Physical Sciences and Mathematics Commons^™

Chemical And Sensory Attributes Of Different Ethanol Reduction Methods In Muscadine Wine Production, Alexandra A. Escalera, Patricia C. Patricio Morillo, Drew Budner, Katherine A. Thompson-Witrick, Andrew J. Macintosh

Chemistry

There has been a recent shift in the global wine market towards reduced-alcohol wines. Muscadine grapes (Vitis rotundifolia) have become a popular choice in many emerging markets; however, their suitability in reduced-alcohol wine production has not been extensively tested. In this study, methods to reduce ethanol in muscadine wine were compared to determine differences in chemical and sensory attributes and consumer preference. The methods evaluated included full fermentation time with Saccharomyces cerevisiae (control), reduced fermentation time with Saccharomyces cerevisiae (stopped fermentation), fermentation with Saccharomycodes ludwigii yeast (instead of Saccharomyces cerevisiae), and vacuum distillation. The control and distilled wines were fermented …

Assessing The Role Of Ocean Literacy In Liberia's Blue Economy : Pathway To Sustainable Blue Ocean Development In Liberia, Precious Tete Nah

Ocean Sustainability, Governance & Management Dissertations

Ocean literacy involves understanding the fundamental concepts of the ocean's functioning, leading to informed and responsible decisions about the ocean. This understanding is vital for developing responsible ocean citizenship and implementing measures to sustain the ocean, as it highlights the ocean's influence on humans and the impact of human activities on it. Using a qualitative research method with a purposive sampling approach, the research asks focus group representatives from New Kru Town and Westpoint, both closed- and open-ended questions, on the importance of ocean literacy, challenges, prospects, and recommendations to promote sustainable blue ocean development.

The results of the research …

Diffusion Of Innovation Of Port Decarbonization Measures : A Case Study Approach, Clint Rocky Mcculloch, Lucas Fernando Vaquero Roviriego

Port Management Dissertations

The dissertation is a study of how stakeholders diffuse innovation in port decarbonization strategies through a case study approach, with emphasis on the Diffusion of Innovation (DOI) relating to the technical and operational measures in the developing regions. Port, being a critical hub in global supply chains, have to manage the increasing pressure of reducing greenhouse gas (GHG) emissions in alignment with International Maritime Organization (IMO) 2023 GHG strategy as well as the Paris Agreement. However, there is a gap in empirical research, specifically in non-European regions like South America and the Caribbean, highlighting the need for insights from stakeholders’ …

Analytical Solutions For Transitional Flow Around Hydrometeors: Implications For Particle Dynamics And Atmospheric Modeling, Ahmad Talaei, Timothy J. Garrett

Physics Student Research

Accurate modeling of hydrometeor dynamics is critical for advancing weather and climate predictions. However, this remains a long-standing challenge in atmospheric science, particularly within the transitional Reynolds number regime, due to the lack of analytical solutions to the Navier–Stokes equations. This study presents two analytical solutions for two-dimensional, incompressible, and viscous flow around a sphere, addressing the gap between low and high Reynolds number regimes. The first framework, an extension of classical expansion methods using hypergeometric, provides a direct analytical relation that characterizes separation angle across the transitional regime. To address post- separation dynamics, a second formulation based on a …

Spatiotemporal Modeling Of Maternal Mortality In South Carolina 2018-2023, Leah Wood, Ray Bai, Emily Mann

Senior Theses

Maternal death serves as a public health indicator due to fact that it is considered preventable with the availability of modern biomedicine, however, it persists broadly throughout the United States. Current literature outlines national trends in maternal mortality with complicating, preexisting conditions, and structural upstream factors often cited as being the largest contributors to increased risk. This study utilizes publicly available, county-level data for maternal death in addition to demographic and descriptive data in order to estimate maternal mortality rates in each of South Carolina’s 46 counties from 2018 to 2023. In order to address sparsity in the outcome variable …

A Better Great Plains: Bridging The Implementation Gap For A Better Future, David W. Sandahl

School of Natural Resources: Dissertations, Theses, and Student Research

The Northern Great Plains is experiencing extensive native grassland loss and landscape degradation, jeopardizing both ecological integrity and the socio-economic systems that rely upon these ecosystems. In an early effort to lessen degradation, the United States Department of Agriculture (USDA) introduced the Conservation Reserve Program (CRP) which generated ecosystem services benefits such as reduced soil erosion, improved water quality, and increased species diversity through the retirement of cropland and rangeland for 10- or 15-year contracts. However, CRP has not fully modernized alongside today’s agriculturalists and adoption remains shaped by an historically fraught socio-political context characterized by deep-seated mistrust between ranchers, …

Better Digital Contracts With Prosocial Friction-In-Design, Brett Frischmann, Moshe Y. Vardi

Faculty Publications

Contract law is supposed to enable people to reach genuine agreements and cooperate. If this ideal was ever a reality, the rise of mass market contracts and boil­erplate rendered it pure fiction. Modern consumer contracts are incomprehensible to most people. No one reads them anyway.

