Digital Commons Network^™

Towards An Extended Resource Theory Of Marital Power: Parental Education And Household Decision-Making In Rural China, Cheng Cheng, Yu Xie

Research Collection School of Social Sciences

Existing literature on the resource theory of marital power has focused on the relative resources of spouses and overlooked the resource contributions of spouses’ extended families. We propose an extended resource theory that considers how the comparative resources of a couple’s natal families are directly associated with marital power, net of the comparative resources of the couple. Using data from the China Panel Family Studies, we examine how the relative education of a couple’s respective parents affects the wife’s decision-making power, net of the relative education of the couple. Results suggest that the higher the wife’s parental education relative to …

Does Relationship Conflict Reduce Novel Idea Communication Through Perceived Leader Openness? Power Distance Orientation As A Moderator, Ming-Hong Tsai

Research Collection School of Social Sciences

Purpose: This paper aims to investigate why followers have low perceptions of leader openness and thus feel reluctant to communicate novel ideas by examining leader–follower relationship conflict (i.e. interpersonal incompatibility) and a follower’s power distance orientation (i.e. an acceptance of uneven power distribution in organizations) as antecedents. Design/methodology/approach: The research administrators conducted a three-wave work behavior survey in Study 1, a laboratory experiment in Study 2, and an online experiment in Study 3. Findings: The results demonstrated that leader–follower relationship conflict reduced followers’ perceptions of leader openness. However, the negative impact of relationship conflict became non-significant when followers have high …

Registered Replication Report: A Large Multilab Cross-Cultural Conceptual Replication Of Turri Et Al. (2015), Braeden Hall, Kathleen Schmidt, Jordan Wagge, Savannah C. Lewis, Sophia C. Weissgerber, Felix Kiunke, ..., Andree Hartanto

Research Collection School of Social Sciences

According to the justified true belief (JTB) account of knowledge, people can truly know something only if they have a belief that is both justified and true (i.e., knowledge is JTB). This account was challenged by Gettier, who argued that JTB does not explain knowledge attributions in certain situations, later called “Gettier-type cases,” wherein protagonists are justified in believing something to be true, but their belief was correct only because of luck. Laypeople may not attribute knowledge to protagonists with justified but only luckily true beliefs. Although some research has found evidence for these so-called Gettier intuitions, Turri et al. …

Deliberately Making And Correcting Errors In Mathematical Problem-Solving Practice Improves Procedural Transfer To More Complex Problems, Janson Boon Khang Yap, Sarah Shi Hui Wong

Research Collection School of Social Sciences

How can students effectively learn and transfer mathematical procedures to solve new problems? Here, we tested the effects of deliberately committing and correcting errors during mathematical problem-solving practice on transfer of the learned procedures. In two experiments, university students were instructed on mathematical algorithms (synthetic division and matrix multiplication) and solved practice problems during open-book study. Learners were then tested on flexibly adapting the algorithms to solve novel problems that were structurally more complex or embedded in “real-life” scenarios (i.e., mathematical word problems). Deliberately committing and correcting procedural errors during problem-solving practice yielded better transfer than errorless repeated practice (Experiment …

Construction And Empirical Assessment Of An Employee Health Management Index System For Chinese Enterprises, Ming Dong

Dissertations and Theses Collection (Open Access)

Purpose: Employee health management is critical for enhancing corporate productivity, and scientific evaluation is core to effective health management practices. This study aims to construct an evaluation index system for assessing the employee health management effectiveness tailored to China’s national conditions (Hereinafter called “evaluation system”), and to empirically assess its differentiation, accuracy, and universality.

Methodology: (1) Grounded in literature and policy analysis, the study adopts the PDCA theory as a foundational framework and employs a modified Delphi method to finalize the evaluation system's structure. Indicator weights were determined using the Analytic Hierarchy Process, and a standard scale was created for …

Impact Of Industrial Park Platforms On Sme Financing: Evidence From The Ld Park, Zhendong Liu

Dissertations and Theses Collection (Open Access)

Small and medium-sized enterprises (SMEs) are essential to the Chinese economy. However, when seeking financing, SMEs often face stricter financing conditions and higher financing costs due to information asymmetry in the market, commonly referred to as the problem of “difficult and expensive financing.” This issue severely limits the growth potential of SMEs. This study explores the positive role that industrial parks play as a bridge between banks and SMEs in alleviating the “difficult and expensive financing” problem. The study surveyed 54 industrial parks and collected 268 valid questionnaires from banks, industrial parks, and SMEs. The data analysis yielded the following …

