Digital Commons Network^™

The Singapore Global Restructuring Initiative, Aurelio Gurrea-Martinez, Smu Office Of Research

Research@SMU Infographics

The SMU School of Law has recently launched the Singapore Global Restructuring Initiative (SGRI) with the support of Ministry of Law. Led by Assistant Professor Aurelio Gurrea-Martinez, the SGRI is working on a variety of projects that seek to promote a better understanding of corporate insolvency laws.

Walls Have Ears: Eavesdropping User Behaviors Via Graphics-Interrupt-Based Side Channel, Haoyu Ma, Jianwen Tian, Debin Gao, Jia Chunfu

Research Collection School Of Computing and Information Systems

Graphics Processing Units (GPUs) are now playing a vital role in many devices and systems including computing devices, data centers, and clouds, making them the next target of side-channel attacks. Unlike those targeting CPUs, existing side-channel attacks on GPUs exploited vulnerabilities exposed by application interfaces like OpenGL and CUDA, which can be easily mitigated with software patches. In this paper, we investigate the lower-level and native interface between GPUs and CPUs, i.e., the graphics interrupts, and evaluate the side channel they expose. Being an intrinsic profile in the communication between a GPU and a CPU, the pattern of graphics interrupts …

Heterogeneous Univariate Outlier Ensembles In Multidimensional Data, Guansong Pang, Longbing Cao

Research Collection School Of Computing and Information Systems

In outlier detection, recent major research has shifted from developing univariate methods to multivariate methods due to the rapid growth of multidimensional data. However, one typical issue of this paradigm shift is that many multidimensional data often mainly contains univariate outliers, in which many features are actually irrelevant. In such cases, multivariate methods are ineffective in identifying such outliers due to the potential biases and the curse of dimensionality brought by irrelevant features. Those univariate outliers might be well detected by applying univariate outlier detectors in individually relevant features. However, it is very challenging to choose a right univariate detector …

Deep Multi-Task Learning For Depression Detection And Prediction In Longitudinal Data, Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Depression is among the most prevalent mental disorders, affecting millions of people of all ages globally. Machine learning techniques have shown effective in enabling automated detection and prediction of depression for early intervention and treatment. However, they are challenged by the relative scarcity of instances of depression in the data. In this work we introduce a novel deep multi-task recurrent neural network to tackle this challenge, in which depression classification is jointly optimized with two auxiliary tasks, namely one-class metric learning and anomaly ranking. The auxiliary tasks introduce an inductive bias that improves the classification model's generalizability on small depression …

The Future Is Urban: The Progressive Renaissance Of The City In Eu Law, De Maartje Visser

Research Collection Yong Pung How School Of Law

For much of the European integration process, local authorities have been on the legal margins. Yet many amongst this group, and cities in particular, consider themselves as important players in realising the Union’s overarching policy objectives. This view is slowly but surely fi nding traction with the EU’s political institutions. This article suggests that the future architecture of the European Union’s (EU’s) operating system will evince a rapprochement between the socio-economic clout of local authorities, notably cities, and their legal-political recognition at Union level. It further suggests that there is room for greater conceptual clarity along two lines when interrogating …

The Future Of Reorganization Procedures In The Era Of Pre-Insolvency Law, Aurelio Gurrea-Martinez

Research Collection Yong Pung How School Of Law

Several countries and regions around the world, including Singapore, the United Kingdom, and the European Union, are amending their restructuring framework to implement a pre-insolvency mechanism that includes most of the features that exist in the US Chapter 11 reorganization procedure. However, unlike what happens in the United States, where unsuccessful reorganizations lead to Chapter 7 liquidations, companies using this ‘de facto Chapter 11’ (DFCH11) are still allowed to use formal reorganization procedures. This article argues that, while the rise of the DFCH11 is not necessarily undesirable provided that various protections are put in place, jurisdictions implementing this restructuring tool …

Mediating Consumer Financial Disputes: Financial Industry Disputes Resolution Centre's Unique House Style, Eunice Chua, Beverly Wee

Research Collection Yong Pung How School Of Law

The Financial Industry Disputes Resolution Centre (“FIDReC”) was established in August 2005 with the purpose of providing a low-cost avenue for consumers to resolve their disputes with financial institutions. This article seeks to outline the role of FIDReC and its processes and, at the same time, seeks to define the house style of mediation that has served FIDReC well over the years. This article also highlights some of the different techniques adopted by FIDReC mediators in the course of facilitating the mediation.

Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying Lin, Ling-Yan Bao, Ze-Minghui Li, Shu-Sheng Si, Chao-Hsien Chu

Research Collection School Of Computing and Information Systems

Deep learning (DL) has been widely applied to achieve promising results in many fields, but it still exists various privacy concerns and issues. Applying differential privacy (DP) to DL models is an effective way to ensure privacy-preserving training and classification. In this paper, we revisit the DP stochastic gradient descent (DP-SGD) method, which has been used by several algorithms and systems and achieved good privacy protection. However, several factors, such as the sequence of adding noise, the models used etc., may impact its performance with various degrees. We empirically show that adding noise first and clipping second will not only …

Nearest Centroid: A Bridge Between Statistics And Machine Learning, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

In order to guide our students of machine learning in their statistical thinking, we need conceptually simple and mathematically defensible algorithms. In this paper, we present the Nearest Centroid algorithm (NC) algorithm as a pedagogical tool, combining the key concepts behind two foundational algorithms: K-Means clustering and K Nearest Neighbors (k- NN). In NC, we use the centroid (as defined in the K-Means algorithm) of the observations belonging to each class in our training data set and its distance from a new observation (similar to k-NN) for class prediction. Using this obvious extension, we will illustrate how the concepts of …

Digital Social Listening On Conversations About Sexual Harassment, Xuesi Sim, Ern Rae Chang, Yu Xiang Ong, Jie Ying Yeo, Christine Bai Shuang Yan, Eugene Wen Jia Choy, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In light of the #MeToo movement and publicized sexual harassment incidents in Singapore in recent years, we built an analytics pipeline for performing digital social listening on conversations about sexual harassment for AWARE (Association of Women for Action and Research). Our social network analysis results identified key influencers that AWARE can engage for sexual harassment awareness campaigns. Further, our analysis results suggest new hashtags that AWARE can use to run social media campaigns and achieve greater reach.

Graphmp: I/O-Efficient Big Graph Analytics On A Single Commodity Machine, Peng Sun, Yonggang Wen, Nguyen Binh Duong Ta, Xiaokui Xiao

Research Collection School Of Computing and Information Systems

Recent studies showed that single-machine graph processing systems can be as highly competitive as cluster-based approaches on large-scale problems. While several out-of-core graph processing systems and computation models have been proposed, the high disk I/O overhead could significantly reduce performance in many practical cases. In this paper, we propose GraphMP to tackle big graph analytics on a single machine. GraphMP achieves low disk I/O overhead with three techniques. First, we design a vertex-centric sliding window (VSW) computation model to avoid reading and writing vertices on disk. Second, we propose a selective scheduling method to skip loading and processing unnecessary edge …

Blockchain-Based Public Auditing And Secure Deduplication With Fair Arbitration, Haoran Yuan, Xiaofeng Chen, Jianfeng Wang, Jiaming Yuan, Hongyang Yan, Willy Susilo

Research Collection School Of Computing and Information Systems

Data auditing enables data owners to verify the integrity of their sensitive data stored at an untrusted cloud without retrieving them. This feature has been widely adopted by commercial cloud storage. However, the existing approaches still have some drawbacks. On the one hand, the existing schemes have a defect of fair arbitration, i.e., existing auditing schemes lack an effective method to punish the malicious cloud service provider (CSP) and compensate users whose data integrity is destroyed. On the other hand, a CSP may store redundant and repetitive data. These redundant data inevitably increase management overhead and computational cost during the …

End-User Perceptions Of Success And Failure: Narratives From A Natural Laboratory Of Rural Electrification Projects In Malaysian Borneo, Terry Van Gevelt, T. Zaman, F. George, M.M Bennett, S.D. Fam, J.E. Kim

Research Collection College of Integrative Studies

Located deep in the Kelabit Highlands in Malaysian Borneo, the remote town of Bario offers us a natural laboratory of rural electrification projects through which to understand end-user perceptions of success and failure, and the factors that contribute to these perceptions. We use a case-study based approach and focus on three off-grid energy projects: a 110 kW mini-hydro power plant; a 12 kW wind turbine system; and a 1.59 MW solar-diesel hybrid system. We find that end-users primarily see the success or failure of a project in technical terms, but that this narrow conceptualization masks important interactions between technical, economic …

Unmaking California’S Central Valley, Sayd Randle

Research Collection College of Integrative Studies

IN THIS YEAR of heat records and fire tornadoes, California faces another potential crisis: drought. In November 2020, more than 80 percent of the state’s land mass was classified as somewhere between “abnormally dry” and “extreme drought” by the United States Drought Monitor. The chances of the winter offering relief look slim, given what’s called a “La Niña climate pattern,” which is associated with arid conditions in much of California. The months ahead are, in general, far more likely to bring water worries than happy surprises.To longtime California residents, such fears are familiar. The state’s most recent drought began in …

