Digital Commons Network^™

Advancing Cns Tumor Management: Novel Modalities In Surgery, Radiation, And Chemotherapy, Armin David Tavakkoli

Dartmouth College Ph.D Dissertations

Most tumors affecting the brain and spine are managed through a combination of surgical resection, radiation, and chemotherapy; however, operative morbidity from invasive surgery, the narrow therapeutic window of conventional radiotherapy, and poor blood-brain barrier penetration of systemic agents are critical barriers that hinder long term tumor control. This thesis presents three complementary strategies to advance brain and spine tumor therapy. First, we investigate laser interstitial thermal therapy (LITT) in the treatment of spinal tumors with metastatic epidural spinal cord compression, replacing “separation surgery” with a minimally invasive, image-guided approach that maximizes tumor ablation while preserving neurologic function. Second, we …

The Impact Of Surveying, Nicholas A. Cosper

Williams Honors College, Honors Research Projects

My project consists of three parts. The first part will be helping the public. To do this I will be helping the Boy Scouts earn their surveying merit badge. This badge is known to be one of the hardest for scouts to obtain. In the next part of my project, I will be running a 3-wire level on the Davey Tree Seed Campus. This project will be extremely useful to them (the rest of this information is confidential). In the final part of my project, I will be conducting a topographical survey for the Cuyahoga Valley National Park for a …

High-Speed Non-Pneumatic Tire (Npt) Design For Speeds Above 60 Mph, Jacob Grams, Brady Maurer, Jake Groewa

Williams Honors College, Honors Research Projects

This project focuses on developing a high-speed non-pneumatic tire (NPT) capable of safely operating at speeds greater than 60 mph, a performance range where most existing airless tire designs fail due to structural instability and performance limitations. The objective of this work is to design, analyze, and prototype a structurally optimized honeycomb-based tire structure with improved load distribution, deformation control, and durability. Multiple geometries were evaluated using finite element analysis (FEA) to assess stress and maximum resultant (total) displacement behavior under loading conditions, and a material selection study was performed to identify a suitable material for the design. The final …

Dashboard And Racing Telemetry, Cole Barach, Jacob Koshel, Ethan Zifzal, Matthew Sullivan

Williams Honors College, Honors Research Projects

The main goal of the project is to design and manufacture a combined dashboard and data logger for the vehicles produced by the Zips Racing design team. The dashboard will intuitively display real-time information to the driver and record all received information while driving. This information may be pulled off the device later for performing data analysis. This project will incorporate custom PCB design, surface mount soldering, embedded software development, and the CAN communication protocol.

Computer-Aided Molecular Design To Identify More Environmentally Friendly Pfas, Melvin M. Keita

Williams Honors College, Honors Research Projects

The goal of this project is to inversely design alternatives to per- and polyfluoroalkyl substances (PFAS) using Computer-Aided Molecular Design (CAMD). PFAS, also described as “forever chemicals”, have been used in industry and consumer products since the 1940s. PFAS can be found in drinking water, food, food packaging, waste sites, and other sources. Exposure to different PFAS can lead to increased risks of some cancers, immune effects, and reproductive effects. Pulling from existing data, this project will use quantitative structure-property relationships (QSPRs) to design PFAS alternatives that possess optimal properties to prevent adsorption into drinking water and other potential sources …

Seat Belt Data Collection Methods: A Comparison Between States And National Guidelines, Madison R A Richards

Williams Honors College, Honors Research Projects

Thousands of fatalities related to vehicle crashes occur every year. One method to reduce fatalities is to encourage seat belt use compliance. To promote statistics regarding seat belt use, there first must be reliable data on seat belt compliance and this comes from good survey design.

This report is a comparative analysis of seat belt data collection methodologies for Ohio, Michigan, and Indiana, in addition to an evaluation of how each state aligns with standards set by the National Highway Traffic Safety Administration (NHTSA). The framework for this analysis focuses on NHTSA’s five core survey design requirements: selection of observation …

Secure Peer-To-Peer Messaging Using Distributed Servers, Jack Stoller

Williams Honors College, Honors Research Projects

Traditional messaging systems that rely on centralized infrastructure often introduce three security vulnerabilities: single points of failure susceptible to availability attacks, metadata leakage, and man-in-the-middle attacks.

