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Articles 331 - 360 of 10590
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Ambiguous Bodies: Third Gender Expressions In Ancient Maya Art, Jayme Horne
Ambiguous Bodies: Third Gender Expressions In Ancient Maya Art, Jayme Horne
Theses
This thesis examines the interpretations of Lintels 23, 24, and 25 from Yachilán, Drawing 18 from Naj Tunich, and Stela H from Copán, with a specific focus on third gender expression. These artworks depict figures that blend masculine and feminine attributes, from costuming to actions, to present intentionally ambiguous representations of the body that all ancient Maya people would have understood. Third gender expression is defined through the blending of masculine and feminine signifiers. It is a gender identity for people who do not identify as male or female, but rather as neither, both, or a combination of male and …
Draft Card Battler, Brian Moore
Draft Card Battler, Brian Moore
Theses
This project investigates how design transparency and player interaction mechanics can enhance emotional connection and strategic depth in competitive digital card game environments. Draft Card Battler transforms traditional sequential turn-based Trading Card Game (TCG) gameplay into a structured round-based system featuring asymmetric card-play patterns (1-2-2-1) and simultaneous combat resolution. Beginning with a physical card game prototype, the project evolved through iterative design and digital implementation, informed by research in social capital theory and player psychology. Through reflective playtesting and technical development, this study explores whether visibility, pacing, and commitment mechanics foster trust, fairness, and cooperation alongside competitive tension. The implementation …
Assessing Expected Cover Of Invasive Flora Species Near Corridor Features By Distance, Joshua G. Logan
Assessing Expected Cover Of Invasive Flora Species Near Corridor Features By Distance, Joshua G. Logan
Theses
Fragmentation of landscapes has been a growing topic of interest within scientific literature over the past several decades, as the way we as humans affect our planet becomes more apparent as the years go on. As humans, we have shaped the land and what it contains in immeasurable ways, erasing or forever altering entire natural ecosystems. Chief among the drivers altering these ecosystems is the fragmentation of landscapes, which can have all kinds of effects on natural ecosystems, from limiting nutrient transport to providing easier access for invasives to permeate throughout a landscape. Corridors are significant areas of interest regarding …
Enhancing Llm Code Generation: A Systematic Evaluation Of Multi-Agent Collaboration And Runtime Debugging For Improving Accuracy, Reliability, And Latency, Nazmus Ashrafi
Theses
The use of large language models (LLMs) for automated code generation has emerged as a significant focus within AI research. As these pretrained models continue to evolve, their ability to understand and generate complex code structures has opened up new possibilities for automating intricate programming tasks with greater accuracy. Although contemporary foundational models demonstrate promising results, researchers continue to explore optimal post-training strategies to enhance code quality. These include supervised fine-tuning, retrieval-augmented generation (RAG), debugging, and many others. In this thesis, I combine two such widely used post training approaches—namely (1) multi agent collaboration and (2) runtime execution of information-based …
Adaptive Security Metric For Optimizing Post-Quantum Cryptography In Constrained Iot Devices, Aisha Nasser Ahmed
Adaptive Security Metric For Optimizing Post-Quantum Cryptography In Constrained Iot Devices, Aisha Nasser Ahmed
Theses
Quantum Computing poses real threat to Classical Public-Key Cryptography requiring the use of Post-Quantum Cryptography for all Internet of Things Devices. However, there are greater computational, memory and communication overheads in PQC algorithms that create additional burdens on resource constrained IoT devices. At this time, there are no standard measures for systems developers to determine optimal PQC settings for the various IoT Device Classes. This Thesis develops a new framework of metrics for determining the most suitable PQC settings based on Security Strength, Performance Indicators (Latency, Memory, Energy), Communication Overhead and Reliability for each IoT device class. The Research introduces …
Solar Power Forecasting Using Deep Learning Techniques, Fatma Abdulrahman
