Digital Commons Network^™

Adaptive Phishing Url Detection Using Hybrid Fuzzy C-Means Clustering And Xgboost, Muntadher Mohammed Kareem, Rawaa I. Farhan

Karbala International Journal of Modern Science

Phishing attacks continue to evolve in sophistication, rendering static detection methods increasingly ineffective. Existing URL-based approaches suffer from limited adaptability to emerging phishing patterns, mislabeled training data, and insufficient validation protocols. This paper proposes a hybrid phishing URL detection system that integrates Fuzzy C-Means (FCM) clustering with XGBoost classification, enhanced by a novel Micro Adaptive Feature Extractor (MAFE). The system employs a multi-stage pipeline: feature engineering generating 36 statistical and interaction features, MAFE producing 15 adaptive features through class-aware dynamic weighting, micro-pattern detection, and entropy analysis, and FCM with K=2 clusters providing soft membership features to XGBoost. A two-pass confidence-based …

Learning, Abstraction, And Creative Search For Interactive Agents, Jonathan Demke

Theses and Dissertations

Artificial intelligence systems are increasingly deployed as autonomous agents that interact directly with complex environments. Ensuring these agents remain reliable, adaptable, and useful presents an ongoing practical challenge. This dissertation studies agent-environment interactions through a progressive lens, examining behavior from foundational training stability and abstraction discovery to adaptation in unpredictable settings and open-ended creative search. The investigation begins by analyzing how hyperparameter settings affect early-stage Deep Q-Network performance, yielding practical guidelines for debugging reinforcement learning implementations. To address the challenge of long-horizon planning, the discovery of temporally extended options is formalized as the Minimum Shortcut Problem, demonstrating how agents can …

Wip: Developing A Generative Ai Autoethnography Assistant, Jyoti Suhag, Jennifer Drewyor, Kathryn Bugbee, Michelle Jarvie-Eggart, Lynn Albers, Leo Ureel

Michigan Tech Publications

Background: Generative AI (genAI) is transforming educational research, offering new possi-bilities for conducting interviews while local sandboxing minimizes data privacy risks and hallucinations. Purpose: This work-in-progress presents the AI Autoethnography Assistant, a project investigating how large language models (LLMs) can support autoethnographic interview design and execution. Approach: Using prompt engineering grounded in Interpretative Phenomenological Anal-ysis, paraphrasing techniques, and structured follow-up questions, we developed protocols that incorporate po-sitionality and prompt reflection on origin stories and pivotal life moments. Outcomes: Conversations conclude at the user’s discretion, with the AI generating a thematic summary. We tested refined prompts across four platforms (Gemini, Claude, …

Fragberta: A Fragment-Aware Molecular Representation Model With Sequential Attachment-Based Fragment Embeddings, Neerav Kaushal, Ajay M.N.V. Penmatsa

Michigan Tech Publications

Automated exploration of chemical space through machine learning has become a central strategy in modern drug discovery, where the ability to learn transferable molecular representations directly impacts predictive modeling performance. Recent advances in chemical language models have primarily relied on atom-level string encodings such as SMILES or SELFIES, treating molecules as sequences of individual atoms or characters. However, medicinal chemistry reasoning is often fragment-centric, emphasizing scaffolds, functional groups, and modular substructures rather than isolated atoms. In this study, we introduce FragBERTa, a molecular fragment-aware transformer-based representation language model pretrained using masked language modeling on Sequential Attachment-based Fragment Embedding (SAFE) representations. …

Development Of Minimalist Trifunctional Building Blocks For Chemical Biology Probe Synthesis, Luke E. Bohrer

Electronic Theses and Dissertations

The completion of the Human Genome Project in 2003 generated expectations that genomic information would accelerate the discovery of new protein drug targets and FDA-approved therapies. However, many small-molecule drug candidates continue to fail in clinical trials, and much of the human proteome remains undercharacterized in terms of structure, function, and disease relevance. Chemical tools are therefore essential for defining protein function, mapping protein interactions, and identifying disease-associated molecular mechanisms. Among these tools, small-molecule chemical probes provide a powerful strategy for connecting biological activity with target identification, functional analysis, and the development of effective therapies.

