Physical Sciences and Mathematics Commons^™

Mgrre_Thinsections_Mgrre-101_6, Mgrre

Thin Sections

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Mgrre_Thinsections_Mgrre-101_16, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-101_18, Mgrre

Thin Sections

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Mgrre_Thinsections_Mgrre-102_5, Mgrre

Thin Sections

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Mgrre_Thinsections_Mgrre-102_12, Mgrre

Thin Sections

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Mgrre_Thinsections_Mgrre-101_1, Mgrre

Thin Sections

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Mgrre_Thinsections_Mgrre-101_11, Mgrre

Thin Sections

No abstract provided.

(R2133) Analysis Of A Bulk Queue With Balking, Adaptive Overloading Service, Multiple Vacation, Inspection And Rework, S. Karpagam, R. Lokesh

Applications and Applied Mathematics: An International Journal (AAM)

We consider a queueing system that utilizes a single server to manage product flow through bulk and overload service modes, depending on queue length. Balking occurs when the queue length reaches ‘N’. After completion of service, products undergo quality inspection, with defective products sent for rework based on specific probabilities. If the product is non-defective, the server continues processing until the queue length exceeds a certain threshold; beyond this point, the server is either routed back to bulk service or directed to an overload service. Also, the server goes into a vacation mode when the queue size is below a …

From 5g To 6g: A Survey On Security, Privacy, And Standardization Pathways, Mengmeng Yang, Youyang Qu, Thilina Ranbaduge, Chandra Thapa, Nazatul Haque Sultan, Ming Ding, Hajime Suzuki, Wei Ni, Sharif Abuadbba, David Smith, Paul Tyler, Josef Pieprzyk, Thierry Rakotoarivelo, Xinlong Guan, Sirine Mrabet

Research outputs 2022 to 2026

The vision for 6G aims to enhance network capabilities, supporting an intelligent digital ecosystem where artificial intelligence (AI) is a key. However, the expansion of 6G raises critical security and privacy concerns due to the increased integration of IoT devices, edge computing, and AI. This survey provides a comprehensive overview of 6G protocols with a focus on security and privacy, identifying risks that have not been experienced in preceding 5G systems, and presenting mitigation strategies. While many vulnerabilities from earlier generations persist, the introduction of AI/ML introduces novel risks like model inversion and malicious manipulation of AI. Vulnerabilities in emerging …

Spatiotemporal Pah Patterns In Size-Fractionated Particles (Pm>10-Pm0.1) From Northern Thailand Biomass Burning Via Sentinel-2, Phakphum Paluang, Watinee Thavorntam, Sarawut Sangkham, Phuchiwan Suriyawong, Hisam Samae, Thaneeya Chetiyanukornkul, Masami Furuuchi, Worradorn Phairuang

Research outputs 2022 to 2026

Biomass burning, particularly from forest fires and crop residue burning during the dry season, is a major source of particulate pollution across many Asian countries. However, accurately identifying these emissions remains challenging due to uncertainties in burned area estimation and the limited availability of country-specific emission factors. This study quantified the spatiotemporal distribution of emissions from biomass burning using satellite imagery. Burned areas were classified using a random forest (RF) algorithm implemented on the Google Colaboratory (Colab) platform. The RF model showed strong performance, with a kappa coefficient of 0.85 and an average accuracy of 0.81. Emission estimates for the …

Geometric Characterization Of Ideals In Bipolar Semigroups, Kittipong Laipaporn, Rasimate Maungchang, David M. Cook, Prathomjit Khachorncharoenkul

Research outputs 2022 to 2026

This paper develops a geometric framework for analyzing the ideal structure of the bipolar semigroup ��={(−��,��)∣��,��∈ℝ+0} under coordinate-wise addition. Subsets of B are interpreted as planar regions, allowing ideals to be described in terms of boundary behavior. In particular, we prove that the complement of a simply connected region is an ideal of the commutative additive semigroup (��,+) if and only if its boundary contains no strictly decreasing segment. This provides a direct and visually verifiable criterion for ideality, linking algebraic structure to geometric shape. Each ideal can be written as a union of translates of the form ��+��, with …

Rvit-Fusionnet: A Local Cross-Attention Feature Fusion-Based Hybrid Framework For Brain Tumor Classification, Naima Islam, Sajeeb Kumar Ray, Md Anwar Hossain, Syed Mohammed Shamsul Islam

