Digital Commons Network^™

The Aerodynamics Of Swept, Canted, And Slotted Winglets, Andrew K. Mahler

Mechanical Engineering Master's Theses

Winglets have been used to improve the aerodynamic performance of wings. They do this by decreasing the lift induced drag that is experienced by the wing. The winglet modifies the wingtip vortex generated by adjusting both its size, location and strength. Motivated by previous research on the manipulation of wake vorticity through the use of a forward or backward sweep discovered originally when investigating crescent wings, the presented work investigates the role of sweep, cant and slots on winglets. Sweep was first applied to positive and negative canted wings with a symmetric airfoil, the ONERA M6. The wing flows were …

Comparative Analysis Of Loss Of Control Definitions, Owen D. Poborsky

Journal of Aviation Technology and Engineering

“Loss of control” (LOC) is a broad term in aviation used to describe an event or series of events that resulted in an accident or incident of an aircraft. Many definitions of LOC exist for aircraft while maneuvering on the ground and in the air. The purpose of this study is to synthesize the numerous LOC definitions found in the literature and from government and rulemaking organizations to better understand the importance of airspeed awareness as it relates to LOC events at low altitudes. Furthermore, emphasis shall be placed specifically on flight training within general aviation, as significant LOC statistical …

Multi-Field Quantum Conference Key Agreement Using An Integrated Photonic Green Machine, Benjamin J. Fisher

Theses and Dissertations

Quantum Conference Key Agreement (QCKA) enables a group of users to generate a shared secret key, which reduces the latency and equipment overhead of establishing multiple Quantum Key Distribution (QKD) links. Conventional QCKA protocols send a multi-photon entangled state from one user to others and a key is generated only when all photons are detected, which is inefficient at high loss and opens side-channels at the receiver side. Here, we overcome this barrier through a multi-field QCKA protocol enabled by designing, fabricating, and testing an integrated photonic Green Machine that implements an eight-mode Hadamard unitary transformation through a beam-splitter network. …

Advances In Bone And Orthopedics 2025 – 5th Edition, Jean-Philippe Berteau, Laurent Pujo-Menjouet, Hélène Follet, Aurélie Levillain

Publications and Research

This volume brings together selected works from the 2025 Bone and Orthopedics Interdisciplinary Symposium (BONITOS), underscoring our community’s ongoing commitment to advancing research in biomechanics, bone health, and orthopedic science. The symposium unites leading experts from around the world, fostering collaboration and the exchange of ideas across disciplines. Organized in partnership with the French-speaking Society of Biomechanics, the French National Institute of Health and Medical Research (INSERM), the University of Lyon, the College of Staten Island of the City University of New York (CUNY), and the American Association of Physical Therapists (APTA) – Brooklyn Staten Island Chapter, BONITOS 2025 represents …

Computational Fluid Dynamics And Fluid Structure Interaction Modeling In Healthy Vertebral Arteries: A Comparative Study, Bryce Clinkenbeard

Electronic Theses and Dissertations

Cerebral perfusion is critical for maintaining proper brain function, with each cerebrovascular artery playing an integral role in the overall cerebrovascular system. When these arteries become damaged or develop plaque, cardiovascular disease (CVDs) such as atherosclerosis can arise, leading to conditions like arterial stenosis. While CVDs are most prevalent in older individuals, they are also observed in young adults, particularly those engaged in high-endurance occupations such as military service. Diagnosis and prediction of CVDs often rely on imaging modalities supported by computational fluid dynamics (CFD) which account for low resolution in fluid flow. CFD models assume rigid arterial walls, which …

Development Of An Embedded Iot Board For Real-Time Floor Estimation Of Autonomous Robots, Carter J. Sorensen

Electronic Theses and Dissertations

As service robots become more prevalent in multi-story environments such as hospitals, hotels, and laboratories, accurate floor-level detection is critical to ensuring operational reliability. Consider a robot tasked with delivering medical samples in a multi-story laboratory. Without accurate feedback, a robot exiting on the wrong floor could introduce delays, disrupt workflows, or compromise sample integrity. Internet of Things (IoT) technologies offer a way to address these risks by providing real-time error detection and corrective capability. However, current IoT-based floor estimation systems often require invasive modifications to building infrastructure—particularly elevator control panels. These approaches introduce challenges related to cost, liability, backward …

