Engineering Commons^™

Enhancing The Utility Of Unmanned Autonomous Vehicles (Uavs) With Model-Based Systems Engineering (Mbse) And Modular Open Systems Approach (Mosa), Aimee Barraza

Open Access Theses & Dissertations

Unmanned Autonomous Vehicles (UAVs) have emerged as versatile tools with significant implications across various industries, particularly in defense. The technological advancements in UAVs have revolutionized military operations, surveillance, and reconnaissance capabilities. However, there exist challenges such as environmental factors affecting sensor and flight performance, limited battery life restricting flight durations, and payload capacity constraints impeding task efficiency.This paper delves into the importance of UAVs in different industries, specifically focusing on their pivotal role in the Department of Defense. It emphasizes the necessity of technological upgrades to overcome current challenges and proposes the adoption of a Modular and Open System Approach …

Myofibroblast Targeted Liposomes For The Treatment Of Skin Fibrosis, Elfa Beaven

Open Access Theses & Dissertations

Continuous overactivation of myofibroblasts leads to excessive deposition of profibrotic proteins, which in turn causes tissue stiffness and, ultimately, organ failure. One of those proteins, Cadherin-11 (CDH11), is reported to be overexpressed in the tissue of fibrotic skin, specifically on myofibroblasts. Similarly, chronic inflammation drives fibrosis progression in autoimmune-related illnesses like systemic sclerosis (SSc). Therefore, it is hypothesized that CDH11 could be a target for cell-specific delivery of antifibrotic therapies to fibrotic skin tissue. Here, a CDH11 peptide conjugated liposome loaded with Tofacitinib, a JAK inhibitor, was developed to understand the potential of targeted therapies to treat skin fibrosis. The …

Geotechnical Aspects Of Extraterrestrial Regolith Simulants, Jesus Baca

Open Access Theses & Dissertations

Geotechnical engineering has been crucial to the success of construction projects on Earth, and now it is time to extend this expertise to other celestial bodies. As NASA planned the Apollo missions, geotechnical engineers conducted extensive studies to understand the properties of lunar soil, using analogs like volcanic ash and other terrestrial materials to simulate the moon's surface. Nevertheless, it was not until the inception of the year 1968 that the Surveyor landers were able to give the first actual estimates of the moon soil geotechnical characteristics such as bearing capacity, void ratio, etc. With the development of more refined …

Developing A Bioengineered Nanoparticle For Improving Oral Absorption Of Iron Supplements., Mila Biswas

Open Access Theses & Dissertations

Iron deficiency (ID) and iron deficiency anemia (IDA) are widespread nutritional issues, affecting millions globally. Conventional iron supplements often suffer from low absorption rates and gastrointestinal side effects. We investigated β-glucan derivatives as potential carriers to enhance iron absorption and mitigate these drawbacks. This study explored a novel β-glucan-based carrier system loaded with ferrous sulfate heptahydrate. In-vitro studies demonstrated sustained iron stability for over six hours in simulated gastric fluids due to the carrier's affinity for stomach mucin. Particle size analysis and scanning electron microscopy (SEM) images confirmed this specific binding. Additionally, drug release studies revealed a pH-dependent release profile, …

Chipless 3d Microfluidic Rf Sensing, Sheikh Dobir Hossain

Open Access Theses & Dissertations

Effective management of the cold chain is essential to uphold the quality and safety of products vulnerability to physical factors like temperature, humidity, pressure, etc., including perishable foods, pharmaceuticals, and vaccines. Chipless Radio Frequency Identification (RFID) sensors have become increasingly favored as a viable technology for tracking, inventory, and sensing industries due to their wireless and non-line of sight (NLOS) situations, straightforward fabrication, cost efficiency, and adaptability to challenging environmental conditions. However, there is still a need for advancements in RFID sensors to make them promise for cold chain applications. Integration of flexibility and non-volatile memory into the existing RFID …

Fatigue Endurance Of Alsi10mg Post Hip Heat Treatment With High Duration Thermal Aging, William Venable Newcomb

Open Access Theses & Dissertations

AlSi10Mg is one of the cornerstones of additive manufacturing (AM), with its materialproperties and relatively low cost making it extremely popular as an AM metal choice, specifically using Laser Powder Bed Fusion (LPBF). Many publications have focused on this material, studying tensile strength, fatigue, heat treatments, and more. However, an area that requires further study is the effect of aging on the materials fatigue properties, with this study examining an industry standard heat treatment of Hot Isostatic Pressing (HIP). Using studies that have already been completed, AlSi10Mg was fatigue tested at near 100% UTS and 75% yield strength after HIP …

