Engineering Commons^™

On-Chip Active Pulse-Clamp Stimulation (Apcs) For Rapid Recovery, Charge-Balanced Neural Stimulation, F. N. U. Tala

Boise State University Theses and Dissertations

Neurostimulations are widely utilized to modulate brains and nervous systems functions for therapeutic purposes. Traditional neurostimulation involves applying a direct current delivered to the excitable tissues to elicit neural response. There is a growing demand for a robust, rapid stimulation system that ensures chronic safety through charge balancing in vivo. This dissertation is a compilation of previously published works, detailing various board-level stimulators, an innovative on-chip stimulation technique, and a distributed modelling method.

Chapter one introduces MEDUSA, a cost-effective, multi-functional neurostimulation system capable of achieving multi-channel, arbitrary stimulation for neuroscience research.

Chapter two delves into a scripted distributed model framework …

Evaluating The Synergy Of Geocell And Microbial-Induced Calcite Precipitation (Micp) In Enhancing Pavement Base Stability: A Field Study On Us 95, Mabin Dahal

Boise State University Theses and Dissertations

The imperative to develop resilient and sustainable infrastructure is escalating, particularly as urban road networks are subjected to unprecedented stresses. Conventional pavement bases often entail the extensive utilization of quarry materials, which significantly exacerbates environmental degradation and amplifies the energy footprint of construction endeavors. The extraction, transportation, and processing of these quarry materials contribute to deforestation, habitat eradication, and greenhouse gas emissions. Given these environmental and operational hurdles, the quest for innovative, sustainable alternatives in pavement engineering is pressing. One solution is to use the native materials treated with microbial-induced calcite precipitation (MICP) alongside geocell technology back in pavement construction …

Multiscale Design And Numerical Modeling Of A Porous Lattice For Concentrated Solar Thermal Applications, Aidan T. Mcconnehey

Boise State University Theses and Dissertations

Due to the rising demand in the market for renewable energy, concentrated solar power (CSP) systems are increasing in popularity. One CSP receiver configuration showing increased promise is the volumetric cavity solar receiver, which employs a porous lattice for radiative heat absorption and transport. However, due to the presence of large temperature gradients, mechanical failure as a result of thermal expansion is a crucial metric in the design of these systems.

This thesis involves the design of a porous lattice, constrained by thermal transport requirements as well as mechanical failure criteria. The design is then numerically analyzed to determine thermal …

Traffic Prediction In 5g Networks Using Machine Learning, Hossein Mehri

Boise State University Theses and Dissertations

The advent of 5G technology promises a paradigm shift in the realm of telecommunications, offering unprecedented speeds and connectivity. However, the efficient management of traffic in 5G networks remains a critical challenge. It is due to the dynamic and heterogeneous nature of network traffic, including bursty patterns, varying user behaviors, and diverse applications, all of which demand highly accurate and adaptable prediction models to optimize network resource allocation and management. This dissertation investigates the intricate domain of traffic prediction within 5G networks, addressing the specific challenges posed by both massive machine type communication (mMTC) networks and 5G cellular networks.

The …

Wildfire Impacts On Soil: Hydrophobicity Inducement And Water Drop Penetration Test, Max A. Veneris

Boise State University Theses and Dissertations

The increasing prevalence of wildfires in today’s day and age has amplified the need for post-fire remediation and environmental restoration, especially in the wildland-urban interface (WUI). One of these impacts is soil hydrophobicity, or soil water repellency, which is a well-documented phenomenon after wildfires. Hydrophobicity can significantly impacting revegetation, slope stability, runoff, and erosion potential. To better understand the soil fire-induced hydrophobicity and its impact on other soil properties, variable levels of hydrophobicity need to be repeatably induced in several types of soils under different controlled testing conditions to measure other soil properties. To reach this goal two ingredients are …

Utilizing Spatial Transcriptomics To Compare Gene Expression In Volumetric Muscle Loss Injury Recovery, Colton Gattis

