Digital Commons Network^™

Teaching Integrated Stem In Middle School, S. Selcen Guzey

Purdue University Press Books

Teaching Integrated STEM in Middle School is a valuable resource for educators, researchers, and policymakers who are committed to furthering integrated STEM education. Through a review of the literature on the topic, the volume offers a clear understanding of the impact of integrated STEM education on instructors’ teaching practices and student outcomes. The book presents a framework and instructional guide that educators can utilize to develop new curricular materials. Two sample units—focused on designing a two-stage water filter and formulating sunscreen—provide step-by-step guidance for lesson implementation and offer strategies for assisting students as they use engineering models to devise design …

Protocols In Root-Microbe Interactions, Anjali S. Iyer-Pascuzzi

Purdue University Press Books

Protocols in Root-Microbe Interactions describes laboratory protocols that have been developed and optimized for scientists working in root-microbe interactions, specifically for those wanting to quantify immune responses in plant roots. The experiments are focused on cellular to whole-root scale and include molecular biology, biochemistry, and histology techniques. Written in an easy-to-understand fashion that is suitable for both early career and experienced scientists, the protocols were optimized for tomato roots but can easily be adapted to roots of other plant species, or if needed, to leaves. The book includes information on quantifying pattern-triggered immune (PTI) responses in plant roots and covers …

Market Signals From Online Behavior, Nicole J. Olynk Widmar, Michael L. Smith, Erin Robinson

Purdue University Press Books

Market Signals From Online Behavior asks, What do social media trends, Google searches, and online chatter reveal about consumer behavior? It also poses the question, How can we interpret these signals without losing sight of the people behind the posts? This book examines the digital traces left by consumers and explores how these signals intersect with food, agriculture, retail, and beyond.

Drawing from real-time data and social-listening analysis, Market Signals connects the dots between what is trending online and what it means for markets in the real world. Whether it is the rise of plant-based eating, changing holiday shopping norms, …

Clear And Concise: Technical Writing For Biological Engineers, Abigail S. Engelberth

Purdue University Press Books

Clear and Concise: Technical Writing for Biological Engineers is a practical guide designed to help students and early career engineers communicate their work with clarity and confidence. Drawing on years of teaching experience, Abigail S. Engelberth breaks down the essentials of technical writing into approachable steps, showing readers how to organize ideas, present data effectively, and write reports that meet professional standards.

Rather than overwhelming readers with theory, the book focuses on real-world application. It includes examples, checklists, and strategies for common engineering documents including formal and memo-style lab reports. Special attention is given to visuals, formatting, and the role …

Horse Evaluation: A Multibreed Text For Competitive Youth Equine Judges, Colleen M. Brady

Purdue University Press Books

Horse judging is one of the most popular activities in 4-H, FFA, and other youth-development organizations. Judging teaches youth how to both critically analyze animals based on a specific set of criteria and justify their decisions through oral reasoning. This book includes information on examining a wide variety of breeds—from quarter horses and Arabians to Saddlebreds, Drafts, and Miniatures—and covers a range of disciplines. Both halter and performance classes are explored, and the rules and regulations used to govern contests at the national level are provided. Example sets of reasons are supplied for most classes, as are lists of potential …

Reviving The Skies: The Impact Of Government Focus On Aviation Industry Growth In The Post-Covid World, Sumeet Hassan Anwar, Humna Asad

Journal of Aviation Technology and Engineering

Travel restrictions and border closures during the COVID-19 epidemic drastically reduced air traffic that affected the aviation sector. With an eye toward regional variances and public-private alliances, this essay investigates how government policies, financial interventions, and regulatory frameworks assisted recovery attempts. The essay also looks at how network-based resilience models lower vulnerabilities and improve operational connection, thus guaranteeing future disturbance readiness. Autoregressive integrated moving average models, among other forecasting instruments, help to forecast aviation demand and match recovery plans with changing market dynamics. By means of comparative policy analysis and network theory, this study reveals best practices from Asia, Europe, …

The Evolution Of Mro Outsourcing: Global Trends, Regulatory Challenges, And Strategic Considerations In Aviation Maintenance, David C. Ison

