Balloon Model For Water Vapor Ablation Of Non-Muscular Invasive Bladder Cancer Cells, Jennifer Mussell

Dissertations and Theses

Bladder cancer has a considerable issue with multiple recurrences of tumors, and current treatments are unable to adequately address these concerns. This results in continuous surveillance. Ablation, or killing, of bladder cancer cells is often incomplete and results in a high probability of recurrence. This paper aims to evaluate a potential method of ablation using a model that simulates a bladder and what conditions are needed for optimal quality and depth penetration. This balloon model for water vapor ablation is intended to simulate bladder cancer cells and determine if this is a viable avenue for future research. A device from …

Development Of A Modular Lab Automation System With Applications To Animal And Bacteria Cell Culture, Timothy William Hartman

Dissertations and Theses

The challenges faced while executing wet lab protocols encourage the development of automation systems to come alongside human scientists. Today’s cutting-edge experiments involve complex protocols with precise measurements usually performed manually. Even simpler biological protocols can be tedious and prone to error, as was seen during the COVID-19 pandemic and society’s demand for high-volume, rapid sample analysis. Moreover, reproducibility suffers when there is excessive variability and insufficient data. Here, we leveraged the Stanford Biodesign process to develop a modular lab automation system and image analysis workflow to address challenges like these. This flagship automation platform at The University of South …

Characterizing Climatic Socio-Environmental Tipping Points In Coastal Communities: A Conceptual Framework For Research And Practice, Julie Elizabeth Shortridge, Anamaria Bukvic, Molly Mitchell, Jesse Goldstein, Tom Allen

Political Science & Geography Faculty Publications

The concept of climate tipping points in socio-environmental systems is increasingly being used to describe nonlinear climate change impacts and encourage social transformations in response to climate change. However, the processes that lead to these tipping points and their impacts are highly complex and deeply uncertain. This is due to numerous interacting environmental and societal system components, constant system evolution, and uncertainty in the relationships between events and their consequences. In the face of this complexity and uncertainty, this research presents a conceptual framework that describes systemic processes that could lead to tipping points socio-environmental systems, with a focus on …

Evaluating The Performance Of Egemaps Features In Depression Detection Using E-Daic Subsets, Joshua Turnipseed

Graduate Research Theses & Dissertations

This paper investigates the performance of the eGeMAPS (extended Geneva Minimalistic Acoustic Parameter Set) feature set in detecting depression from audio samples using subsets of the E-DAIC (Extended Distress Analysis Interview Corpus) database. With depression affecting a significant portion of the U.S. adult population, efficient detection methods are critical for timely diagnosis and treatment. Various classifiers in the WEKA machine learning toolbox are used to evaluate the performance of eGeMAPS features in distinguishing between depressed and nondepressed (D&ND) individuals. Our methodology involves creating balanced subsets of E-DAIC, extracting eGeMAPS features using openSMILE, and testing different machine learning models. This study …

Tunable Metasurface For Efficient Harmonic Generation And Amplitude Modulation, Steve Mares

Masters Theses

The manipulation of microwave signals is critical in the information and communication technology industry. This research investigates the application of time-coding techniques on metasurfaces to achieve tunable control of electromagnetic signal transmission. The integration of mounted PIN diodes facilitates dynamic modulation of signal behavior. Both passive (without PIN diodes) and active (with PIN diodes) metasurfaces were analyzed through simulations using Ansys HFSS and validated with experimental measurements. A major contribution of this work is the design and testing of active metasurfaces that leverage PIN diodes for harmonic generation and amplitude modulation. The study reveals a clear relationship between modulating signal …

Development And Evaluation Of A Retrofittable Variable Rate Applicator Controller, Ahmed Abdalla