This dissertation describes the development …

Modeling And Simulation Of Solar Battery Charge Controller Using Adaptive Particle Swarm Optimization Mppt Algorithm, Mustafa Sacid Endiz, Göksel Gökkus

Mathematical Modelling and Numerical Simulation with Applications

Implementing an effective Maximum Power Point Tracking method is crucial for optimizing solar energy harvesting against environmental fluctuations like solar radiation and temperature. This paper introduces a novel approach for modeling and simulating a solar battery charge controller, using a modified Particle Swarm Optimization algorithm. The power stage of the system is based on a SEPIC converter, which is employed to manage the power conversion and improve the energy transfer to the battery. The developed circuit model is evaluated under various radiation levels at a constant temperature, as well as under different temperature levels at a constant radiation. Simulations are …

Secondary Water Saturation Of The Rock Mass And Quality Of Rocks In Active Mine Areas Bordering The Flooded Workings Of Closed Mines, Mirosława Bukowska

Journal of Sustainable Mining

The goal of this paper was to inspect the influence of capillary water saturation on the specific strain energy of sedimentary rocks. The relationships between the determined specific strain energies in an air-dried state and in a state of capillary water saturation for detrital rock were exponential, with a strong correlation among the variables. For silt, the relationships were described by a second-degree polynomial function, and the correlation was medium or weak. The relationships for kinetic and dissipated energy were described with a linear function. Pearson correlation coefficients indicated a strong correlation among the variables for detrital rock and a …

The Role Of Trauma-Informed Care In Supporting At-Risk Students In Alternative Education, Jar'mel D. Taylor Dr.

Transformations

Students with traumatic experiences commonly fail to meet educational goals and control their emotions while also losing their involvement in classes. Standard trauma-informed care practices remain absent from numerous alternative educational institutions, which leaves their teaching community without adequate support to help traumatized students effectively. The application of Trauma-Informed Care (TIC) strategies toward student outcomes requires investigation to develop effective educational approaches that enhance school success. The researcher used qualitative exploratory case study methodology to study TIC practices in alternative education for Black and Brown adolescent students (aged 12–18) in Washington, D.C. Semi-structured interviews and a focus group with 16 …

A Coupled Reaction-Diffusion Model Of Promoting And Suppressing Interactions Among Cancer Hallmarks In Endometrial Cancer, Jeddy Bennett

Theses and Dissertations

Spatial transcriptomics enables the scoring of Cancer Hallmarks at a high resolution across a tissue biopsy, yet current analyses of these data remain largely descriptive, treating each spot as a static, independent observation. This thesis develops a coupled system of advection-diffusion-reaction partial differential equations to model the hallmark landscape as the steady-state solution of an underlying spatial process, and casts the recovery of its physical parameters as a PDE-constrained inverse problem. The framework is implemented in FEniCSx on tissue-specific finite element meshes derived from two endometrial cancer biopsies provided by the Huntsman Cancer Institute, with subdomains, boundary interfaces, and an …

Rockin’ Rover On The Rainbow Road, Michael Kolta, Lawrence Burgee, Ying Yuan

Transformations

This paper presents a progressive series of age-appropriate lesson plans for grades K-12 that all use the same interdisciplinary activity to educate students about Science, Technology, Engineering, Art, and Mathematics (STEAM) simultaneously. Technology from Texas Instruments (TI) was employed including a TI Nspire graphing calculator that can run Python programs, a TI Innovator Hub, and a TI Rover. The TI Rover is a small, robotic car that has sensors and is controlled by the calculator via the Hub hardware interface. A Python program was developed that uses the color sensor in the Rover to detect the color on colored paper …