How Do Monetary Incentives Influence Prosocial Fundraising? An Empirical Investigation Of Matching Subsidies On Crowdfunding, Zhiyuan Gao

Dissertations and Theses Collection (Open Access)

Monetary incentives, such as matching subsidies, are widely used in traditional fundraising and crowdfunding platforms to boost funding activities and improve funding outcomes. However, its effectiveness on prosocial fundraising is still unclear from both theoretical (Bénabou and Tirole, 2006; Frey, 1997; Meier, 2007a) and empirical studies (Ariely et al., 2009; Karlan and List, 2007; Rondeau and List, 2008). This dissertation aims to examine the effectiveness of matching subsidies on prosocial fundraising in the crowdfunding context. Specifically, I study how the presence of matching subsidies affects overall funding outcomes and funding dynamics in the online prosocial crowdfunding environment.

The first essay …

Vision-Based Analytics For Improved Ai-Driven Iot Applications, Amit Sharma

Dissertations and Theses Collection (Open Access)

Proliferation of Internet of Things (IoT) sensor systems, primarily driven by cheaper embedded hardware platforms and wide availability of light-weight software platforms, has opened up doors for large-scale data collection opportunities. The availability of massive amount of data has in-turn given way to rapidly growing machine learning models e.g. You Only Look Once (YOLO), Single-Shot-Detectors (SSD) and so on. There has been a growing trend of applying machine learning techniques, e.g., object detection, image classification, face detection etc., on data collected from camera sensors and therefore enabling plethora of vision-sensing applications namely self-driving cars, automatic crowd monitoring, traffic-flow analysis, occupancy …

Salary Negotiation: Myths Busted, Abhijeet K. Vadera, Karyn Thye

Research Collection Lee Kong Chian School Of Business

A negotiation expert and a compensation geek came together to answer some of the toughest salary negotiation questions from the Master of Human Capital Leadership (MHCL) 2020 graduate cohort. We hope that our combined experiences in this field would help shed some light on the complex world of salary negotiations.

Is The Synthetic Stock Price Really Lower Than Actual Price?, Jianfeng Hu

Research Collection Lee Kong Chian School Of Business

Conventional wisdom suggests synthetic stock prices are lower than actual prices due to short‐sale constraints and voting premiums. This study finds that such underpricing of the synthetic midquote disappears if arbitrageurs face security borrowing costs. The synthetic spread predominantly contains the actual spread. Synthetic stock overpricing is as common as underpricing but the former is more persistent and more profitable. The difference between synthetic and actual quotes is significantly affected by options market makers' hedging costs and investors' demand for leverage.

Feedback On The International Accounting Standards Board Discussion Paper On Business Combinations—Disclosures, Goodwill And Impairment, Pearl Hock-Neo Tan

Research Collection School Of Accountancy

No abstract provided.

How To Prepare Young Finance & Accounting Professionals For Digital Revolution, Clarence Goh, Gary Pan, Chi Kwan Yuen

Research Collection School Of Accountancy

Automation will alter the work of accountants in the coming years. However, accountants will always have a central role to play in business. In order to continue to thrive, the profession will need to position itself to capitalise on the opportunities that automation will bring. This involves identifying areas of work which computers cannot automate, and to focus on deepening contributions in these areas. This calls for a radical transformation of accounting education in order to equip accounting graduates with relevant work skills that will allow students to navigate a future workplace where computers and technology are the norm.

International Tax Competition And Foreign Direct Investment In The Asia-Pacific Region: A Panel Data Analysis, Chengwei Xu, Alfred M. Wu

Research Collection School Of Accountancy

Purpose: The purpose of this study is to investigate how a country's competitive tax policy influences its inward foreign direct investments (FDI) in the Asia–Pacific region, even when given particular constraints (e.g., population, public governance, skilled labor, and so on) exist. Design/methodology/approach: The paper uses the system GMM estimation approach to test the hypothesis. Data on FDI, corporate income tax, and various confounding factors were drawn from Ernst and Young's worldwide corporate tax guide, the World Bank, and other sources to create a panel of 28 economies over the period 2000–2016. Findings: The present research confirms the negative association between …

Contracting And Reporting Conservatism Around A Change In Fiduciary Duties, Daniel Bens, Sterling Huang, Liang Tan, Wan Wongsumwai

Research Collection School Of Accountancy

We exploit an influential 1991 Delaware court ruling to examine the impact of changes in managerial fiduciary duties on firms’ accounting and contracting choices. The ruling expanded directors’ fiduciary duties in favor of creditors and away from shareholders for a specific group of firms. Using a hand-collected sample of debt contracts around the ruling date, we find that, following the ruling, debt contracts of affected firms rely less on the use of income escalators (provisions in loan contracts which require changes in net worth to reflect losses in full, but only partially for gains and profits) and other conservative adjustments …

Human Capital Leadership Insights: Solving Human Capital Challenges From The Business Perspective, Singapore Management University

Student Publications

In 2016, the Lee Kong Chian School of Business launched the Master of Human Capital Leadership (“MHCL”) program with the strategic objective of growing leaders to champion evidence-based human capital practices. The 2019 MHCL cohort took this a step further with their quest to share insights gained from studies and projects with industry stakeholders. This goal resonates with our mission -- to create and disseminate knowledge.

