Digital Commons Network^™

Towards Testing, Detecting, And Debloating Insecure Components In Android Applications, Zicheng Zhang

Dissertations and Theses Collection (Open Access)

The Android ecosystem’s openness and extensibility have fueled its dominance in the mobile market, but they also broaden the attack surface of applications by introducing insecure or redundant methods. Vulnerabilities arise from various sources, including insecure API usage, code cloning, and feature bloat, especially from unneeded components introduced during development. To address these challenges, this dissertation presents a systematic, three-phase pipeline that transitions seamlessly from vulnerability discovery to clone-based detection and, ultimately, to dynamic mitigation through runtime debloating. Each phase builds upon the insights and limitations of the previous, collectively forming a practical approach to improving Android app security.

In …

Essays On Empirical Asset Pricing, Qi Fan

Dissertations and Theses Collection (Open Access)

My dissertation consists of three studies on how investor behavior affects the outcomes in financial markets. The first study focuses on the investors’ limited capacity on processing the complicated information transmitted through interconnected firms. The other two studies explore the investor heterogeneity on preferred time of trading, due to their personal traits or irrational judgements on the market conditions.

In Chapter 2, I focus on the return predictability across economically linked firms, due to investor limited attention. I document significant outperformance of stocks whose industry peers currently experience salient (attention-grabbing) gains, especially for those with strong social ties. The long-short …

Network-Based Crypto Asset Analysis, Ling Cheng

Dissertations and Theses Collection (Open Access)

The rise of cryptocurrency, particularly Bitcoin (BTC), has revolutionized the financial landscape, enabling decentralized, peer-to-peer transactions without the need for intermediaries such as banks or financial institutions. Since its inception in 2009, Bitcoin has grown exponentially, not only in terms of market value but also in its impact on global finance. However, together with this popularity comes a wide range of cybercrimes including hacking, Ponzi schemes, wash trading, extortion, and money laundering. As noted in recent research, the volume of illicit cryptocurrency activities has grown significantly, with billions of dollars in crypto assets being stolen or used for illegal purposes …

The Impact Of Ai Usage On Employee Work Outcomes: The Mediating Roles Of Personal Control And Job Insecurity And The Moderating Role Of Ai Trust, Tiantian Wang

Dissertations and Theses Collection (Open Access)

The widespread application of artificial intelligence (AI) technology in the workplace offers significant potential for process optimization andperformance improvement. However, the psychological mechanisms throughwhich AI usage affects employee outcomes remain underexplored. To address this gap, the present study investigated a sample of 170 employees froma media company in China, utilizing a three-wave longitudinal survey design. Specifically, this study examined how AI usage influenced employee creativity and task performance improvement through two mediatingmechanisms: the enhancement of personal control in problem-solving and the elicitation of job insecurity. Furthermore, the moderating role of trust in AI inthe relationship between AI usage and job …

The Impact Of Sustainable Urban Development On The Issuance Of Urban Investment Bonds, Xinglin Shou

Dissertations and Theses Collection (Open Access)

Investment, export, and consumption have been viewed as the three driving forces behind economic development in China. Among these, investment has remarkably contributed to the urbanization in the context of China's sustained growth and development. Urbanization involves the mergingof large and medium-sized cities with surrounding areas, renovation of shantytowns and aging urban neighborhoods, and transformation of rural regions into urban areas, culminating in the establishment of a unified market. Such advancements have promoted infrastructure projects that are spearheadedby local governments and aligned with urbanization, thus catalyzing the growth of China's real estate industry, stimulating the Chinese economy, andextending the urbanization-related …

Towards Real-World Unsupervised Anomaly Detection For Images, Zhonghang Liu

Dissertations and Theses Collection (Open Access)

In the era of big data, data quality plays a critical role in computer vision, where the reliability and purity of training images are essential for optimal performance. When training models such as image classifiers and object detectors, the quality of the training data directly influences the success of the model. In other words, if the training dataset is contaminated, the model’s performance might accordingly decrease.