Digital contracting involves design features that amplify traditional boilerplate harms and create others. For example, digital contracting is too cheap; low marginal costs lead to overexpansion in scale and scope. To make matters worse, the loss of autonomy from repeat engagement with digital contracting systems is pernicious. People become increasingly predictable and programmable as digital …

Fast, Slow, And Metacognitive Thinking In Ai, M. Bergamaschi Ganapini, M. Campbell, F. Fabiano, L. Horesh, J. Lenchner, A. Loreggia, N. Mattei, F. Rossi, Biplav Srivastava, K. B. Venable

Faculty Publications

Inspired by the ”thinking fast and slow” cognitive theory of human decision making, we propose a multi-agent cognitive architecture (SOFAI) that is based on ”fast”/”slow” solvers and a metacognitive module. We then present experimental results on the behavior of an instance of this architecture for AI systems that make decisions about navigating in a constrained environment. We show that combining the two decision modalities through a separate metacognitive function allows for higher decision quality with less resource consumption compared to employing only one of the two modalities. Analyzing how the system achieves this, we also provide evidence for the emergence …

Active Measurement Of A Micron-Order Gap Under High-Speed And High-Temperature Conditions, Andrew Becker

Doctoral Dissertations and Master's Theses

The hypersonic regime poses numerous challenges that researchers face in the development of hypersonic flight vehicles. Due to their excellent thermomechanical properties, ultra-high-temperature ceramics (UHTCs) have risen as a promising solution to act as a protective barrier between the harsh environment and surface materials of these flight bodies. The mechanical operation of a portable hypersonic simulation device was developed in-house and tested at Argonne National Laboratories (ANL) to gather in-situ material response of prospective UHTC samples when exposed to a hypersonic regime. An edge detection-based algorithm was developed and used in LabVIEW to monitor the health and operation of the …

(Si15-010) On Perturbations Of Gabor Frames, Jamkhongam Touthang

Applications and Applied Mathematics: An International Journal (AAM)

Stability plays a crucial role in frame theory and its applications. The present paper studies the interaction between Gabor frames and perturbations, presenting perturbation results related to small changes of the frame parameters and the window functions both in regular and irregular settings. Examples are provided for illustration. Additionally, the paper briefly discusses algorithms pertinent to Gabor frames under perturbations and highlights challenging areas in the field.

Assessing Expected Cover Of Invasive Flora Species Near Corridor Features By Distance, Joshua G. Logan

Theses

Fragmentation of landscapes has been a growing topic of interest within scientific literature over the past several decades, as the way we as humans affect our planet becomes more apparent as the years go on. As humans, we have shaped the land and what it contains in immeasurable ways, erasing or forever altering entire natural ecosystems. Chief among the drivers altering these ecosystems is the fragmentation of landscapes, which can have all kinds of effects on natural ecosystems, from limiting nutrient transport to providing easier access for invasives to permeate throughout a landscape. Corridors are significant areas of interest regarding …

The Complexity Of Long-Distance Dependencies And Their Impact On Language Models, Abhijit Shrikant Mahalunkar

Doctoral

Sequential data modeling is an important challenge in various fields and in particular in natural language processing. Building effective sequential models faces a notable challenge in the form of Long-Distance Dependencies (LDDs) within the sequence data. Hence, successfully overcoming this challenge is imperative for developing robust and accurate sequential models across various domains and applications. To tackle this challenge, the first step is to conduct a detailed analysis of the complexity of LDDs observed in various sequence datasets. This thesis offers a thorough exploration and documentation of this analysis. An important finding from this thesis is the consistent patterns of …

Analysis Of The Status And Thematic Trends Of Ai For Science Research Abroad From 2015 To 2024, Fangyuan Wang, Huiting Xu, Jinghua Xue

Journal of Scientific Information Research

[Purpose/significance] This paper analyzes the relevant literature in the field of AI for Science（AI4S）in the WoS core database from 2015 to 2024, and sorts out the research status and development trends in this field, aiming to provide forward-looking insights for the application of AI technology in scientific research.

