Digital Commons Network^™

Advances And Challenges In Digitally Connected Point-Of-Care Biosensing, Abdellatif Ait Lahcen, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Point-of-care (POC) biosensors are undergoing a paradigm shift from isolated diagnostic tools to digitally connected, intelligent platforms that enable continuous and decentralized healthcare delivery. This review critically examines recent advances in wearable, implantable, and portable biosensors, highlighting how integration with wireless communication, the Internet of Medical Things (IoMT), and artificial intelligence is transforming their functionality and clinical utility. Particular attention is given to innovations such as smartphone-enabled interfaces, cloud-based analytics, and machine learning-assisted analysis, which collectively enhance sensitivity, specificity, and user accessibility across diverse healthcare settings, from personalized home monitoring and bedside diagnostics to deployment in resource-limited regions. The review …

Mxene-Enabled Wearable Biosensors: A Design Framework For Autonomous Biosensing, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

MXenes, a rapidly expanding family of two-dimensional transition metal carbides and nitrides, have emerged as leading materials for wearable bioelectronics due to their metallic conductivity, termination-rich surfaces, mechanical compliance, and tunable interlayer structures. However, wearable biosensor performance does not arise from conductivity alone, but from coupled interactions among surface termination chemistry, heterointerface engineering, hierarchical architecture, and device integration under dynamic physiological conditions. This review establishes a predictive structure-interface-device framework linking MXene chemistry to system-level performance across electrochemical, mechanical, gas, optical, and energy-storage modalities. We analyze how termination-controlled adsorption governs charge transfer and selectivity, how heterojunction formation modulates carrier density and …

Meeting Battery Electric Vehicle Demand With A Focus On Throughput Capacity Across The Transport Nodes In The Upstream Cobalt Supply Chain, Nicholas J. Visconti

Dissertations

This study assesses whether cobalt transport capacity in sub-Saharan Africa is sufficient to support projected battery electric vehicle (BEV) demand under the Paris Accord. Using open-source data from ArcGIS, the Highway Capacity Manual, and the World Bank, the analysis applies a simplified linear programming approach to estimate the maximum throughput of the primary transport corridor connecting the Democratic Republic of the Congo to the Port of Durban. The model identifies significant constraints along the Rutenga-to-Beitbridge segment, reducing network capacity to an estimated 42,494 tons of ore per day. When converted to refined cobalt, this capacity falls well short of the …

Political Media Hesitancy And Avoidance In College Students, Taylor Mandile

Honors Theses and Capstones

No abstract provided.

Μmodules: A Low-Cost, Eurorack-Compatible Modular Audio Synthesis System, Nolan K. Juneau

Honors Theses and Capstones

The modular audio synthesizer is one of the fastest-growing industries in contemporary music technology. Unlike a traditional audio synthesizer, a modular synthesizer allows for the user to directly control the signal path and effects of the synthesized sound, allowing for a workflow that is completely customizable to an individual musician and their creative vision. However, the modules and cases currently in production for the common “Eurorack” design standard can be prohibitively expensive to new users, often costing thousands of dollars for even a small system. The µModules project aims to eliminate this financial barrier to modular synthesis by using inexpensive …

Concord Public Transportation Improvement Project, Jacob Holt

Honors Theses and Capstones

The capital city of Concord, New Hampshire, has been served by Concord Area Transit (CAT) since 1989. Despite continued population growth and economic development within the city, CAT’s fixed route bus system has remained unaltered since 2011. The purpose of this project is to rework the CAT system to provide service that better aligns with Concord resident’s current needs. A public survey was conducted to gather data regarding Concord resident’s needs, habits, and perception of the existing system, which was used in the development of the revised system. The project includes suggestions for both system-wide and route-specific modifications. Key changes …

Restoring Tidal Function: Hydrologic And Erosion Controls, On Rare Plant Distribution In New Hampshire Salt Marshes, Nikhila B. Lampman

Honors Theses and Capstones

No abstract provided.

