Digital Commons Network^™

The Link Between Intergenerational Social Mobility Of Cohorts And Individual Self-Rated Health: A Multi-Country Analysis., Jacinth J. X. Tan, Gregory T. H. Hng, Faith A. Wee

Research Collection School of Social Sciences

This research examined the potential health consequences of increased opportunities for social mobility. Specifically, we used indices of intergenerational social mobility of cohorts—the average level of change in economic status relative to one’s parents experienced across individuals within a cohort—as proxy measures of individuals’ exposure to opportunities for social mobility and investigated links to their self-rated health (SRH). We combined recent multi-country data on cohort social mobility from the World Bank with multi-country individual SRH data from the World Values Survey waves six (Ncountries=44, Nrespondents=48,955) and seven (Ncountries=41, Nrespondents=37,051). Multilevel modeling analyses revealed that at the aggregate, SRH had negative …

Competitive Stress And Life History Mismatch, Norman P. Li, Amy J. Y. Lim

Research Collection School of Social Sciences

Simulations, correlational studies, and laboratory experiments have recently shown that cues to high-resource competition may be steering individuals toward increasingly less favorable attitudes toward reproduction and slower life-history strategies. This work suggests that, alongside extrinsic mortality, it may be fruitful to examine the role of competitive stress cues in shaping life-history strategies.

Scaling Up Cooperative Multi-Agent Reinforcement Learning, Minghong Geng

Dissertations and Theses Collection (Open Access)

Multi-agent systems (MAS) involve multiple autonomous agents that coordinate their actions to achieve shared or competing objectives in dynamic environments. Over the past decade, multi-agent reinforcement learning (MARL) has emerged as a powerful paradigm for enabling collaborative behaviors among autonomous agents within MAS to solve complex tasks. This dissertation discusses a critical scalability gap that exists between current MARL capabilities and real-world deployment requirements. Most existing MARL research focuses on small-scale laboratory problems, often struggling to coordinate large agent populations and facing challenges with extended decision-making horizons. In contrast, many real-world applications demand coordination among hundreds or thousands of agents …

Competition Through Entry Fees Between Auctions For Differentiated Objects, Massimiliano Landi, Domenico Menicucci, Domenico Colucci

Research Collection School Of Economics

This paper considers two competing auctions with objects differentiated according to the random utility framework introduced in Perloff and Salop (1985): bidders privately observe their values for the two objects, and values are ex ante i.i.d. across objects and across bidders. For the case of uniform distribution of values, we show that competition under entry fees is less intense than competition under reserve prices in the sense that sellers are better off, and bidders are worse off when competition takes place with entry fees rather than under reserve prices. The key difference between the two settings is that undercutting under …

Gmm Estimation With Brownian Kernels Applied To Income Inequality Measurement, Jin Seo Cho, Peter C. B. Phillips

Research Collection School Of Economics

In GMM estimation, it is well known that if the moment dimension grows with the sample size, the asymptotics of GMM differ from the standard finite dimensional case. The present work examines the asymptotic properties of infinite dimensional GMM estimation when the weight matrix is formed by inverting Brownian motion or Brownian bridge covariance kernels. These kernels arise in econometric work such as minimum Cramér–von Mises distance estimation when testing distributional specification. The properties of GMM estimation are studied under different environments where the moment conditions converge to a smooth Gaussian or non-differentiable Gaussian process. Conditions are also developed for …

From Great “Liberator” To “Landlord Seeking Rent”: The Implications Of U.S. Reciprocal Tariffs Policy In Asia And Beyond, Henry S. Gao

Research Collection Yong Pung How School Of Law

The post-war international economic order was, to a large extent, underwritten by U.S. leadership. Nowhere was this more visible than in Asia, where the United States not only financed post-colonial development but also provided open access to its huge market, laying the foundation for export-led growth across the region. It underpinned regional stability through a blend of military, diplomatic, and economic engagement, including costly interventions in the Korean and Vietnam wars. That legacy, however, was fundamentally disrupted on April 2, 2025, when the Trump administration unveiled sweeping tariffs targeting key Asian economies. As Singapore’s defense minister wryly observed, the United …

