Digital Commons Network^™

Predict Social Economic Outcomes By Transferred Knowledge With Satellite Imagery, Yang Tang, Shih-Fen Cheng, Yunqiang Zhu, Yichen Yang, Zhiqiang Zou

Research Collection School Of Computing and Information Systems

Traditional deep learning methods and econometric models have played a crucial role in the field of data mining, particularly in the prediction of socioeconomic outcomes. However, socio-economic information is unable to be directly extracted from remote sensing data. So, in this paper, we propose a method to leverage transfer learning to predict socioeconomic indicators (outcomes) through satellite imagery. Specifically, we use road network types as a proxy for socioeconomic factors, which is more effective and stable than using nightlight. We have extracted eleven distinct road topological features to generate reasonable road network types. Given the unique characteristics of road networks, …

When Deep Learning Meets Information Retrieval-Based Bug Localization: A Survey, Feifei Niu, Chuanyi Li, Kui Liu, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

Bug localization is a crucial aspect of software maintenance, running through the entire software lifecycle. Information retrieval-based bug localization (IRBL) identifies buggy code based on bug reports, expediting the bug resolution process for developers. Recent years have witnessed significant achievements in IRBL, propelled by the widespread adoption of deep learning (DL). To provide a comprehensive overview of the current state of the art and delve into key issues, we conduct a survey encompassing 61 IRBL studies leveraging DL. We summarize best practices in each phase of the IRBL workflow, undertake a meta-analysis of prior studies, and suggest future research directions. …

Seeing Culture: A Benchmark For Visual Reasoning And Grounding, Burak Satar, Zhixin Ma, Patrick Amadeus Irrawan, Wilfried Ariel Mulyawan, Jing Jiang, Ee-Peng Lim, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Multimodal vision-language models (VLMs) have made substantial progress in various tasks that require a combined understanding of visual and textual content, particularly in cultural understanding tasks, with the emergence of new cultural datasets. However, these datasets frequently fall short of providing cultural reasoning while underrepresenting many cultures.In this paper, we introduce the Seeing Culture Benchmark (SCB), focusing on cultural reasoning with a novel approach that requires VLMs to reason on culturally rich images in two stages: i) selecting the correct visual option with multiple-choice visual question answering (VQA), and ii) segmenting the relevant cultural artifact as evidence of reasoning. Visual …

Usefulness And Diminishing Returns: Evaluating Social Information In Recommender Systems, Qing Meng, Huiyu Min, Ming Shan Hee, Roy Ka-Wei Lee, Bing Tian Dai, Shuai Xu

Research Collection School Of Computing and Information Systems

Social recommendation, which leverages users’ social information to predict users’ preferences, is a popular branch of recommender systems. Many existing studies have attempted to advance the performance of collaborative filtering methods by leveraging the user-user matrix to enhance user embedding learning with user’s social connections. While the existing social recommender systems have demonstrated good performance in various recommendation tasks, the extent of social information usefulness in recommender systems remains unclear. This paper addresses the research gap by designing experiments to answer three research questions: (i) How useful is social information in varying user-item data sparsity? (ii) How much social information …

Distillcaps: Enhancing Audio-Language Alignment In Captioning Via Retrieval-Augmented Knowledge Distillation, Thinh Pham, Nghiem Diep, Lizi Liao, Binh Nguyen

Research Collection School Of Computing and Information Systems

Automated audio captioning (AAC) benefits from incorporatingexternal context to interpret complex sounds, but doing so withretrieval-augmented generation (RAG) at inference is sometimesinfeasible due to data availability or incurs significant latency andcomplexity. We propose DistillCaps, a novel training-time frame-work that leverages RAG to guide knowledge distillation for im-proved audio-language alignment, while lessening the relianceon retrieval during inference. In our framework, a RAG-equippedteacher model retrieves relevant textual information (e.g., simi-lar captions) for each audio clip and uses it for training to gener-ate context-enriched captions. Simultaneously, a student model istrained to imitate this teacher, learning to produce high-qualitycaptions from audio alone. We further …

Unified Molecule Pre-Training With Flexible 2d And 3d Modalities: Single And Paired Modality Integration, Tengwei Song, Min Wu, Yuan Fang

Research Collection School Of Computing and Information Systems

Molecular representation learning plays a crucial role in advancing applications such as drug discovery and material design. Existing work leverages 2D and 3D modalities of molecular information for pre-training, aiming to capture comprehensive structural and geometric insights. However, these methods require paired 2D and 3D molecular data to train the model effectively and prevent it from collapsing into a single modality, posing limitations in scenarios where a certain modality is unavailable or computationally expensive to generate. To overcome this limitation, we propose FlexMol, a flexible molecule pre-training framework that learns unified molecular representations while supporting single-modality input. Specifically, inspired by …

