Digital Commons Network^™

On Discovering Motifs And Frequent Patterns In Spatial Trajectories With Discrete Fréchet Distance, Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, Kai Wang

Research Collection School Of Computing and Information Systems

The discrete Fréchet distance (DFD) captures perceptual and geographical similarity between two trajectories. It has been successfully adopted in a multitude of applications, such as signature and handwriting recognition, computer graphics, as well as geographic applications. Spatial applications, e.g., sports analysis, traffic analysis, etc. require discovering similar subtrajectories within a single trajectory or across multiple trajectories. In this paper, we adopt DFD as the similarity measure, and study two representative trajectory analysis problems, namely, motif discovery and frequent pattern discovery. Due to the time complexity of DFD, these tasks are computationally challenging. We address that challenge with a suite of …

Towards An Instant Structure-Property Prediction Quality Control Tool For Additive Manufactured Steel Using A Crystal Plasticity Trained Deep Learning Surrogate, Yuhui Tu, Zhongzhou Liu, Luiz Carneiro, Caitriona M. Ryan, Andrew C. Parnell, Sean B. Leen

Research Collection School Of Computing and Information Systems

The ability to conduct in-situ real-time process-structure-property checks has the potential to overcome process and material uncertainties, which are key obstacles to improved uptake of metal powder bed fusion in industry. Efforts are underway for live process monitoring such as thermal and image-based data gathering for every layer printed. Current crystal plasticity finite element (CPFE) modelling is capable of predicting the associated strength based on a microstructural image and material data but is computationally expensive. This work utilizes a large database of input–output samples from CPFE modelling to develop a trained deep neural network (DNN) model which instantly estimates the …

Learning From Web Recipe-Image Pairs For Food Recognition: Problem, Baselines And Performance, Bin Zhu, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Cross-modal recipe retrieval has recently been explored for food recognition and understanding. Text-rich recipe provides not only visual content information (e.g., ingredients, dish presentation) but also procedure of food preparation (cutting and cooking styles). The paired data is leveraged to train deep models to retrieve recipes for food images. Most recipes on the Web include sample pictures as the references. The paired multimedia data is not noise-free, due to errors such as pairing of images containing partially prepared dishes with recipes. The content of recipes and food images are not always consistent due to free-style writing and preparation of food …

Secure Cloud Data Deduplication With Efficient Re-Encryption, Haoran Yuan, Xiaofeng Chen, Jin Li, Tao Jiang, Jianfeng Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Data deduplication technique has been widely adopted by commercial cloud storage providers, which is both important and necessary in coping with the explosive growth of data. To further protect the security of users' sensitive data in the outsourced storage mode, many secure data deduplication schemes have been designed and applied in various scenarios. Among these schemes, secure and efficient re-encryption for encrypted data deduplication attracted the attention of many scholars, and many solutions have been designed to support dynamic ownership management. In this paper, we focus on the re-encryption deduplication storage system and show that the recently designed lightweight rekeying-aware …

A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is experiencing explosive growth and has gained extensive attention from academia and industry in recent years. However, most of the existing IoT infrastructures are centralized, which may cause the issues of unscalability and single-point-of-failure. Consequently, decentralized IoT has been proposed by taking advantage of the emerging technology called blockchain. Voting systems are widely adopted in IoT, for example a leader election in wireless sensor networks. Self-tallying voting systems are alternatives to unsuitable, traditional centralized voting systems in decentralized IoT. Unfortunately, self-tallying voting systems inherently suffer from fairness issues, such as adaptive and abortive issues caused …

A Research On The Innovative Performance Of Clustering Enterprises In Industrial Parks: Evidence From Shenzhen, China, Jiangong Bai

Dissertations and Theses Collection (Open Access)

How about the innovation performance of enterprises clustered in the industrial parks? This is the core question of this study. Based on the thinking and evolution of the question, this study will focus on the impact of industrial agglomeration on enterprise innovation performance with enterprise relations and informal institution as intermediate variables.