A Comparison Of Comparisons: Evidence From An International Comparative Study Of 'Smart Cities', Kevin Ward, Teresa Abbruzzese, Tim Bunnell, Paolo Cardullo, I-Chun Catherine Chang, Byron Miller, Ramon Ribera-Fumaz, Haeran Shin, Zachary Spicer, Orlando Woods

Research Collection College of Integrative Studies

Every year the list lengthens of cities with some sort of ‘smart city’ public policy. In some, it emerges as the latest in a long line of urban digital and information communication policies. In others, the introduction of the notion of the ‘smart city’ marks a departure from past approaches to public policy. Additionally, the more studies emerge of actual smart city policies, then the less definitional agreement there seems to be. Nevertheless, that we have witnessed in the last two decades the ‘repeated instance’ of smart cities emerging in cities around the world seems incontrovertible. Like so much urban …

Remaking The Smart City Through The Covid-19 Pandemic: Seoul, Singapore, Taipei, Orlando Woods, I-Chun Catherine Chang, Haeran Shin

Research Collection College of Integrative Studies

The COVID-19 pandemic has proven to be a catalysing force for urban innovation in general, and for smart city agendas specifically, throughout the world. From the development of contact tracing technologies and the enforcement of quarantine and safe distancing measures, to the dissemination of public health information and advancement of telehealth rollouts, the promises of “smart” technologies to reveal and govern patterns of socio-spatial contact and mobility can be found at the core of effective city management during the pandemic. Arguably nowhere is this truer than in the cities of Seoul, Singapore and Taipei, where the Asian developmental state was …

Nationalism And Anglo-American Neo-Colonialism In Southeast Asia, 1945-1965, Wen-Qing (Wei Wenqing) Ngoei

Research Collection College of Integrative Studies

It is tempting to treat the United States’ ill-fated military intervention in Vietnam in the 1960s as the desperate final gasp of a moribund Western imperial system. Certainly, scholars have described Washington’s military debacle in Vietnam as the end of America’s “short-lived empire” in Southeast Asia, emblematic of the broader, decisive triumph of Southeast Asian nationalism over western colonialism. This reading of Southeast Asian countries attaining formal independence after 1945, with tacit assumptions that colonialism and nationalism exist in binary opposition, tends to ossify when the region’s history is viewed through the lens of U.S. defeat in Vietnam.

In contrast, …

Seeing Beyond The State: Private Sector-Led Smart City Governance In Bsd City, Indonesia, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

In recent decades new cities have sprung up at a rapid pace, aided by private sector funding (Hogan et al., 2012). Within the realm of smart city development, private sector influence over urban governance has substantially increased, particularly through Public-Private Partnerships (PPPs). However, in Indonesia, there is an emerging trend of the private sector exerting significant control over ‘independent’ greenfield smart cities beyond state-led frameworks. This paper develops the idea of seeing beyond the state which involves looking past conventional state-centered approaches to urban governance. It considers instead how power and control are exercised outside or beyond the usual boundaries …

Home And Religion, Emma Alexandra Grimley, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

This chapter explores how religious practices and identities intersect with the home as both a construct and physical locale and surveys the social science literature on religion in/and the home. We argue that the shifting space-times of religious practice reflect and influence the changeable and porous boundaries between public and private space, the home and beyond the home. This influence is shown by reference to three areas of focus: the home as a private space of and for religion; the use of religion to cross social and spatial boundaries of home; and the reconfiguration of the home in religious practice …

Scenarios For Csrd Scope Amendments - Advancing Reporting Scope While Reducing Further Burden, Andreas Rasche, Theodor Florian Cojoianu, Andreas G. F. Hoepner, Fabiola Schneider

Research Collection College of Integrative Studies

This paper presents calculations related to the CSRD scope criteria which are modified through the Omnibus I Simplification Package. We show how many companies would be in scope of CSRD when considering the criteria suggested by (a) the Commission’s Omnibus proposal, (b) the position adopted by the Council of the EU, and (c) the European Peoples Party (EPP) proposal in the European Parliament. For each of these three “cases” we show the impact of lowering or increasing the employee-related threshold. 1.    Our calculations demonstrate that the number of in-scope companies varies significantly when modifying the employee threshold. We conclude from …

