Digital Commons Network^™

Not Getting Laid: Consumer Acceptance Of Precision Fermentation Made Egg, Oscar Z. Thomas, Mark Chong, Angela K. Y. Leung, Tricia M. Fernandex, Shu Tian Ng

Research Collection Lee Kong Chian School Of Business

Mounting concern over the negative externalities of industrialized animal agriculture, coupled with falling cost curves of novel food technologies have birthed the field of cellular agriculture: a new category of food technology seeking to reproduce the sensory experiences of animal protein, and promising a cleaner, more ethical way of enjoying animal proteins. This research examines consumer acceptance of precision fermentation (PF) made egg products in Germany, Singapore, and the USA. Using an online survey of 3,006 participants, the study examines demographic and dietary traits that predict willingness to try such products and identifies the reasons why consumers are most attracted …

Log-Based Anomaly Detection Based On Evt Theory With Feedback, Jinyang Liu, Junjie Huang, Yintong Huo, Zhihan Jiang, Jiazhen Gu, Zhuangbin Chen, Cong Feng, Minzhi Yan, R. Michael Lyu

Research Collection School Of Computing and Information Systems

System logs play a critical role in maintaining the reliability of software systems. Fruitful studies have explored automatic log-based anomaly detection and achieved notable accuracy on benchmark datasets. However, when applied to large-scale cloud systems, these solutions face limitations due to high resource consumption and lack of adaptability to evolving logs. In this paper, we present an accurate, lightweight, and adaptive log-based anomaly detection framework, referred to as SeaLog. Our method introduces a Trie-based Detection Agent (TDA) that employs a lightweight, dynamically-growing trie structure for real-time anomaly detection. To enhance TDA's accuracy in response to evolving log data, we enable …

Mentor Holding Behaviours: The Role Of Supervisors And Effects On Protégés, Menzhong Gao

Dissertations and Theses Collection (Open Access)

The concept of holding behaviours has emerged as a response to the paradox that arises when employees require support but organisations face challenges in providing it. In today’s workplaces, job demands and organisational uncertainty have escalated, rendering traditional, hierarchical support systems inadequate to alleviate anxiety. Holding environments offer a temporary safe space for employees to express emotions and cope with uncertainty and insecurity.

Despite the importance of holding behaviours in addressing self-reliance and support dilemmas, limited research has been conducted on their antecedents, consequences, mechanisms, and boundary conditions. To fill this gap, this study proposes a trickle-down model that integrates …

K-St: A Formal Executable Semantics Of The Structured Text Language For Plcs, Kun Wang, Jingyi Wang, Christopher M. Poskitt, Xiangxiang Chen, Jun Sun, Peng Cheng

Research Collection School Of Computing and Information Systems

Programmable Logic Controllers (PLCs) are responsible for automating process control in many industrial systems (e.g. in manufacturing and public infrastructure), and thus it is critical to ensure that they operate correctly and safely. The majority of PLCs are programmed in languages such as Structured Text (ST). However, a lack of formal semantics makes it difficult to ascertain the correctness of their translators and compilers, which vary from vendor-to-vendor. In this work, we develop K-ST, a formal executable semantics for ST in the K framework. Defined with respect to the IEC 61131-3 standard and PLC vendor manuals, K-ST is a high-level …

Generative Model-Based Testing On Decision-Making Policies, Zhuo Li, Xiongfei Wu, Derui Zhu, Mingfei Cheng, Siyuan Chen, Fuyuan Zhang, Xiaofei Xie, Lei Ma, Jianjun Zhao

Research Collection School Of Computing and Information Systems

The reliability of decision-making policies is urgently important today as they have established the fundamentals of many critical applications, such as autonomous driving and robotics. To ensure reliability, there have been a number of research efforts on testing decision-making policies that solve Markov decision processes (MDPs). However, due to the deep neural network (DNN)-based inherit and infinite state space, developing scalable and effective testing frameworks for decision-making policies still remains open and challenging.In this paper, we present an effective testing framework for decision-making policies. The framework adopts a generative diffusion model-based test case generator that can easily adapt to different …

Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The digital economy has brought significant advancements in electronic devices, increasing convenience and comfort in people’s lives. However, this progress has also led to a shorter life cycle for these devices due to rapid advancements in hardware and software technology. As a result, e-waste collection and recycling have become vital for protecting the environment and people’s health. From the operations research perspective, the e-waste collection problem can be modeled as the Heterogeneous Vehicle Routing Problem with Multiple Time Windows (HVRP-MTW). This study proposes a metaheuristic based on the Greedy Randomized Adaptive Search Procedure complemented by Path Relinking (GRASP-PR) to solve …

