Digital Commons Network^™

Micro-Scale Laser-Induced Fluorescence Thermometry For Multiphase Flow In Porous Media, Samuel J. Simmons

Master's Theses

In this thesis the use of Laser-Induced Fluorescence (LIF) thermometry was evaluated as a temperature measurement for multiphase flow in porous media. This optical temperature measurement technique utilizes the temperature-dependent emissive properties of fluorescent dyes to measure temperature. This research evaluates the accuracy, spatial resolution, and temporal resolution of LIF thermometry compared to existing temperature measurements. In this research water-soluble and oil-soluble fluorescent dyes are evaluated in terms of their temperature sensitivity. The ability of these dyes to measure temperature is compared to an Ansys FEA simulation of a fixed temperature gradient. For multiphase flow, the fluorescent dyes were both …

Group-Invariant Reinforcement Learning, Fnu Ankur

Master's Theses

Our work introduces a way to learn an optimal reinforcement learning agent accompanied by intrinsic properties of the environment. The extracted properties helps the agent to extrapolate the learning to unseen states efficiently. Out of all the various types of properties, we are intrigued towards equivariant and invariant properties, which essentially translates to symmetry. Contrary to many approaches, we do not assume the symmetry, rather learn them, making the approach agnostic to the environment and the property. The learned properties offers multiple perspective of the environment to exploit it to benefit decision making while interacting with the environment. By building …

Automatic Presentation Slide Generation Using Llms, Tanya Gupta

Master's Theses

Presentation slides are widely used for conveying information in academic and professional contexts. However, manual slide creation can be time-consuming. Our research focuses on automated slide generation, specifically for scientific research papers. Automating the creation of presentation slides for scientific documents is a rather novel task and hence, there’s limited training data available and there also exists the token constraints of language models like BERT, with a maximum sequence length of 512 tokens. In this study, we fine-tune large language models, including Longformer-Encoder-Decoder (supporting sequences up to 16,834 tokens) and BIGBIRD-Pegasus (supporting sequences up to 4,096 tokens). We tackle this …

Interdependence Of Salt Concentration And Filler Particles On Crystallinity And Mechanical Behavior Of Peo-Litfsi Electrolytes For Lithium-Ion Batteries, Valeria Perez

Master's Theses

Developing composite polymer electrolytes is crucial for enhancing the safety, energy density, and performance of lithium-ion batteries. While it is widely accepted that introducing filler particles in PEO-based electrolytes can reduce crystallinity and enhance ionic conductivity, this conventional understanding applies primarily to electrolytes with high lithium salt concentrations. The hypothesis of this investigation is that the crystallinity change induced by LLZTO ceramic particles in PEO-LiTFSI electrolytes is contingent on the EO:Li molar ratio. This hypothesis is interrogated by measuring changes in crystallinity, spherulite morphology, and stiffness of composite polymer electrolytes with two different EO:Li molar ratios using differential scanning calorimetry, …

Effect Of Spatial Uniformity Of Platelet Aggregates On The Stress-Strain Behavior Of Blood Clots, Tamara Kawa

Master's Theses

Blood clots are a leading contributor to deaths and cardiovascular complications; however, they also play a critical role in wound healing. Though treatments inhibiting platelet activity help prevent thrombosis, they also affect the contractile forces exerted by platelets and, potentially, their distribution. The stiffness of the fibrin matrix that maintains the clot structure is also affected. The hypothesis of this investigation is that blood clots with uniform platelet distribution exhibit higher resistance to deformation than clots with clustered distributions, specifically because of local strain stiffening by platelets. The hypothesis was tested by conducting finite element analysis (FEA) simulations of platelet-rich …

Intrinsic Motivation By The Principles Of Non-Linear Dynamical Systems, Phu C. Nguyen

Master's Theses

The design of appropriate control rules for the stabilization of dynamical systems can require quite substantial domain knowledge. Modern AI methodologies, such as Reinforcement Learning, are often used to mitigate the need for such knowledge. However, these can be slow and often rely on at least some hand-designed reward structure, and thus human input, to be more effective. Here, we propose an alternative route to construct rewards requiring only minimal domain knowledge, essentially relying on the structure of the dynamical system itself. For this, we use truncated Lyapunov exponents as rewards to calculate the stabilizing controller from samples. Concretely, the …

Controllability-Constrained Deep Neural Network Models For Enhanced Control Of Dynamical Systems, Suruchi Sharma

