Digital Commons Network^™

Early Wildfire Detection With Line Sensors, Virginia Yan

Master's Theses

Over the last few years, wildfires have become more devastating to communities as the fires are inevitably destructive to many homes, businesses, and ecosystems. Frequent wildfires also pose a significant threat to power grids and nearby residents as they can damage transmission lines and other electrical equipment, which in turn can cause major power shutdowns. Especially in western U.S., severe drought conditions and weather variability cause residents to become more vulnerable to wildfire disasters as their safety is threatened. We are incompetent to control the wildfires effectively despite existing advanced technologies. Hence, an algorithm based on energy conservation and heat …

Development Of A Robust Methodology To Obtain And Assess Myogenic Precursor Cells For Their Use In Regenerative Therapies, Ricardo Lasa

Master's Theses

Peripheral arterial occlusive disease (PAOD) is characterized by buildup of atherosclerotic plaque in peripheral arteries that leads to an occlusion that can interrupt the supply of blood to the peripheral tissue, causing downstream tissue ischemia/hypoxia. PAOD is estimated to affect over 200 million patients worldwide. Current surgical revascularization treatments can be effective in about half of the patient population, leading to a significant number of patients with no treatment options beyond pharmacological intervention and lifestyle modification. The decrease in blood flow downstream of the occlusion leads to increased blood pressure gradient in the microvasculature, specifically in vessels that connect arterial …

Brain Tumor Detection And Classification From Mri Images, Anjaneya Teja Sarma Kalvakolanu

Master's Theses

A brain tumor is detected and classified by biopsy that is conducted after the brain surgery. Advancement in technology and machine learning techniques could help radiologists in the diagnosis of tumors without any invasive measures. We utilized a deep learning-based approach to detect and classify the tumor into Meningioma, Glioma, Pituitary tumors. We used registration and segmentation-based skull stripping mechanism to remove the skull from the MRI images and the grab cut method to verify whether the skull stripped MRI masks retained the features of the tumor for accurate classification. In this research, we proposed a transfer learning based approach …

Development Of Novel Hardware And Software For Wind Turbine Condition Monitoring, Ryan A. Zhan

Master's Theses

With the increased use of wind turbines as sources of energy, maintenance of these devices becomes more and more important. Utility scale wind turbines can be time consuming and expensive to repair so an intelligent method of monitoring these devices is important. Commercial solutions for condition monitoring exist but are expensive and can be difficult to implement. In this project a novel condition monitoring system is developed. The priority of this system, dubbed the LifeLine, is to provide reliable condition monitoring through an easy-to-install and low-cost system. This system utilizes a microcontroller to collect acceleration data to detect imbalances on …

Ram Air-Turbine Of Minimum Drag, Raymond Akagi

Master's Theses

The primary motivation for this work was to predict the conditions that would yield minimum drag for a small Ram-Air Turbine used to provide a specified power requirement for a small flight test instrument called the Boundary Layer Data System. Actuator Disk Theory was used to provide an analytical model for this work.

Classic Actuator Disk Theory (CADT) or Froude’s Momentum Theory was initially established for quasi-one-dimensional flows and inviscid fluids to predict the power output, drag, and efficiency of energy-extracting devices as a function of wake and freestream velocities using the laws of Conservations of Mass, Momentum, and Energy. …

Condition Monitoring And Fault Detection Of Blade Damage In Small Wind Turbines Using Time-Series And Frequency Analyses, Luke H. Costello

Master's Theses

Condition monitoring systems are critical for autonomous detection of damage when operating remote wind turbines. These systems continually monitor the turbine’s operating parameters and detect damage before the turbine fails. Although common in utility-scale turbines, these systems are mostly undeveloped in distributed, small-scale turbines due to their high cost and need for specialized equipment. The Cal Poly Wind Power Research Center is developing a low-cost, modular solution known as the LifeLine system. The previous version contained monitoring equipment, but lacked decision-making capabilities.