Enhanced Redox Storage And Diverse Intercalation In Layered Metal Organic Frameworks With A Staggered Stacking Mode, Satya Prakash Suman

Open Access Theses & Dissertations

Two-dimensional metal organic frameworks (2D MOFs) with honeycomb-like porous sheets are of growing interest for applications in electrochemical energy storage and electrocatalysis. Notably, 2D MOFs that host their porous sheets in eclipsed or slipped-parallel stacking modes possess continuous one-dimensional pores (1D) and have been widely studied. In contrast, related 2D MOFs with a staggered stacking mode have reduced porosity, are relatively rare, and are largely unexplored for applications. Here we report 2-fold enhanced redox storage and intercalation of diverse ions in a staggered-stacked, nonporous 2D MOF over its eclipsed-stacked, porous counterpart. Interestingly, both MOFs, despite undergoing similar ligand-centered redox processes, …

Basic Safety Message Generation Through A Video-Based Analytics For Potential Safety Application, Abyad Enan

All Theses

With the advancement of modern artificial intelligence techniques, computer vision can play a vital role in enhancing roadway safety by reducing the risk of imminent collisions. To do so, a vision-based safety application is required, where a roadside camera can monitor the roadway traffic and predict potential risks of crashes in real-time. If any risky situation or behavior is observed that may lead to a crash, then a safety application can send warnings to the vehicles at risk. For vision-based safety applications on a roadway section, it is important to accurately monitor each vehicle’s location, speed, acceleration, heading direction, etc. …

Pressureless Sintering Of Sic - Oxide Multiphase Ceramics For Protective Coating Applications, Reilly Boros

All Theses

For hydrogen-fueled combustion, there exists a demand to improve coating materials that are capable of protecting SiC_f/SiC CMC turbine material. Promising coating materials must be able to shield from harsh oxidation while working at extremely high temperatures. The work presented in this thesis aims to expand the understanding of two promising material systems for integrated environmental barrier coating (EBC) – thermal barrier coatings (TBC) by fabricating bulk composite ceramic samples and performing characterization to further understand their sintering behaviors. In this study, a processing procedure to consistently produce dense composite ceramics of PDC SiC – Y₂Si …

Collision Hazard Prevention And Notification For Construction Worker Safety Using Audio Surveillance, Kehinde Elelu

All Dissertations

The construction industry faces significant safety challenges, with collision hazards ranking as the second highest cause of annual fatalities and injuries in the United States, as reported by the Occupational Safety and Health Administration (OSHA). Current collision detection methods predominantly rely on proximity technologies, which necessitate costly and complex installations on each construction equipment piece. Furthermore, auditory situational awareness declines among workers due to hearing loss and intricate construction noises, which further heightens collision risks. This research introduces an innovative, low-cost, audio-based collision prevention technology aimed at enhancing auditory situational awareness for construction workers exposed to high noise levels. The …

Sustainable And User-Driven Scope Development Framework For Engineering Design Services Of Transportation Infrastructure Projects, Ahmad Zaki Ghafari

All Dissertations

Rapid economic growth has led to a significant increase in transportation demands, exerting unprecedented pressure on infrastructure systems in the United States. State transportation agencies play a vital role in maintaining and developing transportation infrastructure networks within their regions. State transportation agencies face immense pressure from federal and state governments, elected officials, and the public to deliver projects efficiently and within budget. State transportation agencies rely on professional consultants for engineering design services. Engineering design services for transportation infrastructure projects are delayed due to incomplete inaccurate scope. For state Department of Transportation (DOTs), a streamlined scope development process is essential …

Magnetic Resonance Imaging Trackable Pathology-Triggered Polymersomes Toward Enzyme Replacement Theranostics For Gm1 Gangliosidosis, Dorian Foster

All Dissertations

This dissertation investigates the development and optimization of pathology-responsive polymersomes for simultaneous enhanced magnetic resonance imaging (MRI) and enzyme replacement therapy (ERT) in the treatment of GM1 gangliosidosis (GM1). While therapeutic strategies exist for similar, non-neuropathic lysosomal storage disorders, implementation towards GM1 faces significant challenges due to the blood-brain barrier.