Global Standards And Local Ambitions Across Green Taxonomies: Climate Change Mitigation From The European Union To South Africa, Theodor Florian Cojoianu, Andreas G. F. Hoepner, Ifigeneia Paliampelou, Anh Vu, Dariusz Wojcik

Research Collection College of Integrative Studies

Country-level green finance taxonomy standards have emerged to provide clarity on environmentally-sustainable economic activities to attract investment, protect financial services consumers, and counteract greenwashing. This paper adopts the Global Production and Financial Network (GPFN) approach and analyses factors affecting the climate change mitigation ambition level of the South African Green Finance Taxonomy (RSA GFT) in comparison with the EU taxonomy, which served as a model for South Africa's (RSA) regulators. It accounts for (i) the interplay between EU’s and RSA’s production and financial networks, and (ii) RSA’s willingness to attract European funding for sustainable development. We find that EU private …

Poster Abstract: Field Evaluation Of Body Thermoregulation-Based Dynamic Bedroom Air Temperature Control To Improve Sleep, Wenhao Zhang, Stefano Schiavon, Clayton Miller

Research Collection College of Integrative Studies

Sleep is essential for human health and well-being. Previous lab-based studies have shown that dynamically adjusting bedroom temperature according to body thermoregulation can improve sleep quality and thermal satisfaction. However, such strategies have not been tested in real-world settings, and there is a lack of practical solutions developed for residential buildings. In this work, we test a body thermoregulation-based dynamic air conditioning (AC) control strategy designed for typical Singapore homes and evaluated it in a pilot field deployment. The preliminary findings suggest that the proposed strategy can be successfully implemented in real bedroom settings and may improve sleep outcomes.

Enhancing Urban Energy Modeling: A Case Study Of Data Acquisition, Enrichment, And Evaluation In Berlin, Felix Rehmann, Martín Mosteiro-Romero, Clayton Miller, Rita Streblow

Research Collection College of Integrative Studies

Urban Building Energy Modeling (UBEM) has become a critical tool for developing local heating and cooling plans, as required by the European Union. Despite growing interest, the reproducibility and reliability of UBEM studies remain limited due to data scarcity and workflow complexity. This paper presents a comprehensive framework to evaluate the data pipeline in UBEM, with a particular focus on data acquisition, enrichment, simulation, calibration, and information application. The approach applies three distinct UBEM workflows (CityEnergyAnalyst, DistrictGenerator, and SimStadt) to the Mierendorffinsel district in Berlin, Germany. We compare the based on quantitative performance metrics and qualitative framework criteria. The results …

A Dataset Exploring Urban Comfort Through Novel Wearables And Environmental Surveys, Patrick Chwalek, Sailin Zhong, Nathan Perry, Tianqi Liu, Clayton Miller, Seiied Hamed Alavi, Denis Lalanne, A. Joseph Paradiso

Research Collection College of Integrative Studies

This study presents a comprehensive dataset capturing indoor environmental parameters, physiological responses, and subjective perceptions across three global cities. Utilizing wearable sensors, including smart eyeglasses, and a modified Cozie app, environmental and physiological data were collected, along with pre-screening, onboarding, and recurring surveys. Peripheral cues facilitated participant engagement with micro-EMA surveys, minimizing disruption over a 5-day collection period. The dataset offers insights into urban comfort dynamics, highlighting the interplay between environmental conditions, physiological responses, and subjective perceptions. Researchers can utilize this dataset to deepen their understanding of indoor environmental quality and inform the design of healthier built environments. Access to …

Sustainable Llm Inference For Edge Ai: Evaluating Quantized Llms For Energy Efficiency, Output Accuracy, And Inference Latency, Erik Johanne Husom, Arda Goknil, Merve Astekin, Lwin Khin Shar, Andre Kasen, Sagar Sen, Benedikt Andreas Mithassel, Ahmet Soylu

