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Tax Challenges In Debt Financing Involving Digital Tokens, Vincent Ooi Sep 2022

Tax Challenges In Debt Financing Involving Digital Tokens, Vincent Ooi

Research Collection Yong Pung How School Of Law

When digital tokens are used in debt finance, one cannot assume that the same orthodox tax treatment will apply. The highly specific nature of tax provisions means that they may apply very differently once digital tokens rather than fiat currency are involved. Through a case study of Singapore law, this article shows that if debt finance transactions involving digital tokens are not carefully structured, there may be severe tax consequences, including the inability to deduct borrowing costs or benefit from common tax incentives, and the possible incurrence of additional tax liabilities. This article submits that, under Singapore tax law, it …

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Skbi Big 5 Survey 2022 August, Singapore Management University Aug 2022

Skbi Big 5 Survey 2022 August, Singapore Management University

Sim Kee Boon Institute for Financial Economics

The latest survey results on the largest five economies (Big5) were revised markedly relative to the prior release (pre-Russia-Ukraine conflict), generally indicating weaker growth and higher inflation coupled with incremental ambiguity on the policy front.

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International Asset Pricing With Strategic Business Groups, Massimo Massa, Hong Zhang, Hong Zhang Aug 2022

International Asset Pricing With Strategic Business Groups, Massimo Massa, Hong Zhang, Hong Zhang

Research Collection Lee Kong Chian School Of Business

Firms in global markets often belong to business groups. We argue that this feature can have a profound influence on international asset pricing. In bad times, business groups may strategically reallocate risk across affiliated firms to protect core “central firms.” This strategic behavior induces co-movement among central firms, creating a new intertemporal risk factor. Based on a novel data set of worldwide ownership for 2002–2012, we find that central firms are better protected in bad times and that they earn relatively lower expected returns. Moreover, a centrality factor augments traditional models in explaining the cross section of international stock returns.

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Holistic Combination Of Structural And Textual Code Information For Context Based Api Recommendation, Chi Chen, Xin Peng, Zhengchang Xing, Jun Sun, Xin Wang, Yifan Zhao, Wenyun Zhao Aug 2022

Holistic Combination Of Structural And Textual Code Information For Context Based Api Recommendation, Chi Chen, Xin Peng, Zhengchang Xing, Jun Sun, Xin Wang, Yifan Zhao, Wenyun Zhao

Research Collection School Of Computing and Information Systems

Context based API recommendation is an important way to help developers find the needed APIs effectively and efficiently. For effective API recommendation, we need not only a joint view of both structural and textual code information, but also a holistic view of correlated API usage in control and data flow graph as a whole. Unfortunately, existing API recommendation methods exploit structural or textual code information separately. In this work, we propose a novel API recommendation approach called APIRec-CST (API Recommendation by Combining Structural and Textual code information). APIRec-CST is a deep learning model that combines the API usage with the …

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The Effects Of Csr Reputation And Csr Crisis Response Strategy On Investor Judgments, Clarence Goh Aug 2022

The Effects Of Csr Reputation And Csr Crisis Response Strategy On Investor Judgments, Clarence Goh

Research Collection School Of Accountancy

I use a controlled experiment to examine, in the context of CSR crises, whether investors’ investment judgments are influenced by a firm’s CSR reputation and CSR crisis response strategy. I find that for good CSR reputation firms, the use of a rebuild or deny crisis response strategy does not lead to improvements in investment judgments. However, for bad CSR reputation firms, the use of a deny response strategy leads to improvements in investment judgments while the use of a rebuild strategy does not.

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Verifying Neural Networks Against Backdoor Attacks, Long Hong Pham, Jun Sun Aug 2022

Verifying Neural Networks Against Backdoor Attacks, Long Hong Pham, Jun Sun

Research Collection School Of Computing and Information Systems

Neural networks have achieved state-of-the-art performance in solving many problems, including many applications in safety/security-critical systems. Researchers also discovered multiple security issues associated with neural networks. One of them is backdoor attacks, i.e., a neural network may be embedded with a backdoor such that a target output is almost always generated in the presence of a trigger. Existing defense approaches mostly focus on detecting whether a neural network is ‘backdoored’ based on heuristics, e.g., activation patterns. To the best of our knowledge, the only line of work which certifies the absence of backdoor is based on randomized smoothing, which is …

