Digital Commons Network^™

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 …

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 …

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 …

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 …

Real-Time Predictive Analytics For Healthcare Monitoring And Terrain Classification Using Data Streaming And Online Learning, Ayemon Baraka

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis develops a scalable, real-time predictive framework aimed at improving outcomes in healthcare monitoring and gait classification. Specifically, it addresses two primary applications: early detection of cardiovascular events, myocardial infarction (MI) and arrhythmia, through continuous analysis of ECG data streams; and adaptive terrain classification from gait data. Utilizing data streaming technologies such as Apache Kafka and Apache Spark, coupled with machine learning models, this framework enables near real-time and precise predictions from high-throughput, real-time data. Furthermore, the integration of online learning frameworks, including the River API and TensorFlow I/O, allows for continuous model adaptation, enhancing the system’s responsiveness and …

Biological Reduction Of Mixed Oxyanions In Wastewater Brine, Katherine J. Earp

UNLV Theses, Dissertations, Professional Papers, and Capstones

Treatment of contaminated brine water is an area of active research spurred by the use of advanced treatment technologies, such as membrane separation, reverse osmosis, ion exchange, etc. for water reuse and recycling, which has become critical due to the impact of climate change on water resources throughout the globe. Biological reduction of harmful organic and inorganic pollutants in water has been demonstrated as an effective method for water and wastewater treatment and would be a potential technology for brine treatment. However, biodegradation of contaminants in high salinity waters is challenging because most microbial communities cannot survive brine environments. The …

Uptake Of Contaminants Of Emerging Concerns (Cecs) By Plants Irrigated With Recycled Waters, Abid Hussain

UNLV Theses, Dissertations, Professional Papers, and Capstones

The increasing demand for water in arid and semi-arid regions necessitates the use of recycled water (RW) for irrigation. RW is a viable alternative to conventional irrigation water at most locations, but it can be a major route for contaminants of emerging concerns (CECs) to be taken up by the tissues of food crops, thereby leading to their subsequent entry into the food chain. CECs include pharmaceuticals, personal care products, and industrial chemicals that are generally present at low concentrations in environmental waters, hence their common designation as trace organic compounds (TOrCs), and CECs also include microbiological constituents such as …

Alteration Of Peripheral Cytokines In Alzheimer’S Disease, Zhengshi Yang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with the clinical symptoms of gradual cognitive decline and memory loss. Biologically, abnormal accumulation of Aβ (Aβ) plaque and tau tangles in the brain are the core pathological hallmarks in AD. Although inflammatory response is not specific to AD, emerging evidence suggests that the disrupted innate immune system within the central nervous system, particularly microglial activation, might act as the bridge linking Aβ aggregation to pathological phosphorylation and aggregation of tau. The inflammatory response was suggested to initially have a neuroprotective role of attempting to clear Aβ plaques, and then become neurotoxic …

Delineating Genetic Influences On Neurodegenerative Disorders And Infectious Diseases Through Advanced Computational Methods, Xiaowei Zhuang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Genetics plays a critical role in understanding the molecular mechanisms underlying neurodegenerative disorders and pathogen evolution in infectious diseases. For example, identifying genetic variants associated with a disease phenotype uncovers functional pathways that could lead to potential drug targets and therapeutic interventions. In addition, tracking the genetic evolution of pathogens enables early detection and warning of infectious disease outbreaks. In both applications, given the large amount of genetic data, advanced computational methods, including longitudinal and multivariate models, could significantly boost the statistical power and capture interrelationships among traits, environmental factors and genetic influences. This dissertation focuses on four applications of …

Assembly And Characterization Of 10 Cm × 10 Cm Cold Atmospheric Pressure Plasma Device, Sumona S. Islam

Boise State University Theses and Dissertations

The primary purpose of this thesis is to assemble, demonstrate, and characterize a Cold Atmospheric Pressure dielectric barrier discharge plasma array of large active plasma discharge region (10 cm × 10 cm). The array is fabricated using the Low Temperature Co-Fired Ceramic (LTCC) dielectric material system and silver paste in printing electrodes. It is important to find the optimal operating parameters of the device to achieve uniform emission and to achieve the best response out of the device, which is the main focus of this thesis. The device is assembled from 43 linear discharge elements. Several I-V sweep measurements, capacitance …

