Digital Commons Network^™

A Descriptive Case Study On How Suburban Texas Police Department Drone Use Conforms To Public Opinion, Terrill Brett Spell

Doctoral Dissertations and Projects

The purpose of this qualitative case study was to describe the use of drones by suburban police departments in Texas, and its central research question asked how that drone use aligns with what prior research found the public supports. The research design used a holistic multiple-case approach that involved interviewing police officers who use drones as part of their law enforcement responsibilities. Relevant theoretical frameworks were social contract theory, Packer’s theory on law enforcement, and evidence-based policing theory. Data collection involved semistructured interviews of 13 officers representing the same number of Texas suburban police departments. The data collected and analyzed …

Performance Analysis Of University Wifi Using 802.11e Information Elements, Douglas Christopher Hales

Theses and Dissertations

Wireless networks, including IEEE 802.11 (WiFi), continue to become more important for many uses, including university classrooms. Factors that impact the performance of these networks have changed greatly over time, with increased scale at which they are used, and growing dependence of latency sensitive applications. In order to better understand the performance of current WiFi networks, a methodology was created to capture and analyze beacon frames with optional 802.11e information elements (IE), using Quality of Service enhanced Basic Service Set or QBSS load (channel utilization) and station count. This methodology is able to collect channel use more frequently than many …

Incorporating Industry-Standard Technical Writing Into A Materials Testing Laboratory, Caleb Levi Head

Theses and Dissertations

The fluid analysis and materials testing laboratories are crucial for engineering students to learn experimental procedures and data interpretation. Engineers spend a significant portion of their workday on report writing, yet many feel their undergraduate education did not adequately prepare them for this task. At the University of Arkansas at Little Rock, students were given an industry-influenced lab report template to expand their knowledge of the necessary information required in technical writing, thereby teaching and improving their technical writing skills actively. These reports were evaluated qualitatively and quantitatively against previous submissions over two semesters in the mechanical engineering fluids and …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B Ms

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease.The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning. This is followed by the derivation of a non-uniform filter bank via selective merging of bandpass …

A Deep-Learning-Based Dehazing Framework For Non-Homogenous Scenes, Shimaa Mohammed Abd Elghany, Doaa A. Altantawy, Hossam El-Din Moustafa Moustafa

Mansoura Engineering Journal

The advancement of single-image dehazing techniques has been rapid in recent years. Several existing algorithms that are based on deep learning have shown remarkable efficiency for dealing with homogeneous hazing-free issues, but convolutional neural networks (CNNS) frequently fail on non-homogeneous dehazing datasets. Meanwhile, dehaze results from dense haze regions are often blurry because the information of these regions is typically unknown and difficult to estimate. To address these issues, an efficient image enhancement dehazing algorithm that utilizes deep learning techniques, and a non-uniform atmospheric scattering model had been proposed. Unlike the majority of existing dehazing methods, the medium transmission function …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease. The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning.

This is followed by the derivation of a non-uniform filter bank via selective merging of …

Rethinking Green Building Development Through Policy And Operational Metrics: Insights From Baton Rouge And Beyond, Oluwafemi Awolesi

LSU Doctoral Dissertations

This dissertation explores the challenges and opportunities associated with the development, adoption, and performance of green buildings in regions with relatively low certification uptake, drawing insights from Baton Rouge and its parish system as a case study. It addresses three primary research questions: (1) How can the adoption rate of green buildings be enhanced? (2) How do certified buildings perform compared to their non-certified counterparts? (3) What operational metrics can be applied to better evaluate building performance in the future?

Using a mixed-methods approach, the study examines stakeholder perceptions in East Baton Rouge, Louisiana, investigates energy performance, indoor environmental quality, …

The Effect Of Transformer Based Pre-Trained Language Models On Biomedical Relation Extractions, Eman Saad, Sherif Kishk, Amr Ali-Eldin, Ahmed I. Saleh

Mansoura Engineering Journal

Biomedical relation extraction represents a critical advancement in healthcare research. As the volume of biomedical publications continues to grow exponentially, efficient extraction of entity relationships has become essential for accelerating knowledge discovery, drug development, and precision medicine initiatives. The field has evolved from focusing on simple binary relations, such as Protein-Protein Interactions (PPI), which are fundamental to understanding cellular processes and therapeutic development, to addressing more complex multi-class classification challenges like Drug-Drug Interactions (DDI) and Chemical-Protein Interactions (CPI).Pre-trained language models have become the cornerstone of modern approaches of extracting biomedical relations. Models like BioBERT, PubMedBERT, and SciBERT, along with general-purpose …

