Digital Commons Network^™

Dormant Propagules In Demographic Studies: A Recurrent Bias And Potential Solutions, Federico Borghesi

Graduate Thesis and Dissertation 2023-2024

In the face of unprecedented anthropogenic change, we increasingly turn to emergent technologies and extensive data sets for solutions that complement much needed systemic changes in our societies. These technological solutions, however, must be approached with care. We must recognize and address biases in the way data has been accumulated. In demographic studies, dormant life stages, such as seed banks, and other cryptic factors have often been neglected. The potential consequences of these omissions have been extensively described in the literature. In the first chapter, I analyze patterns of seed bank omissions in demographic models, finding unjustified omissions are widespread …

Multi-Kilowatt Fiber Laser Amplifiers And Hollow-Core Delivery Fibers, Matthew Cooper

Graduate Thesis and Dissertation 2023-2024

High-power fiber lasers have emerged as a cornerstone in the realm of laser technology. Characterized by their exceptional efficiency, ruggedness, and versatility, fiber lasers are experiencing widespread use in manufacturing, medical, defense, science, and in long range sensing. Unfortunately, high-power applications require strict spatial and spectral performance characteristics to be maintained, which has yet to be perfected.

This dissertation discusses the power scaling of ytterbium-doped fiber laser amplifiers, presenting three significant advancements. First, a novel photonic lantern-based method is introduced for real-time monitoring of laser beam modal content and beam quality. Initial tests highlight the photonic lantern's efficiency in predicting …

A Theoretical Study Of Elementary Processes In Interstellar Plasma, Joshua Forer

Graduate Thesis and Dissertation 2023-2024

Interstellar plasma — interstellar clouds in particular — play an important role in determining the structure and evolution of galaxies. Understanding the time evolution of such plasmas requires knowledge of the chemical processes that drive their dynamics. Two processes are studied in this dissertation: radiative electron attachment (REA) via dipole-bound states (DBSs) and dissociative recombination (DR). Of the several hundred molecules detected in the interstellar medium, only eight anions have been detected: CN-, C3N-, C5N-, C7N-, C4H-, C6H-, C8H-, and C10H-. Their production mechanism is not well known; REA was suggested as a possible formation pathway, but previous theoretical studies …

Deep Learning Approaches For Automatic Colorization, Super-Resolution, And Representation Of Volumetric Data, Sudarshan Devkota

Graduate Thesis and Dissertation 2023-2024

This dissertation includes a collection of studies that aim to improve the way we represent and visualize volume data. The advancement of medical imaging has revolutionized healthcare, providing crucial anatomical insights for accurate diagnosis and treatment planning. Our first study introduces an innovative technique to enhance the utility of medical images, transitioning from monochromatic scans to vivid 3D representations. It presents a framework for reference-based automatic color transfer, establishing deep semantic correspondences between a colored reference image and grayscale medical scans. This methodology extends to volumetric rendering, eliminating the need for manual intervention in parameter tuning. Next, it delves into …

Low Energy Photon Detection, Tianyi Guo

Graduate Thesis and Dissertation 2023-2024

Detecting long wave infrared (LWIR) light at room temperature has posed a persistent challenge due to the low energy of photons. The pursuit of an affordable, high-performance LWIR camera capable of room temperature detection has spanned several decades. In the realm of contemporary LWIR detectors, they can be broadly classified into two categories: cooled and uncooled detectors. Cooled detectors, such as MCT detectors, excel in terms of high detectivity and fast response times. However, their reliance on cryogenic cooling significantly escalates their cost and restricts their practical applications. In contrast, uncooled detectors, exemplified by microbolometers, are capable of functioning at …

A Systematic Review Of Cryptocurrencies Use In Cybercrimes, Kieran B D Human

Graduate Thesis and Dissertation 2023-2024

Cryptocurrencies are one of the most prominent applications of blockchain systems. While cryptocurrencies promise many features and advantages, such as decentralization, anonymity, and ease of access, those very features can be abused. For instance, as documented in various recent works, cryptocurrencies have been frequently abused in many different forms of cybercrime. Despite the plethora of works on measuring and understanding the abuse of cryptocurrencies in the digital space, there has been no work on systemizing this knowledge by comprehensively understanding those contributions, contrasting them based on their merit, and understanding the gap in this research space.

This thesis initiates the …

Material Appearance Modeling For Physically Based Rendering, Alexis Benamira

Graduate Thesis and Dissertation 2023-2024

Photorealistic rendering focuses on creating images with a computer that imitates pictures of reallife scenes as faithfully as possible. To achieve this, rendering algorithms require incorporating accurate modeling of how light interacts with various types of matter. For most objects, this model needs to account for the scattering of the light rays. However, this model falls short when rendering objects of sizes smaller or comparable to the wavelength of the incident light. In this case, new phenomena such as diffraction or interference are observed and have been characterized in optics. Digital rendering of those phenomena involve different light representations than …

Exploring The Feasibility Of Machine Learning Techniques In Recognizing Complex Human Activities, Shengnan Hu

Graduate Thesis and Dissertation 2023-2024

This dissertation introduces several technical innovations that improve the ability of machine learning models to recognize a wide range of complex human activities. As human sensor data becomes more abundant, the need to develop algorithms for understanding and interpreting complex human actions has become increasingly important. Our research focuses on three key areas: multi-agent activity recognition, multi-person pose estimation, and multimodal fusion.

