Digital Commons Network^™

Open Neighbourhood Edge Degree And Metric Descriptors Qspr And Multi Criteria Analysis Of Chemicals And Antiviral Drugs, Gayathri A Ms

Theses and Dissertations

Chemical Graph theory offers powerful computational methods for evaluating chemical structures, significantly impacting cheminformatics and drug analysis. It provides a robust mathematical framework to represent, model, and analyse molecular systems through topological indices and graph invariants. These indices serve as effective numerical descriptors, encapsulating significant structural information that enhances the prediction of physicochemical and biological properties. This thesis utilizes mathematical modeling, algorithmic computation, and decision making process to derive extensive insights to drug discovery and molecular analysis.

The thesis introduces a new class of topological indices ONE1, ONE2, ONE3, ONE4, ONE5,ONE6 and ONE7 based on open-neighbourhood-edge-degree and it evaluates the …

Cooperative Evolution For Discovering Scalable Spiking Neural Network Architectures, Catherine C. Rodriquez

LSU Master's Theses

SNNs are a foundational model in neuromorphic computing, where efficient architectures must be discovered for a wide range of applications. Evolutionary methods, such as EONS, offer a flexible approach to this search but become increasingly difficult to scale as task complexity grows due to the rapidly expanding combined topology–parameter search space and associated memory demands. To address this challenge, we propose a co-evolutionary ensemble framework in which a population of candidate SNNs is evolved with fitness defined by each network’s marginal contribution to group performance. Grounded in cooperative game theory and difference evaluation functions from multiagent systems, this formulation provides …

Mapping And Diagnosing Local Climate Zones For Urban Heat Assessment And Planning In Tropical Cities, Inuwa Sani Sani, Adi Wibowo

Journal of Environmental Science and Sustainable Development

Rapid urbanization and rising heat risk are intensifying thermal stress and environmental degradation in tropical cities. This study applies the Local Climate Zone (LCZ) framework to examine how urban morphology influences land surface temperature (LST) and to support evidence-based urban planning and climate adaptation in Makassar, Indonesia. We hypothesized that compact built LCZs (1–3) exhibit significantly higher LST than vegetated LCZs (A–G). Landsat 8 OLI and MODIS LST datasets (2013–2023) were processed in Google Earth Engine to evaluate decade-long urban development and thermal dynamics. LCZs were classified using a Random Forest (RF) model trained with approximately 100 manually digitized polygons …

Energy Efficiency Limits And Future Electricity Demand Of Computing Devices, Ricardo Pinto, Tiago Domingos, Paul E. Brockway, Matthew Kuperus Heun, Tânia Sousa

University Faculty Publications and Creative Works

• ICT (information and communication technologies) represented 4% of the world electricity consumption in 2020; 
• Computing devices represented 2% of the world electricity consumption in 2020; 
• In recent scenarios datacentre electricity demand reaches 3% of world electricity in 2030, and more than 4% in 2035

Final Basinwide Quality Management Plan (Qmp) – 2026-2030, Revision 0, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Chi Meta-Project Ecosystem Overview - Spring 2026, David B. Smith

Publications and Research

This paper offers a high-level account of the Center for Holistic Integration’s (CHI) meta-project ecosystem as visualized in the included system map. CHI provides an organizational structure framed around persistent meta-projects that support and extend individual initiatives across curriculum, scholarly and applied research, infrastructure, artistic production, AI development, cultural inquiry, and external partnerships. Rather than presenting the map as a static inventory of projects, the paper examines how its core domains function as living systems through which knowledge, tools, documentation, participants, and collaborations can accumulate over time. It also considers how CHI-mediated connectivity, institutional integration, and external funding allow the …

Perspectives Of Scholars, Families, And Advisors On 360-Degree Video Technology In Graduate Education, Oluwatobi A. Mogbojuri, Bridget A. Walsh, Matthew Aguirre