Journal of Aviation Technology and Engineering

The maintenance, repair, and overhaul (MRO) industry plays a critical role in ensuring the safety, efficiency, and sustainability of the global aviation sector. As airlines seek to reduce costs, optimize operations, and access specialized expertise, MRO outsourcing has become an increasingly prevalent strategy. This essay examines the key drivers of MRO outsourcing, including cost reduction, access to advanced technologies, and the focus on core competencies. The essay also explores emerging trends such as the rise of new MRO hubs in Asia and the Middle East, the integration of predictive maintenance and artificial intelligence, and the growing emphasis on environmental sustainability. …

Teachers’ Perspectives On Facilitating Design Talks With Young Learners, Chelsea J. Andrews, Jessica Watkins, Kristen B. Wendell, Rae Woodcock, Vera Gor, Naina Sood Fox, Molly Malinowski, Rachel Bandi, Shannon Rausch

Journal of Pre-College Engineering Education Research (J-PEER)

With intentional teacher facilitation, whole-class conversations can help students refine their engineering reasoning, consider new ideas, and make novel connections between different ways of defining or solving a problem. These conversations can also help students expand their engineering thinking to include perspectives of care and socioethical deliberations. A team of classroom teachers and university researchers has been enacting and studying whole-class engineering design conversations—Design Talks—in first through sixth grade classrooms. We organize Design Talks in five genres: problem-scoping talks, idea generation talks, design-in- progress talks, design synthesis talks, and impact talks. After five years of planning, implementing, and analyzing recorded …

Stocks And Shocks: Assessing The Relative Roles Of Public And Private Inventories In Buffering Rice Price Volatility In The Philippines, Bernhard Dalheimer, Kenneth Foster, Gerald E. Shively, Valerien O. Pede, Dela-Dem Doe Fiankor, Jacob Ricker-Gilbert, Pratibha Bist

Department of Agricultural Economics Faculty Publications

Public stockholding of food is politically contentious and economically challenging. Although private stocks are generally understood to be more efficient than public stocks at providing a reliable buffer against production shortfalls, private stocks often fail to stabilize prices during extreme food market shocks. Moreover, maintaining large public stock programs in which the government acts as the buyer or seller of last resort, can be very costly. This paper analyzes the recent historical success of public and private rice stocks in stabilizing domestic rice prices in the Philippines, the world’s largest net importer of rice. Relying on competitive storage theory and …

Fostering Psychological Ownership And Self-Authorship In Higher Education: Pathways To Student Engagement, Growth And Knowledge Creation, Noora Heino, Markku Ikävalko, Anssi Tarkiainen, Terhi Virkki-Hatakka

International Journal of Teaching and Learning in Higher Education

This study explores the intersection of psychological ownership (PO) and self-authorship (SA) in the context of university students’ project-based learning. It examines how students develop a sense of ownership over their course projects, ideas, and knowledge they create, and how this engagement shapes their learning, identity, and sense of self. The findings highlight the role of control and perceived idea quality in fostering psychological ownership, as well as the importance of intimate knowledge and perceived object quality in supporting self-authorship. The study underscores that when students feel connected to their ideas, their motivation, persistence, and engagement increase, especially in creativity-driven …

Orientation-Specific Surface Response Of Shot Peening In Laser Powder Bed Fusion Ti-6al-4v Parts, Sivasubramanian Chandramouli, Michael S. Titus, Michael P. Sealy

Purdue Polytechnic Graduate Student Poster Symposium

Critical aerospace components, such as turbine blades and landing gears, are increasingly produced using additive manufacturing (AM), especially laser-powder-bed-fusion (LPBF) due to its design flexibility. However, the inherent high surface roughness and tensile residual stresses in LPBF parts compromise performance and dimensional stability. Shot peening, a surface work-hardening process, is an effective post-processing solution.

