Computer Sciences Commons^™

Load Profile Analysis And Forecasting For Rural Mini Grids In Uganda, Prossy Mutesi, Santos L. Kihwele, Emmanuel S. Matee

Tanzania Journal of Science

Accurate load forecasting is essential for the reliable and cost-effective operation of rural mini grids, where constrained generation capacity and high penetration of renewable energy resources require well-informed operational decisions. This study examines electricity demand characteristics and forecasting performance for the Buzaami and Ssenyondo mini grids in Uganda, with particular focus on diurnal load profiles, peak demand behavior, and seasonal variability. 2022 operational data show extended peak demand from early morning to late evening, driven by socio-economic activities that strain resource scheduling and reliability management. To address these challenges, the study evaluates and compares Long Short-Term Memory (LSTM) networks, fuzzy …

Robust Real-Time Uav Target Tracking With Onboard Vision-Based Yaw Control, Rylan Malarchick, Jose Castelblanco, Enrique Amaya, Carmen Dimario, Graysen Brinkman, Chirag Kumar, Kiwon Yoon, Sajid Berhane

Beyond: Undergraduate Research Journal

Autonomous tracking of agile unmanned aerial vehicles (UAVs) presents significant challenges for real-time perception and control systems. This work presents AIRHOUND (Autonomous Intelligent Rotorcraft for Hostile Object Unified Navigation and Detection), a UAV platform implementing vision-based yaw tracking through a modular ROS2 software architecture. The system employs YOLOv8 object detection optimized with NVIDIA TensorRT for embedded deployment on an NVIDIA Jetson Orin companion computer. Detected targets are processed through a geometric tracking module that converts pixel coordinates to angular yaw errors using pinhole camera intrinsics, with a proportional controller generating rate-limited yaw commands. These commands are streamed to a PX4 …

Synthetic-Chicken-Fillets, Chirantan Sen Mukherjee, Seung-Chul Yoon, William J. Beksi

Agriculture

This Synthetic-Chicken-Fillets dataset contains 1,000 synthetic 3D meshes designed to capture the natural variance and size diversity of real broiler fillets. The collection was developed to test automated woody breast detection algorithms within a physics-based simulation environment. We utilized a seed dataset of 2D depth maps derived from 40 real-world RGBD point cloud scans. These real depth maps were fed into a few-shot transfer learning pipeline using a generative adversarial network architecture. The resulting generated depth maps were reconstructed back into 3D meshes. The length and thickness of each mesh were randomly scaled based on physical measurements of real broiler …

Beyond The Best Prompt: A Coverage View Of Multilingual Reasoning, Harshiv Mistry

University Honors Theses

Multilingual LLMs reason more accurately in English than in other languages, and recent work links part of this gap to reasoning behavior: native-language traces contain fewer cognitive behaviors (verification, backtracking, subgoal setting, backward chaining) that support effective problem solving. We test whether prompting for these behaviors at inference time narrows the gap, across seven conditions varying chain-of-thought, instruction and reasoning language, and cognitive-behavior descriptions, on two models, three languages. We find that English-scaffolded reasoning is the strongest single strategy on both models, closing the Hindi gap on Qwen, though the explicit scaffold's value over plain chain-of-thought is model-dependent. Beyond aggregate …

Digital Bodily Autonomy: Consent Issues, Labor Displacement, And Legal Understandings Of Ai Generated Deepfake Pornography, Mariah Barrett

Undergraduate Theses, Capstones, and Recitals

In the United States, nonconsensual pornographic deepfakes are becoming an increasingly prevalent problem as AI deepfake creation software improves and becomes widely available. Despite this, patchwork legislation across the country is inconsistent and conflicting regarding this issue. In this paper, I explore the background of pornography and obscenity laws and demonstrate how these frameworks are not properly constructed to apply to the digital sphere. Then, I address major themes within deepfake literature such as consent issues, bodily autonomy, labor displacement, and verifiable identity as a commodity through the case study of OnlyFans. I explore current and proposed legislation within the …

A Novel, Embedding-Based Approach To Longitudinal Survey Data Imputation, Julia Rezvani