Journal of Human Sciences and Extension

This study explored the experiences of scholars in creating and sharing 360-degree videos, as well as the perspectives of families and advisors who viewed the videos. Focus groups and individual interviews were conducted online using a videoconferencing platform. Perspectives from 20 participants (15 scholars, three advisors, and two family members) were analyzed using thematic analysis. Three primary themes were identified: (1) barriers to 360-degree video use, (2) perspective shifts and limited change, and (3) storytelling and scholar visibility. Findings suggest that 360-degree video technology may be an innovative tool for enhancing recruitment and retention, especially for historically marginalized groups, through …

The Implementation Of Smart City Initiatives In Addressing Climate Change Challenges For The Transformation Of Jakarta Into A Resilient Global City, Roby Dwiputra, Nurulitha Andini Susetyo, Apriano Hanindito Amanza

CSID Journal of Infrastructure Development

Jakarta, a densely populated delta city and Indonesia's former capital undergoing post-relocation transformation, faces escalating climate change impacts, including land subsidence and tidal flooding. Annual subsidence rates of 5–25 cm in northern areas and recurrent tidal floods, including the December 2025 event, pose significant threats to urban sustainability and economic stability. This study employs a qualitative descriptive–analytic approach using a single-case study of Jakarta. Smart city initiatives are examined as governance instruments for climate resilience, drawing on secondary data from regulatory documents, real-time digital monitoring platforms, and global smart city performance indicators. The analysis applies thematic and comparative techniques supported …

Prediction Of Satellite Temperature During An Orbit Of A Cubesat, Michael Reynolds

Honors Theses

This thesis develops a thermal-simulation strategy for predicting CubeSat component temperatures, applied to Jag-Sat-1, a CubeSat developed at the University of South Alabama and deployed from the International Space Station in 2022. The orbit was reconstructed from two-line element (TLE) data using simplified general perturbations (SGP4) propagation, and spacecraft attitude was recovered from onboard gyroscope measurements. Sunlight, penumbra, and umbra intervals were computed geometrically, and the external radiative environment — direct solar, Earth infrared, and albedo heat fluxes — was modeled using orientation-dependent view factors. These time-varying fluxes drove a transient finite-element thermal simulation of the full satellite geometry in …

Beyond Semantic Matching: Integrating Graph Structures, Boolean Logic, And Interactive Aggregation In Modern Retrieval, Quan Mai

Graduate Theses and Dissertations

Modern Natural Language Processing (NLP) and Information Retrieval (IR) systems have achieved remarkable success in semantic understanding; however, they continue to struggle with complex logical reasoning, structural interactions, and dynamic aggregation. This dissertation presents a comprehensive framework to enhance the structural, logical, and interactive capabilities of language models and retrieval systems across four progressive studies. First, we address the challenge of modeling dynamic conversational logic in online debates. We introduce a Sequence Graph Network (SGN) that captures the temporal and interactive exchange of ideas—such as counterarguments and reinforcements—by updating node features sequentially through a novel Sequence Graph Attention (SGA) layer. …

Potassium Fertilization Timing And Critical Stalk Potassium Concentration As Tools To Improve Corn Production, Gabriela Andrade Leite Mengez

Graduate Theses and Dissertations

Potassium (K) is a common yield-limiting nutrient in Mid-Southern U.S. corn (Zea mays L.) production, emphasizing the importance of effective diagnostic tools to support fertilizer decision-making. This study integrated two approaches to improve K management in irrigated corn systems: (i) evaluating K fertilization timing to identify in-season opportunities for correcting K deficiency, and (ii) developing a corn stalk-based diagnostic test to assess end-of-season K and nitrate-nitrogen (NO₃-N) status and fertilizer adequacy. Seven (2024-2025) and eight (2023-2024) field trials were conducted across Arkansas for the K application timing and stalk testing studies, respectively. For the K timing study, fertilizer-K (112 kg …

Robust Graph Learning On The Web: Challenges, Methods, And Applications, Ao Xiang, Yang Liu, Guansong Pang, Yuanhao Ding, Hezhe Qiao, Dawei Cheng, Qing He

Research Collection School Of Computing and Information Systems

Graph learning is transforming web intelligence, powering applications from recommender systems to anomaly detection. However, most existing approaches implicitly assume ideal conditions where training and testing data are accurate, complete, and free from manipulation. In reality, web environments rarely exhibit such stability. Dynamic user behavior, incomplete or outdated content, adversarial interference, and sudden distribution shifts can all erode the reliability of even state-of-the-art models, leading to biased or unsafe outcomes. This tutorial provides a comprehensive survey of emerging strategies for robust graph learning on the web. We first present a structured taxonomy of the principal robustness threats specific to web …

