Digital Commons Network^™

Adapting Independent Large-Scale Pretrained Models For Human Action Recognition, Selen Pehli̇van

Turkish Journal of Electrical Engineering and Computer Sciences

Transferring knowledge from large-scale, independently pretrained image and text models to video understanding requires addressing several challenges, including maintaining generalization capabilities of models, integrating them into multimodal architectures, and fine-tuning with temporal dynamics. This study evaluates the effectiveness of parameter-efficient fine-tuning (PEFT) techniques in transferring pretrained knowledge from two independent models for video action recognition within a simple, streamlined multimodal fusion pipeline. Specifically, we adapt CLIP as the text branch and DINOv2 as the image branch, keeping both backbones frozen to preserve their pretrained robustness, while introducing lightweight, task-specific modules to adapt and fuse the branches with temporal dynamics. A …

What Is The Skeleton Of Cognition? A Structural Account Of World Reconstruction Through Processing Axes, Griselda Poe

Publications and Research

This paper describes how the placement of a single processing axis reorganizes human cognition and generates a reconstructed world.

Most existing psychological and social theories begin from emotion, desire, morality, or social behavior. In doing so, they have discussed what forms on top of the cognitive skeleton without first fixing the skeleton itself. When the skeleton is not fixed, entirely different explanations of the same phenomenon can coexist, and it becomes difficult to identify which constitutes a foundational account.

This paper fixes the skeleton first. That skeleton is the processing axis.

The question is: when a single processing axis organizes …

Degrees Of Access: The Role Of Family Education In Applying To Graduate School, Emma Tweed

Math and Computer Science Honors Theses

Access to graduate education in the United States remains heavily stratified by structural, financial, and informational barriers. While undergraduate first-generation student outcomes are widely studied, fewer structural analyses examine how graduate-level “educational inheritance” shapes prospective applicants' navigational capital, particularly within competitive STEM fields like mathematics. Drawing upon theories of social capital and the “hidden curriculum,” this study investigates the relationship between an individual's knowledge of the graduate school application process and the highest level of education attained by an immediate family member.

Using the Knowledge-GAP survey instrument funded by the National Science Foundation, data were collected from a diverse sample …

The Extraction And Chemical Characterization Of The Avian Pigments Turacin And Turacoverdin, Sarah R. Bekkali

Honors Scholar Theses

Bird coloration is a trait that extends beyond mere aesthetics as it has an extensive range of biological significance. Plumage patterns and hues can influence camouflage, mate choice, social dominance, and physiological performance. Bird fitness, their ability to survive and reproduce, is greatly dependent on color. Melanins, carotenoids, and pterins are well-studied pigment systems that are commonly found across many avian species’. Alternatively, porphyrin-based pigments are rare and less-studied as they only found in turacos a sub-Saharan African bird belonging to the family Musophagidae. This thesis focuses on two pigments of interest: turacin, the deep crimson-red pigment found in …

Saving The Great Basin: Creating Places For The Birds, Bees And Beyond, Carlos Gomez

Hospitality Design Graduate Student Capstones

This project looks at how vacant and underused parcels along the Truckee River in Reno, Nevada, can be rethought as part of a larger ecological system. Rather than treating these parcels as empty leftover spaces, the project sees them as opportunities to create small habitat patches that can support native species, improve stormwater function, and strengthen the river corridor over time. The work focuses on three sites along the Truckee River: California Avenue, Island Avenue, and Commercial Row. Each site responds to a different condition along the urban transect, from a sloped residential river edge to a tighter urban parcel …

The Biowell System: An Integrative Framework That Connects Ecological Sustainability And Mental Wellbeing Through The Regenerative Processes Of Bioswales, Nathan A. Bussa

Hospitality Design Graduate Student Capstones

The Biowell System is an evaluative framework that connects ecological sustainability and mental well-being through the regenerative processes of bioswales.