University Honors Theses

Longitudinal surveys are ubiquitous in the social sciences as a means of tracking changes in behavior and opinions with time and identifying potential causal mechanisms. These surveys are frequently plagued by missing data and semantic drift, both of which limit their effectiveness and scientific utility. Imputation algorithms allow researchers to fill gaps in collected survey datasets, imperfectly reconstructing lost data. Although deep learning algorithms have been used in imputation to great success, approaches which simultaneously leverage the semantic and temporal structure of longitudinal surveys have not yet been developed. We propose a novel imputation architecture which is capable of leveraging …

Data Governance Maturity, Ai Integration, And Equity In Colorado K-12 Public Schools, John R. Curtin

Electronic Theses and Dissertations

Colorado's 179 K-12 public school districts operate as autonomous governance units, each responsible for securing and managing student data assets that span health, financial, residential, and academic records. The accelerating integration of artificial intelligence (AI) and machine learning (ML) tools into administrative workflows, productivity software, and instructional platforms has fundamentally altered the risk landscape for student data, yet governance frameworks at the state, district, and school levels have not kept pace. This dissertation investigates whether Colorado's decentralized educational governance structure is institutionally capable of producing equitable, secure, and sustainable data governance outcomes in the AI era.

Drawing on Institutional Theory …

Evaluation And Distillation Of Source Code Generation Tasks By Large Language Models, Danny Brahman

Electronic Theses and Dissertations

Large Language Models (LLMs) are predominantly assessed based on their common sense reasoning, language comprehension, and logical reasoning abilities. While models trained in specialized domains like mathematics or coding have demonstrated remarkable advancements in logical reasoning, there remains a significant gap in evaluating their code generation capabilities. Existing benchmark datasets fall short in pinpointing specific strengths and weaknesses, impeding targeted enhancements in models’ reasoning abilities to synthesize code.

To bridge this gap, this thesis introduces two novel contributions: CodeEval and CodeQual. CodeEval is an innovative, pedagogical benchmarking method that mirrors the evaluation processes encountered in academic programming courses. It comprises …

Uniform Stability Of Katyusha In Strongly-Convex Settings, Don Li

University Honors Theses

Acceleration of convergence and reduction of variance constitute a trade-off in the design of stochastic optimization machine learning algorithms. Katyusha was introduced to address this trade-off, synthesizing Nesterov Accelerated Gradient (NAG) and Stochastic Variance-Reduced Gradient (SVRG) into a single first-order optimizer with promising empirical performance. However, the generalization properties of Katyusha remain largely unexplored. We conjecture that, in the smooth quadratic regime (i.e., under assumptions of strong convexity and smoothness of the loss function, and boundedness of gradients), Katyusha is uniformly stable in the sense of Bousquet and Elisseeff. Instantiating our framework for NAG, we extend the use of Lyapunov …

Ai In Education And Information: Tool, Threat, Or Teammate? How Academia Is Shaping The Future Of Intelligent Work, Essraa Nawar

Library Presentations, Posters, and Audiovisual Materials

Artificial intelligence is rapidly changing the future of intelligent work across education, healthcare, leadership, communication, workplace culture, and health information management. Yet while AI adoption continues accelerating, institutions and professionals are still trying to understand what this transformation actually means for people, learning, careers, ethics, trust, governance, and human judgment. This interactive and forward-thinking panel brings together voices from higher education and healthcare information management to explore how AI is reshaping classrooms, workplaces, healthcare systems, professional identity, and future workforce expectations across generations.

Rather than focusing only on technology itself, the conversation will examine the broader cultural and organizational shift …

A Protestant Response To The Pope’S Magnifica Humanitas On Ai, Derek Schuurman

University Faculty Publications and Creative Works

Pope Leo XIV released his first papal encyclical, Magnifica Humanitas, on May 25, a roughly 42,000-word document outlining a Catholic response to recent developments in AI. I had been eagerly anticipating this encyclical and spent much of the release day poring over the text. While there have been other Christian efforts to release statements about AI, this is the first comprehensive statement from the Catholic Church. What follows is a summary of the document, followed by my own response.

[Birds-Of-A-Feather] A Tri-Level Roadmap To Ai-Ready Universities: Strategy, Operations, Deployment, Sarah Forzetting, Rochelle Lundy, Ahmad Pratama, Karryl Kim Sagun Trajano, Antara Chakraborthy, Yasmine Wong

FORCE 2026

This panel discussion by three institutions will offer three approaches to conceptualizing and supporting AI use at the national, local, and individual levels.