A Machine-Learning-Based Systematic Framework For Modeling Compression And Recompression Indices For Florida Soils, Michael Morales

Doctoral Dissertations and Master's Theses

This thesis develops a machine-learning framework for estimating the compression index and the recompression index of Florida soils from routinely measured index properties, and reports two studies that build it. Consolidation settlement design requires both indices, and both are obtained from the incremental-loading oedometer test, which occupies a specimen for one to two weeks; the index tests that accompany it are complete within hours. Empirical correlations have filled that interval since the 1950s, but their coefficients are calibrated on specific soil populations and transfer poorly between regions. The first study analyzes 376 consolidation tests compiled for the Florida Department of …

Online Ppo-Based Multi-Hop Task Offloading Strategy For Vehicular Edge Computing, Wenzhu Zhang, Yuewei Bian, Fuli Xiong, Siqi Cai

Journal of System Simulation

Abstract: To address the problems of frequent communication link interruptions caused by dynamic network topologies and the sharp increase in computational complexity triggered by high-dimensional decision spaces in the vehicular edge computing (VEC) environment, a multi-hop task offloading strategy for VEC based on an online PPO algorithm was proposed. A multi-hop task offloading optimization model simultaneously considering link effective time, transmission rate, and computing resource constraints was constructed; a multi-hop A* path search algorithm integrating link stability and end-to-end delay was designed; an online offloading decision framework based on PPO was proposed, which transformed the 0-1 mixed integer nonlinear programming …

Comparative Analysis Of Task Scheduling In Multi-Tier Fog-Cloud Computing: From Classical Approaches To Greedy Multi-Objective Optimization, Zafril Rizal M. Azmi, Najmul Haque, Saydul Akbar Murad

Faculty Publications

Fog computing extends cloud services to the network edge, enabling low-latency processing for time-sensitive applications. However, scheduling complexity significantly increases due to heterogeneous resources, dynamic workloads, and strict Quality-of-Service (QoS) constraints. Although numerous scheduling techniques have been proposed, existing studies often assess only a narrow subset of algorithms or rely on offline metaheuristics unsuitable for real-time environments. This paper presents a comprehensive comparative evaluation of twelve scheduling algorithms, including five classical, one heuristic, and six metaheuristic-inspired approaches, within a realistic 20-node multi-tier fog-cloud topology. Across 1,365 experiments spanning seven utilization levels, we analyze each algorithm’s deadline adherence, load distribution, and …

How Important Is Clean Energy To Utahns?, Elizabeth Brunner, Stacia Ryder

Utah People and Environment Poll (UPEP)

Utah's energy mix has changed significantly over the past several decades as it has moved to cleaner forms of generation. For example, according to the Energy Information Administration, in 2024, coal fueled about 45% of Utah's total electricity net generation, down from 75% in 2015. As can be seen in the chart below, the state anticipates demand growth, with further reductions in coal alongside a significant increase in solar, storage, and natural gas by 2032. Though not represented in these charts, plans for nuclear power generation have been proposed in Brigham City as well as outside of Green River. Utah …

It's All In The (Exponential) Family: An Equivalence Between Maximum Likelihood Estimation And Control Variates For Sketching Algorithms, Keegan Kang, Kerong Wang, Ding Zhang, Rameshwar Pratap, Bhisham Dev Verma, Benedict Wong

Faculty Conference Papers and Presentations

Maximum likelihood estimators (MLE) and control variate estimators (CVE) have been used in conjunction with known information across sketching algorithms and applications in machine learning. We prove that under certain conditions in an exponential family, an optimal CVE will achieve the same asymptotic variance as the MLE, giving a fixed point algorithm for the MLE. Experiments show the fixed point algorithm is faster and numerically stable compared to other root finding algorithms for the MLE for the bivariate Normal distribution, and we expect this to hold across distributions satisfying these conditions. We show how this algorithm leads to reproducibility for …