The present work builds on the LifeLine by developing software-based detection of blade damage. Detection is done by …

Development Of An Infrared Thermography System To Measure Boundary Layer Transition In A Low Speed Wind Tunnel Testing Environment, Damien Horton

Master's Theses

The use of infrared thermography for boundary layer detection was evaluated for use in the Cal Poly Low Speed Wind Tunnel (LSWT) and recommendations for the successful use of this technique were developed. In cooperation with Joby Aviation, an infinite wing model was designed, manufactured and tested for use in the LSWT. The wing was designed around a custom airfoil profile specific for this project, where the nearly-flat pressure gradient at a zero pitch angle would delay the chordwise onset of boundary layer transition. Steady-state, RANS numerical simulations predicted the onset of transition to occur at 0.75 x/c for the …

Biological Semantic Segmentation On Ct Medical Images For Kidney Tumor Detection Using Nnu-Net Framework, Andres Bergsneider

Master's Theses

Healthcare systems are constantly challenged with bottlenecks due to human-reliant operations, such as analyzing medical images. High precision and repeatability is necessary when performing a diagnostics on patients with tumors. Throughout the years an increasing number of advancements have been made using various machine learning algorithms for the detection of tumors helping to fast track diagnosis and treatment decisions. “Black Box” systems such as the complex deep learning networks discussed in this paper rely heavily on hyperparameter optimization in order to obtain the most ideal performance. This requires a significant time investment in the tuning of such networks to acquire …

Adaptive Laboratory Evolution Of Scenedesmus Obliquus For Increased Carbohydrate Content And Biomass Productivity, Nahel Ali

Master's Theses

The economics of microalgal bioproduct commercialization would benefit from increased accumulation of energy storage compounds, such as carbohydrates and lipids, and increased biomass productivity. This thesis explores two adaptive laboratory evolution strategies for improving Scenedesmus obliquus: single UV-mutagenesis and low light cultivation at a high dilution rate to produce cultigens with greater carbohydrate content and iterative UV-mutagenesis and selection under outdoor conditions in a raceway pond at a high dilution rate to increase biomass productivity.

Two cultigens were generated with the goal of increased carbohydrate content: K5 and K7. Both were mutagenized for 5 seconds and cultivated in 50-mL …

Machine Learning Approaches To Historic Music Restoration, Quinn Coleman

Master's Theses

In 1889, a representative of Thomas Edison recorded Johannes Brahms playing a piano arrangement of his piece titled “Hungarian Dance No. 1”. This recording acts as a window into how musical masters played in the 19th century. Yet, due to years of damage on the original recording medium of a wax cylinder, it was un-listenable by the time it was digitized into WAV format. This thesis presents machine learning approaches to an audio restoration system for historic music, which aims to convert this poor-quality Brahms piano recording into a higher quality one. Digital signal processing is paired with two machine …

The Effect Of Focused Ultrasound On Altering The Diameter Class Of Nerve Fibers Contributing To A Compound Evoked Potential, Analyzed Using A Perturbative Decomposition Technique., Megan Wurden

Master's Theses

Peripheral neuropathies are disorders that involve the damage of peripheral nerve fibers, affecting the ability of different parts of the body to communicate. A differentiating factor in diagnosis between various clinical conditions can be which size class of nerve fibers are affected. A nerve conduction velocity test can be used to assess the viability of the nerve but is a single-parameter test and gives no information about the population characteristics of the remaining active fibers. A method developed and previously reported by Szlavik (2016) utilizes a mathematical perturbed decomposition to determine the normalized frequency of each size class of fiber …

Factors Leading To Structure Loss On The Thomas Fire, Rodolfo Uribe

Master's Theses

The recent surge in fire activity and the extent of displaced communities as a result of wildfire has increased awareness of wildfire issues nationwide (Syphard et al., 2017). Climate change, population growth, and continued development in the wildland urban interface (WUI) has contributed to a growing body of research into the underlying causes of this continued destruction (Kramer et al., 2019). There is no doubt that statewide policies, such as defensible space or building regulations, are associated with home survival (Keeley & Syphard, 2019). However, the relative effectiveness of wildfire mitigation depends on a myriad of factors specific to individual …

