Physical Sciences and Mathematics Commons^™

From Image To Insight: Evaluating Llm Accuracy In Understanding Uml Use Case Diagrams With Claude, Mohamed El-Attar, Yasser Khan, Mahmood Niazi, Sajjad Mahmood, Mohammad Alshayeb

All Works

UML use case diagrams are a prominent artefact of requirements engineering, capturing the functional scope of a software system in terms of actors, use cases, and their stereotyped relationships. The emergence of multimodal large language models with image understanding capabilities raises the question of whether such models can reliably extract structured construct-level information from use case diagram images. This paper reports an empirical evaluation of Claude on the task of counting 14 notational construct types from a corpus of 78 computer-generated UML use case diagrams, assessed against manually verified ground truth annotations. Results reveal a strongly differentiated accuracy profile: Claude …

Cliffinsight: An Educational Web Application That Visualizes The Calculation Of Effect-Sizes Using Cliff's Delta, Mohamed El-Attar, Ahmed Shuhaiber, Rima Grati, Sarah Kohail

All Works

The purpose of calculating effect sizes in statistics is to quantify the practical significance of observed differences beyond mere statistical significance. While standardized mean difference measures such as Cohen’s d are widely used, they require normally distributed data, an assumption frequently violated in educational and social science research. Non-parametric alternatives such as Cliff’s delta (δ) are more robust under these conditions yet remain underused due to perceived computational complexity and limited accessible resources. Existing web-based tools for Cliff’s delta function primarily as numerical calculators and do not expose the underlying dominance structure that gives the statistic its meaning. This paper …

A Preliminary Exploratory Assessment Of Chatgpt To Generating Stride Data Flow Diagrams, Hassan Alsayegh, Mohamed El-Attar

All Works

Threat modeling is a core activity in security-by-design practices, enabling early identification of architectural weaknesses before system implementation. The drawings used during STRIDE analysis are typically Data Flow Diagrams (DFDs), referred to as “STRIDE diagrams” in this paper. STRIDE diagrams provide a visual approach for categorizing security threats; however, constructing accurate STRIDE diagrams require experience and is often time-consuming. Recent advances in Large Language Models (LLMs), such as ChatGPT, raise important questions about their suitability for supporting structured security modeling tasks. This study presents a preliminary exploratory assessment of ChatGPT’s ability to generate, analyse, and iteratively refine STRIDE diagrams from …

Leveraging Quantum Storage Mechanism For Digital Forensic Readiness Towards Smart City Security, Bashaer Aljeneibi, Richard Ikuesan

All Works

The increasing digitization of urban infrastructure has introduced advanced efficiency and connectivity in smart cities while exposing them to sophisticated cybersecurity threats. This study explores how Quantum Storage Mechanisms (QSM) can be integrated with digital forensic readiness systems to enhance smart city security and incident response. Through a simulated environment, the research evaluates the effectiveness of QSM against three critical cyberattack scenarios: Distributed Denial of Service (DDoS), sensor spoofing, and supply chain firmware attacks. The findings reveal that QSM-enabled systems outperform traditional cybersecurity tools by ensuring tamper-proof evidence collection, real-time threat detection, and secure long-term data retention. The study also …

Drone Authentication System Using Radio Frequency Fingerprinting, Jamila Muhsen Alnuaimi, Shamma Ghaleb Almansoori, Noura Ahmed Alrumeithi, Richard Ikuesan

All Works

The widespread integration of unmanned aerial vehicles (UAVs) across domains such as logistics, surveillance, and emergency response has introduced critical security challenges, particularly unauthorized access, identity spoofing, and drone cloning. Traditional software-based authentication methods, including GPS tracking and encryption, have proven inadequate against advanced cyber-physical threats. This paper proposes a secure and automated drone authentication framework based on Radio Frequency (RF) fingerprinting, leveraging intrinsic hardware-level signal imperfections to generate unique and unclonable drone identities. Using Random Forest classifiers, the system captures, preprocesses, and analyses RF features to distinguish between authorized and unauthorized UAVs. Validation with real-world RF datasets demonstrates high …