Nanyang Technological University will frame the discussion by examining AI as a social good, highlighting how even advanced initiatives such as Singapore’s face equity gaps that risk leaving vulnerable populations behind. The panelist will further outline how information professionals and other key stakeholders can play a critical role in bridging these gaps in the pursuit of widespread public AI literacy. Stanford University Libraries will outline difficulties institutions have in operationalizing guidelines to help researchers bring a project …

Developing An Assessment Framework To Support Critical Evaluation Of Ai-Powered Academic Search Engines, Huajin Wang

FORCE 2026

As AI-powered tools are emerging in all aspects of research, it’s challenging for researchers, students, and librarians alike to assess the benefit, usefulness, and risks associated with a new AI-powered tool or AI-enhanced features of an existing one. To address this challenge, Carnegie Mellon University Libraries is developing a Tool Evaluation Framework to help users understand how AI-powered tools work, initially focused on AI-enhanced academic search engines. By evaluating criteria such as mechanisms for document retrieval, processes for content generation, and the quality of outputs, this framework guides users to carefully consider the strengths and weaknesses of a tool before …

Supporting Fair Practices In Scholarly Publishing With The Editorial Reference Handbook, Susanna-Assunta Sansone, Allyson Lister, Rebecca Taylor-Grant, Matthew Cannon

FORCE 2026

Co-produced by academics and publishers (incl. CUP, Cell Press, EMBO Press, Taylor & Francis, GigaScience Press, OUP, PLOS, Springer Nature), the Editorial Reference Handbook (https://publishers.fairassist.org) assists scholarly publishers in supporting the sharing of digital research objects and in operationalising FAIR research practices by addressing gaps in editorial workflows, policy implementation and stakeholder alignment. The Handbook comprises three interrelated components—a checklist, detailed guidance documentation, and a flowchart—intended primarily for in-house editorial staff while also providing value to reviewers, authors, and service providers.

Beside this practical collaboratively developed product, the Handbook is also a socio-technical pilot to improve the culture …

Ten Years Of Tuwhera: A Commitment To Sustaining Open Access Publishing, Donna Coventry

FORCE 2026

Tucked away, far from the conference circuit, is a part of the world which doesn’t tend to make the headlines when it comes to open access initiatives. New Zealand and by extension, the South Pacific, is a region struggling with a history of colonisation and trying to make systematic change around decolonisation - open access to research about ‘our place in the world’ is vitally important. 

Ten years ago Auckland University of Technology’s library (Te Mātāpuna) made the decision to start hosting Diamond open access journals. Starting with two established journals, the service was named Tuwhera which can be translated …

Asian Open Research Data And Its Potential For Ai: Bridging The Digital Divide Through Strategic Data Sharing, Mark Hahnel, Simon Porter

FORCE 2026

The growing momentum for open research data in Asia intersects with global advances in artificial intelligence (AI). Open data policies and infrastructures are increasingly recognized as critical enablers of research equity, reproducibility, and innovation. This talk examines the current state of open academic data, highlights economic and scientific arguments for its adoption, and explores the transformative potential of Asian open data ecosystems in powering AI-driven discovery. Drawing on global examples such as the Protein Data Bank and emerging health datasets, the discussion positions Asian institutions to leverage open strategies that simultaneously meet compliance mandates, enhance visibility, and accelerate breakthroughs in …

Managing Ai Bot Access To Open Scholarly Infrastructures, Petr Knoth

FORCE 2026

The rapid rise of generative AI has created unprecedented demand for large, high-quality research corpora. Open access repositories and other open scholarly infrastructures have therefore become primary sources for AI bots, because they host research that is not universally reliable, but remains far more evidence-based than most web content. This is both an opportunity and a strain: repositories are now more valuable than ever, but machine traffic brings sustainability, capacity and policy challenges. Repositories may be able to scale, but who should fund that scaling, and under what conditions?

The core dilemma is how to curb abusive high-load bot activity …

Beyond The Launch: Seven Years Of Sustaining An Open Educational Resource After The Grant Ends, Susan Gardner Archambault

FORCE 2026

This presentation shares seven years of lessons from maintaining Project CORA (Community of Online Research Assignments), an award-winning, open-access platform where librarians and educators share adaptable information literacy assignments. Launched in 2016 with grant support and strong community engagement, CORA saw early success: international page views across 150+ countries, 200+ shared assignments and teaching resources, and community-building features like "adapt this assignment" and leaderboards.