The research objective is to understand the surface strengthening effect from grain refinement by inhomogeneous elastic-plastic deformation across surface orientations (0-90°) in AM parts. Peening parameters, specifically coverage and peening angle, are optimized to mitigate orientation-dependent surface properties in LPBF Ti64. Under optimized conditions, shot peening …

Visual Augmented Tutorial Agent For Software Tutorial, Shengyang Luo, Yingjie Chen

Purdue Polytechnic Graduate Student Poster Symposium

Many existing software tutorials lack clear interaction cues (clicks, drags, shortcuts), causing learners to frequently rewind and lose flow. To address this, we propose a system that infers user actions by analyzing frame-to-frame changes using a multimodal LLM, then overlays predefined visual indicators, such as click ripples, drag trails, and shortcut labels, at precise cursor positions. To ensure reliable task classification and avoid hallucinations, we integrate RAG, grounding the model with official software documentation. This approach aims to enhance older tutorials with accurate, actionable interaction feedback, improving clarity and learning efficiency.

Using Generative Ai In Computer Science Internships; Implications For Career Readiness, Mitra Panahi, Lucas G. Zangari, Gaurang Kamat, Olufisayo Omojokun, Alejandra J. Magana, Ricardo Eiris, Pedro Guillermo Feijóo-García

Purdue Polytechnic Graduate Student Poster Symposium

This empirical study delves into how computer science interns use generative AI tools during their internship experience and shows how these technologies connect academic training with practical professional practice. Grounded on Social Cognitive Career Theory (SCCT), we examine how GenAI usage influences students' self-efficacy and internship outcomes during internships in fast-changing tech environments. Data were gathered via mixed-methods surveys from 40 undergraduate computer science students at a large Southeastern U.S. public university, with internship experience and also worked as teaching assistants. Findings show that while GenAI got the green light in 65.8% of internships, its use was cautious and infrequent …

The Effects Of Altitude On Air Source Heat Pump Performance In The Andes, Ajay Dalal, Walter Daniel Leon-Salas, William Hutzel, Pedro Flores Larico, Miguel Angel Vizcardo Cornejo, Mauricio Postigo Malaga, Miguel Angel Ocharan Pichu

Purdue Polytechnic Graduate Student Poster Symposium

The global push for decarbonization has highlighted the need for sustainable heating solutions, particularly in geographically challenging and remote locations such as the Peruvian Andes, where traditional heating methods are inefficient and pollute the environment. Air source heat pumps are a viable solution but come with their own challenges, including cost, access to electricity, and performance degradation at high altitudes. A project is underway to install and evaluate an air-source heat pump at a research station located at an altitude of 4,128 m in Sumbay, Peru. The primary goal of this research is to evaluate and expand existing models that …

Tailoring Cathode Structure And Materials To Enable Fast Charging And Extended Lifespan In Li-S Batteries, Yuxuan Zhang, Yeongjun Oh, Sunghwan Lee

Purdue Polytechnic Graduate Student Poster Symposium

The practical implementation of Li–S batteries is limited by sluggish sulfur redox kinetics and inefficient ion transport in high-mass-loading cathodes, challenges that are further exacerbated under fast-charging and high-power operation. Conventional electrocatalyst-based strategies can partially suppress electrochemical polarization by lowering reaction energy barriers, yet they do not address concentration and ohmic polarizations, which dominate in thick electrodes. Here, we introduce a coupled material–architecture design that integrates electrocatalysts into a low-tortuosity, correlated dual-gradient electrode fabricated using programmable high-resolution stereolithography and pyrolysis-induced carbonization. By deliberately pairing a microscale pore-size gradient with a corresponding active-material gradient, the electrode synchronizes redox progression across its …

Stretchable Screen-Printed Tpu–Cnf Sensors: Fabrication And Electromechanical Performance, Diana Narvaez, Brittany Newell

Purdue Polytechnic Graduate Student Poster Symposium

Stretchable strain sensors are essential for motion monitoring in wearable systems and soft robotics, requiring materials that combine high elasticity, durability, and stable electromechanical response. In this work, a screen-printable TPU–CNF conductive ink was formulated and used to fabricate stretchable sensors on 3D-printed TPU substrates. Comparison with fully conductive FDM-printed TPU dog-bone samples revealed porosity, weak interlayer adhesion, and unstable resistance, motivating the adoption of a solvent-based ink approach. The TPU–CNF ink produced uniform, well-adhered conductive networks through controlled microcracking during drying, enabling reliable strain sensing across three geometries (i.e., zigzag, interdigitated, line). Mechanical testing showed high elongation and consistent …

