Digital Commons Network^™

(R2094) On Mds Bisymmetric Rhotrices Using Self-Dual Bases And Conjugate Elements Of Finite Fields, Shalini Gupta, Ruchi Narang, Manpreet Singh

Applications and Applied Mathematics: An International Journal (AAM)

Bisymmetric matrices have wide range of applications in statistics, engineering problems, information theory and computer science including coding theory and cryptography. In cryptography, a rhotrix being a couple matrix doubles the security of the cryptosystem. Here, we construct maximum distance separable (MDS) bisymmetric rhotrices using self-dual bases and conjugate elements of finite fields. MDS rhotrices are very crucial for the designing of block ciphers and hash functions in cryptography.

Pymelt-Px: A Python Script For Modeling Melting Of A Pyroxenite-Peridotite Bilithological Mantle, Ana L. Jimenez Bustos

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

The study of oceanic crust formation is a fundamental building block in our understanding of the processes of planetary formation, necessitating an understanding of the melt generation processes that help form oceanic crust. To aid in this purpose, we present pyMeltPX: a bilithological pyroxenite-peridotite mantle modeling script. Although the mantle is primarily comprised of peridotite, pyroxenite is a minor but ubiquitous feature of the mantle and can contribute a disproportionate amount of melt to crustal generation in mid-ocean ridge and ocean island basalt settings. Our model, pyMeltPX, is a python coded, extensible tool based on the Excel calculator by Lambart …

Machine Learning-Optimized Porous Thermally Responsive Ss-Pcm With Switchable Transparency For Adaptive Building Envelope Coatings, Zhiying Xiao, Rajae Bousselham, Mingjiang Tao, Sergio Granados-Focil, Oren Mangoubi, Steven Van Dessel

Chemistry

Buildings account for nearly 40% of total energy consumption, with a significant share of heating and cooling demand arising from building envelopes. Conventional passive envelopes—such as cool roofs, radiative cooling surfaces, glazing systems, and passive solar walls—cannot automatically adapt to environmental conditions by switching between heating and cooling modes. To address this limitation, we propose a passive, adaptive building envelope coating system that responds to ambient temperature changes without external energy input. The system integrates solid–solid phase change materials (SS-PCM), Polydimethylsiloxane (PDMS) and Silver (Ag), enabling switchable radiative cooling and solar heating effects. We investigated the influence of porous structures …

Evaluating Defi Vulnerabilities: The Role Of Bug Bounty Programs On Defi Software Supply Chain, Ping Fan Ke, Yi Meng Lau, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Decentralized finance (DeFi), powered by blockchain technology, enables peer-to-peer financial transactions without intermediaries. Despite rapid adoption, DeFi attracts malicious actors exploiting vulnerabilities. To mitigate risks, we propose a framework assessing entry points in the DeFi software supply chain: smart contracts, oracles/third-party feeds, user interfaces, off-chain storage, and crypto wallets. Applying this framework, we evaluate whether industry solutions—particularly bug bounty programs—adequately address these gaps. Our preliminary analysis indicates that most programs cover smart contract vulnerabilities (85.7%), followed by user interface issues (21.3%) and crypto wallet loopholes (11.9%). However, third-party risks, such as oracle feeds, are frequently deemed out of scope. This …

A Socio-Technical Analysis Of Market Reactions On Meme Coins: Trump’S Presidential Effect, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Meme coins are a unique type of cryptocurrency whose value is shaped by internet culture and viral trends. This study introduces a socio-technical research model to examine key factors influencing meme coin dynamics and applies it to analyze market reactions to Donald Trump’s 2024 U.S. presidential election victory and inauguration, focusing on the $TRUMP meme coin and other politics-related meme coins, known as PolitiFi. Using a mixed-methods approach, we analyze publicly available news, social media activity, and marketplace data to investigate the interaction between social engagement and technical infrastructure. Econometric analysis shows that Trump-related events triggered short-term price surges, increased …

