Digital Commons Network^™

Mat 1600 Syllabus Ii Syllabus, Tian Cai

Open Educational Resources

No abstract provided.

Mat 2100 Calculus Iii Syllabus, Mei Xing

Open Educational Resources

No abstract provided.

Laser Beam Shaping Using A Neural Network, Azeem A. Hakim

Honors Undergraduate Theses

Multiphoton lithography (MPL) is a method of laser-based 3D-printing for fabricating micron-scale structures point-by-point in a photopolymerizable medium. MPL’s high-resolution capabilities have made it a powerful method for the fabrication of many devices, such as microelectromechanical systems (MEMS) and tissue scaffolds.  The throughput of MPL processes can be increased by using spatially shaped laser beams that expose large areas or volumes simultaneously. A laser beam can be reshaped by passing it through a spatial light modulator (SLM) displaying a pre-designed phase mask. One type of laser beam profile used for this purpose is the Bessel beam, a type of structured …

Using Ai To Analyze Survey Data, Sara Martucci

Open Educational Resources

This assignment in Methodology in Sociology/Criminology engages students in the full research process by guiding them through variable selection, data analysis, interpretation, and critical reflection on AI-assisted decision-making. Using a class-generated survey dataset (or an existing dataset), students develop a research question, identify independent and dependent variables, and formulate a hypothesis. They then compare their selections with those suggested by an AI tool, analyzing differences in reasoning and variable choice. Through SPSS, students generate frequency tables, charts, and scatterplots to examine relationships between variables, including potential intervening factors. The assignment culminates in a group presentation and reflective analysis on the …

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.

Modeling Rank Distribution And The Relative Importance Factor Index In Discrete Power-Law Models: Application To Social Resilience Using The Scopus Database, Brian Llinas, Jose Padilla, Humberto Llinas, Erika Frydenlund, Katherine Palacio

VMASC Publications

Prior research on power-law distributions has primarily focused on modeling frequency patterns, with less attention given to rank distributions and how ranked positions reflect relative importance among elements. In discrete power-law distributions, frequency-based metrics often provide limited discrimination in the tail, where elements may exhibit similar counts but differ in relative dominance. These patterns are especially evident, for instance, in academic publishing, where keywords, affiliations, and citations commonly exhibit power-law behavior. To address this limitation, we introduce the Relative Importance Factor (RIF) Index, a statistical measure derived from the estimated discrete power-law rank distribution rather than an additional independent parameter. …

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 …

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 …

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 …

Beyond Full Fine-Tuning: The New Playbook For Adapting Deep Neural Networks, Cristian S. Mcgee

Honors Undergraduate Theses

Fine-tuning is the process of teaching and specializing a pre-trained neural network on a downstream task. Fine-tuning is a rapidly growing topic in artificial intelligence domains; however, many fine-tuning endeavors are highly specialized without a coherent framework connecting them. This work presents a unified perspective on fine-tuning methods and performance metrics. Our perspective organizes the methods in terms of how they are applied to fine-tuning. This framework showcases methods that (i) update effective subspaces of the pre-trained model, (ii) change the adaptation optimization procedure, and (iii) alter the representations of the embedded input. Additionally, we present unconventional metrics such as …

Barriers To Immunity: Understanding Covid-19 Vaccine Uptake In Africa, Emilia Blechschmidt

Honors Theses

This thesis examines the factors influencing COVID-19 vaccine uptake across African countries, with a focus on structural, informational, and behavioral barriers to immunization. Drawing on cross-country data, the study analyzes how access to transportation, reliable information, and healthcare resources shape vaccination rates, alongside the effect of demographics and institutional factors in shaping individual perceptions of risk and vaccine safety.