The Cost Of Cheap Talk: How Campaign Promises And Default Contributions Affect Donation-Based Crowd Funding Success, Tianci Leon Qiu

Dissertations and Theses Collection (Open Access)

Non-profit organisations (NPOs) find it increasingly harder to engage donors and raise funds from the public. Post-pandemic: the emphasis on tactics to raise funds online through donation-based crowdfunding (DCF) platforms has surged in importance for both NPO survival and continued beneficiary aid. However, unlike equity-based crowdfunding platforms where campaign organisers are obligated to provide investors with tangible returns based on funding milestones, NPOs on DCF platforms do not have to adhere to any funding milestones or are beholden to any tangible obligations towards donors. Consequently, NPOs are greatly incentivised to deploy cheap talk – non-binding, unverifiable messages and claims to …

Testsgd: Interpretable Testing Of Neural Networks Against Subtle Group Discrimination, Mengdi Zhang, Jun Sun, Jingyi Wang, Bing Sun

Research Collection School Of Computing and Information Systems

Discrimination has been shown in many machine learning applications, which calls for sufficient fairness testing before their deployment in ethic-relevant domains. One widely concerning type of discrimination, testing against group discrimination, mostly hidden, is much less studied, compared with identifying individual discrimination. In this work, we propose TestSGD, an interpretable testing approach which systematically identifies and measures hidden (which we call ‘subtle’) group discrimination of a neural network characterized by conditions over combinations of the sensitive attributes. Specifically, given a neural network, TestSGD first automatically generates an interpretable rule set which categorizes the input space into two groups. Alongside, TestSGD …

Automated Question Title Reformulation By Mining Modifcation Logs From Stack Overflow, Ke Liu, Xiang Chen, Chunyang Chen, Xiaofei Xie, Zhanqi Cui

Research Collection School Of Computing and Information Systems

In Stack Overflow, developers may not clarify and summarize the critical problems in the question titles due to a lack of domain knowledge or poor writing skills. Previous studies mainly focused on automatically generating the question titles by analyzing the posts’ problem descriptions and code snippets. In this study, we aim to improve title quality from the perspective of question title reformulation and propose a novel approach QETRA motivated by the findings of our formative study. Specifically, by mining modification logs from Stack Overflow, we first extract title reformulation pairs containing the original title and the reformulated title. Then we …

Uncertainty-Adjusted Inductive Matrix Completion With Graph Neural Networks, Petr Kasalicky, Antoine Ledent, Rodrigo Alves

Research Collection School Of Computing and Information Systems

We propose a robust recommender systems model which performs matrix completion and a ratings-wise uncertainty estimation jointly. Whilst the prediction module is purely based on an implicit low-rank assumption imposed via nuclear norm regularization, our loss function is augmented by an uncertainty estimation module which learns an anomaly score for each individual rating via a Graph Neural Network: data points deemed more anomalous by the GNN are downregulated in the loss function used to train the low-rank module. The whole model is trained in an end-to-end fashion, allowing the anomaly detection module to tap on the supervised information available in …

Revisiting The Identification Of The Co-Evolution Of Production And Test Code, Weifeng Sun, Meng Yan, Zhongxin Liu, Xin Xia, Yan Lei, David Lo

Research Collection School Of Computing and Information Systems

Many software processes advocate that the test code should co-evolve with the production code. Prior work usually studies such co-evolution based on production-test co-evolution samples mined from software repositories. A production-test co-evolution sample refers to a pair of a test code change and a production code change where the test code change triggers or is triggered by the production code change. The quality of the mined samples is critical to the reliability of research conclusions. Existing studies mined production-test co-evolution samples based on the following assumption: if a test class and its associated production class change together in one commit, …

Autoconf: Automated Configuration Of Unsupervised Learning Systems Using Metamorphic Testing And Bayesian Optimization, Lwin Khin Shar, Goknil Arda, Erik Johannes Husom, Sagar Sen Sen, Naing Tun Yan, Kisub Kim

