Digital Commons Network^™

Boosting Chart-To-Code Generation In Mllm Via Dual Preference-Guided Refinement, Zhihan Zhang, Yixin Cao, Lizi Liao

Research Collection School Of Computing and Information Systems

Translating chart images into executable plotting scripts-referred to as the chart-to-code generation task-requires Multimodal Large Language Models (MLLMs) to perform fine-grained visual parsing, precise code synthesis, and robust cross-modal reasoning. However, this task is inherently under-constrained: multiple valid code implementations can produce the same visual chart, and evaluation must consider both code correctness and visual fidelity across diverse dimensions. This makes it difficult to learn accurate and generalizable mappings through standard supervised fine-tuning. To address these challenges, we propose a dual preference-guided refinement framework that combines a feedback-driven, dual-modality reward mechanism with iterative preference learning. Our approach introduces a structured …

Auxiliary Prompt Tuning Of Vision‑Language Models For Few‑Shot Out‑Of‑Distribution Detection, Wenjun Miao, Guansong Pang, Zihan Wang, Jin Zheng, Xiao Bai

Research Collection School Of Computing and Information Systems

Recent advancements in CLIP-based out-of-distribution (OOD) detection have shown promising results via regularization on prompt tuning, leveraging background features extracted from a few in-distribution (ID) samples as proxies for OOD features.However, these methods suffer from an inherent limitation: a lack of diversity in the extracted OOD features from the few-shot ID data.To address this issue, we propose to leverage external datasets as auxiliary outlier data (i.e., pseudo OOD samples) to extract rich, diverse OOD features, with the features from not only background regions but also foreground object regions, thereby supporting more discriminative prompt tuning for OOD detection. We further introduce …

Functional Analysis Of R144 In The Flavin Oxidation Mechanism Of A Flavin-Dependent N-Monooxygenase, Reeder Robinson, Korliss Britt, Pablo Sobrado

Chemistry Faculty Research & Creative Works

Flavin-dependent N-monooxygenases (NMOs) are key enzymes in the biosynthesis of hydroxamate-containing siderophores, which are critical virulence factors in pathogenic microorganisms. SidA, an NMO from Aspergillus fumigatus, catalyzes the NADPH- and O2-dependent hydroxylation of L-ornithine (Orn) via a stable C4a-hydroperoxyflavin (FADOOH) intermediate. This study investigates the role of Arg144 in the catalytic cycle of SidA. Site-directed mutagenesis of Arg144 to alanine (R144A) significantly impaired both oxygen consumption and Orn hydroxylation, resulting in an approximately 60-fold reduction in kcat and a ~300-fold decrease in kcat/KM. The pH dependence, solvent kinetic isotope effects, and rapid-reaction kinetics reveal that R144 influences protonation events crucial …

Reflections: Two Linear B Signs (69, *47) In Light Of The Ancient Egyptian ‘Union Of Two Lands’ (Sema-Tawy), Gerald Leonard Cohen

Arts, Languages and Philosophy Faculty Research & Creative Works

This article suggests that two Linear B signs (69, *47) denote ‘union,’ specifically the ancient Egyptian ‘Union of Two Lands,’ i.e., North and South Egypt. The Egyptian term for this union is sema-taui (from sema ‘union’, ta ‘land’; -ui ‘dual; taui ‘two lands'), and the earlier suggestion that sign 69 derives from a picture of a leaf should perhaps be reconsidered in favor of the Egyptian sema-tawy symbol. Also, on a very speculative note I suggest that the Linear B pronunciation of sign 69 as /tu/ may derive from the /t/ and /u/ sounds of taui ‘two lands.’

