Digital Commons Network^™

Customer Satisfaction Index Of Singapore 2020: Q2 Results, Institute Of Service Excellence, Smu

Research Collection Institute of Service Excellence (2007-2024)

The Customer Satisfaction Index of Singapore (CSISG) computes customer satisfaction scores at the national, sector, sub-sector, and company levels. The CSISG serves as a quantitative benchmark of the quality of goods and services produced by the Singapore economy over time and across countries. This is the CSISG’s 14th year of measurement.

Pretrial Justice Reform And Property Crime: Evidence From New Jersey, Jung K. Kim, Yumi Koh

Research Collection Lee Kong Chian School Of Business

Several states and localities have begun to implement various forms of pretrial justice reforms aimed at reducing the size of pretrial detainee population. However, empirical investigation of the effect of such reforms on crimes more broadly (other than recidivism) is limited. We analyse the effect of the 2017 New Jersey Criminal Justice Reform on property crimes. We find that property crime per 100,000 population increased by 22.5% within the first two years. Our findings suggest that reducing the likelihood of pretrial detention for less violent crimes can have substantial impact on behavioural incentives for offenders of such crimes.

Extracting Deep Features From Short Ecg Signals For Early Atrial Fibrillation Detection, Xiaodan Wu, Yumeng Zheng, Chao-Hsien Chu, Zhen He

Research Collection School Of Computing and Information Systems

Atrial Fibrillation (AF) at an early stage has a short duration and is sometimes asymptomatic, making it difficult to detect. Although the use of mobile sensing devices has provided the possibility of real-time cardiac detection, it is highly susceptible to the noise signals generated by body movement. Therefore, it is of great importance to study early AF detection for mobile terminals with noise immunity. Extracting effective features is critical to AF detection, but most existing studies used shallow time, frequency or time-frequency energy (TFE) features with weak representation that need to rely on long ECG signals to capture the variation …

Politically Connected Governments, Christine Cuny, Jungbae Kim, Mihir N. Mehta

Research Collection School Of Accountancy

This paper examines the consequences of powerful political connections for local governments. We find that governments located within the constituencies of, and thus connected to, powerful congressional members reduce their stewardship over public resources. Using plausibly exogenous declines in the power of congressional representation, we show that the effect is causal. To better understand why connected local governments can reduce stewardship, we study electoral characteristics. Our findings suggest that the increased resources that come with powerful congressional representation allow local‐government officials to reduce stewardship without material adverse effects on their reelection prospects. In sum, we provide evidence of a cost …

A Lattice-Based Key-Insulated And Privacy-Preserving Signature Scheme With Publicly Derived Public Key, Wenling Liu, Zhen Liu, Khoa Nguyen, Guomin Yang, Yu Yu

Research Collection School Of Computing and Information Systems

As a widely used privacy-preserving technique for cryptocurrencies, Stealth Address constitutes a key component of Ring Confidential Transaction (RingCT) protocol and it was adopted by Monero, one of the most popular privacy-centric cryptocurrencies. Recently, Liu et al. [EuroS&P 2019] pointed out a flaw in the current widely used stealth address algorithm that once a derived secret key is compromised, the damage will spread to the corresponding master secret key, and all the derived secret keys thereof. To address this issue, Liu et al. introduced Key-Insulated and Privacy-Preserving Signature Scheme with Publicly Derived Public Key (PDPKS scheme), which captures the functionality, …

Detectif: Unified Detection And Correction Of Iot Faults In Smart Homes, Madhumita Maliick, Archan Misra, Niloy Ganguly, Youngki Lee

Research Collection School Of Computing and Information Systems

This paper tackles the problem of detecting a comprehensive set of sensor faults that can occur in IoT-instrumented smart homes customized to infer Activities of Daily Living (ADL) from the activation of sensor sets. Specifically, sensors can suffer faults that (a) span durations that vary between several seconds to hours, (b) can result in both missing or false-alarm sensor-events. Previous fault detection approaches are geared primarily to identify missing faults (absence of sensor readings) of a permanent (very long-lived) nature, or sporadic false-alarm events. We propose DetectIF, a fault-detection framework that detects faults of varying time duration, and identifies both …