Uncovering The Values Of The Metaverse For Leisure Use By Individuals: A Value-Focused Thinking Approach, Ruilin Zheng, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The metaverse is a computer-mediated environment where users take the form of digital avatars when participating in activities and interacting with one another. Given the popularity of the metaverse, especially among the younger population, we identified the values offered by the metaverse for leisure use by its users. Using the Value-Focused Thinking (VFT) approach, we identified these values in the form of fundamental and means objectives. The VFT approach was applied in interviewing users who conduct leisure activities in the metaverse and in analyzing the data collected. A total of 27 metaverse users were interviewed, which generated 8 fundamental objectives …

Simulated Interactive Debugging, Yannic Noller, Erick Chandra, Srinidhi Chandrashekar, Kenny Choo, Cyrille Jegourel, Oka Kurniawan, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

Debugging software, i.e., the localization of faults and their repair, is a key activity in software engineering. Therefore, effective and efficient debugging is one of the core skills a software engineer must develop. However, the teaching of debugging techniques is usually very limited or only taught in indirect ways, e.g., during software projects. As a result, most Computer Science (CS) students learn debugging only in an ad-hoc and unstructured way. In this work, we present our approach called Simulated Interactive Debugging that interactively guides students along the debugging process. The guidance aims to empower the students to repair their solutions …

Disc: Decentralized Identity System With Self-Sovereign Credential Aggregation, Yang Yang, Wai Keung Ching, Minming Huang, Supachate Innet, Guomin Yang, Hwee Hwa Pang, Robert H. Deng

Research Collection School Of Computing and Information Systems

The evolution of decentralized identity (DID) and self-sovereign identity (SSI) frameworks, as endorsed by W3C Verifiable Credentials (VC) and eIDAS 2.0, underscores the need for secure, efficient, and privacy-preserving credential management. However, existing credential systems often depend on centralized issuers, lack efficient aggregation mechanisms, or fail to ensure unlinkability across authentication sessions. To address these challenges, we propose DISC (Decentralized Identity System with Self-Sovereign Credential Aggregation), a novel credential system that enables multi-authority credential issuance, user-controlled credential aggregation, and unlinkable authentication. DISC allows users to aggregate credentials from multiple issuers while maintaining constant-size authentication tokens and supporting batch verification for …

Prrla Members Digital Preservation Landscape, Pin Pin Yeo, Suqing Liu, Pimnapa Amaritworachai

Research Collection Library

The research aimed to assess the current state of digital preservation practices among PRRLA (Pacific Rim Research Libraries Alliance) member libraries. A literature review on digital preservation in academic libraries was conducted. Information was gathered through surveys and interviews. focusing on policies, staffing, skills, funding, collection maintenance and services related to digital preservation. Additionally, the study explored the role of AI, and future trends in digital preservation. Challenges and best practices for sustainable digital preservation were highlighted.

Report On Assessing The Digital Preservation Landscape And Capacity Of Prrla Libraries, Pin Pin Yeo, Suqing Liu, Pimnapa Amaritworachai

Research Collection Library

This project evaluated the current state of digital preservation practices among PRRLA (Pacific Rim Research Libraries Alliance) member libraries. This report outlined the best practices and guidelines of the member libraries. The study involved a literature review to examine existing research and practices in digital preservation. A survey was designed to collect detailed information from PRRLA members, complemented by online interviews with selected institutions to gain deeper insights. The report has the key findings, successful strategies with some suggestions for sustainable development of digital preservation.

Performances In Last-Mile Deliveries Involving Cyclic Services Of Shuttles And Cargo Bikes, Byung Kwon Lee, Young Joo Kim, Joyce M. W. Low

Research Collection Lee Kong Chian School Of Business

This study introduces a novel approximation model that integrates the ideologies of order statistics and max-plus algebra in representing the collection and distribution service schemes of a last-mile delivery system. Under the respective schemes, electric cargo bikes (e-bikes) perform the last-mile delivery near a microhub with shuttles collecting packages from multiple local logistics hubs (or local hubs, for short) and/or distributing packages to multiple microhubs. The framework is designed to estimate the cyclic capacity under varying cargo carrying capacities of the e-bikes and service network configurations. Real-world data, such as the geographic conditions of the streets around the microhubs in …

