Physical Sciences and Mathematics Commons^™

Designing Learning Activities For Experiential Learning In A Design Thinking Course, Benjamin Gan, Eng Lieh Ouh

Research Collection School Of Computing and Information Systems

One experiential learning design challenge is the duration of learning activities. These learning activities take up time and effort for teachers to design and student to perform. Another design challenge is the minimum instructional guidance of these learning activities which potentially impact the learning effectiveness of novice students. In this paper, we describe our findings of applying experiential learning method in a design thinking course with a list of learning activities performed iteratively. Each of the learning activity varies in their duration required and level of instructional guidance. Our survey seeks to find out which of the learning activities are …

Optimal Management Of Virtual Infrastructures Under Flexible Cloud Service Agreements, Zhiling Guo, Jin Li, Ram Ramesh

Research Collection School Of Computing and Information Systems

A cloud service agreement entails the provisioning of a required set of virtual infrastructure resources at a specified level of availability to a client. The agreement also lays out the price charged to the client and a penalty to the provider when the assured availability is not met. The availability assurance involves backup resource provisioning, and the provider needs to allocate backups cost-effectively by balancing the resource-provisioning costs with the potential penalty costs. We develop stochastic dynamic optimization models of the backup resource-provisioning problem, leading to cost-effective resource-management policies in different practical settings. We present two sets of dynamic provisioning …

Compositional Verification Of Heap-Manipulating Programs Through Property-Guided Learning, Long H. Pham, Jun Sun, Quang Loc Le

Research Collection School Of Computing and Information Systems

Analyzing and verifying heap-manipulating programs automatically is challenging. A key for fighting the complexity is to develop compositional methods. For instance, many existing verifiers for heap-manipulating programs require user-provided specification for each function in the program in order to decompose the verification problem. The requirement, however, often hinders the users from applying such tools. To overcome the issue, we propose to automatically learn heap-related program invariants in a property-guided way for each function call. The invariants are learned based on the memory graphs observed during test execution and improved through memory graph mutation. We implemented a prototype of our approach …

An Ai Approach To Measuring Financial Risk, Lining Yu, Wolfgang Karl Hardle, Lukas Borke, Thijs Benschop

Sim Kee Boon Institute for Financial Economics

AI artificial intelligence brings about new quantitative techniques to assess the state of an economy. Here, we describe a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (λ" role="presentation" style="box-sizing: border-box; display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 18px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">λλ) of a linear quantile lasso regression. The FRM is calculated by taking the average …

When Keystroke Meets Password: Attacks And Defenses, Ximing Liu

Dissertations and Theses Collection (Open Access)

Password is a prevalent means used for user authentication in pervasive computing environments since it is simple to be deployed and convenient to use. However, the use of password has intrinsic problems due to the involvement of keystroke. Keystroke behaviors may emit various side-channel information, including timing, acoustic, and visual information, which can be easily collected by an adversary and leveraged for the keystroke inference. On the other hand, those keystroke-related information can also be used to protect a user's credentials via two-factor authentication and biometrics authentication schemes. This dissertation focuses on investigating the PIN inference due to the side-channel …

Multimodal Mobile Sensing Systems For Physiological And Psychological Assessment, Nguyen Phan Sinh Huynh

Dissertations and Theses Collection (Open Access)

Sensing systems for monitoring physiological and psychological states have been studied extensively in both academic and industry research for different applications across various domains. However, most of the studies have been done in the lab environment with controlled and complicated sensor setup, which is only suitable for serious healthcare applications in which the obtrusiveness and immobility can be compromised in a trade-off for accurate clinical screening or diagnosing. The recent substantial development of mobile devices with embedded miniaturized sensors are now allowing new opportunities to adapt and develop such sensing systems in the mobile context. The ability to sense physiological …

Optimal Control For Transboundary Pollution Under Ecological Compensation: A Stochastic Differential Game Approach, Ke Jiang, Ryan Knowles Merrill, Daming You, Pan Pan