To address this challenge, unsupervised anomaly detection (UAD) has become an attractive research area. By automatically removing these anomalous data points, UAD can help improve the accuracy and robustness of machine learning models in …

How Industrial Clusters Affect Technological Innovation: Evidence From Vanyang Small & Micro Industrial Park, Jianming Wu

Dissertations and Theses Collection (Open Access)

This study focuses on the mechanism through which industrial clusters enhance technological innovation among micro and small enterprises. Using the VanYang Micro-Enterprise Park in Zhejiang Province as a representative case, the research integrates perspectives from industrial cluster theory, innovation theory, and spatial economics to explore how clustered environments influence enterprise innovation performance through resource integration, knowledge spillovers, and organizational collaboration. Departing from traditional static comparative methods, this study adopts an event study approach to dynamically capture the impact trajectory and temporal structure of enterprise innovation performance, with "entry into the park" serving as the key event.

Based on panel data …

Competency Of Sales Employees In Knowledge-Intensive Industries An Empirical Study Based On The Pharmaceutical Industry, Yue Zhang

Dissertations and Theses Collection (Open Access)

With the rapid development of modern technology, the pharmaceutical industry is undergoing a period of unprecedented change. On the one hand, global population growth, aging, and the continued increase in people's healthconcerns have led to an ever-expanding demand for the pharmaceutical market. On the other hand, a large amount of capital is pouring into the pharmaceutical field, prompting the emergence of new pharmaceutical enterprises, and the competition in the market is becoming increasingly heated. Against this backdrop, the replacement of pharmaceutical products has acceleratedsignificantly, with new therapeutic methods, pharmaceutical dosage forms andinnovative drugs being introduced to the market. At the …

Digital Capabilities And Customer Service Levels Of Small And Medium Sized Manufacturing Enterprises, Yuegang Niu

Dissertations and Theses Collection (Open Access)

The level of customer service, as an important tool for the differentiatedcompetition of small and medium-sized manufacturing enterprises, has reshaped the value creation model of these enterprises. With the rise of service-oriented manufacturing enterprises under the "manufacturing service- oriented" model, this is a business model that combines manufacturing andservices. It not only provides physical products but also offers related value- added services. This indicates that small and medium-sized manufacturingenterprises urgently need to enhance their digital capabilities in the digital age to achieve dynamic upgrades and further improve their customer service capabilities. High-quality customer service capabilities have put forward newrequirements for …

The Message Framing Effects In The Process Of Health Behavior Change, Zixia Fang

Dissertations and Theses Collection (Open Access)

As a key means to promote health behavior change, information intervention has gradually attracted widespread attention from all walks of life. The same information presented in different ways may lead to different decision-making judgments, especially in the process of transmitting and receiving health information, which affects individual behavioral intentions and health consumption decisions. This information framing effect is considered by most scholars to be an important factor in health behavior intervention, but its specific mechanism of action in health behavior change has not been fully discussed. This paper constructs a theoretical model of information framing effect to explore the specific …

Temporal Relational Graph Convolutional Networks For Financial Applications, Brindha Priyadarshini Jeyaraman

Dissertations and Theses Collection (Open Access)

The financial industry operates within a highly dynamic and interconnected ecosystem, presenting unique challenges for predictive modeling and decision-making. Accurately forecasting financial performance, assessing credit risk, detecting fraud, and ensuring compliance require methodologies that can capture complex temporal, relational, and contextual dependencies within financial data. This thesis investigates the use of Temporal Relational Graph Convolutional Networks (TRGCNs) combined with financial knowledge graphs (FKGs) to address these challenges and enable advanced analytics in the financial domain. We introduce FintechKG, a financial knowledge graph constructed through a threedimensional information extraction process, incorporating entities, temporal dimensions, and domain-specific financial relationships. A TRGCN-based framework …

Statistical Inference For Noisy Matrix Completion Incorporating Auxiliary Information, Shujie Ma, Po-Yao Niu, Yichong Zhang, Yinchu Zhu

Research Collection School Of Economics

This article investigates statistical inference for noisy matrix completion in a semi-supervised model when auxiliary covariates are available. The model consists of two parts. One part is a low-rank matrix induced by unobserved latent factors; the other part models the effects of the observed covariates through a coefficient matrix which is composed of high-dimensional column vectors. We model the observational pattern of the responses through a logistic regression of the covariates, and allow its probability to go to zero as the sample size increases. We apply an iterative least squares (LS) estimation approach in our considered context. The iterative LS …