Registration Is A Powerful Rotation-Invariance Learner For 3d Anomaly Detection, Yuyang Yu, Zhengwei Chen, Xuemiao Xu, Lei Zhang, Haoxin Yang, Yongwei Nie, Shengfeng He

Research Collection School Of Computing and Information Systems

3D anomaly detection in point-cloud data is critical for industrial quality control, aiming to identify structural defects with high reliability. However, current memory bank-based methods often suffer from inconsistent feature transformations and limited discriminative capacity, particularly in capturing local geometric details and achieving rotation invariance. These limitations become more pronounced when registration fails, leading to unreliable detection results. We argue that point-cloud registration plays an essential role not only in aligning geometric structures but also in guiding feature extraction toward rotation-invariant and locally discriminative representations. To this end, we propose a registration-induced, rotation-invariant feature extraction framework that integrates the objectives …

Safe-Sora: Safe Text-To-Video Generation Via Graphical Watermarking, Zihan Su, Xuerui Qiu, Hongbin Xu, Tangyu Jiang, Jun-Hao Zhuang, Chun Yuan, Ming Li, Shengfeng He, Fei Yu

Research Collection School Of Computing and Information Systems

The explosive growth of generative video models has amplified the demand for reliable copyright preservation of AI-generated content. Despite its popularity in image synthesis, invisible generative watermarking remains largely underexplored in video generation. To address this gap, we propose Safe-Sora, the first framework to embed graphical watermarks directly into the video generation process. Motivated by the observation that watermarking performance is closely tied to the visual similarity between the watermark and cover content, we introduce a hierarchical coarse-to-fine adaptive matching mechanism. Specifically, the watermark image is divided into patches, each assigned to the most visually similar video frame, and further …

Jury-And-Judge Chain-Of-Thought For Uncovering Toxic Data In 3d Visual Grounding, Kaixiang Huang, Qifeng Zhang, Jin Wang, Jingru Yang, Yang Zhou, Huan Yu, Guodong Lu, Shengfeng He

Research Collection School Of Computing and Information Systems

3D Visual Grounding (3DVG) faces persistent challenges due to coarse scene-level observations and logically inconsistent annotations, which introduce ambiguities that compromise data quality and hinder effective model supervision. To address these challenges, we introduce Refer-Judge, a novel framework that harnesses the reasoning capabilities of Multimodal Large Language Models (MLLMs) to identify and mitigate toxic data. At the core of Refer-Judge is a Jury-and-Judge Chain-of-Thought paradigm, inspired by the deliberative process of the judicial system. This framework targets the root causes of annotation noise: jurors collaboratively assess 3DVG samples from diverse perspectives, providing structured, multi-faceted evaluations. Judges then consolidate these insights …

Misodice: Multi-Agent Imitation From Mixed-Quality Demonstrations, The Viet Bui, Tien Mai, Hong Thanh Nguyen

Research Collection School Of Computing and Information Systems

We study offline imitation learning (IL) in cooperative multi-agent settings, where demonstrations have unlabeled mixed quality - containing both expert and suboptimal trajectories. Our proposed solution is structured in two stages: trajectory labeling and multi-agent imitation learning, designed jointly to enable effective learning from heterogeneous, unlabeled data. In the first stage, we combine advances in large language models and preference-based reinforcement learning to construct a progressive labeling pipeline that distinguishes expert-quality trajectories. In the second stage, we introduce MisoDICE, a novel multi-agent IL algorithm that leverages these labels to learn robust policies while addressing the computational complexity of large joint …

Cssa-Fusion: Channel Selective And Spatial Alignment Infrared-Visible Image Fusion, Zhen Li, Zhi Zeng, Zhongrui Xiao, Ming Wen, Zhiyuan Zhang, Yibin Tian