The findings emphasize that the broader strength and preparedness of national health systems strongly influence vaccine uptake. Countries that demonstrated higher coverage of routine childhood immunizations, such as polio and hepatitis B, also tended to perform better in COVID-19 uptake efficiency …

Sedimentological Characterization Of Main And Chute Channel Scroll Bars Along The Kantishna River, Alaska, Cooper Sentz

Honors Theses

Scroll bars, arcuate sediment ridges found along the inner banks of river bends, are common floodplain features in meandering river systems that form during lateral channel migration. Two hypothesized formation mechanisms described in prior studies are the aggradation of suspended load onto abandoned inner bank levee (IBL) deposits during overbank flow and the migration of transverse bar packages from the channel bed up onto the point bar during flooding events. To study the sedimentology and geometry of these features, we conduct remote sensing and field analysis on a 60 km portion of the Kantishna River, AK: a highly sinuous, pro-glacial …

First Remi Experiments At A Cryogenic Ion Storage Ring, M. Schulz, F. Herrmann, W. Zhang, A. Dorn, M. Grieser, F. Grussie, H. Kreckel, O. Novotny, A. Wolf, T. Pfeifer, C. D. Schröter, R. Moshammer

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

We have recorded double, triple, and quadruple coincidences between neutralized projectiles, recoiling target ions, and two electrons created in collisions of slow anions with neutral atoms. The experiments were performed at the cryogenic storage ring in Heidelberg. The recoil ions and ejected electrons were momentum-analyzed using a Reaction Microscope (ReMi) spectrometer. Various processes involving electron detachment from the projectile accompanied by various transitions in the target were investigated. Detachment without any transition in the target is qualitatively well described by a quasi-free electron model in the case of an Ar target. In detachment with single target ionization, no signatures of …

Using L1-Magic For Feature Enhancement And Reduced Redundancy In Hyperspectral Data, Ashley Alfred

Mathematics Dissertations

Hyperspectral imaging offers detailed spectral information, but achieving high spatial resolution typically requires large and expensive equipment. This study explores an alternative approach: enhancing low-quality hyperspectral bands using an L1-norm minimization technique known as L1-magic. The goal is to improve the utility of low-cost hardware by preserving discriminative features, promoting sparsity, and reducing spectral redundancy. We apply L1-magic to enhance low-quality bands and hypothesize that this method selectively amplifies key features while suppressing redundant information. Experimental results indicate that the enhanced bands approach the quality of high-resolution data, enabling robust feature extraction without reliance on high-end hyperspectral cameras.

Ultra-Low Noise Ion Detection For Neutrinoless Double Beta Decay Searches, Karen E. Navarro

Physics Dissertations

Neutrinos are the most abundant particles in the universe that carry mass. Yet, we know very little about them since they are electrically neutral and interact weakly. A small instance after the Big Bang, an imbalance occurred that caused matter to be produced in greater quantities than antimatter. A leading candidate for this unexplained process is leptogenesis. Leptogenesis predicts that neutrinos are Majorana particles: a particle that is its own antiparticle. Today, particle detectors are being constructed to search for this property through the yet unobserved neutrinoless double beta decay (0νββ) . If observed, this would demonstrate that neutrinos are …

Rockyou2024: What’S Your Password?, Yixuan Zhang

Honors Theses

Passwords remain a critical part of almost every account security system. As a result, password guessing attacks remain one of the most widespread yet profitable attacks possible. Setting a password resistant to attacks is thus an important task for account holders. In this paper, we use the RockYou2024 database, a collection of approximately 10 billion real-world passwords collected from data breaches, to analyze the characteristics of passwords found in real life. We start with basic statistical property analysis, such as length, distribution of digits and symbols, and proceed onto more complicated properties such as frequencies of combinations of characters, entropy …

Bursty Bulk Flows: The What, The Why, And Their Impacts On The Earth, Fariza Tanvir

2026 Spring Honors Capstones Projects

Due to solar wind-magnetosphere interactions, the Earth's magnetic field lines stretch into a long, comet-shaped magnetotail, which extends thousands of miles away from the Earth. Bursty Bulk Flows (BBFs) are transient, high-speed ion bulk flows in the magnetotail that play an essential role in energy and mass transport. Characterized by their short-lived duration, they are related to magnetic reconnection events. This investigation focuses on being able to identify BBFs using the Magnetospheric Multiscale (MMS) probes, a mission consisting of four probes arranged in a tetrahedron to study the Earth’s magnetosphere. We examine parameters such as energy spectra, spin bulk velocity, …