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The Cryptocurrency Participation Puzzle, Ran Duchin, David H. Solomon, Jun Tu, Xi Wang Aug 2022

The Cryptocurrency Participation Puzzle, Ran Duchin, David H. Solomon, Jun Tu, Xi Wang

Research Collection Lee Kong Chian School Of Business

We show that ongoing zero portfolio weights in cryptocurrency are surprisingly difficult to generate in a standard Bayesian portfolio theory framework. With ten years of prior data, equity market investors would need very pessimistic priors on mean returns to justify never having bought cryptocurrency: -10.6% per month for Bitcoin, and -19.6% per month for a diversified portfolio of cryptocurrencies. Moreover, most priors that involve never purchasing cryptocurrency imply that investors should short cryptocurrency. Optimal absolute weights are generally small but non-trivial (1-5%), frequently positive, and fairly smooth despite returns being volatile. Under a wide range of priors, the certainty equivalent …

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Resumable Zero-Knowledge For Circuits From Symmetric Key Primitives, Handong Zhang, Puwen Wei, Haiyang Xue, Yi Deng, Jinsong Li, Wei Wang, Guoxiao Liu Aug 2022

Resumable Zero-Knowledge For Circuits From Symmetric Key Primitives, Handong Zhang, Puwen Wei, Haiyang Xue, Yi Deng, Jinsong Li, Wei Wang, Guoxiao Liu

Research Collection School Of Computing and Information Systems

Consider the scenario that the prover and the verifier perform the zero-knowledge (ZK) proof protocol for the same statement multiple times sequentially, where each proof is modeled as a session. We focus on the problem of how to resume a ZK proof efficiently in such scenario. We introduce a new primitive called resumable honest verifier zero-knowledge proof of knowledge (resumable HVZKPoK) and propose a general construction of the resumable HVZKPoK for circuits based on the “MPC-in-the-head" paradigm, where the complexity of the resumed session is less than that of the original ZK proofs. To ensure the knowledge soundness for the …

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Self-Checking Deep Neural Networks For Anomalies And Adversaries In Deployment, Yan Xiao, Ivan Beschastnikh, Yun Lin, Rajdeep Singh Hundal, Xiaofei Xie, David S. Rosenblum, Jin Song Dong Aug 2022

Self-Checking Deep Neural Networks For Anomalies And Adversaries In Deployment, Yan Xiao, Ivan Beschastnikh, Yun Lin, Rajdeep Singh Hundal, Xiaofei Xie, David S. Rosenblum, Jin Song Dong

Research Collection School Of Computing and Information Systems

Deep Neural Networks (DNNs) have been widely adopted, yet DNN models are surprisingly unreliable, which raises significant concerns about their use in critical domains. In this work, we propose that runtime DNN mistakes can be quickly detected and properly dealt with in deployment, especially in settings like self-driving vehicles. Just as software engineering (SE) community has developed effective mechanisms and techniques to monitor and check programmed components, our previous work, SelfChecker, is designed to monitor and correct DNN predictions given unintended abnormal test data. SelfChecker triggers an alarm if the decisions given by the internal layer features of the model …

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Legion: Massively Composing Rankers For Improved Bug Localization At Adobe, Darryl Jarman, Jeffrey Berry, Riley Smith, Ferdian Thung, David Lo Aug 2022

Legion: Massively Composing Rankers For Improved Bug Localization At Adobe, Darryl Jarman, Jeffrey Berry, Riley Smith, Ferdian Thung, David Lo

Research Collection School Of Computing and Information Systems

Studies have estimated that, in industrial settings, developers spend between 30 and 90 percent of their time fixing bugs. As such, tools that assist in identifying the location of bugs provide value by reducing debugging costs. One such tool is BugLocator. This study initially aimed to determine if developers working on the Adobe Analytics product could use BugLocator. The initial results show that BugLocator achieves a similar accuracy on five of seven Adobe Analytics repositories and on open-source projects. However, these results do not meet the minimum applicability requirement deemed necessary by Adobe Analytics developers prior to possible adoption. Thus, …

