Digital Commons Network^™

Sprinter Start Block Training Aid, Kayla Lovejoy, Kevin Almontes

Biomedical Engineering

Currently, track and field sprinters ranging from beginner level to world-class have no practical tool that provides quantitative feedback of value on quality of start and quality of the three distinct phases of their sprint race, such that they can quantify the value of their adjustments. Our team will create a device that integrates with the sprint starting block to provide quantifiable data on the quality of a sprinter’s start. This Statement of Work describes drawbacks of current solutions, existing patents, customer requirements, engineering specifications, and our project plan.

Class Imbalance: A Landscape Of Classification Models, Joshua L. Edmonds

Theses and Dissertations

Class imbalance poses significant challenges in machine learning classification. This study evaluates the performance of seven models (ANN, k-Means, kNN, LDA, LR, SVM, XGBoost) across multiple imbalance levels (10\%, 5\%, 1 \%, 0.5\%) and investigates the effectiveness of sampling techniques (Undersampling, SMOTE, SMOTE-ENN). ANOVA results confirm that model choice is the most critical factor, with XGBoost and SVM demonstrating superior robustness. SMOTE improves recall but reduces precision, while undersampling generally degrades overall performance. While significant, imbalance levels do not play a critical role in model effectiveness.

Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros

Theses and Dissertations

Pacific Islands under U.S. jurisdiction are highly vulnerable to natural disasters, yet many lack the infrastructure to effectively respond and recover. Clear communication during and after such events is critical for evacuation, hazard awareness, and first responders’ coordination. This research explores a simulation-based approach using Bluetooth communication to relay messages across Guam, assessing its efficiency through statistical analysis. By examining regional differences and geographic impacts on Bluetooth messaging, the study aims to identify key factors that enhance peer-to-peer communication for timely and effective disaster response.

Maintenance Strategy And Budgeting Optimization For United States Air Force Facilities, Sophia C. Hirtle

Theses and Dissertations

Mission readiness in the United States Air Force (USAF) is critically dependent on the sustainment and maintenance of aging facilities. However, budgetary and manpower constraints have led to a significant backlog of deferred maintenance, estimated at $137 billion. To address these challenges, this research develops an optimization model that aids in prioritizing facility maintenance strategies within a fixed budget. The methodology incorporates existing USAF data from BUILDER, NexGenIT, and financial records to create a simulation-based optimization framework at the base level. The model evaluates four different maintenance strategies—replacement only, preventative maintenance only, corrective maintenance only, and a combination of preventative …

Calibrating Airfield Pavement Asset Management For A Changing Global Climate: A Case Study At Fairchild Air Force Base, Emily L. Worthy

Theses and Dissertations

Military airfields and civilian airports serve as foundational nodes in the global transportation network, enabling travel, economic growth, and the projection of national security. This study investigates the relationship between climate variables projected through climate change and pavement degradation, with a focus on Fairchild Air Force Base (AFB). Using principal component regression (PCR), the research integrates historical pavement condition index (PCI) data with climate variables, including snowfall, precipitation, freeze-thaw cycles, solar irradiance, and wind speed to develop a predictive model of pavement performance under future climate scenarios, Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. These models, for both Portland …

Artificial Intelligence And Internet Of Things Integration In Pharmaceutical Manufacturing: A Smart Synergy, Reshma Kodumuru, Soumavo Sarkar, Varun Parepally, Jignesh Chandarana

Michigan Tech Publications

Background: The integration of artificial intelligence (AI) with the internet of things (IoTs) represents a significant advancement in pharmaceutical manufacturing and effectively bridges the gap between digital and physical worlds. With AI algorithms integrated into IoTs sensors, there is an improvement in the production process and quality control for better overall efficiency. This integration facilitates enabling machine learning and deep learning for real-time analysis, predictive maintenance, and automation—continuously monitoring key manufacturing parameters. Objective: This paper reviews the current applications and potential impacts of integrating AI and the IoTs in concert with key enabling technologies like cloud computing and data analytics, …

An Investigation Of The Mechanical Properties Of Concrete With Different Types Of Waste Plastics For Rigid Pavements, Nuha S. Mashaan, Cherrie Ann E. Ouano