Local Dominance, Emiliano Catonini, Jingyi Xue

SMU Economics and Statistics Working Paper Series

We define a local notion of weak dominance that speaks to the true choice problems among actions in a game tree and does not necessarily require to plan optimally for the future. A strategy is (globally) weakly dominant if and only if it prescribes a locally weakly dominant action at every decision node it reaches, and in this case local weak dominance is characterized by a (wishful-thinking) condition that requires no forward planning. From this local perspective, we identify form of contingent reasoning that are particularly natural, despite the absence of an obviously dominant strategy (Li, 2017). Following this approach, …

$14 Million Ian R. Taylor Memorial Fund Fosters Talent Development At Smu, Singapore Management University

SMU Press Releases

Past and present staff of Vitol Asia have come together to make an endowed gift of $14 million to set up the Ian R. Taylor Memorial Fund (IRT-MF) at the Singapore Management University (SMU) in honour and memory of the late Mr Ian Roper Taylor (7 February 1956 – 8 June 2020). Mr Taylor was the former chief executive and chairman of the Vitol Group who transformed the small Dutch fuel merchant into the global commodities powerhouse that it is today.

The Role Of Employee Proactive Behaviors In Influencing Supervisors’ Trust In Employees, Ngai Meng Ho

Dissertations and Theses Collection (Open Access)

In organizations, proactive employees make things happen. They anticipate, initiate, and drive meaningful changes for a better future. Such proactive behaviors can be manifested in different forms. Initiating work improvements and voicing for changes are examples of the different proactive behaviors commonly demonstrated by employees.

Empirical studies have associated proactive behaviors at work with a range of positive workplace outcomes. However, only limited research has examined how proactive behaviors might be related to one particularly important outcome, trust, i.e., whether an employee’s proactive behaviors will influence the supervisor’s trust toward the employee. Accordingly, in this present research, I conducted two …

Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud, Ximeng Liu, Robert H. Deng, Pengfei Wu, Yang Yang

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and …

Interventional Few-Shot Learning, Zhongqi Yue, Zhang Hanwang, Qianru Sun, Xian-Sheng Hua

Research Collection School Of Computing and Information Systems

We uncover an ever-overlooked deficiency in the prevailing Few-Shot Learning (FSL) methods: the pre-trained knowledge is indeed a confounder that limits the performance. This finding is rooted from our causal assumption: a Structural Causal Model (SCM) for the causalities among the pre-trained knowledge, sample features, and labels. Thanks to it, we propose a novel FSL paradigm: Interventional Few-Shot Learning (IFSL). Specifically, we develop three effective IFSL algorithmic implementations based on the backdoor adjustment, which is essentially a causal intervention towards the SCM of many-shot learning: the upper-bound of FSL in a causal view. It is worth noting that the contribution …

Causal Intervention For Weakly-Supervised Semantic Segmentation, Zhang Dong, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun

Research Collection School Of Computing and Information Systems

We present a causal inference framework to improve Weakly-Supervised Semantic Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by using only image-level labels --- the most crucial step in WSSS. We attribute the cause of the ambiguous boundaries of pseudo-masks to the confounding context, e.g., the correct image-level classification of "horse'' and "person'' may be not only due to the recognition of each instance, but also their co-occurrence context, making the model inspection (e.g., CAM) hard to distinguish between the boundaries. Inspired by this, we propose a structural causal model to analyze the causalities among images, contexts, and …

Debunking Rumors On Twitter With Tree Transformer, Jing Ma, Wei Gao

Research Collection School Of Computing and Information Systems

Rumors are manufactured with no respect for accuracy, but can circulate quickly and widely by "word-of-post" through social media conversations. Conversation tree encodes important information indicative of the credibility of rumor. Existing conversation-based techniques for rumor detection either just strictly follow tree edges or treat all the posts fully-connected during feature learning. In this paper, we propose a novel detection model based on tree transformer to better utilize user interactions in the dialogue where post-level self-attention plays the key role for aggregating the intra-/inter-subtree stances. Experimental results on the TWITTER and PHEME datasets show that the proposed approach consistently improves …