Digital Commons Network^™

Globalizing The Engineering Job Market: Optimizing Engineering Career Expos To Serve International Students, Hailey A. Hesseltine

Journal of Global Education and Research

As the United States hosts approximately one million international students annually, it becomes imperative that on-campus resources are tailored to meet the needs of this diverse student population. One on-campus resource that is crucial to student success is career services, especially considering the aspirations of many international students to secure employment post-graduation. To address this, this study aimed to understand the satisfaction levels of international engineering students with an engineering career expo in Hawaiʻi. Utilizing a combination of surveys and interviews using a neo-racism framework, international students shared their experiences from the career expo through discussion and assessment. Information given …

Impact Of Femalized Kinesthetic Learning Model On African American Middle School Girls’ Career Interest, Mercy F. Fash, Andrea Ofori-Boadu

Journal of Global Education and Research

Engaging African American middle school girls in out-of-school-time (OST) Architecture, Engineering, and Construction (AEC) programs can boost interest in male-dominated AEC careers. This study adopts Lent’s Social Cognitive Career Theory to evaluate the impact of an OST feminized AEC kinesthetic learning model (fAEC-KLM) on the career interests of this demographic. Through a qualitative research approach, fourteen (14) African American middle school girls from Guilford County, NC, completed pre- and post-interviews on how fAEC-KLM interactions influenced their AEC career interests. Inductive thematic analysis was carried out on transcribed interviews. Results show that effective components, such as lectures on AEC, bridge construction …

Calibration Of Time-Domain Impedance Probe (Tdip) To Investigate Space Plasma Dynamics During Periods Of Ionospheric Instability, Piyas Chowdhury, Soumyajit Dey, Edmund A. Spencer

Shelby Hall Graduate Research Forum Posters

The traditional Plasma Impedance Probe (PIP) is popular for diagnosing parameters of the ionospheric plasma to study the space environment. However, the resolution of data measurements of existing PIP instruments, operating at higher frequencies, limits the analysis to studying the plasma features at electron scales. Studying plasma ion parameters is essential to understanding the ionospheric instability growth rates. This can only be accomplished by operating a diagnosing instrument at lower frequencies corresponding to ion scales. A recently developed Time Domain Impedance Probe (TDIP) is implementable for fast moving spacecraft using a time domain approach. The instrument has higher measurement resolution …

Improving Cellular Retention And Distribution To Promote Arteriogenesis In A Mouse Model Of Chronic Arterial Occlusion, Nancy Huang

Biomedical Engineering

Peripheral Arterial Occlusive Disease (PAOD) affects millions of people in the United States, creating pain, discomfort, and limited mobility due to restricted blood flow from obstructed arteries. While current treatments include lifestyle changes and revascularization procedures, these options are often insufficient or inaccessible because of procedural pain and socioeconomic barriers. In some cases, this can lead to critical limb ischemia and amputation as a last resort. Increasing blood flow to the extremities by enhancing collateral vessel growth, a biological process called arteriogenesis, with cell-based therapies can redirect blood flow around obstructions and has potential to mitigate and treat the effects …

Cpap Belly Prevent, Alek Corpuz, Emma Hoffman, Danielle Tran

Biomedical Engineering

Neonates with low gestation periods often face complications such as respiratory distress syndrome, or RDS, which increases risk for complications such as necrotizing enterocolitis. Use of bCPAP helps facilitate regular breathing, but can also force air into the stomach and consequently cause abdominal distention. Clinicians currently use an already inserted feeding tube to vent the accumulated air, however this interrupts the feeding process.

The PreVent device was developed to allow for simultaneous feeding and venting. The dual function minimizes interruptions to NICU nurse workflow and improves capability to relieve abdominal distention before the onset of adverse complications.

Orthopedic Bone Drill, Logan G. Schmid, Matthew T. Wold, May Geng

Biomedical Engineering

This project aims to design a bone drill for orthopedic procedures which alleviates the heat generated in the bone during drilling.