Optimized Wireless Power Transmission For Low-Cost, Energy-Efficient Internet Of Things Devices In Residential Environments, Daniel Brook Hatch

Theses and Dissertations

Wireless power transmission (WPT) offers a promising solution for powering devices in locations where traditional electrical outlets are inaccessible, such as ceilings or outdoor environments. By utilizing electromagnetic waves, such as light, WPT enables power delivery without the need for physical connections. With line-of-sight (LoS) as its primary limitation, this technology offers significant flexibility and potential for a wide range of applications, making it a compelling focus for research and innovation. Despite the advancements in WPT technologies, their practical application for powering Internet of Things (IoT) devices in real-world scenarios remains underexplored. Many IoT devices are installed in locations where …

Online Hyperparameter Tuning For Llm Optimization, Ethan Lin, Nathan Yu, Jeromy Chang

Computer Science and Engineering Senior Theses

Large Language Models (LLMs) are becoming increasingly popular in modern society. However, despite their popularity, the deployment of LLMs in real-world scenarios is extremely challenging due to substantial computational costs and memory constraints. Edge devices, like smartphones and IoT devices, lack resources needed to run these models locally, instead offloading computations for cloud computing. Cloud computing requires users to send their data over the internet leading to numerous privacy and security concerns. In some domains, such as health and finances, sending such sensitive information is not an option. Existing solutions to compress or increase inference speed include Small Language Models …

Remote Sensing Of Seismic Signals Via Enhanced Moiré-Based Apparatus Integrated With Active Convolved Illumination, Adrian A. Moazzam, Anindya Ghoshroy, Durdu Güney, Roohollah Askari

Michigan Tech Publications

The remote sensing of seismic waves in challenging and hazardous environments, such as active volcanic regions, remains a critical yet unresolved challenge. Conventional methods, including laser Doppler interferometry, InSAR, and stereo vision, are often hindered by atmospheric turbulence or necessitate access to observation sites, significantly limiting their applicability. To overcome these constraints, this study introduces a Moiré-based apparatus augmented with active convolved illumination (ACI). The system leverages the displacement-magnifying properties of Moiré patterns to achieve high precision in detecting subtle ground movements. Additionally, ACI effectively mitigates atmospheric fluctuations, reducing the distortion and alteration of measurement signals caused by these fluctuations. …

Intelligent Intrusion Detection In Clustered Wireless Sensor Networks: A Dynamic Clustering And Machine Learning-Based Approach, Abdullah R. Abdulwahhab, Mohd Fadzli Mohd Salleh, Muhammad Firdaus Akb, Mohammed Najm Abdullah

Iraqi Journal for Computer Science and Mathematics

Traditional Intrusion Detection Systems (IDS) designed for more conventional network infrastructures are often ill-equipped to handle the unique challenges WSNs pose, leading to significant gaps in security and resilience. This paper introduces an Intelligent Intrusion Detection System (IIDS) explicitly tailored for clustered WSNs to address these critical challenges. The proposed IIDS integrates dynamic clustering with advanced machine learning algorithms to create a robust and adaptive security solution capable of real-time threat detection and mitigation. The dynamic clustering mechanism is designed to continuously monitor and respond to changes in sensor node network topology and energy levels, ensuring that energy consumption is …

Non-Overlapping Patch-Based Pre-Trained Cnn For Breast Cancer Classification, Lamyaa Sabeeh Ashour, Ahmed Abed Mohammed, Mustafa M. Abd Zaid, Putra Sumari, Ahmed Kateb Jumaah Al-Nussairi, Sura Abdulateef Al-Shammari, Sarah Thabit Abdulmunem

Iraqi Journal for Computer Science and Mathematics

Breast cancer (BC) significantly impacts women's mortality rates and requires early detection to improve survival chances and enable appropriate treatment. Thus, a computer-aided system with high performance can speed up this process. A convolutional neural network (CNN) is considered sensitive to insufficient, noisy data. It cannot achieve high performance, however, restricted access to high-quality medical data, stemming from stringent confidentiality and privacy issues, is a considerable obstacle to the successful training of deep learning models. The current study aims to develop a remarkable, influential model for BC classification whilst considering modern pre-trained models ResNet50, AlexNet, InceptionV3 and VGG16 for extracting …