Potential Electric Vertical Taking-Off And Landing Aircraft (Evtol) Site Location Considering Flight Missions And Repeatability, Yinfei Liu, Joseph Hupy

Purdue Polytechnic Graduate Student Poster Symposium

As electric vertical taking-off and landing aircraft (eVTOL) technology and associated infrastructure continue to advance, the prospect of achieving actual commercial operations is gradually becoming feasible. For this novel urban transportation mode, the capability to continuously accomplish flight missions is one of the critical factors determining its eventual eligibility for commercial operation. An analysis of applying rapid charging can provide valuable insights into the development and potential solutions for enhancing eVTOL mission repeatability, given the limitations of eVTOL battery capacity and endurance. This study focuses on the optimal location selection of eVTOL sites through a hierarchical screening approach utilizing ArcGIS, …

Optimal Anchor Placement For Cable-Driven Parallel Robots On Curved Surfaces, Lei Jin, Dongming Gan, Tarek Taha

Purdue Polytechnic Graduate Student Poster Symposium

Cable-Driven Parallel Robots (CDPRs) are increasingly used for inspection and maintenance on large curved surfaces where traditional planar anchor layouts fail. This work introduces a unified geodesic–optimization framework for determining optimal anchor configurations that ensure both static feasibility and dynamic efficiency. The method first models curved surfaces using local tangent-plane coordinates to compute cable directions accurately, then evaluates anchor candidates through linear-programming tension optimization. Dynamic simulations along representative motion paths—spiral, circular, and zigzag—quantify total cable energy for ranking feasible configurations. Results show that anchors raised above mid-latitude and symmetrically distributed around the workspace minimize both peak tension and total energy …

Modification Of Copper-Based Catalysts With Conductive Polymers For Co2 Conversion With High C2+ Selectivity, Minyoung Kim, Dong Hun Lee, Reilly Eiynck, Meredith Zannacker, Reese Resheske, Sujat Sen, Sunghwan Lee

Purdue Polytechnic Graduate Student Poster Symposium

Carbon Dioxide (CO2) is abundant in our atmosphere, and its conversion to value-added using renewable electricity is currently an active area of investigation at both lab and commercial scale. Previous research has shown that copper-based catalysts can produce a wide range of hydrocarbons through the electrochemical reduction of CO2 under ambient conditions. Herein, we report on the modification of copper-based thin films as composite catalysts by depositing conductive polymers to improve the selectivity of CO2 conversion as well as surface stabilization. The copper layer was thermally evaporated onto PTFE substrates, showing a highly uniform film morphology and thickness with excellent …

Integrated Simulation Of Alloy Composition And Process Parameters For Fluidity Optimization In Hpdc Aluminum Alloys, Xin He, Xiaoming Wang

Purdue Polytechnic Graduate Student Poster Symposium

Fluidity is a critical factor in high-pressure die casting (HPDC) of aluminum alloys, directly influencing mold filling behavior, defect formation, and the mechanical reliability of cast components. This study employs multiphase computational fluid dynamics (CFD) simulations to investigate how alloy composition, process parameters, and die conditions collectively affect molten metal flow and solidification dynamics. Key variables include viscosity, thermal conductivity, solidification range, pouring temperature, injection velocity, die geometry, and preheating temperature. Alloys with a narrow solidification range and lower thermal conductivity exhibit prolonged liquid-phase duration, which enhances flowability and reduces the risk of cold shuts and porosity. In contrast, increased …

Function-Adaptive Hulls: Reconfigurable Building Material For Multipurpose Unmanned Vehicles, Yubing Han, Brittany Newell, Richard Voyles

Purdue Polytechnic Graduate Student Poster Symposium

This research presents a scalable building material for unmanned vehicles, inspired by origami principles and designed for adaptive functionality and stealth. Traditional fixed-shape vehicles face significant limitations in optimizing performance metrics such as velocity, payload capacity, and observability, often resulting in highly specialized designs that increase costs and resource consumption. To address the challenge, we introduce self-folding building material that incorporates pre-constructed creases, embedded actuation mechanisms, and location tags. The system utilizes electric rails organized on multiple levels, enabling switch modules to traverse internal channels and activate folding circuits with precision. A two-step folding process is demonstrated to reduce actuation …