The Waterbug: Adaptive Paddle Board Frame, Remy James Elio Lacchia, Katie Kellum, Madeline Evenson, Shelbi Sullaway

Mechanical Engineering

People with disabilities, particularly wheelchair users, face limitations in participating in outdoor activities like paddleboarding. Central Cal Adaptive, a nonprofit organization, aims to bridge this gap by offering adapted paddleboarding experiences. However, their current paddleboard presents challenges such as portability, range of motion, stability, and safety. Our team, comprising Madeline Evenson, Remy Lacchia, Katie Kellum, and Shelbi Sullaway, has collaborated with Central Cal Adaptive to refine the existing paddleboard design. The team’s goal is to enhance the paddleboard's functionality to better cater to wheelchair users' needs, ensuring lightweight, portable, and safe features for an improved outdoor experience.

Our paddleboard concept …

Piston Crown Design, Kurt L. Lippmann, Liam T. Janssen, Alex Rangel, Larry J. Davis

Mechanical Engineering

This project investigates the effects of dimpling a piston crown, and its impact on engine combustion dynamics. Through computational methods, the effects of piston crown dimpling on flow characteristics were evaluated. Theoretical results were verified with experimental methods. Experimental methods included characterization of exhaust gas content, engine horsepower and torque, and exhaust opacity.

Modeling Instrument Design Risks In Medical Device Reprocessing, Manuel Andres Gutierrez

All Dissertations

Medical device reprocessing is an essential practice in healthcare delivery. While FDA regulations require device manufacturers to develop and validate reprocessing procedures, the increasing complexity of medical device designs and their use environments can increase the risks of inadequate reprocessing and associated device malfunctions and potential patient injury. While some design features present known difficulties for reprocessing, critical information needed to define relative risks or feature-specific parameters that increase or decrease risks of inadequate reprocessing is lacking. There is an urgent need for tools to quantify and predict reprocessing risks associated with design features used in surgical instruments.

The broad …

Investigation Of Conductive Die-Top Thermal Capacitors During Short Circuit Operation Of Silicon Carbide Devices, Youssef Abotaleb

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Silicon carbide (SiC) power devices have garnered significant attention in recent years due to their superior thermal and electrical properties compared to traditional silicon devices. However, SiC power devices suffer from severe reliability issues arising from their mechanical properties. This is because the Young's modulus of SiC is about three times larger than that of silicon, which correspondingly raises the mechanical stresses acting on the bonding structure, often leading to device failure under power shock events.

Traditional packaging materials and designs tend to constrain SiC performance, as hot-spot temperature resulting from a power shock is one of the key factors …

Not All Samples Are Created Equal: Task-Aware Informative Sampling And Adaptive Inference For Efficient Edge Ai, Rebati Gaire

School of Computing: Dissertations, Theses, and Student Research

The rapid proliferation of Internet of Things (IoT) devices has resulted in an unprecedented influx of data generated at the edge by billions of sensors. Traditional approaches relying on cloud-based processing are increasingly inadequate due to constraints in bandwidth, latency, and privacy. Edge computing has emerged as a transformative paradigm, enabling real-time data processing and decision-making by decentralizing computation to the edge. While the integration of deep learning into edge environments—termed edge intelligence—promises autonomous and personalized operations, it is hindered by challenges such as limited computational resources, energy constraints, and data redundancies.

This thesis addresses these challenges by presenting three …

Prevalence Of Autism Spectrum Characteristics In Students Taking Undergraduate Computing Courses, Rachel Michaela Mettenbrink

School of Computing: Dissertations, Theses, and Student Research

The incidence rate of autism spectrum condition (ASC) has increased significantly in recent decades, as awareness of the condition and its impacts increases amongst clinicians, parents, and the general population. Medical literature has proposed that there may be a relationship between ASC and participation in the computing field. This study tests for the prevalence of autism spectrum condition traits measured by delivering the Autism Spectrum Quotient (AQ) to a population of undergraduate computer science students. We examine the relationships between AQ scores and students taking undergraduate computer science classes, sex, socioeconomic status, and parents in the computing industry. Additionally, we …

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 …

Assessing Reproducibility Challenges In Clinical Metabolics, Darcy Lin Cochran

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Current metabolomics research is expanding to be multiplatform and interdisciplinary. Metabolomic analysis has the potential to provide detailed insight into any biological system of interest to analyze the underlying molecular mechanisms of variables like environment, disease, and genetics. Human clinical metabolomics is a major research area that is often focused on finding biomarkers or panels of biomarkers for different diseases. However, results are difficult to compare across different laboratories since the field of metabolomics has yet to widely adopt best practices for sample preparation, data acquisition and data processing, results are difficult to compare across different laboratories.