Retracted: Navigating The Complexities And Artificial Intelligence Of Internet Of Things Security Claims, Tamara Saad Mohamed, Saad Mohammed Khalifah

Iraqi Journal for Computer Science and Mathematics

The term ``Internet of Things'' (IoT) describes a system that allows everyday objects to communicate with one another and with controlled systems, servers, and other linked devices through a variety of connectivity constructions by means of embedded software, sensor technology, electronics, and connections. Data from the Internet of Things (IoT) will be sent to the servers over the internet from a variety of sensors, nods, and collectors. Governments, medical facilities, consumers, and corporations all make use of IoT devices. approximately, More than 65 billion Internet of Things devices are expected to be in operation by 2024. The proliferation of IoT …

Machine Learning Algorithms To Detect Cyber-Attack In The Internet Of Things Platform, Maad Kamal Al-Anni, Rafah M. Almuttairi, Ammar A. Al-Hamadani, Khamis A. Zidan, Husam Ibrahiem Husain Alsaadi, Ghaidaa A. Al-Sultany

Iraqi Journal for Computer Science and Mathematics

In response to escalating cyber threats in Internet of Things (IoT) networks, this research investigates several traffic classification techniques by using benchmark datasets, such as CICIoT2023. This dataset was exclusively used to test the effectiveness of the proposed system, which aims to enhance the data processing for machine learning algorithms amid increasingly complex cyber threats. To prepare the naturally unstructured and raw dataset for analysis, Linear Discriminant Analysis (LDA) is applied for dimensionality reduction. The processed data and attributes are then fed into the proposed Fuzzy-Integrated Relevance Vector Machine Classifier (FIRVM), which is implemented in Python 3.10⁺ using the …

Measurement Of Moisture Levels In Oils And Lubricants Using A Novel Moisture Sensor, Aaron Swartz, Ronak Ali

Electrical and Computer Engineering Graduate Research

It is very challenging to measure moisture levels in oils. There is not a good method to measure it. Using the novel moisture sensor invented by Dr. Zhi David Chen, we tried various methods to measure the moisture levels in oils. The initial trials are to immerse the sensor chip into the oils to see any sensor reading changes with the change of moisture levels in oils. It was observed that the sensor reading was unstable even after immersion into the oil for two weeks. The idea for immersion of the sensor chip into the oils failed due to the …

Western Kentucky University Stormwater Utility Survey 2025, Warren Campbell

SEAS Faculty Publications

This survey provides data on 2147 U.S. and 82 Canadian stormwater utilities. The data is intended to provide useful data to communities that wish to enact stormwater utilities. Different fee systems are examined with the goal of avoiding legal exposure. Recently, the major source of pre-disaster mitigation funds was eliminated. States should consider state-wide stormwater utilities to make up for this loss.

Detection Of Fake News In Short Videos: A Multimodal Approach, Mona Kumari

Master’s Dissertations

The rise of generative models and affordable video editing tools has fueled the spread of fake and manipulated videos, undermining information reliabilityespecially on social media. Traditional detection methods, focused on single modalities like visual artifacts or text cues, often struggle with diverse, user-generated content. This dissertation presents a unified framework for fake video detection that integrates multimodal semantics, narrative structure, and propagation behavior. Visual, audio, text, and OCR features are extracted using pretrained models (CLIP, Wav2Vec2), and segment-level graphs are built to model narrative flow using Graph Attention Networks (GATv2Conv). User engagement dynamics are modeled via a bidirectional LSTM. A …

Xmr: Extensible Model Representation, Jason Cisneros, Lucas Van Der Heijden

Computer Science and Engineering Senior Theses

In safety critical industries, such as aerospace, verification and validation are crucial steps in system development. Validation begins with decomposing a system into its requirements. These requirements are used to create the high level model of the system. The low level system that is created from this must then be verified. Manually ensuring that the system being verified exactly matches the validated design is tedious, time consuming, and error prone. To solve this, we have created an open source tool that can automatically generate the code from UML models. This enables going from the high level model to the low …

Exploring Novel Methods For Real-Time Multi-Camera People Tracking In Machine Learning, Johan Kou, Connor Vallero