The Effect Of Reduction Of Input-Parameters On Data-Driven Prediction Of Critical Heat Flux In Rod Bundles Using Extended Parameters For Reactor Thermal–Hydraulic Safety, Rehan Zubair Khalid, Atif Khan, Farooq Ahmad, Muthanna H. Al-Dahhan, Atta Ullah

Chemical and Biochemical Engineering Faculty Research & Creative Works

Accurate prediction of the critical heat flux (CHF) is a key pillar for ensuring both the safety and economic performance of nuclear reactors. While machine learning (ML)-based methodologies have demonstrated considerable success in predicting CHF, most existing studies have been confined to simplified geometries, such as single tubes. Conversely, limited attention has been devoted to CHF prediction in realistic reactor environments, particularly within rod bundle configurations, where complex multiphase flow and heat transfer phenomena prevail. In this work we develop different AI models based on large dataset operating conditions as well as the complex geometric features of rod bundles. The …

Navigation Beyond Wayfinding: Robots Collaborating With Visually Impaired Users For Environmental Interactions, Shaojun Cai, Nuwan Janaka, Ashwin Ram, Janidu Shehan, Yingjia Wan, Kotaro Hara, David Hsu

Research Collection School Of Computing and Information Systems

Robotic guidance systems have shown promise in supporting blind and visually impaired (BVI) individuals with wayfinding and obstacle avoidance. However, most existing systems assume a clear path and do not support a critical aspect of navigation—environmental interactions that require manipulating objects to enable movement. These interactions are challenging for a human–robot pair because they demand (i) precise localization and manipulation of interaction targets (e.g., pressing elevator buttons) and (ii) dynamic coordination between the user’s and robot’s movements (e.g., pulling out a chair to sit). We present a collaborative human–robot approach that combines our robotic guide dog’s precise sensing and localization …

A Software Package For Generating Robust And Accurate Potentials Using The Moment Tensor Potential Framework, Josiah Roberts, Biswas Rijal, Simon Divilov, Jon Paul Maria, William G. Fahrenholtz, Douglas E. Wolfe, Donald W. Brenner, Stefano Curtarolo, Eva Zurek

Materials Science and Engineering Faculty Research & Creative Works

We present the Plan for Robust and Accurate Potentials (PRAPs), a software package for training and using moment tensor potentials (MTPs) in concert with the Machine Learned Interatomic Potentials (MLIP) software package. PRAPs provides an automated workflow to train MTPs using active learning procedures, and a variety of utilities to ease and improve workflows when utilizing the MLIP software. PRAPs was originally developed in the context of crystal structure prediction, in which one calculates convex hulls and predicts low energy metastable and thermodynamically stable structures, but the potentials PRAPs develops are not limited to such applications. PRAPs produces two potentials, …

Slo Botanical Garden Outdoor Classroom, Nathan Berger, Jake Galster

Construction Management

This paper focuses on the construction and completion of outdoor benches and tabletops for the renovation of the SLO Botanical Garden’s Outdoor Classroom. This project is student lead for the completion of the Cal Poly SLO Construction Management curriculum requirement of a senior project by the project team consisting of Nathan Berger and Jake Galster. The objective of the project is to build two 12’ long benches that allow the SLO Botanical Garden staff to store four bins beneath each bench. The table tops objective to provide students in the outdoor classroom a flat and level workspace that is removable …

Case Study: The Benefits Implementing Azure 3d Printed Homes Onto Dignitymoves Project In San Luis Obispo, Lucy E. Heimer

Construction Management

California is actively addressing the challenges of housing shortages and climate change. These challenges have shifted the construction industry, steering the market into finding more sustainable means of construction. This case study evaluates the sustainable benefits of modular construction fabricated by Azure Homes. The focused project is a DignityMoves project in San Luis Obispo where modular units are factory built in El Segundo, CA and set on site. DignityMoves is a nonprofit organization that aims to provide housing for unhoused individuals throughout California. Thus far, DignityMoves has opted to use prefabricated modular units as their primary means of construction on …

From Concept To Construction: A Carport For The Slo Botanical Garden, Trent A. Denholm

Construction Management

This paper documents the design, budgeting, procurement and construction of a timber framed carport with architectural shingle roofing at the San Luis Obispo Botanical Garden (SLOBG). The Botanical Garden, a nonprofit organization dependent on community support and volunteer labor, identified the need for covered storage and a dedicated charging station for its golf cart, a vehicle central to daily operations across the property. Without permanent shelter, the cart was exposed to the elements year-round, which contributed to equipment wear and reduced operational efficiency. Working simultaneously as project manager and lead builder, Trent coordinated stakeholder relationships, developed a project budget, secured …

Drainage And Pedestrian Access Improvements At City Farms Slo, Benjamin Marc Kocher, Jacob Anthony Booker

Construction Management

This senior project focused on planning, designing, and constructing drainage and pedestrian access improvements at City Farms SLO, a nonprofit in San Luis Obispo that promotes sustainable agriculture and youth education. Prior to construction, the site experienced significant stormwater pooling and erosion in a central area of the farm, making daily operations and visitor access difficult during wet weather. The team excavated an 80-foot trench drain with appropriate slopes, installed a 15-foot corrugated HDPE culvert with proper bedding and backfill, built a seven-foot pedestrian bridge over the trench, and created a 17-foot gravel pathway connecting the bridge to an existing …