This project designs, implements, and validates a distributed peer-to-peer messaging system that addresses each of these concerns through architectural design. A consistent hash ring is used with virtual nodes to distribute user data across a mesh of connected nodes, eliminating centralized dependency on any single server. Message contents travel directly between browser clients over a WebRTC data channel secured with end-to-end DTLS encryption, bypassing the server infrastructure. Inter-node communication is protected by mutual TLS …

Automated Pill Dispenser, Ryan Oderkirk, Connor Beaven, Rachelle Labrie, Josue Panchana

Williams Honors College, Honors Research Projects

The project we propose is an automated system for dispensing dosages of medication throughout the day. It will be able to alert a user when their pills need to be taken and give them the correct dosages of up to four different medications. These dosages are configurable as well as the scheduled time they are to be taken. In addition, the pill dispenser will alert users when they are low on medications and need to refill the machine.

Analysis Of Policies And Incentives For The Successful Implementation Of Hydrogen-Fueled Medium-Duty And Heavy-Duty Vehicles In Humboldt County, California, Alka Verma

Cal Poly Humboldt theses and projects

The 21st century has seen a significant rise in global greenhouse gas (GHG) emissions, with the transportation sector contributing 23% of these emissions. Medium-duty and heavy-duty vehicles (MD/HD) are particularly impactful, accounting for over a quarter of transport-related emissions. In Humboldt County, California, transportation represents 53% of total emissions, with MD/HD vehicles being a major contributor. As light-duty vehicles shift to zero-emission alternatives, the MD/HD sector faces unique challenges. Hydrogen fuel cell vehicles offer a promising solution, providing longer range, higher energy density, and quicker refueling compared to battery electric vehicles (BEVs). These features make hydrogen an attractive option for …

Managing Green And Sustainable Construction Projects: A Computational Analysis Of Associated Risks And Challenges For Improved Performance, Bahaa Chammout, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Green and sustainable building practices have emerged as effective strategies to address the environmental challenges posed by the construction industry. This includes unsustainable resource utilization, excessive waste production, greenhouse gas emissions, and high energy consumption. However, the integration of green and sustainable initiatives in construction introduces distinct risks and challenges that affect project management and may lead to claims and disputes. To this end, and while previous research examined dispute causation across various aspects of the construction industry, there is limited investigation of the unique and complex nature of risks and challenges - and consequently conflicts, claims, and disputes - …

Managing And Accelerating The Circular Economy Transitions Within The Construction Value Chain Using Network Governance And Game Theory Systems Perspectives, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The fragmented nature of the construction industry has hindered its transition toward circular economy (CE) practices. While game theory (GT) has been successfully applied to support the strategic decisions of CE transitions in other sectors, CE-GT models in the construction domain remain extremely limited. This paper addresses two research questions: (1) how are CE network governance activities currently modeled using GT across domains? (2) How can such models be transferred and adapted to solve strategic interactions within the construction value chain in a manner that enables CE practices to emerge as equilibrium outcomes? These questions are driven by the need …

Biaxial Bending Response Of Prestressed Concrete Girders Subjected To Accidental Asymmetric Prestressing Strand Loss, Haitham Abdelmalek, Mohanad Abdulazeez, Ahmed Ibrahim, Mohamed Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Bridge prestressed concrete girders are vulnerable to sudden rupture of prestressing strands caused by accidental collisions with over-height trucks. These incidents often result in the asymmetric loss of prestressing strands and concrete sections, generating a biaxial bending moment caused by the combined effects of lateral bending and existing service loads. The induced lateral bending moment reduces the flexural resistance of prestressed concrete (PC) girders. However, the current AASHTO LRFD (load and resistance factor design) provisions for flexural resistance in PC members do not explicitly address the complexities introduced by biaxial bending, leaving the extent of strength reduction uncertain. This paper …

Multi-User Collaboration In Augmented Reality For Beyond-Visual-Line-Of-Sight Bridge Inspection, Joel Murithi Runji, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Bridge inspection traditionally relies on scaffolds, snooper trucks, and aerial robots for hard-to-reach areas beyond the visual line of sight of inspectors. This study automates the collaborative inspection workflow for multiple users when inspecting hard-to-reach bridge sections by interfacing low-cost multimodal sensors mounted on a magnetically wheeled climbing robot with augmented reality devices in a cyber-physical system. Non-destructive and visual sensors provide near real-time information of automated steel thickness measurements and visual observations of corrosive regions, respectively. The visual sensors also support robot teleoperation. The cyber-physical system is evaluated for its user-friendliness and performance. The system performance is quantified by …