A Study On The Impact Of Relationship Strength In Technological Collaboration Networks, Absorptive Capacity, And Leadership Regulatory Focus On Team Ambidextrous Innovation, Zhen Li

Dissertations and Theses Collection (Open Access)

In the context of rapid global economic development, competition among enterprises has become increasingly fierce, making innovation the core driving force for maintaining competitive advantage and promoting sustainable development. This paper explores the impact of relationship strength within technological collaboration networks, absorptive capacity, and leadership regulatory focus on incremental and radical innovation. The study finds that while relationship strength has no significant impact on incremental innovation, it has a negative effect on radical innovation. The absorptive capacity within technological collaboration networks positively influences both types of innovation. The research also highlights the critical role of leadership regulatory focus: High prevention-focus …

Influence Of Artificial Intelligence (Ai) On Decision-Making For Market-Entry Strategies In Emerging Economies, Tejas Deshpande

Dissertations and Theses Collection (Open Access)

International firms with growth-oriented business models face a complex array of factors when planning to enter emerging markets. These markets are characterized by dynamic socio-economic and geopolitical conditions, often resulting in limited market intelligence and a fragmented understanding of the business ecosystem. To succeed, firms must align their short-term objectives and long-term strategic goals with the specific characteristics of these target markets.

Decision-making in such environments is fraught with uncertainty and is critical in determining the success or failure of market-entry strategies. While business leaders rely on their cognition and heuristics to navigate these challenges, the complexity and volume of …

Social Institutions And Low Birth Rates, Christine Ho, Yutao Wang

Research Collection School Of Economics

We document three cross-sectional stylized facts on labor supply and family formation. First, female labor force participation (FLFP) and total fertility rates (TFRs) are much lower in Eastern societies compared to Western economies. Second, labor hours and the gender pay gap are much higher in the East than in the West. Third, parents invest more in schooling in Eastern societies compared to Western economies. To account for these features, we develop and estimate a rich heterogeneous-agent model with endogenous marriage, fertility, labor supply, and time and money investment in children. Estimates using data from South Korea and the United States …

Granulocyte Colony Stimulating Factor Promotes Scarless Tissue Regeneration, Jianhe Huang, Satish: Murphy Sati, Casey A. Spencer, Emmanuel Rapp, Stephen M. Prouty, Scott Korte, Olivia Ahart, Emily Sheng, Anna E. Kersh, Denis Leung, Thomas H. Leung, Leung, Denis H. Y.

Research Collection School Of Economics

Mammals typically heal with fibrotic scars, and treatments to regenerate human skin and hair without a scar remain elusive. We discovered that mice lacking C-X-C motif chemokine receptor 2 (CXCR2 knockout [KO]) displayed robust and complete tissue regeneration across three different injury models: skin, hair follicle, and cartilage. Remarkably, wild-type mice receiving plasma from CXCR2 KO mice through parabiosis or injections healed wounds scarlessly. A comparison of circulating proteins using multiplex ELISA revealed a 24-fold higher plasma level of granulocyte colony stimulating factor (G-CSF) in CXCR2 KO blood. Local injections of G-CSF into wild-type (WT) mouse wound beds reduced scar …

Latent Representation Learning For Geospatial Entities, Ween Jiann Lee, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Representation learning has been instrumental in the success of machine learning, offering compact and performant data representations for diverse downstream tasks. In the spatial domain, it has been pivotal in extracting latent patterns from various data types, including points, polylines, polygons, and networked structures. However, existing approaches often fall short of explicitly capturing both semantic and spatial information, relying on proxies and synthetic features. This article presents GeoNN, a novel graph neural network-based model designed to learn spatially-aware embeddings for geospatial entities. GeoNN leverages edge features generated from geodesic functions, dynamically selecting relevant features based on relative locations. It introduces …

Kpiroot: Efficient Monitoring Metric-Based Root Cause Localization In Large-Scale Cloud Systems, Wenwei Gu, Xinying Sun, Jinyang Liu, Yintong Huo, Zhuangbin Chen, Jianping Zhang, Jiazhen Gu, Yongqiang Yang, Michael R. Lyu