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Trajectory Optimization For Safe Navigation In Maritime Traffic Using Historical Data, Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar Aug 2022

Trajectory Optimization For Safe Navigation In Maritime Traffic Using Historical Data, Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar

Research Collection School Of Computing and Information Systems

Increasing maritime trade often results in congestion in busy ports, thereby necessitating planning methods to avoid close quarter risky situations among vessels. Rapid digitization and automation of port operations and vessel navigation provide unique opportunities for significantly improving navigation safety. Our key contributions are as follows. First, given a set of future candidate trajectories for vessels in a traffic hotspot zone, we develop a multiagent trajectory optimization method to choose trajectories that result in the best overall close quarter risk reduction. Our novel MILP-based optimization method is more than an order-of-magnitude faster than a standard MILP for this problem, and …

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Mobile Health With Head-Worn Devices: Challenges And Opportunities, Andrea Ferlini, Dong Ma, Lorena Qendro, Cecilia Mascolo Aug 2022

Mobile Health With Head-Worn Devices: Challenges And Opportunities, Andrea Ferlini, Dong Ma, Lorena Qendro, Cecilia Mascolo

Research Collection School Of Computing and Information Systems

Monitoring human behavior and health status using mobile devices, a.k.a. Mobile Health, has gained increasing attention from both academia and industry in recent years. It allows imperceptible health tracking from the users and remote health management from the healthcare service providers. Headworn devices, such as earbuds, glasses, and BCIs (Brain Computer Interfaces), exhibit great potential for mobile health due to their advantageous wearing position, the human head, which is motion-resilient and full of human bio-signals. Although initial attempts have been conducted for different healthcare applications with head-worn devices, this fast-growing area is still under-explored and retains great promises. With this …

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Destress: Computation-Optimal And Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization, Boyue Li, Zhize Li, Yuejie Chi Aug 2022

Destress: Computation-Optimal And Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization, Boyue Li, Zhize Li, Yuejie Chi

Research Collection School Of Computing and Information Systems

Emerging applications in multiagent environments such as internet-of-things, networked sensing, autonomous systems, and federated learning, call for decentralized algorithms for finite-sum optimizations that are resource efficient in terms of both computation and communication. In this paper, we consider the prototypical setting where the agents work collaboratively to minimize the sum of local loss functions by only communicating with their neighbors over a predetermined network topology. We develop a new algorithm, called DEcentralized STochastic REcurSive gradient methodS (DESTRESS) for nonconvex finite-sum optimization, which matches the optimal incremental first-order oracle complexity of centralized algorithms for finding first-order stationary points, while maintaining communication …

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Key Factors In The Strategic Transformation Of Traditional Food Enterprises In China, Hui Ching Lau Aug 2022

Key Factors In The Strategic Transformation Of Traditional Food Enterprises In China, Hui Ching Lau

Dissertations and Theses Collection (Open Access)

The food industry is an important industry for China’s social development and one of the pillar industries of China's industrial economy. With the development of China’s urbanization, the victory of building a moderately prosperous society in all respects, and the continuous improvement of people’s living standards, consumer demand has become diversified and rationalized from “seeking for fullness” to “seeking for good”. In this context, the supplier of food products, that is, food companies, has become more competitive in market segments. With the continuous improvement of China's market openness, many top international food companies have flooded into the food industry. Coupled …

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Assertion, Stakes And Expected Blameworthiness: An Insensitive Invariantist Solution To The Bank Cases, Brandon Yip Aug 2022

Assertion, Stakes And Expected Blameworthiness: An Insensitive Invariantist Solution To The Bank Cases, Brandon Yip

Research Collection School of Social Sciences

Contextualists and Subject Sensitive Invariantists often cite the knowledge norm of assertion as part of their argument. They claim that the knowledge norms in conjunction with our intuitions about when a subject is properly asserting in low or high stakes contexts provides strong evidence that what counts as knowledge depends on practical factors. In this paper, I present new data to suggest they are mistaken in the way they think about cases involving high and low stakes and I show how insensitive invariantists can explain the data. I exploit recent work done on the distinction between flouting a norm and …

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The Exchange Rate System Reform In China: Some Important Results, Paul S. L. Yip, Yiu Kuen Tse, Yingjie Dong Aug 2022