Electronic Theses and Dissertations

The need to optimize resource utilization while increasing crop productivity is paramount. This research proposes a Low-cost Retrofittable Variable Rate Applicator Controller (VRAC) that aims to leverage the adoption of Variable Rate Technologies. The controller operates via the Raspberry Pi platform, a Global Positioning System (GPS), a stepper motor drive, and an anti-slip wheel encoder. The VRAC allows precise, on-the-fly control of variable-rate application of farming inputs. It utilizes GPS with 10 cm accuracy to pinpoint geographic coordinates in real-time. A wheel encoder measures traveling speed with a slip-resistant wheel design for precise RPM readings. The Raspberry processes the data, …

Design And Implementation Of Portable Power And Desalination Units Powered By Renewable Energy, Mo'ath A. Massad

Mechanical Engineering Theses

Freshwater scarcity is a critical global issue, especially in remote areas or areas impacted by natural disasters. Water desalination is one of the most effective methods to provide fresh water where it is needed. However, large-scale desalination plants cannot provide fresh water in the case of a natural disaster far from the plant's location. To address this, portable desalination units powered by renewable energy sources can be developed to supply potable water and power as a by-product for emergency situations. This work explored the application of different desalination methods, including reverse osmosis (RO) and electrodialysis (ED), in conjunction with renewable …

Unlv Title Iii Aanapisi & Mcnair Scholars Institute Research Journal 2024, Jesica Godinez-Paredes, Kian Hassankhan, Apia Hickman, Robin Ruth Kee, Kevin Ayala Pineda, Briana Melendez, Kalli Ramos, Saturn L. Reyes, Fabian Leija, Selena Pepe, Silva Topchyan, Celeste Ainsley, Mayra Arzate, Jessica Balistreri, Zantana Ephrem, Mirella Jasso, Karl Panou, Nichole Pelaez, Miklo Alcala, Akshay Dave, Mey Mey Heng, Michael Finkle, Janessa Montenegro, Reynafe Naol Aniga, Victor Mejia, Angelica G. Diaz, Anayeli Flores-Garibay, Kari Lee Joe Goold, Samantha Hernandez, Lianelys Cabrera Martinez, Caitlin Reynolds, Kimberly N. Usbeck, Abdulrahman Alahdal, Angelica Diaz, Willaine Mae Kahano, Raquel Jackson, Cecia Ruiz-Hernandez, Kers Ung-Watson, Yessenia Henriquez, Vanessa Marie Booth, Alexia Brown, Darlyn Magana, Bianca Navarro, Nicholas Pereira, Gia Renemae Calip, Lucky Heng, Ralph Sagun, Lucas Abreu, Alexandra Maria Acosta, Tristan Benally, Cosset Hernandez Pena, Adrian Montenegro, Cierra Paaaina-Daquioag, Nicole Torosian, Tracy Fuentes, Julissa Martinez, Medina Mcallister, Michal Newhouse-Van Vlerin, Tiria Carr, Nima Abkenar, Isabella Aceituno, Yuhan Bi, Victoria Campos, Melika Cummings, Zachary J. Johnigan, Alexis Sotolongo-Marin

McNair Journal

Journal articles based on research conducted by undergraduate students in the AANAPISI, LSAMP, and McNair Scholars Program.

Table of Contents

About AANAPISI

Dr. Chris Heavey, Interim President

Dr. Keith Rogers, Vice President for Student Affairs

Ms. Zhanna Aronov, Associate Vice President for Retention & Outreach

A Review Of Textmining Techniques: Trends, And Applications In Various Domains, Hiba J. Aleqabie, Mais Saad Sfoq, Rand Abdulwahid Albeer, Enaam Hadi Abd

Iraqi Journal for Computer Science and Mathematics

Text mining, a subfield of natural language processing (NLP), has received considerable attention in recent years due to its ability to extract valuable insights from large volumes of unstructured textual data. This review aims to provide a comprehensive evaluation of the applicability of text mining techniques across various domains and industries. The reviewstarts off with a dialogue of the basic ideas and methodologies that are concerned with textual content mining together with preprocessing, feature extraction, and machine learning algorithms. Furthermore, this survey highlights the challenges faced at some stage in implementing textual content mining strategies. Additionally, the review explores emerging …