Research Collection School Of Computing and Information Systems

Deploying Large Language Models (LLMs) on edge devices presents significant challenges due to computational constraints, memory limitations, inference speed, and energy consumption. Model quantization has emerged as a key technique to enable efficient LLM inference by reducing model size and computational overhead. In this study, we conduct a comprehensive analysis of 28 quantized LLMs from the Ollama library, which applies by default Post-Training Quantization (PTQ) and weight-only quantization techniques, deployed on an edge device (Raspberry Pi 4 with 4GB RAM). We evaluate energy efficiency, inference performance, and output accuracy across multiple quantization levels and task types. Models are benchmarked on …

Sketch-Sparsenet: Sparse Convolution Framework For Sketch Recognition, Jingru Yang, Jin Wang, Yang Zhou, Guodong Lu, Yu Sun, Huan Yu, Heming Fang, Zhihui Li, Shengfeng He

Research Collection School Of Computing and Information Systems

In free-hand sketch recognition, state-of-the-art methods often struggle to extract spatial features from sketches with sparse distributions, which are characterized by significant blank regions devoid of informative content. To address this challenge, we introduce a novel framework for sketch recognition, termed Sketch-SparseNet. This framework incorporates an advanced convolutional component: the Sketch-Driven Dilated Deformable Block (SD3B). This component excels at extracting spatial features and accurately recognizing free-hand sketches with sparse distributions. The SD3B component innovatively bridges gaps in the blank areas of sketches by establishing spatial relationships among disconnected stroke points through adaptive reshaping of convolution kernels. These kernels are deformable, …

Generative Ai And Empirical Software Engineering: A Paradigm Shift, Christoph Treude, Margaret-Anne Storey

Research Collection School Of Computing and Information Systems

The widespread adoption of generative AI in software engineering marks a paradigm shift, offering new opportunities to design and utilize software engineering tools while influencing both developers and the artifacts they create. Traditional empirical methods in software engineering, including quantitative, qualitative, and mixed-method approaches, are well established. However, this paradigm shift introduces novel data types and redefines many concepts in the software engineering process. The roles of developers, users, agents, and researchers increasingly overlap, blurring the distinctions between these social and technical actors within the field. This paper examines how integrating AI into software engineering challenges traditional research paradigms. It …

Pricing Strategies In Global Channels: Considering The Effects Of Parallel Trade, Yuan-Mao Kao, Yang Yang, Shih-Fen Cheng, Cheng-Hung Wu

Research Collection School Of Computing and Information Systems

Pricing a global product differently across multiple regions is a common but controversial practice. Although price differentiation helps capture unique market characteristics, it also encourages parallel trade, which may affect the overall corporate performance of a global company. We study this problem with a single global business unit (GBU) and multiple local business units (LBUs). The GBU manufactures a product and sets a transfer price for supplying the product to all LBUs, and LBUs decide retail prices for their respective regional markets. Customers can purchase products in any region by comparing LBUs’ prices and other parallel-imported factors, and we construct …

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, …

Enhancing Spatial Understanding In Mixed-Reality Presentations, Nam-Dang Vo, Van-Vinh Thai, Nam-Hoi Do, Viet-Tham Huynh, Anthony Tang, Khan-Duy Le

Research Collection School Of Computing and Information Systems

Mixed reality (MR) presentations often involve a presenter wearing a head-mounted display (HMD) and an audience watching via a large display, making it difficult for audiences to perceive spatial relationships between the presenter and virtual objects. We report two experiments testing three design variations: (1) scene camera placement (audience-aligned vs. opposite), (2) overlaying the presenter’s first-person view, and (3) highlighting objects in the presenter’s view. Results show that audience-aligned cameras and object highlighting improve spatial understanding, while combining third- and first-person views can further aid perception. We derive design guidelines for configuring MR presentations to better support audience comprehension.

