carrizales

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The development of intelligent and competitive agents in AI versus AI adversarial environments was explored through the utilization of reinforcement learning techniques with sensing modalities. A Hide-and-Seek simulation environment was developed using the Unity game engine along with the ML-Agents Toolkit. An engagement test campaign with a set of performance metrics was designed. Four AI versus AI adversarial scenarios were considered using the Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) multi-agent reinforcement learning algorithms. Furthermore, the impact of sensing modalities on competing agents’ learning performance was investigated by varying the sensing capabilities of the hider and seeker, respectively. Experiments …

Dataset Generation For Routing Policy Study In Ad Hoc Wireless Networks, Vishnu Vishnu Priya

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Ad Hoc wireless networks, with their decentralized architecture and dynamic topology, present challenges in reliable and energy-efficient routing. While machine learning (ML) and reinforcement learning (RL) offer promising solutions, progress is limited by the lack of realistic, high-fidelity datasets. This research introduces a simulation-based framework for generating four diverse datasets representing combinations of node mobility (mobile vs. static) and spatial distribution (random vs. clustered). Each dataset captures critical metrics such as Signal-to-Interference-plus-Noise Ratio (SINR), bottleneck rate, and power consumption across multi-hop paths. A lookahead-based greedy routing algorithm with scenario-aware power control is implemented to emulate practical behavior. Supervised ML models, …

Isometric Centroid Encoder (Ice) And Synthetic Data Generation Approaches For Biological Datasets, Prathyusha Kanakamalla

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This thesis addressed two main challenges in biological data analysis: structure-preserving dimensionality reduction and synthetic data generation for small sample datasets. I proposed the Isometric Centroid Encoder (ICE), a supervised dimensionality reduction method that preserves pairwise distances between class centroids during dimension reduction. Unlike existing methods like Centroid Encoder and Super Encoder, ICE explicitly maintains geometric relationships between biological classes, achieving nearly perfect structure preservation at C dimensions (where C equals the number of classes) with strong performance even in 2D and 3D spaces. Additionally, I compared three generative models (VAE, LSH-GAN, and scDiffusion) for synthetic data generation on small …

Hydrogen Storage Density And Adsorption Energy Barriers On Li-Decorated Bc3 Nanosheet, Sri Venkat Pavan Upasi

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Hydrogen is considered an emerging carrier of clean energy with renewable capabilities. Widespread hydrogen energy utilization necessitates efficient storage strategies. Functionalized nanomaterials, such as Li-decorated BC3 nanosheets, are among the primary candidate materials for hydrogen storage. This research investigates the feasibility of hydrogen storage by estimating energy barriers and their dependence on storage density on Li-decorated BC3 nanosheet. Density functional theory (DFT) simulations provide estimates of adsorption energies and saddle points for hydrogen storage and compare corresponding reaction rates. The results are expected to help us understand the advantages and possible shortcomings of hydrogen storage on such nanomaterials.

Mid-Wave Infrared Imaging Of Supersonic Combustor Exhaust Flow, Nathan Childs

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A study was completed on the application of mid-wave infrared (MW-IR) imaging for diagnostics in supersonic combustion exhaust flows, with the objective of enhancing optical access and measurement accuracy. Other optical based techniques of thermography require complicated setups and analysis to determine the temperature of a flow with high accuracy, where MW-IR is a more simplistic "point and shoot" technique. The simplicity of MW-IR comes with the trade off of gaining simplicity but adding uncertainty into the measurements. The MW-IR camera was positioned to view the exhaust of the combustor to provide an unobstructed view of the flow, addressing limitations …

Laminar Separation Control Of An Eppler 387 Airfoil, Vincent R. Sheeler

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A variety of aerodynamic devices operate at low Reynolds number conditions, such as unmanned aerial vehicles and low-pressure turbines in gas turbine engines. At low Reynolds numbers, many airfoils experience laminar boundary layer separation as the fow lacks the energy to overcome the adverse pressure gradient. Researchers have documented a variety of methods which can suppress laminar separation, and now focus on ways to reduce energy requirements to provide efective fow control. Aspects of fow control strategy such as actuator location and pulsing at frequencies which exploit natural instabilities in the fow can reduce energy requirements. In a study by …

Using The Historical Equity Action Lens (Heal) To Identify And Remedy Transportation Inequities From The Akron Innerbelt Project, Olivia Lane

Williams Honors College, Honors Research Projects

This project will utilize the Historical Equity and Action Lens (HEAL) to address transportation inequities in marginalized communities by incorporating historical and cultural insights into data collection and analysis. Specifically, the project will focus on the Akron Innerbelt, an infamous highway project that significantly impacted historically Black neighborhoods. By examining the historical, economic, and social context of the Innerbelt, the project will identify the project's long-term impacts Akron communities. The goal is to use this knowledge to inform improve transportation equity in the affected areas by developing a plan for the Innerbelt since its vacancy in 2016. The project will …

Mobile Weather Satellite Receiver, Luke Datsko, Sam Watts, Jason Do, Adam Bechtler

Williams Honors College, Honors Research Projects

The "Mobile Weather Satellite Receiver" project aims to create a portable, user-friendly device that receives and displays weather information from geostationary satellites, addressing the limitations of traditional weather sources like the Internet and weather radio, particularly in remote areas. This device will collect and demodulate satellite data, including imagery and Emergency Managers Weather Information Network (EMWIN) forecasts, to provide users with detailed local forecasts and real-time alerts.

Designed with a user-centric approach, the system includes a satellite dish, Software Defined Radio (SDR), a Raspberry Pi, and a custom software interface for ease of use. Its portability and ability to function …

An Improved Method To Protecting Skin Graft Dressings Following Surgery In Severe Burn Patients, Andrew Martin, Matt Flaker, Hailey Essinger

Williams Honors College, Honors Research Projects

Severe burns, including deep second- and third-degree burns, affect over 450,000 people annually in the U.S., often requiring skin grafts for treatment. Recovery involves wearing wound dressings covered by bandage wraps for at least two weeks. While wraps are breathable, versatile, and simple, they can be painful to apply, especially for larger patients, and their compression varies based on the person applying them. This poses challenges when untrained caregivers are involved. Additionally, wraps often slip during physical therapy. Burn care units seek a new solution that matches current wraps in breathability and comfort but offers quicker application, controlled compression, and …