Applications For The Groups , Where Prime Upper Than 9, Lemya Abd Alameer Hadi, Mahmood S. Fiadh, Niran Sabah Jasim, Jabbar Abed Eleiwy

Iraqi Journal for Computer Science and Mathematics

The problem of finding the cyclic decomposition (c.d.) for the groups ), where prime upper than 9 is determined in this work. Also, we compute the Artin characters (A.ch.) and Artin indicator (A.ind.) for the same groups, we obtain that after computingthe conjugacy classes, cyclic subgroups, the ordinary character table (o.ch.ta.) and the rational valued character table for each group.

Large Retail Logistics Warehouse Execution System, Michael Broughton

Graduate Research Theses & Dissertations

In this study, integrated technical solutions designed for large retail logistics (LRL) material handling equipment (MHE) were integrated with advanced technical industry trends to create a warehouse execution/warehouse control system (WES/WCS) distribution center (DC) model. This model was executed using a distributor profitability framework. The resulting process metrics, financial elements, and forecasted financial drivers within the new model were tested against a standard warehouse management system (WMS) DC model without WES or integrated WCS technical solutions. The hypothesis was that using the WES/WCS DC model in automating store functionality would result in superior cost-effective solutions for the P&L/EBITDA lines of …

Warm Unit Stand Assembly And Testing For Proton Improvement Project Ii, Christopher Allen English

Graduate Research Theses & Dissertations

The Proton Improvement Project II (PIP II), situated at Fermilab, signifies a critical advancement in the realm of high-energy physics. PIP II, a linear accelerator renovation endeavor, aspires to double the output of the existing proton beam, reinforcing Fermilab’ s position as a vanguard in this field. The proton beam's creation involves a series of high-frequency cryomodules, necessitating environmental temperature arrays of magnets and vacuum pumps henceforth described as ‘Warm Units.’ The Warm Units include design features of : 1. insertion between the cryomodules, 2. multi-stage adjustments in six degrees of freedom to ensure precise beam alignment; 3. Natural frequency …

Ai-Based Defect Detection In Aerospace Ultrasonic Signals, Rami Issac Lake

Graduate Research Theses & Dissertations

Ensuring the safety and integrity of materials and structures throughout the manufacturing cycle is a critical concern across various industries, including aerospace, automotive, oiland gas, and civil engineering. Non-Destructive Inspection (NDI) techniques allow for the examination of materials without causing damage or alteration, enabling the early detection of potential issues before materials are utilized in the field. The inspection of fuselage composites presents a particular challenge due to their complex structures, diverse materials, and differences in thickness, making defect detection a challenging yet crucial task. Moreover, defects of various types and causes can emerge across all depths of the material …

Magnetometer-Less State-Estimation Of A Mobile Robot Using Cascaded Kalman Filters, Tommy Le

Graduate Research Theses & Dissertations

Localization, or state-estimation algorithms, are one of the most important aspects inthe development of autonomous mobile robots. Typical localization requires an IMU (Inertial Measurement Unit) along with an external reference, such as GPS (Global Positioning System) for outdoor applications. In indoor applications, the GPS data is not accessible so many mobile robot implementations turn to magnetometers to provide additional pose information. However, in the context of miniaturizing robotic systems, magnetometers are not always reliable due to their proximity to motors and other electronics, causing magnetic distortion and in turn, incorrect pose information. To address this issue, this thesis proposes a …

Perceptions Of Lightboard Videos On Engineering Students' Engagement For Learning: A Mixed-Methods Case Study, Rana Sanyal

Graduate Research Theses & Dissertations

Purpose. Researchers have recommended using comprehensive visual materials in engineering courses, as visuals instill more information in students than auditory information and they have the ability to engage students more effectively than other types of content and to convey the nuances of non-verbal communication. The purpose of this study was to explore the perceptions of engineering students on incorporating technologically advanced video course materials (TAVCM) created with lightboard technology on their engagement in learning. Theoretical Framework. The theoretical framework was based upon an integrative learning environment that incorporated many theories of cognitive learning. The Cognitive Theory of Multimedia Learning (CTML) …