The Computed Microwave Spectrum Of The Protonated Fullerene C60H+, Laszlo Nemes, Jos Oomens, Vincent J. Esposito, Vincent Boudon, Alexander G. G. M. Tielens

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The largest known molecule in the interstellar medium of galaxies, C₆₀, has been detected in its neutral and cationic form through its vibrational, UV-driven fluorescence emission spectrum and its electronic absorption spectrum, respectively. The detection of several polycyclic aromatic hydrocarbon molecules through their pure rotation spectrum in cold, dense, molecular cloud cores suggests that C₆₀ might be present in these environments as well. The low flux of UV pumping photons in molecular cloud cores and the absence of suitably bright background stars, make detection of C₆₀ and its cation through the commonly used methods impractical. As …

Real Bullets, Plastic Guns: Evaluating The Strength Of 3-D Printed Gun Parts, Maria Latenia Mayol

Student Theses

Privately made firearms (PMFs), often referred to as “ghost guns,” are firearms manufactured or assembled by individuals rather than federally licensed manufacturers. Although the terms are frequently used interchangeably, “ghost gun” more specifically describes an unserialized firearm, whereas PMFs include a broader range of firearms produced through nontraditional manufacturing methods. PMFs may be entirely 3-D printed, assembled from partially completed firearm kits, or constructed by integrating additively manufactured components with commercially manufactured firearm parts. The increasing accessibility of additive manufacturing and widespread dissemination of computer-aided design files have raised concerns about concealment, regulation, and forensic evasion, particularly when factory-manufactured components …

A Granularity-Centered Taxonomy Of Personalized Federated Learning, Ei Ei Nyein Chan, Sergei Chuprov, Pretom Roy Ovi, Kamrul Hasan

Computer Science Faculty Publications

Personalized Federated Learning (PFL) has emerged as a key approach to address performance degradation in FL systems under heterogeneous client data. While existing surveys typically categorize PFL methods based on optimization strategies or system-level mechanisms, they often overlook a fundamental question: where is personalization embedded within the model architecture? In this survey, we bridge this knowledge gap and introduce a granularity-centered taxonomy that organizes PFL approaches according to the structural depth of personalization, ranging from head-layer and layer-wise adaptation to model-wise and parameter-wise customization. This novel perspective helps practitioners select appropriate personalization strategies based on model architecture, data heterogeneity, and …

Modeling Formation Of Turbulent Sporadic-E Clouds Using Realistic Wind Data, Aaron M. Schinder, Kenneth S. Obenberger, Jorge L. Chau, Juan M. Urco, Matthias Clahsen, Benjamin F. Akers, Daniel J. Emmons

Faculty Publications

A high resolution two-dimensional multi-fluid model of sporadic-E layers was developed and driven with physically realistic mesosphere, lower thermosphere (MLT) winds measured over Albuquerque, New Mexico. The realistic E-region winds are produced by the HYdrodynamic Point-wise Environment Reconstructor (HYPER) model that ingests meteor derived wind observations from a Spread-spectrum Interferometric Multistatic meteor radar Observing Network (SIMONe) system combined with the Navier-Stokes equations to provide high resolution three-dimensional wind fields over time. Sporadic-E dynamics are simulated using both realistic winds from HYPER as well as idealized hyperbolic tangent windshears to compare and contrast. Overall, the model shows greater inhomogeneity and irregularity …

The 2025 Measles Outbreak In Texas, Tamer Oraby, Martial L. Ndeffo-Mbah

School of Mathematical & Statistical Sciences Faculty Publications

Background: In 2025, Texas experienced its largest measles outbreak in decades, reporting 762 cases by mid-August. Measles is a highly contagious but vaccine-preventable infection transmitted mainly among unvaccinated individuals and capable of causing severe outcomes.