Solar Power Forecasting Using Deep Learning Techniques, Fatma Abdulrahman
Theses
The growing utilization of solar energy and other renewable energy sources has heightened the demand for a proper forecasting model that enables efficient control of the energy supply as well as grid reliability. In this work, we concentrate about the use of novel techniques in ML models, namely Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), to try to forecast power output in a solar-powered plant using past weather and power output records. Production of solar energy is naturally volatile because it is dependent on the weather conditions and is problematic in nature when integrated into power grids. Conventional …
Improving The Accessibility Of Speech For Deaf And Hard-Of-Hearing Individuals Through Affective Captions, Caluã De Lacerda Pataca
Improving The Accessibility Of Speech For Deaf And Hard-Of-Hearing Individuals Through Affective Captions, Caluã De Lacerda Pataca
Theses
Captions have traditionally served as a bridge between the spoken word and its written representation, helping make speech accessible to Deaf and Hard-of-Hearing (DHH) individuals. It is worth considering, however, how much from speech is left out by this ’bridging’ between sound and visuals. This dissertation describes a research project that has, over six studies, looked at this very issue. We first examined whether there is an issue here at all. What does the experience of DHH individuals with captioning systems tell us about these systems’ shortcomings? For one, we found, captions are felt as monotonous and ambiguous. While communication …
Illustrations For A Scientific Review Article Publication : Human Stem Cell-Derived Organoids, Sunghwan Bae
Illustrations For A Scientific Review Article Publication : Human Stem Cell-Derived Organoids, Sunghwan Bae
Theses
This thesis explores the role of scientific illustration in improving the comprehension of complex scientific concepts. It traces the historical development of illustrations in scientific literature and examines their functions in both research and review articles. The central contribution of this work is the development of twelve vector-based illustrations that elucidate the applications of human organoids within a review article context. These visuals transform intricate ideas into clear, engaging representations, supported by extensive research and verification to maintain scientific accuracy. The thesis concludes by addressing the future of scientific illustration, advocating for reader-oriented design approaches and the use of innovative …
Intelligent Monitoring And Alerting System Using Some Deep Learning Models, Omar Alshamsi
Intelligent Monitoring And Alerting System Using Some Deep Learning Models, Omar Alshamsi
Theses
Road traffic crashes cause over 1.19 million fatalities per year worldwide and represent a major challenge for urban safety (World Health Organization, 2023; World Bank Group & WRI India, 2020). Smart city initiatives aim to use technology to reduce such losses through rapid accident detection and response (Arefin et al., 2025). This proposal outlines a vision for a Road Accident Detection and Response System that employs computer vision and deep learning to identify accidents from video feeds and immediately notify emergency services. The core of the system will be a custom-trained YOLOv8 object detection model, leveraging a dataset of annotated …
Democratizing Community Discourse Analysis In Computational Social Science, Md Towhidul Absar Chowdhury
Democratizing Community Discourse Analysis In Computational Social Science, Md Towhidul Absar Chowdhury
Theses
Community resource inequities and undetected infrastructure vulnerabilities cost municipalities billions annually, with disproportionate impacts on marginalized communities. Current computational approaches to community needs assessment suffer from two critical limitations: they rely on aggregate-level analysis that obscures granular community expressions, and they implement sophisticated computational tools that remain inaccessible to stakeholders without technical expertise. This creates what we term the Community-Computational Gap—a persistent divide where domain experts with vital contextual knowledge cannot access the analytical tools they need, while computational experts develop models without sufficient community context. This dissertation addresses these challenges through a novel methodological framework for fine-grained utterance-level classification …
The Missing Link: Gingos, Ingos, And The Fractured Promise Of Localization, Stella D. Bosch