Research outputs 2022 to 2026

Accurate brain tumor classification via MRI is essential for diagnosis and treatment. This study introduces RViT-FusionNet, a hybrid deep learning model that integrates convolutional and transformer architectures for enhanced tumor detection. The model utilizes ResNet-50 to capture textural details and a Vision Transformer for extracting global context. A Local Cross-Attention (LCA) module is proposed to align and merge these features, allowing the network to model local structures and long-range dependencies concurrently. To enhance generalization across varied imaging conditions and tumor types, a domain discriminator is included to discern spatial and domain-specific patterns, fostering the learning of domain-invariant representations. The approach …

Thermal Transformation Of Organic Matter And Impacts On Water Quality In Fire-Affected Jarrah Forest, Kuenzang Tshering, David Blake, Andrea Bravo Escobar, Konrad Miotlinski, Andrew Bath, Mary C. Boyce, Pauline Grierson, Pierre Horwitz

Research outputs 2022 to 2026

Fire in forested catchments significantly alters organic matter fluxes by generating dissolved organic matter (DOM) different from that generated under non-fire conditions. Elucidating the composition of DOM is key to understanding its persistence in the post-fire environment. This laboratory study aimed to establish a relationship between DOM quantity and quality with aspects of fire regime. Soil and litter samples were collected from areas with different burn histories (described as Time Since Last Fire – TSLF). Each sample was subjected to burn temperature treatments simulating different burn severity regimes in a muffle furnace (at 250°C – low severity, 350°C – moderate …

Emotional Support Through Ai: Venting To Artificial Intelligence Or A Perceived Human May Offer Comparable Emotional Well-Being Benefits, Meilan Hu, Jerlyn Q. H. Ho, Claire Ng, Shermaine S. M. Wong, Andree Hartanto

Research Collection School of Social Sciences

Artificial Intelligence (AI) chatbots are increasingly being explored as sources of informal emotional support, with emerging evidence suggesting that venting to these systems can reduce negative affect. Yet, it remains unclear whether such benefits depend on the responder's perceived identity. Given that emotional relief from venting often hinges on perceived authenticity and emotional validation, this study investigates whether the emotional well-being benefits of venting differ when users believe they are interacting with an AI chatbot versus a human, even when responses are content-matched. In a pre-registered experiment ( N = 279), participants were randomly assigned to either an AI-assisted venting …

The Can Challenge: Understanding The Best Ways To Incentivise Recycling Through A Diffusion Approach, Michael Brock, Lucia M. Murgia, Stefania Sitzia, Jiwei Zheng

All Works

Understanding the best ways to incentivise recycling and improve the efficiency of waste practices is a key environmental, social, and economic management problem that needs addressing.We search for solutions to this issue by testing the effectiveness of two incentive mechanisms (a piece-rate and a lottery-based systems). We run a similar field experiment in three different locations, namely a student, residential and workplace environment, to verify the robustness of our findings and thus increase confidence in the external validity of our intervention. By interpreting recycling activity as marketable service, we employ a diffusion model to analyse the potential adoption of the …

The Association Between Ethical Ai Use And Well-Being Among Young Adults In The Uae: A Structural Equation Modeling Approach, Areej Elsayary, Zeina Hojeij, Lames Abdul Hadi

All Works

This study examines the association between ethical AI use and young people’s emotional, social, and psychological well-being in the United Arab Emirates (UAE), where the number of hours spent on GenAI serves as a moderator. Framed within the Theory of Planned Behavior and aligned with the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being) and SDG 13 (Climate Action), this research examines how responsible digital engagement is associated with both individual mental health and broader digital sustainability. A Structural Equation Modeling approach assessed how ethical AI behaviors are associated with well-being. A total of 204 participants, predominantly …

Spatiotemporal Dynamics Of Riparian Land-Cover Change And Impervious-Cover Expansion In A Rapidly Urbanising Himalayan Capital City, Karma Jamtsho, Tashi Dorji, David Blake, Mark A. Lund, Eddie Van Etten