Inside Out: Improving Large Model Safety, Wei Zhao

Dissertations and Theses Collection (Open Access)

While Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) are at the frontier of current advancements in artificial intelligence, demonstrating remarkable capabilities across diverse applications, there are growing concerns about their reliability and security. LLMs remain vulnerable to adversarial attacks through carefully crafted prompts that circumvent safety mechanisms, while MLLMs face additional security challenges stemming from their multimodal nature. Despite considerable efforts in reinforcement learning from human feedback (RLHF) and supervised fine-tuning, existing safeguards have proven inadequate in addressing these critical vulnerabilities. This inadequacy stems from the fact that these models are inherently blackboxes that do not provide …

Designing A Research Study: Controlling For A Variable And Using Chatgpt, Fritz Umbach

Open Educational Resources

This assignment uses a hypothetical society to help students understand the idea of “controlling for a variable” and practice applying it to a real-world research question. Students design a research approach to examine whether income differences are better explained by family background or by systemic prejudice, working within clear data limits. ChatGPT is used as a research guide to help students brainstorm, test, and revise their methods, while encouraging them to critically evaluate the usefulness and limits of AI-generated suggestions. The assignment emphasizes careful reasoning, clear research design, and thoughtful use of AI as a support for learning rather than …

Soft-Constrained Variants Of T-Distributed Stochastic Neighbor Embedding For Global Structure Preservation, Joseph A. Balderas

Mathematics Dissertations

Dimensionality reduction (DR) is a fundamental tool in data science and machine learning that transforms high-dimensional data into a low-dimensional representation while preserving important structural properties of the original data. Among modern DR methods, t-distributed stochastic neighbor embedding (t-SNE) has become one of the most widely used techniques for visualization due to its strong ability to preserve local neighborhood structure and produce visually separated clusters. However, despite its popularity, t-SNE is well known to struggle with preserving global structure of data, often producing embeddings in which distances between clusters and neighborhoods do not accurately reflect relationships in the high-dimensional space. …

Infimum Dimension Nash Embeddings For 2d Projective Shape Analysis, Robert L. Paige, Vic Patrangenaru

Mathematics and Statistics Faculty Research & Creative Works

Vector embeddings make complicated data extracted from networks, words and images, more amendable to data science applications. At the present time, the Veronese-Whitney (VW) matrix embedding of the real projective space is the state of the art for making inference about digital images from an uncalibrated camera, such as a cell phone or security camera. In this work we consider vector embeddings for the projective shape data and in particular determine the minimum dimension isometric (distance-preserving or Nash) vector embedding for a projective space. We determine such an embedding for the projective plane in closed-form. From this embedding we determine …

A Fully Discrete Semi-Implicit Numerical Scheme And Its Optimal Error Estimates For Cahn-Hilliard-Mhd Model With Variable Density, Dongmei Duan, Fuzheng Gao, Xiaoming He, Yanping Lin

Mathematics and Statistics Faculty Research & Creative Works

This paper proposes and analyzes a fully discrete semi-implicit unconditionally energy stable numerical scheme to solve the Cahn-Hilliard Magnetohydrodynamics (Cahn-Hilliard-MHD) model with variable density. The unconditional energy stability and optimal L² error estimates are established for the fully discrete scheme. Major challenges in error estimation arise from the variable density, the strong nonlinearities, and the multi-physics coupling of the model. Under the mathematical induction framework, the Ritz quasi-projection and the Stokes quasi-projection, proposed in [SIAM J. Numer. Anal., 61(3):1218-1245, 2023], are utilized to avoid the gradient terms of the projection errors. The H⁻¹ superconvergence error estimates of Ritz …

Learning Weibull Loss Severity Models From Truncated And Censored Data, Majed Alkhasha

