Digital Commons Network^™

Calculation Of The Basic Parameters Of The Hybrid Power Plant (Hpu) On The Spark Car, Rustam Raximovich Tillahodjaev, Jamoliddin Pardaboy Ugli Turdiev

Technical science and innovation

This article presents one of the effective ways to improve fuel efficiency and reduce emissions of toxic substances, the use of internal combustion engines with the use of an electric drive in their designs. In recent years, two directions in the development of cars with electromechanical drives have been clearly identified, the first is the creation of a pure electric car, the second is the development of an electromechanical drive with a combined (hybrid) power plant. Due to the lack of efficient energy storage available for mass production, pure electric vehicles have relatively low mileage on a single charge. This …

Human Cancer Genomes Harbor The Mutational Signature Of Tobacco-Specific Nitrosamines Nnn And Nnk, Michael Korenjak, Nuri Alpay Temiz, Stéphane Keita, Bérénice Chavanel, Claire Renard, Cécilia Sirand, Jiehong Guo, Et Al.

Michigan Tech Publications

BACKGROUND: Tobacco use is linked to multiple cancer types and a quarter of cancer deaths. Tobacco smoke contains numerous mutagenic chemicals such as polycyclic aromatic hydrocarbons (PAH), however, the mutagenicity of many chemicals in tobacco products remains underexplored. The tobacco-specific nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N'-nitrosonornicotine (NNN), both International Agency for Research on Cancer (IARC) Group 1 carcinogens, form pre-mutagenic pyridyloxobutyl (POB) DNA adducts, yet little is known about the associated genomic mutation landscape(s) in humans. METHODS: We applied bulk and error-corrected next-generation sequencing to a battery of experimental systems comprising mammalian cell lines and animals exposed to NNK or NNN, …

Comprehensive Study On Explainable Artificial Intelligence For Enhanced Decision-Making, Eman Taher, Wessam H. El-Behaidy, Doaa S. Elzanfaly

Computer Science

Artificial Intelligence (AI) models are often criticized for their black-box nature, particularly in high-stakes domains such as finance, healthcare, and business decision-making, where transparency, accountability, and trust are essential. As machine learning advances with more complex architectures, including deep neural networks and ensemble models, the need for explainability becomes increasingly critical. This study focuses on Explainable Artificial Intelligence (XAI) as a key approach to enhance interpretability in classification, regression, and clustering tasks that serve as the foundation of data-driven analytical systems. XAI methods such as SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model-agnostic Explanations), and Integrated Gradients provide a means …

Design And Fpga Deployment Of Quantized Convolutional Spiking Neural Networks For Ecg Arrhythmia Classification, Olamilekan Banjo

Electronic Theses and Dissertations

Wearable ECG monitors enable continuous cardiac surveillance, yet most remain limited to basic heart rate metrics or coarse atrial fibrillation detection, relying on cloud-based analysis that introduces latency, connectivity dependence, and battery drain. Deploying advanced multi-class arrhythmia classification directly on-device is constrained by the tight memory, power, and computational budgets of wearable hardware. This dissertation presents a Quantized Convolutional Spiking Neural Network (QCSNN) for real-time ECG arrhythmia detection on edge hardware, developed across three progressive phases.

Phase 1 introduces a separately trained two-stage QCSNN architecture — a binary classifier cascaded with a four-class classifier — trained directly via surrogate gradient …

Leader Election System For An Unmanned Ground Vehicle Swarm, Milan Chhetri, Brendan Beas, Paul Levin

Electrical Engineering

This senior project presents the design and implementation of a leader-election system for a leader-follower unmanned ground vehicle (UGV) swarm using embedded control and wireless communication. The objective of the project is to improve the robustness and mission longevity of a multi-agent robotic system by allowing the swarm to dynamically select the most suitable leader during operation. Each UGV is equipped with an ESP32 microcontroller, DWM1000 Ultra-Wideband (UWB) ranging modules, an MPU-6050 inertial measurement unit (IMU), motor drivers, and supporting power electronics to enable communication, sensing, and autonomous control. A battery monitoring subsystem was developed using the ESP32's built-in Analog-to-Digital …