In this study, Shenzhen, as a city of innovation, is selected as the research area where sample parks and enterprises can be investigated to obtain data. This study constructs and measures the strength of informal institution and enterprise innovation performance through grounded theory and fuzzy matter-element method, evaluates …

Deep Learning For Video-Grounded Dialogue Systems, Hung Le

Dissertations and Theses Collection (Open Access)

In recent years, we have witnessed significant progress in building systems with artificial intelligence. However, despite advancements in machine learning and deep learning, we are still far from achieving autonomous agents that can perceive multi-dimensional information from the surrounding world and converse with humans in natural language. Towards this goal, this thesis is dedicated to building intelligent systems in the task of video-grounded dialogues. Specifically, in a video-grounded dialogue, a system is required to hold a multi-turn conversation with humans about the content of a video. Given an input video, a dialogue history, and a question about the video, the …

What Drives Companies To Do Good? A “Universal” Ordering Of Corporate Social Responsibility Motivation, Alwyn Lim, Shawn Pope

Research Collection School of Social Sciences

The classic question of why companies do corporate social responsibility (CSR) is central to much theoretical, regression-based, and experimental research. Guiding research into this question is a tripartite schema of normative, instrumental, and political CSR motivations that has become increasingly established in the CSR literature. This paper challenges the schema’s status as a typology of equally plausible alternatives through an integration and analysis of a worldwide literature of 120 existing academic surveys on CSR motivation. Rather, the paper reformulates the schema into a surveyed ordering of CSR motivations that might be called “universal” in having remarkable stability across time periods, …

Subjective Social Class And Life Satisfaction: Role Of Class Consistency And Identity Uncertainty, Bek Wuay Tang, Jacinth Jia Xin Tan

Research Collection School of Social Sciences

Drawing on a recent perspective that inconsistent class identities can negatively impact psychological outcomes, the current research explored if the relative benefit of higher subjective social class for life satisfaction would differ depending on whether it is consistent with one’s objective social class. In Study 1, across two independent samples from Singapore (n = 1,045) and the United States (n = 492), higher subjective social class predicted higher life satisfaction more strongly among those high in objective social class, but less strongly among those low in objective social class. In Study 2, these patterns were replicated in another large U.S. …

Russian Logics And The Culture Of Impossible: Part Ii: Reinterpreting Algorithmic Rationality, Ksenia Tatarchenko, Anya Yermakova, Liesbeth De Mol

Research Collection School of Social Sciences

This article reinterprets algorithmic rationality by looking at the interaction between mathematical logic, mechanized reasoning, and, later, computing in the Russian Imperial and Soviet contexts to offer a history of the algorithm as a mathematical object bridging the inner and outer worlds, a humanistic vision that we, following logician Vladimir Uspensky, call the “culture of the impossible.” We unfold the deep roots of this vision as embodied in scientific intelligentsia. In Part I, we examine continuities between the turn-of-the-twentieth-century discussions of poznaniye—an epistemic orientation towards the process of knowledge acquisition—and the postwar rise of the Soviet school of mathematical logic. …

Reply To Komatsu Et Al.: From Local Social Mindfulness To Global Sustainability Efforts?, N. J. Van Doesum, R. O. Murphy, M. Gallucci, E. Aharonov-Majar, U. Athenstaedt, W. T. Au, L. Bai, R. Böhm, I. Bovina, N. R. Buchan, X. P. Chen, K. B. Dumont, J. B. Engelmann, K. Eriksson, Li, Norman P., S. Fiedler, J. Friesen, S. Gächter, C. Garcia, R. González

Research Collection School of Social Sciences

Komatsu et al. (1) argue that Van Doesum et al. (2) may have overlooked the role of GDP in reporting a positive association between social mindfulness (SoMi) and the Environmental Performance Index (EPI) at country level. Although the relationship between EPI and SoMi is relatively weaker for countries with higher GDP, that does not imply that the overall observed relationship is a statistical artifact. Rather, it implies that GDP may be a moderator of the relationship between EPI and SoMi. The observed correlation is a valid result on average across countries, and the actual effect size would, at least to …

The Catholic Church Abuse Scandal In Ireland: Two Steps Forward, One Step Back By Pope Francis?, Augustine Pang, Eada Hogan, Igor Andrasevic