[Method/process] This paper combines bibliometric analysis with the BERTopic model to analyze the publication trends, publishing countries, core authors, and topic identification and development trends in the field of AI4S.

[Result/conclusion] Through bibliometric analysis, this paper reveals the exponential growth trend of AI4S-related literature, and finds that China ranks first in the …

Dcrda: Deadline-Constrained Function Scheduling In Serverless-Cloud Platform, Priyanka Ashok Birajdar, Divya Meena, Anurag Satpathy, Sourav Kanti Addya

Computer Science Faculty Research & Creative Works

The serverless computing model frees developers from operational and management tasks, allowing them to focus solely on business logic. This paper addresses the computationally challenging function-container-virtual machine (VM) scheduling problem, especially under stringent deadline constraints. We propose a two-stage holistic scheduling framework called DCRDA targeting deadline-constrained function scheduling. In the first stage, the function-to-container scheduling is modeled as a one-to-one matching game and solved using the classical Deferred Acceptance Algorithm (DAA). The second stage addresses the container-to-VM assignment, modeled as a many-to-one matching problem, and solved using a variant of the DAA, the Revised-Deferred Acceptance Algorithm (RDA), to account for …

(Si15-084) Application Of Differentiation Matrices Corresponding To Scaling And Wavelet Functions To Integral Equations, Viresh Kumar, Rakesh Kumar

Applications and Applied Mathematics: An International Journal (AAM)

In the present paper, we have studied the technique by which a differentiation matrix corresponding to scaling and wavelet function is helpful in representing an integral equation in discrete form. In this technique, only finite times continuously differentiable scaling and wavelet functions were used for the differentiation matrix. This method explores the applications of compactly supported wavelets in discretization of Fredholm integral equation and provides us with a bridge for the solution of integral equations via compactly supported finitely differentiable wavelets.

(Si15-017) Modeling Construction Project Uncertainty Using Fuzzy Inference And Nature-Inspired Metaheuristic Knowledge-Based Algorithms, M. Kapoor, B. K. Pathak, R. Kumar

Applications and Applied Mathematics: An International Journal (AAM)

Construction projects are influenced by various uncertain factors, including supervisory knowledge, labor expertise, and weather conditions. These uncertain factors have linguistic properties that are challenging to quantify with the help of traditional set theory. To address this, the study applies fuzzy inference systems, specifically the Mamdani fuzzy inference system, to model and evaluate the impact of these uncertainties on construction projects. This fuzzy inference system provides a more nuanced understanding of these factors compared to traditional set theory methods. Experimental results indicate that uncertainties significantly impact construction projects. These findings establish a valuable framework for developing adaptive strategies, enhancing project …

(Si15-142) Selection Of Single Sampling Plans Based On Zero Inflated Binomial Distribution Using Cost Optimization, Sangeetha S., Shalini K., Hemalatha R., Priyadharshini R.

Applications and Applied Mathematics: An International Journal (AAM)

Economic design of sampling plans involves creating sampling plans that minimize the total cost associated with the inspection process while ensuring quality. It aims to address the quality risk concerns of both producer and consumer, ensuring product quality while minimizing inspection costs. This article’s objective is to design single sampling plans by attributes based on Zero-inflated Binomial (ZIB) distribution, using cost optimization principles by developing an economic model aimed at achieving optimal total cost by considering the Average Total Inspection (ATI). Numerical illustration is provided to illustrate the selection of single sampling plans under ZIB distribution that minimizes producer’s total …

(Si15-113) Augmenting Cryptographic Security Through Inventive Application Of The Kharrat-Toma Transform Algorithm, Prabakaran Raghavendran, Tharmalingam Gunasekar, K. Sakthivel, Kamalendra Kumar, Shalini Gupta

Applications and Applied Mathematics: An International Journal (AAM)

This paper introduces a cryptographic technique combining the Kharrat-Toma Transform and congruence modulo operators to improve the security of message encryption. The proposed model uses the mathematical properties of the Kharrat-Toma Transform and its inverse for direct scrambling and unscrambling processes while embedding sufficient complexity to resist modern cryptanalytic attacks. The model is subjected to experimental tests, including encryption quality analysis, Shannon entropy, and NIST randomness tests, in order to prove the strength of the model. Through encryption quality analysis, symbol frequencies in the ciphertext are masked heavily from having much correlation between plaintext and ciphertext. Entropy values indicate near-theoretical …