A Mold Mating Surface Temperature Monitoring System For Injection Molding Using Infrared Thermography And Mahalanobis Distance, Yoshio Fukushima, Makoto Fukushima, Sho Shibuya, Keigo Kudo, Yuta Abe

ASEAN Journal on Science and Technology for Development

In plastic injection molding, minimizing defects is crucial for sustainable and stable manufacturing because resin behavior and molding conditions fluctuate due to variations in material lots, seasonal shifts, and factory environmental factors such as temperature and humidity. Among various process parameters, mold temperature　- specifically the mold mating surface temperature immediately after part ejection-　 plays a critical role in mitigating these variations and maintaining consistent product quality. However, embedding conventional sensors into the mating surface is structurally difficult. While non-contact infrared thermography is an effective alternative, shiny metallic mold surfaces suffer from low emissivity, leading to inaccurate readings. Furthermore, high-end …

Neuroevolution Of Compact Search Heuristics In Sokoban, Yeonghun Lee

Computer Science Honors Papers

This thesis investigates whether neuroevolution can produce heuristic functions for A* search on Sokoban that are drastically more parameter-efficient than a conventional gradient-trained baseline. Sokoban is a combinatorial planning puzzle that is both NPhard and PSPACE-complete, and solving it at scale requires an accurate cost-to-go heuristic to guide search. The standard approach fixes a neural network architecture and trains it by gradient descent; this thesis investigates whether evolutionary search over network topology can find heuristics that are competitive in accuracy while using orders of magnitude fewer parameters.

Four heuristic approaches are implemented and compared on the medium-difficulty split of the …

Thailand’S Alignment Strategy Amidst The Us-China Rivalry : A Role Theory Perspective, Wen Chou Han

Journal of Social Sciences

This paper seeks to analyze how Thailand, as a middle power, navigates its alignment choices amid an intensifying US-China rivalry in the Asia-Pacific region through the lens of role theory. This paper also proposes several original mechanisms to operationalize the role theory in the analysis of Thailand’s strategy. To this end, Thailand’s foreign policy from the past decade (2012 to mid-2025) will be reviewed. The central argument is that Thailand is adopting a “soft hedging” strategy marked by opportunism and driven by its key goal of development, but is, at the same time, complicated by domestic political dysfunction (“fragmented centralism”). …

Strategic Engagement And Legal Pluralism : Navigating Knowledge And Expertise In Mining Disputes, Sara K. Phillips

Journal of Social Sciences

This article explores how community and civil society actors in mining conflicts strategically engage with legal and technical vocabularies to assert legitimacy, contest exclusion, and influence mining governance. Drawing on an empirical case study of Thailand’s Chatree gold mine, the article analyzes how affected groups navigate overlapping normative systems, such as state law, transnational norms, and technocratic discourses, through informal learning and strategic appropriation of expert language. Framed through the conceptual lens of legal pluralism, the study highlights how actors interpret and mobilize diverse normative orders to articulate grievances, shape narratives, and attempt to gain access to decision-making spaces. These …

Dammed If You Do: Should The Government Be Liable For Hurricane Flooding And Other Natural Disasters?, Lior Jacob Strahilevitz

Coase-Sandor Institute for Law & Economics Research Paper Series

When hurricanes, wildfires, and other natural disasters strike, government officials must make difficult decisions under time pressure and amidst uncertainty over how best to save lives and mitigate the resulting damage to private property. Sometimes landowners who do not second-guess the appropriateness of those decisions made in exigent circumstances nonetheless insist that the government should foot the bill for the resulting destruction. In a 2025 opinion (Ablan) and a 2022 decision (Milton), both involving flooding damage resulting from Hurricane Harvey, the Federal Circuit articulated an expansive vision of government liability under the Takings Clause that can be squared with neither …

Technology, Capabilities, And Power In The Indian Political Economy: A History Of Growth Without Development, Apremeya Sudarshan

Student Scholarship

No abstract provided.

Data-Driven Analysis Of Galactical Evolution, Vidit Bhandari

Student Scholarship

No abstract provided.