Ai-Enabled Multi-Layer Security Operations: A Combined Siem, Ids, And Threat Intelligence Model For Adaptive Cyber Defense, Mohamad Khayat

Dissertations

This dissertation presents a comprehensive framework for the evolution of Security Operation Centers (SOCs) through the integration of advanced artificial intelligence (AI), blockchain, and optimization techniques. Motivated by the increasing complexity of cyber threats and the limitations of traditional reactive SOC strategies, this work begins with a systematic literature review that identifies critical gaps in current SOC operations. Based on these insights, a reference architecture is proposed to guide the integration of intelligent components into SOC environments. To address the challenge of secure and trustworthy information sharing, a blockchain-based threat intelligence platform is developed, leveraging Byzantine Fault Tolerance and Zero-Knowledge …

A Spanish-Language Adaptation Of The Brief Wisconsin Inventory Of Smoking Dependence Motives Among Mexican And Mexican-American Adults Who Smoke, Yessenia Castro, Jose E. Velasquez, Zully C. Guerra, Tatiana Londoño, John R. Moore, Nazanin M. Heydarian

School of Social Work Faculty Publications

Introduction: The smoking pattern of Latino smokers differs from non-Latino white smokers such that physical dependence may not be a strong motivator for smoking among Latinos. Multidimensional measures of dependence may be more useful, but there is a lack of psychometrically sound multidimensional Spanish-language measures. This study evaluated the psychometric properties of a Spanish-language adaptation of the Brief Wisconsin Inventory of Dependence Motives (Brief WISDM) for use among Spanish-speaking Latino smokers in the U.S.

Methods: 287 Spanish-speaking Mexican-origin smokers in the U.S. responded to a revised set of Spanish Brief WISDM items. Confirmatory factor analyses and model trimming procedures were …

The Association Of Cancer-Preventive Lifestyle With Colonoscopy Screening Use In Border Hispanic Adults Along The Texas-Mexico Border, Paul Gerardo Yeh, Audrey C. Choh, Susan P. Fisher-Hoch, Joseph B. Mccormick, David R. Lairson, Belinda M. Reininger

School of Medicine Publications

Purpose: The relationship between engaging in two domains of cancer-preventive behaviors, lifestyle behaviors and colonoscopy screening, is unknown in Hispanic adults. Accordingly, the study examined the association between lifestyle and colonoscopy screening in Hispanic adults along the Texas–Mexico border, where there is suboptimal colorectal cancer prevention.

Methods: Lifestyle behavior adherence and compliance with colonoscopy screening schedules were assessed using 2013–2023 data from the Cameron County Hispanic Cohorta populationbased sample of Hispanic adults living along the Texas–Mexico border. The 2018 World Cancer Research Fund scoring system characterized healthy lifestyle engagement. Multivariable logistic regression quantified the association between lifestyle behaviors and colonoscopy …

Dcrda: Deadline-Constrained Function Scheduling In Serverless-Cloud Platform, Priyanka Ashok Birajdar, Divya Meena, Anurag Satpathy, Sourav Kanti Addya

Computer Science Faculty Research & Creative Works

The serverless computing model frees developers from operational and management tasks, allowing them to focus solely on business logic. This paper addresses the computationally challenging function-container-virtual machine (VM) scheduling problem, especially under stringent deadline constraints. We propose a two-stage holistic scheduling framework called DCRDA targeting deadline-constrained function scheduling. In the first stage, the function-to-container scheduling is modeled as a one-to-one matching game and solved using the classical Deferred Acceptance Algorithm (DAA). The second stage addresses the container-to-VM assignment, modeled as a many-to-one matching problem, and solved using a variant of the DAA, the Revised-Deferred Acceptance Algorithm (RDA), to account for …

Evaluating The Quality Of Support Services For Students With Learning Difficulties: Perspectives Of Resource Room Teachers In The Sultanate Of Oman, Laila Al Salmi, Ibrahim Al Qaryoti, Ali Tekin, Amur Al Aisari, Mariam Al Mamari, Saed Al Saidi