The Missing Link: Gingos, Ingos, And The Fractured Promise Of Localization, Stella D. Bosch
Theses
This thesis examines collaboration gaps between international nongovernmental organizations (INGOs) and grassroots international nongovernmental organizations (GINGOs) in the localization agenda. While humanitarian and development work are often viewed separately, many organizations operate across both areas, shifting between emergency response and long-term engagement. For this research, “localization” refers to efforts aimed at addressing power imbalances and improving collaboration with local actors, especially in small island nations where vulnerabilities and capacities intersect. The study began as a comparative case design across Cabo Verde, Vanuatu, and Comoros but shifted to an explanatory approach after data constraints redirected the scope. Madagascar was added to …
Impact Of Temperature On Larval Mortality And Performance Of The Acorn Barnacle Chthamalus Fissus In San Diego, Ca, Alberto Rivera
Impact Of Temperature On Larval Mortality And Performance Of The Acorn Barnacle Chthamalus Fissus In San Diego, Ca, Alberto Rivera
Theses
Rising ocean temperatures and increasingly frequent marine heatwaves threaten the physiological performance and survival of marine larvae. This study quantifies the thermal tolerance, respiration, and swimming behavior of Chthamalus fissus cyprid larvae to establish a baseline for understanding their vulnerability under future climate scenarios. Larvae were collected from the Scripps Pier in La Jolla, CA and exposed to a range of temperatures (12–50°C, dependent on the experiment) to assess oxygen consumption, mortality, and swimming speeds. Oxygen consumption rates increased significantly with temperature, peaking at 30°C, with cyprids exposed to temperatures above 26°C showing significantly higher respiration rates than those below …
Post-Traumatic Stress Disorder Symptom Scale And Coping Mechanisms Among Internally Displaced Persons Of Typhoon Yolanda, Christian Paul S. Biluan
Post-Traumatic Stress Disorder Symptom Scale And Coping Mechanisms Among Internally Displaced Persons Of Typhoon Yolanda, Christian Paul S. Biluan
Theses
The study aimed to determine the Post-Traumatic Stress Disorder Symptom Scale and the Coping Mechanisms utilized by the Internally Displaced Persons of Typhoon Yolanda. It sought to identify the profile, risk factors of the respondents, the Post-Traumatic Stress Disorder (PTSD) symptoms manifested and coping mechanisms utilized. The study also distinguished the differences in PTSD and Coping mechanisms when respondents are grouped according to their profile and death of family members and examined the relationship of PTSD and Coping. The study adopted the PTSD Symptom Scale and Brief COPE Inventory questionnaires and were consequently translated to Visayan-Waray. These were then pilot-tested …
From Sim To 6dof: Deep Learning For Real-Time Satellite Pose Estimation From Resolved Ground-Based Imagery, Thomas W.N. Dickinson
From Sim To 6dof: Deep Learning For Real-Time Satellite Pose Estimation From Resolved Ground-Based Imagery, Thomas W.N. Dickinson
Theses
This dissertation presents the first practical system for automated six degrees of freedom (6DOF) satellite pose estimation from resolved ground-based adaptive optics (AO) imagery. Addressing a key challenge in Space Domain Awareness (SDA), the proposed approach eliminates the need for human labeling by directly regressing satellite orientation and position from blurry, noisy, and deeply-shadowed imagery. The architecture consists of a multi-stage deep neural network pipeline that localizes the satellite, predicts pose, and optionally smooths predictions over time. Networks are trained exclusively on fully synthetic imagery generated from a 3D CAD model. Despite this, the model generalizes effectively, bridging the Sim2Real …
Spectroscopy Pre-Trained Transformer (Specpt): A Universal Spectroscopic Analysis And Redshift Measurement Framework, Rohan Pattnaik
Spectroscopy Pre-Trained Transformer (Specpt): A Universal Spectroscopic Analysis And Redshift Measurement Framework, Rohan Pattnaik
Theses
Spectroscopic surveys are essential for measuring galaxy redshifts and probing the physical processes driving galaxy evolution. As datasets grow in scale and complexity, traditional analysis methods face increasing limitations, motivating the development of scalable, data-driven alternatives. This thesis presents SpecPT, a transformer-based deep learning framework for general-purpose spectroscopic analysis, with a focus on redshift estimation. The model is first trained on DESI Early Data Release spectra from the Bright Galaxy and Emission Line Galaxy samples, jointly performing spectral reconstruction and redshift regression while learning a latent representation that captures the intrinsic properties of galaxies. SpecPT is then extended to a …