Research Collection School Of Computing and Information Systems

To ensure the reliability of cloud systems, their run-time status reflecting the service quality is periodically monitored with monitoring metrics, i.e., KPIs (key performance indicators). When performance issues happen, root cause localization pinpoints the specific KPIs that are responsible for the degradation of overall service quality, facilitating prompt problem diagnosis and resolution. To this end, existing methods generally locate root-cause KPIs by identifying the KPIs that exhibit a similar anomalous trend to the overall service performance. While straightforward, solely relying on the similarity calculation may be ineffective when dealing with cloud systems with complicated interdependent services. Recent deep learning-based methods …

"Asian" Principles For The Recognition And Enforcement Of Foreign Judgments? Singapore As A Case Study, Adeline Chong

Research Collection Yong Pung How School Of Law

This paper considers if there can be said to be an “Asian” body of principles for the recognition and enforcement of foreign judgments. Tapping on the results of a research project which was conducted from 2016 to 2020, it is submitted that the answer to this query is in the negative. However, it is suggested that what marks out the “Asian” approach to private international law is the willingness of Asian countries to look outwards for reform and development and to balance the adoption of international norms against important local norms and objectives. Singapore’s approach to the recognition and enforcement …

Can Federated Learning Solve Ai’S Data Privacy Problem?: A Legal Analysis, Warren B. Chik, Florian Gamper

Research Collection Yong Pung How School Of Law

Federated learning (FL) is a method of training AI systems on different datasets without sharing data. The promise of FL is to enable AI systems to be trained on data, including personal data, while preserving data privacy and confidentiality, and thus, inter alia, facilitate compliance with data protection legislation. FL has generated a considerable interest amongst the computer science community, yet there is a dearth of legal analysis of FL. This is a problem because the question of whether FL facilitates compliance with data protection legislation is a legal question. This article will fill this lacuna by providing a comprehensive …

Trust And Robotics: A Multi-Staged Decision-Making Approach To Robots In Community, Wenxi Zhang, Willow Wong, Mark Findlay

Research Collection Yong Pung How School Of Law

With the desired outcome of social good within the wider robotics ecosystem, trust is identified as the central adhesive of the human–robot interaction (HRI) interface. However, building trust between humans and robots involves more than improving the machine’s technical reliability or trustworthiness in function. This paper presents a holistic, community-based approach to trust-building, where trust is understood as a multifaceted and multi-staged looped relation that depends heavily on context and human perceptions. Building on past literature that identifies dispositional and learned stages of trust, our proposed decision to trust model considers more extensively the human and situational factors influencing how …

China And Global Trade Order Post Ukraine War: From Value Chains To Values Chains, Henry S. Gao

Research Collection Yong Pung How School Of Law

China has long been hailed as the biggest success story in economic development through integration into global value chains, especially since its accession to the WTO 20 years ago. However, it is much less well-known how China refitted the global value chain narrative to influence economic analysis and trade governance. At the same time, the value chains analysis also backfired when the U.S. tried to cut China out of its supply chains and pushed for decoupling with China, while China itself started to abuse its role in value chains for political gains. The process was further accelerated by the Ukraine …

The Three Eras Of Australian Practice On Mpas: The Interaction Between National And International Law And Policy, Ethan Beringen, Nengye Liu, Michelle Mei Ling Lim

Research Collection Yong Pung How School Of Law

Australia has attempted to position itself as a world leader in Marine Protected Area (MPA) practice through leveraging its significant national MPA network as well as its heavy involvement in the creation of high seas MPAs in the Antarctic. However, the quality of Australia’s domestic and international MPA practice have separately been subject to similar and convincing critiques. Despite this, little research exists which highlights how these two levels of law-making may interact regarding MPAs. Hence, the question to be addressed is: ‘How does Australia’s domestic and international MPA practice interact?’ Through drawing upon middle power theory to characterise this …

Motivating Physical Activity With Fitness Tracking And The Interpersonal Context, Sapphire H. Lin, Sonny Rosenthal, Rich Ling

Research Collection College of Integrative Studies

Many societies have aging populations. Getting older people to exercise can help them achieve a higher quality of life. Fitness tracking and social support can buttress that goal. This study tested the effects of fitness tracking and spousal influence on the physical activity of older adults. In a 2 (blinded vs. feedback) × 2 (individual vs. dyad) between-group experiment, 240 participants received a fitness tracker with a visible or blinded display. They participated in the three-month experiment either individually or with their spouses. Participants who received feedback met daily step counts of 7500 and 10,000 more frequently than those without …