Research Collection School Of Computing and Information Systems

Infrared-visible image fusion aims to integrate complementary information from two modalities to generate images with enriched semantic content. However, existing methods often neglect two critical aspects: the design of a local–global feature enhancement architecture and spatial alignment. To address these challenges, we propose Channel Selective and Spatial Alignment Fusion (CSSA-Fusion), a novel framework composed of two synergistic modules. The first is a selective channel and redundancy suppression module, which introduces a dual-branch selective channel attention mechanism to jointly capture local saliency and global channel importance for enhanced feature representation, and an informativeness–redundancy separation strategy to suppress redundant information while preserving …

The Rise Of Parameter Specialization For Knowledge Storage In Large Language Models, Yihuai Hong, Yiran Zhao, Wei Tang, Yang Deng, Yu Rong, Wenxuan Zhang

Research Collection School Of Computing and Information Systems

Over time, a growing wave of large language models from various series has been introduced to the community. Researchers are striving to maximize the performance of language models with constrained parameter sizes. However, from a microscopic perspective, there has been limited research on how to better store knowledge in model parameters, particularly within MLPs, to enable more effective utilization of this knowledge by the model. In this work, we analyze twenty publicly available open-source large language models to investigate the relationship between their strong performance and the way knowledge is stored in their corresponding MLP parameters. Our findings reveal that …

A Partition Cover Approach To Tokenization, Jia Peng Lim, Shawn Tan, Davin Choo, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Tokenization is the process of encoding strings into tokens of a fixed vocabulary size, and is widely utilized in Natural Language Processing applications. The leading tokenization algorithm today is Byte Pair Encoding (BPE), which formulates the tokenization problem as a compression problem and tackles it by performing sequences of merges. In this work, we formulate tokenization as an optimization objective, show that it is NP-hard via a simple reduction from vertex cover, and propose a polynomial-time greedy algorithm GreedTok. Our formulation naturally relaxes to the well-studied weighted maximum coverage problem which has a simple -approximation algorithm GreedWMC. Through empirical evaluations …

Sheetpedia: A 300k-Spreadsheet Corpus For Spreadsheet Intelligence And Llm Fine-Tuning, Zailong Tian, Zhuoheng Han, Houfeng Wang, Lizi Liao

Research Collection School Of Computing and Information Systems

Spreadsheets are widely used for data analysis and reporting, yet their complex structure and formula logic pose significant challenges for AI systems. We introduce Sheetpedia, a large-scale corpus of over 290,000 diverse spreadsheets (from 324,000+ workbooks) compiled from enterprise email archives and online forums. We detail a rigorous collection and preprocessing pipeline (integrating the Enron email spreadsheet archive and the Fuse web corpus, plus a new crawl of Excel forums) to standardize formats, filter languages, and remove duplicates. Sheetpedia provides extensive coverage of real formulas and annotations – addressing a gap left by prior table datasets (e.g. web tables used …

Cropcapsnet: Enhanced Capsule Network For Crop Disease Classification, Juan Qin, Linfan Deng, Cong Li, Junjie He, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

The prevention and treatment of crop diseases are crucial for the development of smart agriculture. The classification of crop diseases based on deep learning for early disease monitoring and control has become the mainstream direction of research. This paper proposes a novel deep learning model called ”CropCapsNet”, which combines Squeeze-and-Excitation Inception (SE-Inception) module and has improved capsule structure for crop disease classification. The network first extracts shallow features of input samples through double-layer convolution, then uses SE-Inception to achieve deep multi-scale feature acquisition, and finally outputs classification results through an improved capsule structure. SE-Inception adds Squeeze-and-Excitation(SE) attention after each multi-scale …

An Analysis Of Face Synthesis Methods And Their Influence On Human Perception, Maha Habib Almaimani

All Dissertations

Synthetic faces (e.g., computer-generated characters) have been increasingly utilized across various fields, including entertainment, healthcare, and education. Perceptual studies are often conducted to understand how synthetic faces are perceived by humans, aiming to enhance both quality and user experience in these domains. Over the years, numerous methods have been developed to create synthetic faces, ranging from traditional techniques such as image composites, Active Appearance Models, and 3D Morphable Models to more recent machine-learning-based frameworks like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

