Digital Commons Network^™

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 …

Can We Read Ai’S Mind? A Quest For Transparency, Santhosh Kumar Ravindran, Estera Kot, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Although Artificial Intelligence (AI) systems are playing an increasing role in critical domains such as healthcare, finance, and autonomous systems, their decision-making processes remain largely opaque. This paper examines the challenges of AI transparency, addressing the “black box” problem using Explainable AI (XAI) techniques such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME). It also examines the ethical, regulatory, and societal implications of AI opacity and proposes a Comprehensive AI Observability (CAO) Framework that integrates deep explainability, provenance tracking, and real-time monitoring to enhance AI accountability. By bridging technical solutions with governance structures, this research emphasizes the …

Actor-Critic For Continuous Action Chunks: A Reinforcement Learning Framework For Long-Horizon Robotic Manipulation With Sparse Reward, Jiarui Yang, Bin Zhu, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Existing reinforcement learning (RL) methods struggle with long-horizon robotic manipulation tasks, particularly those involving sparse rewards. While action chunking is a promising paradigm for robotic manipulation, using RL to directly learn continuous action chunks in a stable and data-efficient manner remains a critical challenge. This paper introduces AC3 (Actor-Critic for Continuous Chunks), a novel RL framework that learns to generate high-dimensional, continuous action sequences. To make this learning process stable and dataefficient, AC3 incorporates targeted stabilization mechanisms for both the actor and the critic. First, to ensure reliable policy improvement, the actor is trained with an asymmetric update rule, learning …

Leveraging Large Language Models For Career Mobility Analysis: A Study Of Gender, Race, And Job Change Using Us Online Resume Profiles, Palakorn Achananuparp, Ye Xu, Yao Lu, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

We present a large-scale analysis of career mobility of college-educated U.S. workers using online resume profiles to investigate how gender, race, and job change options are associated with upward mobility. This study addresses key research questions of how the job changes affect their upward career mobility, and how the outcomes of upward career mobility differ by gender and race. We address data challenges – such as missing demographic attributes, missing wage data, and noisy occupation labels – through various data processing and Artificial Intelligence (AI) methods. In particular, we develop a large language models (LLMs) based occupation classification method known …

Dual-Lora And Quality-Enhanced Pseudo Replay For Multimodal Continual Food Learning, Xinlan Wu, Bin Zhu, Feng Han, Pengkun Jiao, Jingling Chen

Research Collection School Of Computing and Information Systems

Food analysis has become increasingly critical for health-related tasks such as personalized nutrition and chronic disease prevention. However, existing large multimodal models (LMMs) in food analysis suffer from catastrophic forgetting when learning new tasks, requiring costly retraining from scratch. To address this, we propose a novel continual learning framework for multimodal food learning, integrating a Dual-LoRA architecture with Quality-Enhanced Pseudo Replay. We introduce two complementary low-rank adapters for each task: a specialized LoRA that learns task-specific knowledge with orthogonal constraints to previous tasks’ subspaces, and a cooperative LoRA that consolidates shared knowledge across tasks via pseudo replay. To improve the …

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.

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 …

Editorial: Special Section On Challenges And Opportunities In Retrieval-Augmented Generation For Llms: Techniques, Trends, And Applications, Philip S. Yu, Haofen Wang, Feida Zhu

Research Collection School Of Computing and Information Systems

Retrieval-Augmented Generation (RAG) represents a transformative advancement for Large Language Models (LLMs) by integrating external knowledge to substantially improve accuracy and mitigate hallucinations. As a pivotal technology in the contemporary generative Artificial Intelligence (AI) landscape, RAG addresses fundamental challenges in knowledge-intensive tasks. This special issue serves as a dedicated platform to showcase these cutting-edge advancements. It features six rigorously peer-reviewed papers that present state-of-the-art research and applications in the rapidly evolving field of RAG.