Research outputs 2022 to 2026

The increasing demand for sustainable construction practices has prompted the exploration of innovative materials, such as waste plastics, to enhance both the environmental and mechanical performance of concrete, particularly for rigid pavements. This review investigates the mechanical properties of concrete incorporating four types of waste plastics—high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyvinyl chloride (PVC), and polypropylene (PP). The primary focus is on how these materials affect key mechanical properties, including compressive strength, tensile strength, and flexural strength. The analysis reveals that HDPE and PP, at optimal levels (5–10%), can enhance flexural and crack resistance, making them suitable for non-structural applications. …

Sustainable Utilisation Of Mining Waste In Road Construction: A Review, Nuha S. Mashaan, Sammy Kibutu, Chathurika Dassanayake, Ali Ghodrati

Research outputs 2022 to 2026

Mining by-products present both an environmental challenge and a resource opportunity. This review investigates their potential application in road pavement construction, focusing on materials such as fly ash, slag, sulphur, red mud, tailings, and silica fume. Drawing from laboratory and field studies, the review examines their roles across pavement layers—subgrade, base, subbase, asphalt mixtures, and rigid pavements—emphasising mechanical properties, durability, moisture resistance, and ageing performance. When properly processed or stabilised, many of these wastes meet or exceed conventional performance standards, contributing to reduced use of virgin materials and greenhouse gas emissions. However, issues such as variability in composition, leaching risks, …

Assessing The Perceived Safety Of Cyclists With Virtual Reality, Vahid Balali

Mineta Transportation Institute

In 2022, 7,522 pedestrians and 1,084 bicyclists were killed and approximately 67,000 pedestrians and 46,195 bicyclists injured in motor vehicle crashes on public roadways in the United States, according to the Insurance Institute for Highway Safety (IIHS). The transportation industry is faced with a pressing need to bolster the safety of these vulnerable road users. This research develops models of design and environmental factors that influence bicyclists’ and pedestrians’ perception of safety using Virtual Reality (VR) technology and ultimately informs transportation infrastructure design to better accommodate nonmotorized travelers. The goal of the bicycle element of this research is to develop …

Smart Highway Construction Site Monitoring Using Artificial Intelligence, Mehran Mazari, Yahaira Nava-Gonzalez, Ly Jacky N. Nhiayi, Mohamad H. Saleh

Mineta Transportation Institute

Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. …

Smart Manufacturing Readiness Assessment - Analysis Of A Modern Tool From A Sociotechnical Perspective, Todd Lemon

All-Inclusive List of Electronic Theses and Dissertations

Smart Manufacturing has emerged out of the pervasive buzzwords in publications as a competitive strategy, characterized by the intensive use of digital information and technology throughout the production processes; shop-floor, people, and systems are married by the Internet creating services critical to manufacturing. The work completed and presented here extends the research in the area of Smart Manufacturing (SM) readiness to include a more comprehensive approach to production floor implementation. The overarching goal is to explore SM implementation in attempt to identify underlying latent factors that relate to preparedness from a joint social and technical perspective, striving for a model …

Development And Validation Of An Artificial Intelligence System For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Kellie R. Brown, Kathleen K. Christians, Douglas B. Evans, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Background

Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for improved surgical case length prediction by applying natural language processing and machine-learning methods.

Methods

All inpatient elective surgical cases longer than 30 minutes completed between 2017 and 2023 at a single, quaternary care hospital were considered. Data were split into training, test, and hold-out validation for model training and testing. Linear regression, CategoricalBoost, and feed-forward neural network each were trained and used embeddings created …

Investigation Of Innovative Heat Pipes / Fins System For Diesel Engine Cooling, Mohammad Shafiq Anees

Theses

Engine cooling is considered one of the most important factors that affect their efficiency and therefore their performance, so a new cooling method is proposed using both heat pipes and fins to improve the cooling efficiency of internal combustion engines and shall be examined theoretically and experimentally. A test rig has been designed and built using a specimen material with similar properties to the real engine materials with similar dimensions as the engine cylinder head / liner thickness. The experiment employed a specially designed testing apparatus that included a gas burner for consistent heating, a modifiable support structure, and an …