A Single-Stage Passive Vibration Isolation System For Scanning Tunneling Microscopy, Toan T. Le

Master's Theses

Scanning Tunneling Microscopy (STM) uses quantum tunneling effect to study the surfaces of materials on an atomic scale. Since the probe of the microscope is on the order of nanometers away from the surface, the device is prone to noises due to vibrations from the surroundings. To minimize the random noises and floor vibrations, passive vibration isolation is a commonly used technique due to its low cost and simpler design compared to active vibration isolation, especially when the entire vibration isolation system (VIS) stays inside an Ultra High Vacuum (UHV) environment. This research aims to analyze and build a single-stage …

Effect Of Simulated Storage And Distribution On Listeria Innocua Growth In Non-Traditional Salad Ingredients, Emma L. Sandquist

Master's Theses

The fresh-cut produce industry has seen expansive growth in recent years, to meet consumer demand ready-to-eat (RTE) salads have included the use of non-traditional ingredients. Uncommon ingredients include beet greens, kale, broccoli stalk, and Brussels sprouts, since these ingredients have not historically been consumed raw, potential food safety issues should be reassessed. Current processing technologies include produce washes that can reduce microbial levels but do not eradicate all populations. The lack of a kill step in produce processing emphasizes the need to minimize pathogen contamination during production and growth during a product’s shelf life. Listeria monocytogenes, a leading cause …

Exposing The Effects Of Reaction Cavity In Solid-Phase Reaction Kinetics, Michael Carr

Master's Theses

Reactivity of molecular solids is governed by topochemical considerations, where minimizedmolecular movement dictates both product identity and kinetics. This Thesis explores the central role reaction cavity plays in the topochemical principle by using the highly varied cavities formed by the different facets of a tetracene crystal. The relative rates for ten different reaction cavities were measured via energy dispersive X-ray spectroscopy for the reaction of tetracene with vapors of maleic anhydride. Variance in cavities resulted in Diels-Alder reaction rates that differed by as much as a factor of 2.6. Effects were understood via molecular dynamic simulations which modeled the approach …

Options For Low-Cost Manufacturing And Safer Cell Therapies, Melis Keceli

Master's Theses

The proposed work aims to overcome the economical and feasibility-related limitations of the chimeric antigen receptor therapies by developing an artificial cell signaling pathway whose design transforms K562 cells into in vivo living vectors to synthesize therapeutic proteins upon engaging diseased cells in the treatment of ovarian cancer. There are various advantages of using K562 cells throughout this process. First, Food and Drug Administration approves the reinfusion of K562 cells into patients’ bodies. Second, K562 cells are more affordable than T lymphocytes, and finally, these cells can be easily manipulated with any desired genetic material and can keep the expression …

Assessing The Role Of The Interaction Between Polyamines And Heparan Sulfate In Coxsackievirus B3 Viral Infection, Oreoluwa Omoba

Master's Theses

Non-polioenteroviruses are highly infectious viruses that typically cause mild asymptomatic cases but can cause severe disease such as aseptic meningitis and dilated cardiomyopathy. Coxsackievirus B3 (CVB3) is a member of this group and is prevalent in the United States and Eastern Asia. Viruses like CVB3 rely on the host cell for many molecules in order to replicate. One such set of molecules is the polyamines. Polyamines are small, positively charged molecules that play a role in a multitude of cellular processes including RNA/DNA stabilization, gene expression, translation, and regulating membrane fluidity. Previous studies have shown CVB3 relies on polyamines for …

Pseudomonas Aeruginosa Prophages And Engineered Temperate Phages, Genevieve Johnson

Master's Theses

The rising rate of antibiotic-resistant bacteria is a global health concern, and the Pseudomonas aeruginosa is estimated to be a leader in serious threats. Bacteriophages, or viruses that infect bacteria, have gained renewed interest in Western Medicine as an alternative to antibiotics. Phage therapy of P. aeruginosa infections has primarily focused on obligately lytic phages. However, prophages, or phages in the lysogenic life cycle, are estimated to far outnumber obligately lytic phages. In theory, these prophages can be genetically modified to be obligately lytic and thus ideal candidates for phage therapy. To date there has not been a comprehensive analysis …

