Digital Commons Network^™

Sea-Ice Observation In The Arctic By The Arab Satellite 813, Simulated By The Radiative Transfer Model ‘Sciatran’, Tuqa Mohsin Al Hajri

Theses

The purpose of this research is to explore the spectral behavior of sea ice and to understand how Arctic sea ice surfaces appear when they are observed with a hyperspectral sensor. This is crucial because sea ice changes a lot during the melt season, and different surface types can sometimes look similar to a human eye, but physically they are different. It is thus essential to identify the spectral differences between these surfaces. The main objective of this study is to examine how the spectra of white ice and melt ponds change when their physical and optical properties are varied, …

Effects Of Led Light Spectra And 1-Mcp On Postharvest Quality And Bioactive Compounds Of Cucumber (Cucumis Sativus L.) During Cold Storage, Imad Eldin Abbas Yousif

Theses

Extending postharvest quality and maintaining the nutritional value of cucumber fruit requires specific storage conditions to postpone senescence and enhance marketability. The postharvest lighting environment is a main factor that influences quality preservation for harvested biomass. The objective of this study was to investigate the effects of different light emitting diodes (LED) spectra (green, red, blue, and white LED) alone or in combination with 1-Methylcyclopropene (1-MCP) on postharvest quality and bioactive compounds of cucumber fruit during cold storage for 16 days at 5°C, the control fruit were left in the dark. For combined treatment, the fruits were exposed to 1-MCP …

Analytical And Numerical Methods For Solving Fractional Integro-Differential Equations Using The Modified Operational Matrix Method, Nour Alzoubi

Theses

Fractional calculus has attracted considerable attention in recent years because of its wide applicability to model a variety of linear and nonlinear physical phenomena across different scientific disciplines. In particular, fractional diferential equation systems have proven to be effective in describing processes with memory and hereditary properties. However, the solvability and analysis of such systems strongly depend on the type of fractional operator employed, especially in the presence of nonlocal fractional derivatives with singular kernels, which remain an open and challenging area of research.

The main objective of this thesis is to develop efficient analytical and numerical techniques for solving …

Ai-Powered Student Support And Development Platform, Wadha Rashed Alyammahi

Theses

Over the past few years, academic stress and student mental well-being have become critical concerns in educational settings, significantly affecting academic performance and overall quality of life. Students increasingly rely on digital platforms for academic support; however, many existing solutions lack the ability to adapt to users’ emotional states or provide personalized, context-aware assistance. In response to this challenge, this study presents the design and development of an intelligent, stress-aware conversational support system for students based on advanced natural language processing techniques and large language models.

The main goal of this study is to explore the effectiveness of an LLM-based …

Heat Transfer And Micropolar Characteristic Analysis For Fluid Flow Over A Contracting Permeable Infinite-Length Cylinder: A Fractional Derivative Study, Khalid Al Homran

Theses

This study presents a comprehensive analysis of heat transfer and micropolar fluid characteristics for flow over a contracting permeable infinite-length cylinder using fractional derivative modeling. The micropolar fluid model accounts for microstructure effects that are prevalent in many practical applications, such as polymeric fluids, colloidal suspensions, and biological fluids. The inclusion of fractional derivatives allows the analysis to incorporate memory effects, which provide a more accurate depiction of the physical phenomena compared to classical integer-order models. The governing partial differential equations, representing the momentum, micropolar momentum and energy transport processes, are transformed into a set of nonlinear ordinary differential equations …

Malicious Quic Traffic Detection Using Malicious Quic Traffic Detection Using Malicious Quic Traffic Detection Using Malicious Quic Traffic Detection Using, Choudhary Muhammad Zia

Theses

The enhanced QUIC protocol's encryption capabilities not only encrypt the traffic payload but also encrypt the packet headers that network security tools rely on for packet inspection. This enhanced encryption capability introduces challenges for network operators in monitoring and analyzing network traffic by creating blind spots in firewalls, intrusion detection systems, and deep packet inspection devices. Earlier research has demonstrated that training machine learning classifiers on individual QUIC packets across different classifiers has failed to detect any malicious traffic due to encrypted packet headers.