Numerical Investigation On Enhancing The Performance Of A Parabolic Trough Collector Using A Threaded Absorber Tube, Shayan Pourhemmati, Abdellah M. Shafieian, Hussein A. Mohammed, Barun Kumar Das, Majid Tolouei-Rad

Research outputs 2022 to 2026

The growing global demand for energy and heightened environmental concerns have elevated the importance of solar energy harvesting in recent years. Parabolic trough collectors (PTCs) are widely utilized for capturing direct solar radiation; however, conventional PTC efficiency is limited by low convection heat transfer rate in the absorber section, which is then delivered to heat transfer fluid (HTF). This study numerically investigates the use of a threaded tube as a fluid flow disruption technique to enhance heat transfer rate within the absorber, with Reynolds numbers ranging from 4000 to 10,000. Three key geometric parameters of the thread: pitch (300, 150 …

Orthogonal Time Frequency Space Modulation For Underwater Acoustic Communication Systems: A Review, Bevek Subba, Quoc Viet Phung, Stefan Lachowicz, Walid K. Hasan, Muhammad Haziq, Daryoush Habibi, Iftekhar Ahmad

Research outputs 2022 to 2026

Underwater Acoustic Communication (UAC) has garnered significant attention due to its applications in marine science, defence, and exploration. With the vast majority of the Earth's surface covered by water, there is a growing demand for reliable and effective communication techniques in underwater environments. However, the underwater acoustic channel is the most challenging channel due to its harsh characteristics, which significantly hinder the reliability and performance of UAC systems. Orthogonal Time Frequency Space (OTFS) modulation has emerged as a promising solution for next-generation UAC systems to address high Doppler and high mobility scenarios. It has demonstrated tolerance to fast time-varying channel …

Control Of Pore Nucleation And Rearrangement Kinetics During Aluminium Anodizing In Phosphoric Acid Electrolyte, Ilya V. Roslyakov, Nikita A. Shirin, Dmitry M. Tsymbarenko, Sergei N. Pavlov, Sergey E. Kushnir, Nikolay V. Lyskov, Kirill S. Napolskii

Journal of Electrochemistry

Anodic aluminium oxide (AAO) porous films with an interpore distance of several hundred nanometers are of great interest due to their unique interaction with visible and near-infrared light, and high thermal stability up to 1500 °C. These porous films are prepared by aluminium anodizing at high voltages in weak acids, leading to a slow kinetics of initial stages of porous structure formation. Here, we propose an approach to accelerate AAO formation in electrolytes based on weak acids such as phosphoric acid. Aluminium foils, pre-patterned using first anodizing under different conditions and subsequent selective dissolution of a sacrificial AAO layer, were …

Optimized Deep Learning Framework With H2o For Lung Cancer Prediction, Walaa Hassan Ibrahim, Mohamed S. Saraya, Sally M. Elghamrawy, Ali I. Eldesouky

Mansoura Engineering Journal

The automatic diagnosis of lung cancer using chest X-ray (CXR) images has significantly advanced with progress in computing, machine learning, and deep learning. However, detecting lesions and nodules remains challenging due to CXR limitations. Early lung cancer detection is critical for successful treatment, but current AI algorithms often rely on large annotated datasets, which are not always available. To address this, a novel multi-classification deep learning framework is proposed that combines CXR and CT images. This approach leverages the detailed feature detection capabilities of CT scans alongside the complementary views from CXRs, improving early-stage lung cancer detection and classification precision. …

Evaluating Domains' Trustworthiness Based On Uncertainty-Driven Methodologies In The Era Of Sixth Generation, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

The onset of today's innovations pledges to have a beneficial influence on contemporary civilization in an era of intelligent revolutions, setting a precedent for unrivaled efficiency, creativity, and connectedness. The integration between these technologies contributes to the mutual benefit of each one, wherein this relation is a so-called ``reciprocal partnership''. For instance, the sixth generation (6G) wireless networks permit blockchain nodes to coordinate huge volumes of transaction data in real-time. On the other hand, blockchain is considered a secure valve because spectrum sharing can be automated with blockchain and smart contracts. Accordingly, analyzing and evaluating the contribution of these technologies …

Evaluating Regularized Logistic Regression And K-Nn On Mnist Under Increasing Random Missingness, Daniel Markwei