Archimedean Spiral Antenna Array With Klopfenstein And Exponential Tapered Balun Feeds, Leo Joseph Alvelais Iv, Paul Obrecht, Naguib Abdulla, Preston Mavady, Collin Fan

Electrical Engineering

This project presents the design, fabrication, and experimental evaluation of a broadband 3x3 Archimedean spiral antenna array tile for 2.8-3.8 GHz. Each element combines a two-arm spiral on Rogers RO4350B, a printed 50 to 150 Ω tapered balun, and a conductive backplane. Klopfenstein and Exponential feed implementations were modeled in Ansys HFSS, generated and tuned with automated scripting, fabricated, and evaluated with calibrated network and anechoic-chamber measurements. The Klopfenstein-fed hardware met the -10 dB input-reflection criterion across the project band. The exponential array provided a broad matched response but reached approximately -8 dB near 2.95 GHz. Measured center-element patterns retained …

Vision-Based Autonomous Tracking Rover, Alejandro Ahumada, Erick Ayala, Jonathan Chavez

Electrical Engineering

AAC Vision designed and constructed a vision-based autonomous tracking rover capable of exploring an indoor environment, avoiding obstacles, generating a two-dimensional LiDAR map, detecting a standard orange basketball, and approaching the target without manual steering. The rover uses a Raspberry Pi 4, an Intel RealSense D435 RGB-D camera, an RPLIDAR C1, four JGB37-520 Hall-encoder motors, dual H-bridge motor drivers, a 12 V battery, and a custom aluminum chassis measuring approximately 8 in by 12 in and weighing 6.7 lb. The final mission emphasized reliable target discovery rather than travel between predetermined points. The software integrates Python, OpenCV, Ultralytics YOLO, RealSense …

Nb–Zr Interdiffusion In The (Hf,Ta,Ti,Nb)B2–(Hf,Ta,Ti,Zr)B2 High-Entropy Boride System, Ana C. Feltrin, Yue Zhou, Stefano Curtarolo, Gregory E. Hilmas, William G. Fahrenholtz

Materials Science and Engineering Faculty Research & Creative Works

Niobium (Nb) presents a challenge for achieving homogeneous solid solutions in high-entropy boride and carbide ceramics. In this work, we synthesized (Hf,Ta,Ti,Zr)B₂ (Zr-HEB) and (Hf,Ta,Ti,Nb)B₂ (Nb-HEB) ceramics by boro/carbothermal reduction, followed by densification via spark plasma sintering (SPS). Diffusion couples were prepared to investigate the interdiffusion behavior of Nb and zirconium (Zr) in these complex systems at temperatures between 2000°C and 2200°C. Aside from Nb and Zr, the other elements exhibited no significant concentration gradient across the diffusion interface. Nb exhibited lower diffusion coefficients ((Formula presented.) Nb = 1.7 x 10⁻¹⁷–1.2 x 10⁻¹⁶ m^{2 …}

Perspectives Of Scholars, Families, And Advisors On 360-Degree Video Technology In Graduate Education, Oluwatobi A. Mogbojuri, Bridget A. Walsh, Matthew Aguirre

Journal of Human Sciences and Extension

This study explored the experiences of scholars in creating and sharing 360-degree videos, as well as the perspectives of families and advisors who viewed the videos. Focus groups and individual interviews were conducted online using a videoconferencing platform. Perspectives from 20 participants (15 scholars, three advisors, and two family members) were analyzed using thematic analysis. Three primary themes were identified: (1) barriers to 360-degree video use, (2) perspective shifts and limited change, and (3) storytelling and scholar visibility. Findings suggest that 360-degree video technology may be an innovative tool for enhancing recruitment and retention, especially for historically marginalized groups, through …

Analysis Of Construction Safety Costs In Girder Erection Work On Toll Road Projects To Reduce Risks And Construction Accident Costs, Aditya Daniar Wicaksono, Rossy Armyn Machfudiyanto

