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Articles 151 - 180 of 13080
Full-Text Articles in Entire DC Network
Sok: Understanding Zkvm: From Research To Practice, Guomin Yang, Yunbo Yang, Yuejia Cheng, Haibo Tang, Bingsheng Zhang, Kui Ren
Sok: Understanding Zkvm: From Research To Practice, Guomin Yang, Yunbo Yang, Yuejia Cheng, Haibo Tang, Bingsheng Zhang, Kui Ren
Research Collection School Of Computing and Information Systems
Zero-knowledge virtual machine (zkVM) is a powerful infrastructure for proving the correctness of a program execution with a succinct proof, attracting significant interest from researchers, developers, and users. It has been widely used in applications such as blockchain rollups, privacy-preserving machine learning, and off-chain computation. As the field grows, a wide range of zkVMs have been proposed. However, they adopt different choices in instruction formats, trace layouts, and proving backends, which results in a highly heterogeneous design landscape and makes it difficult to understand the relations among these systems.To bridge this gap, we provide a comprehensive study of zkVMs that …
Vehicle-Based Multi-Services For Future Smart Cities, Hao Sun, Jinhua Zhao, Hai Yang, Shenhao Wang, Hamsa Balakrishnan, Thomas W. Malone, Hai Wang
Vehicle-Based Multi-Services For Future Smart Cities, Hao Sun, Jinhua Zhao, Hai Yang, Shenhao Wang, Hamsa Balakrishnan, Thomas W. Malone, Hai Wang
Research Collection School Of Computing and Information Systems
Vehicles are crucial for sustaining socioeconomic activity and improving quality of life in modern cities by offering diverse services. These include passenger mobility, goods delivery, information acquisition, and acting as mobile servers such as food trucks and mobile lockers. At the same time, they also contribute to traffic congestion and air pollution. This tension fosters the rise of urban resource-conserving and sustainable service solutions. In this article, we introduce the concept of “Vehicle-Based Multi-Services” (VeMuS), in which a single vehicle offers multiple services simultaneously. Drawing on practical use cases, we examine service classification and integration for vehicles and the potential …
Enhancing Pointing Gestures Of Non-Hmd Users In Asymmetric Collocated Mixed Reality Collaboration, Nam-Dang Vo, Van-Vinh Thai, Anthony Tang, Khanh-Duy Le
Enhancing Pointing Gestures Of Non-Hmd Users In Asymmetric Collocated Mixed Reality Collaboration, Nam-Dang Vo, Van-Vinh Thai, Anthony Tang, Khanh-Duy Le
Research Collection School Of Computing and Information Systems
A common collocated group setting in mixed-reality (MR) collaboration is a person wearing a MR headset (HMD user) and presenting MR contents to audiences who are not provided with such specialized devices (Non-HMD users). In this setting, while Non-HMD users can view the MR environment shown on a large physical display, it still remains challenging for the HMD user to interpret their pointing gesture when they spatially refer to objects in the MR environment. To address this, we designed and evaluated two pointing techniques—SCREEN and SCREEN+SPACE—that support Non-HMD users in referring to MR content. Screen pointing allows users to refer …
Esg Reporting Lifecycle Management With Large Language Models And Ai Agents, Thong Hoang, Mykhailo Klymenko, Xiwei Xu, Shidong Pan, Yi Ding, Xushuo Tang, Zhengyi Yang, Jieke Shi, David Lo
Esg Reporting Lifecycle Management With Large Language Models And Ai Agents, Thong Hoang, Mykhailo Klymenko, Xiwei Xu, Shidong Pan, Yi Ding, Xushuo Tang, Zhengyi Yang, Jieke Shi, David Lo
Research Collection School Of Computing and Information Systems
Environmental, Social, and Governance (ESG) standards have been increasingly adopted by organizations to demonstrate accountability towards ethical, social, and sustainability goals. However, generating ESG reports that align with these standards remains challenging due to unstructured data formats, inconsistent terminology, and complex requirements. Existing ESG lifecycles provide guidance for structuring ESG reports but lack the automation, adaptability, and continuous feedback mechanisms needed to address these challenges. To bridge this gap, we introduce an agentic ESG lifecycle framework that systematically integrates the ESG stages of identification, measurement, reporting, engagement, and improvement. In this framework, multiple AI agents extract ESG information, verify ESG …