Data Science and Data Mining

This paper investigates the effect of random missingness on the performance of regularized multinomial logistic regression and the k-nearest neighbors (k-NN) classifier for handwritten digit recognition on the MNIST dataset. In particular, we study L1-regularized (LASSO) logistic regression and L2-regularized (Ridge) logistic regression alongside k-NN. Varying percentages of random missingness were introduced into the original dataset, and each model was evaluated in terms of its classification performance. The results show that random missingness degrades the performance of all three classifiers. Overall, k-NN consistently achieves higher accuracy than both L1- and L2-regularized logistic regression across all missingness levels; however, its performance …

Design And Control Of A Multi-Modal Electromagnetic Floor Array For Foot-Based Human Locomotion And Stabilization In Microgravity, Aryan Anand

Electrical Engineering Theses

Long-duration living and working in microgravity creates everyday mobility problems such as drifting, loss of stable footing, higher effort to move, and difficulty doing routine tasks safely. Many solutions have been proposed in literature, including handrails, restraint systems, and concepts for artificial gravity using rotation. Artificial gravity could improve comfort, but it is complex to build and operate for large spacecraft, especially when future missions may include not only trained astronauts but also common people. With companies like SpaceX pushing toward large-scale travel and long-term settlement goals, there is a need for simpler mobility support technologies that can work inside …

A Pathfinder Lunar Construction Mission Concept Using Regolith Filled Bags, Cameron S. Dickinson, Fu Nan Shi, Ketan Vasudeva, Rudranarayan M. Mukherjee, Joshua Blanchard, Steve Dubrule, Paul Van Susante, Et Al.

Michigan Tech Publications

Two challenges that have a permanent presence on the Moon are solar and cosmic radiation, as well as the large surface temperature variation between lunar day and night. To address these problems, we propose a lunar pathfinder mission concept that uses robotic systems to investigate whether regolith-filled bags can be used as a versatile construction medium for lunar surface structures and sensors to obtain data on the lunar regolith. The primary objectives of this mission are as follows: evaluation of the surface and subsurface regolith as fill material, lunar excavation using a robotic manipulator equipped with a bucket scoop, bag …

Chapter 6 - Robust Stabilization Ellipsoidal Design For Normal And Contingency Operated Power Systems Using Markov Jump, Ehab Bayoumi

Mechanical Engineering

No abstract provided.

Machine Learning–Driven Prediction Of Dementia From Mri And Clinical Features: A Comparative Analysis Of Ensemble And Baseline Models, Sarah Raad Hameed, Zainab Muhannad Nahid, Rawan Ahmed Abdulmahdi

AUIQ Technical Engineering Science

Early detection of dementia remains a pressing challenge in clinical neuroscience, as delayed diagnosis limits therapeutic impact and healthcare planning. Leveraging the Open Access Series of Imaging Studies (OASIS) cross-sectional dataset of 436 participants, this study developed a robust machine learning pipeline integrating sociodemographic, clinical, and neuroimaging-derived features. Preprocessing included removal of highly sparse variables (Delay), median imputation of partially missing but clinically essential measures (SES, MMSE, CDR, Educ), Winsorization of extreme values, and skewness correction. The target Clinical Dementia Rating (CDR) was binarized (0 = no dementia, ≥ 0.5 = dementia) to align with clinically actionable screening. Categorical features …

Integrating Sustainable Material Procurement In Construction Waste Management: A Systematic Review With Narrative Synthesis For The Libyan Construction Sector, Ramzi Fouzi Hamad Abdullah, Safaa N Saud Al-Humairi, Zunirah Binti Mohd Talib

Journal of Sustainable Construction Materials and Technologies

Integrating sustainable material procurement with construction waste management is essential to reduce construction and demolition waste in Libya, where current practices remain largely reactive and disposal-oriented. This narrative review aims to develop a conceptual framework linking procurement decisions to waste-generation pathways in Libyan construction projects, clarifying how proactive, sustainability-driven purchasing can serve as a primary driver of waste prevention. Using a PRISMA-guided systematic search of Web of Science, Scopus, and IEEE Xplore for 2001–2026, and a bibliometric analysis via VOSviewer, 956 high-quality studies were synthesized to map global knowledge and to expose the paucity of integrated SMP–CWM studies in developing …

Advances In Real-Time American Sign Language Recognition System Using Deep Learning Techniques For Enhanced Accessibility, Bader Alsharif