The Digitalization Of Insolvency Proceedings, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Despite the international divergences existing in the design of insolvency law, there is a common feature of insolvency proceedings that, to a greater or lesser extent, is somehow universal: insolvency proceedings are generally costly and lengthy processes. For that reason, it is not surprising that a significant body of the literature on insolvency law deals with different mechanisms to make insolvency proceedings more efficient. This article examines how technology can contribute to that goal. To that end, it starts by reviewing how countries are deploying, or can deploy, technology in different aspects and stages of insolvency proceedings and how such …

Decarbonising Digital Infrastructure And Urban Sustainability In The Case Of Data Centres, Felicia H. M. Liu, Karen P. Y. Lai, Bertrand Seah, Winston T. L. Chow

Research Collection College of Integrative Studies

This paper critically assesses the complex interplay between urban transitions of digitisation and sustainability. Building on a mixed-method research design, we unpack the challenges of decarbonising digital infrastructure while attending to urban sustainability goals in a land- and water-scarce country facing significant physical climate risks. We identify transferrable lessons on the economic, technological, and environmental synergies and trade-offs behind data centre development and argue that stewarding the global data centre sector towards sustainability requires an ecosystem-wide approach. We identify implementation gaps across five key dimensions: technological innovation, policy and regulation, finance, infrastructure, and people. We find that the progress and …

What Is A Digital Twin Anyway? Deriving The Definition For The Built Environment From Over 15,000 Scientific Publications, Abdelrahman Mahmoud, Edgardo Macatulad, Binyu Lei, Matias Quintana, Clayton Miller, Filip Biljecki

Research Collection College of Integrative Studies

The concept of Digital Twins (DT) has attracted significant attention across various domains, particularly within the built environment. However, there is a sheer volume of definitions and the terminological consensus remains out of reach. The lack of a universally accepted definition leads to ambiguities in their conceptualization and implementation, and may cause miscommunication for both researchers and practitioners.We employed Natural Language Processing (NLP) techniques to systematically extract and analyze definitions of DTs from a corpus of more than 15,000 full-text articles spanning diverse disciplines. The study compares these findings with insights from an expert survey that included 52 experts. The …

The Insurgent Smart City: How A Social Movement Created An Alternative Imaginary Of The Smart City, Andrew Stokols

Research Collection College of Integrative Studies

Urban scholars have critiqued smart cities for their association with neoliberal governance, narrow focus on quantifiable aspects of urban systems, and failure to incorporate citizens’ needs or aspirations. The “smart city” remains a contested concept and as such is subject to reappropriation. Here, I analyze the case of an urban social movement, the 2019–2020 Hong Kong Anti-ELAB protests, as an alternative, “insurgent smart city.” Following from an earlier network analysis of Telegram channels used during the protests, I show how the communications system underpinning much of the protest action simultaneously enabled coordination while also remaining open to grassroots decision-making and …

On Generalization Across Environments In Multi-Objective Reinforcement Learning, Jayden Jing Xiang Teoh, Pradeep Varakantham, Peter Vamplew

Research Collection School Of Computing and Information Systems

No abstract provided.

Pearl: Towards Permutation-Resilient Llms, Liang Chen, Li Shen, Yang Deng, Xiaoyan Zhao, Bin Liang, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

The in-context learning (ICL) capability of large language models (LLMs) enables them to perform challenging tasks using provided demonstrations. However, ICL is highly sensitive to the ordering of demonstrations, leading to instability in predictions. This paper shows that this vulnerability can be exploited to design a natural attack - difficult for model providers to detect - that achieves nearly 80% success rate on LLaMA-3 by simply permuting the demonstrations. Existing mitigation methods primarily rely on post-processing and fail to enhance the model's inherent robustness to input permutations, raising concerns about safety and reliability of LLMs. To address this issue, we …

Ada-Gen: Iterative And Incremental Generation Of Full-Stack Apps For Learning Agile/Devops Software Development Practices, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

To learn Agile/DevOps practices effectively, students need to apply them in an actual software development project. This is challenging if students are mostly from non-computing backgrounds and they do not have time in the curriculum to learn programming and related tools. Therefore, it is important to help students who do not possess programming foundations to develop fully functional software during the process of learning Agile/DevOps concepts. We noted that existing low-code/no-code app development platforms have not been designed to teach Agile/DevOps practices. On the other hand, recent AI-based tools for code generation such as GitHub Copilot have been built mainly …