The Exchange Rate System Reform In China: Some Important Results, Paul S. L. Yip, Yiu Kuen Tse, Yingjie Dong

Research Collection School Of Economics

We provide a review and empirical study on the exchange rate system reform in China. In the initial stage of the reform the Chinese central bank PBoC's implicit promise of gradual appreciation helped to contain the appreciation rate and volatility of the renminbi. Subsequently, under US pressure for faster appreciation and hence the PBoC's moderate violation of the implicit promise, there was a significant rise in the appreciation rate and the volatility of the renminbi. The moderate violation deteriorated further, forming a vicious cycle of speculative flows and faster exchange rate changes. Upon the onset of the global financial crisis …

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Investigating Toxicity Changes Of Cross-Community Redditors From 2 Billion Posts And Comments, Hind Almerekhi, Haewoon Kwak, Bernard J. Jansen Aug 2022

Investigating Toxicity Changes Of Cross-Community Redditors From 2 Billion Posts And Comments, Hind Almerekhi, Haewoon Kwak, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

This research investigates changes in online behavior of users who publish in multiple communities on Reddit by measuring their toxicity at two levels. With the aid of crowdsourcing, we built a labeled dataset of 10,083 Reddit comments, then used the dataset to train and fine-tune a Bidirectional Encoder Representations from Transformers (BERT) neural network model. The model predicted the toxicity levels of 87,376,912 posts from 577,835 users and 2,205,581,786 comments from 890,913 users on Reddit over 16 years, from 2005 to 2020. This study utilized the toxicity levels of user content to identify toxicity changes by the user within the …

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Integrated Assessment Of Urban Overheating Impacts On Human Life, N. Nazarian, E. S. Krayenhoff, B. Bechtel, D. M. Hondula, R. Paolini, J. Vanos, T. Cheung, Winston T. L. Chow, Et Al Aug 2022

Integrated Assessment Of Urban Overheating Impacts On Human Life, N. Nazarian, E. S. Krayenhoff, B. Bechtel, D. M. Hondula, R. Paolini, J. Vanos, T. Cheung, Winston T. L. Chow, Et Al

Research Collection College of Integrative Studies

Urban overheating, driven by global climate change and urban development, is a major contemporary challenge that substantially impacts urban livability and sustainability. Overheating represents a multifaceted threat to the well-being, performance, and health of individuals as well as the energy efficiency and economy of cities, and it is influenced by complex interactions between building, city, and global scale climates. In recent decades, extensive discipline-specific research has characterized urban heat and assessed its implications on human life, including ongoing efforts to bridge neighboring disciplines. The research horizon now encompasses complex problems involving a wide range of disciplines, and therefore comprehensive and …

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Throwing Stones In Glass Houses: Protecting Privacy Under The Law Of Nuisance, Cheng Lim Saw, Joon Wei Aaron Yoong Aug 2022

Throwing Stones In Glass Houses: Protecting Privacy Under The Law Of Nuisance, Cheng Lim Saw, Joon Wei Aaron Yoong

Research Collection Yong Pung How School Of Law

The limits of the law of nuisance were recently tested in the controversial decisions of Fearn v Tate Gallery Board of Trustees, both before the UK High Court and UK Court of Appeal. Against the backdrop of these decisions, this article argues that the tort of private nuisance can indeed, in appropriate cases, protect against invasions of privacy caused by overlooking – all within the present framework and ambit of the action. It is also proposed that a communitarian approach be adopted in fashioning the appropriate remedy for actions founded in nuisance.