Methods: We investigate counterfactual measles control scenarios based on daycare and school closures and reactive vaccination of infants and children, including mixed interventions. We analyze the 2025 Texas outbreak using an age-structured multi-stage SEIR model formulated as a system of ordinary differential equations. The model is fit to case data using Bayesian inference to estimate the effective reproduction number and generate posterior predictive trajectories under …

From Reluctance To Resilience: The Link Between Attitude And Growth Mindset In Calculus Students, Olivia Valente, Kathryn E. Pedings-Behling, Amy N. Langville

Journal of Educational Research and Practice

Many postsecondary students enter general education mathematics courses with negative attitudes, shaping their willingness to engage with the content. This study explores the relationship between students’ attitudes towards mathematics and their growth mindset, revealing effective strategies to enhance learning experiences, particularly for students who are reluctant learners. The research investigates two questions: (1) How do students’ Attitude Toward Mathematics Inventory (ATMI) scores and Growth Mindset Scale (GMS) scores relate? and (2) Do gender or course modality affect this relationship? This study addresses a gap in literature by examining how enjoyment, motivation, self-confidence, and perceived value connect with growth mindset. The …

Closing The Awareness–Behavior Gap: A Role-Based Phishing Training Framework For Higher Education, Ranylene O. Olaybal, Ryan A. Olaybal

Journal of Cybersecurity Education, Research and Practice

Phishing remains one of the most persistent cybersecurity threats facing higher education institutions, where diverse user populations and highly connected digital environments increase exposure to social engineering attacks. Although cybersecurity awareness initiatives are widely implemented, high awareness does not always translate into secure behavior. This study examined phishing awareness, phishing-related practices, phishing susceptibility, and phishing experiences among college students, teaching faculty, and administrative staff in a private higher education institution in the Philippines. Using a quantitative cross-sectional design, data were collected from 553 respondents through a validated survey instrument and analyzed using descriptive statistics, one-way analysis of variance, Tukey's honestly …

Measuring Cosmic Expansion From Early To Late Times Using Quasars, Galaxies, & Local Supernovae, Rajeev Vaisakh

Physics Theses and Dissertations

This dissertation investigates the evolution of cosmic expansion across a wide redshift ($z$) range by combining measurements from quasars \& galaxies in the distant universe $(z > 0.8)$ with those obtained from stripped-core collapse supernovae observations from the nearby universe $(z < 0.1)$. Using the DESI spectroscopic survey, we analyze large-scale clustering from quasars over $0.8 < z < 2.1$ and emission line galaxies over $0.8 < z < 1.6$, contributing to DESI DR2 BAO and full-shape measurements of cosmic expansion and structure growth. Combined with BBN in flat $\Lambda$CDM, DESI DR2 BAO gives $H_0 = 68.51 \pm 0.58$ km s$^{-1}$ Mpc$^{-1}$, while combinations of DESI BAO with CMB and supernova data show a preference for evolving dark energy, with representative constraints such as $w_0 = -0.752 \pm 0.057$ and $w_a = -0.86^{+0.23}_{-0.20}$ for DESI+CMB+DESY5. Using the ROTSE-III Supernova Survey and the expanding photosphere method (EPM), we measure distances to a sample of six supernovae for which the thermal phase can be clearly identified. This analysis focuses on testing whether reliable EPM distances can be obtained for this population. The resulting distances will eventually be compared with independent estimates from the literature. Establishing consistency with these external measurements represents an important step toward applying this methodology to larger samples, with the eventual goal of using ROTSE supernova distances to provide an independent measurement of the local Hubble constant.