What Is Beyond Measurement For Social Cohesion?, Qian Hui Tricia Tok, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

“What gets measured gets managed” has long been a mantra to rally improvement throughout various domains of life. Perhaps this is also the case for existing work on social cohesion, whereby much of its conceptual and operational elements have received interest in both academic and policy research aiming for practical improvement with regard to the cohesiveness of communities and societies. We contend, however, that not everything that matters for social cohesion may be measurable, and not everything that has been measured for social cohesion may matter. This is not to suggest that not measuring any indicators is better than measuring …

Constrained Assortment Optimization Under The Cross-Nested Logit Model, Cuong Le, Tien Mai

Research Collection School Of Computing and Information Systems

We study the assortment optimization problem under general linear constraints, where the customer choice behavior is captured by the cross-nested logit model. In this problem, there is a set of products organized into multiple subsets (or nests), where each product can belong to more than one nest. The aim is to find an assortment to offer to customers so that the expected revenue is maximized. We show that, under the cross-nested logit model, the unconstrained assortment problem is NP-hard even when there are only two nests, and the problem is generally NP-hard to approximate to any constant factors. To tackle …

Video Editing For Video Retrieval, Bin Zhu, Kevin Flanagan, Adriano Fragomeni, Michael Wray, Dima Damen

Research Collection School Of Computing and Information Systems

Though pre-training vision-language models have demonstrated significant benefits in boosting video-text retrieval performance from large-scale web videos, fine-tuning still plays a critical role with manually annotated clips with start and end times, which requires considerable human effort. To address this issue, we explore an alternative cheaper source of annotations, single timestamps, for video-text retrieval. We initialise clips from timestamps in a heuristic way to warm up a retrieval model. Then a video clip editing method is proposed to refine the initial rough boundaries to improve retrieval performance. A student-teacher network is introduced for video clip editing: the teacher model is …

Stagedvulbert: Multi-Granular Vulnerability Detection With A Novel Pre-Trained Code Model, Yuan Jiang, Yujian Zhang, Xiaohong Su, Christoph Treude, Tiantian Wang

Research Collection School Of Computing and Information Systems

The emergence of pre-trained model-based vulnerability detection methods has significantly advanced the field of automated vulnerability detection. However, these methods still face several challenges, such as difficulty in learning effective feature representations of statements for fine-grained predictions and struggling to process overly long code sequences. To address these issues, this study introduces StagedVulBERT, a novel vulnerability detection framework that leverages a pre-trained code language model and employs a coarse-to-fine strategy. The key innovation and contribution of our research lies in the development of the CodeBERT-HLS component within our framework, specialized in hierarchical, layered, and semantic encoding. This component is designed …

Nigerian Software Engineer Or American Data Scientist? Github Profile Recruitment Bias In Large Language Models, Takashi Nakano, Kazumasa Shimari, Raula Gaikovina Kula, Christoph Treude, Marc Cheong, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have taken the world by storm, demonstrating their ability not only to automate tedious tasks, but also to show some degree of proficiency in completing software engineering tasks. A key concern with LLMs is their “black-box” nature, which obscures their internal workings and could lead to societal biases in their outputs. In the software engineering context, in this early results paper, we empirically explore how well LLMs can automate recruitment tasks for a geographically diverse software team. We use OpenAI's ChatGPT to conduct an initial set of experiments using GitHub User Profiles from four regions to …

Retrofitting A Legacy Cutlery Washing Machine Using Computer Vision, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Industry 4.0, the digitalization of manufacturing promises to lead to lowered cost, efficient processes and even discovery of new business models. However, many of the enterprises have huge investments in legacy machines which are not 'smart'. In this study, we thus designed a cost-efficient solution to retrofit a legacy conveyor belt-based cutlery washing machine with a commodity web camera. We then applied computer vision (using both traditional image processing and deep learning techniques) to infer the speed and utilization of the machine. We detailed the algorithms that we designed for computing both speed andutilization. With the existing operational constraints of …

Predicting The Limits: Tailoring Unnoticeable Hand Redirection Offsets In Virtual Reality To Individuals' Perceptual Boundaries, Martin Feick, Kora Persephone Regitz, Lukas Gehrke, André Zenner, Anthony Tang, Tobias Patrick Jungbluth, Maurice Rekrut, Antonio Krüger