CSID Journal of Infrastructure Development

The construction of toll roads, as part of Indonesia’s National Strategic Projects, plays a crucial role in enhancing mobility and economic competitiveness. Girder erection work constitutes one of the most critical phases in toll road bridge construction, characterized by high safety risks due to confined workspaces, technical complexity, and suboptimal risk management practices. This study aims to analyze construction safety costs in girder erection work to reduce risks and construction accident costs. The research process includes hazard identification, effective risk control analysis, risk impact valuation, and cost-benefit analysis of safety investments. The methods employed consist of secondary data analysis, risk …

Nebraska And The Midwest Agtech Ecosystem: Benchmarking Innovation Investment And Translation Gaps, Ankit Chandra, Ishani Lal, Brennan Costello

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

Agricultural innovation is central to the sustainable transformation of food systems, yet the capital that finances it is unevenly distributed relative to where food is produced. This paper develops a diagnostic framework for measuring this mismatch and applies it across the U.S. Midwest from 2021 to 2025, with particular emphasis on Nebraska's structural position within this landscape. Drawing on venture capital deal-flow data, 17 stakeholder interviews, and a novel strength-weakness-opportunity-gap (SWOG) ecosystem mapping methodology, we document $736 million in tracked Midwest AgTech funding across eight states (Nebraska, Iowa, Missouri, Illinois, Indiana, Kansas, North Dakota, and South Dakota). We introduce three …

Dc/Dc Converter For A Solar Module, Stella Uribe, Richie Zaragoza, Olivia Grace Tran, Phillip Tyler Rich

Electrical Engineering

This project focuses on the design and validation of a general-purpose DC/DC power converter intended for use with photovoltaic (PV) solar modules operating under variable environmental and loading conditions. Solar panels exhibit significant variation in output voltage, current, and available power due to changes in irradiance, temperature, and operating point, making direct connection to downstream loads impractical. The proposed system addresses this challenge by providing a single, user-adjustable regulated DC output capable of both stepping up and stepping down the solar module voltage. The converter is designed to interface with solar modules rated between 50 W and 400 W, with …

Autonomous Terrain-Mapping Robot For Search And Rescue, Soumil Joshi, Seann Calub

Electrical Engineering

This report documents the design, modular testing, and challenges faced while developing an autonomous terrain-mapping robot intended to navigate to a destination waypoint and deliver a small payload for search-and-rescue applications. The system combines a LiDAR sensor, an IMU sensor, and a Raspberry Pi 3B as the onboard processor, and an ESP32 microcontroller interfacing with motor drivers over a four-wheel chassis. A companion mobile application was developed to enable remote control and monitoring of the robot over a WiFi hotspot connection. A lithium-ion battery pack supplies power to all onboard components, with power budgets verified against component datasheets. Testing progresses …

Evaluating The Safety Efficiency Of U.S. Air Traffic Control Tower Operations Using Data Envelopment Analysis, Kenneth James Gilbert Ii

Doctoral Dissertations and Master's Theses

Air traffic control (ATC) tower safety efficiency remains inadequately measured despite critical workforce challenges, including staffing shortages, training pipeline constraints, and geographic retention difficulties. This mixed-methods study developed and validated a comprehensive framework for measuring tower safety efficiency by integrating subject-matter expert insights with multi-model data envelopment analysis (DEA) across 66 Federal Aviation Administration (FAA) tower facilities from 2016 to 2024. Six focus group interviews with experienced professionals (100% with > 20 years of experience), averaging 96.4 minutes, identified critical efficiency factors through systematic coding, achieving substantial inter-rater reliability (Cohen's kappa 𝜅 = .68). Qualitative findings showed that staffing shortages don't …

Influence Of Stormwater Flooding Events On The Mobile County School District Student Population, Kadence Kali Johnston