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 …

Artem: Enhancing Large Language Model Agents With Spatial-Temporal Episodic Memory, Cassandra Hui Ming Tan, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Current large language models (LLMs) exhibit significant deficiencies in episodic memory tasks including encoding, storing, and retrieving specific information from temporally dependent events over a long period of time. Recent approaches to handle memory tasks in LLMs, such as in-context learning, retrieval-augmented generation (RAG), and fine-tuning, may resolve the long-term retention issues, but are still inadequate to handle tasks requiring chronological awareness of the stored information. We introduce Agentic Retrieval with Temporal-Episodic Memory (ARTEM), a hybrid LLM-based agent architecture integrating LLMs with a self-organizing neural network named Spatial-Temporal Episodic Memory (STEM), designed to handle episodic memory tasks. Our approach employs …

Dystop: Dynamic Staleness Control And Topology Construction For Asynchronous Decentralized Federated Learning, Yizhou Shi, Qianpiao Ma, Yan Xu, Junlong Zhou, Ming Hu, Yunming Liao

Research Collection School Of Computing and Information Systems

Federated Learning (FL) has emerged as a potential distributed learning paradigm that enables model training on edge devices (i.e., workers) while preserving data privacy. However, its reliance on a centralized server leads to limited scalability. Decentralized federated learning (DFL) eliminates the dependency on a centralized server by enabling peer-to-peer model exchange. Existing DFL mechanisms mainly employ synchronous communication, which may result in training inefficiencies under heterogeneous and dynamic edge environments. Although a few recent asynchronous DFL (ADFL) mechanisms have been proposed to address these issues, they typically yield stale model aggregation and frequent model transmission, leading to degraded training performance …

Llamoco: Instruction Tuning Of Large Language Models For Optimization Code Generation, Zeyuan Ma, Yue-Jiao Gong, Hongshu Guo, Jiacheng Chen, Yining Ma, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Recently, combining the strength of large language models (LLMs) and Evolutionary Computation (EC) has shown promising results for addressing optimization problems. It typically involves either iterative next-step solution seeking or directly prompting LLMs to generate critical optimization codes. However, these methods often suffer from low computational efficiency, high sensitivity to prompt design, and a lack of domain-specific knowledge. We introduce LLaMoCo, the first instruction-tuning framework designed to adapt LLMs for solving optimization problems in a code-to-code manner. LLaMoCo features a comprehensive instruction set that includes code-style problem descriptions as input prompts and robust optimization codes from expert EC optimizers as …

Understanding Wage Theft: Beyond The Numbers Through Community Practice, Lived Experience, And Research, André Simões Da Silva, Lenita Reason, Cristina Araujo Brinkerhoff

Gastón Institute Publications

Wage theft is a widespread form of labor exploitation that disproportionately affects immigrant and other vulnerable workers. This report examines the scope and impact of wage theft in Massachusetts by analyzing case data from the Brazilian Worker Center (BWC) alongside wage and labor enforcement data from the Massachusetts Attorney General’s Office (AGO). The analysis demonstrates how wage theft affects immigrant workers across industries, with particularly high numbers of cases in construction, cleaning, and hospitality. The data also reveal significant gaps in the reporting and enforcement of wage violations, particularly among domestic workers, whose cases are likely substantially underrepresented in available …

Social Support, Trauma And Neurophysiological Stress, Devon S. Glicken

UNF Graduate Theses and Dissertations

Traumatic life experiences and the prolonged effects of stress can negatively impact an individual’s mental and physical health. Hyperreactivity to acute stressors can often be seen in individuals with anxiety, depression, and suicidal ideations, conditions commonly observed with endocrine dysfunction. How do traumatic experiences, particularly experiences related to military affiliation, influence stress responses and feelings of burdensomeness and thwarted belongingness? This study predicted (1) that military-affiliated individuals (and those with PTSD symptomology and high perceived life stress) will have heightened neurophysiological responses to minor levels of acute stress compared to individuals without military-affiliations (and those without PTSD symptomology or high …

Novice Teachers' Perceptions Of Clinical Experience And Their Preparedness To Teach In High-Need Urban Schools, Robin D. Renelus

UNF Graduate Theses and Dissertations

This hermeneutic phenomenological study examined novice teachers’ perceptions of how clinical experiences in a teacher preparation program prepared them to teach in high-need urban schools. The study included 12 novice teachers with three or fewer years of teaching experience who completed their clinical experience at the same university in Northeast Florida. Data were collected using Seidman’s (2019) three-interview approach, which explored participants’ backgrounds, day-to-day teaching experiences, and reflections on their sense of preparedness. Data were analyzed to develop textural descriptions of what participants experienced and structural descriptions of how those experiences were shaped (Moustakas, 1994).