Librarians' Hopes And Fears: Perspectives On Emerging Technologies In Library Works, Oghap Kim

Student Scholarship

No abstract provided.

Does Anything Beat A Naive Forecast? Machine Learning, Garch, And Equity Volatility, Anthony Le

Student Scholarship

No abstract provided.

Women Redefining Leadership In Sport, Violet Mitchell

Student Scholarship

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Charging The Corridors: A Distance-Weighted Difference-In-Differences Analysis Of Nevi Interstate Fast-Charging Deployment, Gasoline Consumption, And Air Quality Across California Counties, Khoi Van

Student Scholarship

No abstract provided.

Micro-Moments In Acl Injury: Analysis Of The Posture Of The Lower Leg During Change Of Direction, Joseph Reed Nobili

Student Scholarship

No abstract provided.

Structured Interactions With Llms To Support Ltl: Supplemental Information, Karenna Kung, Maanas Punuru, Alicia M. Grubb, Paola Spoletini

Computer Science: Faculty Publications

This repository contains the supplemental information for the paper: "Structured Interactions with LLMs to Support LTL", which investigates how students interact with and can be supported by LLM explanations while translating linear temporal logic formulae into English natural language.

Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan

Research Collection School Of Computing and Information Systems

Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.

Smart City And Smart Tourism Destinations: A Look At Split, Croatia, Bj Fletcher, Saša Drezgić, Molly Schnoke

All Maxine Goodman Levin School of Urban Affairs Publications

This case study was a multi-institutional collaborative effort shaped by interdisciplinary expertise including people and tools. Led by the Faculty of Economics and Business at the University of Rijeka, Croatia, the team includes researchers from the University of Illinois at Springfield (USA) and Cleveland State University (USA). The research team conducted a site visit of the city of Split between June 12-14, 2025. The visit included field observations, in-person interviews with local officials; informal meetings and conversations with varying experts and residents; examination and documentation of field visit sites; and review of strategies, plans and publicly available information.

Researchers utilized …

Investigating Ui Based And Ai Based Interactions In Vr Environments For Human Anatomy Education, Siddharth Sondhi

Master's Projects

Traditional approaches to learning and simulation often struggle to convey the complexity of three dimensional structures. In anatomy education, methods such as textbooks, lectures, and cadaver based learning are used, but can make it difficult to understand the complex structure of organs within the human body. Virtual Reality (VR) offers a promising alternative by providing immersive and interactive 3D environments that allow users to explore and manipulate anatomical structures more intuitively. These environments can be further enhanced by integrating large language models (LLMs) as intelligent agents capable of guiding users through natural language interaction. This project presents a Unity-based VR …

Javatutor: An Integrated Llm Framework For Structured Programming Tutoring And Problem-Solving In Java, Amey Makarand Dhongade

Master's Projects

Large Language Models (LLMs) are being adopted more actively to assist in pro- gramming tasks, but much of the available AI code assistants devices are encouraging the rapid generation of solutions, as opposed to assisting students in developing an understanding. As a result, they can give the students correct code without teaching on how to judge a problem and how to build solutions or how to debug their programs themselves. This study describes JavaTutor, an LLM-based tutoring system that is used to assist learners in the learning process in a three-step process of understand- ing, generating a solution, and refining …

Adaptive Real-Time Fraud Detection Using Online Learning And Explicit Concept-Drift Detection, Purva Govind Tugaonkar

Master's Projects

Real-time credit card fraud detection faces challenges such as extreme class imbalance, delayed feedback, and concept drift in transaction streams. This project implements and evaluates an adaptive streaming fraud detection framework based on three methodologies: (1) online learning with incremental updates, (2) explicit conceptdrift detection using statistical monitoring, and (3) separate models for immediate and delayed supervision, combined with cost-sensitive learning and anomaly detection. The system processes the credit card fraud dataset in a batched streaming fashion, uses multiple online learners and ensembles. Experiments show that online, driftaware models maintain high recall on frauds while controlling false positives under imbalanced …