Honors Theses

Mobile County, Alabama, receives among the highest annual rainfall totals in the United States resulting in frequent stormwater flooding that intersects with existing socioeconomic vulnerabilities. Within the Mobile County Public School System (MCPSS), 77% of students are economically disadvantaged and over 10% experience homelessness, creating heightened risk for educational disruption during flood events. This study investigates how stormwater flooding influences school attendance, closures, and academic performance across MCPSS, providing insight into how climate-driven hazards exacerbate educational inequities. The research integrates flood frequency, school performance metrics, and GIS flood-zone mapping and teacher perceptions to understand how flooding affects student learning opportunities. …

Decoration Of Lactic Acid Bacterium By Exploiting In Vitro Sortase A Transpeptidase, Faisal Hamd Alqhtani

Graduate Theses and Dissertations

Attaching a drug module to the surface of lactic acid bacteria was the main aim of this dissertation, and it was achieved. By using the Sortase A mechanism, the drug module (green fluorescent protein fused to the LPETG motif) was anchored to the LAB surface. To reach the final results, this dissertation will describe the process that I undertake to achieve the end goal. Modifying media, producing pure enzymes with less impurity, and reducing the protease activity in E. coli BL21 were all described in this five-chapter dissertation. Keywords: drug delivery, lactic acid bacteria, green fluorescent protein, sortase A, fusion …

Interpretable Machine Learning Of Plasma Proteomics Reveals Stage-Specific Signatures Across The Alzheimer's Disease Continuum, Hemshankar Laugi

2026 Spring Honors Capstones Projects

Alzheimer’s pathology begins years before clinical symptoms, starting early with amyloid-β accumulation, followed by tau deposition and neurodegeneration. Although existing tools, such as cerebrospinal fluid (CSF) screening and PET/MRI imaging, can accurately track disease progression, they are invasive, expensive, and not scalable for population-level screening. So, there is a growing interest in using blood-based plasma biomarkers as a scalable alternative. While recent studies demonstrate strong predictive performance with plasma biomarkers, most rely on a small set of canonical blood-based protein biomarkers such as amyloid-β, p-tau, and neurofilament light. These biomarkers primarily reflect downstream brain pathology and may fail to capture …

Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat, Yelei Zhu, Shoulin Shen, Jiang Zhu, Chuanhua Wen

Journal of System Simulation

Abstract: Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of microlevel tactical autonomy, meso-level resource constraints, and macro-level network collaboration. In view of the problem that a single-scale modeling method is difficult to simultaneously characterize individual decision-making details, resource flow process, and system collaboration mechanism, a multi-scale modeling method integrating multi-agent modeling, system dynamics, and complex network theory was proposed. By designing six formal coupling operators to achieve cross-layer information mapping, a time progression mechanism based on a master-slave clock and hybrid synchronization was established, and a proof of error boundedness was provided. A prototype system was implemented on …

Distinct Regulatory Dna Methylation Signatures Across Multiple Sclerosis, Neuromyelitis Optica, And Neurological Post-Acute Sequelae Of Covid-19, Syed Ilyas Munzir, Daniel B. Hier, Michael D. Carrithers

Electrical and Computer Engineering Faculty Research & Creative Works

Background/Objectives: Our prior epigenome-wide association study (EWAS) on multiple sclerosis (MS) identified myeloid-associated methylation signatures and an association with enhancer regions. Here we compared differential DNA methylation across three central nervous system inflammatory disorders: MS, neuromyelitis optica (NMO), and neurologic post-acute sequelae of COVID-19 (neuro-PASC). Methods: Whole-blood DNA was profiled on Infinium MethylationEPIC arrays. Analyses included EWAS at the CpG level, differentially methylation region (DMR) analysis, and gene regulatory-element enrichment using Locus Overlap Analysis (LOLA). Limma linear models were adjusted for race, EPIC array version, age, sex, disease-modifying treatment class, and blood cell composition. Results: All three diseases were associated …

Pfas Quantification Using Solid Phase Extraction And Low Field Nuclear Magnetic Resonance (Spe-Nmr), Nicholas N.A. Ling, Ghasemi, Ella Shilliday, Masoumeh Zargar, Einar Fridjonsson, Michael L. Johns