Herein, we developed and characterized a range of low molecular weight hyaluronic acid-b-polylactic acid (HA-PLA) polymersomes (PSs) capable of encapsulating therapeutic enzymes in their hydrophilic core. These polymersomes exhibit pathophysiology-triggered responsiveness, degrading in the presence of acidic conditions, which is characteristic of lysosomes, and enzymes such as hexosaminidase A, which …

Performance Evaluation Of Bio-Oil And High Rubber Content Modified Asphalt: More Effective Waste Utilization, Zihao Ju, Dongdong Ge, Songtao Lv, Dongzhao Jin, Yanhua Xue, Jianping Xian, Wenhui Zhang

Michigan Tech Publications

In this study, the bio-oil was used to reduce the viscosity and preparation temperature of high content of rubber-modified asphalt. The high rubber content modified bio-asphalt (RMBA) was prepared, the rubber and bio-oil contents were 20 %-30 % and 5 %-15 % (mass ratio of neat asphalt), respectively. The viscosity, temperature sweep (TS), frequency sweep (FS), multi-stress creep recovery (MSCR), and bending beam rheometer (BBR) tests were performed to assess the properties of RMBA. The Fourier Transform infrared spectroscopy (FTIR), Fluorescence microscopy (FM), and Scanning electron microscope (SEM) tests were conducted to explore the microscopic morphology of RMBA. Besides, the …

Low-Cost Vehicle Controller Testing System, Kevin R. Jung

Electrical Engineering

This project aims to create a system to facilitate easier evaluation of PCBs designed for low-voltage vehicle applications with an emphasis on accessibility for student teams in collegiate design series' such as Formula SAE. Student teams or smaller vehicle electronics manufacturers often need to verify designs and validate functionality during both development and manufacturing. An inexpensive, small, and portable, yet capable, system for taking measurements and simulating inputs would allow designers to put their boards into vehicle-representative conditions and environments without needing to connect to actual vehicle hardware. Additionally, while systems exist off-the-shelf that could fulfill the requirements needed by …

Debtor Eligibility Prediction Using Deep Learning With Chatbot-Based Testing, Reski Noviania, Enny Itje Sela, Luther Alexander Latumakulita, Steven R. Sentinuwo

Knowledge Engineering and Data Science

Predicting debtor eligibility is essential for effective risk management and minimizing lousy credit risks. However, financial institutions face challenges such as imbalanced data, inefficient feature selection, and limited user accessibility. This study combines Recursive Feature Elimination (RFE) and Deep Learning (DL) to improve prediction accuracy. It integrates a chatbot interface for user-friendly testing. RFE effectively identifies critical features, while the DL model achieves a validation accuracy of 97.62%, surpassing previous studies with less comprehensive methodologies. The chatbot's novel design not only ensures accessibility but also enhances user engagement through flexible input options, such as approximate values, enabling non experts to …

Optimal Strategy For Handling Unbalanced Medical Datasets: Performance Evaluation Of K-Nn Algorithm Using Sampling Techniques, Yulita Salim, Aulia Putri Utami, Abdul Rachman Manga, Huzain Azis, Fadhila Tangguh Admojo

Knowledge Engineering and Data Science

This study addresses the critical role of medical image classification in enhancing healthcare effectiveness and tackling the challenges of imbalanced medical datasets. It focuses on optimizing classification performance by integrating Canny edge detection for segmentation and Hu-moment feature extraction and applying oversampling and undersampling techniques. Five diverse medical datasets were utilized, covering Alzheimer’s and Parkinson’s diseases, COVID-19, brain tumours, and lung cancer. The K-Nearest Neighbors (K-NN) algorithm was implemented to enhance classification accuracy, aiming to develop a more robust framework for medical image analysis. The evaluation, conducted using cross-validation, demonstrated notable improvements in key metrics. Specifically, oversampling significantly enhanced lung …

A Hierarchical Density-Based Spatial Clustering Of Applications With Noise (Hdbscan) Approach For Identifying Potential Villages In Buleleng Regency, Dina Nur Amalina, Achmad Fauzan

Knowledge Engineering and Data Science

Buleleng Regency, located in Bali Province, possesses diverse village potential, including agricultural production and tourist attractions. However, this potential has not been fully optimized. Therefore, it is important to enhance village potential by clustering villages based on their specific characteristics to identify and prioritize those requiring special attention. This approach aims to promote equitable village development and reduce poverty levels. This study clusters villages in Buleleng Regency based on their potential using the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) method. The data utilized in this study comprises village potential data obtained from the Buleleng Regency Statistics Office …

Experimental Evaluation Of A Recrosslinkable Co2-Resistant Micro-Sized Preformed Particle Gel For Co2 Sweep Efficiency Improvement In Reservoirs With Super-K Channels, Adel Alotibi, Tao Song, Ali Al Brahim, Baojun Bai, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