Statistical Methodologies For Count Time Series Analysis And Topological Data Analysis Of Medical Images, Yuhyeong Jang

Statistical Science Theses and Dissertations

This dissertation addresses two distinct topics related to count time series analysis and topological medical image analysis, respectively. The first part of the dissertation comprises an application of a count time series model to analysis of US monthly sex trafficking data and development of a new model for multivariate count data that exhibits serial dependence and overdispersion. By imposing a family of multivariate mixed Poisson distributions on the count random vector, the proposed model can accommodate a broad range of overdispersion as well as positive contemporaneous correlations. For maximum likelihood estimation, a computationally feasible EM-type algorithm is derived based on …

Single Fluorogens And Orientation-Localization Microscopy For Quantifying Chemical And Biomolecular Dynamics At The Nanoscale, Yiyang Chen, Yuanxin Qiu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Many chemical systems look uniform only because ensemble measurements average over their most interesting molecules. Electron-transfer rates vary across electrode surfaces; lipid membranes contain nanodomains with distinct packing and fluidity; peptide aggregates exhibit local polymorphism; and biomolecular condensates contain transient networks of interactions that are blurred in ensemble images. A central challenge in chemical imaging is not simply to see smaller structures, but to measure chemical variables such as polarity, redox potential, and molecular confinement at the single-molecule level. In this Account, we describe how fluorogens, molecules whose brightness, blinking, spectral shifts, orientation, rotational mobility, and motion are directly shaped …

Dynamics Of Microscale Droplets In Respiratory Airways, Md Shamser Ali Javed

Mathematics Theses and Dissertations

We investigate trajectories of microscale evaporating droplets in a stagnation point flow near a wall of a respiratory airway. The configuration is motivated by the problem of advection and deposition of microscale droplets of respiratory fluids in human airways during transmission of infectious diseases such as tuberculosis and COVID-19. Laminar boundary layer equations are solved to describe the air flow while the equations of motion of the droplet include contributions from gravity, aerodynamic drag, and Saffman force. Evaporation is accounted for at both the droplet surface and the wall of the respiratory airway and is shown to delay droplet deposition …

Ground To Roof Snow Load Ratio (Gr) Data Release, Brennan Bean, Cooper Nelson, Jesse Wheeler, Scout Jarman, Salam Adil Al-Rubaye, Marc Maguire

Browse all Datasets

This data release provides historical ground-to-roof snow load ratio (GR) datasets used for snow load research and model development. The release includes original referenced datasets, cleaned country specific datasets, and a master dataset that combines Canadian and United States datasets into a standardized format for research and engineering applications.

Data Repository For "The Influence Of Hydrologic And Salinity Conditions On Drought-Tolerant Great Salt Lake Wetland Plant Species" By Samantha Kurkowski And Karin Kettenring, Samantha Kurkowski

Browse all Datasets

This greenhouse experiment investigated the effects of salinity (3 levels) and hydrologic condition (5 levels),  on the cover and biomass of a single mix of 11 native drought- and salt-tolerant species.

Algebraic And Topological Methods In Computational Neuroscience, Trong-Thuc Trang

Electronic Theses and Dissertations 2020 - Present

Neural data is incredibly rich in combinatorial, topological, and geometrical information, reflecting the intricate shape and connectivity of neural firing patterns. To decipher these structures, neuroscience increasingly relies on advanced mathematical tools to analyze neural activity. Here we study (1) neural codes within the poset P_Code of neural codes and (2) the connectivity of neural population activity within the insular cortex when responding to interoceptive information. In (1), we establish combinatorial constructions for all upward covering relations based on what we call “isolated subsets” with supporting theorems and give a slight modification of the existing downward covering relations. We …

The Effect Of Spin Polarization On Ion-Acoustic Solitary Waves In Quantum Plasmas, Amirhosein Rezvani, Sedigheh Miraboutalebi, Leila Rajaei, Mahmoodreza Sharifian

Turkish Journal of Physics

The exchange interaction, a fundamentally quantum-mechanical phenomenon, can significantly modify the classical description of cold, overdense plasmas. These quantum effects can be systematically analyzed within the framework of quantum magnetohydrodynamic (QMHD) theory, which enables the use of separate momentum equations for spin-up and spin-down electron populations. In this study, we adopt this approach to incorporate exchange interactions for both spin species and investigate the excitation of ion-acoustic wave (IAW) solitons in the plasma system. Using a perturbative expansion method, the governing equations are reduced to a nonlinear Schrödinger equation (NLSE), which admits solitonic wave solutions. The stability of these solitons …