Research Collection Lee Kong Chian School Of Business

Purpose: Ireland is viewed as the shining base for Catholicism. That image is shattered as survivors revealed the abuse in the Magdalene Laundries and Mother and Baby Homes, and sexual abuse by priests. This study aims to examine image repair efforts by the Pope during his August 2018 visit. Design/methodology/approach: Examined against the Letter of His Holiness released days earlier, this study evaluates all the Pope's speeches during his visit to Ireland using the image repair theory (Benoit and Pang, 2008) as its theoretical lens. Findings: Pope Francis used the evasion of responsibility strategy to address the Magdalene Laundries and …

How Does Firm Scope Depend On Customer Switching Costs? Evidence From Mobile Telecommunications Markets, Niloofar Abolfathi, Simone Santamaria, Charles Williams

Research Collection Lee Kong Chian School Of Business

This paper examines the relative advantages of single-product and multiproduct firms following changes in customer switching costs. Whereas a single-product firm can closely tailor offerings to customers' needs, a multiproduct firm can create value for customers in the form of flexibility, allowing them to change between product varieties as preferences evolve without needing to switch providers. We argue that this value-creation mechanism is more effective when customers face high switching costs and explore this prediction in the mobile telecommunications sector, using an exogenous policy change (mobile number portability) that suddenly decreases customer switching costs. Our results reveal that when customer …

The Role Of Emotions As Mechanisms Of Mid-Test Warning Messages During Personality Testing: A Field Experiment, Hairong Li, Jinyan Fan, Guoxiang Zhao, Minghui Wang, Lu Zheng, Hui Meng, Qingxiong Weng, Yanping Liu, Filip Lievens

Research Collection Lee Kong Chian School Of Business

This study focuses on the role of emotions in personnel selection and faking research. In particular, we posit that emotions are likely to be activated when applicants receive warning messages from organizations. Drawing on Nabi (Nabi, Communication Theory, 9, 1999, 292) cognitive-functional model of discrete negative emotions, we propose and empirically test the effects of three discrete negative emotions (guilt, fear, and anger) triggered by a warning message during a personality test on personality score accuracy and perceived test fairness. Participants in this within-subjects field experiment were 1,447 applicants for graduate school at a large public university in China. They …

The Associations Between Poor Antibiotic And Antimicrobial Resistance Knowledge And Inappropriate Antibiotic Use In The General Population Are Modified By Age, Huiling Guo, Zoe Jane-Lara Hildon, David Chien Boon Lye, Paulin Tay Straughan, Angela Chow

Research Collection School of Social Sciences

Objectives: Understanding factors influencing inappropriate antibiotic use can guide the design of interventions to improve antibiotic practices and reduce antimicrobial resistance (AMR). Methods: A nationally representative cross-sectional survey (N = 2004) was conducted between November 2020 and January 2021. Knowledge of antibiotic use and AMR using the World Health Organization’s Multi-Country AMR Survey questionnaire, and antibiotic practices were examined. Multivariable logistic regression was performed to identify factors associated with inappropriate antibiotic use and examine effect measure modifications. Results: After adjusting for potential confounding, poor knowledge of antibiotic use was associated with a 3x increased odds of inappropriate antibiotic use in …

The Derring Effect: Deliberate Errors Enhance Learning, Sarah Shi Hui Wong, Stephen Wee Hun Lim

Research Collection School of Social Sciences

How can we strategically and systematically learn from our errors? Over their long history, errors have traditionally been prevented entirely or, at best, permitted to occur spontaneously. Across three experiments, we tested and found evidence for a counterintuitive phenomenon that we termed the derring effect—deliberately committing errors even when one already knows the correct answers produces superior learning than avoiding them, particularly when one’s errors are corrected. Learners engaged in an educationally relevant task of learning scientific term-definition concepts via open-book study by deliberately generating conceptually incorrect definitions with or without correction, or copying and underlining them (Experiment 1). On …

China Rising, 2000-2010, William A. Callahan

Research Collection School of Social Sciences

No abstract provided.