Do Conditional Cash Transfers Increase School Enrollment? Evidence From Brazil, Jeanette L. Silvernale

Master's Theses

Conditional cash transfer programs have been widely deployed across the globe. They seek to bolster human capital by providing benefits contingent upon a variety of actions such as school attendance and regular health checkups. Bolsa Familia is the most extensive conditional cash transfer program, serving 46 million Brazilian citizens. Despite its expansive size, there have been seldom large-scale micro evaluations of the program. Limited data has resulted in small sample sizes drawn from a single point in time. Our study diverges from the rest and utilizes a novel administrative dataset with an overall sample of nearly 60 million and a …

An Efficient Design Methodology For Complex Sequential Asynchronous Digital Circuits, Tomasz Chadzynski

Master's Theses

Asynchronous digital logic as a design alternative offers a smaller circuit area and lower power consumption but suffers from increased complexity and difficulties related to logic hazards and elements synchronization. The presented work proposes a design methodology based on the speed-independent sequential logic theory, oriented toward asynchronous hardware implementation of complex multi-step algorithms. Targeting controller-centric devices that perform data-driven non-linear execution, the methodology offers a CSP language-based controller workflow description approach and the specification of a project implementation template supported by a two-stage design process. First, the CSP layer describes complex speed-independent controller behavior offering better scalability and maintainability than …

The Impact Of Compensation On Engagement And Organizational Tenure: The Moderating Role Of Perceived Organizational Support, Alexis Johnson

Master's Theses

Compensation is a crucial tool utilized by companies to help attract, retain, and motivate employees. However, previous research has overlooked the ways in which compensation might add value to important employee outcomes such as engagement and organizational tenure. Therefore, this present study aimed to close this gap by examining the relationship between pay level and engagement, as well as pay level and organizational tenure. It was hypothesized that higher pay levels would increase the engagement dimensions of dedication, vigor, and absorption in an employee, and that higher pay levels would increase organizational tenure in an individual. It also sought to …

Influence Of Social Circles On User Recommendations, Chaitanya Krishna Kasaraneni

Master's Theses

Recommender systems are powerful tools that filter and recommend content relevant to a user. One of the most popular techniques used in recommender systems is collaborative filtering. Collaborative filtering has been successfully incorporated in many applications. However, these recommendation systems require a minimum number of users, items, and ratings in order to provide effective recommendations. This results in the infamous cold start problem where the system is not able to produce effective recommendations for new users. In recent times, with escalation in the popularity and usage of social networks, people tend to share their experiences in the form of reviews …

Transfer Learning For Hyperspectral Images Utilizing Channel Selection Techniques And Ensemble Methods, Scott Daniel Vogel

Master's Theses

Hyperspectral images contain information from a wider range of the electromagnetic spectrum than natural images which gives them potential for better classification ability. However, hyperspectral datasets are typically small due to the expensive equipment needed to obtain the images, which can limit classification performance. One solution to this problem is transfer learning, in which a model trained on one dataset is reused for a separate dataset. Research has shown that transfer learning between hyperspectral datasets can give improved performance over models without transfer learning when training data are limited. Since extra hyperspectral data are not always available, the solution proposed …

Nuclear Thermal Rocket Engine With A Toroidal Aerospike Nozzle, Kyle Stewart

Master's Theses

This thesis describes the coupling of a nuclear thermal rocket engine with a toroidal aerospike nozzle. The coupling of the two systems consists of two phases. The first of these phases begin with top-level systems and subsystems analysis and design of the new engine. The second phase is the analysis and characterization of the major engine systems through the use of computational fluid dynamics analysis. With the coupling of the nuclear thermal rocket engine with the aerospike nozzle, the new system will be known as the Nuclear Thermal Propulsion System. Due to the uniqueness of coupling a nuclear thermal rocket …