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Did Twitter Deliberately Mislead Elon Musk In His Acquisition Bid?, Mark Humphery-Jenner Jul 2022

Did Twitter Deliberately Mislead Elon Musk In His Acquisition Bid?, Mark Humphery-Jenner

Perspectives@SMU

Elon Musk has officially ended his bid to acquire Twitter on the grounds that it misled the market in its disclosures, writes UNSW Business School's Mark Humphery-Jenner

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Gamifying An Assessment Method: What Signals Are Organizations Sending To Applicants?, Konstantina Georgiou, Filip Lievens Jul 2022

Gamifying An Assessment Method: What Signals Are Organizations Sending To Applicants?, Konstantina Georgiou, Filip Lievens

Research Collection Lee Kong Chian School Of Business

Purpose: The paper aims to expand the authors' knowledge on gamification and the signals sent on behalf of the organization when gamified assessments are used. The authors examine the mechanisms through which the use of gamification into an assessment method may increase the attractiveness of an organization as a prospective employer. Design/methodology/approach: The first study examines, following a longitudinal design, the signals that an organization sends to applicants about the organization's symbolic traits (e.g. innovativeness), through the characteristics of a gamified assessment, in terms of enjoyment and flow and impact on organizational attractiveness. Upon clarifying this mechanism, the second study …

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Learning To Ask Critical Questions For Assisting Product Search, Zixuan Li, Lizi Liao, Tat-Seng Chua Jul 2022

Learning To Ask Critical Questions For Assisting Product Search, Zixuan Li, Lizi Liao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Product search plays an essential role in eCommerce. It was treated as a special type of information retrieval problem. Most existing works make use of historical data to improve the search performance, which do not take the opportunity to ask for user’s current interest directly. Some session-aware methods take the user’s clicks within the session as implicit feedback, but it is still just a guess on user’s preference. To address this problem, recent conversational or question-based search models interact with users directly for understanding the user’s interest explicitly. However, most users do not have a clear picture on what to …

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Self-Guided Learning To Denoise For Robust Recommendation, Yunjun Gao, Yuntao Du, Yujia Hu, Lu Chen, Xinjun Zhu, Ziquan Fang, Baihua Zheng Jul 2022

Self-Guided Learning To Denoise For Robust Recommendation, Yunjun Gao, Yuntao Du, Yujia Hu, Lu Chen, Xinjun Zhu, Ziquan Fang, Baihua Zheng

Research Collection School Of Computing and Information Systems

The ubiquity of implicit feedback makes them the default choice to build modern recommender systems. Generally speaking, observed interactions are considered as positive samples, while unobserved interactions are considered as negative ones. However, implicit feedback is inherently noisy because of the ubiquitous presence of noisy-positive and noisy-negative interactions. Recently, some studies have noticed the importance of denoising implicit feedback for recommendations, and enhanced the robustness of recommendation models to some extent. Nonetheless, they typically fail to (1) capture the hard yet clean interactions for learning comprehensive user preference, and (2) provide a universal denoising solution that can be applied to …

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Designing Flipped Learning Activities For Beginner Programming Course, Benjamin Gan, Eng Lieh Ouh Jul 2022

Designing Flipped Learning Activities For Beginner Programming Course, Benjamin Gan, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

This study focuses on designing flipped classroom learning activities across pre-class problem-based exercises; with in-class active discussions and practical problem-solving sessions; and follow up with postclass problem-based labs and assessments. We evaluate the effectiveness of our learning activities based on student surveys, course feedback, grades, and teacher feedback for a beginner programming course with non-IS students. We describe detail programming learning activities with comparisons to existing practices based on related work. Our findings are that majority of students (86%) agreed with flipped classroom, but teachers should be aware of the 14% who disagreed and cater for them. Teachers should avoid …

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Gbgallery: A Benchmark And Framework For Game Testing, Zhuo Li, Yuechen Wu, Lei Ma, Xiaofei Xie, Yingfeng Chen, Changjie Fan Jul 2022

Gbgallery: A Benchmark And Framework For Game Testing, Zhuo Li, Yuechen Wu, Lei Ma, Xiaofei Xie, Yingfeng Chen, Changjie Fan

Research Collection School Of Computing and Information Systems

Software bug database and benchmark are the wheels of advancing automated software testing. In practice, real bugs often occur sparsely relative to the amount of software code, the extraction and curation of which are quite labor-intensive but can be essential to facilitate the innovation of testing techniques. Over the past decade, several milestones have been made to construct bug databases, pushing the progress of automated software testing research. However, up to the present, it still lacks a real bug database and benchmark for game software, making current game testing research mostly stagnant. The missing of bug database and framework greatly …

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Structured And Natural Responses Co-Generation For Conversational Search, Chenchen Ye, Lizi Liao, Fuli Feng, Wei Ji, Tat-Seng Chua Jul 2022