Genetic Engineering Of Escherichia Coli For The Production Of Riboflavin, Adeyemi Adesanwo

Graduate Research Theses & Dissertations

Riboflavin, a water-soluble vitamin B2, is essential for the growth and reproduction of living organisms. However, humans and animals lack a riboflavin synthesis pathway and must rely on diets derived from plants and microbes for this essential vitamin. To meet our needs for vitamin B2, industrial riboflavin production is currently being pursued using strains of Bacillus subtilis. The fermentation process is successful, but improvements are needed for better substrate-to-product conversion yield. To this end, it is imperative to develop alternative microbial strains for cost-effective riboflavin production.

Due to its simple growth requirement, well-understood genetic background, and widely available genetic tools, …

Active Uncertainty Representation Learning: Toward More Label Efficiency In Deep Learning, Salman Mohamadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

The primary goal of this dissertation is to investigate and improve the efficiency of deep learning algorithms, especially within computer vision problem domains, from the perspective of label-efficiency. This investigation showed that deep learning algorithms are mostly notorious for the lack of uncertainty representation. Accordingly, we aimed to develop an array of deep learning frameworks rich with uncertainty representation. These frameworks are mainly within two current pillars of machine learning, deep active learning and self-supervised learning. These frameworks include deep active ensemble sampling for efficient sample selection within deep active learning, a two-stage ensemble-based general self-training approach for existing visual …

Modeling, Control, And Fault Detection Of Energy Systems Under Limited High-Confidence Data Scenarios, Selorme K. Agbleze

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract

Modeling, Control, and Fault Detection of Energy Systems under Limited High-Confidence Data Scenarios

Selorme K. Agbleze

Utilizing process measurements for fault detection is an established approach for processes with adequate datasets. For systems with limited high-confidence data representing fault cases and some amount of low-confidence data, few quantitative hybrid techniques exist for performing fault detection. In real systems, it is time-consuming, expensive, and sometimes not productive to generate enough high-confidence data with fault characteristics of a specific process. The problem of limited high-confidence data scenarios may also arise due to process novelty, the need for new operating conditions, or …

Data-Driven Approaches For Achieving Carbon Neutrality: Predictive Models For Reducing Co2 Emissions And Enhancing Industrial Sustainability, Farzana Islam

Graduate Theses, Dissertations, and Problem Reports (ETD)

In response to the escalating challenges posed by climate change and industrial inefficiency, this thesis presents a comprehensive investigation aimed at advancing the predictive modeling of global CO2 emissions and enhancing operational efficiency in steel manufacturing through Electric Arc Furnace (EAF) temperature optimization. Leveraging a rich dataset sourced from the World Development Indicators database alongside a meticulously curated dataset specific to EAF operations, our study applies an innovative blend of econometric and machine learning techniques, including Pooled Ordinary Least Squares (Pooled OLS), Random Effects (RE), Fixed Effects (FE), and Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) models. The …

Site Specific Probable Maximum Precipitation Implications For High Hazard Dams In West Virginia, Levi Jacob Cyphers

Graduate Theses, Dissertations, and Problem Reports (ETD)

Estimates of probable maximum precipitation (PMP) are necessary for designing the maximum reservoir storage necessary to prevent dam overtopping. Recent investigations in Ohio, Virginia, and Pennsylvania imply that reducing PMP rainfall estimates in West Virginia may be appropriate; however, additional studies in this data deficient region with changing climate is necessary before any reductions are contemplated. The objective of this study was to re-evaluate PMP for the Howard Creek Dam watershed in West Virginia. The 6-hr, 10 mi² PMP was evaluated for current (2019) and projected (2100) climates and compared to the design PMP. Then, the impact of the …