Empirical Analysis Of Incentivized Energy Assessment Recommendations And Iiot Cost-Effectiveness In U.S. Smes, Fatemeh Ghafari

LSU Master's Theses

The industrial sector in the United States accounted for 33% of total energy consumption in 2022. Small and medium-sized enterprises (SMEs), which comprise 99.9% of U.S. businesses present a critical opportunity for energy efficiency improvements. Although energy audits provide actionable Assessment Recommendations (ARs) to reduce consumption, high implementation costs remain a key barrier to adoption.

While prior studies have explored rebate programs, most are limited to residential and commercial sectors or focus narrowly on specific technologies or geographic areas for the industrial sector. The objective of this study is to empirically investigate the “Incentivized Assessment Recommendation” (IAR) trends and to …

Research On Simulation Training Technology For Special Vehicle Command Based On Gesture Behavior Cognition Interaction, Xiangyang Li, Zhili Zhang, Rui Wang, Xiao Wang, Cheng Chi

Journal of System Simulation

Abstract: To overcome the practical shortcomings in the driving command training of special vehicles, a simulation training technology framework based on gesture behavior cognition and command interaction was proposed. A somatosensory interactive motion capture device and human skeleton model were used to conduct the real-time dynamic recognition and spatial coordinate transformation of the gesture actions of the command training personnel. The median filtering method was applied to eliminate the abrupt data and random noise. The spatial coordinates were processed consistently by using the human skeleton centralization and normalization method. Based on the command gesture action behavior model library and the …

Enhanced Restoration Of Covid-19 Ct Scan Images Utilizing Advanced Wiener Filtering Techniques, Warqaa Shaher Alazawee, Marwa Subhi Ibrahim, Raghda Salam Al Mahdawi, Ali Albu-Rghaif, Ahmed Sabri Altaie

Iraqi Journal for Computer Science and Mathematics

COVID-19, caused by the SARS-CoV-2 virus, was declared a global pandemic by the World Health Organization (WHO) and rapidly spread worldwide from late 2019. While Reverse Transcription Polymerase Chain Reaction (RT-PCR) is the primary diagnostic tool, its sensitivity ranges from only 60% to 70%, leading to false negatives. Computed Tomography (CT) imaging has emerged as a valuable alternative for accurate diagnosis; however, the quality of CT images is often degraded by motion-induced blur and additive noise, particularly in children, individuals with mental health conditions, or those with phobias of CT scans. This study aims to enhance COVID-19 CT image quality …

Motionfusion: A Robust Ensemble Learning Framework For Accurate Sensor-Based Human Activity Recognition, Hussein K. Almulla, Hussam J. Mohammed, Alaa S. Al-Waisy, Shumoos Al-Fahdawi, Ahmed Adnan Had, Bourair Al-Attar

Iraqi Journal for Computer Science and Mathematics

Human activity Recognition (HAR) has emerged as an important research area due to its potential applications in health, sport, and recreation. The widespread availability of smartphone sensors has facilitated data collection for HAR systems. Although machine learning and deep learning models have proven to be effective in detecting human activity from sensor data, their performance may be limited, this study proposes MotionFusion which is an ensemble learning model to increase HAR accuracy utilizing accelerometer and gyroscope data from a smartphone. By combining Histogram-Based Gradient Boosting, Random Forest, and Extra Trees models with a Support Vector Machine classifier and using feature …

The Future Of Intelligent Industrial Systems: Plc, Node-Red, And Iot/Iiot, Firas Ahmed Hussein, Mohammad Tariq Yaseen, Mohammed Obaid Mustafa

AUIQ Technical Engineering Science

Integrating Programmable Logic Controllers (PLCs) with Node-RED and IoT/IIoT has emerged as a transformative technique for developing intelligent industrial systems as industrial automation improves. This narrative review brings together more than 70 research sources on industrial PLC, Node-RED, IoT, and IIoT applications. Case studies, experimental implementations, and industry reports are used to discover trends, challenges, and opportunities. The review focuses on three main topics: PLCs in modern industrial systems and their evolution and integration with IoT/IIoT; Node-RED as a middleware for industrial automation and its ability to connect PLCs to cloud and edge computing; and IIoT and smart manufacturing and …