Semi-Rational Strategies For Antifungal Peptide Design, Akilah I. Mateen

Seton Hall University Dissertations and Theses (ETDs)

A recently emerged opportunistic fungi, Candida auris, has been subject to increased scrutiny due to its virulence and rapid geographical spread. Due to the indiscriminate use of antimicrobials as treatments for infectious diseases and as pesticides, the ubiquitous threat of multidrug resistance (MDR) looms large. The lack of progress in antifungal development is of high concern in the treatment of infectious diseases and a rise in fungal resistance highlight the need for updated treatment strategies. This work describes three strategies used to address these concerns:

•  The synthesis of a photosensitizer-membrane-active peptide (PS-MAP) conjugate, Ir-HKII15, that combines the ability of …

Subject: Quarterly Operations And Maintenance Report Grove Gulch Sedimentation Bay For Fourth Quarter 2025 And First Quarter 2026 Silver Bow Creek/Butte Area Npl Site – Butte Priority Soils Operable Unit Consent Decree-Civil Action No. Cv 89-039-Bu-She, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Micromagnetic Simulations Of Field-Driven Antiferromagnetically Coupled Skyrmions, Aidan D. Kirk

Physics and Astronomy Honors Papers

Competing magnetic interactions can stabilize smooth magnetization textures and can be characterized by a topological winding number. A specific spin configuration/texture, spatially localized within a two-dimensional plane, is commonly known as a skyrmion. On the classical level, the significance of skyrmions for condensed matter physics and their potential for applications, ranging from spintronic devices to qubits, has been intensely investigated in recent years. This thesis focuses on antiferromagnetically (AF) coupled Neel-type magnetic skyrmions, which are comprised of two skyrmions with opposite topological charges, yielding a net topological charge of 0. This configuration results in the cancellation of their respective Magnus …

Accuracy Of Parameter Estimation For A Simple Gene Regulatory Network Model Is Sensitive To Network Motif, Number Of Parameters Estimated, And Magnitude And Direction Of Regulatory Relationships, Nikki C. Chun, Kam Dahlquist

Honors Thesis

A gene regulatory network (GRN) is a set of transcription factors that regulate the expression of genes encoding other transcription factors. The dynamics of a GRN explain how gene expression changes over time. GRNmap is a MATLAB software package that uses ordinary differential equations to model dynamics of small-scale GRNs. We used the program to estimate production rates, expression thresholds, and regulatory weights for each transcription factor in three related literature-derived GRNs based on yeast cold shock microarray data previously collected in the Dahlquist Lab. We noticed large differences in estimated weight values when 1-2% of the expression values were …

Phase Field Modeling And A Fully Discrete Numerical Scheme For Two-Phase Incompressible Mhd Flows With Different Densities, Electric Conductivities And Viscosities, Xiaoyong Chen, Rui Li, Jian Li, Xiaoming He, Yanping Lin

Mathematics and Statistics Faculty Research & Creative Works

This article establishes a phase field model for governing the two-phase incompressible MHD flows with different densities, electric conductivities, and viscosities. In addition to the coupling between the Cahn–Hilliard phase field equations and the single-phase MHD equations together with the varying parameters, it is physically faithful and mathematically rigorous for the modeling to incorporate a relative flux term, which is related to the diffusion of the components, into the coupled system, inspired by Abels et al. and Shen and Yang. We present a linear fully discrete numerical scheme for this complex multi-physics system, which leverages the artificial compressibility method, an …

An Evaluation Of Artificial Intelligence Chatbots As Alternatives To Specialized Software In Teaching Bayesian Pharmacokinetic Analysis, Reza Mehvar

Pharmacy Faculty Articles and Research

Objective

Methods

Welcome Tilly Norwood: Forecasting Hollywood’S Ai Policy Futures, Samuel P. Rooker

Senior Honors Projects, 2020-current

In late 2025, weekly trade publication Variety Magazine reported on the announcement of a new acting talent in Hollywood: Tilly Norwood. Norwood is an industry outsider and the pet project of Eline Van der Velden, who unveiled the actress’ existence to the world at the Zurich Film Festival. The announcement quickly gained media coverage while Van der Velden has since faced cyclical backlash from Hollywood trade unions, which does not seem entirely without reason. Tilly Norwood is a digital persona, a generative artificial intelligence (GenAI) program, designed by Van der Velden’s novel AI talent studio, Xicoia, to become the next …

Shelters In Motion, Erin Nicole Vallido Trasmano

Hospitality Design Graduate Student Capstones

Shelters in Motion is a modular temporary shelter system for festival and outdoor events that replaces disposable tents with reusable, durable design. Overall reducing environmental impact while significantly improving comfort and user experience.