Delving Into Invisible Semantics For Generalized One-Shot Neural Human Rendering, Yihong Lin, Xuemiao Xu, Huaidong Zhang, Cheng Xu, Weijie Li, Yi Xie, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Traditional human neural radiance fields often overlook crucial body semantics, resulting in ambiguous reconstructions, particularly in occluded regions. To address this problem, we propose the Super-Semantic Disentangled Neural Renderer (SSD-NeRF), which employs rich regional semantic priors to enhance human rendering accuracy. This approach initiates with a Visible-Invisible Semantic Propagation module, ensuring coherent semantic assignment to occluded parts based on visible body segments. Furthermore, a Region-Wise Texture Propagation module independently extends textures from visible to occluded areas within semantic regions, thereby avoiding irrelevant texture mixtures and preserving semantic consistency. Additionally, a view-aware curricular learning approach is integrated to bolster the model's …

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 …

Robust Contracting Under Distributional Uncertainty, Jiangtao Li, Kexin Wang

Research Collection School of Economics

We study contract design when the principal has limited information about the output distributions induced by the agent's actions. In a baseline model where only the means are known, we show that increasing affine contracts are robustly optimal. The mean restrictions accommodate a wide range of output distributions, including extreme cases that help establish this optimality. We then extend the analysis to environments with additional constraints on the distributions. Our main result shows that the robust optimality of increasing affine contracts persists even when the principal knows more—for example, that each action induces a distribution with full support.

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.

Adolescent Executive Function As A Resilience Factor In The Family Stress Model Among Mexican-Origin Families, Su Yeong Kim, Yayu Du, Tianlu Zhang, Jingyi Shen, Kiera M. Coulter, Lester Sim, Wen Wen, Belem G. Lopez, Maria M. Arredondo, Shen Yishan, Hou Yang

Research Collection School of Social Sciences

Mexican-origin families often face economic hardship due to systemic oppression, increasing the likelihood of adolescent marijuana use. While the family stress model provides insight into the mechanism of the association between family economic hardship and adolescent marijuana use, resilience factors are relatively unknown. The present study uses a three-wave longitudinal data set of Mexican immigrant families in the United States (Wave 1—adolescents: Mage = 12.29, SD = 0.93; mothers: Mage = 38.57, SD = 5.71) to investigate the mechanism underlying the association between family income and adolescents’ likelihood of marijuana use, guided by the family stress model. The protective role …

Harnessing Se Community Knowledge For Developer-Centric Code Intelligence, Chengran Yang

Dissertations and Theses Collection (Open Access)

The integration of Large Language Models (LLMs), particularly those tailored for programming tasks—referred to as code LLMs—has created novel opportunities to enhance developer productivity. These advanced models automate routine and repetitive coding tasks, such as code generation and debugging, and enable faster prototyping and more efficient problem-solving. Despite these remarkable advantages, the current generation of code LLMs exhibits notable limitations that impact their practical effectiveness in real-world software engineering scenarios. These models frequently produce code that is inefficient or suboptimal in runtime performance, demonstrate opaque reasoning processes, and struggle to adapt effectively to diverse developer contexts and specific requirements. Moreover, …

Factors Influencing Consumers’ Online Purchase Decisions: Evidence From Amazon.Com, Weiwei Li

Dissertations and Theses Collection (Open Access)

With the rapid expansion of cross-border e-commerce, platform sellers increasingly adopt diverse price formatsto influence consumer decision-making. In this context, consumers’ perceptions of and responses to price information have become a pivotal issue in understanding online purchase behavior. Using Amazon as the research setting, this study employs a dynamic panel model with monthly product-level data spanning January 2024 to June 2025 to investigate how different price formats—such as Prime-exclusive pricing and coupon mechanisms—affect consumers’ online purchase intentions when the out-ofpocket price is held constant. Furthermore, the moderating effect of promotional events is systematically examined.