Digital Twin-Assisted Optimization Of 6g Wireless Networks: Ensuring Deterministic Communication, Yingpu Nian, Bo Yi, Xingwei Wang, Sajal K. Das

Computer Science Faculty Research & Creative Works

With the rapid advancement of 6G technology and the increasing use of smart devices, Deterministic 6G Wireless Networks (D6WN) have emerged to meet the growing network transmission demands. In particular, applications such as autonomous vehicles, remote surgery, and industrial automation require extremely low transmission latency to function effectively, highlighting the critical need for D6WN in supporting these time-sensitive use cases. Yet, the conventional TCP/IP framework lacks effective unified traffic and congestion control scheduling, aggravating latency and uncertainty, posing a challenge to ensuring reliable real-time critical applications. To address the challenges of deterministic transmission in D6WN, this paper integrates Digital Twin …

Modeling And Simulation Of Efficient State Information Diffusion In Wireless Ad Hoc Networks, Mengyao Jia, Shaozhu Gu, Junhan Wang, Denghao Wang, Du Xu, Xiaoning Zhang

Journal of System Simulation

Abstract: To solve the problems of significant communication overhead and limited real-time response capability in the traditional flooding-based state diffusion mechanism, an efficient diffusion algorithm based on regional partitioning and information compression was proposed. A multi-dimensional feature clustering method integrating geographic distance and link quality was used to achieve high-cohesion network partitioning through weighted Euclidean distance and the K-means algorithm; a dynamic selection mechanism for representative nodes was designed to conduct comprehensive scoring by combining the link quality and geographic centrality of nodes, realizing the efficient compression and aggregated transmission of regional information. Simulation results indicate that the algorithm significantly …

Ethos: A Computational Framework For Material Culture Research, Chelsea L. Grafe

Department of Textiles, Merchandising and Fashion Design: Dissertations, Theses, and Student Research

Museum catalog records make large collections searchable, but they do not always preserve the reasoning behind the claims they contain. A record may present a quilt's identity as settled while leaving the reasoning behind that claim invisible, making it difficult for later researchers to check, question, or reuse. This project asks whether museum catalog data can be analyzed in a way that keeps each analytical claim connected to the evidence that supports it. To test this question, the project applies a material-first computational framework named Ethos. Ethos formalizes an object-centered inquiry sequence in which material dependencies establish where analysis begins …

Math 119: Math For Elementary School Teachers Syllabus, Seth Lehman

Open Educational Resources

OER course syllabus for Math 119, Math for Elementary School Teachers, at Queens College

Accountable Agents In Software Engineering: An Analysis Of Terms Of Service And A Research Roadmap, Christoph Treude

Research Collection School Of Computing and Information Systems

AI coding assistants and autonomous agents are becoming integral to software development workflows, reshaping how code is produced, reviewed, and maintained. While recent research has focused mainly on the capabilities and impacts of productivity of these systems, much less attention has been paid to accountability: who is responsible when agents generate, modify, or recommend code? In practice, accountability is defined through the Terms of Service (ToS) and related policy documents that govern the use of AI-powered development tools.In this vision paper, we present a comparative analysis of the Terms of Service for widely used AI coding assistants and agent-enabled development …

Operationalizing Ethics For Ai Agents: How Developers Encode Values Into Repository Context Files, Christoph Treude, Sebastian Baltes, Marc Cheong

Research Collection School Of Computing and Information Systems

As AI coding agents become embedded in software development workflows, developers are beginning to operationalize ethical principles by encoding behavioral rules into repository-level context files for AI agents, such as AGENTS.md files. Rather than examining the ethics of AI agents in the abstract, this vision paper investigates how ethics and values are already being translated for AI agents into actionable instructions that shape agent behavior. Through a preliminary investigation, we find that developers are already embedding guidance related to fairness, accessibility, sustainability, tone, and privacy. These artifacts function as a developer-authored governance layer, translating abstract principles into situated, natural-language directives …

A Dataset Of Agentic Ai Coding Tool Configurations, Matthias Galster, Seyedmoein Mohsenimofidi, Levi Böhme, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes

Research Collection School Of Computing and Information Systems

Agentic AI coding tools such as Claude Code and OpenAI Codex execute multi-step coding tasks with limited human oversight. To steer these tools, developers create repository-level configuration artifacts (e.g., Markdown files) for configuration mechanisms such as Context Files, Skills, Rules, and Hooks. There is no curated dataset yet that captures these configurations at scale. This dataset, collected from open-source GitHub repositories, fills that gap. We selected 40,585 actively maintained repositories through metadata filtering, classified them using GPT-5.2 to identify 36,710 as belonging to engineered software projects, and systematically detected configuration artifacts in these repositories. The dataset covers 4,738 repositories across …

Tranx-Adapter: Bridging Artifacts And Semantics Within Mllms For Robust Ai-Generated Image Detection, Wenbin Wang, Yuge Huang, Jianqing Xu, Yue Yu, Jiangtao Yan, Shouhong Ding, Pan Zhou, Yong Luo

Research Collection School Of Computing and Information Systems

Rapid advances in AI-generated image (AIGI) technology enable highly realistic synthesis, threatening public information integrity and security. Recent studies have demonstrated that incorporating texture-level artifact features alongside semantic features into multimodal large language models (MLLMs) can enhance their AIGI detection capability. However, our preliminary analyses reveal that artifact features exhibit high intra-feature similarity, leading to an almost uniform attention map after the softmax operation. This phenomenon causes attention dilution, thereby hindering effective fusion between semantic and artifact features. To overcome this limitation, we propose a lightweight fusion adapter, TranX-Adapter, which integrates a Task-aware Optimal-Transport Fusion that leverages the Jensen-Shannon divergence …

Rendering Data Unlearnable By Exploiting Llm Alignment Mechanisms, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly trained on massive, heterogeneous text corpora, raising serious concerns about the unauthorised use of proprietary or personal data during model training. In this work, we address the problem of data protection against unwanted model learning in a realistic blackbox setting. We propose Disclaimer Injection, a novel data-level defence that renders text unlearnable to LLMs. Rather than relying on model-side controls or explicit data removal, our approach exploits the models’ own alignment mechanisms: injecting carefully designed alignment-triggers to prevent effective learning. Through layer-wise analysis, we find that finetuning on such protected data induces persistent activation …

Pharmed. System Manual: Hololens Application, Eden Woldeselassie

Systems Manuals - 2026

This document provides the full life cycle of PharmEd HoloLens. PharmEd stands for Pharmacy Education. The overall document will go through the complete system manual by going over requirements, followed by design, how to install the application, how to upload the application to Microsoft store, troubleshooting and source code. The first section will explain the background, the existing problems and why the need to develop PharmEd.  Here techniques of requirement gathering and some statistics will elaborated. The following section discusses about functional requirements. The requirement section includes subtopics: functional and nonfunctional requirements for both -programmer and end user- and the …

Robot Remote Control Utility, Jeremy Cantu, Paul Uhlig

Systems Manuals - 2026

The purpose of this document is to describe the Robot Control Management Utility developed in the course of this graduate project. Information included in this document will include the background of the developed product, as well as the functional requirements, data structures, software modules, interface design, installation guide, and sample and troubleshooting guides.

E Classroom+, Ami B. Jariwala

Systems Manuals - 2026

A software platform that enhances many processes correlated with learning is called a learning management system (LMS). It is also known as a management software package that enables the delivery of learning content, resources and activities and also that handles the correlated administration operations. In classrooms, today, teachers, are being commenced with convenience to remodel learning from a traditional transmission model to a student-centered model where students are mostly responsible for their learning. The research conveys that in order to remodel learning, schools require to support a student-centered approach where students can be supported in finding, analyzing, organizing, evaluating, internalizing, …

Smart Atm, Majid Hakeem

Systems Manuals - 2026

The Smart ATM is a new system that goal is to create a new experience for ATMs users by creating a different way of using the ATM. It would protect users from germs and bacteria. Instead of using buttons and touch screens, the main input for this system will be the motion sensor. To specify, the system uses Microsoft Kinect, which is the motion sensor for the Xbox One.

This document is a user guide, which is intended to give assistance to users for using the Smart ATM. This document contains an application overview, list of user requirements, the design …