Biomedical Engineering Undergraduate Honors Theses

Volumetric Muscle Loss (VML) injuries are known to disrupt the normal regenerative process via fibrosis leading to an extensive permanent loss of muscle function. The specific causation of this disruption remains to be defined; however, with new developments in transcriptomics, genetic trends can be identified across regions of tissue over time. This study follows VML injuries within the tibialis anterior of a mouse model for fifteen days after initial injury to attempt to identify expected transitions in healing. Genetic presence began to become more diversified as recovery progressed from four to fifteen days post injury with spatial clusters becoming globalized …

Photo-Carbon Monoxide Releasing Molecules For Antibacterial Benefits In Vascular Grafts, Beste Caner

Theses and Dissertations

Globally, the annual hemodialysis procedures surpass 1.5 million, emphasizing the vital role of reliable vascular access methods. However, common challenges like access infections and clot-induced blood flow reduction necessitate innovative solutions. This study delved into the potential therapeutic role of carbon monoxide (CO) and its effects on both endothelialization and non-pathogenic bacteria causing infections. The primary focus was evaluating the impact of loading different concentrations of carbon monoxide-releasing molecules (CORMs), specifically CORM diketone 4 (DK4), within 2D spin-coated films on cultured E. coli and endothelial cells. Initial assessments of CO release kinetics from DK4-loaded films demonstrated that the 10% condition …

High-Power Dc-Dc Transformer For Medium-Voltage Grids With High-Voltage Sic Technology, Roderick Gomez

Graduate Theses and Dissertations

The objective of this dissertation is to present the theoretical analysis, design process, application and manufacturing of a proposed solid-state transformer intended for medium-voltage applications with minimal high-frequency oscillations. Galvanic isolation on medium-voltage DC-DC converters tend to employ large number of turns in the high voltage side of the transformers leading to non-negligible parasitic stray capacitances which form resonance tanks with the transformer inductances. Therefore, it is critical to estimate these parasitic capacitances to avoid severe high frequency oscillations which can significantly impact the converter performance. The main contribution of this thesis is the extension of a proposed custom-core design …

Modeling Of Rotor Wake Vortex Dynamics And Interactions In Non-Homogenous Vertiport Environments, Garrison P. Shaw

Doctoral Dissertations and Master's Theses

The current research serves to analyze and study the effects ground forces can have on the thrust performance of a propeller in multiple different configurations. The current research utilizes an open source Computational Fluid Dynamics (CFD) software known as OpenFOAM to generate calculate and visualize these runs. The model used for this experiment is a hybrid model that employs both a Unsteady Reynolds-Averaged Navier-Stokes (URANS) and a detached eddy simulation using a hybrid Large Eddy Simulation (LES) via a KomegaSSTDDES model. This model serves to save computational time as well as allow for accurate results. The three cases run are …

Development Of A More Sustainable High And Ultra-High-Performance Concrete, Enrique Chirino Andalco

Theses and Dissertations

The urgent need to address climate change and environmental damage presents humanity with significant challenges that must be tackled quickly, not acting promptly will result in irreversible consequences, such as extreme weather events, public health risks, and water shortages, among other impacts.

Due to its enormous size and variety of uses, the construction industry is a key factor in addressing the climate challenge. Specifically, concrete as the most used construction material in the world is a good target for developing innovative and Sustainable improvements to reduce environmental impacts.

Using by-products from other industries in concrete manufacturing is a common and …

Machine Learning Predictive Models For Load Identification Of Railroad Bridges Subjected To Train-Induced Vibration, Md Masnun Rahman

Theses and Dissertations

The U.S. rail network is among the world's largest, safest, and most efficient. However, many its railway bridges, which play an essential role in its connectivity, are over 100 years old, showing signs of structural deterioration exceeding their practical service life. The increased weight and speed of modern trains also pose a risk to these bridges. Traditional load identification and monitoring technologies like Weigh-in-Motion (WIM) systems are rarely used on railway bridges due to their cost and practical limits. This thesis explores a cost-effective approach to utilize vibration sensors on railway bridges to identify and predict train load features (speed …

Numerical Study Of New Tuned Mass Friction Damper For Seismic Protection Of Civil Structures, Syed Muhammad Bilal Haider