Lstm-Enabled Level Curve Tracking In Scalar Fields Using Multiple Mobile Robots, Kunj J. Parikh

Master's Theses

Autonomous mobile sensor networks are ideal candidates for exploring large-scaleunknown fields with tasks ranging from source seeking, level curve tracking, mapping an unknown field, and many more. In this work, we investigate the problem of level curve tracking in unknown scalar fields using a limited number of mobile sensors. The level curve tracking problem has been studied in many applications such as monitoring the propagation of fire boundaries and the algae blooms. We design and implement a long short term memory (LSTM) enabled control strategy for a mobile sensor network to detect and track the desired level curve. We develop …

Adaptive Learning Technique For Facial Recognition, Rachana Dineshkumar Bumb

Master's Theses

This research describes the adaptive learning technique for facial recognition. It is a common practice in convolutional neural network(CNN) based facial recognition to save its trained result on a large dataset and then load and apply it to ongoing facial recognition tasks. This generally used method lacks adaptation, and the ongoing evolution of new knowledge poses a key technical challenge. In this research, we propose a continued learning technique to incorporate new knowledge derived in each facial recognition process. A positive recognition with confidence score is assigned, and the image associated with this confidence is added to the image dataset …

Supervisor And Coworker Support: Their Moderating Roles On The Relationship Between Diversity Climate Perceptions And Retention-Related Outcomes, Sarah Crouse

Master's Theses

The purpose of the present study was to examine perceived supervisor support and perceived coworker support as moderators of the relationship between diversity climate perceptions and retention-related outcomes (affective commitment, organizational identification, and turnover intentions). Results from a self-report survey of 150 participants showed that neither perceived supervisor support nor perceived coworker support moderated the relationship between diversity climate perceptions and these outcomes. However, the results showed diversity climate perceptions were positively related to perceived supervisor support and perceived coworker support, and independently predicted these retention-related outcomes. Results also showed that perceived supervisor support was more strongly related to these …

Deep Reinforcement Learning Based Path-Planning For Multi-Agent Systems In Advection-Diffusion Field Reconstruction Tasks, Deepak Talwar

Master's Theses

Many environmental processes can be represented mathematically using spatial-temporal varying partial-differential equations. Timely estimation and prediction of processes such as wildfires is critical for disaster management response, but is difficult to accomplish without the availability of a dense network of stationary sensors. In this work, we propose a deep reinforcement learning-based real-time path-planning algorithm for mobile sensor networks traveling in a formation through a spatial-temporal varying advection-diffusion field for the task of field reconstruction. A deep Q-network (DQN) agent is trained on simulated advection-diffusion fields to direct the mobile sensor network to travel along information-rich trajectories. The field measurements made …

Inclusive Leadership, Psychological Empowerment, And Affective Organizational Commitment: A Mediated Model, Mariah Lyn Van Buskirk

Master's Theses

Inclusive leadership has become an important contextual factor to study in organizations given its impact on positive workplace outcomes. However, little is known about the ability of inclusive leadership to affect a wider range of outcomes and the various mediating mechanisms between inclusive leadership and outcomes. Therefore, the present study explored the mediating role of psychological empowerment on the relationship between inclusive leadership and affective organizational commitment. It was hypothesized that inclusive leadership would be positively related to affective organizational commitment both directly and indirectly through psychological empowerment. Results of an online survey from 189 employed individuals showed that inclusive …

Adaptive Discounting In Reinforcement Learning, Milan Zinzuvadiya

Master's Theses

In Markov Decision Process (MDP) models of sequential decision-making, it is common practice to account for temporal discounting by incorporating a constant discount factor. While the effectiveness of fixed-rate discounting in various Reinforcement Learning (RL) settings is well-established, the efficiency of this scheme has been questioned in recent studies. Another notable shortcoming of fixed-rate discounting stems from abstracting away the experiential information of the agent, which is shown to be a significant component of delay discounting in human cognition. To address this issue, this thesis proposes a novel method for adaptive discounting entitled State-wise Adaptive Discounting from Experience (SADE). This …