Digital Commons Network^™

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 …

Iud Insertion Pain Management, Sandhya Sridhar, Olivia Armas, Lucy Campochiaro

Biomedical Engineering

This project focuses on developing an atraumatic cervical stabilization device that serves as a modern alternative to the traditional tenaculum used during IUD insertion procedures. Current devices rely on sharp metal prongs that pierce the cervix and often cause significant pain and bleeding. The goal of this project is to design a device that provides the same stability and control for clinicians while eliminating the need to puncture cervical tissue. The device is intended to be used by gynecologists, nurse practitioners, physician assistants, primary care physicians, or any medical professional performing an IUD insertion. The device is intended to be …

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.

Newborn Spinal Needle, Allison Inouye, Kyle Morton, Evan Russell

Biomedical Engineering

Spinal punctures, or lumbar punctures, are important diagnostic procedures used to collect cerebrospinal fluid (CSF) to diagnose issues in the central nervous system (CNS) such as meningitis. While these procedures are routinely performed on adult and neonatal patients, the current tools are not optimized for use on newborns. Existing spinal needles are often modified versions of adult devices, leading to challenges in fluid collection efficiency, user ergonomics, and patient safety when used in neonatal care.

The Newborn Spinal Needle Project aims to design and develop a spinal needle specifically optimized for neonatal anatomy and clinical workflow. The goal is to …

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.

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 …

Design, Testing, And Safety Performance Of Movable Guardrail Systems: A Prisma-Based Systematic Review, Navid Hashemi Taba, Ahdieh Sadat Khatavakhotan, Majid Tolouei-Rad

Research outputs 2022 to 2026

Movable guardrail systems are increasingly used in work zones, reversible lanes, and temporary traffic operations; however, evidence on their crashworthiness, material performance, and operational reliability remains dispersed across multiple design typologies and regulatory frameworks. This PRISMA-compliant systematic review synthesizes 78 studies involving full-scale crash tests, validated finite-element simulations, field performance evaluations, and compliance evaluations under MASH, EN 1317, NCHRP 350, and AS/NZS 3845.1. The findings indicate that modular rigid barriers reliably achieve TL-3/TL-4 performance when joint alignment and foundation conditions are properly controlled; semi-rigid steel systems provide a practical balance between containment capacity and redeployability, but remain sensitive to post …

Elevating The Underrepresented And Marginalized Using Experiences In Stem (Lumens): A Stem Diversity And Inclusion Initiative, Robert Cobb Jr, Paula E. Faulkner, Deiadra Modlin, Obinna Chiekezi, Victoria Cobbold, Madison Beaudoin

Journal of Research Initiatives

The study offered a 5-week summer immersion program to address the shortage of students from underrepresented populations enrolling in degree programs and seeking careers in science, technology, engineering, and mathematics (STEM). The study also addressed the importance of offering summer immersion programs to close the achievement gap. A quantitative descriptive design was used to gather data from participants related to STEM lessons during the program. Gender, grade level, and race served as the demographic variables. The study included 21 secondary students in grades 9–12. Pre- and post-tests assessed participants' knowledge gain regarding STEM lessons. Data analyzed with SPSS version 29 …

Joint Capacity Allocation And Job Assignment Under Uncertainty, Peng Wang, Yun Fong Lim, Gar Goei Loke

Research Collection Lee Kong Chian School Of Business

We study a multi-period joint capacity allocation and job assignment problem. The goal is to simultaneously allocate resources across J different supply nodes and assign jobs from I different demand origins to these J supply nodes, so as to maximize the reward for matching or minimize the cost of failure to match. We consider three features: (i) supply is replenishable after some random time, (ii) demand is random, and (iii) demand can wait and needs not be fully fulfilled immediately. Such problems emerge in many service management settings such as fleet re-positioning for car-sharing, and patient management in healthcare. We …

Development Of A Framework For Identifying Asphalt Pavement Cracking Distresses Using Machine Learning, Dingxin Cheng

Mineta Transportation Institute

Asphalt pavement cracking is one of the most critical distresses affecting pavement performance and service life. When pavement deteriorates, it can lead to safety hazards, higher vehicle maintenance costs, and expensive repairs for cities and states—making early detection essential for everyone who relies on the roadway system. To address this challenge, the research team developed a prototype cracking identification system that integrates a customized machine learning model with computer vision algorithms. High-resolution images collected from drones or ground-based cameras are processed within the system to automatically detect and classify major cracking types. The core of the framework utilizes the You …