But when funding ended in 2018, Project CORA entered what many open projects experience but few discuss publicly: the precarious post-grant phase, when initial funding and enthusiasm fade but infrastructure still needs support. Annual contributions dropped …

[Birds-Of-A-Feather] Understanding And Handling Software Plagiarism In The Age Of Generative Ai, Daniel S. Katz, Scott C. Edmunds

FORCE 2026

Computing and software have supported research since their inception, and continue to play a significant role in knowledge production. However, the means of communicating research methods and results were developed long before computing existed, and the research community lacks best practices for documenting computational research elements transparently, reproducibly, and reusably.
Publishers are now more accepting of the inclusion of software (typically, source code) associated with submitted manuscripts, and many want to support processes to vouch for the integrity of software just as they do for other content, such as ensuring that ethical and legal concerns such as authorship, plagiarism, copyrights …

Diamond Open Access Journals In India: Status, Sustainability And Challenges, Mallikarjun Dora, Kanagasabai K, Raj Kishor Kampa

FORCE 2026

Open-access publishing has transformed scholarly communication in recent decades. The share of OA articles between 2014 and 2024 increased by 26%, from a modest 14% in 2014 to 40% in 2024. OA journals have evolved over time and exist in various models based on funding mechanisms, including the Gold, Green, Hybrid, and Diamond models. While OA publishing emerged in response to scientific inequality, middle- and low-income countries face the barrier of high Article Processing Charges (APC), which hinder them from publishing in those journals (Alperin, 2022). The Article Processing Charges are part of the Gold and Hybrid OA models, where …

Can Ai Help In Systematic Reviews? A Comparative Study Of Manual, Ai-Assisted, And Ai-Dominant Workflows For Librarians And Researchers, Aster Zhao

FORCE 2026

Systematic reviews are essential to evidence-based research but are often time-consuming and labor-intensive, for researchers to conduct, and for librarians to participate in, or teach. The rapid advances in Generative AI and AI-powered research tools, have created a growing interest in whether these technologies can assist—or even automate—parts of the systematic review process. However, questions remain about their effectiveness, reproducibility, and potential bias. This study explores the role of GenAI tools in the early stages of a systematic review: from literature discovery and screening, up to the identification of included studies.

We propose a comparative case study of one systematic …

Genai In Qualitative Data Analysis: Framework-Guided Prompt Engineering In Library Research Practice, Debby R. Wegener

FORCE 2026

As Generative AI (GenAI) tools become increasingly integrated across the research lifecycle, researchers need practical, reproducible methods for the responsible use of these technologies. This presentation will demonstrate a systematic approach to using GenAI for qualitative data analysis through a case study of thematic coding in a library website usability study at the Singapore Institute of Technology.

Drawing on prompt engineering frameworks like CLEAR, this session will illustrate how structured prompts can maintain academic rigour and enhance the reliability of GenAI-assisted analysis. The presentation will walk through the complete workflow, that is, from initial data preparation and tool selection to …

Using Ai-Assisted Programming To Develop Research Services Tools For Research Impact, Open Access Publishing & More, Gary Lee

FORCE 2026

Academic libraries play a vital role in scholarly communication, As research practices become more data‑driven and interdisciplinary, librarians can help scholars by creating and sharing flexible, customizable tools that align with local workflows and user needs.

AI Assisted programming (sometimes called “vibe coding”) offers a new way for librarians without extensive programming knowledge to develop such tools . This allows previously non-expert librarians to go from conceptual goals to working applications by rapid prototyping, experimentation, and roll-out, resulting in service innovation and improvement.

This presentation illustrates how librarians at HKUST have explored vibe coding with tools like GROK, POE, and …

Recognizing And Rewarding Peer Review: Rethinking Research Assessment For Openness, Fairness, And Global Equity, Tung Tung Chan, Bernd Pulverer, Johan Rooryck

FORCE 2026

The Coalition for Advancing Research Assessment (CoARA) Working Group on Recognizing and Rewarding Peer Review has developed a comprehensive framework for reforming how scholarly review is valued within research careers. Our recommendations address a fundamental question: how can peer review, a critical yet often invisible scholarly contribution, be made visible, credited, and meaningfully integrated into research assessment?