Asphalt Rubber Chip Seals A Cost Effective And Sustainable Solution For Road Infrastructure, Gunnar C. Bertsch

Construction Management

Asphalt Rubber Chip Seals provide a durable, cost effective, and environmentally friendly alternative to traditional paving methods by incorporating recycled waste tires. This study evaluates Asphalt Rubber Chip Seals implementation in Arizona and Michigan comparing its effectiveness to conventional paving approaches and the current applications in California. Variations in state funding for road maintenance significantly impact infrastructure quality and longevity, influencing the choice of paving solutions. ARCS has demonstrated resilience in extreme weather conditions, making it a viable option for expansion to states like Arizona and Michigan, where climate variations pose challenges for pavement longevity. The research assesses construction costs, …

Transfer Efficiencies Of Surface-To-Surface Transport Of Micron-Sized Actinide Surrogate Particles, Austin R. Powell

Theses and Dissertations

Particle effluent of varying sizes is released during routine activities within laboratory environments and these particles can come in contact with a wide range of surfaces. Particles of micron size or smaller can be especially pervasive and can transfer between multiple subsequent surfaces, leading to the progressive contamination of a laboratory. Understanding the transport dynamics of micron sized particles will help inform facility personnel of the possibility of contamination by these potentially hazardous materials of interest. In this research, the transfer efficiency of micron sized surrogate actinide particles (Europium-doped Gadolinium Oxysulfide (EGOS)) is measured for multiple materials, between two particle …

Application Of An Adaptive Neuro-Fuzzy Inference System To Control The Wastewater Treatment Process, Jaloliddin Abdurazzakovich Eshbobaev, Bakhodir Tajiddinovich Khamidov, Marcos Torices Fallanza

Chemical Technology, Control and Management

This study explores the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling wastewater treatment processes using ion-exchange resins. It addresses the critical challenges of water scarcity and pollution by enhancing the regulation of water hardness (H) and Total Dissolved Solids (TDS). Using a pilot laboratory device and experimental data from the mixed wastewater of the Kungrad Soda Plant in Uzbekistan, an ANFIS model was developed in MATLAB to automate process control. The model leverages water hardness and TDS as input parameters to regulate the water flow rate by servo valve opening degree, ensuring precise and efficient treatment. Compared …

Evaluation Of Health Monitoring Parameters For Automotive Pneumatic Elastomeric System Using Soft Pressure Sensors For Enhanced Vehicle Performance., Md Jarir Hossain, Sarah Suresh Kamath, Jong Min Park, Heung-Seok Oh

University Research

In the rapidly evolving automotive industry, the need for reliable and efficient pneumatic elastomeric components necessitates cutting-edge health monitoring methods, given that the pneumatic components are directly connected to dampening properties, ride comfort, vehicle safety, and stability. A novel approach for pneumatic elastomeric component health monitoring utilizing ionic liquid (IL)-based soft sensor technology has been proposed, which has the promise to enable real-time health monitoring and prognostics of vehicle systems. The proposed polymer sensor leverages the distinctive characteristics of flexibility, stretchability, and high sensitivity. These properties are critical for precisely measuring load, vertical displacement, air pressure, force locations, and load …

Investigation Of Methane Content And Sorption Properties Of Lignite Deposits, Marcin Karbownik

Journal of Sustainable Mining

Methane is one of the main greenhouse gases (GHG) affecting climate change, and proper quantification of the amount of its emissions to the atmosphere is crucial. The basic parameter for determining the potential amounts of naturally occurring methane in coal for both hard coal and lignite is the methane content. Determination of the methane content of lignite for open-pit mines is not commonly used and required as there is no possibility of its accumulation in the mine workings, as is the case for underground hard coal mines. In this article, two research areas for open-pit lignite mines were analyzed in …

Evaluating The Health Performance Of Mass Housing Projects In Egypt Lighting Design Of Dar Masr Project, New Damietta, Hala Mohamed Raslan, Huda El-Baz M.