Research outputs 2022 to 2026

Urbanisation and impervious-cover expansion are reshaping riparian landscapes, particularly in mountain cities where steep terrain concentrates development along valley floors. This study examined spatiotemporal land-cover change within the regulated riparian corridors of Thimphu City, Bhutan, over a 25-year period from 1997 to 2022 using Landsat imagery, Random Forest classification and Google Earth Engine. Results show substantial transformation of riparian land cover, with impervious cover increasing from 26.14% to 32.63%, equivalent to an overall increase of 24.83%, while agriculture/barren/low-vegetation declined from 30.59% to 26.01%, equivalent to an overall decrease of 14.98%. A modest increase in detectable vegetation cover was also observed, …

The Implementation Of Scintillation Detectors With The Cuore/Cupid Collaboration In The Search For Neutrinoless Double Beta Decay, Reese Sandra Cormier

Physics

CUORE (Cryogenic Underground Observatory for Rare Events) is an experiment at the Gran Sasso National Laboratory in Assergi, Italy, currently searching for an answer to the matter-antimatter asymmetry problem; the question: why do we exist? One proposed explanation is neutrinoless double beta decay, a theorized exotic decay that would prove that neutrinos are their own antiparticle, violating the current Standard Model for particle physics. However, current detection methods do not distinguish different types of particle interactions, resulting in alpha decays contributing to the background. Therefore, the experimental sensitivity is too limited to make confident determinations about the data. For this …

Flood Risk Assessment And Water Diversion Scenarios For Terre Haute, Indiana Based On Time-Series Remote Sensing And In-Situ Measurements, Hung Q. Ha

2026 Spring Reports (Terre Haute)

The City of Terre Haute has faced growing concerns over the increasing frequency and intensity of riverine flooding along the Wabash River, alongside risks associated with urban inundation. To create more safely floodable areas – specifically by locating wetland areas using GIS and researching government ordinances on development in those areas – the City of Terre Haute sought to better understand flood patterns and identify viable floodwater diversion strategies. The project was formally titled as “Pattern of Flooding along the Wabash River in Vigo County and Scenarios for Floodwater Diversion”. Faculty and students from Geospatial Intelligence Lab, Department of Earth …

Utah Growing Water Smart: The Water-Land Use Integration Guidebook For Central Utah, Kelly Kopp, Joanna Endter-Wada

Utah Growing Water Smart

The Utah Growing Water Smart workshop brings together key staff and water and land use planning decision makers to help communities build a more resilient and sustainable water future. The workshop uses a range of public engagement, planning, communication, and policy implementation tools to help community teams realize their water efficiency, smart growth, watershed health, and water resiliency goals.

Gauss Composition And Orthogonal Modular Forms On Binary Lattices, Haochen Wu

Dartmouth College Ph.D Dissertations

We revisit Gauss composition over a general base scheme, with a focus on orthogonal groups. We show that the Clifford and norm functors provide a discriminant-preserving equivalence of categories between binary quadratic modules and pseudoregular modules over quadratic algebras. This perspective synthesizes the constructions of Kneser and Wood, reconciling algebraic and geometric approaches and clarifying the role of orientations and the natural emergence of narrow class groups.

As an application, we restrict to lattices and show that binary orthogonal eigenforms correspond to Hecke characters. Using theta series, we show the explicit connection between Hilbert modular forms and orthogonal modular forms …

Incipient: Contemporary Wildfire Management In The American West, Carlyn A. Mcaleer

Environmental Studies Senior Theses

The frequency, severity, and total area burned by wildfires has escalated dramatically alongside a similar increase in federal suppression spending. However, contemporary management remains rooted in a suppression‑centric framework that originated in the early‑20th‑century. Our current wildfire management practices are unsustainable in the face of this growing threat. Using an approach that blends historical analysis and spatial analysis, this thesis asks how current spatial patterns of burn probability (BP) overlap with existing fire-response infrastructure and population in eight states (Arizona, Colorado, Idaho, Montana, New Mexico, Nevada, Utah, Wyoming) in the American West and which barriers inhibit the adoption of proactive …

Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …

A Novel Hierarchical Multi-Agent System For Payments Using Llms, Donghao Huang, Joon Kiat Chua, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Large language model (LLM) agents, such as OpenAI’s Operator and Claude’s Computer Use, can automate workflows but unable to handle payment tasks. Existing agentic solutions have gained significant attention; however, even the latest approaches face challenges in implementing end-to-end agentic payment workflows. To address this gap, this research proposes the Hierarchical Multi-Agent System for Payments (HMASP), which provides an end-to-end agentic method for completing payment workflows. The proposed HMASP leverages either open-weight or proprietary LLMs and employs a modular architecture consisting of the Conversational Payment Agent (CPA - first agent level), Supervisor agents (second agent level), Routing agents (third agent …