Communication Assistance Using A Large Language Model, Justin Y. Li

Electrical and Computer Engineering Senior Theses

The number of people diagnosed with Autism Spectrum Disorder is growing annually at a rapid pace. Autistic people are known to have multiple problems with communication, requiring assistance and coaching which is already limited in availability due to the amount of training required. At the same time, there has been a recent exponential rise in usage of LLMs like ChatGPT which is widely available. This project aims to prototype a solution using ChatGPT to provide communication assistance to those diagnosed with autism. The project would record voice input through a microphone and transcribe it into text. The text would be …

Recent Advances In Modelling Of Frost Formation For Mechanical Systems, Yong Tao

Mechanical Engineering Faculty Publications

The physics underlying frost and ice formation has been extensively studied over the past few decades, with significant contributions to our understanding of this phenomenon. These insights have primarily been applied to engineering systems with refrigerated surfaces, such as refrigerators, freezers and heat pumps of various sizes. Despite considerable progress, the dynamic and complex mechanisms governing frost and ice formation remain an active area of research, as competing factors continue to challenge predictive accuracy. The increasing interest from stakeholders in reducing energy consumption and carbon footprints in mechanical systems further underscores the importance of advancing modelling and simulation capabilities in …

A Predictive Framework For Early Detection And Personalised Monitoring Of Parkinson’S Disease Using Artificial Intelligence And Large Language Models, Priyadharshini S

Theses and Dissertations

Parkinson’s Disease (PD) is a multifaceted and progressive neurodegenerative disorder that presents a spectrum of motor and non-motor symptoms. Early and accurate diagnosis is essential for effective disease management and improved patient outcomes, yet remains clinically challenging due to symptom overlap and diagnostic limitations. This thesis proposes a comprehensive and interpretable artificial intelligence (AI)-driven diagnostic framework that aims to transform the early detection, personalised monitoring, and treatment recommendation process for PD. The proposed solution integrates deep learning, radiomics, evolutionary optimisation, and large language models (LLMs), ensuring a highly accurate and clinically adaptable system.

The research begins by analysing T2-weighted 3D …

Decision Analysis Data Model For Digital Engineering Decision Management, Gregory S. Parnell, C. Robert Kenley, Devon Clark, Jared Smith, Frank Salvatore, Chiemeke Nwobodo, Sheena Davis

Industrial Engineering Faculty Publications and Presentations

Decision management is the systems engineering life cycle process for making program/system decisions. The purpose of the decision management process is: "& mldr;to provide a structured, analytical framework for objectively identifying, characterizing and evaluating a set of alternatives for a decision at any point in the life cycle and select the most beneficial course of action". Systems engineers and systems analysts need to inform decisions in a digital engineering environment. This paper describes a Decision Analysis Data Model (DADM) developed in model-based systems engineering software to provide the process, methods, models, and data to support decision management. DADM can support …

An Acoustofluidic Device For Sample Preparation And Detection Of Small Extracellular Vesicles, Jessica F. Liu, Jianping Xia, Joseph Rich, Shuaiguo Zhao, Kaichun Yang, Brandon Lu, Ying Chen, Tiffany Wen Ye, Tony Jun Huang

Faculty Publications

Small extracellular vesicles (sEVs) have emerged as powerful vectors for liquid biopsy, offering a noninvasive window into the dynamic physiological and pathological states of the body. However, to fully leverage the clinical potential of sEV biomarkers, it is imperative to develop robust and efficient technologies for their isolation and analysis. In this study, we introduce a novel sharp-edge acoustofluidic platform designed for rapid and effective sample preparation, coupled with sensitive detection of specific sEV populations based on their surface markers. Our approach utilizes acoustically activated sharp-edge microstructures to concentrate bead-bound sEVs within the microfluidic device, facilitating immediate visualization by fluorescence …

Mode Engineering And Functional Enhancement In Piezoelectric-On-Silicon Mems Resonators With Magnetic Field Sensing Applications, Ugur Guneroglu

USF Tampa Graduate Theses and Dissertations

This dissertation significantly advances the field of micro-electro-mechanical systems (MEMS) resonators by exploring novel post-fabrication tuning techniques, electrode configuration effects, and innovative sensor applications for thin-film piezoelectric-on-silicon (TPoS) resonator devices. Driven by the increasing demand for tunable, high-precision and robust MEMS resonators in radio frequency (RF) applications such as sensing, timing, and filtering, this research aim to provide foundational knowledge and practical solutions for overcoming existing technological limitations. The dissertation is organized into three main research thrusts, each addressing critical challenges and opportunities in the design, fabrication, and application of TPoS MEMS resonators.