Capo: Cooperative Plan Optimization For Efficient Embodied Multi-Agent Cooperation, Jie Liu, Pan Zhou, Yingjun Du, Ah-Hwee Tan, Cees Snoek, Jan-Jakob Sonke, Efstratios Gavves

Research Collection School Of Computing and Information Systems

In this work, we address the cooperation problem among large language model (LLM) based embodied agents, where agents must cooperate to achieve a common goal. Previous methods often execute actions extemporaneously and incoherently, without long-term strategic and cooperative planning, leading to redundant steps, failures, and even serious repercussions in complex tasks like search-and-rescue missions where discussion and cooperative plan are crucial. To solve this issue, we propose Cooperative Plan Optimization (CaPo) to enhance the cooperation efficiency of LLM-based embodied agents. Inspired by human cooperation schemes, CaPo improves cooperation efficiency with two phases: 1) meta-plan generation, and 2) progress-adaptive meta-plan and …

Ivyapc: Auditable Generalized Payment Channels, Ming Li, Yuxian Li, Jian Weng, Yingjiu Li, Jiasi Weng, Junzuo Lai, Robert H. Deng

Research Collection School Of Computing and Information Systems

Payment channels are a cornerstone of a scalable blockchain infrastructure that enables transacting parties to lock assets on the blockchain and perform rapid off-chain updates with minimal latency and overhead. These protocols dramatically reduce on-chain interaction and improve throughput, with blockchain consensus only invoked in the event of disputes or final closure. While widely adopted in single-chain settings—such as in the Lightning Network for Bitcoin—existing constructions have several limitations, in particular they suffer from at least one of the following limitations: 1. No cross-chain. They do not enable fast trading of assets that reside on multiple isolated blockchains. 2. Non-optimal …

Rethinking Light Decoder-Based Solvers For Vehicle Routing Problems, Ziwei Huang, Jianan Zhou, Zhiguang Cao, Yixin Xu

Research Collection School Of Computing and Information Systems

Light decoder-based solvers have gained popularity for solving vehicle routing problems (VRPs) due to their efficiency and ease of integration with reinforcement learning algorithms. However, they often struggle with generalization to larger problem instances or different VRP variants. This paper revisits light decoder-based approaches, analyzing the implications of their reliance on static embeddings and the inherent challenges that arise. Specifically, we demonstrate that in the light decoder paradigm, the encoder is implicitly tasked with capturing information for all potential decision scenarios during solution construction within a single set of embeddings, resulting in high information density. Furthermore, our empirical analysis reveals …

Rethinking Neural Multi-Objective Combinatorial Optimization Via Neat Weight Embedding, Jinbiao Chen, Zhiguang Cao, Jiahai Wang, Yaoxin Wu, Hanzhang Qin, Zizhen Zhang, Yue-Jiao Gong

Research Collection School Of Computing and Information Systems

Recent decomposition-based neural multi-objective combinatorial optimization (MOCO) methods struggle to achieve desirable performance. Even equipped with complex learning techniques, they often suffer from significant optimality gaps in weight-specific subproblems. To address this challenge, we propose a neat weight embedding method to learn weight-specific representations, which captures weight-instance interaction for the subproblems and was overlooked by most current methods. We demonstrate the potentials of our method in two instantiations. First, we introduce a succinct addition model to learn weight-specific node embeddings, which surpassed most existing neural methods. Second, we design an enhanced conditional attention model to simultaneously learn the weight embedding …

Dps: Design Pattern Summarisation Using Code Features, Najam Nazar, Sameer Sikka, Christoph Treude

Research Collection School Of Computing and Information Systems

Automatic summarisation has been used efficiently in recent years to condense texts, conversations, audio, code, and various other artefacts. A range of methods, from simple template-based summaries to complex machine learning techniques -- and more recently, large language models -- have been employed to generate these summaries. Summarising software design patterns is important because it helps developers quickly understand and reuse complex design concepts, thereby improving software maintainability and development efficiency. However, the generation of summaries for software design patterns has not yet been explored.Our approach utilises code features and JavaParser to parse the code and create a JSON representation. …