Structured And Natural Responses Co-Generation For Conversational Search, Chenchen Ye, Lizi Liao, Fuli Feng, Wei Ji, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Generating fluent and informative natural responses while maintaining representative internal states for search optimization is critical for conversational search systems. Existing approaches either 1) predict structured dialog acts first and then generate natural response; or 2) map conversation context to natural responses directly in an end-to-end manner. Both kinds of approaches have shortcomings. The former suffers from error accumulation while the semantic associations between structured acts and natural responses are confined in single direction. The latter emphasizes generating natural responses but fails to predict structured acts. Therefore, we propose a neural co-generation model that generates the two concurrently. The key …

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Test Mimicry To Assess The Exploitability Of Library Vulnerabilities, Hong Jin Kang, Truong Giang Nguyen, Bach Le, Corina S. Pasareanu, David Lo Jul 2022

Test Mimicry To Assess The Exploitability Of Library Vulnerabilities, Hong Jin Kang, Truong Giang Nguyen, Bach Le, Corina S. Pasareanu, David Lo

Research Collection School Of Computing and Information Systems

Modern software engineering projects often depend on open-source software libraries, rendering them vulnerable to potential security issues in these libraries. Developers of client projects have to stay alert of security threats in the software dependencies. While there are existing tools that allow developers to assess if a library vulnerability is reachable from a project, they face limitations. Call graphonly approaches may produce false alarms as the client project may not use the vulnerable code in a way that triggers the vulnerability, while test generation-based approaches faces difficulties in overcoming the intrinsic complexity of exploiting a vulnerability, where extensive domain knowledge …

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Using Constraint Programming And Graph Representation Learning For Generating Interpretable Cloud Security Policies, Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar Jul 2022

Using Constraint Programming And Graph Representation Learning For Generating Interpretable Cloud Security Policies, Mikhail Kazdagli, Mohit Tiwari, Akshat Kumar

Research Collection School Of Computing and Information Systems

Modern software systems rely on mining insights from business sensitive data stored in public clouds. A data breach usually incurs signifcant (monetary) loss for a commercial organization. Conceptually, cloud security heavily relies on Identity Access Management (IAM) policies that IT admins need to properly confgure and periodically update. Security negligence and human errors often lead to misconfguring IAM policies which may open a backdoor for attackers. To address these challenges, frst, we develop a novel framework that encodes generating optimal IAM policies using constraint programming (CP). We identify reducing dormant permissions of cloud users as an optimality criterion, which intuitively …

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Order Constraints In Optimal Transport, Fabian Lim, Laura Wynter, Shiau Hong Lim Jul 2022

Order Constraints In Optimal Transport, Fabian Lim, Laura Wynter, Shiau Hong Lim

Research Collection School Of Computing and Information Systems

Optimal transport is a framework for comparing measures whereby a cost is incurred for transporting one measure to another. Recent works have aimed to improve optimal transport plans through the introduction of various forms of structure. We introduce novel order constraints into the optimal transport formulation to allow for the incorporation of structure. We define an efficient method for obtaining explainable solutions to the new formulation that scales far better than standard approaches. The theoretical properties of the method are provided. We demonstrate experimentally that order constraints improve explainability using the e-SNLI (Stanford Natural Language Inference) dataset that includes human-annotated …

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Data Quality Matters: A Case Study On Data Label Correctness For Security Bug Report Prediction, Xiaoxue Wu, Wei Zheng, Xin Xia, David Lo Jul 2022

Data Quality Matters: A Case Study On Data Label Correctness For Security Bug Report Prediction, Xiaoxue Wu, Wei Zheng, Xin Xia, David Lo

Research Collection School Of Computing and Information Systems

In the research of mining software repositories, we need to label a large amount of data to construct a predictive model. The correctness of the labels will affect the performance of a model substantially. However, limited studies have been performed to investigate the impact of mislabeled instances on a predictive model. To bridge the gap, in this article, we perform a case study on the security bug report (SBR) prediction. We found five publicly available datasets for SBR prediction contains many mislabeled instances, which lead to the poor performance of SBR prediction models of recent studies (e.g., the work of …

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