Research Collection School Of Computing and Information Systems

Many illusion and interaction techniques in Virtual Reality (VR) rely on Hand Redirection (HR), which has proved to be effective as long as the introduced offsets between the position of the real and virtual hand do not noticeably disturb the user experience. Yet calibrating HR offsets is a tedious and time-consuming process involving psychophysical experimentation, and the resulting thresholds are known to be affected by many variables—limiting HR’s practical utility. As a result, there is a clear need for alternative methods that allow tailoring HR to the perceptual boundaries of individual users. We conducted an experiment with 18 participants combining …

Themis: Automatic And Efficient Deep Learning System Testing With Strong Fault Detection Capability, Dong Huang, Tsz On Li, Xiaofei Xie, Heming Cui

Research Collection School Of Computing and Information Systems

Deep Learning Systems (DLSs) have been widely applied in safety-critical tasks such as autopilot. However, when a perturbed input is fed into a DLS for inference, the DLS often has incorrect outputs (i.e., faults). DLS testing techniques (e.g., DeepXplore) detect such faults by generating perturbed inputs to explore data flows that induce faults. Since a DLS often has infinitely many data flows, existing techniques require developers to manually specify a set of activation values in a DLS’s neurons for exploring fault-inducing data flows. Unfortunately, recent studies show that such manual effort is tedious and can detect only a tiny proportion …

Joint Weakly Supervised Image Emotion Analysis Based On Interclass Discrimination And Intraclass Correlation, Xinyue Zhang, Zhaoxia Wang, Guitao Cao, Seng-Beng Ho

Research Collection School Of Computing and Information Systems

Regional information-based image emotion analysis has recently garnered significant attention. However, existing methods often focus on identifying region proposals through layered steps or merely rely on visual saliency. These approaches may lead to an underestimation of emotional categories and a lack of comprehensive interclass discrimination perception and emotional intraclass contextual mining. To address these limitations, we propose a novel approach named InterIntraIEA, which combines interclass discrimination and intraclass correlation joint learning capabilities for image emotion analysis. The proposed method not only employs category-specific dictionary learning for class adaptation, but also models intraclass contextual relationships and perceives correlations at the channel …

Navigating Governance Paradigms: A Cross-Regional Comparative Study Of Generative Ai Governance Processes & Principle, Jose Luna, Ivan Tan, Xiaofei Xie, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

As Generative Artificial Intelligence (GenAI) technologies evolve at an unprecedented rate, global governance approaches struggle to keep pace with the technology, highlighting a critical issue in the governance adaptation of significant challenges. Depicting the nuances of nascent and diverse governance approaches based on risks, rules, outcomes, principles, or a mix across different regions around the globe is fundamental to discern discrepancies and convergences and to shed light on specific limitations that need to be addressed, thereby facilitating the safe and trustworthy adoption of GenAI. In response to the need and the evolving nature of GenAI, this paper seeks to provide …

Exploring Conversations Between A Practitioner And A Person With Dementia, Kotaro Hara, Rosiana Natalie, Wei Soon Cheong, Jingjing Gu, Qianli Xu

Research Collection School Of Computing and Information Systems

In social service centers, practitioners engage in conversations with clients with dementia to facilitate their daily activities and provide support when they are distressed. However, the nature of the care demands the practitioner’s active engagement, which becomes difficult to deliver as the number of people who need care expands. Researchers have been investigating the efficacy of developing agents that assume conversational tasks to alleviate this work. To contribute to the future design of agents for caregiving, we collected and analyzed ten conversations between clients with mild dementia and practitioners who provide care. Our analyses of turn-taking dynamics and dialogue acts …

Temporal Relational Graph Convolutional Network Approach To Financial Performance Prediction, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang

Research Collection School Of Computing and Information Systems

Accurately predicting financial entity performance remains a challenge due to the dynamic nature of financial markets and vast unstructured textual data. Financial knowledge graphs (FKGs) offer a structured representation for tackling this problem by representing complex financial relationships and concepts. However, constructing a comprehensive and accurate financial knowledge graph that captures the temporal dynamics of financial entities is non-trivial. We introduce FintechKG, a comprehensive financial knowledge graph developed through a three-dimensional information extraction process that incorporates commercial entities and temporal dimensions and uses a financial concept taxonomy that ensures financial domain entity and relationship extraction. We propose a temporal and …