This thesis focuses …

Deep Learning Vision-Based Bridge Inspection With Resource-Constrained Unmanned Aircraft Systems, Ji Young Lee

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Bridge inspection is critical for ensuring structural integrity, extending the service life of infrastructure, and minimizing maintenance costs. As bridges age and endure increasing loads, regular inspections help detect early signs of wear, such as cracks or corrosion, that could impact safety and performance. However, traditional inspection methods are labor-intensive, requiring significant time, specialized equipment, and manual access to challenging areas, which can lead to costly disruptions. Additionally, reliance on human inspectors introduces subjectivity, with assessments varying by individual expertise. These factors highlight the inefficiencies and safety risks in current inspection practices, underscoring the need for more objective, efficient solutions. …

Sensitive Grip Mounting Surfaces For Physical Human-Robot Interaction., Branden Shay

Electronic Theses and Dissertations

As the development of robotics becomes ever increasingly present in our society, the need for studying how humans and robots interact with each other becomes more of a necessity to be properly integrated in the changing world around us. In this thesis, we undertake the study and development of how to create a tactile human-robot operator interface to guide a robot perform a physical task. The implementation of tactile interfaces such as SkinCell sensor arrays emulating skin, and of a robotic handlebar fitted with tactile sensors are critical examples of the challenges that come with mounting and packaging such sensors …

Investigating The Contribution Of First-Order Streams To Floods In Downstream Water Bodies On The Central Appalachian Plateau., Luke Ott

Electronic Theses and Dissertations

Flash floods are the costliest natural disaster in Appalachia. The goal of this study is to better understand flood response in headwater streams and the role of these systems in the generation of downstream floods. We applied a process-based hydrologic model using data from the Robinson Forest environmental monitoring network to estimate the contribution of headwaters to downstream floods. We then used the model to understand the effects of landscape disturbance in headwaters on downstream floods. Finally, we developed empirical hydrologic models to identify useful data for predicting downstream peak flood discharge. Results indicate that headwaters in our study catchment …

Learning-Based Feature Identification For Rendezvous And Capture Of Non-Cooperative Space Objects, Trupti Mahendrakar

Theses and Dissertations

In recent years, On-Orbit Servicing (OOS) and Active Debris Removal (ADR) have attracted increasing interest due to growing concerns about space debris. This debris poses a significant risk to spacecraft, as collisions can catastrophically end missions and potentially trigger a cascading chain reaction of more debris. Space debris ranges from tiny paint chips to large non-functional spacecraft and even launch vehicle components. One way to mitigate the formation of additional space debris is to reduce the total number of large non-cooperative resident space objects present in operational orbits. This can be achieved through two approaches: de-orbiting these objects as part …

Demonstrating Feasibility Of Ultrasound-Sensitive Microbubbles Delivery To Treat Disruptions In The Blood Brain Barrier Endothelium, Rubens Jourdain

Theses and Dissertations

Vascular cognitive impairment and dementia (VCID) is one of the main causes of dementia. VCID is caused by age and other genetic factors that lead to disruptions in the blood brain barrier (BBB) and allow blood components to enter the brain. The currently available treatments of VCID include opening the BBB with high-frequency-ultrasound to deliver drugs to the brain. However, this only treats the already developed disease. Consequently, we developed a new drug delivery system whose goal is to restore the brain capillary endothelial cells (BCEC) lining the blood vessel. The objective of this study was to demonstrate the feasibility …

Breaking The Procrastination Barrier, Bianca Ebanks

Theses and Dissertations

Procrastination is a common barrier to productivity, impacting individuals' ability to achieve goals, especially in academic and professional settings. This study investigates a mixed-methods online intervention combining Behavioral Analysis (BA) principles with mindfulness exercises to reduce procrastination. The aim was to develop a human-centered, personalized intervention that utilizes behavioral reminders and mindfulness techniques to address procrastination in 43 participants. Participants' procrastination levels were assessed using the Irrational Procrastination Scale (IPS), and interventions were tailored based on individual procrastination tendencies. Reminders were sent via email or text, with timing adjusted to participants’ specific needs. The intervention also included mindfulness exercises designed …