Journal of Educational and Psychological Studies

This study investigates the quality-of-service provision offered by the Learning Difficulties Programs (LDPs) in Oman from the perspective of resource room teachers. Employing a descriptive approach, a sample of 329 teachers responded to a researcher-designed 49-item questionnaire, assessing six key domains: administrative and technical support, diagnosis and assessment procedures, family-school partnerships, curriculum and intervention programs, educational and technological aids, and behavior modification strategies. Results revealed that teachers held neutral perceptions regarding the overall quality of LDPs across most domains, except for the appropriateness of curriculum content for students with learning difficulties, which was rated positively. The study identified a lack …

Making Math Accessible: Addressing Language Challenges In 3rd Grade English Medium Math Classrooms, Salha Mohamad

Theses

The research article, Making Math Accessible: Addressing Language Difficulties in 3^rd Grade English Medium Math Classrooms, addresses the issue of how the teachers in UAE elementary schools assist a student who is to study mathematics in English rather than Arabic. In the School X, Grades 1 and 2 applied mathematics and science using the Ministry of Education (MOE) Arabic-medium curriculum. Since Grade 3, however, the school has used the American curriculum, so students are expected to study these subjects in English. This change brings major barriers in understanding basic mathematical terms, word problems, and instructions. The research applies …

Analyzing The Evolving Digital Public Dialogue On Juneteenth, Ky Nguyen, Quan Nguyen, Khusi Singh, Annie Tran

Annual Student Research Poster Session

This research explores how public conversations surrounding Juneteenth have evolved over time by analyzing 10,000 tweets. Through annotation of sentiment, emotion, and topics, the project provides insight into how Juneteenth is celebrated, debated, and understood across diverse cultural and political contexts. The resulting dataset lays the groundwork for a machine learning model capable of identifying large-scale patterns in language, tone, and narrative.

Weak Identification Of Long Memory With Implications For Volatility Modeling;, Jia Li, Peter C. B. Phillips, Shuping Shi, Jun Yu

Research Collection School Of Economics

This paper explores implications of weak identification in common ‘long memory’ and recent ‘rough’ approaches to modeling volatility dynamics of financial assets. We unveil an asymptotic near-observational equivalence between a long memory model with weak autoregressive dynamics and a rough model with a near-unit autoregressive root. Standard methods struggle to distinguish them, and conventional asymptotics are invalid. We propose an identification-robust approach to construct confidence sets that reveal the uncertainty and aid inference. Empirical studies based on realized volatility and trading volume often fail to statistically reject either model, thereby providing evidence of their potential coexistence.

Unpacking Singapore's Leasehold Relativity Table: An Empirical And Legal Analysis, Koon Shing Kwong, Jing Rong Goh, Seng Wei, Edward Ti

Research Collection School Of Economics

In Singapore, most land is state-owned, with the state generally issuing leasehold estates via state leases of not more than 99 years1, depending on the intended land use. Naturally, the value of a leasehold estate, which erodes over time as the lease approaches the end of its term, is a key component of the premium charged for lease renewals, or the tax imposed for permission given in relation to a development that would increase the value of the land. By law, the state valuation of leasehold land is prescribed by a leasehold relativity table colloquially known as ‘Bala’s Curve’ or …

Short-Term Mortality And Healthcare Utilization Consequences Of Pension Income Receipt: Evidence From South Korea, Mimi Jeon, Seonghoon Kim, Kanghyock Koh

Research Collection School Of Economics

We examine short-term consequences of pension income receipt on mortality and healthcare utilization within the monthly payment cycle. Using the national death registry data of South Korea, we document that the mortality rate decreases by 1.2–1.4 percent in the week of the disbursement date. The mortality-reducing effects are larger for causes of death that could have been avoided through timely and effective healthcare interventions. Using healthcare claims data, we document that the number of hospital admissions increases during the disbursement week. We provide suggestive evidence of greater mortality-reducing effects from a smaller but more frequent disbursement than from a monthly …

Civil Liability For Invasions Of Privacy: Whither Singapore?, Yu Han Lam

Research Collection Yong Pung How School Of Law

Intrusions upon privacy are becoming increasingly common in Singapore. Singapore has yet to establish a tort addressing this issue, although the SAL Law Reform Committee has proposed a tort of misuse of private information. Australia has also recently introduced a statutory tort of serious invasion of privacy. This article will argue for the need for a Singapore tort of intrusion upon seclusion, on top of the already proposed tort of misuse of private information, to cover more appropriately instances of intrusions upon privacy.