Theses and Dissertations

Tuned Mass Friction Dampers (TMFDs) are passive control systems designed to mitigate vibrations in civil structures subjected to extreme lateral forces such as windstorms and earthquakes. The objective of this thesis is to propose a new TMFDs with enhanced energy dissipation capability for seismic protection of multi-story frame buildings. This new TMFD is termed as “Tuned Mass Multi-Sliding Friction Damper” (TMMSFD) consisting of multiple masses connected to the primary structure through linear springs and while sliding relative to each other at multiple sliding surfaces. TMMSFD offers an improved damping mechanism with reduced stick-slip motion effects compared to standard TMFDs which …

Model-Based And Model-Free Control Approaches In Subgrids: A Conceptual Review Of Control Strategies In Microgrids, Omobolade H. Abioye

Theses and Dissertations

Increased reliance on the power grid and concerns over climate change issues have resulted in the rapid adoption of renewable energy technologies. Consequently, it is necessary to consider how renewable energy resources are combined and controlled. The microgrid serves as the control center for distributed energy resources. This thesis paper introduces the microgrid elements and framework, its control strategies highlighting frequency and voltage control, and the prospects of artificial intelligence for control, considering two significant approaches. Key components of sub grids like the energy management system (EMS) and energy storage systems (ESSs) are discussed, and lastly, the …

Particle Swarm Optimization For Training Quadrotor Pid Controller, Eric Xavier Rodriguez

Theses and Dissertations

The objective of this research is to establish a fundamental approach to tuning PID (Proportional-Integral-Derivative) parameters for a simulated quadrotor drone. Implementing a PID controller for autonomous flight provides a straightforward and efficient method for monitoring and correcting robotic movement based on the robot's current state. However, applying a PID approach to a quadrotor's flight controller poses challenges, such as assigning multiple parameters to control an inherently under-actuated system. This includes the need to find optimal parameter values that reduce the likelihood of large overshoots and lengthy adjustment times. Ineffectively tuning PID parameters can have detrimental effects on autonomously …

Developing Resilient Defense Strategies Against Pheromone-Based Attacks In Foraging Robot Swarms, Ryan A. Luna

Theses and Dissertations

This thesis delves into the security of stochastic pheromone-based foraging algorithms within swarm robotic systems, a subset of foraging algorithms distinguished by their reliance on probabilistic decision-making mechanisms inspired by the natural world. Such algorithms face vulnerabilities in stigmergic communication that threaten to disrupt swarm operations. This research investigates these vulnerabilities, presenting two distinct contributions.

The first contribution examines the implementation of quarantine strategies as a defensive measure to isolate and mitigate the impact of fake resource attacks. By simulating these attacks, this study quantitatively assesses their detrimental effects on swarm efficiency and explores the efficacy …

Rsm For The Optimization Of Selective Laser Melting Process Parameters For Manufacturing Initial Layers Of Horizontal Overhang Structures, Prince Yaw Asamani

Theses and Dissertations

While prevalent in 3D printed objects, overhang features are difficult to print with selective laser melting due to the limitation of a purely vertical laser. To address this issue, overhang features are typically built on temporary supports, which are removed following printing. However, this results in wasted material and longer production time. Several authors have studied printing overhangs without support structures. However, there has not been a systematic approach to studying the effect of multiple process parameters on the quality of a printed overhang. This thesis investigates the effect of laser power, scanning speed, and hatch distance on the surface …

A Dedicated Lane Analysis For Supply Chain Resilience In The U.S.-Mexico Border: Cost-Comparison And Simulation Models, Carlo A. Zorola Gonzalez

Theses and Dissertations

Supply chains have been actively developing and implementing strategies to enhance resilience in response to various disruptive events like the COVID-19 pandemic, hurricanes, geopolitical tensions, and climate change. These strategies aim to address demand and supply imbalances, logistical challenges, and policy restrictions encountered in transborder commerce. One area significantly impacted by such disruptions is cross-border trade between the US and Mexico. Understanding these strategies is crucial for achieving supply chain resilience, defined as the ability of a supply chain to quickly adapt to sudden disruptions without affecting the flow of goods. In both the US-Mexico and US-Canada borders …

Automatic Speech Recognition For Air Traffic Control Using Convolutional Lstm, Sakshi Nakashe