Research outputs 2022 to 2026

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals that are highly resistant to biodegradation. Due to their bioaccumulation, long-term persistence, and adverse human health effects, they have been classified as organic pollutants. The leaching of PFAS into water sources has resulted in their detection in global drinking water supplies. To mitigate adverse health effects and minimise environmental damage, regulations regarding maximum allowable PFAS concentrations in water have been imposed. Traditional PFAS in water quantification methods, such as liquid chromatography–mass spectrometry (LC–MS), gas chromatography–mass spectrometry (GC–MS), and high-performance liquid chromatography (HPLC), have intrinsic limitations that pose challenges in such PFAS analysis. …

Advancing Social Media Analytics And Personalized Generation Via Transfer Learning, Discourse-Aware Modeling, And Collaborative Modeling, Gibson Nkhata

Graduate Theses and Dissertations

Social media platforms have become central to information exchange, shaping public opinion across social, political, and economic domains. However, the massive volume of user-generated content, combined with its informal, nuanced, and often noisy nature, presents significant challenges for automated analysis and generation. Tasks such as stance detection, rumor verification, and personalized content generation are further complicated by sarcasm, evolving discourse structures, and diverse user preferences. Addressing these challenges requires models that can effectively leverage linguistic nuance, conversational dynamics, and collaborative user signals. Transfer learning has emerged as a powerful paradigm for improving performance in low-resource and complex language understanding tasks. …

Anomaly Management In Unmanned Aerial Vehicles: A Systematic Literature Review, Ivan Tan Wei Han, Christopher M. Poskitt, Lingxiao Jiang, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Unmanned Aerial Vehicles (UAVs) are increasingly deployed in safety-critical applications such as logistics, surveillance, disaster response, and urban air mobility. While their autonomy enables powerful capabilities, it also introduces vulnerabilities due to hardware faults, software defects, communication failures, and adversarial interference. This survey presents a comprehensive review of research studies closely related to UAV anomalies published between 2015 and 2025, covering 111 papers from academic and industrial sources. We introduce a unified five-pillar taxonomy—anomaly generation, prevention, detection, recovery, and analysis—that organizes existing work across the full anomaly management lifecycle. In contrast to prior surveys that focus primarily on detection algorithms, …

Adaptive Solar Energy Collection Fenestration Systems; Measured Performance On Test Cell Under Real Weather Conditions., Noel O’Neill

Doctoral

Buildings account for a significant share of global energy use, and improving façade performance is critical to achieving nearly zero-energy building targets. This research addresses the challenge of integrating multiple adaptive functions into a single façade system to reduce heat loss, harness solar energy, and provide dynamic environmental control. The aim was to design, construct, and evaluate an adaptive Multi-Functional Façade (MFF) that integrates vacuum glazing, switchable opacity glazing, and a ventilated cavity with active airflow control to provide façade insulation, heated fresh air, recirculated air, or exhaust ventilation.

A Solar Thermal Test Cell (STTC) designed to Passive House standard, …

Cellulose Membrane Performance And Properties With Focus On Dialysis Application, Juliana Marçal

Graduate Theses and Dissertations

Chronic kidney disease affects approximately 35 million individuals in the United States, with nearly 550,000 patients dependent on dialysis for survival. Chronic kidney disease and end stage kidney disease impose substantial burdens on patients and healthcare systems, driving demand for improved dialysis membranes with enhanced flux, selectivity, and biocompatibility. The performance of dialysis membranes plays a critical role in treatment efficiency, governing solute transport, fluid removal, and overall therapeutic outcomes. In hemodialysis, membranes must achieve an optimal balance between high permeability and selective solute rejection while maintaining mechanical stability and long-term biocompatibility. Conventional dialysis membranes are commonly fabricated from polymeric …

Thermal Transport Tuning Via Nanoscale Hierarchical Frameworks For Fe2val Thermoelectric Materials, Apoorva Pradip Joshi