Computer Science and Engineering Senior Theses

Multi-camera people tracking is the process of tracking persons and their paths, continuously across different camera fields of view. It can help track suspects across large areas, and assist individuals in emergency situations. The current state-of-the-art (SOTA) method involves using geometric-consistent constraints, information on the appearance of subjects, and pose estimation for dealing with occlusion issues. This current SOTA works well, but is still lacking in its ability to handle occlusion and perform well in real-time applications on a network. With occlusion, the IDs assigned to persons can be accidentally swapped in high density areas, or places where there are …

An Ai-Driven Microfinance Platform To Enhance The Growth Of Small Businesses, Abdullah Naveed, Yunzhou Wang

Computer Science and Engineering Senior Theses

Microfinance provides financial services to businesses which do not have access to regular banking institutions. There have been many digital applications developed to support microfinance schemes globally. However, the applications currently on the market do not yet fully leverage technology features, which are already being widely used in traditional banking. In conjunction with the Miller Center of Social Entrepreneurship at Santa Clara University, we have developed an application utilizing the latest technologies to help small businesses and lenders in all stages of a microfinance project.

Variable Natural Language Translator For Video Games, Gabriel Bernini, Cole Propach

Computer Science and Engineering Senior Theses

In the field of video games, developers work to immerse players in a variety of ways. In one genre of video games, 2D exploration, or Metroidvania as its colloquially known, developers try to immerse players by letting them explore large worlds with the hope to overcome isolation. Often these worlds are sparse or dead worlds where the player is alone, but by exploring more of the world familiarity with the space is achieved and this isolation can be overcome. We hope to innovate in this genre by utilizing a new way to simulate and overcome this isolation, through language learning. …

Compliant Mechanisms For Scalable Systems And Precision Deployment, Jared Rodney Hunter

Theses and Dissertations

Compliant mechanisms offer advantages in precision applications where size, scaling, and environmental effects render traditional mechanisms inadequate or likely to fail. However, designing compliant mechanisms and integrating them into larger, more complex systems remains a challenging problem. This thesis presents work that addresses this issue with analytical models and experiments on flat springs, scalable compliant mechanisms, and origami arrays. Storing and releasing energy in tiny, flat compliant mechanisms opens the door for the design of innovative actuators and products in space-constrained situations. Scaling compliant mechanisms allows novel systems to be made that can operate across scales. By designing for scalability …

Towards A Robust Hydrologic Data Assimilation System For Hurricane-Induced River Flow Forecasting, Peyman Abbaszadeh, Fatemah Gholizadeh, Keyhan Gavahi, Hamid Moradkhani

Civil and Environmental Engineering Faculty Publications and Presentations

The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) is a method developed to enhance hydrologic model predictions while accounting for different sources of uncertainties involved in various layers of model simulations. While the effectiveness of this data assimilation in forecasting streamflow has been proven in previous studies, its potential to improve flood forecasting during extreme events remains unexplored. This study aims to demonstrate this potential by employing HEAVEN to assimilate streamflow data from United States Geological Survey (USGS) stations into a conceptual hydrologic model to enhance its capability to forecast hurricane-induced floods across multiple locations within …

Llm Music Creation And Recommendation Applications, Curtis Robinson, Allan Yang, Thomas Liu

Electrical and Computer Engineering Senior Theses

This thesis explores the application of large language models (LLMs) in music analysis, creation, and interaction, focusing on their potential to reshape traditional workflows in the music domain. The study begins by contextualizing the role of artificial intelligence in music technology, particularly emphasizing the emergence of LLMs like GPT and their unique capabilities in multimodal and musical contexts. A comprehensive survey of current research and toolsets highlights both creative and analytical implementations, ranging from text-based music generation to music information retrieval. The core contribution is an experimental framework that integrates LLMs with music processing libraries, enabling novel interactions such as …

The Grd Companion, Julius Gamboa, Muti Shuman, Tro Hovasapian

Electrical and Computer Engineering Senior Theses

This project introduces the design and development of the GRD Companion. This gesture-controlled reminder device aims to support individuals with special needs in their daily routines, in the hope of them being more independent. The system we designed integrates a Raspberry Pi Zero 2 W, PAJ7620U2 gesture sensor, and audio playback components, all housed in a custom 3D-printed case. Some of our key design priorities included accessibility by relying only on gesture recognition to control the device, eliminating screens and buttons, as well as portability, enabling all users to carry the device anywhere. The device is paired with our WaveLink …