Enhancing Adversarial Robustness In Convolutional Neural Networks By Integrating Human Viewing Strategies, Diana Velychko
Enhancing Adversarial Robustness In Convolutional Neural Networks By Integrating Human Viewing Strategies, Diana Velychko
Theses
Adversarial examples pose a serious threat to the reliability of deep neural networks by subtly manipulating inputs to induce incorrect outputs. Despite progress in the field, convolutional neural networks (CNNs) remain vulnerable to such perturbations. This research proposes a novel approach to improve adversarial robustness of CNNs by incorporating human viewing behavior into both training and testing processes. To establish a baseline for comparison with models trained from scratch, an eye-tracking dataset—collected during experiments involving novel objects from the Greeble dataset—was used to capture how humans learn to classify previously unseen object categories. This study compares model saliency with human …
Design That Builds Communitites: An Evaluation Method For Analyzing, Assessing, And Improving The Way We Plan And Design The Places Around Us, Devine Karas-Gonzalez
Design That Builds Communitites: An Evaluation Method For Analyzing, Assessing, And Improving The Way We Plan And Design The Places Around Us, Devine Karas-Gonzalez
Theses
The places around us shape and impact on the way we interact and live within our communities. As such, it is important to place greater emphasis on designing spaces which are meant to better respond to the needs and functions of a place. With an architectural design process this will result in the use of design strategies which will inform much of the design. In this research, multiple design strategies (Smart Growth, Placemaking, Place Value, and Street Experiments) are evaluated and compared using four regionally similar cities to analyze and assess how the different strategies impact the design process by …
Predicting Hollywood Movie Success Using Predictive Machine Learning Algorithms, Saeed Alghabshi Hathboor
Predicting Hollywood Movie Success Using Predictive Machine Learning Algorithms, Saeed Alghabshi Hathboor
Theses
The Decision Trees are always simple to understand and interpret techniques, a single tree may not be enough for the model to learn the characteristics from. In this IMDb movie review prediction problem, evading all other simple mechanisms, the Random Forest, on the other hand, is a "Tree"-based algorithm that makes judgments by combining the attributes of numerous Decision Trees is used. The primary goal of this work is to evaluate the predictive performance of a random forest model with various parameters used for forecasting numerical user ratings of a movie based on pre-release data such as actors, directors, profit, …
The Petrological And Geochemical Analysis Of The Grant Intrusive Breccia And Vaughn Intrusive Within Hicks Dome, Hardin County, Illinois, Aaron Michael Beirl
The Petrological And Geochemical Analysis Of The Grant Intrusive Breccia And Vaughn Intrusive Within Hicks Dome, Hardin County, Illinois, Aaron Michael Beirl
Theses
Hicks Dome is a crypto-volcanic feature found in the southeastern corner of Hardin County, Illinois. The dome formed around 270 Ma (late Permian), as part of the Permian Wauboukigou Igneous Province (PWIP), through a series of explosive igneous intrusions that caused uplift and clear structural deformation to the area. There was not enough magma feeding the intrusions to breach the surface, but due to the unique geochemistries of the magma(s), these intrusions formed amalgamations of alkaline, carbonatitic, and ultramafic gabbros. The overall geochemistry of these intrusions have high amounts of iron (Fe) and calcium (Ca), with relatively low amounts of …
Using Equivalence-Based Instruction And Behavioral Skills Training To Teach Social Skills, Alexander Orzeck
Using Equivalence-Based Instruction And Behavioral Skills Training To Teach Social Skills, Alexander Orzeck
Theses
Social skills are an integral part of human life, so it stands to reason that teaching methodologies should be developed to instruct people in this complex topic. One method to teach social skills has been behavioral skills training, in which the four-step sequence of vocal and written instruction, modeling, roleplay, and feedback exposes learners to the social concepts until a mastery criterion is reached. Skills relevant to socialization have also been taught with equivalence-based instruction, in which the concept of stimulus equivalence is employed to generate novel relations between stimuli for the purpose of teaching some skill. No instance was …