A System Framework To Symbolically Explore Intel Tdx Module Execution, Pansilu Pitigalaarachchillage, Xuhua Ding

Research Collection School Of Computing and Information Systems

We present TDXplorer, the first dynamic symbolic analysis system for Intel's TDX Module, the software trusted computing base of TDX. Without using TDX hardware, an analyzer function on top of TDXplorer can not only apply dynamic analysis to control and instrument the TDX Module's execution, but also carry out symbolic execution for path exploration as well as security and functionality reasoning. The two types of analysis are seamlessly integrated in a way that symbolic execution is conducted directly upon the TDX Module's binary code and runtime states, which are shaped by using dynamic analysis techniques. We implement TDXplorer on Linux …

Contrastrepair: Enhancing Conversation-Based Automated Program Repair Via Contrastive Test Case Pairs, Jiaolong Kong, Xiaofei Xie, Mingfei Cheng, Shangqing Liu, Xiaoning Du, Qi Guo

Research Collection School Of Computing and Information Systems

Automated Program Repair (APR) aims to automatically generate patches for rectifying software bugs. Recentstrides in Large Language Models (LLM), such as ChatGPT, have yielded encouraging outcomes in APR,especially within the conversation-driven APR framework. Nevertheless, the efficacy of conversation-drivenAPR is contingent on the quality of the feedback information. In this article, we propose ContrastRepair, anovel conversation-based APR approach that augments conversation-driven APR by providing LLMs withcontrastive test pairs. A test pair consists of a failing test and a passing test, which offer contrastive feedback tothe LLM. Our key insight is to minimize the difference between the generated passing test and the …

Digital Leadership: Secondary Education Principals’ Perceptions And Change Competencies Toward Implementing Digital Citizenship Curricula, Waylon M. Randolph

Electronic Theses and Dissertations

Secondary education public schools are increasingly being confronted with student misuse of information and communication technologies (ICTs). Students are using these technologies to engage in disruptive and harmful behaviors like cyberbullying and sexting. As a result, some public school districts have responded by banning the use of ICTs in the classroom, while others have turned to teaching digital citizenship through a dedicated digital citizenship curriculum. However, effectively implementing such a curriculum remains a significant challenge. According to the literature, the best way to implement a digital citizenship curriculum is by fostering a positive school culture where stakeholders model and support …

Interpreting The Private‑ And Public‑Sector Service Criteria For Singapore’S Aspiring Presidential Candidates, Benjamin Joshua Ong

Research Collection Yong Pung How School Of Law

The Singapore President's role is not only ceremonial: from 1991, it has encompassed the substantive function of serving as a guardian of public reserves and the integrity of the public service. A person must meet certain qualifying criteria in order to run in a Presidential election. This article focuses on one set of qualifying criteria, namely, the "service criteria": the requirement that candidates have had certain experience in serving in certain roles in the public sector or the private sector. The service criteria were last amended in 2016, and came to the fore in the 2023 Presidential Election following George …

Precipitated By The Pandemic: From Remote Witnessing To Electronic Wills, Edward Ti, Hang Wu Tang

Research Collection Yong Pung How School Of Law

The COVID-19 pandemic exposed the rigidity of will-making laws requiring in-person witnessing. Jurisdictions responded differently: some introduced temporary measures, others implemented permanent reforms allowing remote witnessing. This article compares responses in England and Wales, selected Australian states, Singapore, and Hong Kong SAR, tracing developments toward potential recognition of electronic wills. The central argument is that law reform should balance accessibility with safeguards against fraud and undue influence, avoiding overly burdensome formalities that deter compliance. The article concludes by examining how national digital identity systems could be used for the execution of electronic wills.