A Transdisciplinary Approach To Advancing Water Security And Public Health: The “Nurse + Engineer” Model For Achieving Sustainability In Wash Systems Using Community-Based Participatory Research, Daniel B. Oerther, Sarah Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Human health is linked to the health of the environment, a concept referred to as planetary health. As environmental challenges become increasingly complex, single-disciplinary approaches are insufficient to achieve sustainable solutions. This article presents a transdisciplinary framework, termed the "Nurse + Engineer" model, as a novel methodology for addressing complex problems at the nexus of environmental engineering and public health. The model integrates the technical design and systems-level thinking of environmental engineering with the community-based, patient-centered care of nursing. This work details the key lessons learned from the retrospective application of this framework to a series of multi-year, community-based participatory …

Evaluation And Design Of A Footing Hybrid Connection For Innovative Hollow-Core Fiber-Reinforced Polymer–Concrete–Steel Composite Columns, Mohanad M. Abdulazeez, Mohamed A. Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

To support the advancement of accelerated bridge construction in high-seismic regions, this study investigates a novel prefabricated column-to-footing connection designed for improved resiliency, constructability, and cost efficiency. The socket connection utilizes hollow-core fiber-reinforced polymer–concrete–steel (HC-FCS) columns with embedded corrugated steel pipes (CSPs). The composite HC-FCS column consists of a concrete shell sandwiched between an outer fiber-reinforced polymer tube and an inner steel tube. The inner steel tube is embedded into the footing connection of the HC-FCS column. The same authors tested the innovative socket connection on a large HC-FCS column under seismic loads, showing high ductility, strong moment and drift …

Exploring Aggregate Morphological Characteristics Under Laboratory Polishing For Enhanced Pavement Skid Resistance, Ahmed S. El-Ashwah, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

As the use of recycled asphalt pavement (RAP) in pavement construction grows for sustainable development, it becomes essential to investigate potential frictional deterioration over time. This study evaluated the friction properties of recovered RAP material aggregates compared with raw aggregates across various polishing cycles. The micro-Deval test was employed to simulate aggregate loss of texture, while morphological and friction properties were measured using an aggregate imaging measurement system (AIMS-II), along with a British pendulum tester (BPT) and dynamic friction tester (DFT). Additionally, Fourier transform infrared spectroscopy (FTIR) was employed to assess its potential in determining the origin and composition of …

A Four-Step Thermocatalytic Route For Converting Co2 Into High-Purity Oxalic Acid, Hao Feng, Muhammad Kashif Khan, Lei Li, Hongyan Ma, Xinhua Liang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This research outlines a four-step methodology for transforming CO₂ into high-purity oxalic acid. CO2 was first sequestered as KHCO₃ through its reaction with aqueous KOH, followed by hydrogenation using a supported AgPd/CNT catalyst in a batch reactor at an initial H₂ pressure of 60 bar and a temperature of 150°C. The formate yield reached 91.8% at optimum conditions. Potassium formate in the solid state was thermally coupled in the presence of KOH at 400°C under N2 flow, yielding potassium oxalate of up to 76% yield. The final step was the selective precipitation of potassium oxalate with ferrous …

Metagenomic Polymorphic Toxin Effector And Immunity Profiling Predicts Microbiome Development And Disease-Related Dysbiosis, Hunter W. Schroer, Francesco Beghini, Juan Antonio Raygoza Garay, Nicholas A. Christakis, Dustin E. Bosch

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Bacteria use antagonistic interbacterial weapons, such as polymorphic toxin secretion systems (TSS), to compete for niches in the human gut microbiome. We hypothesized that TSS influence gut microbiome development and disease-related dysbiosis. We developed a bioinformatic marker gene approach (PolyProf) to quantify TSS including ~200 effector and immunity genes and applied it to ~15,000 publicly available human metagenomes. PolyProf alpha and beta diversity readily distinguished 12 different human disease states and enabled the construction of highly accurate linear regression classifier machine learning models. Elastic net machine learning models integrating bacterial taxonomy with PolyProf had strong predictive value for 12 disease …