Dartmouth College Master’s Theses

Waste heat represents a vast, untapped energy resource. Thermoelectric materials offer a promising route to harvest this energy by directly converting thermal gradients into electricity. The Heusler alloy Fe2VAl is a prime candidate for such applications because it is non-toxic and cost-effective. However, its intrinsically-high thermal conductivity severely limits performance. A detailed understanding of thermal transport mechanisms is therefore essential for improving its thermoelectric efficiency. This work examines the effect of atomic disorder on the thermal transport behaviour of Fe2VAl. We use germanium doping to introduce atomic-scale disorder and demonstrate a substantial reduction in thermal conductivity, from 28 W/m-K in …

The Privacy Trap: Keeping Sensitive Data Safe In The Ai Era, Xiaohui Liang

Paul English Applied Artificial Intelligence (AI) Institute Publications

This presentation examines privacy and data security risks associated with the growing use of artificial intelligence, with particular attention to the sensitive information users may disclose when interacting with AI systems. It explores how voice, text, images, and prompts can expose personally identifiable and privacy-sensitive information and introduces privacy threats associated with large language models and other AI systems. The presentation discusses approaches for identifying and protecting sensitive information, including named entity recognition, prompt modification, masking, replacement, and other privacy-preserving techniques. It also examines the trade-off between protecting privacy and maintaining the usefulness of AI-generated responses. Drawing on research in …

Confidenceai: A Wearable And Predictive Ai Ecosystem, Denzil Paul, Xuejun Kong, Raymond Wang, Flora Fleith Lopes, Zhengjia Yang, Brain Chu, Weijian Wang, Leo Chen

Paul English Applied Artificial Intelligence (AI) Institute Publications

This group project presents ConfidenceAI, a conceptual wearable and predictive artificial intelligence ecosystem designed to help teenagers build confidence and manage stress in high-pressure situations such as classroom participation and public speaking. The system combines wrist-based biosensing with a personalized machine-learning model that uses physiological signals, including heart rate and heart rate variability, electrodermal activity, skin temperature, and movement, to learn an individual's baseline patterns and anticipate heightened stress responses. Rather than relying on universal thresholds, ConfidenceAI is designed to personalize the timing, method, and delivery of interventions based on each user's physiological patterns and prior responses. The proposed ecosystem …

How Do Different Food Influents Affect Biogas Production, Process And Operational Stability, And System Performance In The Armfield W8, A Bench-Scale Anaerobic Digester, Jarko Rumbaoa, Anahita Adhikari

Rose-Hulman Undergraduate Research Publications

No abstract provided.

The Neuropsychological Analysis Of The Effect Of Shame And Traumatic Memories In Paranoia: A Network Analysis, Anwesha Maitra

Clinical Psychology Dissertations

Paranoia is increasingly recognized as a multidimensional psychological phenomenon influenced by trauma-related distress, shame, maladaptive interpersonal experiences, and emotional functioning. Although these factors have been extensively associated with paranoia, their relationships with neurocognitive functioning, social cognition, and global functioning remain less well understood. The present study examined these relationships using traditional statistical analyses, network analysis, and machine-learning approaches in a non-clinical sample of 42 adults.

Participants completed self-report measures assessing trauma-related distress, childhood interpersonal experiences, shame, paranoia, depressive symptoms, fear of negative evaluation, self-esteem, and hostile attribution bias, in addition to a comprehensive neurocognitive battery, an emotion recognition task, and …

Examining Data Richness In Undergraduate Students’ Reflections: A Linguistic Analysis Of Three Data Collection Methods, Kirsten A. Davis, Anne Wrobetz

School of Engineering Education Faculty Publications

Researchers select data collection methods for a variety of reasons. In our research on experiential education programs, we perceived that when we collected students’ reflections using different methods, the data we received was different. However, we found few existing studies to help us characterize what was different across our data sets to inform our decisions about which methods to use. Thus, the purpose of our study was to compare data richness across three data sets from previous studies of engineering students studying abroad, each collected using a different method (written diaries, interviews, video diaries). We used linguistic inquiry as a …