Electronic Theses and Dissertations 2020 - Present

Advancements in technology have significantly contributed to the development of innovative tools aimed at improving communication and accessibility for individuals with hearing impairments. This dissertation explores various machine learning and deep learning techniques for recognizing American Sign Language (ASL) gestures, focusing on enhancing accessibility and bridging the communication gap between hearing-impaired and hearing individuals. Traditional machine learning models, such as Random Forest, Support Vector Machines (SVM), and K-Nearest Neighbors (KNN), alongside deep learning architectures like AlexNet, ResNet-50, EfficientNet, ConvNeXt, and VisionTransformer, were investigated for their effectiveness. Experiments conducted on an extensive dataset of 87,000 ASL gesture images revealed exceptional recognition …

Design And Implementation Of A Microblaze‑Based Embedded System For Programmable Led Control On An Artix‑7 Fpga, Shensheng Tang

Day of Scholarship

This paper presents the design and implementation of a MicroBlaze‑based embedded system developed using the AMD/Xilinx VIVADO Design Suite to control programmable LED patterns on an Artix‑7 FPGA development board via push‑button inputs. The MicroBlaze, a 32/64‑bit RISC Harvard‑architecture soft‑core processor, provides a flexible and configurable platform that enables integration of customized peripheral, memory, and interface components within a single FPGA. The proposed system employs two GPIO controllers—one interfacing with sixteen LEDs and the other with five push buttons—connected to the MicroBlaze processor through an AXI interconnect to support efficient on‑chip communication. LED functionality is managed through a software application …

Ainet: Integrating Mamba And Cbam For Enhanced Camouflage Object Detection, Henry O. Velesaca, P. Andrea Mero, Abel A. Reyes-Angulo, Angel D. Sappa

Michigan Tech Publications

This paper introduces AINet, a novel deep learning architecture designed for detecting camouflaged objects in complex and diverse environments. The objective of this work is to design an end-to-end camouflaged object detection architecture that simultaneously captures long-range dependencies and refines subtle camouflage cues, improving segmentation accuracy and boundary delineation across both standard COD benchmarks and real-world agricultural scenarios. AINet leverages the strengths of Mamba, an efficient sequential state model for capturing long-range dependencies, and the Convolutional Block Attention Module (CBAM) for feature refinement through attention mechanisms. Detecting camouflaged objects is a significant challenge across a wide range of real-world applications, …

Note: Greenvent – Revolutionizing Methane Management With Hybrid Energy Processing In Mine Ventilation, Roman J. Jędrzejczyk, Damian K. Chlebda, Jacek Dańczak, Piotr Rosikowski, Monika A. Koperska, Robert E. Hayes, Joseph P. Mmbaga, Robert Hildebrandt, Joanna Profic-Paczkowska

Journal of Sustainable Mining

Methane plays a significant role in intensifying the greenhouse effect, possessing a global warming potential more than twenty times greater than that of CO₂ when measured on a carbon-dioxide-equivalent basis. Hence, identifying efficient methods to mitigate methane emissions is crucial for safeguarding the environment, ensuring economic viability, and maintaining practicality. Globally, research initiatives are dedicated to crafting an effective catalyst system for methane oxidation, which involves developing catalysts, comprehending their characteristics, and determining the best way of bonding them to structural supports to enhance functionality. Notably, systems that incorporate metals from the non-noble d-block of the periodic table as …

Enhancing Workforce Development In Construction Management Through Collaborative Teaching (Co-Teaching) Models, John Annor, Francois Jacobs

Online Journal for Workforce Education and Development

This study evaluated the effectiveness of a collaborative co-teaching initiative implemented across three educational institutions—the University of State, Community College, and High School—through two key construction courses: Construction Materials and Methods and Construction Safety. Designed to bridge gaps across educational levels, the initiative adopted a mixed-methods research approach to assess student learning outcomes, instructional effectiveness, and stakeholder perceptions. Quantitative data were collected from standardized assessments, including quizzes, a safety plan project, and exams administered across multiple years. Analytical techniques such as Welch's two-sample t-tests and Welch ANOVA were employed to compare student performance between and within institutions, adjusting for unequal …

Uas Path Planning With Dynamic Rerouting Using A Space-Time Graph, Kimoy Williams

Electronic Theses and Dissertations 2020 - Present

UAS systems have emerged as multifaceted technologies with applications across a wide range of sectors. Their ability to access areas that are difficult or unsafe for manned systems has made them invaluable tools in various domains. As a result, UAS have transformed numerous industries, including infrastructure inspection, delivery and logistics, military and defense, as well as precision agriculture and environmental monitoring.

The advancement in UAS technology is fundamentally reliant upon ongoing research efforts in the specialized area of UAS path planning. Optimal flight planning is essential for a UAV to effectively execute its mission’s task safely, effectively, and in congruence …