Digital Commons Network^™

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 …

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 …

Real-Time Task Scheduling Strategy For 3d Printing Cloud Platforms In Health Scenes, Jianjia He, Jian Wu, Jingran Ni, Yuning Zhang, Keng Siau

Research Collection School Of Computing and Information Systems

In health scenes, 3D Printing Cloud Platform (3DPCP) needs to cope with unpredictable fluctuations in tasks and resources, but traditional scheduling methods have problems such as incomplete consideration of factors, poor optimization, and weak dynamic adaptability, which make it difficult to meet real-time scheduling requirements. To this end, the real-time task scheduling problem of 3DPCP for health scenes is defined, a real-time task scheduling model is established, the design time of user personalized services is considered, a rescheduling scheme is designed in combination with task variations and device variations, and a scheduling strategy that incorporates dynamic mechanisms and improved multi-objective …

Polyqent: A Polynomial Quantified Entailment Solver, Krishnendu Chatterjee, Amir Kafshdar Goharshady, Ehsan Kafshdar Goharshady, Mehrdad Karrabi, Milad Saadat, Maximilian Seeliger, Dorde Zikelic

Research Collection School Of Computing and Information Systems

Polynomial quantified entailments with existentially and universally quantified variables arise in many problems of verification and program analysis. We present PolyQEnt which is a tool for solving polynomial quantified entailments in which variables on both sides of the implication are real valued or unbounded integers. Our tool provides a unified framework for polynomial quantified entailment problems that arise in several papers in the literature. Our experimental evaluation over a wide range of benchmarks shows the applicability of the tool as well as its benefits as opposed to simply using existing SMT solvers to solve such constraints.

Law Grapples With Its Achilles’ Heel? Uncertainties, Digital Experiments, And The Ai Frontier, Heng Wang

Research Collection Yong Pung How School Of Law

The governance of digitalization— which encompasses developments such as artificial intelligence (AI) and central bank digital currencies (CBDCs) — confronts serious challenges. At the core of the challenges are uncertainties, which form the central obstacle to effective governance. These uncertainties range from cyber risks to shifting societal responses. Law, as an institutionalized framework of governance, faces mounting pressure and wrestles with a fundamental vulnerability: traditional legal frameworks struggle to address uncertainties in digitalization.

To tackle the pervasive challenges of uncertainties, this article addresses two connected questions: What uncertainties does law face in governing digitalization shaped by emerging technologies? How can …

Juxtaposing Approaches To Risk-Based Ai Governance In Different ‘Rights’ Contexts: A Comparative Analysis Between Singapore And The Eu, Jane Loo, Mark Findlay

Research Collection Yong Pung How School Of Law

Comparative analysis of European and certain Asian approaches to governance often degenerates into simplistic dichotomies based on universal human rights assumptions. This chapter rejects such dualities, ill-informed by theory and historical reflection. The emerging argument is founded on a historical realist approach to theorising difference. Assisted by Polanyi’s double movement, the detailed substantive comparison is preceded by considerations of how recent trends in governing AI have uniformly adopted a countermovement against the dis-embedding of data and technology from the social leading to a risk/responsibility paradigm. From here, a more nuanced reflection of AI governance approaches in the EU and Singapore …

Beneficial Ownership In Domestic Tax Legislation, Some Clarity, But Far From ‘Well Established’: Hargreaves Property Holdings Ltd V Hmrc [2024] Ewca Civ 365, Vincent Ooi

Research Collection Yong Pung How School Of Law

The concept of beneficial ownership is extensively used in domestic tax legislation, but several decades ofinconsistent case law have muddied the waters as to exactly what it means. With the leading casesstopping short of the apex court, it is difficult to reconcile the cases and come up with a clear definition ofbeneficial ownership. The recent Hargreaves decision by Falk LJ (with whom Nugee and Peter JacksonLJJ agreed) represents the most structured judicial attempt to rationalise the concept to date. This notesuggests that, contrary to Falk LJ’s statement that the concept is ‘well established’, the law pre-Hargreaveswas far from clear. This …

Oral History Interview With Alan Chan, Alan Chan

Oral History Collection

The interview covered:

• Starting at SMU
• Administration
• Challenges and Future; Teaching and Curriculum
• Research
• College of Integrative Studies 
• Students
• Advice for Students

Risk Premia-Return Spillovers Among Commodity-Us Equity Markets, Marinela Adriana Finta

Sim Kee Boon Institute for Financial Economics

This study examines the risk premia-return spillovers of eight commodities (corn, soybean, wheat, copper, silver, gold, oil, and natural gas) and the U.S. equity market from 2008 to 2016. We define volatility, skewness, and kurtosis risk premia as the difference between implied and realized moments. Our results reveal an increasing trend in cross-market and cross-moment spillovers until mid-2012, with various announcements explaining these effects. Moreover, we document substantial cross-energy and cross-metal spillovers to the equity market and cross-return spillovers to risk premia. Higher-order risk premia also exhibit the highest effects on returns. In addition, we underline the prominent influence of …

Impacts Of U.S. Environmental Regulations On Industry, Xiao Ji, Mengyu Wang, Tianyi Zhang

