Digital Commons Network^™

Two Sides Of The Same Coin: Exploiting The Impact Of Identifiers In Neural Code Comprehension, Shuzheng Gao, Cuiyun Gao, Chaozheng Wang, Jun Sun, David Lo, Yue Yu

Research Collection School Of Computing and Information Systems

Previous studies have demonstrated that neural code comprehension models are vulnerable to identifier naming. By renaming as few as one identifier in the source code, the models would output completely irrelevant results, indicating that identifiers can be misleading for model prediction. However, identifiers are not completely detrimental to code comprehension, since the semantics of identifier names can be related to the program semantics. Well exploiting the two opposite impacts of identifiers is essential for enhancing the robustness and accuracy of neural code comprehension, and still remains under-explored. In this work, we propose to model the impact of identifiers from a …

Menger Or Marx? The Political Ontology Of Cryptocurrency, Rector Tully, J.G. Allen

Research Collection Yong Pung How School Of Law

One of the perennial fault-lines in monetary theory is that between commodity and credit theories of money. The emergence of alternative payment systems based on blockchain and distributed ledger technologies, of which Bitcoin is the most prominent example, has raised a host of important questions in relation to this debate. This article considers two. The first is ontological: Are Bitcoin and similar ‘cryptocurrencies’ best conceived of as money? The second is political: Do these money candidates represent an emancipatory development over state-backed fiat currency? The ontological question, we will argue, invites the political one. If it is the case, as …

The Mutual Constitution Of Culture And Psyche: The Bidirectional Relationship Between Individuals’ Perceived Control And Cultural Tightness-Looseness, Anyi Ma, Krishna Savani, Fangzhou Liu, Kenneth Tai, Aaron C. Kay

Research Collection Lee Kong Chian School Of Business

According to the theory of mutual constitution of culture and psyche, just as culture shapes people, individuals’ psychological states can influence culture. We build on compensatory control theory, which suggests that low personal control can lead people to prefer societal systems that impose order, to examine the mutual constitution of personal control and cultural tightness. Specifically, we tested whether individuals’ lack of personal control increases their preference for tighter cultures as a means of restoring order and predictability, and whether tighter cultures in turn reduce people’s feelings of personal control. Seven studies (five preregistered) with participants from the United States, …

Discoverability And Search Engine Visibility Of Repository Platforms, Danping Dong, Aaron Tay

Research Collection Library

It is of increasing interest and importance to understand the discoverability of content hosted on institutional repositories (IRs) and data repositories beyond the library context and on the wider web, as IRs play a significant role in promoting and disseminating the research outputs of an institution. This chapter provides an overview of early studies on IR discoverability in search engines, discusses standardized metrics for repository usage and ways to monitor search engine optimization, and provides practical suggestions to expose IR content to non-Google indexes and aggregators, such as Unpaywall. The second part of this chapter presents a case study and …

Arousing Motives Or Eliciting Stories? On The Role Of Pictures In A Picture–Story Exercise, Philipp Schäpers, Stefan Krumm, Filip Lievens, Nikola Stenzel

Research Collection Lee Kong Chian School Of Business

Picture–story exercises (PSE) form a popular measurement approach that has been widely used for the assessment of implicit motives. However, current theorizing offers two diverging perspectives on the role of pictures in PSEs: either to elicit stories or to arouse motives. In the current study, we tested these perspectives in an experimental design. We administered a PSE either with or without pictures. Results from N = 281 participants revealed that the experimental manipulation had a medium to large effect for the affiliation and power motive domains, but no effect for the achievement motive domain. We conclude that the herein chosen …

C-Wall: Conflict-Resistance In Privacy-Preserving Cloud Storage, Xiaoguo Li, Tao Xiang, Yi Mu, Fuchun Guo, Zhongyuan Yao

Research Collection School Of Computing and Information Systems

Following the success of cloud computing, it has been shown its importance to realize various access control models in the cloud storage setting. Chinese Wall is a traditional access control model in business for solving the conflict of interest (CoI) problem, and it would be very interesting to achieve conflict-resistant in cloud storage system. However, the access control model does not ensure the privacy of users, and it may reveal the user's interest, investment tendency, etc. Therefore, it raises a big challenge to implement the Chinese Wall without compromising the user's privacy. In this paper, we focus on the Chinese …

The Influence Of Transformational Leadership On Team Performance And Team Creativity: A Team-Level Resilient Proactive Model, Youwei Zhu

Dissertations and Theses Collection (Open Access)

The current Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) era is characterized by a number of factors, including globalization, technological advancements, geopolitical instability, and shifting consumer demands. These factors have combined to create an environment in which businesses and organizations must be highly adaptable and agile to survive and thrive.