Research Collection Lee Kong Chian School Of Business

To account for previously ignored, yet widely observed uncertainty in nature's capability to replenish the natural environment in ways that should inform ideal design of ecological compensation (EC) regimes, this study constructs a stochastic differential game (SDG) model to analyze transboundary pollution control options between a compensating and compensated region. Equilibrium strategies in the stochastic, two player game inform optimal control theory and reveal a welfare distribution mechanism to form the basis of an improved cooperative game contract. A case-based numerical example serves to verify the theoretical results and supports three key insights. First, accounting for various random disturbance factors, …

Selective Discrete Particle Swarm Optimization For The Team Orienteering Problem With Time Windows And Partial Scores, Vincent F. Yu, Perwira A. A. N. Redi, Parida Jewpanya, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This paper introduces the Team Orienteering Problem with Time Windows and Partial Scores (TOPTW-PS),which is an extension of the Team Orienteering Problem with Time Windows (TOPTW). In the context of theTOPTW-PS, each node is associated with a set of scores with respect to a set of attributes. The objective ofTOPTW-PS is to find a set of routes that maximizes the total score collected from a subset of attributes whenvisiting the nodes subject to the time budget and the time window at each visited node. We develop a mathematical model and propose a discrete version of the Particle Swarm Optimization (PSO), …

Study Group Travel Behaviour Patterns From Large-Scale Smart Card Data, Xiancai Tian, Baihua Zheng

Research Collection School Of Computing and Information Systems

In this paper, we aim at studying the group travel behaviour (GTB) patterns from large-scale auto fare collection (AFC) data. GTB is defined as two or more commuters intentionally and regularly traveling together from an origin to a destination. We propose a method to identify GTB accurately and efficiently and apply our method to the Singapore AFC dataset to reveal the GTB patterns of Singapore commuters. The case study proves that our method is able to identify GTB patterns more accurately and efficiently than the state-of-the-art.

An Empirical Study Of Sms One-Time Password Authentication In Android Apps, Siqi Ma, Runhan Feng, Juanru Li, Yang Liu, Surya Nepal, Elisa Bertino, Robert H. Deng, Zhuo Ma, Sanjay Jha

Research Collection School Of Computing and Information Systems

A great quantity of user passwords nowadays has been leaked through security breaches of user accounts. To enhance the security of the Password Authentication Protocol (PAP) in such circumstance, Android app developers often implement a complementary One-Time Password (OTP) authentication by utilizing the short message service (SMS). Unfortunately, SMS is not specially designed as a secure service and thus an SMS One-Time Password is vulnerable to many attacks. To check whether a wide variety of currently used SMS OTP authentication protocols in Android apps are properly implemented, this paper presents an empirical study against them. We first derive a set …

The Dynamic Impacts Of Online Healthcare Community On Physician Altruism: A Hidden Markov Model, Kai Luo, Qiu-Hong Wang, Hock Hai Teo

Research Collection School Of Computing and Information Systems

Physician altruism is not only a key foundation of modern medical professionalism, but also a critical component in the theoretical health economics study. There is considerable interest in understanding the impacts of contemporary healthcare technology on physician altruism. In this paper, we investigate the dynamic influence of multiple incentive mechanisms developed by an online healthcare community (OHC) on physician altruism. We model physician altruism as the degree of tendency to benefit the patients at the cost of oneself and focus on the incentive mechanisms that give physicians social and economic returns. The dynamics of physician altruism is characterized via a …

The Information Disclosure Trilemma: Privacy, Attribution And Dependency, Ping Fan Ke

Research Collection School Of Computing and Information Systems

Information disclosure has been an important mechanism to increase transparency and welfare in various contexts, from rating a restaurant to whistleblowing the wrongdoing of government agencies. Yet, the author often needs to be sacrificed during information disclosure process – an anonymous disclosure will forgo the reputation and compensation whereas an identifiable disclosure will face the threat of retaliation. On the other hand, the adoption of privacy-enhancing technologies (PETs) lessens the tradeoff between privacy and attribution while introducing dependency and potential threats. This study will develop the desirable design principles and possible threats of an information disclosure system, and discuss how …