Emotional Support Through Ai: Venting To Artificial Intelligence Or A Perceived Human May Offer Comparable Emotional Well-Being Benefits, Meilan Hu, Jerlyn Q. H. Ho, Claire Ng, Shermaine S. M. Wong, Andree Hartanto
Emotional Support Through Ai: Venting To Artificial Intelligence Or A Perceived Human May Offer Comparable Emotional Well-Being Benefits, Meilan Hu, Jerlyn Q. H. Ho, Claire Ng, Shermaine S. M. Wong, Andree Hartanto
Research Collection School of Social Sciences
Artificial Intelligence (AI) chatbots are increasingly being explored as sources of informal emotional support, with emerging evidence suggesting that venting to these systems can reduce negative affect. Yet, it remains unclear whether such benefits depend on the responder's perceived identity. Given that emotional relief from venting often hinges on perceived authenticity and emotional validation, this study investigates whether the emotional well-being benefits of venting differ when users believe they are interacting with an AI chatbot versus a human, even when responses are content-matched. In a pre-registered experiment ( N = 279), participants were randomly assigned to either an AI-assisted venting …
Extensive And Intensive Margin Labor Supply On Ride-Sourcing Platforms, Hao Sun, Hai Wang, Zhixi Wan
Extensive And Intensive Margin Labor Supply On Ride-Sourcing Platforms, Hao Sun, Hai Wang, Zhixi Wan
Research Collection School Of Computing and Information Systems
The rapid expansion of ride-sourcing platforms has enabled freelance drivers to flexibly determine both their participation and working hours. Understanding this flexible labor supply behavior is essential for managing platform capacity and evaluating the impacts of pricing and incentive policies on driver welfare. This study develops a labor supply model in which drivers optimally choose whether to participate (extensive margin) and how long to work (intensive margin) to maximize their utility from consumption and leisure. The model incorporates heterogeneity in drivers’ other income, idle time, and participation costs, allowing us to analytically characterize equilibrium labor supply decisions. The results show …
When Politics Meets Digital Assets: Gender Identity Salience And Nft Pricing After Roe V. Wade, Xiang Liu, Yao Zhao, Ping Fan Ke
When Politics Meets Digital Assets: Gender Identity Salience And Nft Pricing After Roe V. Wade, Xiang Liu, Yao Zhao, Ping Fan Ke
Research Collection School Of Computing and Information Systems
Major sociopolitical events can reshape public attention toward identity-related issues, potentially influencing valuation patterns in digital markets where identity-related characteristics are embedded in digital assets. Using the overturning of Roe v. Wade as an exogenous policy shock, this paper examines how gender attributes represented in non-fungible token (NFT) avatars affect market outcomes. Using transaction data from six major avatar-based NFT collections traded on Etherscan in 2022, we apply a quasi-experimental design combining propensity score matching and a difference-in-differences model. The results indicate that the policy shock significantly increased the resale prices of NFTs representing female avatars. These findings suggest that …
Scaling Up Multi-Agent Reinforcement Learning For Large Agent Teams And Long-Horizon Tasks: A Survey, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan
Scaling Up Multi-Agent Reinforcement Learning For Large Agent Teams And Long-Horizon Tasks: A Survey, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Multi-agent reinforcement learning (MARL) empowers multiple autonomous agents to acquire effective policies for collaborative problem-solving. Over the last decade, MARL has seen significant advancements, with numerous algorithms achieving impressive performance across various benchmarks and real-world applications. Nevertheless, the scalability of multi-agent systems, in terms of the number of agents and the length of the task horizon, remains a critical consideration for applying MARL methods to complex problem-solving. Given that a dedicated review of the existing approaches and challenges in scaling up multi-agent systems remains largely absent, this survey aims to bridge this gap by delivering a comprehensive review of MARL …