The Ashrae Great Energy Predictor Iii Competition: Overview And Results, Clayton Miller, Pandarasamy Arjunan, Anjukan Kathirgamanathan, Chun Fu, Jonathan Roth, Young June Park, Chris Balbach, Krishnan Gowri, Zoltan Nagy, D. Anthony Fontanini, Jeff Haberl

Research Collection College of Integrative Studies

In late 2019, ASHRAE hosted the Great Energy Predictor III (GEPIII) machine learning competition on the Kaggle platform. This launch marked the third energy prediction competition from ASHRAE and the first since the mid-1990s. In this updated version, the competitors were provided with over 20 million points of training data from 2,380 energy meters collected for 1,448 buildings from 16 sources. This competition’s overall objective was to find the most accurate modeling solutions for the prediction of over 41 million private and public test data points. The competition had 4,370 participants, split across 3,614 teams from 94 countries who submitted …

Microfoundations Of Dynamic Managerial Capabilities: A Personality Perspective, Alan Jiun Haw Tea

Dissertations and Theses Collection (Open Access)

Research in dynamic capabilities (Teece 2007) looks at how organizations derive and potentially sustain competitive advantage by dynamically making sense of opportunities, marshalling and manipulating assets and resources in response to these opportunities (Eisenhardt & Martin, 2000; Teece, 2007). The study of dynamic managerial capabilities is concerned with the microfoundations – attendant attributes as it were – that underpin managers’ ability to effectively participate in the dynamic capabilities of sensing, seizing and reconfiguring (Helfat & Martin, 2015b; Helfat & Peteraf, 2015). Apart from the predominant cognitive account of microfoundations, there remains an under-theorized and underresearched gap in the field of …

The Industry Expertise Of Sell-Side Equity Analysts, Matthew Louis Dearth

Dissertations and Theses Collection (Open Access)

Institutional investors, the most important consumer of analyst research, consistently rank industry knowledge as the most important attribute of analysts. Despite this, little is known about how investors measure industry knowledge since analyst output which can be evaluated objectively is usually associated with firm-level outcomes such as earnings forecasts or price targets. Comprehensive data are recently available for analyst forecasts of key performance indicators (“KPIs”), firm-performance metrics specific to a particular industry. Whereas reactions to earnings forecasts and other firm-level outputs only inform us about analyst skill in firm-level predictions, stock-price reactions to forecast revisions of industryspecific KPIs can proxy …

Does A District Mandate Matter For The Behavior Of Politicians? An Analysis Of Roll-Call Votes And Parliamentary Speeches, Andreas Born, Aljoscha Janssen

Research Collection School Of Economics

In most democracies, members of parliament (MPs) are elected either through a party list or by a district. We use a discontinuity in the German electoral system to investigate the causal effect of a district election on an MP’s conformity with the party line. A district election does not affect roll-call voting behavior causally, possibly due to overall high adherence to party-line voting. Analyzing the parliamentary speeches of each MP allows us to overcome the high party-line discipline with regard to parliamentary voting. Using textual analysis and machine learning techniques, we create two measures of closeness of an MP’s speeches …

Are Simple Mechanisms Optimal When Agents Are Unsophisticated?, Jiangtao Li, Piotr Dworczak

Research Collection School Of Economics

We study the design of mechanisms involving agents that have limited strategic sophistication. We define a mechanism to be simple if—given the assumed level of strategic sophistication—agents can determine their optimal strategy. We examine whether it is optimal for the mechanism designer who faces strategically unsophisticated agents to offer a simple mechanism. We show that when the designer uses a mechanism that is not simple, while she loses the ability to predict play, she may nevertheless be better off no matter how agents resolve their strategic confusion

Uniform Nonparametric Inference For Spatially Dependent Panel Data: The Xtnpsreg Command, Jia Li, Zhipeng Liao, Wenyu Zhou

Research Collection School Of Economics

In this article, we introduce a command, xtnpsreg, that implements a uniform nonparametric inference procedure for possibly unbalanced panel datasets with general forms of spatio-temporal dependence. We demonstrate how to apply this command in several use cases, including (i) the nonparametric estimation of conditional mean function and its marginal response; (ii) the construction of uniform confidence bands for these nonparametric functional parameters; (iii) specification tests for parametric model restrictions; and (iv) the estimation and uniform inference for functional coefficients in semi-nonparametric models.