From Text To Action: Seeing Software Commands Through Ar Gestures, Shengyang Luo, Yingjie Chen

Purdue Polytechnic Graduate Student Poster Symposium

Learning feature-rich software often requires mastering complex keyboard-mouse combinations, yet text-based tutorials struggle to convey how these interactions should physically happen. Many learners pause, re-read, and search online, still unsure how to execute commands until a TA or peer demonstrates the gesture in person. We explore an AR-based tutorial approach that displays 3D hand and input animations directly within the learner’s view as they operate the software. By turning written instructions into embodied, real-time motion guidance, this system aims to make advanced software interactions more intuitive and accessible, reducing confusion and supporting confident skill development.

From Outdoor Curiosity To Engineering Learning: Developing An Augmented Reality Module Grounded In Student Experiences, Mohammed Metwaly, Adel Elwakil, Selena Nadjarian, Farid El Breidi

Purdue Polytechnic Graduate Student Poster Symposium

Engineering education often overlooks the formative influence of outdoor experiences in shaping students’ curiosity about how things work. This study examines how such experiences contribute to students’ interest in engineering and demonstrates how those insights can inform experiential learning tools. A mixed-methods survey was administered to 189 Mechanical Engineering Technology undergraduates, yielding 150 complete responses. The instrument combined Likert-scale items and open-ended prompts to capture demographics, nature affinity, formative outdoor activities, and connections between those experiences and engineering interest. Reliability testing confirmed strong internal consistency (α = 0.854; ω = 0.751). Nearly half of respondents (47%) identified outdoor experiences as …

Explanations For Machine Learning Pipelines Under Data Drift, Jahid Hasan, Romila Pradhan

Purdue Polytechnic Graduate Student Poster Symposium

Ensuring the robustness of data preprocessing pipelines is essential for maintaining the reliability of machine learning model performance in the face of real-world data shifts. Traditional methods optimize preprocessing sequences for specific datasets but often overlook their vulnerability to future data variations. This research introduces a vulnerability score to quantify the susceptibility of preprocessing components to data shift. We propose a Linear Regression approach to establish a predictive relationship between the vulnerability of the pipeline components and changes in the model’s performance. The generated relationships act as explanations for practitioners of the system and help them quantify the robustness of …

Emotion Driven Rumor Detection And Analysis: An Llm(Large Language Model) Augmented Approach, Chinelo Njoku, Yingjie Chen

Purdue Polytechnic Graduate Student Poster Symposium

Misinformation and rumors during public health crises significantly affect lives and increases mistrust in government and public health institutions. The circulation and amplification of rumors often worsen disease transmission and impede effective interventions. Historically, rumor spread has been a recurring issue in public health emergencies. For example, during the Ebola outbreak, misinformation about the virus and its treatment created deep mistrust of health workers. Similarly, in the COVID-19 pandemic, widespread misinformation fueled public panic and vaccine hesitancy. Previous research has primarily identified social media as a channel for rumor dissemination and focused on automatic rumor detection for fact-checking using binary …

Electro-Thermal Performance Of Dc-Powered Heat Pumps In Nanogrid Applications, Ehijie Ebewele, William Hutzel

Purdue Polytechnic Graduate Student Poster Symposium

This research investigates the electro-thermal performance of DC-powered air-source heat pump systems integrated into residential DC Nanogrids. By avoiding AC-DC conversion losses and further optimizing renewable energy integration, DC-powered heat pumps offer better energy efficiency and system stability. A comprehensive MATLAB/Simulink model is developed by integrating electrodynamics and thermodynamics to predict system behavior across a wide range of environmental and operational conditions.