Research Collection School Of Computing and Information Systems

Unsupervised learning systems using clustering have gained significant attention for numerous applications due to their unique ability to discover patterns and structures in large unlabeled datasets. However, their effectiveness highly depends on their configuration, which requires domain-specific expertise and often involves numerous manual trials. Specifically, selecting appropriate algorithms and hyperparameters adds to the com- plexity of the configuration process. In this paper, we propose, apply, and assess an automated approach (AutoConf) for config- uring unsupervised learning systems using clustering, leveraging metamorphic testing and Bayesian optimization. Metamorphic testing is utilized to verify the configurations of unsupervised learning systems by applying a …

On Predicting Esg Ratings Using Dynamic Company Networks, Gary Ang, Zhiling Guo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Environmental, social and governance (ESG) considerations play an increasingly important role due to the growing focus on sustainability globally. Entities, such as banks and investors, utilize ESG ratings of companies issued by specialized rating agencies to evaluate ESG risks of companies. The process of assigning ESG ratings by human analysts is however laborious and time intensive. Developing methods to predict ESG ratings could alleviate such challenges, allow ESG ratings to be generated in a more timely manner, cover more companies, and be more accessible. Most works study the effects of ESG ratings on target variables such as stock prices or …

The Need For Growth, Hian Teck Hoon, Edmund S. Phelps, Gylfi Zoega

Research Collection School Of Economics

The falling rate of productivity growth in the West has made equilibrium real rate of interest fall, causing sky-high stock prices and stagnated real wages. Eliminating or reducing impediments to growth—such as rules and regulations that protect vested interests—would lower the burden of debt, make it easier to reduce greenhouse gas emissions and increase political stability. There are also measures that strengthen institutions that encourage innovations; a healthy financial system, well-protected property rights and values that emphasize self-reliance, independence and good work ethics. While special interests are more entrenched in some developed countries than others, there is hope that current …

Option Market Maker Hedging And Stock Market Liquidity, James O′Donovan, Gloria Yang Yu, Jinyuan Zhang

Research Collection Lee Kong Chian School Of Business

This paper demonstrates that option market maker hedging impacts the liquidity of underlying stocks. Options contracts have zero net supply, and option market makers engage in delta hedging to manage the risk of their net imbalances, unlike option end-users. Consequently, when option market makers hold a net short (long) position, their dynamic hedging demands liquidity from (or supplies liquidity to) the underlying stock, leading to market destabilization (or stabilization). Leveraging proprietary option exchange data that categorizes option trading by trader type, we document this effect and show that it is stronger for stocks where liquidity supply is expected to be …

The Devil Is In The Tails: How Long-Tailed Code Distributions Impact Large Language Models, Xin Zhou, Kisub Kim, Bowen Xu, Jiakun Liu, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Learning-based techniques, especially advanced Large Language Models (LLMs) for code, have gained considerable popularity in various software engineering (SE) tasks. However, most existing works focus on designing better learning-based models and pay less attention to the properties of datasets. Learning-based models, including popular LLMs for code, heavily rely on data, and the data's properties (e.g., data distribution) could significantly affect their behavior. We conducted an exploratory study on the distribution of SE data and found that such data usually follows a skewed distribution (i.e., long-tailed distribution) where a small number of classes have an extensive collection of samples, while a …

Real: A Representative Error-Driven Approach For Active Learning, Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du

Research Collection School Of Computing and Information Systems

Given a limited labeling budget, active learning (al) aims to sample the most informative instances from an unlabeled pool to acquire labels for subsequent model training. To achieve this, al typically measures the informativeness of unlabeled instances based on uncertainty and diversity. However, it does not consider erroneous instances with their neighborhood error density, which have great potential to improve the model performance. To address this limitation, we propose Real, a novel approach to select data instances with Representative Errors for Active Learning. It identifies minority predictions as pseudo errors within a cluster and allocates an adaptive sampling budget for …

Are We Ready To Embrace Generative Ai For Software Q&A?, Bowen Xu, Thanh-Dat Nguyen, Thanh Le-Cong, Thong Hoang, Jiakun Liu, Kisub Kim, Chen Gong, Changan Niu, Chenyu Wang, David Lo, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Overflow after only 6 days from its release. The main reason provided by the official Stack Overflow is that the answers generated by ChatGPT are of low quality. To verify this, we conduct a comparative evaluation of human-written and ChatGPT-generated answers. Our methodology employs both automatic comparison and a manual study. Our results suggest that human-written and ChatGPT-generated answers are semantically similar, however, human-written answers outperform ChatGPT-generated ones consistently across multiple aspects, …