Sim Kee Boon Institute for Financial Economics

This paper analyzes the impacts of U.S. environmental regulations on industry, focusing on command-and-control environmental regulations (CCER) and market-based environmental regulations (MBER). Drawing on empirical data from the Environmental Protection Agency (EPA) spanning over four decades, we examine key legislation such as the Clean Water Act (CWA), Clean Air Act (CAA), and the Resource Conservation and Recovery Act (RCRA), while also discussing more recent frameworks like the Inflation Reduction Act (IRA). Our findings suggest that although penalties under CCER contribute to immediate compliance, they often fail to elicit long-term changes in corporate behavior. In contrast, MBER, exemplified by the IRA, …

Converting Counterfeiters In Emerging Markets To Authorized Suppliers: A New Anti-Counterfeiting Measure, Liling Lu, Xin Fang, Sarah Yini Gao, Burak Kazaz

Research Collection Lee Kong Chian School Of Business

With more products being infringed by counterfeits, anti-counterfeiting measures, such as law enforcement and consumer education, have commonly been adopted in emerging markets. In recent years, “super fakes,” i.e., counterfeits of high quality, have become popular. Super fake manufacturers’ capability to produce high-quality products inspires a new anti-counterfeiting measure: converting counterfeiters to authorized suppliers. To study the effectiveness of this anticounterfeiting measure, our paper employs a game-theoretic model to examine the interactions between a brand-name firm with its home supplier, and a counterfeiter who produces high-quality counterfeits and can be potentially converted to an authorized overseas supplier. Our results show …

Organization Research As An Applied Science: Lessons From Fields That Shape Practice And Policy, Stephen X. Zhang, Gokhan Ertug

Research Collection Lee Kong Chian School Of Business

As an applied science, our field aims to improve organizational effectiveness and solve practical problems (Hideg, DeCelles & Tihanyi, 2020; Pfeffer & Fong. 2002; Pillutla & Thau, 2013). However, despite the increasing sophistication in methods and greater emphasis on theory in recent decades, we have not made commensurate strides in relevance and impact. As we see it, the heart of this challenge is the culture in our field that demands novel theoretical advancement from every paper (Aguinis & Cronin, 2022), which may inadvertently constrain our ability to address pressing organizational challenges. Previous appeals to enhance our impact as an applied …

Temporal Patterns Of New Product Introductions And Ipo Value: The Importance Of Recency, Dispersion, And Asymmetry, Suyun Mah, Rebecca J. Slotegraaf, Girish Mallapragada

Research Collection Lee Kong Chian School Of Business

A firm’s innovation activity is often judged by the number and type of new products it launches, but when these products are introduced may be equally important, especially before going public. This research investigates how the temporal pattern of new product introductions (NPIs) influences a firm’s initial public offering (IPO) value. The analysis uses data from 298 firms that went public between 2006 and 2023, and focuses on three patterns of timing: recency (how recently the latest product was launched before the IPO), dispersion (the degree to which NPIs before the IPO are spread out over time), and asymmetry (how …

Esg News, Future Cash Flows, And Firm Value, Francois Derrien, Philipp Krüger, Augustin Landier, Tianhao Yao

Research Collection Lee Kong Chian School Of Business

We investigate the expected consequences of negative environmental, social, and governance (ESG) news on firms' future profits. After learning about negative ESG news, analysts significantly downgrade their forecasts at short and longer horizons. Negative ESG news affects forecasts more strongly at longer horizons than other types of negative corporate news. The negative revisions of earnings forecasts following negative ESG news largely reflect expectations of lower future sales, rather than higher future costs. Quantitatively, forecast revisions can explain most of the negative impacts of ESG news on firm value. Analysts are correct to revise forecasts downward following negative ESG news.

A General Test For Functional Inequalities, Jia Li, Zhipeng Liao, Wenyu Zhou

Research Collection School Of Economics

This paper develops a nonparametric test for general functional inequalities that include conditional moment inequalities as a special case. It is shown that the test controls size uniformly over a large class of distributions for observed data, importantly allowing for general forms of time series dependence. New results on uniform growing dimensional Gaussian coupling for general mixingale processes are developed for this purpose, which readily accommodate most applications in economics and finance. The proposed method is applied in a portfolio evaluation context to test for “all-weather” portfolios with uniformly superior conditional Sharpe ratio functions.

Banking On Incumbents: How Do Fintech Start-Ups Benefit From Collaborations, Theodor Florian Cojoianu, Pia Helbing, Vladimir Pazitka, Dariusz Wojcik, Beiyun Xiao

Research Collection College of Integrative Studies

We investigate whether collaborations with established incumbents bolster innovation and access to capital for FinTech start-ups. Collaborations increase patent applications and raise both short-and long-term citations. Collaborations with finance incumbents stimulate finance and technology citations and boost both short-and long-horizon venture capital fundraising. These effects persist after addressing endogeneity and conducting additional robustness tests. Theoretically, our findings test the resource based theory in the FinTech ecosystem and enrich the open innovation literature by showing that, despite power asymmetries, FinTech start-ups can sustain innovative momentum and capture innovation gains via collaborations with incumbents. Collaborations function as credible signals that confer capital …