To succeed in the current VUCA era, organizations must have the ability to anticipate and respond to change quickly while also being able to adapt to new technologies and business models. This task requires a strong focus on innovation, agility, and collaboration as well as a willingness to take calculated risks …

Ceo Humility And Firm Resilience, Yuehua Shen

Dissertations and Theses Collection (Open Access)

In today’s fast-changing world, firm resilience becomes an important force for firms to survive and develop. This dissertation aims to investigate the relationship between CEO humility and firm resilience, and further tackle the underlying mechanism behind the relationship. Based on upper echelons theory, this dissertation proposes that CEO humility promotes firm resilience, and the positive influence is mediated by stakeholder relationship capability. Moreover, competitive uncertainty and CEO work experience variety positively moderate the connection between CEO humility and stakeholder relationship capability. Using survey data from 119 CEOs in China, this dissertation tests the theoretical hypotheses and offers several implications for …

How To Find Actionable Static Analysis Warnings: A Case Study With Findbugs, Rahul Yedida, Hong Jin Kang, Huy Tu, Xueqi Yang, David Lo, Tim Menzies

Research Collection School Of Computing and Information Systems

Automatically generated static code warnings suffer from a large number of false alarms. Hence, developers only take action on a small percent of those warnings. To better predict which static code warnings should ot be ignored, we suggest that analysts need to look deeper into their algorithms to find choices that better improve the particulars of their specific problem. Specifically, we show here that effective predictors of such warnings can be created by methods that ocally adjust the decision boundary (between actionable warnings and others). These methods yield a new high water-mark for recognizing actionable static code warnings. For eight …

Can Conflict Cultivate Collaboration? The Positive Impact Of Mild Versus Intense Task Conflict Via Perceived Openness Rather Than Emotions, Ming-Hong Tsai

Research Collection School of Social Sciences

Public Significance Statement In contrast to previous research on the negative associations between conflict and collaboration, the current investigation demonstrates the positive effects of conflict on collaboration and performance and offers practical suggestions on beneficial conflict expressions. Specifically, when people debate and deliberate about their different viewpoints about task-related issues, they tend to collaborate and thus achieve high task performance by enhancing their perceptions of others' openness rather than by influencing their emotions.Previous research has demonstrated negative associations between task-relevant conflicts and collaboration. To supplement the previous findings and explore the potential benefits of conflicts, we differentiate between two types …

Regulating Artificial Intelligence In International Investment Law, Mark Mclaughlin

Research Collection Yong Pung How School Of Law

The interaction between artificial intelligence (AI) and international investment treaties is an uncharted territory of international law. Concerns over the national security, safety, and privacy implications of AI are spurring regulators into action around the world. States have imposed restrictions on data transfer, utilised automated decision-making, mandated algorithmic transparency, and limited market access. This article explores the interaction between AI regulation and standards of investment protection. It is argued that the current framework provides an unpredictable legal environment in which to adjudicate the contested norms and ethics of AI. Treaties should be recalibrated to reinforce their anti-protectionist origins, embed human-centric …

Maximising Effectiveness Of Talent Pools Through Mindfulness: An Empirical Investigation In A Multinational Corporation, Tarmo Raudsepp

Dissertations and Theses Collection (Open Access)

Traditional human resource management is looking to identify and develop talent for maximising human capital in a competitive environment with limited resources and negative demographic trends. Attracting, deploying, motivating, developing and retaining talented employees is a corporate norm for meeting organisational goals. Proper human resource processes through rigorous mapping of employees according to the performance-potential matrix allow the grading of employees against peer groups to establish talent pools for development and internal succession planning.