Auditor Materiality Threshold And Audit Quality: Evidence From The Revised Isa 700 In The United Kingdom, Beng Wee Goh, Kiat Bee Jimmy Lee, Dan Li, Na Li, Muzhi Wang

Research Collection School Of Accountancy

Using a broad sample of U.K. firms that are required to disclose auditor materiality thresholds under the International Standards on Auditing (U.K. and Ireland) 700, we examine whether the auditor materiality threshold is associated with audit quality. We document that a lower materiality threshold is associated with higher audit quality, as measured by lower absolute discretionary accruals, higher accruals quality, and a lower propensity to just meet or beat analysts’ earnings expectations. We also find some evidence that the negative association between the materiality threshold and audit quality is attenuated when the audit committee is more effective and when the …

Acceptance Of Communication Technology, Emotional Support And Subjective Well-Being For Chinese Older Adults Living Alone During Covid-19: A Moderated Mediation Model, Ze Ling Nai, Woan Shin Tan, William Tov

Research Collection School of Social Sciences

Stringent social distancing measures implemented to control the spread of COVID-19 affected older adults living alone by limiting their social interaction beyond their households. During these restrictions, interactions beyond the household could be facilitated by communication technology (CT) such as voice calls, instant messages. Our study provides evidence on how CT acceptance could influence the emotional support and in turn, subjective well-being (SWB) of older adults living alone. We did a cross-sectional survey with 293 community-dwelling Chinese older adults. Participants were surveyed from September to November 2020 and had completed measures on CT acceptance (competency), emotional support, and SWB. PROCESS …

Chinese Visions Of Self And Other: The International Politics Of Noses, William A. Callahan

Research Collection School of Social Sciences

How does China view the world? While much has been written about how China's international relations are best seen as intercultural relations that do not exclude the Other, this article examines how self/Other relations are visualized in terms of the human face in China, in particular through iconic images that construct the Chinese self with and against foreigners with large noses. It employs interpretivist methods to consider the interplay of social relations and international relations in order to see how ‘external appearance’ and ‘external relations’ inform each other in Chinese theory and practice. It mobilizes the classical Chinese concept ‘deep-set …

Fine-Grained In-Context Permission Classification For Android Apps Using Control-Flow Graph Embedding, Vikas Kumar Malviya, Naing Tun Yan, Chee Wei Leow, Ailys Xynyn Tee, Lwin Khin Shar, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Android is the most popular operating system for mobile devices nowadays. Permissions are a very important part of Android security architecture. Apps frequently need the users’ permission, but many of them only ask for it once—when the user uses the app for the first time—and then they keep and abuse the given permissions. Longing to enhance Android permission security and users’ private data protection is the driving factor behind our approach to explore fine-grained contextsensitive permission usage analysis and thereby identify misuses in Android apps. In this work, we propose an approach for classifying the fine-grained permission uses for each …

Housing Fever In Australia 2020-23: Insights From An Econometric Thermometer, Shuping Shi, Peter C. B. Phillips

Research Collection School Of Economics

Australian housing markets experienced widespread and, in some cases, extraordinary growth in prices between 2020 and 2023. Using recently developed methodology that accounts for fundamental economic drivers, we assess the existence and degree of speculative behaviour, as well as the timing of exuberance and downturns in these markets. Our findings indicate that speculative behaviour was indeed present in six of the eight capital cities at some time over the period studied. The sequence of events in this nation-wide housing bubble began in the Brisbane market and concluded in Melbourne, Canberra, and Hobart following the interest rate rise implemented by the …

Threshold Attribute-Based Credentials With Redactable Signature, Rui Shi, Huamin Feng, Yang Yang, Feng Yuan, Yingjiu Li, Hwee Hwa Pang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Threshold attribute-based credentials are suitable for decentralized systems such as blockchains as such systems generally assume that authenticity, confidentiality, and availability can still be guaranteed in the presence of a threshold number of dishonest or faulty nodes. Coconut (NDSS'19) was the first selective disclosure attribute-based credentials scheme supporting threshold issuance. However, it does not support threshold tracing of user identities and threshold revocation of user credentials, which is desired for internal governance such as identity management, data auditing, and accountability. The communication and computation complexities of Coconut for verifying credentials are linear in the number of each user's attributes and …

Endwatch: A Practical Method For Detecting Non-Termination In Real-World Software, Yao Zhang, Xiaofei Xie, Yi Li, Sen Chen, Cen Zhang, Xiaohong Li