An Integrated Framework For Establishing Long-Term Transportation Management Strategies Promoting Sustainable Urban Growth, M Imtiaz Rahman

Graduate Theses, Dissertations, and Problem Reports (ETD)

Urban land areas are experiencing a more rapid expansion compared to their population growth on a global scale. This phenomenon, known as urban sprawl, is characterized by low-density development in the outskirts of cities. This unplanned urban growth leads to changing urban transportation patterns, posing a threat to sustainable development. In response, government agencies implement growth management practices, with transportation management strategies playing a crucial role in achieving sustainable urban growth. However, developing effective growth management strategies is difficult because of several challenges, including limited understanding of the key influencing factors, the complex interdependencies among these factors, and the uncertainties …

Spin Wave Devices For Embedded Applications And Information Processing, Raisa Fabiha

Theses and Dissertations

Device miniaturization is a prerequisite for modern day electronics. Spintronics offers immense potential in energy efficient data storage, solid states devices, ultrafast computing and other electronic applications because of their low power consumption, non-volatile nature and unique activation mechanism. The conventional nano-antennas used for wireless communication, biomedical and wearable devices and IoT applications are limited by the traditional Harrington limit. As we attempt to miniaturize the antenna size beyond its emitted wavelength (also called “subwavelength” antenna), its gain and efficiency plummet. To overcome this challenge, the researchers have proposed magnetoelectric antennas. The ultra-thin film based magnetoelastic antennas suffer from eddy …

On The Area-Averaged Effective Sound Absorption Coefficient Of Porous Materials Excited By A Monopole, Franck Sgard, Noureddine Atalla, Olivier Robin, Alain Berry

Études primaires

The area-averaged effective sound absorption coefficient (SAC) of a rigid-backed homogeneous porous material subjected to a monopole excitation is calculated as the absorbed-to-incident sound power ratio. Using Allard's model to describe the sound propagation above the porous material, an analytical model for this power-based SAC is proposed and proves to give a good approximation of the sound absorption performance under monopole excitation of sufficiently large areas of material. The impact of factors on the power-based SAC, such as monopole height, material radial dimension used to calculate the sound powers, and material properties is discussed. The power-based SAC frequency-dependent behavior is …

Machine Learning Applications In Spine Biomechanics, Farshid Ghezelbash, Amir Hossein Eskandari, Xavier Robert-Lachaine, Shufan Cao, Mehran Pesteie, Zhuohua Qiao, Aboulfazl Shirazi-Adl, Christian Larivière

Études primaires

Spine biomechanics is at a transformation with the advent and integration of machine learning and computer vision technologies. These novel techniques facilitate the estimation of 3D body shapes, anthropometrics, and kinematics from as simple as a single-camera image, making them more accessible and practical for a diverse range of applications. This study introduces a framework that merges these methodologies with traditional musculoskeletal modeling, enabling comprehensive analysis of spinal biomechanics during complex activities from a single camera. The real-world applications explored in this study include assessment in workplace lifting, evaluation of whiplash injuries in car accidents, and biomechanical analysis in professional …

Simulation Of A Pick And Place System For Electronic Cards Using A Yumi Cobot, Derrick Sze, Rosula Sj Reyes, Patricia Angela R. Abu

Electronics, Computer, and Communications Engineering Faculty Publications

Collaborative Robots are one of the main drivers of Industry 4.0, which started as a vision focusing on industrial production. It addresses several challenges in the current manufacturing industry such as performing repetitive work and requiring highly skilled workers. The goal of the research is to be able to simulate a pick and place environment with electronic cards using a YuMi cobot and mobile platforms in Coppeliasim. The mobile robot is responsible for transporting the electronic cards to the target location through path planning implemented using the OMPL plug-in. After arriving at the target location, YuMi will then perform the …

Investigating The Influence Of Container Design And A Bulge Reduction Technique In Corrugated Fiberboard Containers Under Static Compression, Jay Singh, Koushik Saha