Layer-Wise Prediction Of Overhang-Related Geometric Deviation In Metal Additive Manufacturing With Conditional Generative Adversarial Networks, Himal Sapkota
Theses
Ensuring dimensional precision in parts with complex overhangs is a significant concern in Metal Additive Manufacturing (MAM), as undetected geometric deviations can compromise functionality and reliability. This research introduces a Conditional Generative Adversarial Network (cGAN), specifically the Pix2Pix framework, to predict layer-wise geometric deviations in Laser Powder Bed Fusion (LPBF) printed parts with overhang geometries using paired 2D CAD slices and corresponding X-ray Computed Tomography (XCT) based ground truth images. A key innovation is using RGB color-coded CAD slices to encode overhang angle information, enhancing feature distinction and prediction accuracy compared to non-color-coded inputs. Eighteen Pix2Pix models were trained across …
Design Of A 32-Bit 4-Phase Asynchronous Risc-V Processor, Sean Jacobs
Design Of A 32-Bit 4-Phase Asynchronous Risc-V Processor, Sean Jacobs
Theses
As microchips become more complex, smaller, and faster, the clock skew and power consumption present significant design challenges. Asynchronous circuits offer a solution to these issues by replacing the global clock routing with handshaking circuitry. This thesis details the implementation of an asynchronous 32-bit RISC-V processor leveraging 4-phase bundled data handshaking to replace the clock used for synchronization. Key contributions include the development of a 4-stage pipelined RISC-V compliant processor architecture adapted for asynchronous operation, the design of a custom 45nm C-element cell crucial for handshaking synchronization, and analysis of its performance in terms of area, timing, and power. This …
Design Of A Posit Based 6-Bit Configurable Cnn Hardware Accelerator For Audio And Image Classification, Steven Ng
Theses
The rapid development and growing interest in Artificial Intelligence (AI) have resulted in a trend of models increasing in size and complexity at an accelerating rate. These larger models have demonstrated a greater ability to accomplish increasingly sophisticated tasks compared to smaller models, furthering the trend of making models larger. However, as the models continue to improve and grow larger, this has created a new challenge in deploying them into practical applications. Current models typically run inference on the same systems where they were trained. Large data centers comprising Central Processing Units (CPUs) and Graphics Processing Units (GPUs) are well-suited …
Global Trail: Interactive Travel Memory System For Unesco Sites, Anne Sophie Beatrice Min Fa
Global Trail: Interactive Travel Memory System For Unesco Sites, Anne Sophie Beatrice Min Fa
Theses
Global Trail is an interactive mobile app designed for travellers or culture seekers to reimagine how they discover new places, engage with cultural sites and remember their travel experiences. In this digital world, photos get easily lost in phone galleries and sometimes lack an organized way to find specific memories to places visited. Through design, the app experience addresses three core objectives: Discover — users explore Unesco sites represented by badges through an interactive world map; Engage — they unlock and earn those badges when they visit those sites where they can post their memories on a community platform; and …
Multiplex Leiden Optimized Dynamic Network Microsegmentation And Flow Validation For Software Defined Networks, Rashed Husni Rashed Alnuman
Multiplex Leiden Optimized Dynamic Network Microsegmentation And Flow Validation For Software Defined Networks, Rashed Husni Rashed Alnuman
Theses
Modern digital infrastructure is fundamentally built upon robust networks, which underpin seamless communication, data exchange, and the operation of critical systems. These networks facilitate everything from internet access and real-time patient vital sign transfers in healthcare to the management and control of industrial processes. As demands on networks have surged, their complexity and functionality have evolved significantly, continuously adapting to diverse sectoral needs. However, this rapid evolution has also amplified security challenges. The escalating scale and intricacy of contemporary networks have exposed vulnerabilities that traditional perimeter-based security models are often insufficient to counter. Static defenses prove inadequate in dynamic environments …