“Grandpa, Can You Speak Nicer?”: Envisioned Chatbot Roles And Design Tensions In Intergenerational Communication Conflicts, Tianyi Zhang, Emran Bin Elias Poh, Yueyue Hou, Yi-Chieh Lee, Renwen Zhang, Jiannan Li, Anthony Tang
“Grandpa, Can You Speak Nicer?”: Envisioned Chatbot Roles And Design Tensions In Intergenerational Communication Conflicts, Tianyi Zhang, Emran Bin Elias Poh, Yueyue Hou, Yi-Chieh Lee, Renwen Zhang, Jiannan Li, Anthony Tang
Research Collection School Of Computing and Information Systems
Intergenerational conversations often break down when differences in tone, language, or expectations lead participants to feel dismissed or misunderstood. In this work, we explore how people envision AI-driven chatbot interventions for addressing communication problems in text-based intergenerational family chat. We conducted a scenario-based design interview with 10 pairs of family members from different generations, in which participants designed chatbot interventions that varied in intervention target and timing. Our findings show that participants expect chatbots to perform multiple themes of intervention, including mediating understanding, providing emotional support, offering evaluative commentary, and guiding interaction through behavioral suggestions. These expectations varied systematically across …
The Stars Align: Modeling User Rating Calibration With Sparse Semantic Review Features, Rodrigo Alves, Antoine Ledent
The Stars Align: Modeling User Rating Calibration With Sparse Semantic Review Features, Rodrigo Alves, Antoine Ledent
Research Collection School Of Computing and Information Systems
User ratings are often treated as comparable across users, although identical scores may reflect different experiences. We study whether ratings can be viewed as user-specific discretizations of a shared semantic continuum derived from review text. Our method maps reviews into sparse semantic features with a sparse autoencoder and learns user-specific filters for each rating level. On Amazon Electronics, the learned embeddings align along a shared low-dimensional rating axis. Users differ mainly in how they anchor and partition this continuum, while preserving its overall ordinal structure. These findings support a semantic view of calibration beyond scalar bias correction.
“From Remembering To Shaping”: Narrating Shared Experiences By Co-Designing Cultural Heritage Artifacts In Collaborative Vr, Yushang Yang, Fanxu Meng, Fiona Fui-Hoon Nah, L. C. Ray
“From Remembering To Shaping”: Narrating Shared Experiences By Co-Designing Cultural Heritage Artifacts In Collaborative Vr, Yushang Yang, Fanxu Meng, Fiona Fui-Hoon Nah, L. C. Ray
Research Collection School Of Computing and Information Systems
The ways people remember and recall places reveal an invisible aspect of cultural heritage (CH), reflecting how individuals and communities relate to these places. Heritage is communal, emerging through collaboratively constructed narratives rather than individual records. To probe how people may share collective memories, we designed an immersive two-person workflow for collaboratively co-designing 3D artifacts and environments in virtual heritage locations, using Generative AI (GenAI) to instantiate these intangible memories. Observations of the co-creation process revealed that participants merged prompts and model placements when negotiating different perspectives. They used spatial operations to compose scenes, and also to express personal and …
Not Too Early, Not All At Once: Design Tensions In Ai-Mediated Self-Disclosure In Online Dating, Pei-Hua Tsai, Tianyi Zhang, Emran Bin Elias Poh, Anthony Tang, Yung-Ju Chang
Not Too Early, Not All At Once: Design Tensions In Ai-Mediated Self-Disclosure In Online Dating, Pei-Hua Tsai, Tianyi Zhang, Emran Bin Elias Poh, Anthony Tang, Yung-Ju Chang
Research Collection School Of Computing and Information Systems