Despite the growing adoption of synthetic face generation and the variety of algorithms available for their creation, …

Declined Charge: An Attempt At The Horror Game Genre, Fernando Sepulveda Guizar

Computer Science and Software Engineering

Books and movies are a great medium for people to experience new worlds and experiences through a usually passive method. This can be great for stories with a set story and have all the pieces fall into place as the author intended. Video games on the other hand can give players a more active role in the worlds and stories that they experience. Players have direct control over the player character, and their actions have consequences that may or may not persist throughout the entire game, which is not usually the case with movies or books. This is why horror …

The Influence Of Tight Binaries On Protoplanetary Disk Masses, K. Flaherty, P. Knowlton, T. Smith-Gandy, A. M. Hughes, M. Kounkel, Eric L.N. Jensen, J. Muzerolle, K. Covey

Physics & Astronomy Faculty Works

Binary systems are a common site of planet formation, despite the destructive effects of the binary on the disk. While surveys of planet-forming material have found diminished disk masses around binaries with medium separation (∼10–100 au), less is known about tight (< 10 au) binaries, where a significant circumbinary disk may escape the disruptive dynamical effects of the binary. We survey over 100 spectroscopic binaries in the Orion A region with the Atacama Large Millimeter/submillimeter Array (ALMA), detecting significant continuum emission among 21 of them with disk masses ranging from 1 to 100 M_⊕. We find evidence of systematically lower disk masses among the binary sample when compared to single-star surveys, which may reflect a diminished planet-forming potential around tight binaries. The infrared excess fraction among the binary sample is comparable to that of single stars, although the tight binaries without significant ALMA emission display tentative evidence of weaker 3–5 …

From Static Prediction To Mindful Machines: A Paradigm Shift In Distributed Ai Systems, Rao Mikkilineni, W. Patrick Kelly

Barowsky School of Business | Faculty Scholarship

A special class of complex adaptive systems—biological and social—thrive not by passively accumulating patterns, but by engineering coherence, i.e., the deliberate alignment of prior knowledge, real-time updates, and teleonomic purposes. By contrast, today’s AI stacks—Large Language Models (LLMs) wrapped in agentic toolchains—remain rooted in a Turing-paradigm architecture: statistical world models (opaque weights) bolted onto brittle, imperative workflows. They excel at pattern completion, but they externalize governance, memory, and purpose, thereby accumulating coherence debt—a structural fragility manifested as hallucinations, shallow and siloed memory, ad hoc guardrails, and costly human oversight. The shortcoming of current AI relative to human-like intelligence is therefore …

The Price Of Priorities: How Human Choices Fuel Climate And Ecological Decline, Keisha Hickman

Biological Sciences Undergraduate Honors Theses

This thesis examines the ways in which human priorities and behaviors contribute to the escalating climate crisis and ecological systems. We will first analyze the role of social media in shaping public discourse on climate change and critically evaluate the priorities of institutions that have the means to assist in wildlife conservation. Both speak to the current behaviors of humankind prioritizing their own entertainment over meaningful efforts to mitigate climate change and preserve biodiversity. We will then shift to exploring the profound impact of human population growth and its associated activities on other species and ecosystems. Finally, the thesis will …

Full Issue, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Nonlinear Phase Space Analysis For Anomaly Detection In Ros 2 Communications: Detecting Man-In-The-Middle Attacks In Simulated Environments, William L. Locklier

Graduate Theses and Dissertations (2019 - present)

Robot Operating System 2 (ROS 2) marks a significant advancement over its predecessor through the transition from a centralized to a decentralized architecture, integrating the Data Distribution Service (DDS) to support real-time, scalable communications. Despite these improvements, inherent vulnerabilities in the ROS 2 communication stack continue to leave these systems exposed to sophisticated network-based attacks. This study leveraged nonlinear phase space analysis (NLPSA) as an intrusion detection system (IDS) to detect man-in-the-middle (MitM) attack anomalies in ROS 2 traffic. Grounded in Takens’ embedding theorem, NLPSA reconstructs the phase space of communication features and compares the resulting structure against a baseline …