The first research thrust investigates an innovative …

Security Analysis Of Encrypted Mempool, Prabal Das

Master’s Dissertations

With the rapid growth of Decentralized Finance (DeFi), the challenge of Maximum Extractable Value (MEV) has become increasingly significant-particularly on Ethereum. MEV allows malicious actors to manipulate transaction order within blocks, enabling exploitative strategies such as frontrunning and sandwich attacks. In response, recent research has proposed encrypted mempools, which conceal trans- action content until after ordering is finalized, thereby reducing the exploitable surface for MEV. This thesis investigates encrypted mempool, specifically the Shutter protocol, a threshold encryption-based approach designed to mitigate MEV by hiding transac- tion contents during the mempool phase. We analyze its core architecture, under- lying cryptographic mechanisms, …

Towards The Wearable Cardiorespiratory Sensors For Aerospace Applications, Chandan Sheikder

Journal of Aviation/Aerospace Education & Research

In safety-critical aviation operations, adaptive Human-Machine Interfaces (HMI) rely on accurate physiological monitoring to mitigate cognitive overload. While cardiorespiratory sensors are promising for real-time cognitive workload assessment, existing studies lack rigorous validation of consumer-grade devices in high-stress aviation contexts and fail to address measurement uncertainty propagation. This study evaluates the Zephyr BioHarness, a commercial wearable sensor, against clinical-grade equipment during arithmetic tasks simulating aviation cognitive demands. By integrating a neuro-fuzzy system with uncertainty propagation methods, we quantify the reliability of heart rate (HR) and breathing rate (BR) metrics for workload estimation. Results demonstrate moderate HR accuracy (RMSE: 4.85 bpm, CC: …

Identifying Individual Factors Which Impact Student Learning In A Desktop Flight Training Simulator, Tim Ryley, Guido Carim Junior, James Mcbroom, Elvira Marques, Chris Campbell, Nnenna Ike

Journal of Aviation/Aerospace Education & Research

With expected global growth in air transport demand and forecasted shortage of pilots, there is a need for faster and cheaper flight training. A range of protocols was used to assess factors such as student’s emotional state, adaptive performance, and situational awareness as possible predictors of flight performance based on the influence of these factors on student flight performance conducted using a Personal Computer-based Aviation Training Devices (PCATD). Factor analysis and regression models were used to identify how these factors related to student performance during a visual flight conducted using a desktop simulator and our findings demonstrated some influence of …

The State Of Uas Operations At Airports, A Perspective From Airport Managers, Damon Lercel, Sarah M. Hubbard

Journal of Aviation/Aerospace Education & Research

As the number of Uncrewed Aircraft Systems (UAS) operating in our National Airspace System (NAS) increases, so do UAS operations near or at an airport. The accelerating technology in Advanced Air Mobility (AAM) and related business opportunities will only further increase UAS operations at airports. This continued growth in new UAS technologies and applications introduces new hazards and risks to the airport environment. This proliferation of UAS highlights the importance of airports developing a robust Safety Management System (SMS) that includes specific UAS risk mitigations. There is currently little empirical data regarding UAS traffic around airports and there is no …

Vibration-Based Detection For The Monitoring Of Neonatal Bcpap Respiratory Support To Minimize Duration Of Disconnections, Kaitlyn G. Calabresi, Meera R. Bhat, Lavinia L. Kong, Eli J. Foster, Jonathan Wang, Sangeeta Koilada, Angela Mak, Aastha Kapadia, Niam Mohseni, W. Keith Leung, Suneetha Desiraju, Constanza Miranda

School of Medicine Faculty Publications

Bubble continuous positive airway pressure (bCPAP) is a minimally invasive respiratory support for neonates experiencing respiratory distress syndrome (RDS). It exerts continuous, oscillatory air pressure to encourage lung function and development. Neonates’ movement may cause disconnections at the nasal interface. These disconnections are characterized by the cessation of bubbling at the bCPAP respiratory circuit output and frequently go unnoticed until hypoxia develops. Common Neonatal Intensive Care Unit (NICU) bCPAP systems lack a built-in alarm or accessory device to monitor for disconnections. As a result, nursing personnel must exercise extreme caution utilizing current bCPAP procedure. If a neonate is disconnected, it …