Autonomous Vehicle Adoption Behavior And Safety Concern: A Study Of Public Perception, Fatemeh Nazari, Mohamadhossein Noruzoliaee, Abolfazl (Kouros) Mohammadian

Civil Engineering Faculty Publications

Realizing the economic and societal benefits of autonomous vehicles (AVs) hinges on widespread public acceptance. However, existing research offers limited insights into two key behavioral factors shaping AV acceptance, namely, perceived AV safety concern and travel behavior, the latter reflecting how heterogenous mobility patterns influence the AV acceptance. These factors are often treated as exogenous, limiting insight into their true behavioral interdependencies with AV acceptance and their distinct behavioral roots. This study addresses these gaps by introducing a recursive trivariate econometric model that jointly estimates AV acceptance, perceived safety concern, and current travel behavior (proxied by annual vehicle-miles traveled or …

Efficient Active Training For Deep Lidar Odometry, Beibei Zhou, Zhiyuan Zhang, Zhenbo Song, Jianhui Guo, Hui Kong

Research Collection School Of Computing and Information Systems

Robust and efficient deep LiDAR odometry models are crucial for accurate localization and 3D reconstruction, but typically require extensive and diverse training data to adapt to diverse environments, leading to inefficiencies. To tackle this, we introduce an active training framework designed to selectively extract training data from diverse environments, thereby reducing the training load and enhancing model generalization. Our framework is based on two key strategies: Initial Training Set Selection (ITSS) and Active Incremental Selection (AIS). ITSS begins by breaking down motion sequences from general weather into nodes and edges for detailed trajectory analysis, prioritizing diverse sequences to form a …

Fixel-Based Analysis Of Pretreatment Mri Identifies White Matter Abnormalities In Pediatric Anti-Nmdar Encephalitis, Daniel Ackom, Janine Taitt-Tap, Scott A. Beardsley, Ricardo Vega, Alyssa Jobe, Andrew J. D. Crow, Brian Schmit, Lileth Mondok, Pradeep Javarayee

Biomedical Engineering Faculty Research and Publications

Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is an autoimmune disorder in which conventional MRI often appears normal, leading to clinical–radiologic dissociation and hindering early diagnosis and monitoring. We retrospectively studied five pediatric patients with anti-NMDAR encephalitis and compared their pretreatment diffusion MRI to age- and sex-matched controls. Using fixel-based analysis (FBA), we quantified tract-specific white matter abnormalities at the individual level. All patients showed significantly reduced fiber density and cross-section, with patterns ranging from focal to widespread involvement. In two patients, FBA abnormalities corresponded to seizure lateralization on EEG despite normal MRI, emphasizing FBA's added value in detecting seizure-concordant injury. One patient, …

Informing Consumer Product Sound Quality Analysis Using Generative Adversarial Networks, Daniel Jeffery Lesko, Vinh Nguyen

Michigan Tech Publications

Sound quality attributes have been proven important predictors of customer satisfaction with consumer goods and appliances. The results of several studies indicate that level-based, tonal, and temporal aspects of sound influence the perceived quality of consumer products. The current state-of-the-art of inferring consumer satisfaction with sound attributes is based on the jury test methodology. However, product engineers often find the models generated from these studies incomplete, resulting in products that fail to meet consumer expectations. Therefore, this study aims to utilize generative data-driven approaches to create a range of acceptable sound quality attributes given consumer satisfaction requirements. A baseline sound …

N-Dqn: Neutrosophic Deep Q-Network For Uncertainty-Aware Forecasting And Decision Optimization, Rania Lutfi

Neutrosophic Systems with Applications

Uncertainty remains a critical challenge in dynamic spatiotemporal forecasting. This study proposes the Neutrosophic Deep Q-Network (N-DQN), a framework that integrates neutrosophic logic with deep reinforcement learning to enhance decision optimization under uncertainty. Features are modeled through truth, indeterminacy, and falsity membership functions, enabling robust handling of ambiguous data. The framework incorporates attention-guided preprocessing and horizon-aware optimization to adapt predictions across short- and long-term intervals. Experiments on benchmark traffic datasets (METR-LA and PEMS-BAY) demonstrate improved forecasting accuracy and reduced error rates compared with established baselines. The results highlight the scalability and resilience of N-DQN, positioning it as a promising approach …