A recross linkable CO₂-resistant branched preformed particle gel (CO₂-BRPPG) was developed for controlling CO₂ injection conformance, particularly in reservoirs with super-permeable channels. Previous work focused on a millimeter-sized CO₂-BRPPG in open fractures, but its performance in high-permeability channels with pore throat networks remained unexplored. This study used a sand pack model to evaluate a micro-sized CO₂-BRPPG under varying conditions of salinity, gel concentration, and pH. at ambient conditions, the equilibrium swelling ratio (ESR) of the gel reached 76 times its original size. This ratio decreased with increasing salinity but remained stable …

Transmission Main Construction Management - An Assessment Of Project Tracking During Transition To A Cloud Based System, Martin C. Munger

LSU New Orleans Theses and Dissertations

A massive $2B settlement between the Federal Government and the City of New Orleans to remediate the damage to municipal infrastructure from Hurricane Katrina and the failed USACE levee system required the repair of roughly 400 of 1600 miles of roadways in New Orleans. The mandated repairs included many subsurface utilities below those roads. Traditional engineering construction project management practices proved inadequate to manage such a massive undertaking on the strict timelines mandated by FEMA funding. Unprecedented volumes of work for the engineering and construction industries and the government agencies tasked with performing the work from design through construction revealed …

A Talking Cart, Abdullah Bin Naeem

LSU New Orleans Theses and Dissertations

This research investigates the development of a robust AI-powered detection and tracking engine aimed at revolutionizing the retail checkout experience. The foundation of this work is a comprehensive exploration of state-of-the-art Computer Vision methodologies, particularly focusing on object detection, segmentation, and tracking. The study employs a modular pipeline that integrates advanced visual recognition algorithms with a robust data processing framework.

Key to this work is the construction of a synthetic dataset using Unity3D, enabling the generation of high-quality annotated data that mirrors real-world retail scenarios. This approach addresses the challenge of insufficient labeled datasets by simulating diverse and cluttered shopping …

Building Energy Management: A Data-Driven Approach Using Clustering And Load Forecasting, Aviral Kandel

LSU New Orleans Theses and Dissertations

The increase of smart meters in the grid has led to the generation of a vast amount of high dimensional energy data with improving temporal resolution. During analysis, relying on short samples like a day or week of data, could lead to wrong conclusion due to seasonal dynamics and customer behavior variations. To effectively utilize the vast amount of information, it must be compressed into a low-dimensional representation. This thesis explores the state-of-the-art dimensionality reduction techniques for a high-dimensional, non-linear energy dataset and proposes a novel deep learning based method to address the limitation of existing approaches. The proposed method …

Implementation Of Non-Linear Filtering Techniques For Object Tracking, Shaswat Koirala

LSU New Orleans Theses and Dissertations

No abstract provided.

Physics-Informed Deep Learning For Pilot Parameter Estimation And Pilot-Induced Oscillation Characterization, Stephen A. Brutch

Doctoral Dissertations and Master's Theses

This thesis investigates the issue of loss-of-control in flight which is a driving contributor to fatal aviation accidents. The two main contributors tackled in this research are human pilot error and categories of pilot-induced-oscillations. The primary objective is to develop models that can capture the mathematical parameters that relate to human pilot control under the widely used McRuer Mathematical pilot model. The goal is that if the mathematical parameters that relate to human pilot control can be monitored during flight then the pilot’s input to the control system and pilot-induced-oscillations (PIO) can be monitored during flight to avoid loss-of-control. This …

Assessing General Propulsion Architectures For Fast Transit Times To Mars For Crewed Missions, Vivek Bhatt

Doctoral Dissertations and Master's Theses

As NASA and commercial contractors, such as SpaceX, continue to develop their programs with Artemis and Starship, respectively, it is becoming more and more apparent that the program developments are ultimately for finding a way to put humans onto Mars. However, when we approach the current timeline of going to Mars, it usually involves a 6-9 month one way trip. Due to this, human spaceflight to Mars becomes more dangerous as exposure to affects such as solar radiation, long exposure to low gravity fields, and isolation. These are some of the many hazards that come with interplanetary space travel for …

Manifold Learning And Undersampling Approaches For Imbalanced Class Sentiment Classification, L.M. Risman Dwi Jumansyah, Agus Mohamad Soleh, Utami Dyah Syafitri