Alphaedit: Null-Space Constrained Knowledge Editing For Language Models, Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi, Xiang Wang, Xiangnan He, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Large language models (LLMs) often exhibit hallucinations, producing incorrector outdated knowledge. Hence, model editing methods have emerged to enabletargeted knowledge updates. To achieve this, a prevailing paradigm is the locatingthen-editing approach, which first locates influential parameters and then edits themby introducing a perturbation. While effective, current studies have demonstrated that this perturbation inevitably disrupt the originally preserved knowledge within LLMs, especially in sequential editing scenarios. To address this, we introduce AlphaEdit, a novel solution that projects perturbation onto the null space of the preserved knowledge before applying it to the parameters. We theoretically prove that this projection ensures the output …

Open-Set Graph Anomaly Detection Via Normal Structure Regularisation, Qizhou Wang, Guansong Pang, Mahsa Salehi, Xiaokun Xia, Christopher Leckie

Research Collection School Of Computing and Information Systems

This paper considers an important Graph Anomaly Detection (GAD) task, namely open-set GAD, which aims to train a detection model using a small number of normal and anomaly nodes (referred to as *seen anomalies*) to detect both seen anomalies and *unseen anomalies* (*i.e*., anomalies that cannot be illustrated the training anomalies). Those labelled training data provide crucial prior knowledge about abnormalities for GAD models, enabling substantially reduced detection errors. However, current supervised GAD methods tend to over-emphasise fitting the seen anomalies, leading to many errors of detecting the unseen anomalies as normal nodes. Further, existing open-set AD models were introduced …

Can Industrial Agriculture Be Resilient To External Shocks? Industrial Agriculture In Diversified Clusters In Rural China, Qian Forrest Zhang, Zhanping Hu

Research Collection School of Social Sciences

We propose a new model – “industrial agriculture of smallholders” – to conceptualize the agri-food system in China. These smallholders are embedded in “diversified clusters” in rural China, which also include rural industries and extensive rural-urban linkages. Their relationships with markets are more complex and dynamic than what is often portrayed under the linear framework of “commodity chains”. As an alternative to the globalized model of industrial agriculture, we argue that “industrial agriculture of smallholders” has greater resilience to external shocks. Using a village in northern China during the COVID-19 pandemic, we illustrate how economic diversity within this “diversified cluster” …

Registered Replication Report: Study 3 From Trafimow And Hughes (2012), Sean C. Rife, Et Al

Research Collection School of Social Sciences

Terror-management theory (TMT) proposes that when people are made aware of their own death, they are more likely to endorse cultural values. TMT is a staple of social psychology, featured prominently in textbooks and the subject of much research. The implications associated with TMT are significant because its advocates claim it can partially explain cultural conflicts, intergroup antagonisms, and even war. However, considerable ambiguity regarding effect size exists, and no preregistered replication of death-thought-accessibility findings exists. Moreover, there is debate regarding the role of time delay between the manipulation of mortality salience and assessment of key measures. We present results …

Context-Aware Representation: Jointly Learning Item Features And Selection From Triplets, Rodrigo Alves, Antoine Ledent

Research Collection School Of Computing and Information Systems

In areas of machine learning such as cognitive modeling or recommendation, user feedback is usually context-dependent. For instance, a website might provide a user with a set of recommendations and observe which (if any) of the links were clicked by the user. Similarly, there is growing interest in the so-called “odd-one-out” learning setting, where human participants are provided with a basket of items and asked which is the most dissimilar to the others. In both of those cases, the presence of all the items in the basket can influence the final decision. In this article, we consider a classification task …

Digital Transformation And The Future Of Work: Closing The Digital Skills Gap, Siu Loon Hoe

Research Collection School Of Computing and Information Systems

The purpose of this article is to discuss the near future digital technology landscape and propose several specific in-demand digital skills for organizations and individuals in the next few years. This article reviews some recent publications from representative inter-governmental, governmental, non-governmental, and commercial organizations on the rise of digital technologies and corresponding growth in digital jobs. Within this context, several specific in-demand skills are proposed by the author who has written a book on the topic of digital transformation. Rapid advancements in digital technologies continue to shape organizational practices and the future of work. To take advantage of emerging digital …