Towards A Context-Aware Driving Assistance System (Ca-Das): Advancing Intelligent Vehicular Safety Through Multimodal Context Integration, Fatma Outay, Siham Farrag, Anjum Zameer, Ansar Yassar

All Works

Driving-related behavioural factors are responsible for 90% of traffic collisions. The rapid growth of urbanization and the complexity of the traffic conditions demand a smart, efficient, and flexible transportation system. The advancement of transportation through technologies such as the Internet of Things (IoT) and AI have reshaped the way that drivers interact with their vehicles and the surrounding environment. In this paper, we propose a comprehensive Context-Aware Driving Assistance System (CA-DAS) that employs sensor fusion, semantic context modelling, along with a machine-learning-based approach to provide personalised and proactive driving assistance across dynamic scenarios. The proposed CA-ADS was developed using a …

Celebrating Faculty Scholarship 2026, Smith College Libraries

Celebrating Faculty Scholarship: Bibliographies

Bibliography of selected scholarly and creative work produced by Smith College faculty and submitted by faculty for the 2026 celebration in the Neilson Library Skyline Reading Room, Smith College on September 14, 2026.

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs' responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model's output. The LLM-CXR model is selected as the medical …

Theoretical Study Of Long-Range Molecular Interactions, Adrian Luis Batista-Planas

Doctoral Dissertations

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions—with electrostatic, induction, and dispersion as main components—play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well-established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed Long-Range-Fit (LRF), an interactive and user-friendly software package designed to automate …

Mechanisms Driving Disparities In Income Mobility Across The Income Distribution, Joe Larkins

Honors Theses

This study examines intergenerational income persistence across the income distribution, testing whether mechanisms driving inequality differ between families in the top and bottom halves of the income distribution. Using data from the National Education Longitudinal Study of 1988 (NELS:88), a nationally representative longitudinal survey of 8th grade students and their parents, this research estimates an interaction model comparing parental income effects for children in advantaged versus disadvantaged economic circumstances. The analysis reveals that a $1,000 increase in parental income yields eight times greater income gains for children in the bottom half of the distribution compared to those in the top …

Small Antiperfect Steiner Triple Systems, Justin Z. Schroeder, Joshua Ganschow

Research & Publications

The cycle structure of Steiner triple systems (STS) has been well studied with regard to uniform STS and cycle switching. Of particular interest among uniform STS are perfect STS, in which every cycle graph consists of a single cycle. In this paper, we initiate the study of antiperfect STS, in which every cycle graph consists of a union of at least two cycles. We prove that an antiperfect STS(n) exists for all admissible n ≥ 15 and provide a complete listing of all antiperfect STS(n) for n ≤ 19 and all antiperfect STS(21) with a non-trivial automorphism. Furthermore, it is …

Inferential Statistics For Industrial Organizational Psychologists: A Practical Guide For Testing Hypotheses Using R, Caitlin Lapine

Open Touro Created

2026

This text aims to provide a practical guide for students in industrial organizational psychology or related fields to complete inferential statistics using R open-source programming language. It provides information about when to use particular statistical analyses and how to perform those with statistical software.

Hydrogeochemical And Redox Controls On Nitrate And Arsenic Co-Occurrence In The Western Kansas High Plains Aquifer (Usa): A Composite Health Risk Assessment And The Case For Risk-Informed Private Well Governance, Jonathan Kuffour Owusu

Master's Theses or Doctor of Nursing Practice

Fifty-one private domestic wells across western Kansas were sampled to quantify nitrate and arsenic occurrence, identify geochemical controls, and evaluate carcinogenic and non-carcinogenic health risks for adult and child receptors in a region where groundwater serves as the primary drinking water source with no routine regulatory oversight. Samples were analyzed for major ions, nutrients, and trace elements by ICP-MS, ion chromatography, and UV-Vis spectrophotometry. Shapiro-Wilk testing confirmed non-normal distributions for both contaminants; inter-county comparisons were therefore conducted using Kruskal-Wallis tests with Dunn's post-hoc correction. Health risk was quantified via chronic daily intake (CDI), hazard quotient (HQ), HQ-based Water Quality Index …

Special Issue: Innovative Numerical Approaches For Problems In Science And Engineering, Xiaoming He, Shuhao Cao, Qiao Zhuang

Mathematics and Statistics Faculty Research & Creative Works

No abstract provided.