Thermal And Non-Thermal Mass Transport Effects In Plasmon-Assisted Electrochemistry., Md Al Amin

Electronic Theses and Dissertations

Plasmon-assisted electrochemistry has received attention due to its effects of hot charge carriers, photothermal heating, and enhanced electromagnetic field impact on electrochemical transformation. These effects have contributed to lowering the onset potential and increasing the reaction kinetics. Numerous studies have been employed to differentiate the effect of photothermal heating from hot charge carriers on the electrochemical reaction. Most of these studies have been employed to measure and quantify the photothermal heating effects at equilibrium temperature; however, localized heating from the incident light does not result in homogeneous heating across the electrochemical cell. Many studies investigating the photothermal heating effect in …

A Persistent Homology Framework For Scrna-Seq: Assessing Clustering Robustness And Quantifying Preprocessing And Integration Effects On Topological Features., Jonah Daneshmand

Electronic Theses and Dissertations

As single-cell RNA sequencing (scRNA-seq) data expands, robust methods for integrating diverse datasets are critical. This dissertation applies Persistent Homology (PH), a technique from Topological Data Analysis (TDA), to a collection of scRNA-seq datasets spanning eight tissue types to quantify how data integration affects topological features and biological interpretability. We assessed global topological structure using Betti curves, Euler characteristics, and persistence landscapes across raw, normalized, and integrated data representations. Our analysis revealed a performance inversion: while conventional methods excelled on unintegrated data, high-granularity topological methods, particularly those sensitive to global data structure, became superior after integration. This suggests a synergy …

Controlling Selectivity In Electrocatalytic Co2 Reduction With An External Magnetic Field., Nawaraj Karki

Electronic Theses and Dissertations

My dissertation describes how to alter the speciation and concentration of molecules at the electrode-electrolyte interface, and how those alterations affect reactivity and selectivity. This dissertation presents two distinct approaches to control the mass transport of neutral molecules such as carbon dioxide (CO₂) at the electrode-electrolyte interface by using an external magnetic field. The first finding demonstrates that magnetic fields indirectly affect the mass transport of target analytes such as CO₂ molecules by selectively interacting with charged species, such as hydroxide ions (OH^-). Such interaction induces magnetohydrodynamic (MHD) effects, which generate localized hydrodynamic flow and …

Preparing Confident Elementary Mathematics Teachers: Addressing Anxiety, Building Fluency, And Strengthening Practice., Amber Diamond Pendleton

Electronic Theses and Dissertations

This dissertation, presented in three articles, examines how elementary preservice teachers (PSTs) experience and develop as mathematics learners and future educators when methods coursework deliberately integrates mathematical reasoning with affective supports. Collectively, the studies investigate how research-informed instructional design may help address mathematics anxiety (MA), mathematics teaching anxiety (MTA), procedural fluency, and instructional practice. The first article, written for practitioners and elementary mathematics teachers, illustrates how well-established instructional routines, such as number talks and student work analysis, can be facilitated to support procedural fluency in multiplication. Using classroom vignettes, this article highlights instructional moves that make structure visible, promote strategy …

Plasma-Enhanced Carbon Nanomaterial Synthesis: A Pathway To Reducing Greenhouse Gasses And Carbon-Based Waste., Zane Ronau

Electronic Theses and Dissertations

This research leveraged incorporation of capacitively coupled radio frequency plasma into chemical vapor deposition (CVD) for a reduction in the temperature requirements [a reduction of energy barrier] needed for the conversion of methane (CH₄), carbon dioxide (CO₂), and various carbon-based-waste to produce value-added carbon nanomaterials. An array of catalysts and catalyst supports were employed to optimize the synthesis of graphitic carbon under various gas environments, temperatures and pressures. The nanomaterials synthesized after fine tuning the growth parameters included graphene, carbon nanotubes (CNT), carbon microtubes and carbon nanocages with a variety of properties. Raman Spectroscopy was used …