The Excellent Legal Scholar, Seow Hon Tan

Research Collection Yong Pung How School Of Law

The Excellent Legal Scholar: This article considers how virtues pan out in the life of the legal scholar, bearing in mind the purpose of legal scholarship and the identity of the legal scholar, who plays multifarious roles in today's research landscape. I consider how vision is important for the excellent legal scholar, bearing in mind that an aretaic account should be attentive to eudaimonia. I conclude with soul-searching questions for the legal scholar who endeavours to live an examined life that stands up to aretaic appraisal.

Deep Learning For Hate Speech Detection: A Comparative Study, Jitendra Singh Malik, Hezhe Qiao, Guansong Pang, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Automated hate speech detection is an important tool in combating the spread of hate speech, particularly in social media. Numerous methods have been developed for the task, including a recent proliferation of deep-learning based approaches. A variety of datasets have also been developed, exemplifying various manifestations of the hate-speech detection problem. We present here a largescale empirical comparison of deep and shallow hate-speech detection methods, mediated through the three most commonly used datasets. Our goal is to illuminate progress in the area, and identify strengths and weaknesses in the current state-of-the-art. We particularly focus our analysis on measures of practical …

Multi-Period Risk-Aware Procurement Optimization Under Covid-19 Disruption, Jonathan Chase, Hoong Chuin Lau, Jinfeng Yang, Lu Liu

Research Collection School Of Computing and Information Systems

Supply chain resilience has been a topic of active research in the operations research and AI communities for several years, but the COVID-19 pandemic threw the frailties of global supply chains into sharp relief. Disruptions and delays caused by fresh outbreaks leading to lockdowns, put severe strain on supply chains in many industries. In this work we develop lockdown-resilient procurement capabilities for a global technology company. First, through analysis of lockdown data from China we develop a logarithmic regression-based lockdown prediction method to complement a supplier risk metric for conventional risks. Second, we develop a multi-period stochastic optimization model that …

Classical Shadows With Improved Median-Of-Means Estimation, Winston Fu, Dax Enshan Koh, Siong Thye Goh, Jian Feng Kong

Research Collection School Of Computing and Information Systems

The classical shadows protocol, introduced by Huang et al (2020 Nat. Phys. 16 1050), makes use of the median-of-means (MoM) estimator to efficiently estimate the expectation values of M observables with failure probability δ using only O ( log ⁡ ( M / δ ) ) measurements. In their analysis, Huang et al used loose constants in their asymptotic performance bounds for simplicity. However, the specific values of these constants can significantly affect the number of shots used in practical implementations. To address this, we studied a modified MoM estimator proposed by Minsker (2023 Proc. 36th Conf. on Learning Theory …

Cookingdiffusion: Cooking Procedural Image Generation With Stable Diffusion, Yuan Wang, Bin Zhu, Yanbin Hao, Chong-Wah Ngo, Yi Tan, Xiang Wang

Research Collection School Of Computing and Information Systems

Recent advancements in text-to-image generation models have excelled in creating diverse and realistic images. This success extends to food imagery, where various conditional inputs like cooking styles, ingredients, and recipes are utilized. However, a yet-unexplored challenge is generating a sequence of procedural images based on cooking steps from a recipe. This could enhance the cooking experience with visual guidance and possibly lead to an intelligent cooking simulation system. To fill this gap, we introduce a novel task called cooking procedural image generation. This task is inherently demanding, as it strives to create photo-realistic images that align with cooking steps while …

Rethinking Teaching Evaluation Reports: Designing Ai-Transformed Student Feedback For Instructor Engagement, Ruoxi Shang, Keri Mallari, Au Wei Bin Yeong, Ken Yasuhara, Anthony Tang, Gary Hsieh