To tackle the problem of monitoring coordinated team activities from spatio-temporal traces, we introduce a new framework that incorporates field of view data to predict team performance. Our framework uses Spatial Temporal Graph Convolutional Networks (ST-GCN) and recurrent …

Optical Characterization Of Liquids: Refractive Index And Raman Gain Coefficient Measurements, Cesar A. Lopez-Zelaya

Graduate Thesis and Dissertation 2023-2024

Novel technologies capable of generating wavelengths not accessible with typical laser gain media have been among the primary drivers of the field of nonlinear optics. Here, we are interested in the linear and nonlinear properties of liquids beyond the visible spectrum, motivated in part by their use as core materials in optical fibers. Given their dispersion, nonlinearities, transparency, and ability to be mixed, liquids show potential for exploiting in-fiber nonlinear phenomena for developing the new generation of low cost, size, weight, and power wavelength-agile fiber-laser sources. For the design, modeling, and experimental realization of these liquid-core fiber laser sources, proper …

Exploring A Lab-Scale Cascade Upflow Bioreactor System For Nitrogen Removal Via Biosorption Activated Media, Alejandra Robles Lecompte

Graduate Thesis and Dissertation 2023-2024

Many Best Management Practices (BMPs) have been developed to reduce excessive nutrients in stormwater runoff and mitigate harmful algal blooms in downstream receiving water bodies. This study demonstrates a new BMP by comparing two green sorption media (i.e., specialty adsorbents) for nutrient removal in cascade upflow biofiltration systems operated in parallel. The proposed filtration technology can control hydraulic gradients, prevent clogging and settlements, and increase hydraulic loading while removing more nutrients in an integrated physicochemical and microbiological treatment process. The two green sorption media being tested in this study include zero-valent-iron and perlite-based green sorption media (ZIPGEM) and biochar, iron, …

Optimizing Deep Neural Networks Performance: Efficient Techniques For Training And Inference, Ankit Sharma

Graduate Thesis and Dissertation 2023-2024

Recent advances in computer vision tasks are mainly due to the success of large deep neural networks. The current state-of-the-art models have high computational costs during inference and suffer from a high memory footprint. Therefore, deploying these large networks on edge devices remains a serious concern. Furthermore, training these over-parameterized networks is computationally expensive and requires a longer training time. Thus, there is a demand to develop techniques that can efficiently reduce training costs and also be able to deploy neural networks on mobile and embedded devices. This dissertation presents practices like designing a lightweight network architecture and increasing network …

Dna Capture And Translocation Through Nanopore, Swarnadeep Seth

Graduate Thesis and Dissertation 2023-2024

This thesis investigates DNA dynamics and translocation through nanopores using Brownian dynamics (BD) simulations, offering insights into sequencing technologies, DNA marker detection, and accurate barcoding utilizing solid-state nanopore platforms. First, we in silico study the intricate process of capture and translocation in a single nanopore. Our simulation reveals a high probability of hairpin loop formation during the capture process. However, attaching a charged tag to one end of DNA improves multi-scan rates and enhances unidirectional translocations. We use modulating voltage biases to multi-scan a lambda-phage dsDNA with oligonucleotide flap markers (tags) through a single and double nanopore system. Our study …

Reconstructing 3d Humans From Visual Data, Ce Zheng

Graduate Thesis and Dissertation 2023-2024

Understanding humans in visual content is fundamental for numerous computer vision applications. Extensive research has been conducted in the field of human pose estimation (HPE) to accurately locate joints and construct body representations from images and videos. Expanding on HPE, human mesh recovery (HMR) addresses the more complex task of estimating the 3D pose and shape of the entire human body. HPE and HMR have gained significant attention due to their applications in areas such as digital human avatar modeling, AI coaching, and virtual reality [135]. However, HPE and HMR come with notable challenges, including intricate body articulation, occlusion, depth …

Towards A Robust And Efficient Deep Neural Network For The Lidar Point Cloud Perception, Zixiang Zhou

Graduate Thesis and Dissertation 2023-2024

In recent years, LiDAR has emerged as a crucial perception tool for robotics and autonomous vehicles. However, most LiDAR perception methods are adapted from 2D image-based deep learning methods, which are not well-suited to the unique geometric structure of LiDAR point cloud data. This domain gap poses challenges for the fast-growing LiDAR perception tasks. This dissertation aims to investigate suitable deep network structures tailored for LiDAR point cloud data, and therefore design a more efficient and robust LiDAR perception framework. Our approach to address this challenge is twofold. First, we recognize that LiDAR point cloud data is characterized by an …