Predictive Models In Software Engineering: Challenges And Opportunities, Yanming Yang, Xin Xia, David Lo, Tingting Bi, John C. Grundy, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-performed studies in various research domains, including software requirements, software design and development, testing and debugging, and software maintenance. This article is a first attempt to systematically organize knowledge in this area by surveying a body of 421 papers on predictive models published between 2009 and 2020. We describe the key models and approaches used, classify the different models, summarize the range of key application …

Github Discussions: An Exploratory Study Of Early Adoption, Hideaki Hata, Nicole Novielli, Sebastian Baltes, Raula Kula, Christoph Treude

Research Collection School Of Computing and Information Systems

Discussions is a new feature of GitHub for asking questions or discussing topics outside of specific Issues or Pull Requests. Before being available to all projects in December 2020, it had been tested on selected open source software projects. To understand how developers use this novel feature, how they perceive it, and how it impacts the development processes, we conducted a mixed-methods study based on early adopters of GitHub discussions from January until July 2020. We found that: (1) errors, unexpected behavior, and code reviews are prevalent discussion categories; (2) there is a positive relationship between project member involvement and …

Contextualized Knowledge-Aware Attentive Neural Network: Enhancing Answer Selection With Knowledge, Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Wai Lam, Ying Shen

Research Collection School Of Computing and Information Systems

Answer selection, which is involved in many natural language processing applications, such as dialog systems and question answering (QA), is an important yet challenging task in practice, since conventional methods typically suffer from the issues of ignoring diverse real-world background knowledge. In this article, we extensively investigate approaches to enhancing the answer selection model with external knowledge from knowledge graph (KG). First, we present a context-knowledge interaction learning framework, Knowledge-aware Neural Network, which learns the QA sentence representations by considering a tight interaction with the external knowledge from KG and the textual information. Then, we develop two kinds of knowledge-aware …

Contracts Formed By Software: An Approach From The Law Of Mistake, Vincent Ooi

Research Collection Yong Pung How School Of Law

A ‘Contracting Problem’ arises when software is used to autonomously enter into contracts without human input. Questions arise as to how and whether there can be an expression of an objective intention to be legally bound. This article considers three leading solutions to the Contracting Problem. The ‘Mere Tools Theory’, which views software as ‘mere tools’ of communication, is too harsh as it binds users to any software malfunction. The Agency Approach, which treats software as Electronic Agents, capable of contracting on behalf of their users, is untenable as it ascribes unrealistic characteristics to software. The article submits that the …

Improperly Obtained Evidence In Criminal Proceedings: An Updated Framework, Siyuan Chen, Zhi Jia Koh, Jian Wei Joel Soon

Research Collection Yong Pung How School Of Law

The 2012 amendments to the Evidence Act “significantly broadened the admissibility criteria for expert evidence”; at the same time, the judicial discretion to deny admissibility of relevant expert opinion evidence was also introduced. This article considers the key developments pre- and post-amendments, and in doing so provides an updated framework for prosecutors and defence counsel alike to admit and challenge expert opinion evidence in criminal proceedings. Since it complements earlier articles in this series on similar fact and hearsay evidence, readers are assumed to be broadly familiar with the features of the Evidence Act, such as its admissibility paradigm, the …

The 2022 Global Philanthropy Environment Index Singapore, Tan K. B. Eugene

Research Collection Yong Pung How School Of Law

The three indicator questions in this section pertain to the laws and regulations governing philanthropic organizations (POs). The scoring questions for this category cover three aspects of regulations: (A) formation and registration; (B) operations; and (C) dissolution.

Re-Formulating The Test For Ascertaining The Proper Law Of An Arbitration Agreement: A Comparative Common Law Analysis, Darius Chan, Jim Yang Teo

Research Collection Yong Pung How School Of Law

Following two recent decisions from the apex courts in England and Singapore on the appropriate methodology to ascertain the proper law of an arbitration agreement, the positions in these two leading arbitration destinations have now converged in some respects. But other issues of conceptual and practical significance have not been fully addressed, including the extent to which the true nature of the inquiry into whether the parties had made a choice of law is in substance an exercise in contractual interpretation, the applicability of a validation principle, and the extent to which the choice of a neutral seat may affect …