Participants described clinical experiences as …

From Preparation To Practice: A Study Of Assistant Principals After Completion Of An Aspiring Assistant Principal Preparation Program, Mallory L. Mcconnell

UNF Graduate Theses and Dissertations

Leadership programs and readiness in schools, particularly those in Florida, is well studied. However, few studies have investigated how current assistant principals who have completed Clay County District School’s Aspiring Assistant Principal Program describe their experiences, believe the program has prepared them for the realities of school leadership, or identify the most impactful elements that have supported their leadership development. This case study seeks to collect foundational research knowledge by analyzing data from the program, participants, and key facilitators. Using a sampling of current assistant principals who have completed the Aspiring Assistant Principal Program, this research examines the results in …

Development Of Alternative Plasma Etching Techniques For The Selective Removal Of Tan With Respect To Sioch Dielectric Materials To Enable Future Back-End-Of-The-Line Scaling, Ivo Otto Iv

Electronic Theses & Dissertations (2024 - present)

Transistor scaling has continued according to Moore’s Law for over fifty years. As transistor size decreases, adequate power delivery is required to enable transistor scaling without performance loss. Power delivery is provided by a metal interconnect network with insulating dielectric that connects the transistor level to the power source, the signal speed within this metal line network limiting transistor level switching speeds. Reduction of signal delay has moved from primarily dimension-based improvement towards adoption of conductor and dielectric materials with lower resistivity and a reduced dielectric constant value, respectively: transitioning from Al/SiO₂ to Cu/low-κ SiOCH. With this transition comes …

Genetic Diversity Of Cryptosporidium Species In New York State, Kimberly A. Mergen

Electronic Theses & Dissertations (2024 - present)

The knowledge regarding Cryptosporidium infections in New York State (NYS) is severely lacking in two ways: 1) there are currently no NYS-based data regarding the subtypes of Cryptosporidium parvum and Cryptosporidium hominis, which are the two most prevalent species that infect humans and 2) information regarding uncommon Cryptosporidium species that infect the New York population is also unavailable. Filling these gaps concerning this pathogenic parasite would provide a substantial amount of information when considering public health, outbreak investigations, and prevention measures. Therefore, improving Cryptosporidium subtype and species surveillance in NYS will aid in prevention and control efforts as well …

As If It Were Food: A Prose Translation Of The Old English Genesis B, Kane R. Malone

Electronic Theses & Dissertations (2024 - present)

The anonymous Old English poem known as “Genesis B” comes down to us as one of the most inherently human retellings of the Fall of Adam and Eve. Despite this, the piece is seldom read by the average twenty-first century middle-school learner. The poem, originally penned in Old English, has been translated into modern English numerous times, yet as I read through a variety of these translations, they all seemed to downplay the human element which I found intriguing. Thus, I created my own translation of “Genesis B” with a more general audience in mind, looking to create something that …

Entropic Foundation Of Finance And Physics: Securities Price Dynamics And Quantum Theory, Mohammad Abedi

Electronic Theses & Dissertations (2024 - present)

In many scientific and financial contexts, we must reason and make predictions under conditions of incomplete information. This dissertation develops Entropic Dynamics (ED) as a unified framework for deriving dynamical laws directly from principles of inference. Within this approach, probability distributions represent states of knowledge, and their evolution is determined through entropy maximization subject to relevant constraints. This leads to a novel concept of entropic time and a formulation of dynamics as an inferential process. In this talk, I will present how ED provides a common foundation across multiple domains. In physics, quantum dynamics for particles and scalar fields in …

Human Vaccine Hesitancy Spillover In The Field Of Veterinary Medicine: A Systematic Narrative Review Of Impacts And Veterinary Responses, Allison Schimpf

HEAL Project Outputs

Human vaccine hesitancy spillover in the veterinary field is a relatively new concept that has gained traction since the COVID-19 pandemic. Concerns about vaccine safety have increased among pet owners leading to questions about the potential impacts of reduced vaccination and how veterinarians can address these attitudes. A systematic search strategy following PRISMA 2020 guidelines was used with 3 different databases to collect peer-reviewed research articles from 2022 until now. The initial search yielded 376 articles for review and 11 were included after screening. Articles were analyzed using a narrative review format. Results showed that pet owners are more vaccine …