Online dating relies on self-disclosure, yet initial conversations are fragile: users must navigate uncertainty around timing, boundaries, and reciprocity with little shared context. While advances in AI raise the possibility of mediating disclosure, how such support might reshape the experience of early-stage relational disclosure remains underexplored. We conducted 29 semi-structured interviews to examine how daters envision AI-mediated self-disclosure in online dating. Our findings surface recurring design tensions rather than simple opportunities or risks. Participants welcomed guidance that could pace disclosure, support reflection, and reduce social awkwardness, but stressed preserving agency and authorship. They valued interpretive assistance for sense-making of ambiguous …
Context Matters: Auditing Gender Bias In T2i Generation Through Risk-Tiered Use-Case Profiles, Jose Luis Luna Campoverde, Yankun Wu, Xiaofei Xie, Noa Garcia
Context Matters: Auditing Gender Bias In T2i Generation Through Risk-Tiered Use-Case Profiles, Jose Luis Luna Campoverde, Yankun Wu, Xiaofei Xie, Noa Garcia
Research Collection School Of Computing and Information Systems
Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting to be integrated into higher-impact pipelines. Since generated images tend to reinforce stereotypes, producing representational erasure via “default” depictions and shaping perceptions of who belongs in certain roles, a growing body of work has proposed metrics to quantify gender bias in T2I outputs. Yet existing evaluations remain fragmented. Metrics are often reported without a shared view of what they measure, what assumptions they entail, or how their results should be interpreted under different deployment contexts. This limits the usefulness of gender …
Rc-Nf: Robot-Conditioned Normalizing Flow For Real-Time Anomaly Detection In Robotic Manipulation, Shijie Zhou, Bin Zhu, Jiarui Yang, Xiangyu Zhao, Jingjing Chen, Yu-Gang Jiang
Rc-Nf: Robot-Conditioned Normalizing Flow For Real-Time Anomaly Detection In Robotic Manipulation, Shijie Zhou, Bin Zhu, Jiarui Yang, Xiangyu Zhao, Jingjing Chen, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
Recent advances in Vision-Language-Action (VLA) models have enabled robots to execute increasingly complex tasks. However, VLA models trained through imitation learning struggle to operate reliably in dynamic environments and often fail under Out-of-Distribution (OOD) conditions. To address this issue, we propose Robot-Conditioned Normalizing Flow(RC-NF), a real-time monitoring model for robotic anomaly detection and intervention that ensures the robot's state and the object's motion trajectory align with the task. RC-NF decouples the processing of task-aware robot and object states within the normalizing flow. It requires only positive samples for unsupervised training and calculates accurate robotic anomaly scores during inference through the …
A Novel Hierarchical Multi-Agent System For Payments Using Llms, Donghao Huang, Joon Kiat Chua, Zhaoxia Wang
A Novel Hierarchical Multi-Agent System For Payments Using Llms, Donghao Huang, Joon Kiat Chua, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
Large language model (LLM) agents, such as OpenAI’s Operator and Claude’s Computer Use, can automate workflows but unable to handle payment tasks. Existing agentic solutions have gained significant attention; however, even the latest approaches face challenges in implementing end-to-end agentic payment workflows. To address this gap, this research proposes the Hierarchical Multi-Agent System for Payments (HMASP), which provides an end-to-end agentic method for completing payment workflows. The proposed HMASP leverages either open-weight or proprietary LLMs and employs a modular architecture consisting of the Conversational Payment Agent (CPA - first agent level), Supervisor agents (second agent level), Routing agents (third agent …
How To Save The Take-Home Essay With Oral Assessments, Matthew Hammerton, Jacqueline Ho
How To Save The Take-Home Essay With Oral Assessments, Matthew Hammerton, Jacqueline Ho
Research Collection School of Social Sciences
In a commentary, the authors opined that pairing take-home essays with oral assessments is a more effective response to AI than policing its use. Students who cannot adequately explain their work can be marked down, reducing incentives to rely on AI. They noted that oral exams help preserve key elements of university education – intellectual effort, ownership, and human relationships – while allowing take-home essays to remain relevant in an AI-driven landscape that demands greater emphasis on understanding, responsibility, and dialogue.