How Dust Impacts Galaxy Evolution In The Early Universe With Champs: Data Reduction And Source Detection, Felix Martinez
How Dust Impacts Galaxy Evolution In The Early Universe With Champs: Data Reduction And Source Detection, Felix Martinez
Theses
How dust impacts galaxy evolution in the early universe is largely unconstrained due to under sampling in the rest-frame far-IR. New detections of optically dark galaxies (galaxies that have no rest-frame optical counterparts) have shown that there is a population of galaxies that have largely gone undetected due to this under sampling. CHAMPS (PI: A. Faisst) is designed to study how dust impacts galaxy evolution in the early universe by complimenting MIRI and NIRCam observations from JWST in COSMOS-Web and PRIMER with new ALMA observations focused at 1.2 mm (ν = 250 GHz). This thesis presents the data reduction and …
Product, Process, And Behavior Influences On Value Retention Processes: Toward A Circular Economy In Consumer Electronics, Kyle Parnell
Product, Process, And Behavior Influences On Value Retention Processes: Toward A Circular Economy In Consumer Electronics, Kyle Parnell
Theses
Consumer electronic products (CEP) manufacturing and retail contribute markedly to global industrial activity; worldwide estimates suggest revenue growth from $1 trillion in 2020 to $1.5 trillion by 2026. Consequently, the production, distribution, use, and end-of-life (EOL) disposition of these products are responsible for considerable social and environmental impacts, including 35 million metric tonnes of waste to landfill per year, 793 million metric tonnes (MMT)—and growing—of carbon dioxide-equivalent (CO2e) greenhouse gas (GHG) emissions per year, and innumerable adverse effects on human health and development. Driving these impacts are the inherent characteristics of CEPs themselves, which increasingly require critical materials in design, …
Advancing The Utility Of Unmanned Aerial Systems (Uas)-Based Imaging Techniques In Broadacre Agriculture: A Multimodal Case Study On Table Beets, Mohammad Shahriar Saif
Advancing The Utility Of Unmanned Aerial Systems (Uas)-Based Imaging Techniques In Broadacre Agriculture: A Multimodal Case Study On Table Beets, Mohammad Shahriar Saif
Theses
Efficient and sustainable food production and management are growing concerns in the context of an ever-increasing global population. It is in this context that the integration of remote sensing with advanced imaging technologies presents transformative opportunities for data-driven decision-making in agriculture. This study therefore explores the use of unmanned aerial systems (UAS) equipped with multispectral, hyperspectral, and LiDAR sensors for the non-destructive monitoring of table beet (Beta vulgaris) crop traits, with a specific focus on root yield estimation and foliar disease assessment. Table beet, a subterranean crop of increasing commercial and nutritional importance, poses unique challenges for above-canopy sensing due …
Radio Emission As A Probe Of Astrophysical Sources And Ionized Media, Olivia R. Young
Radio Emission As A Probe Of Astrophysical Sources And Ionized Media, Olivia R. Young
Theses
Broadband radio emission originates from a wide range of astronomical sources, such as the hot plasma of the middle solar corona and the exotic environments found around objects such as radio pulsars. For many of these sources, radio emission mechanisms and regions are not well understood, as they are complex and obscured from direct observation by the ionized media that the emission must traverse as it radiates outward toward the observer. Broadband radio waves from galactic astrophysical sources are delayed and distorted on their paths toward the Earth as they pass through the free electrons that compose a variety of …
Towards A Foundational Framework For Real-World Active Learning: Theory, Algorithms, And Applications, Dayou Yu
Theses
While supervised learning has seen great success in the modern machine learning era, the challenge of obtaining high-quality labeled training data still exists. In many knowledge-rich domains, we still face the problem of letting machine learning models learn well using a limited number of labels. Active learning (AL) has been a prominent learning paradigm that deals with such problems. This thesis reviews the classical challenges of AL, summarizes how our prior work has advanced the field, and charts a course for adapting AL to realistic and challenging scenarios. We begin by discussing past work on standard scenarios for AL, including …