Advancing Eye-Gaze Writing Systems With Computer Vision, And Dynamic Text Suggestions, Walid Abdallah Shobaki

Theses and Dissertations

Eye gaze writing, a novel interaction modality, has the potential to revolutionize communication for individuals with limited mobility. In our research, we investigated the deep learning algorithms efficiency for real-time eye gaze writing. We have compared many algorithms' performance in many computer vision areas, such as object detection in which we used first YOLOv8, the second algorithm SSD, and the third algorithm is Faster R-CNN, the second computer vision area is the image segmentation in which we used DeepLab and U-Net, and the last computer vision area is self-supervised learning we have used SimCLR algorithm. By evaluating these models on …

Towards Leveraging Social Media Data For Fostering Collaborations Among Non-Profits, Monazil Chowdhury

LSU Doctoral Dissertations

Nonprofit organizations serve a crucial role in tackling a wide range of significant social, environmental, and economic issues. But it is often hard to get a clear picture of their work because their information is spread out and it is difficult to see how they are collaborating. To address this issue we developed a web-based tool to collect scattered data—from a variety of sources, such as the IRS, social media, and the Census, into one easy-to-use resource. The tool begins by taking IRS records and geocoding each nonprofit’s physical address With its coordinates. It then retrieves census tract information from …

Aeroponic System Optimization For Butterhead Lettuce Growth And Future Sustainability Using Flow Blurring Atomization: An Overview, Taylor J. Johnson

Beyond: Undergraduate Research Journal

The global population has grown by 6 billion people over the last century and is trending toward 9.7 billion people by the year 2050. Agriculture accounts for 70% of global fresh water usage. Technology must be developed to accommodate the increase of food production demanded by the growing global population and the subsequent increase in water usage. Aeroponic technology is a water-efficient vertical farming technology that can reduce water usage by 90% by suspending plant roots in air within a controlled chamber and supplying atomized droplets of a water-nutrient solution directly to the roots.

This study simultaneously tests six droplet …

Design & Development Of Efficient Biometric Authentication And Key Agreement Schemes For Wireless Body Area Network, Aarthi S

Theses and Dissertations

Wireless Body Area Networks (WBANs) play a vital role in continuous health monitoring, where sensitive biometric and physiological data must be protected from privacy breaches and emerging quantum-based threats. Conventional security mechanisms are often inadequate due to resource constraints, scalability issues, and vulnerability to advanced attacks. To address these challenges, this research proposes a lightweight, scalable, and future-proof security framework tailored for WBAN applications, focusing on secure communication, privacy preservation, and quantum resilience.

An anonymous Certificate-Based Signcryption–Mutual Authentication and Key Agreement (CBS-MAKE) protocol is introduced to secure extra-body communications while ensuring patient anonymity. The protocol integrates Elliptic Curve Cryptography with …

Isolation Enhancement Based On Tm010 And Te30 Mode Characteristics In A Patch Antennas Using Genetic Algorithm Optimization For Ku-Band Applications, Muddineni Raveendra, U. Saravanakumar, P. Padmaloshani, P. Saam Prasanth Dheeraj, Anand Anbalagan, R. Sreelakshmy

Electrical and Computer Engineering Faculty Publications and Presentations

This paper proposes a novel technique to enhance isolation in rectangular patch antennas by leveraging the mode characteristics of TM010 and TE30 to achieve better than −40 dB between the transmitter and receiver with dual‐polarization features. The primary innovation of this work lies in achieving significant isolation enhancement solely by combining two resonant modes with orthogonal polarizations, without incorporating any additional design elements such as parasitic components or decoupling structures. To validate the isolation enhancement based on these mode characteristics, a pair of rectangular transmitter and receiver patch antennas was designed to operate in the frequency range from 14 to …

Conceptualizing The Research Cycle For The Field Of Materials Science And Engineering, Jennifer L.W. Carter

Faculty Scholarship

Abstract: Early-career materials researchers often receive guidance from their individual advisors on best practices for conducting research, but the materials science community lacks an explicit model of the research process. As a result, the lived experience of an individual researcher can be quite different from their peers since they may be exposed to a different unique set of implicit research steps. In this article, we translate an existing research heuristic from other fields and make explicit the steps, methodologies, and strategies materials science engineering researchers utilize to advance our collective materials science knowledge. This newly proposed research cycle can improve …