Equilibrium Stability Under Nuclear Confrontation, Martin Bohner, A. A. Martynyuk

Mathematics and Statistics Faculty Research & Creative Works

This article proposes and analyzes mathematical models of confrontation between two and n countries, including countries with nuclear weapons. The proposed models are based on a generalization of Richardson's well-known mathematical model of the arms race. Namely, the factor of hostility is filled with expanded content, including public opinion and the armed forces of the opposing countries. Qualitative analysis of confrontation models is carried out by the method of Lyapunov functions and by applying nonlinear integral inequalities. As a result of the analysis, the conditions for the stability of the equilibrium state of the opposing countries are established, and the …

Relativistic And Recoil Corrections To Light-Fermion Vacuum Polarization For Bound Systems Of Spin-0, Spin-1=2, And Spin-1 Particles, Gregory S. Adkins, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

In bound systems whose constituent particles are heavier than the electron, the dominant radiative correction to energy levels is given by light-fermion (electronic) vacuum polarization. In consequence, relativistic and recoil corrections to the one-loop vacuum-polarization correction are phenomenologically relevant. Here, we generalize the treatment, previously accomplished for systems with orbiting muons, to bound systems of constituents with more general spins: spin-0, spin-1=2, and spin-1. We discuss the application of our more general expressions to various systems of interest, including spinless systems (pionium), muonic hydrogen and deuterium, and devote special attention to the excited non-S states of deuteronium, the bound system …

An Introduction To Field Excursions For The 2026 Geological Society Of America Cordilleran Section Meeting In Loreto, Baja California Sur, México, Scott E.K. Bennett, Michael H. Darin, Genaro Martínez Gutiérrez

Geology Faculty Publications and Presentations

The 122nd annual meeting of the Geological Society of America (GSA) Cordilleran Section will be held in Loreto, Baja California Sur, México, an idyllic and historic Sonoran Desert city nestled on the eastern shore of the Baja California peninsula. The 2026 Loreto meeting marks a milestone for GSA as it is the first time in the Section’s century-plus history that the meeting has been held on the Baja California peninsula and only the third time that the meeting has been held in México. Thus, the 2026 Loreto meeting and related field trips represent a meaningful expansion of the Section’s engagement …

Effective Deep Learning Architectures For Structured Data Analysis And Generation, Md Atik Ahamed

Theses and Dissertations--Computer Science

The effective utilization of structured data is fundamental to modern machine learning, yet it presents distinct challenges in both predictive analysis and generative modeling. Traditional deep learning architectures, particularly Transformers, often suffer from quadratic computational complexity when processing long sequences. This dissertation addresses these limitations by introducing novel architectures based on State-Space Models (SSMs) and Diffusion Models. In the area of predictive analysis, we focus on overcoming the computational bottlenecks of attention mechanisms for tabular and time-series data. First, we introduce MambaTab, a selective state-space architecture designed for efficient tabular classification. By leveraging the linear complexity of SSMs, MambaTab significantly …

Threshold Asymmetric Conditional Autoregressive Range (Tacarr) Model, Isuru Ratnayake, V. A. Samaranayake

Mathematics and Statistics Faculty Research & Creative Works

This paper introduces a Threshold Asymmetric Conditional Autoregressive Range (TACARR) model for analyzing the daily price ranges of financial assets. The proposed formulation assumes that the conditional expected range switches between two regimes, representing upward and downward market states, with the disturbance distribution also allowed to vary across regimes. A self-adjusting threshold component, determined by past values of the series, is used to identify the prevailing market regime. In this way, the model is able to capture asymmetric and heteroscedastic volatility behavior in financial markets. The TACARR model is designed to address several limitations of existing price range models, including …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …

Intelligent Formation Control Using Orfbls And Adaptive Backstepping Sliding-Mode Control To Address Uncertain Tilting In Multi-Quadrotors During Wind Gusts, Ching-Chih Tsai, Chun-Fu Mao, Kumail Hussain

Journal of Marine Science and Technology–Taiwan

In terms of aerial robotics, stable and precise formation control is a significant challenge for tilting multi-quadrotors during disturbances. This paper proposes a fixed-time formation control strategy for tilting multi-quadrotors to address the effect of external wind gusts. The observer accurately predicts environmental disturbances and an adaptive backstepping sliding-mode control (ABSMC) method with an output recurrent fuzzy broad learning system (ORFBLS) addresses these disturbances within a finite time. ORFBLS dynamically adjusts its structure through a growing ORFBLS structure to allow nodes to be added as needed. The method's stability is validated using Lyapunov stability theory and ensures the convergence of …

Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou

Journal of Marine Science and Technology–Taiwan

Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.

This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …

Using Remote Sensing Technology To Develop A Framework For Improving Hydrologic Models, Marissa Cook

Theses, Dissertations and Capstones

With increased storm intensity due to climate change and urbanization, flash flooding has become an increasingly significant issue globally and regionally. Although the factors influencing urban flash flooding are well-known, there is a growing need for technology to accurately and remotely predict the chance of a flash flood occurring from any given rain event to give people time to prepare. This study aims to use multispectral satellite imagery to provide a framework for improving near real-time flood predictions in an urban area of a high gradient, fourth order stream impacted by flooding. Specifically, we utilize satellite imagery to create the …

Hydrodynamic Tipping Points In The Mississippi Sound In Response To Bonnet Carré Spillway Openings, Mustafa Kemal Cambazoglu, Brandy N. Armstrong, Mohsena Lopa, Marc Diard, Jerry D. Wiggert

Faculty Publications

This project examines the current operational strategy of the Bonnet Carré Spillway (BCS), a Mississippi River flood-control structure located about 21 miles northwest of New Orleans, Louisiana, and managed by the U.S. Army Corps of Engineers. The BCS is part of the larger Mississippi River and Tributaries Project, a network of levees and control structures designed to minimize flooding from the American plains to southern Louisiana. The spillway is opened when river discharge at New Orleans is forecasted to exceed 1,250,000 cubic feet per second, diverting significant volumes of Mississippi River water into Lake Pontchartrain which subsequently flows into Mississippi …

Short-Term Response Mechanisms Of Water Quantity And Quality Of Daihai Lake Under Temperature-Driven Changes, Hao Zhang, Xiaohong Shi, Xianhua Li, Junping Lu, Ruizhong Gao, Xixi Wang, Shuhao Zhang, Longmei Xie, Yu Liu

Civil & Environmental Engineering Faculty Publications

Temperature-driven mechanisms involving complex feedback and lag that affect the evolution of hydrological processes and ecological functions in cold- and arid-region lakes represent a core scientific issue in current hydrology and lake ecology research. In this study, based on month-scale temperature and environmental factor data from Daihai Lake in Inner Mongolia from January to December 2023, statistical methods (redundancy analysis, Tukey's test analysis, correlation analysis, structural equation modeling), time series analysis methods (dynamic time warping), and machine learning methods (random forest) were combined. A hierarchical and phased response framework was constructed that encompassed driver identification, path tracing, lag characterization, and …

A Variance Decomposition Approach To Inconclusives In Forensic Black Box Studies, Amanda Luby, Joseph B. Kadane

Mathematics and Statistics Faculty Work

In the USA, ‘black box’ studies are increasingly being used to estimate the error rate of forensic disciplines. A sample of forensic examiner participants is asked to evaluate a set of items whose source is known to the researchers but not to the participants. Participants are asked to make a source determination (typically an identification, exclusion, or some kind of inconclusive). We study inconclusives in two black box studies, one on fingerprints and one on bullets. Rather than treating all inconclusive responses as functionally correct (as is the practice in reported error rates in the two studies we address), irrelevant …