Research Collection School Of Computing and Information Systems

Detecting non-termination is crucial for ensuring program correctness and security, such as preventing denial-of-service attacks. While termination analysis has been studied for many years, existing methods have limited scalability and are only effective on small programs. To address this issue, we propose a practical termination checking technique, called EndWatch, for detecting non-termination through testing. Specifically, we introduce two methods to generate non-termination oracles based on checking state revisits, i.e., if the program returns to a previously visited state at the same program location, it does not terminate. The non-termination oracles can be incorporated into testing tools (e.g., AFL used in …

Rosas: Deep Semi-Supervised Anomaly Detection With Contamination-Resilient Continuous Supervision, Hongzuo Xu, Yijie Wang, Guansong Pang, Songlei Jian, Ning Liu, Yongjun Wang

Research Collection School Of Computing and Information Systems

Semi-supervised anomaly detection methods leverage a few anomaly examples to yield drastically improved performance compared to unsupervised models. However, they still suffer from two limitations: 1) unlabeled anomalies (i.e., anomaly contamination) may mislead the learning process when all the unlabeled data are employed as inliers for model training; 2) only discrete supervision information (such as binary or ordinal data labels) is exploited, which leads to suboptimal learning of anomaly scores that essentially take on a continuous distribution. Therefore, this paper proposes a novel semi-supervised anomaly detection method, which devises contamination-resilient continuous supervisory signals. Specifically, we propose a mass interpolation method …

Hercules: Boosting The Performance Of Privacy-Preserving Federated Learning, Guowen Xu, Xingshuo Han, Shengmin Xu, Tianwei Zhang, Hongwei Li, Xinyi Huang, Robert H. Deng

Research Collection School Of Computing and Information Systems

In this paper, we address the problem of privacy-preserving federated neural network training with N users. We present Hercules, an efficient and high-precision training framework that can tolerate collusion of up to N−1 users. Hercules follows the POSEIDON framework proposed by Sav et al. (NDSS’21), but makes a qualitative leap in performance with the following contributions: (i) we design a novel parallel homomorphic computation method for matrix operations, which enables fast Single Instruction and Multiple Data (SIMD) operations over ciphertexts. For the multiplication of two h×h dimensional matrices, our method reduces the computation complexity from O(h3) to O(h) . This …

Arduinoprog: Towards Automating Arduino Programming, Imam Nur Bani Yusuf, Diyanah Binte Abdul Jamal, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Writing code for Arduino poses unique challenges. A developer 1) needs hardware-specific knowledge about the interface configuration between the Arduino controller and the I/Ohardware, 2) identifies a suitable driver library for the I/O hardware, and 3) follows certain usage patterns of the driver library in order to use them properly. In this work, based on a study of real-world user queries posted in the Arduino forum, we propose ArduinoProg to address such challenges. ArduinoProg consists of three components, i.e., Library Retriever, Configuration Classifier, and Pattern Generator. Given a query, Library Retriever retrieves library names relevant to the I/O hardware identified …

Rethinking Acting In Concert: Activist Esg Stewardship Is Shareholder Democracy, Dan W. Puchniak, Umakanth Varottil

Research Collection Yong Pung How School Of Law

In May 2021, Engine No. 1, an investment fund, was lauded by the responsible investment community for successfully placing three dissident independent directors on ExxonMobil’s board. It achieved this by being a catalyst for institutional investors to become backers of environmental shareholder activism. The unprecedented success of Engine No. 1’s campaign has spurred calls for a new, more sustained, activist engagement model by institutional investors, now known as “activist stewardship”.However, there is a significant legal hurdle that has been almost entirely overlooked by those calling for this new approach for institutional investors to become activist stewards: acting in concert rules. …

A Non-Contractual Approach To Smart Contracts, Florian Gamper

Research Collection Yong Pung How School Of Law

This article adds to the debate on what, legally speaking, smart contracts are and what they should be. Currently, much of this debate focuses on the relationship between smart contracts and legal contracts, overlooking that other legal categories may also be appropriate. This article suggests that the concept of abandonment can be fruitfully applied to smart contracts. Using the concept of abandonment has the advantage of allowing smart contracts, as close as legally possible, to be utilized as machines (or using the terminology suggested by Vitalik Buterin, founder of Etherium, as a ‘persistent script’). It would also make other issues, …