Wherefore Art Thou Competitors? How Situational Affordances Help Differentiate Among Prosocials, Individualists, And Competitors, Y. Liu, A.W. Stivers, R.O. Murphy, N.J. Van Doesum, J. Joireman, M. Gallucci, E. Aharonov-Majar, U. Athenstaedt, L. Bai, R. Böhm, N.R. Buchan, X.-P. Chen, K.B. Dumont, J.B. Engelmann, Li, Norman P., H. Euh, S. Fiedler, J. Friesen, S. Gächter, C. Garcia

Research Collection School of Social Sciences

The Triple Dominance Measure (choosing between prosocial, individualistic, and competitive options) and the Slider Measure (“sliding” between various orientations, for example, from individualistic to prosocial) are two widely used techniques to measure social value orientation, that is, the weight individuals assign to own and others’ outcomes in interdependent situations. Surprisingly, there is only moderate correspondence between these measures, but it is unclear why and what the implications are for identifying individual differences in social value orientation. Using a dataset of 8021 participants from 31 countries and regions, this study revealed that the Slider Measure identified fewer competitors than the Triple …

Artificial Intelligence, Fundamental Motives, And Evolutionary Mismatch, Amy J. Lim, Jose. C. Yong, Edison Sora Tan

Research Collection School of Social Sciences

In recent years, the intersection of artificial intelligence (AI) and psychology has garnered unprecedented attention, particularly following the advent of generative AI tools in 2022. These tools, capable of producing human-like text, images, and even deepening our understanding of cognitive processes, have not only captured the public imagination but also sparked new concerns and debates within the psychological community. While AI has been a subject of research for decades, the emergence of its generative capabilities has truly thrust AI into the spotlight. This article explores how these advancements are reshaping our understanding of human cognition and behavior, as well as …

Active Synchronous Participation In Online University Courses: Areview, María Dolores Rueda Montero

Capítulos de libros

This work explores the nature of synchronous active participation in online university education, focusing on its pedagogical value, challenges, and effective design strategies. While asynchronous learning dominates online higher education due to flexibility, the literature consistently highlights its limitations in engagement, motivation, and social connection. Synchronous active participation can compensate for these constraints by fostering social presence, sustained attention, and real-time interaction, especially when it is intentionally designed and facilitated. This study examines key themes such as webcam use, multimodal participation, community building, instructional design, and instructor digital competence. Findings show that non-use of cameras often reflects privacy, anxiety, or …

Developing Your Research Project: Writing An Annotated Bibliography, Fabiola Ceballos-Durham

Open Educational Resources

Students build the foundation for a criminal justice research project by evaluating and summarizing scholarly articles and websites in an APA-style annotated bibliography.

Creating A Social Media Campaign, Alexa Capeloto

Open Educational Resources

Students research an issue related to social good and apply visual, news, and digital literacy skills to design an original image and a proposed social media campaign.

Writing To Different Audiences For Different Purposes, Kim Liao

Open Educational Resources

Students research a recent technology and write three pieces for different audiences: an informational guide for nonexperts, an analytical memo for professionals, and a public-facing op-ed. They revise these pieces into a portfolio and reflect on how their writing choices serve each audience and purpose.

Toxicology Case Study Model, Ana Pego

Open Educational Resources

Graduate students apply laboratory skills to an authentic forensic toxicology case by interpreting evidence, recommending analytical methods, and presenting a critical group assessment.

Challenges And Best Practices For The Development Of Coastal Hazard Decision Support Tools, Noah Hallisey

Open Access Dissertations

There is growing interest in developing Decision Support Tools (DSTs) supporting emergency managers and other decision-makers during coastal storm events. Yet many tools fail to inform decision-making due to challenges associated with their development and transition into operational tools for real-time decision-making. This dissertation investigates these challenges and offers best practices for their development and implementation for real-world decision-making through a literature review, interviews with subject matter experts in the United States, and a real-world case study.

Manuscript 1 reviews existing published literature to understand whether and how tool developers are incorporating emergency managers in the development of DSTs and …

The Influence Of China’S Economic Soft Power: The Perceptions Of Youth In The Case Of Cambodia As A Small State, Mommarolin Srey

Graduate Research Theses & Dissertations

The debate on the continued rise of China remains relevant and central in global politics. China has been employing soft power as a strategic approach to enhance its reputation as a global power on the international stage. While China has made tremendous efforts in soft power diplomacy to foster positive perceptions among many countries, the global survey on the perception of China remains largely negative with only a slight increase in positive perceptions. This thesis examines the younger generation or youth perceptions of China’s economic soft power. This qualitative research uses the case study of Cambodia as small state and …