Electronic Theses, Projects, and Dissertations

The need for automatic speech recognition in air traffic control is critical as it enhances the interaction between the computer and human. Speech recognition helps to automatically transcribe the communication between the pilots and the air traffic controllers, which reduces the time taken for administrative tasks. This project aims to provide improvement to the Automatic Speech Recognition (ASR) system for air traffic control by investigating the impact of convolution LSTM model on ASR as suggested by previous studies. The research questions are: (Q1) Comparing the performance of ConvLSTM with other conventional models, how does ConvLSTM perform with respect to recognizing …

Effectiveness Of Cnn-Lstm Models Used For Apple Stock Forecasting, Ethan White

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the effectiveness of convolutional neural networks mixed with long short-term memory (CNN-LSTM) models, and an ensemble method, extreme gradient boosting (XGBoost), in predicting closing stock prices. This quantitative analysis utilizes recent AAPL stock data from the NASDAQ index. The chosen research questions (RQs) are: RQ1. What are the optimal hyperparameters for CNN-LSTM models in stock price forecasting? RQ2. What is the best architecture for CNN-LSTM models in this context? RQ3. How can ensemble techniques like XGBoost effectively enhance the predictions of CNN-LSTM models for stock price forecasting?

The research questions were answered through a thorough …

Deep Learning Using Vision And Lidar For Global Robot Localization, Brett E. Gowling

Master's Theses

As the field of mobile robotics rapidly expands, precise understanding of a robot’s position and orientation becomes critical for autonomous navigation and efficient task performance. In this thesis, we present a snapshot-based global localization machine learning model for a mobile robot, the e-puck, in a simulated environment. Our model uses multimodal data to predict both position and orientation using the robot’s on-board cameras and LiDAR sensor. In an effort to minimize localization error, we explore different sensor configurations by varying the number of cameras and LiDAR layers used. Additionally, we investigate the performance benefits of different multimodal fusion strategies while …

A Smart Hybrid Enhanced Recommendation And Personalization Algorithm Using Machine Learning, Aswin Kumar Nalluri

Electronic Theses, Projects, and Dissertations

In today’s age of streaming services, the effectiveness and precision of recommendation systems are crucial in improving user satisfaction. This project introduces the Smart Hybrid Enhanced Recommendation and Personalization Algorithm (SHERPA) a cutting-edge machine learning approach aimed at transforming how movie suggestions are made. By combining Term Frequency Inverse Document Frequency (TF-IDF) for content based filtering and Alternating Squares (ALS) with Weighted Regularization for filtering SHERPA offers a sophisticated method for delivering tailored recommendations.

The algorithm underwent evaluation using a dataset that included over 50 million ratings from 480,000 Netflix users encompassing 17,000 movie titles. The performance of SHERPA was …

Automated Brain Tumor Classifier With Deep Learning, Venkata Sai Krishna Chaitanya Kandula

Electronic Theses, Projects, and Dissertations

Brain Tumors are abnormal growth of cells within the brain that can be categorized as benign (non-cancerous) or malignant (cancerous). Accurate and timely classification of brain tumors is crucial for effective treatment planning and patient care. Medical imaging techniques like Magnetic Resonance Imaging (MRI) provide detailed visualizations of brain structures, aiding in diagnosis and tumor classification^[8].

In this project, we propose a brain tumor classifier applying deep learning methodologies to automatically classify brain tumor images without any manual intervention. The classifier uses deep learning architectures to extract and classify brain MRI images. Specifically, a Convolutional Neural Network (CNN) …

Cultural Awareness Application, Bharat Gupta

Electronic Theses, Projects, and Dissertations

In an increasingly interconnected global landscape, cultural awareness and competency have become indispensable skills for individuals and organizations alike. This paper introduces a pioneering cultural awareness application, grounded in the Cultural Orientation Model—a comprehensive framework devised by Dr. Walker [8]to guide individuals in understanding, appreciating, and effectively engaging with diverse cultures. The application encompasses ten primary dimensions, each representing fundamental aspects of social life shared by members of any socio-cultural environment. Through a combination of cultural education, interactive learning, guidance on cultural etiquette, and integration of cultural events, the application aims to foster empathy, tolerance, and effective cross-cultural communication skills. …

Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark

Honors Theses

Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …

Bay Water Level Influences On Inundation And Morphological Changes Of A Semi-Connected Barrier Island During A Hurricane, Sydney D. Goodman