Identifying Regional Trends In Avatar Customization, Peter Mawhorter, Sercan Sengun, Haewoon Kwak, D. Fox Harrell

Research Collection School Of Computing and Information Systems

Since virtual identities such as social media profiles and avatars have become a common venue for self-expression, it has become important to consider the ways in which existing systems embed the values of their designers. In order to design virtual identity systems that reflect the needs and preferences of diverse users, understanding how the virtual identity construction differs between groups is important. This paper presents a new methodology that leverages deep learning and differential clustering for comparative analysis of profile images, with a case study of almost 100 000 avatars from a large online community using a popular avatar creation …

An Iot-Driven Smart Cafe Solution For Human Traffic Management, Maruthi Prithivirajan, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In this study, we present an IoT-driven solution for human traffic management in a corporate cafe. Using IoT sensors, our system monitors human traffic in a physical cafe located at a large international corporation located in Singapore. The backend system analyzes the streaming data from the sensors and provides insights useful to the cafe visitors as well as the cafe manager.

Harmony Search Algorithm For Time-Dependent Vehicle Routing Problem With Time Windows, Yun-Chia Liang, Vanny Minanda, Aldy Gunawan, Angela Hsiang-Ling Chen

Research Collection School Of Computing and Information Systems

Vehicle Routing Problem (VRP) is a combinatorial problem where a certain set of nodes must be visited within a certain amount of time as well as the vehicle’s capacity. There are numerous variants of VRP such as VRP with time windows, where each node has opening and closing time, therefore, the visiting time must be during that interval. Another variant takes time-dependent constraint into account. This variant fits real-world scenarios, where at different period of time, the speed on the road varies depending on the traffic congestion. In this study, three objectives – total traveling time, total traveling distance, and …

A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja

Research Collection School Of Computing and Information Systems

A green mixed fleet vehicle routing with realistic energy consumption and partial recharges problem (GMFVRP-REC-PR) is addressed in this paper. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. The realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicle. Partial recharging policy is included into the problem to represent the real life scenario. The objective of this problem is to minimize the total travelled distance and the total emission produced by internal …

Appmod: Helping Older Adults Manage Mobile Security With Online Social Help, Zhiyuan Wan, Lingfeng Bao, Debin Gao, Eran Toch, Xin Xia, Tamir Mendel, David Lo

Research Collection School Of Computing and Information Systems

The rapid adoption of Smartphone devices has caused increasing security and privacy risks and breaches. Catching up with ever-evolving contemporary smartphone technology challenges leads older adults (aged 50+) to reduce or to abandon their use of mobile technology. To tackle this problem, we present AppMoD, a community-based approach that allows delegation of security and privacy decisions a trusted social connection, such as a family member or a close friend. The trusted social connection can assist in the appropriate decision or make it on behalf of the user. We implement the approach as an Android app and describe the results of …

Smu Teaching Bank: Case Study Of A Multiyear Development Project Utilizing Student Resources, Alan Megargel, Terence P. C. Fan, Venky Shankararaman

Research Collection School Of Computing and Information Systems

A domain refers to a business sector such as banking, healthcare, insurance, manufacturing etc. For an IS student, it is imperative that the domain knowledge includes a comprehension and understanding of business processes, technology and data related to the chosen domain. For example, when learning the retail banking domain, an IS student must have an understanding of the transactions concerned with retail banking such as fund transfers and loan repayments. The student must also gain a strong foothold in transaction fulfilment processes, the various application services that are used, the data that is transferred, etc. Teaching domain knowledge is very …

Treecaps: Tree-Structured Capsule Networks For Program Source Code Processing, Vinoj Jayasundara, Duy Quoc Nghi Bui, Lingxiao Jiang, David Lo