A Descriptive Analysis Of Plant Leaf Disease Detection Using Machine Learning And Deep Learning Models: A Systematic Review, Arzoo Chamoli, Anuj Kumar

Turkish Journal of Electrical Engineering and Computer Sciences

Plant leaf disease detection (PLDD) is a growing active research area with burgeoning practical applications across various sectors such as agricultural monitoring, food security, and environmental conservation. Accurate segmentation and classification of plant leaf diseases remains a key challenge in the field of plant leaf disease prediction. The challenge demands automated methods for the plant disease identification because it needs to develop better crop management systems, which will boost agricultural production. In this article, we provide a systematic review of various machine learning (ML) and deep learning (DL) methods extensively used for PLDD. The review strategy follows a formal protocol, …

Complex-Valued Convolutional Neural Network With Time-Frequency Representation For Electrocardiogram-Based Arrhythmia Detection, Kajeeth Kumar Gurusamy, Muthurajkumar Sannasy

Turkish Journal of Electrical Engineering and Computer Sciences

This research proposes an end-to-end procedure for arrhythmia detection based on electrocardiogram (ECG) signals using complex-valued convolutional neural network (CVCNN) incorporated with time-frequency representation. The proposed model leverages complex numbers to capture amplitude and phase information that enhances the ability of the model for detecting time-frequency variation in cardiac signals. First, signal preprocessing techniques---including normalization, wavelet denoising, and R-peak detection---are applied. Subsequently, the model extracts complex features from raw ECG data by employing the Hilbert transform to derive the analytic signal and the short-time Fourier transform (STFT) to generate a time–frequency representation. The proposed CVCNN framework effectively learns spatial-temporal features …

Multiobjective Optimization Framework For Renewable Energy Iot Networks Balancing Security, Energy Efficiency, And Communication Reliability, Muhammad Hjouj Btoush, Ashraf S. Mashaleh, Amjad Gawanmeh

Turkish Journal of Electrical Engineering and Computer Sciences

The deployment of Internet of things (IoT) networks powered by renewable energy sources presents unique challenges in balancing security requirements, energy efficiency, and communication reliability. This paper presents a comprehensive multiobjective optimization framework for secure renewable energy IoT nodes that addresses fundamental trade-offs between these competing objectives. We develop a mathematical model incorporating energy harvesting dynamics, security protocols, and communication performance metrics across various environmental scenarios. The proposed framework employs a modified NSGA-II algorithm to identify Pareto-optimal configurations for different deployment contexts. Through extensive simulation analysis, we demonstrate that hybrid energy sources (solar-wind combinations) with lightweight security protocols achieve optimal …

Predictive Current Control Approach For Grid-Integrated Multifunctional Converter Under Source And Load Disturbances, Ravi Kumar Majji, Tirumalasetty Chiranjeevi, Chilukoti Varaha Narasimha Raja, Nagulapati Kiran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper discusses and presents a model predictive control (MPC)-based predictive current control technique for a solar photovoltaic (PV)-integrated grid system during dynamic operation. This control technique employs extension pq (EPQ) theory to estimate reference currents and utilizes an MPC framework for tracking reference currents. Various MATLAB/Simulink simulations were conducted for solar PV generation (source disturbances) and dynamic loading. The results of the OPAL-RT OP4510 real-time simulation are also presented. A multifunctional grid-integrated converter (MFGC) integrates solar active power into the utility grid while achieving unity power factor, reactive power compensation, current balancing, and harmonic suppression. EPQ optimizes mathematical calculations, …

The Origins Of Chondrite Families, Isabelle M. Perron

UNLV Theses, Dissertations, Professional Papers, and Capstones

Chondrites, a type of primitive asteroid, are thought to have formed from dust and gas early in the life of our Solar System. These chondrites have remained unchanged since their formation, avoiding being melted or differentiated like other rocky bodies have. Due to this unique characteristic, chondrites can give us useful insight into how asteroids, planetesimals, and even the terrestrial planets formed. In order to study chondrites and their formation, I used code developed by Li et al. (2020), which utilizes thermodynamic code GRAINS (Petaev 2009), to see what conditions the chondrites may have originated from. GRAINS uses a variety …

Preservation Of Sedimentary Rubidium Isotopic Signatures In Subduction Zones: Insights From The Schistes Lustrés Hp-Uhp Metasediments, Western Alps, Mary Clarich