This thesis demonstrates that shifting to network flow analysis resolves this problem. Rather than analyzing individual …

The Impact Of Elevated Co2, Uv-B Irradiation, And Rising Temperature On Quinoa, Mohamed Yousif

Theses

Climate change is driving simultaneous increases in atmospheric CO₂, surface UV-B radiation, and temperature, yet most crop research has examined these stressors in isolation, leaving their combined effect on nutritional quality poorly understood. Quinoa (Chenopodium Quinoa Wild.), a stress-tolerant C3 pseudocereal, has been promoted as a climate-resilient forage and food crop for arid regions, but its performance under realistic multi-stress conditions remains uncertain. This study therefore asked whether quinoa can maintain biomass, yield, and mineral quality when exposed to elevated CO₂, enhanced UV-B, and rising temperature individually and in combination, and whether their interaction is additive or non-additive.

To …

Artificial Personhood: The Implications Of Recognizing The Legal Personhood Of Artificialintelligence, Daniel C. Borges

Vanderbilt Journal of Entertainment & Technology Law

Artificial intelligence (AI) is here in a big way. As society grapples with the implications of this profound new technology, the question of whether AI entities should be granted independent legal recognition, akin to human personhood, has emerged as a pivotal topic in jurisprudence. This Article explores the foundations, evolution, and implications of AI personhood, addressing philosophical perspectives, the development of personhood as a legal fiction (with specific emphasis on corporate personhood), and the need for AI personhood to counter the risks posed by rapidly developing AI technology. It defines the "AI person" as one whose legal recognition furthers a …

Who's Afraid Of Copyright And Ai?, Deborah R. Gerhardt

Vanderbilt Journal of Entertainment & Technology Law

Copyright and AI need not be a copyright no man’s land. Recent decisions by the Copyright Office have gotten so much media attention that many creators are unsure if they can secure copyright protection if they use AI as a creative tool. The proposed creative control paradigm can help us all tackle the challenge of determining when works created with the assistance of AI are copyrightable. Instead of relying on long-established nuanced precedent for protecting works generated with new technology, the Copyright Office asserts that any content generated with assistance from AI tools is unprotectable. This position is radically inconsistent …

Controlling The Narrative:Copyright’S Derivative Rights Doctrine & Semiotic Disobedience In The Age Of Ai, John Tehranian

Vanderbilt Journal of Entertainment & Technology Law

This Article argues that copyright’s derivative rights doctrine—long treated as a technical mechanism of market control—has operated as a powerful but underexamined tool of epistemic governance. As the doctrine’s scope has expanded, it has increasingly privileged dominant narratives while recasting resistive ones as acts of infringement. Drawing on historical and contemporary case studies—from the largely forgotten copyright disputes over the English translations of Mein Kampf and Bambi on the eve of World War II to the infamous stand-off between Wall Street’s Charging Bull and Fearless Girl statues—the Article demonstrates how derivative rights have been deployed to suppress what Sonya Katyal …

Patent Law's Trade Remedy, Michael L. Doane

Vanderbilt Journal of Entertainment & Technology Law

Although a trade remedy, not an intellectual property rights statute, Section 337 of the Tariff Act of 1930 plays an important and controversial role in the enforcement of intellectual property rights in the United States. As a trade remedy, Section 337 is designed and intended to promote innovation and investment in the United States through support of statutorily defined domestic industries against unfair competition from infringing imported products. This Article analyzes Section 337 as a trade remedy from the perspective of intellectual property rights owners and innovators such as start-up companies, universities, individual inventors, and other research and development-focused entities. …

Addressing The Stale Line Of Sports-Betting Behavior: Examining The Economic Shortfalls And Tax Solutions In Legalizing Sports Betting, Peyton Rameas