Populations Digitally Excluded From Education: Issues, Factors, Contributions And Actions For Policy, Practice And Research In A Post-Pandemic Era, Don Passey, Jean Gabin Ntebutse, Manal Yazbak Abu Ahmad, Janet Cochrane, Simon Collin, Asmaa Ganayem, Elizabeth Langran, Sadaqat Mulla, Ma. Mercedes T. Rodrigo, Toshinori Saito, Miri Shonfeld, Saunand Somasi

Department of Information Systems & Computer Science Faculty Publications

This conceptual paper draws on a wide range of research and policy literature, providing a contemporary view of issues, factors and practices that affect education for digitally excluded populations. Concern for how education for digitally excluded populations can be supported is focal to this paper, with different sections offering key related perspectives. From an analysis of issues, factors and practices, actions for policy, practice and research are identified. Given a key finding that power issues can have major effects on plans, implementation processes and outcomes when addressing needs of education for digitally excluded populations, the paper concludes by offering frameworks …

Study Of Temperature Effects Of Glucose And Microwave Dielectric Dispersion Model, Ethan Grant Boone

Theses and Dissertations

In this study, the temperature effect of dielectric properties in various aqueous solutions containing glucose are examined. A design for a new testing chamber is introduced to provide improved conditions for testing to ensure accurate and precise measurements. A N-SMA Adaptor is used when obtaining dielectric characteristics of glucose solutions ranging 100-300mg/dl. Dielectric parameters are obtained adopting a modified Debye dispersion model. MATLAB is used to confirm coaxial dimensions are suitable fabrication designs using fixed dielectric parameters of air and water. Simulations and design models were implemented utilizing ANSYS High Frequency Structure Simulator and 3-D Modeler software to develop the …

3d Bioprinted Coaxial Tubule Optimization For Human Aortic Endothelial Cell Growth, Ilse Gabriela Perez Garcia

Theses and Dissertations

This paper introduces a research study of printing parameter optimization of extruded, cell-laden, 3D bioprinted coaxial tubules, as well as cell interaction observations. Optimization of printing parameters seeks to reduce variability of the tubules’ inner and outer diameters. The tubules were manufactured from a 0.4% Collagen I - 1.6% NaC6H7O6 (Sodium Alginate) bioink, that reaches gelation through interaction with a 3.2% CaCl2 (Calcium Chloride) solution. The bioinks were extruded through a dual syringe pump mechanism connected to a coaxial nozzle, which is mounted on an adapted 3D FDM (Fused Deposition …

Physicochemical Property Effects On Immune Modulating Polymeric Nanoparticles: Potential Applications In Spinal Cord Injury, Daniel J. Kolpek, Jaechang Kim, Hisham Mohammed, John C. Gensel, Jonghyuck Park

Markey Cancer Center Faculty Publications

Nanoparticles (NPs) offer promising potential as therapeutic agents for inflammation-related diseases, owing to their capabilities in drug delivery and immune modulation. In preclinical studies focusing on spinal cord injury (SCI), polymeric NPs have demonstrated the ability to reprogram innate immune cells. This reprogramming results in redirecting immune cells away from the injury site, downregulating pro-inflammatory signaling, and promoting a regenerative environment post-injury. However, to fully understand the mechanisms driving these effects and maximize therapeutic efficacy, it is crucial to assess NP interactions with innate immune cells. This review examines how the physicochemical properties of polymeric NPs influence their modulation of …

Assessing Khumbu Region Glaciers Mass Balance Change Using Geospatial Techniques From 2012 To 2024, Yashvi Jagatbhai Shah

Electronic Theses, Projects, and Dissertations

The glaciers in the Hindu Kush Himalaya are critical for sustaining the water supply of South Asia's major rivers, upon which over 230 million people, both in the mountainous regions and lowland areas, depend. Climate change is driving rapid glaciers melt near the summit of Mount Everest, located at an elevation of approximately 7,906 meters (25,938 feet). This has resulted in glacier thinning occurring up to 80 times faster than the original ice formation. However, due to their disposition in a complex topographic setting and inaccessible terrain, continuous glacier observations pose significant challenges.

This study evaluated the mass balance of …