Daily Problematic Smartphone Use Predicts Decreases In Self-Control Capacity: Evidence From Random-Intercept Cross-Lagged Panel Model, Adalia Yin Hui Goh, Andree Hartanto
Daily Problematic Smartphone Use Predicts Decreases In Self-Control Capacity: Evidence From Random-Intercept Cross-Lagged Panel Model, Adalia Yin Hui Goh, Andree Hartanto
Research Collection School of Social Sciences
Amidst the widespread increase in global smartphone screen time and the phenomenon of ‘The Great Exhaustion’, where multiple surveys indicate pervasive tiredness and feelings of being drained, there is growing concern about the link between problematic smartphone use and the capacity for self-control. While numerous studies have investigated the relationship between problematic smartphone use and self-control capacity, they are mostly cross-sectional. Thus, it is unclear whether the lack of capacity for self-control is an antecedent or consequence of problematic smartphone use. Addressing the research gap, we conducted a 7-day diary study to investigate the bidirectional relationship between problematic smartphone use …
Ai Fatigue In Human–Ai Interaction: Conceptual Framework, Scale Development And Validation, And Associations With Ai Engagement, Gabriel R. Lau, K. T. A. Sandeeshwara Kasturiratna, Adalia Y. H. Goh, Eddie M. W. Tong, Andree Hartanto
Ai Fatigue In Human–Ai Interaction: Conceptual Framework, Scale Development And Validation, And Associations With Ai Engagement, Gabriel R. Lau, K. T. A. Sandeeshwara Kasturiratna, Adalia Y. H. Goh, Eddie M. W. Tong, Andree Hartanto
Research Collection School of Social Sciences
Emerging from the accelerating pace of AI development, user fatigue arising from prolonged human–AI interaction has become an increasing concern in public discourse. This growing attention underscores the need to clarify why sustained engagement with AI systems can generate psychophysiological strain and how such exhaustion manifests in users. The present research develops a conceptual framework for AI fatigue and introduces the 15-item AI Fatigue Scale as a validated tool for examining its correlates. Across four studies with 717 participants, we generated and content-validated an item pool, identified and confirmed a four-factor (cognitive, emotional, physical, behavioural) higher-order model. The scale demonstrated …
Drone Urbanisms, Siew Ying Shee
Drone Urbanisms, Siew Ying Shee
Research Collection School of Social Sciences
Across contemporary cities, unmanned aerial vehicles (UAVs) particularly drones have emerged as critical instruments for sensing, visualizing, and reconfiguring the built environment. Yet, urban space is not merely a passive backdrop for drone activity; it both shapes and is reshaped by them. The central question for understanding drone urbanism, then, is not only what drones do, but how their deployment redistributes the agency to see, know, and intervene across human operators, infrastructures, and algorithms.This renegotiation of visibility, authority, and knowledge takes shape through the ways drones mediate the governance and experiential textures of the city. Departing from the distant totalities …
Happycal: Designing Text And Image-Based Supports For Savouring Positive Work Experiences, Molly Stewart, Minghao Cai, Anthony Tang, Sam Liu, Chris Mosunic, Sowmya Somanath
Happycal: Designing Text And Image-Based Supports For Savouring Positive Work Experiences, Molly Stewart, Minghao Cai, Anthony Tang, Sam Liu, Chris Mosunic, Sowmya Somanath
Research Collection School Of Computing and Information Systems
Savouring positive work experiences can promote positive affect and well-being at work, yet there is limited guidance on how digital applications can support workers to engage in savouring. We developed HappyCal, a work-focused savouring application offering two forms of savouring support: text-based, a common modality in workplace reflection tools, and images, a largely unexplored approach in work-related savouring. We conducted an exploratory qualitative study where participants (N=36) used HappyCal over five days and engaged in savouring through either a text-only modality (n=17) or text input paired with image output (n=19). We found that (1) participants in both groups reported heightened …
Towards Efficient Continual Learning: From Memory Optimization To Foundation Models, Zilin Luo
Towards Efficient Continual Learning: From Memory Optimization To Foundation Models, Zilin Luo
Dissertations and Theses Collection (Open Access)
Continual learning, also termed lifelong learning, enables machine learning models to incrementally acquire new knowledge while mitigating the degradation of previously learned information—a capability essential for adapting to dynamic, real-world data environments. This dissertation investigates the core challenges of continual learning and extends its application to enhancing training efficiency in the era of foundation models. The first part of this dissertation addresses the constraints of few-shot exemplar storage with a novel compression framework. While leveraging class activation maps to downsample non-discriminative pixels, we introduce an adaptive masking model, optimized through bilevel optimization, to store more exemplars efficiently. The second part …