How (Not) To Find Bugs: The Interplay Between Merge Conflicts, Co-Changes, And Bugs, Luis Amaral, Marcos C. Oliveira, Welder Luz, José Fortes, Rodrigo Bonifacio, Daniel Alencar, Eduardo Monteiro, Gustavo Pinto, David Lo

Research Collection School Of Computing and Information Systems

Context: In a seminal work, Ball et al. [1] investigate if the information available in version control systems could be used to predict defect density, arguing that practitioners and researchers could better understand errors "if [our] version control system could talk". In the meanwhile, several research works have reported that conflict merge resolution is a time consuming and error-prone task, while other contributions diverge about the correlation between co-change dependencies and defect density. Problem: The correlation between conflicting merge scenarios and bugs has not been addressed before, whilst the correlation between co-change dependencies and bug density has been only investigated …

An Empirical Study Of The Dependency Networks Of Deep Learning Libraries, Junxiao Han, Shuiguang Deng, David Lo, Chen Zhi, Jianwei Yin, Xin Xia

Research Collection School Of Computing and Information Systems

Deep Learning techniques have been prevalent in various domains, and more and more open source projects in GitHub rely on deep learning libraries to implement their algorithms. To that end, they should always keep pace with the latest versions of deep learning libraries to make the best use of deep learning libraries. Aptly managing the versions of deep learning libraries can help projects avoid crashes or security issues caused by deep learning libraries. Unfortunately, very few studies have been done on the dependency networks of deep learning libraries. In this paper, we take the first step to perform an exploratory …

Marble: Model-Based Robustness Analysis Of Stateful Deep Learning Systems, Xiaoning Du, Yi Li, Xiaofei Xie, Lei Ma, Yang Liu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

State-of-the-art deep learning (DL) systems are vulnerable to adversarial examples, which hinders their potential adoption in safetyand security-critical scenarios. While some recent progress has been made in analyzing the robustness of feed-forward neural networks, the robustness analysis for stateful DL systems, such as recurrent neural networks (RNNs), still remains largely uncharted. In this paper, we propose Marble, a model-based approach for quantitative robustness analysis of real-world RNN-based DL systems. Marble builds a probabilistic model to compactly characterize the robustness of RNNs through abstraction. Furthermore, we propose an iterative refinement algorithm to derive a precise abstraction, which enables accurate quantification of …

The Gap Of Semantic Parsing: A Survey On Automatic Math Word Problem Solvers, Dongxiang Zhang, Lei Wang, Luming Zhang, Bing Tian Dai, Heng Tao Shen

Research Collection School Of Computing and Information Systems

Solving mathematical word problems (MWPs) automatically is challenging, primarily due to the semantic gap between human-readable words and machine-understandable logics. Despite the long history dated back to the 1960s, MWPs have regained intensive attention in the past few years with the advancement of Artificial Intelligence (AI). Solving MWPs successfully is considered as a milestone towards general AI. Many systems have claimed promising results in self-crafted and small-scale datasets. However, when applied on large and diverse datasets, none of the proposed methods in the literature achieves high precision, revealing that current MWP solvers still have much room for improvement. This motivated …

Weakly Paired Multi-Domain Image Translation, M.Y. Zhang, Zhiwu Huang, D.P. Paudel, J. Thoma, Gool L. Van

Research Collection School Of Computing and Information Systems

In this paper, we aim at studying the new problem of weakly paired multi-domain image translation. To this end, we collect a dataset that contains weakly paired images from multiple domains. Two images are considered to be weakly paired if they are captured from nearby locations and share an overlapping field of view. These images are possibly captured by two asynchronous cameras—often resulting in images from separate domains, e.g. summer and winter. Major motivations for using weakly paired images are: (i) performance improvement towards that of paired data; (ii) cheap labels and abundant data availability. For the first time in …