Vanderbilt Journal of Entertainment & Technology Law

Sports betting is a form of gambling that does not suffer from the same negative social stigma as casino gambling despite its equally addictive properties and damaging impact on household consumption. While sports betting was previously banned in most of the United States, following the Murphy v. National Collegiate Athletic Association decision, which empowered states to regulate sports betting within their borders, a wave of states that previously banned all forms of sports betting legalized the practice. Unsurprisingly, this rapid legalization of sports betting was accompanied by a flurry of statewide regulations, leading to disparate consumer protection across the states. …

Hipaa Coverage Of Pre-Processed Neural Telemetry From Brain-Computer Interface Implants, Yurie Lee

Cornell Law Library Cantwell Prize for Exemplary Student Research Papers

Brain-computer interface implants allow patients with degenerative neurological conditions to control robotic limbs or electronic devices through neural commands alone and suppress Parkinson's tremors or seizures in real time. These implants record neural signals millisecond-by-millisecond from electrodes implanted in the brain.

Nevertheless, BCI manufacturers have argued that this data falls outside the scope of HIPAA's Privacy Rule. Existing legal scholarship also seems to have accepted this as true.

This paper challenges that conclusion. It rebuts and considers manufacturers’ counterarguments, concluding that patients have a right to their pre-processed neural telemetry under HIPAA's right-of-access provision.

Long-Term Mine Planning: A Survey Of Classical, Hybrid And Artificial Intelligence-Based Methods, Nurul Asyikeen Azhar, Aldy Gunawan, Shih-Fen Cheng, Erwin Leonardi

Research Collection School Of Computing and Information Systems

The aim of long-term mine planning (LTMP) is two-fold: to maximize the net present value of profits (NPV) and determine how ores are sequentially processed over the lifetime. This scheduling task is computationally complex as it is rife with variables, constraints, periods, uncertainties, and unique operations. In this paper, we present trends in the literature in the recent decade. One trend is the shift from deterministic toward stochastic problems as they reflect real-world complexities. A complexity of growing concern is also in sustainable mine planning. Another trend is the shift from traditional operational research solutions — relying on exact or …

To Wait Or To Transfer? A Three-Level Optimization Framework For Intermodal Transfer Coordination In First Train Timetabling And Bus Bridging Services Management, Hao Li, Liujiang Kang, Norman Weik, Huijun Sun, Qingying Lai, Zhiguang Cao

Research Collection School Of Computing and Information Systems

This study addresses the integrated optimization of the first train timetabling and bus bridging service design (FTT-BBSD) for morning transfer challenges, two critical but interdependent passenger services in the public transit system. In contrast to most existing studies and conventional approaches, this study explicitly models the influence of passenger path choices and transfer mode selections on FTT-BBSD. Through a novel dual-level network representation that integrates subway and bus systems, we formulate the FTT-BBSD problem as a mixed-integer nonlinear programming model. The model simultaneously determines subway and bus timetables and bridging line deployment to minimize total travel time for all first …

Extensive And Intensive Margin Labor Supply On Ride-Sourcing Platforms, Hao Sun, Hai Wang, Zhixi Wan

Research Collection School Of Computing and Information Systems

The rapid expansion of ride-sourcing platforms has enabled freelance drivers to flexibly determine both their participation and working hours. Understanding this flexible labor supply behavior is essential for managing platform capacity and evaluating the impacts of pricing and incentive policies on driver welfare. This study develops a labor supply model in which drivers optimally choose whether to participate (extensive margin) and how long to work (intensive margin) to maximize their utility from consumption and leisure. The model incorporates heterogeneity in drivers’ other income, idle time, and participation costs, allowing us to analytically characterize equilibrium labor supply decisions. The results show …

When Politics Meets Digital Assets: Gender Identity Salience And Nft Pricing After Roe V. Wade, Xiang Liu, Yao Zhao, Ping Fan Ke