Knowledge Engineering and Data Science

Movie reviews are crucial in determining a film's success by influencing audience decisions. Automating sentiment classification is essential for efficient public opinion analysis. However, it faces challenges such as high-dimensional data and imbalanced class distributions. This study addresses these issues by applying manifold learning techniques, Principal Component Analysis (PCA) and Laplacian Eigenmaps (LE) to reduce data complexity and undersampling strategies (Random Undersampling (RUS) and EasyEnsemble) to balance data and improve predictions for both sentiment classes. On reviews of The Raid 2: Berandal, EasyEnsemble achieved the highest average G-Mean of 0.694 using Term Frequency-Inverse Document Frequency (TF IDF) features with a …

Constructing Qur’An Recitation Classification Using Alexnet Algorithm, Harits Ar Rosyid, Dzulkifli Abdullah, Mohammed S. Alqahtani

Knowledge Engineering and Data Science

The growing demands for accurate and efficient methods in the Qur'an recitation classification highlight the limitations of existing models, particularly in assisting the memorization process. This study aims to address these challenges by implementing the AlexNet Convolutional Neural Network architecture, widely recognized for its effectiveness in image classification, to classify the Qur'an recitations using the Mel Frequency Cepstral Coefficient (MFCC) as the feature extraction method. The research involves several stages, including data collection, preprocessing (audio segmentation by verse), data augmentation, feature extraction, and classification using the AlexNet architecture, followed by performance evaluation. Key results demonstrate that the combination of MFCC …

Deep Learning Approach For Dental Anomalies X-Ray Imaging Using Yolov8, Amelia Ritahani Ismail, Md Salim Sadman Taseen

Knowledge Engineering and Data Science

Dental X-ray imaging is a critical diagnostic tool for identifying various dental anomalies. However, manual interpretation is time-consuming, prone to human error, and requires specialized expertise. Deep learning models, particularly object detection frameworks like YOLO, have demonstrated promising results in automating medical image analysis. This study aims to develop and evaluate a YOLOv8-based deep learning model for automated detection and classification of 14 dental anomaly categories, including Caries, Crowns, Fillings, Implants, and Periapical lesions. The proposed approach addresses limitations in previous YOLO versions by leveraging anchor-free detection and enhanced feature extraction for improved accuracy. The model was trained on a …

Classification Of Anxiety Levels Entering The World Of Work In Final Year Students Using The Neighbor Weighted K-Nearest Neighbor Method, Awang Hendrianto Pratomo, Muhammad Fahmi Adam, Dessyanto Boedi Prasetyo

Knowledge Engineering and Data Science

This study evaluates the accuracy of the Neighbor Weighted K-Nearest Neighbor (NWKNN) method in classifying the anxiety levels of final-year students as they prepare to enter the workforce, particularly in cases of unbalanced data distribution. The system was developed using the prototype method, and NWKNN was applied to classify anxiety levels into low, medium, and high categories. Testing using the Confusion Matrix demonstrated strong performance, achieving an accuracy of 94% based on a dataset of 1009 students, with a 90:10 ratio of training to test data. The results indicate that NWKNN effectively provides classification input values, making it a reliable …

Comparative Analysis Of Bpnn And Lvq For Sundanese Character Recognition, Haviluddin Haviluddin, Herman Santoso Pakpahan, Dinda Izmya Nurpadillah, Hario Jati Setyadi, Medi Taruk, Rayner Alfred

Knowledge Engineering and Data Science

The Sundanese script (Aksara Sunda), an essential part of Sundanese cultural heritage, has been used since the 14th century AD. However, recognizing handwritten Sundanese characters remains challenging due to variations in individual writing styles. This study compares the performance of Backpropagation Neural Network (BPNN) and Learning Vector Quantization (LVQ) for recognizing handwritten Sundanese vowel (Swara) characters. A dataset was collected from 15 individuals, each writing seven Sundanese vowel characters, which were then used for training and testing the recognition models. Experimental results show that BPNN outperforms LVQ, achieving a higher classification accuracy (95.23%), lower Mean Squared Error (MSE), and faster …

Cyclic Thermal Stability Of Native Oxide Solar Thermal Absorbers On Femnnialcr High Entropy Alloys For Energy Applications, Xiaoxue Gao

Dartmouth College Ph.D Dissertations

High entropy alloys (HEAs) are promising candidates for cost-effective high-temperature materials in high-efficiency power cycles. A potential application is in concentrated solar power (CSP) systems, where native oxides of cost-effective FeMnNiAlCr HEAs can also synergistically serve as a high-efficiency solar thermal absorber. However, the huge and repetitive temperature change of the CSP system in day-night cycles greatly challenges its thermal stability. In this thesis, we investigated the cyclic oxidation behavior of FeMnNiAlCr HEAs to improve the optical performance and thermal stability of their native oxides as a solar absorber for next-generation CSP systems. We found that the duplex oxide scale …