(Si15-067) Ahp And Moora Decision Making Methods On Bipolar Fuzzy Sets, S. Anita Shanthi, R. Preethi

Applications and Applied Mathematics: An International Journal (AAM)

Decision making, in the present contemporary world, has been inherently complicated. Nowadays, the major challenge is the selection of an appropriate option. The arrival of numerous brands and models makes a purchase challenging. Hence, in this paper, four different models of the same branded laptops are considered, for the selection of an appropriate option, using the Analytic Hierarchy Process (AHP) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA), with bipolar fuzzy sets, which help decision makers arrive at the most logical choice based on their preferences. The bipolar fuzzy Analytic Hierarchy Process efficaciously supports decision making in cases …

The Fate Of Recycled Water In Restored Wetlands, Punyotoya Paul

Environmental Science and Management Professional Master's Project Reports

This research investigates the hydrological fate of treated wastewater or "recycled water" used for irrigation at a restored wetland site (Thomas Dairy) near Tigard, Oregon, that is managed by Clean Water Services (CWS). CWS is interested in understanding how treated wastewater moves through plants and soil in ecosystems that might be targeted for recycled water applications. Using a water balance approach, we evaluated irrigation inputs, soil infiltration dynamics, and hydraulic conductivity measurements across three soil types with different textures and other properties. Field measurements were collected using advanced sensors (TEROS and ATMOS devices) and laboratory tools (KSAT) to quantify soil …

Dimension Of Subalgebras Of Fomin-Kirillov Algebras, Taro Ikeda, Sirous Homayouni

Annual Student Research Poster Session

One of the central open problems concerning the Fomin-Kirillov algebras was whether their dimension is finite or infinite. This question was recently resolved in one research by C. Barligea, where it was shown that FK(n) is infinite-dimensional for all n ≥ 6. In our work, we investigate the dimension of a certain subalgebra of FK(6).

Topoimages: Incorporating Local Topology Encoding Into Deep Learning Models For Medical Image Classification, Pengfei Gu, Hongxiao Wang, Yejia Zhang, Huimin Li, Chaoli Wang, Danny Z. Chen

Computer Science Faculty Publications

Topological structures in image data, such as connected components and loops, play a crucial role in understanding image content (e.g., biomedical objects). Despite remarkable successes of numerous image processing methods that rely on appearance information, these methods often lack sensitivity to topological structures when used in general deep learning (DL) frameworks. In this paper, we introduce a new general approach, called TopoImages (for Topology Images), which computes a new representation of input images by encoding local topology of patches. In TopoImages, we leverage persistent homology (PH) to encode geometric and topological features inherent in image patches. Our main objective is …

Persistent Chemicals In Particulate Matter (Pm) Near A Hazardous Waste Thermal Treatment Facility, Chuqi Guo, Martine E. Mathieu-Campbell, Thomas Blanchard, Lavrent Khachatryan, Md Abdullah Al-Mamun, Qingzhao Yu, Myron Lard, Oluwafeyikemi Ogunmusi, Brenda Vallee, Wilma Subra, Iriel Edwards, David Malone, Slawo Lomnicki, Stephania A. Cormier, Jennifer Richmond-Bryant

School of Public Health Faculty Publications

Colfax, an overburdened community in central Louisiana, hosts the last commercially-operated open-burn/open-detonation (OB/OD) hazardous waste thermal treatment facility in the United States. Until December 2023 when their permit disallowed OB/OD, the facility processed military waste, fireworks, propellants, soils excavated from Superfund sites, and other hazardous materials. This community-engaged study measured ambient fine particulate matter (PM2.5), environmentally persistent free radicals (EPFRs), polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), and metals using two high-volume PM2.5 samplers deployed 1.2 mi and 9.0 mi from the facility from April, 2022 through February, 2023. Elevated PM2.5 concentrations were recorded at both sites during spring and summer 2022. …

Honors Faculty Research Talk Ml Tlachac, Ml Tlachac

Honors Programs

PowerPoint Slides of Honors Research Talk by ML Tlachac.