UNLV Theses, Dissertations, Professional Papers, and Capstones

When oceanic plates bend and sink into the mantle at subduction zones, they carry sediments from the surface down into the mantle. The recycled sediments contain elements, that are depleted in the mantle, thereby influencing the composition of the mantle wedge and the formation of arc magmas, which are the building blocks of juvenile continental crust. However, it remains poorly constrained how much these elements, particularly fluid-mobile elements such as rubidium (Rb), are lost into fluids during metamorphic dehydration, and how much is transported to sub-arc depths where arc magmas are generated. Rubidium in subducting sediments is mainly hosted in …

Harnessing Backcasting To Identify Drivers Of Critical Warming At Hoover Dam Using Hydrodynamic And Machine Learning Models, Eunice Ledres

UNLV Theses, Dissertations, Professional Papers, and Capstones

Elevated water temperatures can pose a significant threat to dam infrastructure, potentially damaging turbines, overheating internal components, and forcing generator shutdowns. This study uses a backcasting framework to evaluate how future scenarios may result in elevated water temperatures. Backcasting defines undesirable outcomes and works backward to identify the conditions that lead to them. The developed backcasting framework integrates 3D physics-based simulations with a Long-Short Term Memory (LSTM)surrogate model and SHapely Additive exPlanations (SHAP) interpretation. The combination captures temporal water temperature dynamics and quantifies the contributions of different drivers to elevated water temperature releases. As proof of concept, these methods are …

Constructing A Laser Stabilization System For Frequency Metrology, Stephanie Letourneau

UNLV Theses, Dissertations, Professional Papers, and Capstones

Frequency metrology and quantum control, which uses light as a tool for measurement and manipulation, relies on spectrally narrow, stable lasers. Often thought of as being perfectly monochromatic and coherent, in reality, the free-running instantaneous linewidth of lasers can be on the order of hundreds of kHz in the millisecond time-frame and drift on the order of tens of MHz over hours. To correct for these instabilities in real-time, a variety of laser stabilization methods have been implemented, including the Pound-Drever-Hall (PDH) method, saturation absorption spectroscopy (SAS), and dichroic atomic vapor laser locking (DAVLL). All of these methods rely on …

Thermal Physiological Ecology Of The Relict Leopard Frog At Hot And Cold Springs, Robert P. Pelletier Iii

UNLV Theses, Dissertations, Professional Papers, and Capstones

The relict leopard frog (Rana onca) once ranged across drainages in southern Nevada, northwestern Arizona, and southwestern Utah. Following a decline, the species only persisted in a few geothermally influenced hot springs, which led to the perspective that hot springs were high-quality habitat. Rana onca has been under intensive, multiagency management and the species has been translocated to establish additional populations, including at cold-water sites. Three research studies are presented into the thermal physiological ecology of R. onca with the aim of informing conservation strategy. The research was focused at a thermally influenced hot spring and a cold-water spring to …

A Pedagogically Effective Conceptual Framework For The Resilience Of Unit Test Suites To Refactoring, Daniel Paul Knight

Theses and Dissertations

Unit test suites are intended to support safe and efficient source code refactoring, yet in practice they can hinder rather than help when tests are tightly coupled to implementation details. Such non-resilient tests require frequent co-evolution, consume valuable engineering time, and may disincentivize beneficial code improvements. While concepts such as passive and active resilience, test smells, and technical debt have been studied individually, they have not been integrated into a single actionable framework, nor has their pedagogical value been systematically evaluated. This dissertation introduces a novel conceptual framework for the resilience of unit test suites to refactoring, grounded in resilience …

Classification Of Hif Detection In Nev Profile Using Wavelet Transform And Convolution Neural Network, Abdul Hafiz Kassim, Mohd Abdul Talib Mat Yusoh, Aster Smith Valentinie Wilson Nottelmarc, Ahmad Farid Abidin, Sim Sy Yi, Daw Saleh Sasi Mohammed

Turkish Journal of Electrical Engineering and Computer Sciences

High impedance faults (HIFs) present a critical challenge in power systems due to their subtle signal characteristics, which often remain undetected by conventional protection methods. These faults typically do not produce significant phase disturbances, making reliable detection difficult. However, analysis of the neutral-to-earth voltage (NEV) profile under fault conditions provides a promising alternative for fault identification. Existing approaches for detecting and classifying HIFs using NEV signals remain limited and may result in inaccurate maintenance decisions. This paper proposes a fault classification framework for multiple fault types, including HIF, three-phase fault, three-phase fault to ground, double line, double line to ground, …