Task Complexity Matters: An Empirical Study Of Reasoning In Llms For Sentiment Analysis, Donghao Huang, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) with reasoning capabilities have fueled a compelling narrative that reasoning universally improves performance across language tasks. We test this claim through a comprehensive evaluation of 504 configurations across seven model families—including adaptive, conditional, and reinforcement learning-based reasoning architectures—on sentiment analysis datasets of varying granularity (binary, five-class, and 27-class emotion). Our findings reveal that reasoning effectiveness is strongly task-dependent, challenging prevailing assumptions: (1) Reasoning shows task-complexity dependence—binary classification degrades up to -19.9 F1% points (pp), while 27-class emotion recognition gains up to  +16.0 pp; (2) Distilled reasoning variants underperform base models by 3–18 pp on simpler tasks, …

Enhancing Pointing Gestures Of Non-Hmd Users In Asymmetric Collocated Mixed Reality Collaboration, Nam-Dang Vo, Van-Vinh Thai, Anthony Tang, Khanh-Duy Le

Research Collection School Of Computing and Information Systems

A common collocated group setting in mixed-reality (MR) collaboration is a person wearing a MR headset (HMD user) and presenting MR contents to audiences who are not provided with such specialized devices (Non-HMD users). In this setting, while Non-HMD users can view the MR environment shown on a large physical display, it still remains challenging for the HMD user to interpret their pointing gesture when they spatially refer to objects in the MR environment. To address this, we designed and evaluated two pointing techniques—SCREEN and SCREEN+SPACE—that support Non-HMD users in referring to MR content. Screen pointing allows users to refer …

Adaptive Outlier Detection Over Data Stream, Rui Zhu, Mingyuan Jiang, Xiaochun Yang, Baihua Zheng, Bin Wang, Tao Qiu

Research Collection School Of Computing and Information Systems

Continuous distance-based outlier detection in streaming data poses significant challenges and has a wide range of practical applications. Traditional threshold-based methods perform well under stable streaming conditions, where fixed parameters remain effective. However, they often struggle with dynamic data distributions and high stream speeds, leading to suboptimal performance, limited control over the number of returned outliers, and failure to meet real-time detection requirements. To address these issues, this paper introduces a novel Recall and Proportion-Aware Outlier Detection (RPA-OD) query. In RPA-OD, ρ defines a distance relaxation that enables real-time outlier detection. Specifically, objects with fewer than k neighbors within the …

Navigating Oer Support Without Drowning In Ai, Lydia Burrage-Goodwin, Christine Moynihan

Joseph P. Healey Library Publications

This was a presentation at the June 2026 Boston Library Consortium at Connecticut College.

UMB Healey Librarians Lydia Burrage-Goodwin and Christine Moynihan talk about what experiences they have had with faculty using OER and AI, which led them to develop ethics guidelines to support librarians who work with faculty authors. Attendees learned about creating AI use statements for OERs, using AI transparency logos, and applying open licenses to fully AI generated content as well as OER adaptations.

Deployment-Aware Deep Learning For Computer Vision: Efficient Architectures From 3d Segmentation To Mixed Reality, Bahar Uddin Mahmud

Dissertations

Deep learning has become the dominant approach for solving vision-centric problems; however, its successful deployment in real-world applications remains limited by high computational cost, data dependency, and insufficient integration with practical and human-centered environments. While state-of-the art deep learning models often achieve impressive performance in controlled settings, they frequently fail to generalize or operate efficiently under deployment constraints such as limited resources, complex data modalities, and real-time interaction requirements. These limitations motivate the need for a deployment-oriented deep learning framework that balances accuracy, efficiency, and practical usability.

This dissertation investigates the design and deployment of efficient deep learning architectures for …

Reduced Product Type Monoid-Module Extensions, Darryl Jent

Dissertations

In 1955, I. M. James introduced the James Construction, a free topological monoid that models the loops on the suspension of a given space. In 1969, S. Y. Husseini generalized this idea to RPT monoids: topological monoids with a free-like monoid structure that can be used to model a broader class of loop spaces. In order to prove that these topological monoids are models of loop spaces, both I. M. James and S. Y. Husseini constructed contractible spaces on which these topological monoids act. We define a topological module as a space equipped with an action by a topological monoid. …