Departing from prior research that largely …

The Role Of Employee Engagement In Predicting Risk Management Outcome, Jenny Tan

Dissertations and Theses Collection (Open Access)

Risk performance is a key business performance indicator as it measures how well an organization manages its uncertainties. Well-balanced risk performance instills confidence in stakeholders (including investors) and improves organizational performance broadly speaking. This dissertation studies the relationship between Perceived Organizational Support, employee engagement and risk appetite and how that relates downstream to organisational risk performance. Using the lens of Social Exchange Theory (SET; Blau, 1964) I examine how perceived organizational support (POS) predicts employee engagement and how this then relates to risk appetite and subsequent levels of risk taking in an organization. I then make predictions about how exchange …

Psychological Characteristics Of Board Secretaries And Information Disclosure Quality - An Empirical Analysis Based On The Questionnaire Survey And Interviews With Board Secretaries Of A-Share Listed Companies, Shuijun Dai

Dissertations and Theses Collection (Open Access)

The capital market functions fundamentally on the principles of information, and effective information disclosure acts as the cornerstone of its operation. At present, China's capital market is fully advancing the registration-based reform that is primarily focused on information disclosure. In this context, the secretary of the board of directors ("board secretary")—who serves as the legal officer tasked with overseeing information disclosure for A-share listed companies—plays a vital role in information release and transmission.

In the context of the comprehensive implementation of the registration system and establishment of an investor-oriented capital market, this study surveys over 400 board secretaries from A-share …

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 …

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, …

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 …

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.

Review Of Victor Fan, “Cinema Illuminating Reality: Media Philosophy Through Buddhism”, Teng-Kuan Ng

Research Collection College of Integrative Studies

This is a book review of Victor Fan, Cinema Illuminating Reality: Media Philosophy through Buddhism (Minneapolis: University of Minnesota Press, 2022)

On Modeling Of Multiplicative Bias Factor For Multivariate Degradation Data, Bingxin Yan, Qiuzhuang Sun, Zhisheng Ye

Research Collection College of Integrative Studies

Multivariate degradation data are increasingly common due to advances in sensor technology. They provide rich information for reliability analysis and remaining useful life (RUL) prediction. The multivariate measurement typically contains actual degradation of multiple performance characteristics (PCs) and measurement errors. The multiple PCs often have different physical meanings with different orders of magnitude, making the associated measurement errors vary in the orders of magnitude as well. It is highly desirable to have a parsimonious model accounting for the possible correlation in degradation measurements, so that more flexibility can be reserved for modeling the actual multivariate degradation. This study proposes a …

Early Signs The Eu Carbon Border Adjustment Mechanism Is Reshaping Eu-India Steel Trade, Gian Luca Vriz, Theodor Florian Cojoianu, Carolyn Fischer, Luca Taschini

Research Collection College of Integrative Studies

This study examines early signals of the EU CBAM's impact on iron and steel exporters from India by integrating firm-level export data with third-party estimates of manufacturers' emissions and production. Changes in trade flows and pricing during the CBAM reporting phase indicate that high-emission-intensity firms have decreased both their average unit prices and shipment sizes to the EU, while low-emission-intensity firms have not changed shipment behavior and may have benefited from increasing prices. Such supply chain adjustments are in line with EU policy intentions, creating opportunities for low-emission producers while reducing reliance on high-emission suppliers to the EU.

Make Yourself Comfortable: Nudging Urban Heat And Noise Mitigation With Smartwatch-Based Just-In-Time Adaptive Interventions (Jitai), Clayton Miller, Xuan Yun Chua, Matias Quintana, Binyu Lei, Filip Biljecki, Mario Frei

Research Collection College of Integrative Studies

Humans can play a more active role in improving their comfort in the built environment if given the right information at the right place and time. This paper outlines the use of Just-in-Time Adaptive Interventions (JITAI) implemented in the context of the built environment to provide information that helps humans minimize the impact of heat and noise on their daily lives. This framework is based on the open-source Cozie iOS smartwatch platform. It includes data collection through micro-surveys and intervention messages triggered by environmental, contextual, and personal history conditions. An eight-month deployment of the method was completed in Singapore with …

Hlcg: A Hierarchical Lane-Changing Gaming Decision Model For Heterogeneous Traffic Flow On Two-Lane Highways, Tianyi Wang, Chong He, Hao Li, Yixuan Li, Yiming Xu, Yangyang Wang, Junfeng Jiao

Research Collection College of Integrative Studies

Discretionary lane-changing behavior is one of the most common highway operations, which seriously affects traffic efficiency and safety. Nowadays, connected and automated vehicles (CAVs) are advancing rapidly, though not yet fully widespread. As a result, a mixed traffic environment with traditional human-driven vehicles (HDVs) and CAVs will persist for the foreseeable future. To achieve effective automatic lane-changing maneuvers, it’s necessary to propose a lane-changing decision model for heterogeneous traffic flow on two-lane highways. This paper firstly extends longitudinal car-following models based on the intelligent driver model and lateral lane-changing models using quintic polynomial curves to accommodate heterogeneous traffic flow, and …