Mindfulness originates from 2,500-year-old Buddhist spiritual practices and has a rare combination of spirituality and science. Eastern perspective originates from Asian traditions focusing on the self-regulation …

The Impact Of Subordinates’ Proactive Personality On Empowering Leadership, Xin Zhan

Dissertations and Theses Collection (Open Access)

Research has documented numerous benefits of proactive personality for employees’ job outcomes. However, the success of proactive employees largely depends on their leaders’ empowerment. Extant research has focused on the bright side of proactive personality for inducing empowerment, without considering its risks. We thus have an incomplete understanding of the effects of employees’ proactive personality on empowering leadership. I take a balanced perspective on proactive personality and propose that proactive personality has an inverted U-shaped relationship with empowering leadership, such that empowering leadership is highest when proactive personality is at a moderate level. I argue that leader-member exchange (LMX) mediates …

Supporting Novices Author Audio Descriptions Via Automatic Feedback, Rosiana Natalie, Joshua Shi-Hao Tseng, Hernisa Kacorri, Kotaro Hara

Research Collection School Of Computing and Information Systems

Audio descriptions (AD) make videos accessible to those who cannot see them. But many videos lack AD and remain inaccessible as traditional approaches involve expensive professional production. We aim to lower production costs by involving novices in this process. We present an AD authoring system that supports novices to write scene descriptions (SD)—textual descriptions of video scenes—and convert them into AD via text-to-speech. The system combines video scene recognition and natural language processing to review novice-written SD and feeds back what to mention automatically. To assess the effectiveness of this automatic feedback in supporting novices, we recruited 60 participants to …

Parsing-Conditioned Anime Translation: A New Dataset And Method, Zhansheng Li, Yangyang Xu, Nanxuan Zhao, Yang Zhou, Yongtuo Liu, Dahua Lin, Shengfeng He

Research Collection School Of Computing and Information Systems

Anime is an abstract art form that is substantially different from the human portrait, leading to a challenging misaligned image translation problem that is beyond the capability of existing methods. This can be boiled down to a highly ambiguous unconstrained translation between two domains. To this end, we design a new anime translation framework by deriving the prior knowledge of a pre-Trained StyleGAN model. We introduce disentangled encoders to separately embed structure and appearance information into the same latent code, governed by four tailored losses. Moreover, we develop a FaceBank aggregation method that leverages the generated data of the StyleGAN, …

Reference-Based Screentone Transfer Via Pattern Correspondence And Regularization, Zhansheng Li, Nanxuan Zhao, Zongwei Wu, Yihua Dai, Junle Wang, Yanqing Jing, Shengfeng He

Research Collection School Of Computing and Information Systems

Adding screentone to initial line drawings is a crucial step for manga generation, but is a tedious and human-laborious task. In this work, we propose a novel data-driven method aiming to transfer the screentone pattern from a reference manga image. This not only ensures the quality, but also adds controllability to the generated manga results. The reference-based screentone translation task imposes several unique challenges. Since manga image often contains multiple screentone patterns interweaved with line drawing, as an abstract art, this makes it even more difficult to extract disentangled style code from the reference. Also, finding correspondence for mapping between …

Graphsearchnet: Enhancing Gnns Via Capturing Global Dependencies For Semantic Code Search, Shangqing Liu, Xiaofei Xie, Jjingkai Siow, Lei Ma, Guozhu Meng, Yang Liu

Research Collection School Of Computing and Information Systems

Code search aims to retrieve accurate code snippets based on a natural language query to improve software productivity and quality. With the massive amount of available programs such as (on GitHub or Stack Overflow), identifying and localizing the precise code is critical for the software developers. In addition, Deep learning has recently been widely applied to different code-related scenarios, ., vulnerability detection, source code summarization. However, automated deep code search is still challenging since it requires a high-level semantic mapping between code and natural language queries. Most existing deep learning-based approaches for code search rely on the sequential text ., …

Design, Development, And Evaluation Of An Interactive Personalized Social Robot To Monitor And Coach Post-Stroke Rehabilitation Exercises, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Bermudez I Badia

