Physical Sciences and Mathematics Commons^™

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 …

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 …

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 …

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 …

Evaluating The Spatial Relationship Between Geomorphology And Subsurface Structures On The Us Atlantic Margin With Applications To Other Terrestrial Planets, Andrea Caitlyn Stiles

Theses and Dissertations

High-resolution digital elevation models (DEMs) are widely available for terrestrial planetary bodies, but subsurface structural data remain limited. This research evaluated whether surface geomorphology could predict subsurface features, specifically faults and methane seeps, along the US Atlantic continental margin as an analog site. Faults were mapped with seismic interpretation and compared with quantitative geomorphic classifications derived from 100-m bathymetry including slope, aspect, rugosity, bathymetric position index, and geomorphon classes. Maximum-entropy modelling was used to predict fault occurrences from surface data. Results indicated that specific geomorphic landforms and slopes had the strongest control on fault presence, reflected in topographic expression of …

Integrating Augmented Reality Visualizations Into Data Science Notebooks Using Microsoft Hololens 2, Derek Willis

Theses and Dissertations

Data-science notebooks support iterative analysis but are limited to two-dimensional (2D) displays. This work presents an approach to extend such environments with rapid augmented reality (AR) visualization while preserving conventional 2D workflows. An opensource R package was developed to convert notebook objects into three-dimensional (3D) models, export them in the Graphics Language Transmission Format (glTF), and transfer directly to a Microsoft HoloLens 2 via a USB connection for viewing in the native 3D Viewer application. The proposed workflow eliminates manual conversion and transfer steps required by earlier methods. A user study employing a post-session questionnaire indicated that participants found the …

Assessing The Relationship Between Subsurface Geology And Surficial Geomorphology: Remotely Predicting Geologic Features And Geohazards Using An Elevation-Trained Machine Learning Algorithm In The Northern Gulf Of Mexico, Allison L. Wing

Theses and Dissertations

This thesis evaluates the capacity to predict subsurface geologic features and submarine landslide susceptibility using surficial geomorphology derived from bathymetric elevation data in the Northern Gulf of Mexico. Quantitative geomorphic variables including slope, curvature, aspect, rugosity, geomorphons, and Bathymetric Position Index were generated from 30-meter digital elevation models and used as explanatory variables in presence-only Maximum Entropy models. Known locations of faults, pockmarks, mud volcanoes, hydrocarbon seeps, and landslides (particularly intact scarps) were used to train and validate predictive models through k-fold cross validation. Model performance was assessed using omission rates and AUC values. Results demonstrate that specific geomorphic signatures, …

Regional Variability In Tornado Tracks: A Gis-Based Study Of Surface Roughness And Land Cover Differences Between The Lower Midwest And Southeast United States, Joshua Morgan Dison

Theses and Dissertations

Throughout the years, much research has been dedicated to the physical processes leading to tornadogenesis and tornado decay. Much of this research is centered around the inner workings of the supercell itself. Recent studies are now showing that tornadogenesis and decay processes may be generated by interactions with the Earth’s surface. This study examines longtrack tornadoes from 2001-2016 in the southeast and lower Midwest regions of the United States. Utilizing the National Land Cover Database (NLCD) and American Meteorological Society / Environmental Protection Agency / Regulatory Model (AERsurface) surface roughness values, efforts are made to see if statistical significance is …

Adaptive Channel Switching For Contention Resolution, Shafqat Hasan

Theses and Dissertations

Contention resolution is a fundamental problem in distributed computing, where multiple devices compete to transmit over a shared channel without centralized coordination. Classical models typically assume a single always-available channel and focus on minimizing makespan. However, modern wireless systems increasingly operate under spectrum-sharing frameworks in which access to high-capacity spectrum is opportunistic and may be interrupted by higher-priority users. These settings introduce new challenges, including asymmetric channel speeds, adversarially scheduled evictions, and non-trivial switching costs. In this thesis, we study contention resolution in a dual-channel model consisting of a slow, always-available channel and a faster channel subject to adversarially scheduled …

Low-Dimensional Metal Halides For Light-Emitting Diodes (Leds): Photophysical Aspects And Device Engineering, Udara Madushanka Kuruppu Kuruppu Achchige Don

Theses and Dissertations

In recent years, low-dimensional metal halides have garnered significant interest due to their exceptional optical properties. This dissertation focuses on the structural, optical, and photophysical properties of both lead-based and lead-free low-dimensional metal halides and investigates their applications in light-emitting diodes. In Chapter II, the nature of Mn2+ doping in two-dimensional (2D) lead halide perovskites is discussed. 2D perovskites show strong excitonic and dielectric confinement due to their quantum well structures. Introducing optically active Mn²⁺ dopant ions into these 2D perovskites further enhances their optical properties and promotes energy transfer from the host to the Mn²⁺ dopants, resulting in dual …