Mansoura Engineering Journal

The Egyptian government has recently established many governmental mass housing projects to meet the housing needs nationwide. These projects are characterized by their unified repetitive design that rarely consider geographic, climatic and social variations from one site to another. The study objectives are to examine the health performance of mass housing projects; “Dar Misr” as an example. Dar Misr consists of 150,000 units distributed over 15 different cities, and is fully finished with unified electrical installations and preinstalled luminaires. The study examines the health performance of the project’s lighting design, both natural and electrical light, using the “WELLV2 rating system …

Safety Distances For Fires In Underground Hard Rock Mines, Rickard Hansen

Journal of Sustainable Mining

Preventing the ignition of combustibles in an underground mine will be one of the decisive actions affecting the risk to mining personnel during a fire. This study focuses on the application of safety distances in underground hard rock mines, where a safety distance will ensure that the incipient heat flux upon the fuel surface will not be sufficient for ignition. No earlier study has been conducted on safety distances in underground mines, and where data from earlier fire experiments and studies were applied. Safety distances were calculated using empirical expressions, accounting for influencing parameters. It was found that safety distances …

Developmental Patterns And Formation And Evolutionary Mechanisms Of Surface Cracks Induced By The Mining Of Shallowly Buried Coal Seams, Hou Enke, Mu Jiaxin, Xie Xiaoshen, Feng Dong, Yang Lei, Li Yan, He Tao, Bao Kangguang, Chen Xiaosheng

Coal Geology & Exploration

Objective Surface cracks are recognized as one of the most common geologic hazards in coal mining areas in northern Shaanxi Province. These cracks directly cause damage to surface ecosystems. Furthermore, those penetrating fractures in the overburden act as primary channels for surface water to burst underground, threatening the safe production underground. Methods This study aims to further reveal the developmental patterns of surface cracks induced by the mining of shallowly buried coal seams and elucidate their formation and evolutionary mechanisms. To this end, this study investigated mining face 15218 and 25213 in the Hongliulin Coal Mine in northern Shaanxi. Specifically, …

Numerical Analyses Of Construction Materials At Different Scales For Improved Resilience And Sustainability Of Civil Infrastructures, Chenchen Huang

Theses and Dissertations

The resilience and sustainability of civil infrastructure are fundamental to supporting modern society in the face of growing environmental challenges and resource limitations. This study aims to use multi-scale numerical tools to evaluate mechanical performance of different construction materials under various environmental and loading conditions. Firstly, we adopt the discrete element method (DEM) to evaluate the influence of freeze-thaw cycles (FTCs) action on the mechanical properties of rock from the micro perspective. A simplified plastic model is proposed to capture the residual deformation produced during FTCs. To further explore the deterioration of FTCs on rock, the water-contained grain-based model (GBM) …

Immersive Modeling To Communicate And Manage Risks Of Water Shortages, David Rosenberg, Erki Porse

Civil and Environmental Engineering Faculty Publications

Our project goal is to use immersive online collaborative modeling as a tool for active learning to communicate and manage users conflicting risks of water shortages because decisions now to manage risk effect future risk. State-of-the art river basin forecasting tools provide probabilistic estimates of streamflow at hourly to annual scales. Water resource models quantify tradeoffs and risk across hundreds or thousands of scenarios of inflow and demand forecast out decades. Our project objectives are: 1) Formulate extreme scenarios for reservoir inflows without probabilities one to three years out that pose imminent risk of water shortages. 2) Hold immersive model …

Potential Of Individual Upper-Limb Muscles To Contribute To Postural Tremor: Simulations From Neural Drive To Joint Rotation, Spencer A. Baker, Landon J. Beutler, Daniel B. Free, Dario Farina, Steven Knight Charles

Faculty Publications

Background: It is unclear which muscles contribute most to tremor and should therefore be targeted by tremor suppression methods. Previous studies used mathematical models to investigate how upper-limb biomechanics affect muscles’ potential to generate tremor. These investigations yielded principles, but the models included at most only 15 muscles. Here we expand previous models to include 50 upper-limb muscles, simulate tremor propagation, and test the validity of the previously postulated principles. Methods: Tremor propagation was characterized using the gains between tremorogenic neural drive to the 50 muscles (inputs) and tremulous joint rotations in the 7 joint degreesof- freedom (DOF) from shoulder …