Towards Auto-Evaluation For Large Language Models, Jiahao Ying
Towards Auto-Evaluation For Large Language Models, Jiahao Ying
Dissertations and Theses Collection (Open Access)
The rapid advancement of large language models (LLMs) has created an urgent need for evaluation methodologies that are timely, scalable, reliable, and informative. Conventional evaluation benchmarks, although essential for measuring model capabilities and guiding model development, are often constructed and maintained through labor-intensive human annotation. As LLMs continue to improve through increases in model scale, training data, and computational resources, static benchmarks may quickly lose discriminative power. Moreover, the growing use of large and diverse training corpora increases the risk of benchmark leakage, which can inflate evaluation results and obscure the true capabilities of models. These challenges call for a …
Hide-And-Sweep: Detecting Concealed Cameras Via Led Illumination Sweeps, Jonghyuk Yun, Jaeyoung Moon, Yunseo Park, Sean Rui Xiang Tan, Byunghyun Kim, Rajesh Krishna Balan, Jun Han
Hide-And-Sweep: Detecting Concealed Cameras Via Led Illumination Sweeps, Jonghyuk Yun, Jaeyoung Moon, Yunseo Park, Sean Rui Xiang Tan, Byunghyun Kim, Rajesh Krishna Balan, Jun Han
Research Collection School Of Computing and Information Systems
Hidden cameras have increasingly infiltrated hotel and Airbnb rooms, posing serious privacy risks. Detecting such cameras is challenging because they are visually inconspicuous and often embedded inside everyday objects. Even worse, existing handheld detectors are manual and also rely on single-angle illumination and hence suffer from high false-positive rates. We present SweepLED (pronounced "sweepled")1, a practical hidden camera detection system that operates on a commodity smartphone augmented with an unobtrusive LED-embedded case. SweepLED performs LED sweeping - a controlled sequence of multi-angle illumination - while the user simply holds the phone still by hand, enabling the camera to capture how …
Task Complexity Matters: An Empirical Study Of Reasoning In Llms For Sentiment Analysis, Donghao Huang, Zhaoxia Wang
Task Complexity Matters: An Empirical Study Of Reasoning In Llms For Sentiment Analysis, Donghao Huang, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
Large language models (LLMs) with reasoning capabilities have fueled a compelling narrative that reasoning universally improves performance across language tasks. We test this claim through a comprehensive evaluation of 504 configurations across seven model families—including adaptive, conditional, and reinforcement learning-based reasoning architectures—on sentiment analysis datasets of varying granularity (binary, five-class, and 27-class emotion). Our findings reveal that reasoning effectiveness is strongly task-dependent, challenging prevailing assumptions: (1) Reasoning shows task-complexity dependence—binary classification degrades up to -19.9 F1% points (pp), while 27-class emotion recognition gains up to +16.0 pp; (2) Distilled reasoning variants underperform base models by 3–18 pp on simpler tasks, …
Ai In Healthcare: Regulatory Guidelines And Judge-Made Negligence Principles For Ai Implementers, Gary K. Y. Chan
Ai In Healthcare: Regulatory Guidelines And Judge-Made Negligence Principles For Ai Implementers, Gary K. Y. Chan
Research Collection Yong Pung How School Of Law
The use of artificial intelligence (AI) in healthcare may, notwithstanding its potential benefits, result in harm to patients from allegedly negligent acts or omissions by hospitals and medical doctors. In such circumstances, how should the principles in the tort of negligence (duty of care, breach, causation, remoteness of damage, and defences) respond to AI innovations in healthcare? In particular, how may the standard of care expected of hospitals and medical doctors be informed by regulatory guidelines? We refer to case law precedents and regulatory guidelines on the roles and responsibilities of doctors and hospitals as AI implementers. Importantly, they prompt …
Navigating “I” And “We”: Coupled Identity And Spousal Influence In The Physical Activity Of Older Adults, Sapphire H. Lin, Rich Ling, Sonny Rosenthal
Navigating “I” And “We”: Coupled Identity And Spousal Influence In The Physical Activity Of Older Adults, Sapphire H. Lin, Rich Ling, Sonny Rosenthal
Research Collection College of Integrative Studies