Recirculated Submarine Groundwater Discharge Dominates Nutrient Inputs And Enhances Eutrophication Risk In A Coastal Lagoon, Júlia Rodriguez-Puig, Clara Ruiz-González, Marc Diego-Feliu, Irene Alorda-Montiel, Aaron Alorda-Kleinglass, Daniel Romano-Gude, Andrea G. Bravo, Júlia Dordal-Soriano, Javier Gilabert, Sophia Bergeler, Celine Lavergne, Gemma Casas, Marisol Manzano, Jordi Garcia-Orellana, Valentí Rodellas

OES Faculty Publications

Submarine groundwater discharge (SGD) is a widely recognized pathway for nutrient transport to coastal systems. Prior studies overlook the unique biogeochemical signatures of different SGD pathways, neglecting their differences in biogeochemical transformations and spatiotemporal factors. Here, we present an integrated assessment of nutrient delivery through three SGD pathways (fresh SGD, long‐scale recirculated SGD, and short‐scale porewater exchange), alongside surface water inputs, to evaluate their seasonality and impact on nutrient dynamics in a coastal lagoon. We conducted five field surveys in March, July, and November 2021, July 2024, and March 2025 in the Mar Menor lagoon, an ecosystem facing severe ecological …

Seasonal And Geologic Controls On Submarine Groundwater Discharge-Derived Nutrient Fluxes To Two Coastal Embayments, Moira Taylor, Joseph J. Tamborski, Aaron Alorda-Kleinglass, Nathaniel Maynard

OES Faculty Publications

Submarine groundwater discharge and porewater exchange are critical but often overlooked sources of nutrients to coastal systems. This study investigates how sediment permeability and summer-winter seasonal dynamics influence the magnitude and biogeochemistry of nutrient fluxes from submarine groundwater discharge and porewater exchange. Reaction rates in the subterranean estuary were used to identify the transformations and drivers of nutrient loading in two geologically distinct embayments in the U.S. East Coast: the highly permeable Peconic Bay estuary (NY), and the surficially fine-grained coastal embayments of the southern Delmarva Peninsula (VA). We applied radium isotope mass balances to distinguish total submarine groundwater discharge …

Revisiting The Life Cycle Of Margalefidinium Polykrikoides Group Iii, Eduardo Pérez-Vega, Kenneth N. Mertens, Pjotr Meyvisch, Margaret R. Mulholland

OES Faculty Publications

Dinoflagellates produce cysts as a strategy to withstand environmental stressors, with nutrient depletion generally considered a key trigger for cyst production. Resting cysts are thick-walled, typically composed of one to several layers, and characterized by a prolonged dormancy period. In contrast, pellicle cysts possess a thin, single wall and exhibit no dormancy or a markedly shorter dormancy than resting cysts of the same species. Margalefidinium polykrikoides produces pellicle and resting cysts, whereas its congener, M. fulvescens, has been shown to produce pumpkin-like structures. Using phase-contrast microscopy, time-lapse microscopy, FlowCam, and attenuated total reflection Fourier transform infrared microspectroscopy (ATR μ-FTIR), …

Machine Learning Classification Of Prostate Cancer Genomic Sequences Using K-Mer And Sequence-Derived Features, Kuldeep Rawat, Hirendra Nath Banerjee, Jamie Noble, Saa Naudia Deloatch, Satyendra Banerjee, Sachin Shetty, Soumya Banerjee

VMASC Publications

Prostate cancer disproportionately impacts African American men, who experience significantly higher mortality rates and earlier disease onset than other populations. Current diagnostic approaches, including prostate-specific antigen testing and biopsy, lack sufficient specificity and sensitivity, underscoring the need for accurate, molecular-level classification tools. This paper presents a machine learning framework for binary classification of genomic DNA sequences as cancerous or healthy. A dataset of 1684 FASTA-formatted sequences obtained from the National Library of Medicine - GenBank was analyzed, with 1662 sequences retained after quality control filtering. Feature engineering yielded 67 attributes, including GC content, Shannon entropy, sequence length, and trinucleotide k-mer …