Research Collection School Of Computing and Information Systems

Socially assistive robots are increasingly being explored to improve the engagement of older adults and people with disability in health and well-being-related exercises. However, even if people have various physical conditions, most prior work on social robot exercise coaching systems has utilized generic, predefined feedback. The deployment of these systems still remains a challenge. In this paper, we present our work of iteratively engaging therapists and post-stroke survivors to design, develop, and evaluate a social robot exercise coaching system for personalized rehabilitation. Through interviews with therapists, we designed how this system interacts with the user and then developed an interactive …

Rntrajrec: Road Network Enhanced Trajectory Recovery With Spatial-Temporal Trans-Former, Yuqi Chen, Hanyuan Zhang, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

GPS trajectories are the essential foundations for many trajectory-based applications. Most applications require a large number of high sample rate trajectories to achieve a good performance. However, many real-life trajectories are collected with low sample rate due to energy concern or other constraints. We study the task of trajectory recovery in this paper as a means to increase the sample rate of low sample trajectories. Most existing works on trajectory recovery follow a sequence-to-sequence diagram, with an encoder to encode a trajectory and a decoder to recover real GPS points in the trajectory. However, these works ignore the topology of …

Insights Into Accuracy Of Social Scientists' Forecasts Of Societal Change, Igor Grossma, Andree Hartanto, Nadyanna M. Majeed, Et Al See Comments For Full List Of Authors

Research Collection School of Social Sciences

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. Following provision of historical trend data on the domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N=86 teams/359 forecasts), with an opportunity to update forecasts based on new data six months later (Tournament 2; N=120 teams/546 forecasts). Benchmarking forecasting accuracy revealed that social …

Multinational Family Firms’ Internationalization Depth And Breadth Following The Global Financial Crisis, Sebastian P. L. Fourné, Miriam Zschoche, Christian Schwens, Reddi Kotha

Research Collection Lee Kong Chian School Of Business

This study examines how large family firms react to a macroeconomic shock in terms of their internationalization depth and breadth. Building on new internalization theory and acknowledging the dysfunctional manifestations of bifurcation bias in large family-owned MNEs, we argue that an unexpected shock induces family firms to recombine their family firm-specific resources with their thus far underutilized or unequally treated nonfamily resources. This recombination allows most family firms to economize on bifurcation bias and leverage their resources as firm-specific advantages (FSAs) resulting in an increased depth and breadth of internationalization post shock (while some of them may continue to suffer …

Bubbleu: Exploring Augmented Reality Game Design With Uncertain Ai-Based Interaction, Minji Kim, Kyungjin Lee, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Object detection, while being an attractive interaction method for Augmented Reality (AR), is fundamentally error-prone due to the probabilistic nature of the underlying AI models, resulting in sub-optimal user experiences. In this paper, we explore the effect of three game design concepts, Ambiguity, Transparency, and Controllability, to provide better gameplay experiences in AR games that use error-prone object detection-based interaction modalities. First, we developed a base AR pet breeding game, called Bubbleu that uses object detection as a key interaction method. We then implemented three different variants, each according to the three concepts, to investigate the impact of each design …

Giving Back: Contributions Congruent To Library Dependency Changes In A Software Ecosystem, Supatsara Wattanakriengkrai, Dong Wang, Raula Gaikovina Kula, Christoph Treude, Patanamon Thongtanunam, Takashi Ishio, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

The widespread adoption of third-party libraries for contemporary software development has led to the creation of large inter-dependency networks, where sustainability issues of a single library can have widespread network effects. Maintainers of these libraries are often overworked, relying on the contributions of volunteers to sustain these libraries. To understand these contributions, in this work, we leverage socio-technical techniques to introduce and formalise dependency-contribution congruence (DC congruence) at both ecosystem and library level, i.e., to understand the degree and origins of contributions congruent to dependency changes, analyze whether they contribute to library dormancy (i.e., a lack of activity), and investigate …

Revisiting Tocqueville's American Woman, Christine Dunn Henderson

Research Collection College of Integrative Studies

This paper revisits Tocqueville’s famous portrait of the American female, which begins with assertions of her equality to males but ends with her self-cloistering in the domestic sphere. Taking a cue from Tocqueville’s extended sketch of the “faded” pioneer wife in “A Fortnight in the Wilderness” and drawing connections to Tocqueville’s criticisms of the division of industrial labor, I argue that the American girl’s ostensibly free choice to remove herself from public life is not an act of freedom. Rather, it is a manifestation of a particular type of unfreedom that reveals underappreciated connections between the two great dangers about …