On Cosmological Equation Of State From The First Law Of Thermodynamics, Ch'ng Han Siong

Turkish Journal of Physics

We derive several equations of state for different types of energy from the first law of thermodynamics. We derive the equation of state of a Machian universe from the well-known energy formulaE=mc2. This equation of state is consistent with previously reported results. We then propose hypothetical forms of energy that lead to the equations of state of the Chaplygin gas, generalized Chaplygin gas, and modified Chaplygin gas. We also obtain the energy density of the Chaplygin gas by dividing the hypothetical energy by the volume of the universe, and find that it is consistent with previously reported results. Finally, we …

Design And Fabrication Of Petri Dish Optimized For High-Frequency Acoustic Microscopy Using 3d Printing, Tuna Pesen, Beyza Ceren Eren, Arda İnanç, Bora Akgün

Turkish Journal of Physics

High-frequency imaging in acoustic microscopy requires the use of Petri dishes with thin and acoustically transparent bottoms to minimize signal attenuation and distortion. Commercially available options suitable for this purpose are often expensive or limited in compatibility with custom setups. Here, we present a cost-effective and easily customizable alternative developed in our laboratory, consisting of a 3D-printed frame combined with commercially available stretch film. The stretch film serves as an ultrathin (8 µm thickness) base that supports efficient high-frequency acoustic transmission, enabling clear and reliable imaging. Beyond acoustic microscopy, the adaptable design is also compatible with other modalities such as …

Ai And The Music Industry: Its Current Status And A Speculative Projection Of Its Evolutionary Trajectory, Rhett D. Morris, Clayton Rosati, Stefan Fritsch

Honors Projects

Music serves as one of society's biggest cultural outlets, allowing millions to share in what used to be a uniquely human form of expression. The commodification of music has built a huge industry full of companies and platforms that have used technology and property laws to shape music's relationship with the public. This study aims to look into the future to see how AI and its implementation could affect the structure of the music industry. To look into the future, this piece establishes two of the most pressing kinds of AI technology for the music industry and looks to contextualize …

Toroidal Plasmonic Nanodimers For Enhanced Near-Infrared Emission In Heterostructured Inp Quantum Dots, Arda Gülücü, Emre Ozan Polat

Turkish Journal of Physics

Near-infrared (NIR) emitters operating in the 650--900 nm spectral range are highly attractive for imaging and sensing in turbid media. However, cadmium-free InP-based quantum dots (QDs) often exhibit limited brightness owing to nonradiative recombination pathways and inefficient photon outcoupling. In particular, heterostructured InP QDs may possess band alignments that induce partial spatial separation of charge carriers, thereby reducing the electron-hole wavefunction overlap. This characteristic modifies the intrinsic recombination dynamics and increases the sensitivity of their emission to the surrounding photonic environment. Here, we investigate silver toroidal plasmonic nanoantenna dimers (Ag TPNDs) using finite-difference time-domain (FDTD) simulations as a geometry-tunable platform …

Radiation Pressure And Membrane Dynamics In Cavity Optomechanics: Interaction Hamiltonian And Quantization, Mahmut Can Özuygur

Turkish Journal of Physics

Cavity optomechanics explores the interaction between light confined in optical cavities and mechanical oscillators, primarily driven by radiation pressure forces. These interactions enable significant advances in precision measurements, quantum information processing, and tests of fundamental quantum mechanics. This paper presents a detailed analysis of membrane vibration and radiation pressure force within a cavity optomechanical system. The membrane's equation of motion is derived, the radiation pressure force is evaluated within the Lorentz force formalism, and the corresponding interaction Hamiltonian is formulated. Quantization of the resulting Hamiltonian enables the investigation of quantum phenomena, including entanglement generation and quantum state transfer, and provides …