Direct And Satellite-Based Quantification Of Greenhouse Gas Fluxes In Small Ponds., Mark Christopher Tierney

Electronic Theses and Dissertations

As evidenced by their historic losses due to anthropogenic activities, wetlands are undervalued ecosystems that provide numerous ecosystem services, from recreational opportunities to carbon (C) storage. However, these wetlands are also the largest natural source of atmospheric methane (CH₄). Additionally, small water bodies (< 10,000 m²) are disproportionately large emitters relative to larger lakes and reservoirs. As construction and restoration efforts proceed, it is crucial to identify wetlands that need restoration and to understand the factors driving both greenhouse gas (GHG) fluxes and the C balance of these systems. This dissertation investigates the drivers of greenhouse gas fluxes …

Synthesis, Characterization, And Chemical Reactivity Of Calcium-Alginate Hydrogel Beads Containing Metal Nanoparticles And Nanoclusters., Rajiv Kumar Singh

Electronic Theses and Dissertations

This dissertation explores the synthesis, stability, and reactivity of various metal nanoparticles (NPs) and nanoclusters (NCs) of varied size and stabilizers contained within millimeter-sized calcium alginate (Ca-Alg) hydrogel polymer beads. Hydrogel beads synthesized by combining sodium alginate with Au or Ag NPs stabilized with trisodium citrate (Cit) and adding dropwise into a 4.0 M Ca²⁺ solution remained stable and contained within the beads. Those synthesized Au, Pd and AuPd NCs stabilized with glutathione (SG) became partially released from the hydrogel within a day. The synthesis of beads containing aggregated Cit Au NPs occurs by inducing aggregation with tetrakis(hydroxymethyl) phosphonium …

El Poder Del Bilingüismo Y La Ciencia, Isabella Winslow

World Languages and Cultures

This project is an explanation of the importance of bilingualism, science, and our responsibility as humans within this environment. As living beings on this planet, we have a responsibility to respect and protect it. Over the course of the last several hundred years, we humans have made countless advancements. We have created unimaginable technology and discovered incredible resources produced by the land. However, in the process of doing so, we have damaged and continue to damage our environment. Reefs in the ocean have been bleached by increases in acidity, thousand year old glaciers have melted, forests have been destroyed by …

Onset Of Strong Iceland-Scotland Overflow Water 3.6 Million Years Ago, Matthias Sinnesael, Boris Theofanis Karatsolis, Paul N. Pearson, Anne Briais, Sidney R. Hemming, Leah J. Levay, Tom Dunkley Jones, Ying Cui, Anita Di Chiara, Justin P. Dodd, Deepa Dwyer, Deborah E. Eason, Sarah A. Friedman, Emma Hanson, Katharina Hochmuth, Halima E. Ibrahim, Claire E. Jasper, Saran Lee-Takeda, Danielle E. Leblanc, Melody R. Lindsay, David D. Mcnamara, Sevasti E. Modestou, Margaret A. Morris, Bramley J. Murton, Suzanne Oconnell, Gabriel Pasquet, Sheng Ping Qian, Yair Rosenthal, Sara Satolli, Takuma Suzuki, Thena Thulasi, Bridget S. Wade

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

North Atlantic Deep Water (NADW), the return flow component of the Atlantic Meridional Overturning Circulation (AMOC), is a major inter-hemispheric ocean water mass with strong climate effects but the evolution of its source components on million-year timescales is poorly known. Today, two major NADW components that flow southward over volcanic ridges to the east and west of Iceland are associated with distinct contourite drift systems that are forming off the coast of Greenland and on the eastern flank of the Reykjanes (mid-Atlantic) Ridge. Here we provide direct records of the early history of this drift sedimentation based on cores collected …