A Hybrid Active Learning Framework For Personal Thermal Comfort Models, Duygu Zeynep Tekler, Yue Lei, Yuzhen Peng, Clayton Miller, Adrian Chong

Research Collection College of Integrative Studies

Personal thermal comfort models are used to predict individual-level thermal comfort responses to inform design and control decisions of buildings to achieve optimal conditioning for improved comfort and energy efficiency. However, the development of data-driven thermal comfort models requires collecting a large amount of sensor-related measurements and user-labelled data (i.e., user feedback) to achieve accurate predictions, which can be highly intrusive and labour intensive in real-world applications. In this work, we propose a hybrid active learning framework to reduce data collection costs for developing data-efficient and robust personal comfort models that predict users’ thermal comfort and air movement preferences. Through …

A Review And Reflection On Open Datasets Of City-Level Building Energy Use And Their Applications, Xiaoyu Jin, Chong Zhang, Fu Xiao, Ao Li, Clayton Miller

Research Collection College of Integrative Studies

Data related to building energy use fuels the research and applications on building energy efficiency, which is an essential measure to address global energy and environmental challenges. However, in most cities, there is a lack of comprehensive and publicly accessible building energy use datasets with necessary temporal and spatial granularities to support urban building energy modeling, regional energy planning, city-level building performance benchmarking, and policymaking on building energy efficiency. Data owners and governments are facing challenges in determining which and how building energy use data should be disclosed at the city level and how to protect data privacy. This review …

Adjustment With Many Regressors Under Covariate-Adaptive Randomizations, Liang Jiang, Liyao Li, Ke Miao, Yichong Zhang

Research Collection School Of Economics

Our paper identifies a trade-off when using regression adjustments (RAs) in causal inference under covariate-adaptive randomizations (CARs). On one hand, RAs can improve the efficiency of causal estimators by incorporating information from covariates that are not used in the randomization. On the other hand, RAs can degrade estimation efficiency due to their estimation errors, which are not asymptotically negligible when the number of regressors is of the same order as the sample size. Failure to account for the cost of RAs can result in over-rejection of causal inference under the null hypothesis. To address this issue, we develop a unified …

Economic Forecasting In Singapore: The Covid-19 Experience, Hwee Kwan Chow-Tan, Keen Meng Choy

Research Collection School Of Economics

This Special Feature considers how accurately professional forecasters have predicted GDP growth and inflation in Singapore, especially during rare events such as the Global Financial Crisis (GFC) and COVID-19. It also illustrates the value of forecast probability distributions in inferring forecasters’ uncertainty when making predictions, and the degree of consensus between projections from different forecasters. The authors find that one-year ahead forecast errors for GDP growth and inflation increased during the GFC and the COVID-19 pandemic. While professional forecasters did not appear to have followed the Government’s forecasts when predicting growth during the GFC, they may have exhibited ”leader-following” behaviour …

Estimation And Inference With Near Unit Roots, Peter C. B. Phillips

Research Collection School Of Economics

New methods are developed for identifying, estimating, and performing inference with nonstationary time series that have autoregressive roots near unity. The approach subsumes unit-root (UR), local unit-root (LUR), mildly integrated (MI), and mildly explosive (ME) specifications in the new model formulation. It is shown how a new parameterization involving a localizing rate sequence that characterizes departures from unity can be consistently estimated in all cases. Simple pivotal limit distributions that enable valid inference about the form and degree of nonstationarity apply for MI and ME specifications and new limit theory holds in UR and LUR cases. Normalizing and variance stabilizing …

Informational Content Of Factor Structures In Simultaneous Discrete Response Models, Shakeeb Khan, Arnaud Maurel, Yichong Zhang

Research Collection School Of Economics

We study the informational content of factor structures in discrete triangular systems. Factor structures have been employed in a variety of settings in cross sectional and panel data models, and in this paper we attempt to formally quantify their informational content in a bivariate system often employed in the treatment effects literature. Our main findings are that under the factor structures often imposed in the literature, point identification of parameters of interest, such as both the treatment effect and the factor load, is attainable under weaker assumptions than usually required in these systems. For example, we show is that an …