Graduate Theses and Dissertations (2019 - present)

This research aims to identify flooding and erosion changes along a semi-connected barrier island system due to varying bay water levels during storm conditions. The numerical model XBeach is used to simulate Hurricane Michael conditions and the resulting inundation and morphological change near Tyndall Air Force Base (Tyndall AFB). The installation is located 12 miles southeast of Panama City Beach along the panhandle of Florida and is vulnerable to flooding due to its proximity to the Gulf of Mexico (GoM), Saint Andrew Sound and Saint Andrew Bay. A land bridge connects the barrier island to the mainland of Tyndall AFB …

Biophysical Model Of Retraction Motor Neurons And Their Modification By Operant Conditioning, Maria Rasheed

Dissertations and Theses (Open Access)

Operant conditioning (OC) is a form of associative learning in which an animal modifies its behavior based on the consequences that follow that behavior. Despite its ubiquity, the underlying mechanisms of OC are poorly understood. Insights into the mechanisms of OC can be obtained by studying Aplysia feeding behavior as it can be modified by OC. This behavior is mediated by a central pattern generator (CPG) network in the buccal ganglia that contains a relatively small number of neurons. This CPG generates rhythmic motor patterns (BMPs) that move food into the gut by closing a tongue-like structure (i.e., radula) during …

A Reinforcement Learning Framework For Powertrain Control Including Shared Learning Among A Fleet Of Vehicles, Lindsey Kerbel

All Dissertations

The transportation sector provides a significant opportunity to reduce global emissions, both through technological advancements and vehicular control strategies. Model-based control systems are popular methods for increasing the operating efficiency of vehicles. However, these systems often rely on models that require costly calibrations that still fail to capture the complexity of modern powertrain systems and the variations found in real-world driving. The recent availability of operational data through connected vehicle technology and/or edge devices has led to the emergence of data-driven control strategies that can learn optimal control policies through the interactions of the vehicle’s control system with the environment. …

An In Vitro Investigation Of Urothelial Cell Function In Response To Hypoxia And Pressure In Relation To Bladder Outlet Obstruction, Britney Hudson

All Dissertations

Bladder outlet obstruction (BOO) is a prevalent urological condition and can be characterized by the presence of lower urinary tract symptoms (LUTS), such as hesitancy, weak stream, and nocturia. The main cause of BOO is a partial blockage of the urethra, which results in elevated voiding pressure, high storage pressure, and tissue ischemia, which are thought to be the triggers of bladder inflammation and subsequent fibrosis. Often patients do not seek treatment until the conditions get severe. Thus, it would be ideal to have an early diagnostic tool to detect changes in the bladder due to BOO. Extracellular vesicles (EVs) …

Locally Injectable Peptide Hydrogel For Conversion Of Temozolomide And Codelivery Of Sirna In Glioblastoma Multiforme Treatment, Megan Pitz

All Dissertations

Traditional treatment methods for glioblastoma multiforme (GBM) are largely unsuccessful, with a 5-year survival rate of 5.6%. Temozolomide (TMZ), the only chemotherapy FDA-approved for GBM treatment, is a hydrophobic prodrug that is stable in an acidic pH and begins converting to its active form at a physiological pH of 7.4. However, complete conversion of TMZ is observed only at a higher pH, and only about 30% of administered TMZ reaches the central nervous system. Therefore, there is a need for new treatment methods that maximize TMZ delivery to and efficacy at the tumor site. Self-assembling peptides are a unique class …

Optical Wavelength Measurement Based On Microwave-Photonics And Fiber Dispersion, Yongji Wu

All Dissertations

In modern photonics, combining microwave techniques with optical measurements has introduced a novel research direction. This study introduces a novel Microwave Photonics Wavelength Measurement System (MP-WMS), integrating microwave photonics with fiber chromatic dispersion to achieve direct wavelength measurement. Utilizing cost effective single mode optical fibers as dispersion devices, this system employs chromatic dispersion to convert optical frequency domain measurements into microwave time domain measurements. We established a mathematical model to describe how different wavelengths are detected, enhancing the system's effectiveness. The MP-WMS system offers an affordable solution with high resolution. In the experiment, we used a 35km long SM-28 single-mode …