Master's Theses

Control of a dynamical system without the knowledge of dynamics is an important and challenging task. Modern machine learning approaches, such as deep neural networks (DNNs), allow for the estimation of a dynamics model from control inputs and corresponding state observation outputs. Such data-driven models are often utilized for the derivation of model-based controllers. However, in general, there are no guarantees that a model represented by DNNs will be controllable according to the formal control-theoretical meaning of controllability, which is crucial for the design of effective controllers. This often precludes the use of DNN-estimated models in applications, where formal controllability …

Deep Learning In Ai Medical Imaging For Stroke Diagnosis, James Mario Guzman

Master's Theses

Enhancing medical imaging stroke diagnosis applications with artificial intelligence (AI) tools to determine lesion volume, location and clinical metadata is vital toward guiding patient treatment and procedure. A major hardship in developing stroke diagnosis AI tools is the scarcity of publicly available clinical 3D stroke datasets. Through working with Johns Hopkins University, University of Michigan’s ICPSR data repository and SJSU research, we gained access to potentially the largest 3D MRI stroke dataset with clinical metadata annotated by neuroradiologists known as ICPSR 38464. With the ICPSR 38464 dataset recently being available through institutional review board (IRB) approval or exemption, we were …

Detecting The Onion Routing Traffic In Real-Time By Using Reinforcement Learning, Dazhou Liu

Master's Theses

Anonymous networks have been popularly utilized to protect user anonymity and facilitate network security for a decade. However, such networks have been a platform for adversarial affairs and various network attacks including suspicious traffic generators. As a result, detecting anonymous network traffic is one critical task to defend a network against unpredictable attacks. Many new methods using machine learning and deep learning techniques have been proposed. However, many of them rely heavily on a vast amount of labeled data and have complicated architectures. Since network traffic always fluctuates under different network environments, those techniques may degrade in performance due to …

Kinetic Modeling Of Methanol Synthesis From Carbon Monoxide, Carbon Dioxide, And Hydrogen Over A Cu/Zno/Cr2o3 Catalyst, Daaniya Rahman

Master's Theses

The main purpose of this study was to investigate kinetic models proposed in the

literature for methanol synthesis and select the best fit model using regression techniques

in POLYMATH. Another aim was to use the results from the best fit model to explain

some aspects and resolve some questions related to methanol synthesis kinetics. Two

statistically sound kinetic models were chosen from literature based on their goodness of

fit to the respective kinetic data. POLYMATH, the non-linear regression software, was

used to fit published experimental data to different kinetic models and evaluate kinetic

parameters. The statistical results from POLYMATH were …

Charge Injection And Clock Feedthrough, Jonathan Yu

Master's Theses

Turning off a transistor introduces an error voltage in switched-capacitor circuits. Circuits such as analog-to-digital converters (ADC), digital-to-analog converters (DAC), and CMOS image sensor pixels are limited in performance due to the effects known as charge injection and clock feedthrough. Charge injection occurs in a switched-capacitor circuit when the transistor turns off and disperses channel charge into the source and drain. The source, which is the sampling capacitor, experiences an error in the sampled voltage due to the incoming channel charge. Simultaneously, the coupling due to gate-source overlap capacitance also contributes to the total error voltage, which is known as …

Implementation Of Risk Management In The Medical Device Industry, Rachelo Dumbrique

Master's Theses

This study looks at the implementation and effectiveness of risk management (RM) activities in the medical device industry. An online survey was distributed to medical device professionals who were asked to identify RM-related activities performed during the device life cycle. RM activities and techniques included Establishing Risk Acceptance Criteria, Hazard Identification, Human Factors/Usability, Fault Tree Analysis (FTA), Design Failure Mode and Effects Analysis (DFMEA), Process Failure Mode and Effects Analysis (PFMEA), Hazard and Operability Study (HAZOP), Hazard Analysis and Critical Control Point (HACCP), Risk Benefit Analysis, and Risk Assessment of Customer Complaint. Devices were identified by type (therapeutic, surgical/clinical tools, …

Denoising Of Natural Images Using The Wavelet Transform, Manish Kumar Singh

Master's Theses

A new denoising algorithm based on the Haar wavelet transform is proposed. The methodology is based on an algorithm initially developed for image compression using the Tetrolet transform. The Tetrolet transform is an adaptive Haar wavelet transform whose support is tetrominoes, that is, shapes made by connecting four equal sized squares. The proposed algorithm improves denoising performance measured in peak signal-to-noise ratio (PSNR) by 1-2.5 dB over the Haar wavelet transform for images corrupted by additive white Gaussian noise (AWGN) assuming universal hard thresholding. The algorithm is local and works independently on each 4x4 block of the image. It performs …

Flexural Comparison Of The Aci 318-08 And Aashto Lrfd Structural Concrete Codes, Nathan Jeffrey Dorsey

Master's Theses

No abstract provided.