Developed through a collaborative effort across 16 European organisations, the Working Group’s outputs offer targeted recommendations for four key stakeholder groups: research performing organizations, research funding bodies, publishers and editors, and individual researchers. These recommendations are structured across five key dimensions:
(1) Openness: …

Open Research Information - How To Support Publishers To Make Metadata Openly Availble, Bianca Kramer

FORCE 2026

Research information, or scholarly metadata, is important for decision making around strategic priorities, distribution of resources, and evaluation of researchers and institutions. It is also used to assess the effect of policies, and to find and assess research results. Open research information (free to access and free to (re)use) is increasingly valued for fair assessment and equitable decision making, and is also important in digital sovereignty.


The Barcelona Declaration on Open Research Information calls on organizations performing, funding and evaluating research to make openness of research information the default, work with services and systems that support and enable open research …

Biologically Informed Negative Samplingfor Antibody Chain Pairing Classification, Ishita Singh

Computer Science Senior Theses

Antibody heavy and light chain (H/L) pairing is fundamental to antigen recognition and stability. While single-cell sequencing preserves native pairing information, widely used bulk repertoire and spatial transcriptomics platforms do not, motivating the need for efficient ML methods to infer H/L pairing. Training a binary classifier for this task faces the methodological challenge of a lack of true biological negatives, since natural selection eliminates B cells with incompatible H/L pairs.

In this thesis, I introduce a biologically informed negative sampling strategy for H/L pairing classification, drawing on known V-gene biases in heavy and light chain pairing. Pseudo-negatives are constructed by …

Capturing Large Language Model Similarity Through Spectral Analysis, Ishan Verma Prasad

Computer Science Senior Theses

With the rapid development of open-sourced models on Huggingface, there is a strong need for a way to systematically determine the similarity between models. More strongly, for intellectual property and organization, we need a way to determine the "lineage" of models. We borrow principles from Heavy-Tailed Self-Regularization and Random Matrix Theory to provide an inference-free method to accomplish this. We cluster a corpus of several model families by their spectral fingerprints and demonstrate that each model family occupies a distinct region in weight space. This confirms prior ideas of training setups leaving artifacts on model weights and allows us to …

Ai, Translation, And Telling The Truth, David I. Smith

University Faculty Publications and Creative Works

I am working on a large translation project this year. I have been surprised to find several conversation partners voicing the assumption that I am getting AI to do the translating for me. I’ve been wondering how to respond.

A short, but in the end inadequate answer is that, impressive as the current variations on machine translation are, they still get things wrong. Neural machine translation services such as Google Translate and DeepL still produce oddities fairly regularly. I have been working lately with seventeenth-century Czech texts, an area in which I would expect machine translation to struggle a little …

Residential Ai Data Centers: Security, Privacy, And Governance Concerns, Alan Saquella

Publications

The concept of placing mini data centers and distributed AI computer nodes inside residential homes may appear innovative from an energy efficiency perspective, but it introduces significant security, privacy, governance, and liability concerns. What is effectively occurring is the expansion of commercial and potentially critical infrastructure into lightly protected residential environments.

Once a residence becomes part of a distributed computer grid supporting hyper-scalers, AI providers, or enterprise workloads, the home is no longer simply a private residence. It becomes a commercial technology asset, a potential cyber target, and even a physical target. A distributed network of thousands of residential nodes …

A Systematic Review Of Intrusion Detection Systems For Internet Of Medical Things: Performance, Efficiency, Explainability, And Generalization, Oswald Adohinzin, Youssef Harrath

Research & Publications

The Internet of Medical Things (IoMT) has transformed health care delivery through medical devices, remote patient monitoring, and real-time clinical decision support. However, the proliferation of IoMT devices introduces security vulnerabilities that put patient safety and data privacy at risk. Intrusion Detection Systems (IDS) have emerged as essential components for protecting IoMT networks from cyberattacks. This article presents a systematic review of IoMT-IDS research, analyzing 53 high-quality papers published between 2020 and 2025, identified through database searches spanning 2016–2025 across IEEE Xplore, Springer, ScienceDirect, and ACM Digital Library. We organize the literature through a comprehensive taxonomy spanning classical machine learning …