Research Collection School Of Computing and Information Systems

Program comprehension is a fundamental task in software development and maintenance processes. Software developers often need to understand a large amount of existing code before they can develop new features or fix bugs in existing programs. Being able to process programming language code automatically and provide summaries of code functionality accurately can significantly help developers to reduce time spent in code navigation and understanding, and thus increase productivity. Different from natural language articles, source code in programming languages often follows rigid syntactical structures and there can exist dependencies among code elements that are located far away from each other through …

Online Content Consumption: Social Endorsements, Observational Learning And Word-Of-Mouth, Qian Tang, Tingting Song, Liangfei Qiu, Ashish Agarwal

Research Collection School Of Computing and Information Systems

The consumption of online content can occur through observational learning (OL) whereby consumers follow previous consumers’ choices or social endorsement (SE) wherein consumers receive content sharing from their social ties. As users consume content, they also generate post-consumption word-of-mouth (WOM) signals. OL, SE and WOM together shape the diffusion of the content. This study examines the drivers of SE and the effect of SE on content consumption and post-consumption WOM. In particular, we compare SE with OL. Using a random sample of 8,945 new videos posted on YouTube, we collected a multi-platform dataset consisting of data on video consumption and …

Guest Editorial: Special Issue On Software Engineering For Mobile Applications, Sebastiano Panichella, Fabio Palomba, David Lo, Meiyappan Nagappan

Research Collection School Of Computing and Information Systems

As Andreessen stated “software is eating the world” (Andreessen 2011). Most of todays industries, from engineering, manufacturing, logistics to health, are run on enterprise software applications and can efficiently automate the analysis and manipulation of several, heterogeneous types of data. One of the most prominent examples of such software diffusion is represented by the widespread adoption of mobile applications. Indeed, during the recent years, the Global App Economy experienced unprecedented growth, driven by the increasing usage of apps and by the greater adoption of mobile devices (e.g., smartphone) around the globe. This mobile application market, which is expected in few …

Salience-Aware Adaptive Resonance Theory For Large-Scale Sparse Data Clustering, Lei Meng, Ah-Hwee Tan, Chunyan Miao

Research Collection School Of Computing and Information Systems

Sparse data is known to pose challenges to cluster analysis, as the similarity between data tends to be ill-posed in the high-dimensional Hilbert space. Solutions in the literature typically extend either k-means or spectral clustering with additional steps on representation learning and/or feature weighting. However, adding these usually introduces new parameters and increases computational cost, thus inevitably lowering the robustness of these algorithms when handling massive ill-represented data. To alleviate these issues, this paper presents a class of self-organizing neural networks, called the salience-aware adaptive resonance theory (SA-ART) model. SA-ART extends Fuzzy ART with measures for cluster-wise salient feature modeling. …

Influence, Information And Team Outcomes In Large Scale Software Development, Subhajit Datta

Research Collection School Of Computing and Information Systems

It is widely perceived that the egalitarian ecosystems of large scale open source software development foster effective team outcomes. In this study, we question this conventional wisdom by examining whether and how the centralization of information and influence in a software development team relate to the quality of the team's work products. Analyzing data from more than a hundred real world projects that include development activities over close to a decade, involving 2000+ developers, who collectively resolve more than two hundred thousand defects through discussions covering more than six hundred thousand comments, we arrive at statistically significant evidence indicating that …

Punctuation Prediction For Vietnamese Texts Using Conditional Random Fields, Hong Quang Pham, Binh T. Nguyen, Nguyen Viet Cuong

Research Collection School Of Computing and Information Systems

We investigate the punctuation prediction for the Vietnamese language. This problem is crucial as it can be used to add suitable punctuation marks to machine-transcribed speeches, which usually do not have such information. Similar to previous works for English and Chinese languages, we formulate this task as a sequence labeling problem. After that, we apply the conditional random field model for solving the problem and propose a set of appropriate features that are useful for prediction. Moreover, we build two corpora from Vietnamese online news and movie subtitles and perform extensive experiments on these data. Finally, we ask four volunteers …