A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang

Research Collection School Of Computing and Information Systems

Knowledge Graphs (KGs) are increasingly used in finance to manage complex, interconnected data and support advanced analytics. This survey provides an overview of how KGs are applied across various financial areas, such as fraud detection, credit risk assessment, anti-money laundering, and regulatory compliance. We examine key techniques for building and using KGs in finance, including graph construction, embedding methods, and machine learning models. The survey also discusses challenges specific to finance, like handling private data, ensuring interpretability, and managing real-time data. Additionally, we explore the emerging combination of KGs with large language models and generative AI, which offers new possibilities …

Filterfl: Knowledge Filtering-Based Data-Free Backdoor Defense For Federated Learning, Yanxin Yang, Ming Hu, Xiaofei Xie, Yue Cao, Pengyu Zhang, Yihao Huang, Mingsong Chen

Research Collection School Of Computing and Information Systems

As a distributed machine learning paradigm, Federated Learning (FL) enables large-scale clients to collaboratively train a model without sharing their raw data. However, due to the lack of data auditing for untrusted clients, FL is vulnerable to poisoning attacks, especially backdoor attacks. By using poisoned data for local training or directly changing the model parameters, attackers can easily inject backdoors into the model, which can trigger the model to make misclassification of targeted patterns in images. To address these issues, we propose a novel data-free trigger-generation-based defense approach based on the two characteristics of backdoor attacks: i) triggers are learned …

Seeing 3d Through 2d Lenses: 3d Few-Shot Class-Incremental Learning Via Cross-Modal Geometric Rectification, Tuo Xiang, Xuemiao Xu, Bangzhen Liu, Jinyi Li, Yong Li, Shengfeng He

Research Collection School Of Computing and Information Systems

The rapid growth of 3D digital content necessitates expandable recognition systems for open-world scenarios. However, existing 3D class-incremental learning methods struggle under extreme data scarcity due to geometric misalignment and texture bias. While recent approaches integrate 3D data with 2D foundation models (e.g., CLIP), they suffer from semantic blurring caused by texture-biased projections and indiscriminate fusion of geometric-textural cues, leading to unstable decision prototypes and catastrophic forgetting. To address these issues, we propose Cross-Modal Geometric Rectification (CMGR), a framework that enhances 3D geometric fidelity by leveraging CLIP’s hierarchical spatial semantics. Specifically, we introduce a Structure-Aware Geometric Rectification module that hierarchically …

Omnivton: Training-Free Universal Virtual Try-On, Zhaotong Yang, Yuhui Li, Shengfeng He, Xinzhe Li, Yangyang Xu, Junyu Dong, Yong Du

Research Collection School Of Computing and Information Systems

Image-based Virtual Try-On (VTON) techniques rely on either supervised in-shop approaches, which ensure high fidelity but struggle with cross-domain generalization, or unsupervised in-the-wild methods, which improve adaptability but remain constrained by data biases and limited universality. A unified, training-free solution that works across both scenarios remains an open challenge. We propose OmniVTON, the first training-free universal VTON framework that decouples garment and pose conditioning to achieve both texture fidelity and pose consistency across diverse settings. To preserve garment details, we introduce a garment prior generation mechanism that aligns clothing with the body, followed by continuous boundary stitching technique to achieve …

Lsfdnet: A Single-Stage Fusion And Detection Network For Ships Using Swir And Lwir, Yanyin Guo, Runxuan An, Junwei Li, Zhiyuan Zhang

Research Collection School Of Computing and Information Systems

Traditional ship detection methods primarily rely on single-modal approaches, such as visible or infrared images, which limit their application in complex scenarios involving varying lighting conditions and heavy fog. To address this issue, we explore the advantages of short-wave infrared (SWIR) and long-wave infrared (LWIR) in ship detection and propose a novel single-stage image fusion detection algorithm called LSFDNet. This algorithm leverages feature interaction between the image fusion and object detection subtask networks, achieving remarkable detection performance and generating visually impressive fused images. To further improve the saliency of objects in the fused images and improve the performance of the …

Parameter-Efficient Variational Autoencoder For Multimodal Multi-Interest Recommendation, Nhu Thuat Tran, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Learning user preferences in recommendation systems is enriched by multimodal features, such as textual and visual content, and amplified by multi-interest modeling with Variational AutoEncoders (VAEs). However, prior efforts are limited by single modality focus and cumbersome, parameter-heavy architecture designs. To address these limitations, we introduce an innovative solution that blends the semantic richness of multimodal data with the representational power of multi-representation VAEs. Drawing inspiration from Mixture of Experts (MoE), we cast each VAE as an expert tailored to a specific modality, then fuse them via a novel parameter-merging function into a lean, unified model. This approach efficiently captures …