Opening The Door To Fickle-Minded Guilty Pleas? Public Prosecutor V Dinesh S/O Rajantheran, Teng Jun Gerome Goh

Research Collection Yong Pung How School Of Law

Unlike applications to retract guilty pleas, accused persons are not required to provide valid and sufficient reasons when qualifying their guilty pleas in mitigation. In Criminal Reference No. 5 of 2018, the Court of Appeal held that section 228(4) of the Criminal Procedure Code allows accused persons to qualify their guilty pleas in mitigation to the extent that it amounts to a retraction of their guilty pleas unless there is an abuse of the court’s process. This comment considers the desirability of the current law and suggests that the law applying to such withdrawals of guilty pleas should be …

Corporate Social Responsibility And Sustainable Finance: A Review Of The Literature, Hao Liang, Luc Renneboog

Research Collection Lee Kong Chian School Of Business

Corporate Social Responsibility (CSR) refers to the incorporation of Environmental, Social, and Governance (ESG) considerations into corporate management, financial decision making, and investors’ portfolio decisions. Socially responsible firms are expected to internalize the externalities (e.g. pollution) they create, and are willing to be accountable to shareholders as well as a broader group of stakeholders (employees, customers, suppliers, local communities,…). Over the past two decades, various rating agencies developed firm-level measures of ESG performance, which are widely used in the literature. A problem for past and a challenge for future research is that these ratings show inconsistencies, which depend on the …

Research On The Impact Of Venture Capital On The Operating Performance Of Startups, Ziqiang Sun

Dissertations and Theses Collection (Open Access)

Venture capital can not only realize its own capital appreciation, but also promote the development of startups and boost the development of high-tech industries; therefore, it has obvious positive externalities. With the development of venture capital in China, the impact of venture capital on the operating performance of startups gradually attracts widespread attention.

This paper investigates the impact of venture capital on the operating performance of startups and conducts an in-depth discussion on the problem formulation, empirical relationship, cause and effect analysis, and countermeasure suggestions. The main research contents include:

The first part is the introduction, which analyzes the research …

The Optimal Degree Of Reciprocity In Tariff Reduction, Pao-Li Chang

Research Collection School Of Economics

This paper characterizes the optimal reciprocal trade policy in the environment of Melitz (2003) with firm productivity heterogeneity. With all the conflicting effects of import tariffs on welfare considered, the optimal degree of reciprocity in multilateral tariff reduction is shown to be free trade.

The Optimal Degree Of Reciprocity In Tariff Reduction, Pao-Li Chang

Research Collection School Of Economics

This paper characterizes the optimal reciprocal trade policy in the environment of Melitz (2003) with firm productivity heterogeneity. In particular, without making parametric assumptions on firm productivity distribution, this paper derives the optimal degree of reciprocal tariff reductions that maximize the world welfare. A reciprocal import subsidy raises the industry productivity, lowering aggregate price; a reciprocal import tariff helps correct the markup distortion, increasing nominal income. With all the conflicting effects of import tariffs on welfare considered, the optimal degree of reciprocity in multilateral tariff reduction is shown to be free trade.

Exclusion Of Duty And The Irreducible Core Content Of Trusteeship: A Re-Assessment, Rebecca Lee, Man Yip

Research Collection Yong Pung How School Of Law

This article reviews Millett LJ’s classic characterisation of the irreducible core content of trusteeship. Using duty modification / exclusion clauses that are commonly found in modern trust-corporate structures to circumvent a trustee’s duty to actively engage in corporate management as an example, this article has two main objectives. First, this article re-examines the duty to act honestly and in good faith in the irreducible core; and secondly, it considers how our reanalysis can help conceptualise and construe the ‘residual supervisory obligation’ enunciated by the courts in the recent Zhang v DBS litigation.