Learning To Self-Train For Semi-Supervised Few-Shot Classification, Xinzhe Li, Qianru Sun, Yaoyao Liu, Shibao Zheng, Qin Zhou, Tat-Seng Chua, Bernt Schiele

Research Collection School Of Computing and Information Systems

Few-shot classification (FSC) is challenging due to the scarcity of labeled training data (e.g. only one labeled data point per class). Meta-learning has shown to achieve promising results by learning to initialize a classification model for FSC. In this paper we propose a novel semi-supervised meta-learning method called learning to self-train (LST) that leverages unlabeled data and specifically meta-learns how to cherry-pick and label such unsupervised data to further improve performance. To this end, we train the LST model through a large number of semi-supervised few-shot tasks. On each task, we train a few-shot model to predict pseudo labels for …

Clustering Models For Topic Analysis In Graduate Discussion Forums, Mallika Gokarn Nitin, Swapna Gottipati, Venky Shankararaman

Research Collection School Of Computing and Information Systems

Discussion forums provide the base content for creating a knowledge repository. It contains discussion threads related to key course topics that are debated by the students. In order to better understand the student learning experience, the instructor needs to analyse these discussion threads. This paper proposes the use of clustering models and interactive visualizations to conduct a qualitative analysis of graduate discussion forums. Our goal is to identify the sub-topics and topic evolutions in the discussion forums by applying text mining techniques. Our approach generates insights into the topic analysis in the forums and discovers the students’ cognitive understanding within …

Gesture-Based Profiling Of Commonplace Lifestyle And Physical Activity Behaviors, Meeralakshmi Radhakrishnan

Dissertations and Theses Collection (Open Access)

The widespread availability of sensors on personal devices (e.g., smartphones, smartwatches) and other cheap, commoditized IoT devices in the environment has opened up the opportunity for developing applications that capture and enhance various lifestyle-driven daily activities of individuals. Moreover, there is a growing trend of leveraging ubiquitous computing technologies to improve physical health and wellbeing. Several of the lifestyle monitoring applications rely primarily on the capability of recognizing contextually relevant human movements, actions and gestures. As such, gesture recognition techniques, and gesture-based analytics have emerged as a fundamental component for realizing personalized lifestyle applications.

This thesis explores how such wealth …

Enhanced Gesture Sensing Using Battery-Less Wearable Motion Trackers, Huy Vu Tran

Dissertations and Theses Collection (Open Access)

Wearable devices are gaining in popularity, but are presently used primarily for productivity-related functions (such as calling people or discreetly receiving notifications) or for physiological sensing. However, wearable devices are still not widely used for a wider set of sensing-based applications, even though their potential is enormous. Wearable devices can enable a variety of novel applications. For example, wrist-worn and/or finger-worn devices could be viable controllers for real-time AR/VR games and applications, and can be used for real-time gestural tracking to support rehabilitative patient therapy or training of sports personnel. There are, however, a key set of impediments towards realizing …

Happy Toilet: A Social Analytics Approach To The Study Of Public Toilet Cleanliness, Eugene W. J. Choy, Winston M. K. Ho, Xiaohang Li, Ragini Verma, Li Jin Sim, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

This study presents a social analytics approach to the study of public toilet cleanliness in Singapore. From popular social media platforms, our system automatically gathers and analyzes relevant public posts that mention about toilet cleanliness in highly frequented locations across the Singapore island - from busy shopping malls to food 'hawker' centers.

Automating Change-Level Self-Admitted Technical Debt Determination, Meng Yan, Xin Xia, Emad Shihab, David Lo, Jianwei Yin, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Self-Admitted Technical Debt (SATD) refers to technical debt that is introduced intentionally. Previous studies that identify SATD at the file-level in isolation cannot describe the TD context related to multiple files. Therefore, it is more beneficial to identify the SATD once a change is being made. We refer to this type of TD identification as “Change-level SATD Determination”, and identifying SATD at the change-level can help to manage and control TD by understanding the TD context through tracing the introducing changes. In this paper, we propose a change-level SATD Determination mode by extracting 25 features from software changes that are …