Accurate Diagnosis Of Diseases By A Novel Ai Pipeline Based On Feature Extraction, Feature Ranking, And Feature Selection From Medical Images, Tuğba Nur Bozkurt, Mehmet Emi̇n Yüksel

Turkish Journal of Electrical Engineering and Computer Sciences

The rapid growth of the global population has led to a substantial increase in the number of patients, while the availability of healthcare professionals has not expanded at a comparable rate. This imbalance highlights the urgent need for efficient and reliable computer-aided decision support systems that can reduce clinical workload while maintaining high diagnostic accuracy. In this study, a novel and systematically integrated artificial intelligence-based pipeline is proposed for medical image classification, combining statistical significance-driven feature ranking with evolutionary feature selection in a unified framework. The proposed pipeline consists of four sequential stages: feature extraction, ranking, selection, and classification. Features …

Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control For Robotic Manipulators Based On Disturbance Observer, Xin Zhang, Xu Wang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an adaptive backstepping nonsingular fast terminal sliding mode controller integrated with a nonlinear disturbance observer to achieve precise trajectory tracking of robotic manipulators subject to model uncertainties and unknown time-varying disturbances. A dead-zone–based adaptive gain mechanism is introduced to dynamically adjust the control gain according to the deviation of the sliding surface, thereby enhancing robustness and reducing chattering. The proposed reaching law ensures fast, nonsingular, and adaptive convergence, suppressing high-frequency oscillations without compromising stability and the nonlinear disturbance observer enables real-time estimation and compensation of modeling errors, friction, and external disturbances for superior rejection. The semiglobal uniform …

Chaotic Artificial Bee Colony-Optimized Stacking Ensemble For Robust Multifault Diagnosis Of Wind Turbines, Veilraj Revathi, Solaimalai Jeyadevi, Madasamy Sudalaimani

Turkish Journal of Electrical Engineering and Computer Sciences

The complex electromechanical structure of wind turbines, along with harsh operating conditions, poses significant challenges for precise and robust fault diagnosis. To address this challenge, an ensemble multifault diagnostic framework based on an adaptive chaotic artificial bee colony (C-ABC)-optimized support vector machine (SVM) and gradient boosting machine (GBM) is proposed. In the proposed framework, data redundancy and overfitting are reduced through a two-stage hybrid filter-transformer-based feature reduction approach using ReliefF, followed by Principal Component Analysis. The chaos function of the proposed C-ABC maintains an adaptive balance between the exploration and exploitation phases, thereby preventing premature convergence, which is a common …

From Natural Language To Cryptographic Protocol Specifications: Evaluating Llms For Cpsa Generation, Martin Duclos

Theses and Dissertations

Formal verification can prove the security properties of cryptographic protocols, but translating natural language specifications into formal models requires specialized expertise, limiting the broader adoption of formal verification methods. This dissertation investigates whether large language models (LLMs) can lower this barrier by automatically generating Cryptographic Protocol Shapes Analyzer (CPSA) models from natural language protocol specifications. We evaluate three complementary strategies for improving LLM-based CPSA code generation through systematic experimentation across 104 protocols and 15 language models. First, we analyze prompt engineering and find that moderate structured guidance yields the most accurate outputs, while excessive prompt complexity degrades performance. Second, we …

Validation And Implementation Of Automated Planning Optimization In Utah Valley Hospital, Oluwatobi Adeniji

UNLV Theses, Dissertations, Professional Papers, and Capstones

The increasing complexity of modern radiotherapy demands planning workflows that are efficient, standardized, and dosimetrically robust across diverse disease sites. Knowledge-based planning (KBP) systems such as RapidPlan offer a data-driven approach to automate and improve treatment planning by learning geometric–dosimetric relationships from high-quality clinical plans. In this work, I am evaluating the performance, generalizability, and clinical applicability of vendor-provided RapidPlan models across seven anatomical sites: intracranial SRS, prostate SBRT, right and left lung SBRT, liver SBRT, head and neck, and glioblastoma. Subsequently, a complementary institution-specific SRS model tailored to single-isocenter multitarget workflows was created. Seventy retrospectively selected patients were replanned …