Metacan: Improving Generalizability Of Few‑Shot Anomaly Detection With Meta‑Learning, Zhisheng Lv, Jianfeng Zhang, Songlei Jian, Chenlin Huang, Hongguang Zhang, Guansong Pang, Zhong Liu

Research Collection School Of Computing and Information Systems

Few-shot Anomaly Detection (AD) for images aims to detect anomalies with few-shot normal samples from the target dataset. It is a crucial task when only few samples can be obtained, and it is challenging since it needs to be generalized to different domains. Existing methods try to enhance the generalizability of AD by incorporating large vision-language models (LVLMs).However, how to transform category semantic information in LVLMs into anomaly information to improve the generalizability of AD remains a challenge facing existing methods.To address the challenge, we propose a few-shot AD method called MetaCAN, a novel category-to-anomaly network trained with AD meta-learning …

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 …

International Workshop On Multimodal Generative Search And Recommendation (Mmgensr@Cikm 2025), Yi Bin, Haoxuan Li, Haokai Ma, Yang Zhang, Wenjie Wang, Yunshan Ma, Yang Yang, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Recent breakthroughs in generative Artificial Intelligence (AI) have ignited a revolutionary wave across information retrieval and recommender systems. This workshop serves as a premier interdisciplinary platform to explore how generative models, particularly Large Language Models (LLMs) and Large Multimodal Models (LMMs), are transforming multimodal search and recommendation paradigms [3, 6, 9, 10, 12-14]. We aim to convene researchers and practitioners to discuss innovative architectures, methodologies, and evaluation strategies spanning generative document retrieval [5, 8] generative image retrieval [ 7, 16], grounded answer generation [17], generative recommendation [2, 4, 11], and related tasks involving multiple modalities [1,15]. The workshop will facilitate …

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 …

Instructors’ Strategies In Creating And Implementing Constructivist Llm-Based Learning Activities, Emily Aurelia, Shun Yi Yeo, Michelle Lui, Effie Lai-Chong Law, Anthony Tang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly being integrated into educational settings, enabling more adoption of constructivist teaching and learning approaches in classrooms. This paper explores the strategies instructors are currently using to incorporate LLMs into learning activities that align with constructivist principles, which emphasize that learners actively construct their own knowledge. Through interviews with nine instructors who have designed eleven distinct LLM-based activities and using reflexive thematic analysis, this study identifies various types of learning activities with respect to four different aspects of the constructivist learning theory. The strategies employed and challenges faced to foster constructivist student-LLM interaction were also …

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 …

From Personas To Talks: Revisiting The Impact Of Personas On Llm-Synthesized Emotional Support Conversations, Shenghan Wu, Yimo Zhu, Wynne Hsu, Mong-Li Lee, Yang Deng

Research Collection School Of Computing and Information Systems

The rapid advancement of Large Language Models (LLMs) has revolutionized the generation of emotional support conversations (ESC), offering scalable solutions with reduced costs and enhanced data privacy. This paper explores the role of personas in the creation of ESC by LLMs. Our research utilizes established psychological frameworks to measure and infuse persona traits into LLMs, which then generate dialogues in the emotional support scenario. We conduct extensive evaluations to understand the stability of persona traits in dialogues, examining shifts in traits post-generation and their impact on dialogue quality and strategy distribution. Experimental results reveal several notable findings: 1) LLMs can …

Interaction2code: Benchmarking Mllm-Based Interactive Webpage Code Generation From Interactive Prototyping, Jingyu Xiao, Yuxuan Wan, Yintong Huo, Zixin Wang, Xinyi Xu, Wenxuan Wang, Zhiyao Xu, Yuhang Wang, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance on the design-to-code task, i.e., generating UI code from UI mock-ups. However, existing benchmarks only contain static web pages for evaluation and ignore the dynamic interaction, limiting the practicality, usability and user engagement of the generated webpages. To bridge these gaps, we present the first systematic investigation of MLLMs in generating interactive webpages. Specifically, we formulate the Interaction-to-Code task and establish the Interaction2Code benchmark, encompassing 127 unique webpages and 374 distinct interactions across 15 webpage types and 31 interaction categories. Through comprehensive experiments utilizing state-of-theart (SOTA) MLLMs, evaluated via both automatic …