Documentation-Aware Code Generation Via Retrieval Augmented Generation, Daniel Amirtharaj, Rahmin Norwood

Computer Science and Engineering Senior Theses

Modern large language models (LLMs) increase the speed of software development but frequently hallucinate code, forcing developers to debug and rewrite generated code manually. This project introduces Documentation-Aware Code Generation, a retrieval-augmented generation (RAG) framework that injects authoritative documentation into the LLM prompt to reduce hallucinations in generated code. We build an ingestion pipeline that scrapes, cleans, chunks, and embeds official API documentation into a Pinecone vector database, then design a retrieval and re-ranking pipeline that retrieves the most relevant snippets for each user query. Results show that augmenting prompts with documentation lowers code hallucination by up to 60%. The …

Lock And Roll, Varun Mangla, Zachary Common, Gaby Gamarro-Gomez

Computer Science and Engineering Senior Theses

As electronic bikes continue to increase in popularity, cycling has become a means of daily travel for more and more people. However, as the price and quantity of these consumer bicycles increase in public areas, so does the probability of their theft. Newer bikes, especially those with onboard electronics, are a priority target for thieves.

Lock and Roll, therefore, is an advanced smart bike wheel lock that aims to address the growing demands for increased bike security. By providing a variety of security features, such as GPS positioning, a gyroscopic alarm system, and remote monitoring, Lock and Roll represents a …

Emg Vocal Translations, Lucas Amlicke, Raphael Kusuma, Cole Heider, Kayleigh Vu, Monica Sommer

Electrical and Computer Engineering Senior Theses

In this paper, we propose a novel augmentative and alternative communication (AAC) framework for silent speech. Many individuals with speech impairments are unable to vocalize effectively due to various conditions that affect the vocal cords. To engage in social activities, many rely on AAC devices that often lack flexibility and expressiveness. Users may still find self-expression and spontaneity difficult with such devices. This project presents a novel approach to developing a silent speech interface (SSI), providing a more adaptable and user-centered solution to give the vocally impaired a voice. Using surface electromyography (sEMG) alongside machine learning techniques, we aim to …

Santa Clara Radio Astronomy Project Iv: Data Acquisition, Nicholas Alva, Peter Lattimer

Electrical and Computer Engineering Senior Theses

Santa Clara Radio Astronomy Project (SCRAP) is a multi-year project that aims to make radio astronomy accessible to the Santa Clara University community. Previous iterations have focused on constructing and improving a parabolic radio telescope located on the balcony of the fourth floor at The Sobrato Campus for Discovery and Innovation at Santa Clara University. Until this year, the radio telescope has been stationary. As a consequence, the telescope is only capable of observing celestial objects directly above it, severely limiting the data capture area. This thesis describes the contributions of SCRAP IV Data Acquisition to the project: enabling 2D …

Enhancing Gpr Reliability For Concrete Infrastructure: Integrating Signal Processing And Deep Learning For Defect And Corrosion Assessment, Priyam Chowdhury

Theses and Dissertations

This research addresses the critical issue of deteriorating civil infrastructure by utilizing GPR integrated with advanced signal processing and machine learning. Employing the Conquest 100 system, four concrete slab configurations were tested: multi-layer rebar with defects, single- and double-layer rebar setups, varied rebar spacing, and pre-corroded rebars (0–30% mass loss). GPR B-scans collected over 3–60 days demonstrated that detection accuracy varied significantly with curing time, structural complexity, and moisture levels. A custom-developed Python script surpassed EKKO_Project software in rebar localization, achieving lower position errors (0.4–0.7 inches compared to 0.5–1.25 inches). Notably, the amplitude of GPR signals unexpectedly increased with corrosion …

Netgen: Network Traffic Generator, Arya Pefourque, Cole Fettkether, Johnathon Maschler

Computer Science and Engineering Senior Theses

This project will investigate the development of a transformer-based machine learning model (NetGen), with the purpose of generating realistic and usable synthetic network traffic from natural language inputs. Network research and testing in the cybersecurity field depend on publicly available packet data (PCAP). Many of these datasets are either outdated or fail to represent more modern traffic patterns. We attempt to address this issue by preprocessing available network data into structured and tokenized sequences, suitable for training a transformer model. The transformer architecture allows us to translate user-provided descriptions—“simulate a TCP handshake from IP A to IP B”—into structurally accurate …