Distributed Temperature Sensing In The Spray-Cooled Shell Of A 150-Ton Dc Electric Arc Furnace Using Brillouin Optical Fiber Technology, Farhan Mumtaz, Yeshwanth Reddy Mekala, Koustav Dey, Rony Kumer Saha, Ogbole Collins Inalegwu, Manoj Kumar Pullagura, Bohong Zhang, Muhammad Roman, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the deployment and validation of a Brillouin - distributed temperature sensing (DTS) system for real-time thermal monitoring of the spray-cooled upper shell of a 150-ton direct current Electric Arc Furnace (DC EAF) at Big River Steel Plant, Osceola, AR, USA. A four-channel Brillouin DTS system from OZ Optics was employed, with one active channel instrumented using an in-house-fabricated Brillouin scattering-depressed single-mode optical fiber (SMF28e+). The 60 m optical fiber sensor was fabricated, with 20 m allocated for thermal measurement and 40 m used as lead-in fiber to isolate the interrogator from the furnace environment. The fiber was …

Self-Calibrating Uav Navigation: Reinforcement Learning Approaches For Horizontal Trajectory Estimation, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate unmanned aerial vehicle (UAV) trajectory estimation is essential for autonomous navigation, particularly in GPS-denied environments. Visualodometry and simultaneous localization and mapping (SLAM) approaches require precise camera intrinsic parameters, which are typically obtained through predefined or offline calibration. Instead, in this work, we propose a reinforcement learning (RL)-based self-calibration framework that estimates camera intrinsic parameters directly from monocular video sequences, without requiring prior knowledge of the camera, environment, or calibration targets. This intrinsic parameter estimation is then leveraged to achieve robust UAV trajectory estimation using only video data. We formulate the problem as a sequential decision-making task, where an RL …

Digital Twin Technologies For Battery Systems: Advancements, Applications, And Future Directions, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

The relationships among deep learning, edge computing, artificial intelligence (AI), and the most recent advancements in digital twin (DT) technology for battery energy storage systems are discussed in this paper. The study highlights the need for improved cloud-edge coordination, AI model development, and stronger cybersecurity features by demonstrating real-world applications of digital twin technology in electric vehicles (EVs), aircraft, and grid storage. It also described DT-based structures for fault detection, real-time monitoring, and optimization through standardization and battery management system (BMS) fusion. Because DT-based solutions for distributed energy resources (DERs) offer improved energy management systems, various studies have been conducted …

Automated Writer And Acquisition-Condition Classification Of Digitally Captured Handwriting Using Statistical Dynamic Features And Support Vector Machines, Long-Huang Tsai, Hsiang-Ju Lai, Wen-Chao Yang, Jiajun Jiang, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

Digitally captured handwriting preserves pen trajectories and dynamic signals, but it also records hardware- and input-dependent properties that can confound forensic interpretation. This study revises a support vector machine (SVM) screening framework using 16,500 samples from 30 writers, 11 writing-content categories, and five acquisition conditions spanning three tablets and stylus or finger input. Twenty-four raw and derived time-series variables were summarized by maximum, minimum, mean, median, and standard deviation, yielding 120 features; the mode statistic was removed. Writing direction and angular velocity were recalculated with atan2-based vector formulas. Unavailable device/API channels were encoded as zero, and Z-score parameters were estimated …

Injectable Hydrogels For Bone Regeneration: Mechanical Reinforcement Strategies Using Nanoparticles And Nanofibers: Review Paper, Fariba Ganji, Morteza Mirzagoli, Lobat Tayebi

Electrical & Computer Engineering Faculty Publications

Background and Purpose: The growing demand for bone regeneration following severe injuries highlights the importance of scaffolds in bone tissue engineering (BTE). Injectable hydrogels have emerged as promising candidates because their properties closely mimic the native extracellular matrix (ECM). However, their limited mechanical strength and structural instability restrict their practical application. Approach: This review summarizes recent strategies for reinforcing in situ-forming injectable hydrogels to improve their mechanical performance for bone regeneration. Particular emphasis is placed on nanomaterial-based strategies, including the incorporation of nanoparticles and nanofibers, and their ability to enhance the physical properties of polymeric networks. Key Results: Evidence from …

Comparative Assessment Of Energy And Emission Costs For Geothermal Heat Pumps And Fossil-Fuel Heating Systems Across U.S. Climatic Zones, Md Shahin Alam, Shima Afshar, Seyed Ali Arefifar, Mohammad Haq