Research Collection School Of Computing and Information Systems

Major sociopolitical events can reshape public attention toward identity-related issues, potentially influencing valuation patterns in digital markets where identity-related characteristics are embedded in digital assets. Using the overturning of Roe v. Wade as an exogenous policy shock, this paper examines how gender attributes represented in non-fungible token (NFT) avatars affect market outcomes. Using transaction data from six major avatar-based NFT collections traded on Etherscan in 2022, we apply a quasi-experimental design combining propensity score matching and a difference-in-differences model. The results indicate that the policy shock significantly increased the resale prices of NFTs representing female avatars. These findings suggest that …

Rode: Linear Rectified Mixture Of Diverse Experts For Food Large Multi-Modal Models, Pengkun Jiao, Xinlan Wu, Bin Zhu, Jingjing Chen, Chong-Wah Ngo, Yu-Gang

Research Collection School Of Computing and Information Systems

Large Multi-modal Models (LMMs) have significantly advanced a variety of vision-language tasks. The scalability and availability of high-quality training data play a pivotal role in the success of LMMs. In the realm of food, while comprehensive food datasets such as Recipe1M offer an abundance of ingredient and recipe information, they often fall short of providing ample data for nutritional analysis. The Recipe1M+ dataset, despite offering a subset for nutritional evaluation, is limited in the scale and accuracy of nutrition information. To bridge this gap, we introduce Uni-Food, a unified food dataset that comprises over 100,000 images with various food labels, …

Frozen Lvlms For Micro-Video Recommendation: A Systematic Study Of Feature Extraction And Fusion, Huatuan Sun, Yunshan Ma, Changguang Wu, Yanxin Zhang, Pengfei Wang, Xiaoyu Du

Research Collection School Of Computing and Information Systems

Frozen Large Video Language Models (LVLMs) are increasingly employed in micro-video recommendation (MVR) due to their strong multimodal understanding. However, existing apporches typically deploy LVLMs as fixed black-box feature extractors without systematically comparing alternative representation strategies. To address this gap, we present the first systematic empirical study on various feature extraction paradigms and integration strategies, along with hierarchical representations from frozen LVLMs for MVR. Extensive experiments on representative LVLMs reveal that hidden states from multiple decoder layers provide richer and more effective representations for MVR. Guided by this insight, we propose the Dual Feature Fusion (DFF) Framework, a lightweight approach …

Co-Designing With Autistic Livestreamers: Care, Constraints, And Trade-Offs In Livestreaming, Terrance Mok, Anthony Tang, Lora Oehlberg

Research Collection School Of Computing and Information Systems

Autistic livestreamers use platforms like Twitch for social connection, self-expression, and community, but these spaces also impose ongoing social and emotional demands. Prior work has documented these experiences, but less is known about what autistic creators themselves envision for the tools and platforms they use. We address this gap through a Research through Design (RtD) co-design study with three autistic Twitch streamers, using speculative artefacts as discussion prompts to explore how participants reasoned about potential livestreaming technologies. Across three co-design activities, we identify three overarching tensions shaping autistic streaming practice: Expression versus Misinterpretation and Harm; Public Participation versus Control and …

A Survey Of Earable Technology: Trends, Tools, And The Road Ahead, Changshuo Hu, Qiang Yang, Yang Liu, Tobias Röddiger, Kayla-Jade Butkow, Mathias Ciliberto, Adam Luke Pullin, Jake Stuchbury-Wass, Mahbub Hassan, Cecilia Mascolo, Dong Ma

Research Collection School Of Computing and Information Systems

Earable devices, wearables positioned in or around the ear, are undergoing a rapid transformation from audio-centric accessories into multifunctional systems for interaction, contextual awareness, and health monitoring. This evolution is driven by commercial trends emphasizing sensor integration and by a surge of academic interest exploring novel sensing capabilities. Building on the foundation established by earlier surveys, this work presents a timely and comprehensive review of earable research published since 2022. We attempt to answer three core questions: (1) how has earable research evolved in recent years, (2) what enabling resources are now available, and (3) what opportunities remain for future …