Industrial Technology and Packaging

This study explored the bulge effect in corrugated fiberboard boxes caused by excessive weight, leading to compromised stacking strength and potential product damage. It investigated how container design, specifically the height variations of regular slotted containers (RSCs), affects bulging under compression and its vulnerability to environmental conditions. Testing met ASTM standards, with samples conditioned according to ASTM and TAPPI protocols, revealing that changes in box height influence bulge displacement. Subsequent research examined the impact of top-to-bottom static compression loads on bulging in tape-reinforced RSC designs, evaluating bulge reduction and compression strength across various tape placements and environments. Notably, previous studies …

Co-Evolving Multi-Agent Transfer Reinforcement Learning Via Scenario Independent Representation, Ayesha Siddiqua

Graduate Theses/Dissertations

Multi-Agent Reinforcement Learning (MARL) addresses complex tasks involving cooperation and competition among agents, training them to develop optimal policies for collective goals. However, facilitating simultaneous learning for multiple agents is challenging because the complexity increases rapidly with the number of agents. Current methods encompass a variety of centralized, decentralized, semi-centralized, and hybrid approaches to balance the trade-offs between computational efficiency, scalability, and coordination in MARL. In this study, I employed a centralized training with semi-centralized execution (CTSCE) framework, utilize both local observations from agents and abstracted global observations to effectively train agents in cooperative environments. Additionally, earning complex, domain-specific tasks …

A Review On Machine Learning Methods For Customer Churn Prediction And Recommendations For Business Practitioners, Awais Manzoor, M. Atif Qureshi, Etain Kidney, Luca Longo

Articles

Due to market deregulation and globalisation, competitive environments in various sectors continuously evolve, leading to increased customer churn. Effectively anticipating and mitigating customer churn is vital for businesses to retain their customer base and sustain business growth. This research scrutinizes 212 published articles from 2015 to 2023, delving into customer churn prediction using machine learning methods. Distinctive in its scope, this work covers key stages of churn prediction models comprehensively, contrary to published reviews, which focus on some aspects of churn prediction, such as model development, feature engineering and model evaluation using traditional machine learning-based evaluation metrics. The review emphasises …

Enhancing Microwave Disinfection: Impact Of Sodium Chloride On Microbial Inactivation, Saleh A. Alfawaz, Ibrahim Nasser I. Alquaydheb, Amirreza Ghadimi Avval, Sara Ghayouraneh, Samir M. El-Ghazaly, Jianhong Zhou

Electrical Engineering and Computer Science Faculty Publications and Presentations

This study explores the role of sodium chloride (NaCl) in enhancing the efficiency of microbial inactivation using microwave energy with two distinct methods: temperature-controlled treatment and predefined cycle. The primary objective is to maintain a stable temperature within the biological samples during treatment. Detailed descriptions of the treatment system’s design and the function of each element are provided. Simulations are conducted to illustrate the heating behavior of liquids with and without NaCl, revealing significant differences in temperature profiles between the two media. The experimental design and the objective behind each iteration are discussed. The experimental design includes three different power …

Dynamics Of A 3-D Inlet/Isolator Measured With Fast Pressure-Sensitive Paint, Andrew N. Bustard, Mark E. Noftz, Mitsugu Hasegawa, Hirotaka Sakaue, Joseph S. Jewell, Nicholas J. Bisek, Thomas J. Juliano

Publications

Fast pressure-sensitive paint (PSP) was applied to an inlet/isolator designed using the Osculating Internal Waverider Inlet with Parallel Streamlines (OIWPS) method. The dorsal isolator surface pressure was measured using anodized-aluminum PSP through transparent cast acrylic that makes up the ventral portion of the isolator. Temperature-sensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at Re = 8.5 ×106 /m and 10.2 ×106 /m in the AFOSR–Notre Dame Large Mach-6 Quiet Tunnel (ANDLM6QT) under conventional noise conditions. Flow phenomena, such as shocks originating in the inlet and flow separation at the …