Parhsom: A Novel Parallel Hierarchical Self-Organizing Map Implementation, Rebekah E. Lane

Theses and Dissertations

The digital age has completely transformed the way that information is processed and stored, which makes cybersecurity a crucial field of research. Cybersecurity contains many different domains, but this work focuses on Intrusion Detection Systems (IDSs). Within the literature, Hierarchical Self-Organizing Maps (HSOMs) have been used to create trustworthy, explainable, and AI-based IDSs. However, HSOMs are trained sequentially, which means that training HSOMs on large datasets is slow. This work presents a novel parallel HSOM architecture, called parHSOM. The purpose of this research is to investigate the effect that parallel computation has on the HSOM training time. parHSOM is tested …

Assessment Of Local Ecological Knowledge, Oyster Predation, And Habitat Function To Improve Management Of Nearshore Habitats, Cynthia Evelyn Marie Lupton

Theses and Dissertations

Coastal ecosystems along the northern Gulf of Mexico are ecologically and economically vital yet increasingly threatened by environmental change, habitat degradation, and knowledge gaps that complicate restoration and management efforts. This dissertation integrates social and ecological approaches to improve understanding of predator dynamics, stakeholder perceptions, and habitat function related to nearshore habitats. Thereby, providing information that can inform adaptive management and restoration in the region through addressing three overarching objectives: 1) evaluate stakeholder perceptions of oyster (Crassostrea virginica) predation and management practices; 2) quantify environmental and habitat factors influencing oyster drill (Stramonita haemastoma complex) abundance; and, 3) assess the influence …

Using Seafloor Geomorphology, Classification Schema, And Spatial Analysis To Predict Geologic Structures, With Applications For Mars, Emma Morgan

Theses and Dissertations

This study evaluated whether seafloor geomorphology can be used to predict subsurface fault locations along the Cascadia continental margin and explored whether such relationships can be transferred to Mars. Geomorphological classification schemas such as geomorphons, bathymetric position index (BPI), slope, rugosity, aspect, and curvature were derived from seafloor bathymetry data and used as predictor variables in maximum entropy (MaxEnt) models developed separately for Pre-Pleistocene, Pleistocene, Quaternary, and active fault datasets. Model performance ranged from AUC = 0.62 to 0.67, showing moderate predictive skill, with younger fault systems exhibiting stronger geomorphic associations. A secondary analysis showed a weaker but detectable relationship …

Unbounded Derivations On Algebras Associated With Monothetic Groups: An Expository Thesis, Britton Phillips

Theses and Dissertations

This thesis is an expository exploration of the paper Unbounded Derivations in Algebras Associated with Monothetic Groups. Monothetic groups will be utilized to create a minimal system that gives rise to two C*-algebras, and once we have these algebras, unbounded derivations will be able to be defined on them. These derivations are able to be classified and decomposed into ”special” derivations, and these decompositions help simplify the comparisons between derivations on different algebras. In particular, we emphasize the classification, covariance properties, innerness and approximate innerness, and the lifting behavior of these derivations.

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 …

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 …

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, …

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 …

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 …

Beyond English: Auditing And Mitigating Cross-Lingual Data Contamination In Multimodal Large Language Models, Pavan Dharma Adapa

Theses and Dissertations

This thesis extends data contamination auditing for multimodal large language models to multilingual settings. Using LLaVA 1.5 and a high-fidelity French parallel dataset derived from ScienceQA, the study evaluates how performance changes when identical image-question pairs are translated from English to French. The resultsshow a substantial cross-lingual performance decline and frequent flips from correct English predictions to incorrect French predictions, indicating that benchmark performance can depend heavily on memorized English-specific patterns rather than stable multimodal reasoning. To address this weakness, the thesis introduces an inference-time mitigation strategy based on perturbation ensembling and cross-lingual consistency aggregation. The proposed method reduces instance-level …

Evaluation And Mitigation Of Bias And Toxicity In Open-Source Large Language Models Using Crows-Pairs And Bold, Sai Harika Gade

Theses and Dissertations

This thesis evaluates bias and harmful language generation in five open-source language models and tests practical mitigation methods that do not require retraining. Two masked models are assessed with a sentence-pair benchmark for stereotype preference, and three generative models are assessed with a prompt-based benchmark for harmful continuations across demographic domains. The study uses a unified experimental workflow to compare model behavior, summarize differences across bias categories, and measure changes after intervention. Results show that the masked models favor stereotypical content above a random baseline, while the generative models usually produce low average toxicity but still show uneven risk across …

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 …

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