Research Collection School Of Computing and Information Systems

Student feedback is critical for improving teaching, yet instructors often avoid reading evaluations due to emotional burden and information overload. We present a systematic exploration of how language models can distill and transform student evaluations into adaptive, actionable insights. Through a systematic design space exploration combining 4 feedback strategies (removing harmful content, paraphrasing criticism, sandwiching negatives, adding constructive suggestions) with 4 presentation formats (themes, cards, letters, chatbots), we created six AI-augmented prototypes of teaching evaluations. Interviews with 16 post-secondary instructors revealed that effective use of AI in feedback processing should: (1) support action formation through focused views and divergent thinking, …

Polymind: Parallel Visual Diagramming With Large Language Models To Support Prewriting Through Microtasks, Qian Wan, Jiannan Li, Huanchen Wang, Zhicong Lu

Research Collection School Of Computing and Information Systems

Prewriting is the process of generating and organising ideas before a first draft. It consists of a combination of informal, iterative, and semi-structured strategies such as visual diagramming, which poses a challenge for collaborating with large language models (LLMs) in a turn-taking conversational manner. We present Polymind, a visual diagramming tool that leverages multiple LLM-powered agents to support prewriting. The system features a parallel collaboration workflow in place of the turn-taking conversational interactions. It defines multiple ''microtasks'' to simulate group collaboration scenarios such as collaborative writing and group brainstorming. Instead of repetitively prompting a chatbot for various purposes, Polymind enables …

Stroke2sketch: Harnessing Stroke Attributes For Training-Free Sketch Generation, Rui Yang, Huining Li, Yiyi Long, Xiaojun Wu, Shengfeng He

Research Collection School Of Computing and Information Systems

Generating sketches guided by reference styles requires precise transfer of stroke attributes, such as line thickness, deformation, and texture sparsity, while preserving semantic structure and content fidelity. To this end, we propose Stroke2Sketch, a novel training-free framework that introduces cross-image stroke attention, a mechanism embedded within self-attention layers to establish fine-grained semantic correspondences and enable accurate stroke attribute transfer. This allows our method to adaptively integrate reference stroke characteristics into content images while maintaining structural integrity. Additionally, we develop adaptive contrast enhancement and semanticfocused attention to reinforce content preservation and foreground emphasis. Stroke2Sketch effectively synthesizes stylistically faithful sketches that closely …

Genwardrobe: A Fully Generative System For Travel Fashion Wardrobe Construction, Peng Jin, Yilin Wen, Mingzhe Yu, Yunshan Ma, Rong Zheng, Jin‑Tu Fan, Chong Wah Ngo

Research Collection School Of Computing and Information Systems

With the increasing demand for outfit planning in real-world travel scenarios, the need for constructing a travel fashion wardrobe, a series of outfits tailored to a user's personalization and destination-specific context over a short travel period, has grown significantly. However, existing systems or works often focus on isolated factors and rely on retrieval-based methods, with insufficient utilization of generative models, limiting their adaptability to real-world travel scenarios. To address this issue, this study introduces GenWardrobe, a fully generative system for travel fashion wardrobe construction. GenWardrobe consists of three key modules: user query analysis, fashion knowledge retrieval via retrieval-augmented generation and …

Ivycross: A Privacy-Preserving And Concurrency Control Framework For Blockchain Interoperability, Ming Li, Jian Weng, Jia-Si Weng, Yi Li, Yongdong Wu, Dingcheng Li, Guowen Xu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Interoperability is a fundamental challenge for long-envisioned blockchain applications. A mainstream approach is using Trusted Execution Environment (TEE) to support interoperable off-chain execution. However, this incurs multiple TEE configured with non-trivial storage capabilities running on fragile concurrent processing environments, rendering current strategies based on TEE far from being practical. This paper aims to fill this gap and design a practical interoperability mechanism with simplified TEE as the underlying architecture. Specifically, we present IvyCross, a TEE-based framework that achieves low-cost, privacy-preserving, and race-free blockchain interoperability. IvyCross allows running arbitrary smart contracts across heterogeneous blockchains atop two distributed TEE-powered hosts. We design …