Stepwise Sudoku Reasoning Training Using Transformers, Lok Man Chu

Master's Projects

Sudoku is a constraint satisfaction problem that serves as a testbed for studying reasoning and stepwise deduction. While many solvers can produce correct solutions, they often fail to generate human interpretable sequences of logically consistent steps. This study investigates whether a transformer trained on stepwise deduction traces can learn to solve Sudoku puzzles through sequential, logically deducible moves. Results show that solve accuracy improves significantly with more training data, reaching approximately 78% at 1500k samples. Stepwise analysis indicates that the model effectively learns simple strategies, achieving near-perfect performance. However, performance on more complex strategies remains limited. Overall, while the model …

Machine Learning Prediction Of Incident Hypertension In Australian Men: Integrating Survey, Pharmaceutical And Healthcare Utilisation Data From The Ten To Men Cohort, Ebenezer Afrifa-Yamoah, Emmanuel Peprah-Yamoah, Victor Opoku-Yamoah, Eric Adua

Research outputs 2022 to 2026

Background: Hypertension is a leading modifiable contributor to cardiovascular disease. We developed and evaluated machine learning models to predict incident hypertension in Australian men using baseline survey data linked to pharmaceutical (PBS) and healthcare utilisation (MBS) administrative records from the Ten to Men cohort.

Methods: Among 13,519 men free of hypertension at baseline (2014), incident hypertension over 10 years was ascertained from PBS antihypertensive dispensing. Twenty-five baseline features spanning sociodemographic, anthropometric, lifestyle, clinical and administrative domains were used to train logistic regression, random forest, gradient boosting and XGBoost models, evaluated by five-fold cross-validation with out-of-fold prediction. Discrimination, calibration and threshold-based …

Choice-Based Crowdshipping For Next-Day Delivery Services: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra

Research Collection School Of Computing and Information Systems

This paper studies integrating the crowd workforce into next-day home delivery services. In this setting, both crowd drivers and contract drivers collaborate in making deliveries. Crowd drivers have limited capacity and can choose not to deliver if the presented tasks do not align with their preferences. The central question addressed is: How can the platform minimize the total task fulfilment cost, which includes payouts to crowd drivers and additional payouts to contract drivers for delivering the unselected tasks by customizing task displays to crowd drivers? To tackle this problem, we formulate it as a finite-horizon Stochastic Decision Problem, capturing crowd …

Towards Secure Program Partitioning For Smart Contracts With Llm’S In-Context Learning, Ye Liu, Yuqing Niu, Chengyan Ma, Ruidong Han, Wei Ma, Yi Li, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging because they stem from inherent data confidentiality issues rather than straightforward implementation bugs. To tackle this by preventing sensitive information leakage, we present PARTITIONGPT, the first LLM-driven approach that combines static analysis with the in-context learning capabilities of large language models (LLMs) to partition smart contracts into critical (privileged) and normal codebases, guided by a few annotated sensitive data variables. We evaluated PARTITIONGPT on 18 annotated smart contracts containing 99 sensitive functions. The results demonstrate that PARTITIONGPT successfully generates …

Qualitative Study For Llm-Assisted Design Study Process: Strategies, Challenges, And Roles, Shaolun Ruan, Rui Sheng, Xiaolin Wen, Jiachen Wang, Tianyi Zhang, Yong Wang, Tim Dwyer, Jiannan Li

Research Collection School Of Computing and Information Systems

Design studies aim to develop visualization solutions for real-world problems across various application domains. Recently, the emergence of large language models (LLMs) has introduced new opportunities to enhance the design study process, providing capabilities such as creative problem-solving, data handling, and insightful analysis. However, despite their growing popularity, there remains a lack of systematic understanding of how LLMs can effectively assist researchers in visualization-specific design studies. In this paper, we conducted a rnulti-stage qualitative study to fill this gap, which involved 30 design study researchers from diverse backgrounds and expertise levels. Through in-depth interviews and carefully-designed questionnaires, we investigated strategies …