Defeating The Scourge Of Terrorism: How Soft Law Instruments In Singapore Can Develop Societal Trust And Promote Cooperative Norms, Tan K. B. Eugene

Research Collection Yong Pung How School Of Law

The maintenance of a ‘moderate, mainstream’ Muslim community as a bulwark against the fraying of harmonious ethnic relations has become a key governance concern in multiracial, multi-religious societies post9/11. In light of the global concern, and often paranoia, with diasporic Islam, Islamic religious institutions and civil society have been portrayed in the popular media as hotbeds of radicalism, promoters of hatred, and recruiters for a “conflict of civilisation” between the Muslim world and the modern world. Singapore has taken a broad-based community approach in advancing interreligious tolerance, including a subtle initiative to include the putative Muslim civil society in advancing …

Manufacturing Hate 4.0: Can Media Studies Rise To The Challenge?, Sun Sun Lim

Research Collection College of Integrative Studies

This article reflects on the growing scourge of hate speech and its propagation via digital social media networks. It discusses how media studies has drawn attention to salient aspects of online hate speech including technological affordances, communication tactics, representational tropes, and audience response. It argues that insights from media studies are vital for unpacking the societal impact of the media and indeed for tackling a destructive force such as online hate speech. It further encourages media studies scholars to engage vigorously with colleagues in and across other disciplines to forge interdisciplinary research collaborations to address pressing societal issues. It urges …

Revisiting The Precedential Status Of Crown Court Decisions, Kwan Ho Lau

Research Collection Yong Pung How School Of Law

The binding authority of substantive decisions made by the Crown Court in the exercise of its criminal jurisdiction is often assumed to be negligible. In 2013, the Court of Appeal appeared to confirm the correctness of that assumption. Yet there was little in the way of explanation or case law that was cited in support by the court. This article suggests that a re-evaluation of the place and treatment of such decisions within the doctrine of precedent is overdue, and considers that they should be recognised to have some binding effect if there is able to be established a reasonably …

General Principle, Adeline Chong

Research Collection Yong Pung How School Of Law

This is the first Principle in the set of Asian Principles. It sets out the proposition that a foreign judgment in a commercial matter is generally entitled to recognition and enforcement. The chapter explores the extent to which this Principle is adopted in the countries under study. It also considers the modes through which a foreign judgment is given effect, the theoretical bases for recognising and enforcing a foreign judgment and suggests a way forward in view of different approaches on this issue.

Impossible Attempts And The Punishment Of Intent: Han Fang Guan V Public Prosecutor, Wing Cheong Chan

Research Collection Yong Pung How School Of Law

This comment reviews the new “two-stage framework” developed by the Singapore Court of Appeal in the case of Han Fang Guan v Public Prosecutor for impossible attempts under the Misuse of Drugs Act. The new framework clarifies the law and it is suggested that the approach should be adopted for all other criminal laws as well.

Attribution Of Civil Liability For Accidents Involving Automated Cars, Siyuan Chen, Jie Hao Sampson Lim, Beverly Kai Li Lim

Research Collection Yong Pung How School Of Law

With the much-anticipated revolution in autonomous (or “self-driving”) cars fast becoming reality, the Singapore Academy of Law’s Law Reform Committee (‘LRC’) has considered how liability should be attributed in the event of accidents involving such cars, and the issues that may arise in seeking to apply existing liability frameworks.

Wait For It: Identifying 'On-Hold' Self-Admitted Technical Debt, Rungroj Maipradit, Christoph Treude, Hideaki Hata, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

Self-admitted technical debt refers to situations where a software developer knows that their current implementation is not optimal and indicates this using a source code comment. In this work, we hypothesize that it is possible to develop automated techniques to understand a subset of these comments in more detail, and to propose tool support that can help developers manage self-admitted technical debt more effectively. Based on a qualitative study of 333 comments indicating self-admitted technical debt, we first identify one particular class of debt amenable to automated management: on-hold self-admitted technical debt (on-hold SATD), i.e., debt which contains a condition …