This study explored how established dyadic social ties—particularly spousal relationships—influence older adults’ physical activity. While social support is often viewed as a positive force in promoting health behaviours, long-standing spousal dynamics can exert both enabling and constraining effects. Drawing on qualitative interviews with 22 older adults who participated in a field experiment examining the effects of feedback from fitness trackers and spousal influence, this study delves into the relational, individual, and situational factors shaping physical activity patterns. These factors led to both positive and negative outcomes in terms of step counts, goal attainment, and a diminished interdependence in couples’ physical …
The City As Showroom: Singapore And The Rise Of The "Urban Solutions" Industry, Sol Andrew Stokols
The City As Showroom: Singapore And The Rise Of The "Urban Solutions" Industry, Sol Andrew Stokols
Research Collection College of Integrative Studies
This article uses the concept of the “city as showroom” to describe an emergent logic shaping urban development that stems from the growing importance of “urban solutions” as an industry. Focusing primarily on Singapore, the article examines how certain urban districts and high-profile sites are conceptualized as “showrooms” for the infrastructure and urban technologies they aim to export around the world. The idea of the “city as showroom” combines aspects of the curation of a city’s image through showcase districts, as well as “testbed urbanism” seen in certain smart-city projects. Singapore's need to reproduce itself as a model of urban …
Potential Recyclable Materials In Buildings: A Framework For Greenhouse Gas Emissions Assessment Of Residential Buildings In Singapore, Pradeep Alva, Riccardo Talami, Wanyu Pei, Goran Sibenik, Martin Mosteiro-Romero, Clayton Miller, Rudi Stouffs
Potential Recyclable Materials In Buildings: A Framework For Greenhouse Gas Emissions Assessment Of Residential Buildings In Singapore, Pradeep Alva, Riccardo Talami, Wanyu Pei, Goran Sibenik, Martin Mosteiro-Romero, Clayton Miller, Rudi Stouffs
Research Collection College of Integrative Studies
As countries aim to reduce resource consumption and greenhouse gas (GHG) emissions, Whole Life Carbon Assessment (WLCA) has become a vital method for quantifying embodied and operational GHG emissions. However, few studies have conducted WLCA on an urban scale, often addressing operational or embodied GHG emissions in isolation without considering their cumulative impact. This study introduces a city-wide WLCA framework to assess the potential recyclable materials of urban building stock, using Singapore as a case study with 5915 public residential buildings. Upfront GHG emissions are calculated from material intensity and building information, while operational emissions are based on energy use …
Patchfuzz: Patch Fuzzing For Javascript Engines, Junjie Wang, Zhihua Xie, Xiaofei Xie, Xiaoning Du, Xiangwei Zhang
Patchfuzz: Patch Fuzzing For Javascript Engines, Junjie Wang, Zhihua Xie, Xiaofei Xie, Xiaoning Du, Xiangwei Zhang
Research Collection School Of Computing and Information Systems
Context: Patch fuzzing is a technique aimed at identifying vulnerabilities that arise from newly patched code. While researchers have made efforts to apply patch fuzzing to testing JavaScript (JS) engines with considerable success, these efforts have been limited to using ordinary test cases or publicly available vulnerability PoCs (Proof of Concepts) as seeds, and the sustainability of these approaches is hindered by the challenges associated with automating the PoC collection. Objective: To address these limitations, we propose an end-to-end sustainable approach for JS engine patch fuzzing, named PatchFuzz. Method: It automates the collection of PoCs of a broader range of …
To Wait Or To Transfer? A Three-Level Optimization Framework For Intermodal Transfer Coordination In First Train Timetabling And Bus Bridging Services Management, Hao Li, Liujiang Kang, Norman Weik, Huijun Sun, Qingying Lai, Zhiguang Cao
To Wait Or To Transfer? A Three-Level Optimization Framework For Intermodal Transfer Coordination In First Train Timetabling And Bus Bridging Services Management, Hao Li, Liujiang Kang, Norman Weik, Huijun Sun, Qingying Lai, Zhiguang Cao
Research Collection School Of Computing and Information Systems
This study addresses the integrated optimization of the first train timetabling and bus bridging service design (FTT-BBSD) for morning transfer challenges, two critical but interdependent passenger services in the public transit system. In contrast to most existing studies and conventional approaches, this study explicitly models the influence of passenger path choices and transfer mode selections on FTT-BBSD. Through a novel dual-level network representation that integrates subway and bus systems, we formulate the FTT-BBSD problem as a mixed-integer nonlinear programming model. The model simultaneously determines subway and bus timetables and bridging line deployment to minimize total travel time for all first …