Electrical & Computer Engineering Faculty Publications

In response to growing concerns over global warming and energy sustainability, transitioning from fossil-fuel-based heating systems to renewable alternatives is essential. This study evaluates the economic and environmental performance of geothermal heat pumps for building heating and compares it with conventional coal-fired boilers, natural-gas boilers, and diesel furnaces. Using the heating degree-day (HDD) method, heating energy demand was analyzed for four U.S. cities—Anchorage (AK), San Francisco (CA), Salt Lake City (UT), and Las Vegas (NV)—representing diverse climatic zones. The analysis integrates thermodynamic and economic parameters, including the coefficient of performance (COP = 2–5) and annual fuel-utilization efficiency (AFUE = 80–97%), …

Personality Exceptions: Enhancing Character In Narrative Planners With Internal Memory, Elinor Rubin-Mcgregor

University of Kentucky Doctoral Dissertations

Stories and narratives are powerful tools for forging connections between people, as they induce emotions shared through their audience and help build empathy and understanding through sharing unique perspectives. Interactive stories can do all this and more, as they can be used to better educate and engage their audience. But in such stories, the characters must have consistent personality and human-like emotions in order for the audience to relate to them. Current implementations of personality in interactive narratives either portrays characters with static personality that feel less realistic, or else require a great deal of additional work from the author …

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

Social Safety And Social Security: Validating Context-Specific Instruments For Slums, Liss D. Romero, Katherine Palacio, Zacheous Ako Abang, Valeria Silgado, Humberto Llinas, Leidy González, Erika Frydenlund, Daniel Bolivar, Jose J. Padilla

VMASC Publications

Social safety and social security are concepts that help explain a community's well-being by assessing how it manages and mitigate existing, or perceived, risks. However, these terms are often conflated, which can limit understanding, particularly in areas with unstable living conditions. This study explores both concepts in the context of residents living in slums. As the number of displaced people grows, slums and informal settlements are becoming increasingly common worldwide, making it essential to clarify these concepts. Residents of slums face numerous hazards, including crime, violence, inadequate housing, overcrowding, and limited access to essential services. To measure social safety and …

Distilling The Complexity Of Agent-Based Simulations Into Textual Explanations Via Large Language Models, Noé Y. Flandre, Philippe J. Giabbanelli

VMASC Publications

Communicating the design and results of agent-based models (ABMs) to subject matter experts is challenging, which hinders participation and limits trust in simulation-based decision support. Large language models (LLMs) can communicate ABMs as textual summaries, thus complementing traditional disclosure through statistical and visualization techniques. While prior work translated the structure of conceptual models into narratives via LLMs, our extension covers the dynamics of simulation models via an automated simulation-to-text method that extracts contextual information from NetLogo ABMs, performs repeated simulations, and generates narrative descriptions (including the model’s purpose, parameters, and simulation dynamics) using mutimodal LLMs. Furthermore, four summarization algorithms spanning …

A Dataset-Centric Analysis Of Evaluation Protocols In Face Morph Attack Detection, Sheerko R. Hmasalah, Abdulbasit K. Al-Talabani, Aras T. Asaad

Polytechnic Journal

Face morph attack detection (MAD) is often evaluated using datasets collected from diverse sources, created for different purposes, and acquired under varying conditions. This heterogeneity raises questions about how evaluation protocols and dataset characteristics influence reported performance. This work adopts a dataset-centric perspective to analyze the effects of evaluation protocol and dataset composition, including visual quality and morph-to-genuine imbalance, on MAD performance. Experiments are conducted on eight datasets and four morphing techniques using a fixed pipeline evaluated across six backbones, including Vision Transformer (ViT) and five CNN architectures, and ten evaluation scenarios covering homogeneous and heterogeneous cross-morph generalization. Performance is …

Evaluating The Use Of Machine Learning For Road Maintenance Cost Estimation, Shahla Shirinzad, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

Accurate estimation of highway maintenance costs is essential for efficient resource allocation and long-term infrastructure sustainability. This study evaluates the effectiveness of advanced machine learning models, including ResNet, Transformer, and other neural network architectures, for forecasting maintenance costs using historical data from the Highway Maintenance Improvement Program (HMIP) provided by the North Carolina Department of Transportation (NC DOT). A comprehensive comparative analysis is conducted across multiple models using standard performance metrics, including R², MAE, RMSE, and MSE. The results demonstrate that advanced architectures, particularly ResNet and Transformer, consistently outperform traditional statistical approaches and baseline machine learning models, achieving …