Edge Ai-Enabled Vagus Nerve Analysis For Adaptive Neuromodulation In Diabetes, Saeka Rahman, Reepa Saha, Md Motiur Rahman, Ardavan Vakil, Hope Teng, Muhammad Arafin Khan, Benjamin Larimer, Rita Basu, Andy Basu, Amy Warriner, Miad Faezipour, S. Abdollah Mirbozorgi

Purdue Polytechnic Graduate Student Poster Symposium

Comprehending the neural mechanisms underlying Type 2 Diabetes (T2D) is critical to developing next generation bioelectronic therapies. This work-in-progress presents a novel neural interface that integrates edge artificial intelligence (AI), machine learning (ML), and flexible implantable electronics to record, analyze, and modulate vagus nerve activity in real time for potential diabetes treatment and reversal. The proposed system combines low-power, semi-analog signal processing with embedded AI/ML algorithms capable of performing on-chip feature extraction and classification of neural signals under stringent power and communication constraints. By leveraging edge-based learning, the platform will enable adaptive neuromodulation of vagus nerve activity, providing a closed-loop …

Assessing Disparities In Breast Cancer Incidence Across Indiana Counties With Geographic Information System And Machine Learning, Shuning Yin, Gaurav Nanda, Raji Sundararajan

Purdue Polytechnic Graduate Student Poster Symposium

This study investigates potential spatial variations in breast cancer incidence across Indiana counties using geographic information systems (GIS) and machine learning (ML) techniques. Breast cancer continues to be a major public health challenge influenced by unequal access to healthcare, socioeconomic disparities, lifestyle factors, and environmental exposures. By integrating GIS and ML, this research identifies key factors and potential spatial patterns associated with breast cancer incidence across Indiana. The statistical analysis produced a highly significant result (p < 0.001), indicating that the independent variables collectively contribute to explaining breast cancer incidence, though the model’s explanatory power was moderate (adjusted R² = 0.25). Among all variables, distance to the nearest hospital and tobacco expenditure showed significant associations with breast cancer incidence, while other factors such as health insurance coverage were not statistically meaningful. The Koenker (BP) statistic was 5.141, indicating spatial stability and confirming that no distinct spatial variation was observed across counties. Findings show that counties farther from healthcare facilities did not necessarily have higher breast cancer incidence, and higher incidence in urban areas, such as Indianapolis, Lake, and Porter Counties, likely reflect better access to screening and diagnosis rather than higher disease occurrence. These results emphasize the importance of incorporating additional variables, including genetic predispositions, racial and ethnic disparities, and environmental conditions, in future studies. Expanding the analytical framework could enhance understanding of spatial patterns and guide efforts to improve healthcare access and cancer prevention in Indiana.

Ai-Powered Pacifier With Intraoral Sound Analysis For Neonatal Pulmonary Monitoring, Shiva Shokouhmand, Md Motiur Rahman, Saeka Rahman, Indya Mooney, Guoliang Zhang, Smriti Bhatt, Namasivayam Ambalavanan, Colm P. Travers, S. Abdollah Mirbozorgi, Miad Faezipour

Purdue Polytechnic Graduate Student Poster Symposium

Respiratory monitoring in neonates remains a clinical challenge due to the limitations of existing pulmonary function assessment tools and the infant’s delicate physiology. This work-in-progress presents an artificial intelligence (AI)-driven framework for intraoral respiratory analysis using a smart pacifier platform that integrates acoustic sensing, embedded electronics, and deep learning. The proposed AI model is based upon a deep convolutional neural network that processes intraoral breathing sound reflections passively, or in presence of active sound stimuli. By learning complex temporal-spectral features from the breathing sound signals, the AI model will estimate key cardiorespiratory measures (e.g., respiratory rate, lung capacity) and the …

Adaptive Focus Agent For Video-Based Software Learning, Shengyang Luo, Yingjie Chen

Purdue Polytechnic Graduate Student Poster Symposium

Not every learner has a powerful computer or a dual-monitor setup. Some follow software tutorials with only a laptop, or even a phone, squinting to catch tiny cursor movements and clicks meant for larger screens. These moments slow their progress, break their flow, and make advanced digital skills feel farther away than they should be. Our work aims to explore how an AI-assisted dynamic zoom system can help. By automatically detecting interaction moments and enlarging the relevant region in tutorial videos, we aim to make subtle actions clearer, support confident learning across device conditions, and bring expert-level instruction closer to …