The Effects Of Transportation Distribution On The Performance Of Insulated Thermal Containers, Edmund B. Tang

Journal of Applied Packaging Research

This research examines the effect of simulated transportation distribution testing on insulated thermal containers, also known as cold chain shippers. This study compares the thermal performance of an insulated thermal container in its ideal pristine condition with no external factors that challenge the integrity of the package to insulated thermal containers that are subjected to common and acceptable test inputs using established and accepted industry package performance and simulation standards. Currently, little research evaluates the thermal performance of insulated thermal containers after simulated distribution testing. A total of nine different real-world scenarios using test standards of varying severities or other …

A Novel Preprocessing Model For Multi Modal Brain Mri Image Classification For Stroke Prognosis, Alwin Joseph, Chandra J

Northeast Journal of Complex Systems (NEJCS)

Magnetic Resonance Imaging (MRI) is an imaging technique used for the diagnosis and observing the progression in various neurological disorders. Stroke is one of the prominent neurological disorders that creates significant impacts in the patients. It occurs when the blood supply to part of the brain is interrupted or reduced, preventing brain tissues from getting oxygen and nutrients. Multimodal data from various modalities help clinicians in proper prognosis of stroke. Ischemic Stroke Lesion Segmentation Challenge (ISLES22) provides data of stroke data for various stroke patients, the dataset consists of three modalities of data – Fluid Attenuated Inversion Recovery (FLAIR), Apparent …

02.24.2025 Ored Connect, Liz Williamson

ORED Newsletter

Collaborate Opportunity

SEC Faculty Travel Grants

Participant Support Cost Resources

Facial Swap Detection Based On Deep Learning: Comprehensive Analysis And Evaluation, Israa Mishkhal, Nibras Abdullah, Hassan H. Saleh, Nur Intan Raihana Ruhaiyem, Fadratul Hafinaz Hassan

Iraqi Journal for Computer Science and Mathematics

In recent years, Advancements in Artificial Intelligence (AI), particularly deep learning (DL), have made great strides in the creation of highly realistic deepfakes, which manipulate facial forensics to generate convincing fake faces or expressions. These manipulations pose significant threats to individual privacy and the integrity of legal, political, and social institutions. In fact, several existing studies have recently pursued the development of machine learning techniques for detecting deepfake content, with the overarching aim of protecting the victim's privacy or curbing the rise of picture fabrication. Despite extensive research on DL-based deepfake detection systems, challenges such as detecting facial swaps under …

Reliability Analysis Of Long‑Span Concrete Box Arch Bridge Under Temperature Effect Combinations, Zheng Junlin, Jiang Youbao, Zheng Xinhao, Lu Naiwei

Journal of China & Foreign Highway

The existing design methods for concrete arch bridge structures do not consider the random characteristics of the eccentricity generated by load effects and overlook the influence of stochastic eccentricity on structural reliability.To address this deficiency,a calculation model for eccentricity under temperature effect combinations was derived.The random characteristics of eccentricity for different sections of the main arch of concrete arch bridges and their sectional bearing capacities were analyzed under different load parameter combinations.By utilizing the Monte Carlo method,reliability indices were computed for different sections of the main arch and different load parameter combinations after considering the random characteristics of eccentricity.The results …

Utilizing Convolutional Autoencoders For Anomaly Detection And Drill Bit Damage Assessment In Rotary Percussion Drilling, Lesego Senjoba, Hajime Ikeda, Hisatoshi Toriya, Tsuyoshi Adachi, Youhei Kawamura

Journal of Sustainable Mining

Monitoring drill bit wear during drilling improves operational efficiency. Wear in drill bits is influenced by factors related to drilling parameters and rock properties and can be categorized into types based on the cause of failure. Several studies have used machine learning to detect drill bit wear, mainly using classification models. However, these models require an extensive amount of data that includes different possible drill bit failures. This presents a challenge as acquiring data is difficult due to the scarcity of anomalies. This study introduces a novel approach utilizing convolutional autoencoders (CAE) for both anomaly detection and drill bit damage …