Current Research Progress On Electrode Materials For All-Vanadium Redox Flow Batteries, Wen-Qi Wang, Jie Jin, Li-Min Wang, Xin-Yue Liu, Tao Cheng, Yong Hou, Han Xue, Zhi-Yu Wang, Bo Liu, Jia-Bao Liu, Xu-Bin Lu

Journal of Electrochemistry

The redox active species in all-vanadium redox flow batteries (VRFBs) reside in the electrolyte, while the heterogeneous reactions occur on the electrode surface; the electrode is therefore the decisive platform for dynamic adsorption, electron transfer, and ion conversion, especially for the VO²⁺/VO₂⁺ and V²⁺/V³⁺ couples. One of the major challenges for VRFBs is the slow charge transfer in VO²⁺/VO₂⁺ and V²⁺/V³⁺ reactions, mainly caused by poor catalytic performance of electrodes and weak adhesion of catalysts to electrodes. This review focuses on the key challenges and recent …

An Electrochemiluminescence-Based Arsenic (Iii) Sensor Using Luminol On Screen-Printed Gold Electrodes, Harmesa Harmesa, Isnaini Rahmawati, Andrea Fiorani, Yasuaki Einaga, Eny Kusrini, A’An Johan Wahyudi, Asep Saefumillah, Tribidasari A Ivandini

Journal of Electrochemistry

Electrochemiluminescence (ECL) of luminol has been studied on a screen-printed gold electrode for a simple and sensitive detection of arsenic ions (As(III)). Cyclic voltammetry (CV) was applied as the proposed technique to study luminol’s electrochemical behavior and to evaluate the arsenic’s effect in the ECL system, while hydrogen peroxide (H₂O₂) served as a co-reactant to enhance luminol’s light emission under alkaline conditions. To achieve optimal electrode performance, key parameters including pH, scan rate, and the concentrations of H₂O₂ and luminol were carefully optimized. The presence of As(III) induced a quenching effect on the …

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 …

Single-Valued, Double-Valued, Triple-Valued, Quadruple-Valued, And Quintuple-Valued Neutrosophic Graph, Takaaki Fujita, Arif Mehmood, Arkan A. Ghaib

Neutrosophic Systems with Applications

Concepts such as fuzzy sets, neutrosophic sets, rough sets, and plithogenic sets have been extensively studied as formal tools for modeling uncertainty, and they have found broad applications across many disciplines. A Double-Valued Neutrosophic Set (DVNS) extends the classical neutrosophic framework by splitting indeterminacy into two distinct components: one leaning toward truth and the other leaning toward falsity. In recent years, further refinements—namely Triple-Valued, Quadruple-Valued, and Quintuple-Valued Neutrosophic Sets—have also been introduced and investigated. These uncertainty models have naturally been lifted to graph-theoretic settings, where vertices and edges represent entities and relationships under ambiguity. Although fuzzy graphs and neutrosophic graphs …

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 …

Neutrosophic Finsler–Cohomological Framework For Engineering Systems Under Uncertainty, Mona Gharib, Ghulam Muhammad, Muhammad Idrees, Zeeshan Gul

Neutrosophic Systems with Applications

This paper introduces a novel mathematical framework that combines Neutrosophic Finsler Geometry with Neutrosophic Cohomology for evaluating the performance of Brushless Direct Current (BLDC) motors under uncertain and indeterminate operating conditions. Classical motor performance models typically assume precise measurements of torque, current, and efficiency; however, in real-world settings, these parameters are often affected by noise, incomplete information, and conflicting observations. By embedding motor operating states into a neutrosophic Finsler space, the proposed approach captures variations not only in magnitude but also in direction, uncertainty, and conflict of performance metrics. In addition, neutrosophic Cohomology is employed to characterize global invariants of …

An Uncertainty-Aware Entropy-Oreste Framework For Big Data Platform Selection In Complex Multi-Sector Environments, Ahmed M. Ali, Ibrahim Alrashdi, Karam M. Sallam