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

Research Collection School Of Computing and Information Systems

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

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

Research Collection School Of Computing and Information Systems

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

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

Research Collection School Of Computing and Information Systems

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

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

Research Collection School Of Computing and Information Systems

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

Happycal: Designing Text And Image-Based Supports For Savouring Positive Work Experiences, Molly Stewart, Minghao Cai, Anthony Tang, Sam Liu, Chris Mosunic, Sowmya Somanath

Research Collection School Of Computing and Information Systems

Savouring positive work experiences can promote positive affect and well-being at work, yet there is limited guidance on how digital applications can support workers to engage in savouring. We developed HappyCal, a work-focused savouring application offering two forms of savouring support: text-based, a common modality in workplace reflection tools, and images, a largely unexplored approach in work-related savouring. We conducted an exploratory qualitative study where participants (N=36) used HappyCal over five days and engaged in savouring through either a text-only modality (n=17) or text input paired with image output (n=19). We found that (1) participants in both groups reported heightened …

“Alexa, Do Not Say That In Front Of My Boss!” A Cross-Cultural Comparison Of User And Ai Preferences For Privacy-Aware Smart Speaker Interactions Across Contexts, Lynne Warin, Emily Aurelia, Anthony Tang, Emily Aurelia, Delphine Reinhardt

Research Collection School Of Computing and Information Systems

Due to their limited ability to reason about the social context in which they are used, smart speakers pose significant privacy risks by responding in ways that may violate people's implicit social boundaries. We conducted a cross-cultural vignette study (N = 944) in Germany and Singapore to investigate how situational factors—specifically social context (bystander relationships and closeness), physical context (location), and interaction context (topic and deceptive intent)—regulate user preferences for smart speaker responses. Our results demonstrate that these factors are superior predictors of response preferences than dispositional user traits (i.e., intrinsic personal traits). We identify two distinct social dynamics: a …

Cfalr: Collaborative Filtering-Augmented Large Language Model For Personalized Fashion Outfit Recommendation, Yujuan Ding, Junrong Liao, Yunshan Ma, Yi Bin, Wenqi Fan, Tat-Seng Chua, Qing Li

Research Collection School Of Computing and Information Systems

Personalized outfit recommendation poses a significant challenge in e-commerce and social media platforms, requiring systems that balance user preferences with aesthetic compatibility. Collaborative filtering (CF) provides a traditional solution for this, but it struggles with data-sparse scenarios and complex user-item-outfit relationships. Meanwhile, existing template-based approaches are constrained by rigid pre-designed structures. To bridge these research gaps, we introduce CFALR (Collaborative Filtering-Augmented Large Language Model for Recommendation), a novel framework that synergizes collaborative filtering with large language models for personalized outfit recommendation. Specifically, CFALR describes user-outfit interactions in natural language and leverages LLMs to capture fashion semantics while employing CF-enhanced embeddings …

Flight To The Margins: Harriet Jacobs And Liminal Fugitivity, Lucy Britt

All Faculty Scholarship

What would it look like to flee oppression and violence if you could not get very far away? Although enslaved people’s fugitivity in the United States is often understood through the story of complete escape, there were many more enslaved people who fled within slave states. This article defines liminal fugitivity as a type of flight in which enslaved people fled to peripheral spaces near sites of enslavement, such as crawl spaces, edges of forests, or borders of towns and plantations. It reads Harriet Jacobs’s Incidents in the Life of a Slave Girl as an illustration of liminal fugitivity. Jacobs …

Overcoming Adversity With Resilience: A Phenomenological Examination Of African American Women Leaders Facing Microaggressions In Corporate Spaces, Dionne Trenise Johnson

Electronic Theses and Dissertations

African American women leaders in Fortune 500 companies experience persistent challenges of subtle yet pervasive systems of discrimination in the form of microaggressions that cause negative impacts to their psychological well-being, workplace performance, and career advancement. These women exhibit incredible resilience that enable them to thrive at work, mitigate mental health challenges, and navigate their careers successfully. However, unlike people who fall into either a racial minority group or a gender minority group, African American women experience compounded effects of microaggressions due to the intersection of their race and gender. As a result of microaggressions, these women experience impacts to …