Graduate Studies Theses and Dissertations 2026

In modern actuarial science and risk management, due to various loss control mechanisms, observed severity losses are typically left-truncated at the deductible, right-censored at the policy limit, and scaled by a pre-specified co-insurance factor. This results in two types of actuarial payment random variables: payment-per-payment (PPP) and payment-per-loss (PPL). To learn ground-up Weibull loss severity models from PPP and PPL sample data, we implement two estimation techniques: Maximum Likelihood Estimation (MLE) and the dynamic Method of Trimmed Moments (MTM). MLE is employed to obtain efficient estimates of the Weibull shape and scale parameters. However, MLE may assign unnecessarily large point …

Connecting The Existing Fiber Infrastructure To The Future With Antiresonant Hollow Core Fibers, Timothy Bate

Graduate Studies Theses and Dissertations 2026

Optical fiber systems based on solid-core silica waveguides underpin modern telecommunications, high-power laser delivery, precision sensing, and coherent optical systems. However, nonlinear effects, material absorption, and thermal limitations within silica increasingly constrain further scaling in both optical power and transmission performance. Antiresonant hollow-core fibers provide a promising alternative by guiding light predominantly in air, substantially reducing nonlinear interactions, latency, and optical damage while enabling transmission regimes inaccessible to conventional solid-core fibers. Despite rapid advances in antiresonant hollow-core fiber attenuation and power handling, one of the largest remaining barriers to widespread adoption is reliable integration with the existing solid-core fiber ecosystem. …

The Case For Friction In Ai-Mediated Information Seeking And Learning, Susan G. Archambault, Priya Kizhakkethil

Librarian Publications & Presentations

Introduction. This paper challenges the assumption that frictionless AI-mediated information seeking represents progress. We argue that AI systems eliminating productive friction, such as uncertainty, exploration, and reflective processes, undermine intellectual virtues essential for critical thinking in an AI-saturated information environment.

Method. This conceptual article employs a theory synthesis approach, drawing on library information science (LIS) theories of information behaviour, experience, and literacy, virtue epistemology, and human–computer interaction (HCI) friction design literature.

Analysis. We map intellectual virtues such as curiosity, thoroughness, and intellectual humility onto the Association of College and Research Libraries (ACRL) Framework for Information Literacy for Higher Education, building …

Structured Interactions With Llms To Support Ltl: Supplemental Information, Karenna Kung, Maanas Punuru, Alicia M. Grubb, Paola Spoletini

Computer Science: Faculty Publications

This repository contains the supplemental information for the paper: "Structured Interactions with LLMs to Support LTL", which investigates how students interact with and can be supported by LLM explanations while translating linear temporal logic formulae into English natural language.

Predictive Analytics For Optimising Delivery Performance In Supply Chain Management, Vishwanath Sai Krishna Teja

ICT

Supply chain management has always been a challenging area where delivery delays stand as one of its main ongoing issues. Many companies continue to use outdated data collection systems despite the advancements in data collection tools. This study investigates how predictive analytics can help companies to prevent their operational problems from reaching their customers.

In this study, two datasets were used. The first is the Data Co Smart Supply Chain dataset which covers order level operations from 2015 to 2018, and the second is the World Bank Logistics Performance Index, which covers logistics quality across more than 160 countries. After …

Bio-Orthogonal Chemistry-Based Strategy To Turn-On And Turn-Off Crispr-Cas9 Gene Editing In Solution And In Live Cells, Bhoomika Pandit

Electronic Theses & Dissertations (2024 - present)

The CRISPR–Cas9 system is a widely popular tool for genome engineering. There is a strong interest in developing tools for temporal control of CRISPR-Cas9 activity to address some of the challenges and to broaden the scope of potential applications. In this thesis I describe two biorthogonal based approaches to either Turn-ON and Turn-OFF CRISPR-Cas9 gene editing.

In first project work I describe a bio-orthogonal chemistry-based approach to Turn-ON Cas9 nuclease activity with temporal precision. We report a TCO-acylimidazole reagent that acylates 2′-OH groups of RNA. Poly-acylation (“cloaking”) of RNA was optimized in vitro using a model 18-nt oligonucleotide, as well …