Cats Are Not Fish: Deep Learning Testing Calls For Out-Of-Distribution Awareness, David Berend, Xiaofei Xie, Lei Ma, Lingjun Zhou, Yang Liu, Chi Xu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

As Deep Learning (DL) is continuously adopted in many industrial applications, its quality and reliability start to raise concerns. Similar to the traditional software development process, testing the DL software to uncover its defects at an early stage is an effective way to reduce risks after deployment. According to the fundamental assumption of deep learning, the DL software does not provide statistical guarantee and has limited capability in handling data that falls outside of its learned distribution, i.e., out-of-distribution (OOD) data. Although recent progress has been made in designing novel testing techniques for DL software, which can detect thousands of …

Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao

Research Collection School Of Computing and Information Systems

Sharing digital medical records on public cloud storage via mobile devices facilitates patients (doctors) to get (offer) medical treatment of high quality and efficiency. However, challenges such as data privacy protection, flexible data sharing, efficient authority delegation, computation efficiency optimization, are remaining toward achieving practical fine-grained access control in the Electronic Medical Record (EMR) system. In this work, we propose an innovative access control model and a fine-grained data sharing mechanism for EMR, which simultaneously achieves the above-mentioned features and is suitable for resource-constrained mobile devices. In the model, complex computation is outsourced to public cloud servers, leaving almost no …

Smart Contract Repair, Xiao Liang Yu, Omar Al-Bataineh, David Lo, Abhik Roychoudhury

Research Collection School Of Computing and Information Systems

Smart contracts are automated or self-enforcing contracts that can be used to exchange assets without having to place trust in third parties. Many commercial transactions use smart contracts due to their potential benefits in terms of secure peer-to-peer transactions independent of external parties. Experience shows that many commonly used smart contracts are vulnerable to serious malicious attacks, which may enable attackers to steal valuable assets of involving parties. There is, therefore, a need to apply analysis and automated repair techniques to detect and repair bugs in smart contracts before being deployed. In this work, we present the first general-purpose automated …

Towards Generating Thread-Safe Classes Automatically, Haichi Wang, Zan Wang, Jun Sun, Shuang Lin, Ayesha Sadiq, Yuan Fang Li

Research Collection School Of Computing and Information Systems

The existing concurrency model for Java (or C) requires programmers to design and implement thread-safe classes by explicitly acquiring locks and releasing locks. Such a model is error-prone and is the reason for many concurrency bugs. While there are alternative models like transactional memory, manually writing locks remains prevalent in practice. In this work, we propose AutoLock, which aims to solve the problem by fully automatically generating thread-safe classes. Given a class which is assumed to be correct with sequential clients, AutoLock automatically generates a thread-safe class which is linearizable, and does it in a way without requiring a specification …

Towards Interpreting Recurrent Neural Networks Through Probabilistic Abstraction, Guoliang Dong, Jingyi Wang, Jun Sun, Yang Zhang, Xinyu Wang, Ting Dai, Jin Song Dong, Xingen Wang

Research Collection School Of Computing and Information Systems

Neural networks are becoming a popular tool for solving many realworld problems such as object recognition and machine translation, thanks to its exceptional performance as an end-to-end solution. However, neural networks are complex black-box models, which hinders humans from interpreting and consequently trusting them in making critical decisions. Towards interpreting neural networks, several approaches have been proposed to extract simple deterministic models from neural networks. The results are not encouraging (e.g., low accuracy and limited scalability), fundamentally due to the limited expressiveness of such simple models.In this work, we propose an approach to extract probabilistic automata for interpreting an important …

Bus Frequency Optimization: When Waiting Time Matters In User Satisfaction, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng

Research Collection School Of Computing and Information Systems

Reorganizing bus frequency to cater for the actual travel demand can save the cost of the public transport system significantly. Many, if not all, existing studies formulate this as a bus frequency optimization problem which tries to minimize passengers’ average waiting time. However, many investigations have confirmed that the user satisfaction drops faster as the waiting time increases. Consequently, this paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services …