Neutrosophic Systems with Applications

The increasing reliance on Big Data platforms across various industries has necessitated the development of systematic decision-support frameworks to guide their evaluation and selection. Given the diversity of available platforms, each offering different capabilities, scalability, and computational efficiency, choosing the optimal solution remains a complex challenge. This research proposes a novel analytical framework that integrates Spherical Fuzzy Sets (SFS) with the Entropy and ORESTE methods to address uncertainty and enhance the accuracy and robustness of Big Data platform evaluation. This hybrid integration, not previously applied to Big Data platform selection, enables objective criteria weighting through the Entropy method and comprehensive …

Triphenylmethane-Derived Levelers For High-Speed Redistribution Layer Copper Electroplating Of Tailored Surface Morphologies, Zi-Hao Song, Wei-Bin Wang, Xiao-Hui Liu, Xiao-Min Han, Yi Zhou, Rui Huang, Yan-Xia Jiang, Zhe Li, Xiao-Wei Liu, Mei-Ling Xiao, Hong-Gang Liao, Wei-Lin Xu, Rong Sun

Journal of Electrochemistry

Redistribution Layer (RDL), composed of layered dielectrics and electroplated copper materials, is a basic structure to rearrange numerous I/O pads on the chip surface in wafer-level advanced packaging. As the key chemicals in electrolyte baths, electroplating additives have undergone continuous development to meet the industrial needs for high-speed and fine-line/fine-pitch applications. Meanwhile, the intricate relationships between additive chemical structures and electroplated copper properties are yet to be well understood. In this work, a pair of triphenylmethane-based dye molecules, i.e., gentian violet (GV) and methyl green (MG), was comparatively investigated as levelers for high-speed RDL copper electroplating. Compared to GV, significantly …

Physiological And Neurological Impact Of Biophilic Design In Architectural Design Studios: A Case Study Of King Salman International University, Islam Ashraf Mohamed, Alaa El-Eishy, Marwa A. Soliman

Mansoura Engineering Journal

Biophilic design integrates nature into architecture to enrich sensory and cognitive experiences, enhance psychological well-being, and improve performance. This study explores its physiological and neural effects in design studios at King Salman International University through an experimental methodology combining theoretical review and lab-based investigation. Tools included electrocardiography (ECG) for heart rate variability (HRV), eye-tracking for visual attention, and the Self-Assessment Manikin (SAM) for emotional evaluation. Nine participants viewed five digital architectural scenes with varying biophilic integration. Direct nature connections elicited greater visual attention, pleasure, and perceived control, indicating higher engagement and relaxation.  A scene lacking biophilic elements led to reduced …

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. …

Balancing Carbon Emissions In Façade Of Residential Buildings Through Bim-Lca: A Comparative Analysis Of Insulation Materials, Mehran Alipour

Journal of Sustainable Construction Materials and Technologies

Thermal insulation materials play a significant role in balancing buildings' total carbon emissions. Balancing involves applying the optimized amount of insulation materials to avoid excessive emissions in either the operational or embodied phases. Due to the wide range of insulation materials and variations of their specifications, it is vital to analyse them individually. The focus of this study is to optimize the amount of insulation materials in the facades of Residential Buildings (RB) to balance the amount of Operational Carbon Emissions (OCE) and Embodied Carbon Emissions (ECE) by applying the Building Information Modelling-Life Cycle Assessment (BIM-LCA) integration method. The Life …

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 …

Rapid-Response Reconnaissance Architecture Design For Planetary Defense With Nested Trajectory Optimization, Adam P. Wilmer, Justin A. Atchison, Marcus J. Holzinger, Robert A. Bettinger

Faculty Publications

Reconnaissance is a vital component in a comprehensive planetary defense mitigation strategy—aimed at preventing or reducing the impact threat posed by celestial objects on close-approach trajectories to Earth. It provides decision-makers with critical information on the physical and orbital properties of a near-Earth object (NEO), enabling better assessment of size, composition, and trajectory. This study investigates how to optimally pre-position a fleet of reconnaissance spacecraft prior to the discovery of a specific hazardous NEO. It evaluates response timelines and mission success rates for combinations of spacecraft launched from Earth and those maneuvering from pre-deployed locations within the Sun-Earth system. A …